3D Surface Modeling [PhenLabs]📊 3D Surface Modeling
Version: PineScript™ v6
📌 Description
The 3D Surface Modeling indicator revolutionizes technical analysis by generating three-dimensional visualizations of multiple technical indicators across various timeframes. This advanced analytical tool processes and renders complex indicator data through a sophisticated matrix-based calculation system, creating an intuitive 3D surface representation of market dynamics.
The indicator employs array-based computations to simultaneously analyze multiple instances of selected technical indicators, mapping their behavior patterns across different temporal dimensions. This unique approach enables traders to identify complex market patterns and relationships that may be invisible in traditional 2D charts.
🚀 Points of Innovation
Matrix-Based Computation Engine: Processes up to 500 concurrent indicator calculations in real-time
Dynamic 3D Rendering System: Creates depth perception through sophisticated line arrays and color gradients
Multi-Indicator Integration: Seamlessly combines VWAP, Hurst, RSI, Stochastic, CCI, MFI, and Fractal Dimension analyses
Adaptive Scaling Algorithm: Automatically adjusts visualization parameters based on indicator type and market conditions
🔧 Core Components
Indicator Processing Module: Handles real-time calculation of multiple technical indicators using array-based mathematics
3D Visualization Engine: Converts indicator data into three-dimensional surfaces using line arrays and color mapping
Dynamic Scaling System: Implements custom normalization algorithms for different indicator types
Color Gradient Generator: Creates depth perception through programmatic color transitions
🔥 Key Features
Multi-Indicator Support: Comprehensive analysis across seven different technical indicators
Customizable Visualization: User-defined color schemes and line width parameters
Real-time Processing: Continuous calculation and rendering of 3D surfaces
Cross-Timeframe Analysis: Simultaneous visualization of indicator behavior across multiple periods
🎨 Visualization
Surface Plot: Three-dimensional representation using up to 500 lines with dynamic color gradients
Depth Indicators: Color intensity variations showing indicator value magnitude
Pattern Recognition: Visual identification of market structures across multiple timeframes
📖 Usage Guidelines
Indicator Selection
Type: VWAP, Hurst, RSI, Stochastic, CCI, MFI, Fractal Dimension
Default: VWAP
Starting Length: Minimum 5 periods
Default: 10
Step Size: Interval between calculations
Range: 1-10
Visualization Parameters
Color Scheme: Green, Red, Blue options
Line Width: 1-5 pixels
Surface Resolution: Up to 500 lines
✅ Best Use Cases
Multi-timeframe market analysis
Pattern recognition across different technical indicators
Trend strength assessment through 3D visualization
Market behavior study across multiple periods
⚠️ Limitations
High computational resource requirements
Maximum 500 line restriction
Requires substantial historical data
Complex visualization learning curve
🔬 How It Works
1. Data Processing:
Calculates selected indicator values across multiple timeframes
Stores results in multi-dimensional arrays
Applies custom scaling algorithms
2. Visualization Generation:
Creates line arrays for 3D surface representation
Applies color gradients based on value magnitude
Renders real-time updates to surface plot
3. Display Integration:
Synchronizes with chart timeframe
Updates surface plot dynamically
Maintains visual consistency across updates
🌟 Credits:
Inspired by LonesomeTheBlue (modified for multiple indicator types with scaling fixes and additional unique mappings)
💡 Note:
Optimal performance requires sufficient computing resources and historical data. Users should start with default settings and gradually adjust parameters based on their analysis requirements and system capabilities.
Tìm kiếm tập lệnh với "美股标普500"
FVG Premium [no1x]█ OVERVIEW
This indicator provides a comprehensive toolkit for identifying, visualizing, and tracking Fair Value Gaps (FVGs) across three distinct timeframes (current chart, a user-defined Medium Timeframe - MTF, and a user-defined High Timeframe - HTF). It is designed to offer traders enhanced insight into FVG dynamics through detailed state monitoring (formation, partial fill, full mitigation, midline touch), extensive visual customization for FVG representation, and a rich alert system for timely notifications on FVG-related events.
█ CONCEPTS
This indicator is built upon the core concept of Fair Value Gaps (FVGs) and their significance in price action analysis, offering a multi-layered approach to their detection and interpretation across different timeframes.
Fair Value Gaps (FVGs)
A Fair Value Gap (FVG), also known as an imbalance, represents a range in price delivery where one side of the market (buying or selling) was more aggressive, leaving an inefficiency or an "imbalance" in the price action. This concept is prominently featured within Smart Money Concepts (SMC) and Inner Circle Trader (ICT) methodologies, where such gaps are often interpreted as footprints left by "smart money" due to rapid, forceful price movements. These methodologies suggest that price may later revisit these FVG zones to rebalance a prior inefficiency or to seek liquidity before continuing its path. These gaps are typically identified by a three-bar pattern:
Bullish FVG : This is a three-candle formation where the second candle shows a strong upward move. The FVG is the space created between the high of the first candle (bottom of FVG) and the low of the third candle (top of FVG). This indicates a strong upward impulsive move.
Bearish FVG : This is a three-candle formation where the second candle shows a strong downward move. The FVG is the space created between the low of the first candle (top of FVG) and the high of the third candle (bottom of FVG). This indicates a strong downward impulsive move.
FVGs are often watched by traders as potential areas where price might return to "rebalance" or find support/resistance.
Multi-Timeframe (MTF) Analysis
The indicator extends FVG detection beyond the current chart's timeframe (Low Timeframe - LTF) to two higher user-defined timeframes: Medium Timeframe (MTF) and High Timeframe (HTF). This allows traders to:
Identify FVGs that might be significant on a broader market structure.
Observe how FVGs from different timeframes align or interact.
Gain a more comprehensive perspective on potential support and resistance zones.
FVG State and Lifecycle Management
The indicator actively tracks the lifecycle of each detected FVG:
Formation : The initial identification of an FVG.
Partial Fill (Entry) : When price enters but does not completely pass through the FVG. The indicator updates the "current" top/bottom of the FVG to reflect the filled portion.
Midline (Equilibrium) Touch : When price touches the 50% level of the FVG.
Full Mitigation : When price completely trades through the FVG, effectively "filling" or "rebalancing" the gap. The indicator records the mitigation time.
This state tracking is crucial for understanding how price interacts with these zones.
FVG Classification (Large FVG)
FVGs can be optionally classified as "Large FVGs" (LV) if their size (top to bottom range) exceeds a user-defined multiple of the Average True Range (ATR) for that FVG's timeframe. This helps distinguish FVGs that are significantly larger relative to recent volatility.
Visual Customization and Information Delivery
A key concept is providing extensive control over how FVGs are displayed. This control is achieved through a centralized set of visual parameters within the indicator, allowing users to configure numerous aspects (colors, line styles, visibility of boxes, midlines, mitigation lines, labels, etc.) for each timeframe. Additionally, an on-chart information panel summarizes the nearest unmitigated bullish and bearish FVG levels for each active timeframe, providing a quick glance at key price points.
█ FEATURES
This indicator offers a rich set of features designed to provide a highly customizable and comprehensive Fair Value Gap (FVG) analysis experience. Users can tailor the FVG detection, visual representation, and alerting mechanisms across three distinct timeframes: the current chart (Low Timeframe - LTF), a user-defined Medium Timeframe (MTF), and a user-defined High Timeframe (HTF).
Multi-Timeframe FVG Detection and Display
The core strength of this indicator lies in its ability to identify and display FVGs from not only the current chart's timeframe (LTF) but also from two higher, user-selectable timeframes (MTF and HTF).
Timeframe Selection: Users can specify the exact MTF (e.g., "60", "240") and HTF (e.g., "D", "W") through dedicated inputs in the "MTF (Medium Timeframe)" and "HTF (High Timeframe)" settings groups. The visibility of FVGs from these higher timeframes can be toggled independently using the "Show MTF FVGs" and "Show HTF FVGs" checkboxes.
Consistent Detection Logic: The FVG detection logic, based on the classic three-bar imbalance pattern detailed in the 'Concepts' section, is applied consistently across all selected timeframes (LTF, MTF, HTF)
Timeframe-Specific Visuals: Each timeframe's FVGs (LTF, MTF, HTF) can be customized with unique colors for bullish/bearish states and their mitigated counterparts. This allows for easy visual differentiation of FVGs originating from different market perspectives.
Comprehensive FVG Visualization Options
The indicator provides extensive control over how FVGs are visually represented on the chart for each timeframe (LTF, MTF, HTF).
FVG Boxes:
Visibility: Main FVG boxes can be shown or hidden per timeframe using the "Show FVG Boxes" (for LTF), "Show Boxes" (for MTF/HTF) inputs.
Color Customization: Colors for bullish, bearish, active, and mitigated FVG boxes (including Large FVGs, if classified) are fully customizable for each timeframe.
Box Extension & Length: FVG boxes can either be extended to the right indefinitely ("Extend Boxes Right") or set to a fixed length in bars ("Short Box Length" or "Box Length" equivalent inputs).
Box Labels: Optional labels can display the FVG's timeframe and fill percentage on the box. These labels are configurable for all timeframes (LTF, MTF, and HTF). Please note: If FVGs are positioned very close to each other on the chart, their respective labels may overlap. This can potentially lead to visual clutter, and it is a known behavior in the current version of the indicator.
Box Borders: Visibility, width, style (solid, dashed, dotted), and color of FVG box borders are customizable per timeframe.
Midlines (Equilibrium/EQ):
Visibility: The 50% level (midline or EQ) of FVGs can be shown or hidden for each timeframe.
Style Customization: Width, style, and color of the midline are customizable per timeframe. The indicator tracks if this midline has been touched by price.
Mitigation Lines:
Visibility: Mitigation lines (representing the FVG's opening level that needs to be breached for full mitigation) can be shown or hidden for each timeframe. If shown, these lines are always extended to the right.
Style Customization: Width, style, and color of the mitigation line are customizable per timeframe.
Mitigation Line Labels: Optional price labels can be displayed on mitigation lines, with a customizable horizontal bar offset for positioning. For optimal label placement, the following horizontal bar offsets are recommended: 4 for LTF, 8 for MTF, and 12 for HTF.
Persistence After Mitigation: Users can choose to keep mitigation lines visible even after an FVG is fully mitigated, with a distinct color for such lines. Importantly, this option is only effective if the general setting 'Hide Fully Mitigated FVGs' is disabled, as otherwise, the entire FVG and its lines will be removed upon mitigation.
FVG State Management and Behavior
The indicator tracks and visually responds to changes in FVG states.
Hide Fully Mitigated FVGs: This option, typically found in the indicator's general settings, allows users to automatically remove all visual elements of an FVG from the chart once price has fully mitigated it. This helps maintain chart clarity by focusing on active FVGs.
Partial Fill Visualization: When price enters an FVG, the indicator offers a dynamic visual representation: the portion of the FVG that has been filled is shown as a "mitigated box" (typically with a distinct color), while the original FVG box shrinks to clearly highlight the remaining, unfilled portion. This two-part display provides an immediate visual cue about how much of the FVG's imbalance has been addressed and what potential remains within the gap.
Visual Filtering by ATR Proximity: To help users focus on the most relevant price action, FVGs can be dynamically hidden if they are located further from the current price than a user-defined multiple of the Average True Range (ATR). This behavior is controlled by the "Filter Band Width (ATR Multiple)" input; setting this to zero disables the filter entirely, ensuring all detected FVGs remain visible regardless of their proximity to price.
Alternative Usage Example: Mitigation Lines as Key Support/Resistance Levels
For traders preferring a minimalist chart focused on key Fair Value Gap (FVG) levels, the indicator's visualization settings can be customized to display only FVG mitigation lines. This approach leverages these lines as potential support and resistance zones, reflecting areas where price might revisit to address imbalances.
To configure this view:
Disable FVG Boxes: Turn off "Show FVG Boxes" (for LTF) or "Show Boxes" (for MTF/HTF) for the desired timeframes.
Hide Midlines: Disable the visibility of the 50% FVG Midlines (Equilibrium/EQ).
Ensure Mitigation Lines are Visible: Keep "Mitigation Lines" enabled.
Retain All Mitigation Lines:
Disable the "Hide Fully Mitigated FVGs" option in the general settings.
Enable the feature to "keep mitigation lines visible even after an FVG is fully mitigated". This ensures lines from all FVGs (active or fully mitigated) remain on the chart, which is only effective if "Hide Fully Mitigated FVGs" is disabled.
This setup offers:
A Decluttered Chart: Focuses solely on the FVG opening levels.
Precise S/R Zones: Treats mitigation lines as specific points for potential price reactions.
Historical Level Analysis: Includes lines from past, fully mitigated FVGs for a comprehensive view of significant price levels.
For enhanced usability with this focused view, consider these optional additions:
The on-chart Information Panel can be activated to display a quick summary of the nearest unmitigated FVG levels.
Mitigation Line Labels can also be activated for clear price level identification. A customizable horizontal bar offset is available for positioning these labels; for example, offsets of 4 for LTF, 8 for MTF, and 12 for HTF can be effective.
FVG Classification (Large FVG)
This feature allows for distinguishing FVGs based on their size relative to market volatility.
Enable Classification: Users can enable "Classify FVG (Large FVG)" to identify FVGs that are significantly larger than average.
ATR-Based Threshold: An FVG is classified as "Large" if its height (price range) is greater than or equal to the Average True Range (ATR) of its timeframe multiplied by a user-defined "Large FVG Threshold (ATR Multiple)". The ATR period for this calculation is also configurable.
Dedicated Colors: Large FVGs (both bullish/bearish and active/mitigated) can be assigned unique colors, making them easily distinguishable on the chart.
Panel Icon: Large FVGs are marked with a special icon in the Info Panel.
Information Panel
An on-chart panel provides a quick summary of the nearest unmitigated FVG levels.
Visibility and Position: The panel can be shown/hidden and positioned in any of the nine standard locations on the chart (e.g., Top Right, Middle Center).
Content: It displays the price levels of the nearest unmitigated bullish and bearish FVGs for LTF, MTF (if active), and HTF (if active). It also indicates if these nearest FVGs are Large FVGs (if classification is enabled) using a selectable icon.
Styling: Text size, border color, header background/text colors, default text color, and "N/A" cell background color are customizable.
Highlighting: Background and text colors for the cells displaying the overall nearest bullish and bearish FVG levels (across all active timeframes) can be customized to draw attention to the most proximate FVG.
Comprehensive Alert System
The indicator offers a granular alert system for various FVG-related events, configurable for each timeframe (LTF, MTF, HTF) independently. Users can enable alerts for:
New FVG Formation: Separate alerts for new bullish and new bearish FVG formations.
FVG Entry/Partial Fill: Separate alerts for price entering a bullish FVG or a bearish FVG.
FVG Full Mitigation: Separate alerts for full mitigation of bullish and bearish FVGs.
FVG Midline (EQ) Touch: Separate alerts for price touching the midline of a bullish or bearish FVG.
Alert messages are detailed, providing information such as the timeframe, FVG type (bull/bear, Large FVG), relevant price levels, and timestamps.
█ NOTES
This section provides additional information regarding the indicator's usage, performance considerations, and potential interactions with the TradingView platform. Understanding these points can help users optimize their experience and troubleshoot effectively.
Performance and Resource Management
Maximum FVGs to Track : The "Max FVGs to Track" input (defaulting to 25) limits the number of FVG objects processed for each category (e.g., LTF Bullish, MTF Bearish). Increasing this value significantly can impact performance due to more objects being iterated over and potentially drawn, especially when multiple timeframes are active.
Drawing Object Limits : To manage performance, this script sets its own internal limits on the number of drawing objects it displays. While it allows for up to approximately 500 lines (max_lines_count=500) and 500 labels (max_labels_count=500), the number of FVG boxes is deliberately restricted to a maximum of 150 (max_boxes_count=150). This specific limit for boxes is a key performance consideration: displaying too many boxes can significantly slow down the indicator, and a very high number is often not essential for analysis. Enabling all visual elements for many FVGs across all three timeframes can cause the indicator to reach these internal limits, especially the stricter box limit
Optimization Strategies : To help you manage performance, reduce visual clutter, and avoid exceeding drawing limits when using this indicator, I recommend the following strategies:
Maintain or Lower FVG Tracking Count: The "Max FVGs to Track" input defaults to 25. I find this value generally sufficient for effective analysis and balanced performance. You can keep this default or consider reducing it further if you experience performance issues or prefer a less dense FVG display.
Utilize Proximity Filtering: I suggest activating the "Filter Band Width (ATR Multiple)" option (found under "General Settings") to display only those FVGs closer to the current price. From my experience, a value of 5 for the ATR multiple often provides a good starting point for balanced performance, but you should feel free to adjust this based on market volatility and your specific trading needs.
Hide Fully Mitigated FVGs: I strongly recommend enabling the "Hide Fully Mitigated FVGs" option. This setting automatically removes all visual elements of an FVG from the chart once it has been fully mitigated by price. Doing so significantly reduces the number of active drawing objects, lessens computational load, and helps maintain chart clarity by focusing only on active, relevant FVGs.
Disable FVG Display for Unused Timeframes: If you are not actively monitoring certain higher timeframes (MTF or HTF) for FVG analysis, I advise disabling their display by unchecking "Show MTF FVGs" or "Show HTF FVGs" respectively. This can provide a significant performance boost.
Simplify Visual Elements: For active FVGs, consider hiding less critical visual elements if they are not essential for your specific analysis. This could include box labels, borders, or even entire FVG boxes if, for example, only the mitigation lines are of interest for a particular timeframe.
Settings Changes and Platform Limits : This indicator is comprehensive and involves numerous calculations and drawings. When multiple settings are changed rapidly in quick succession, it is possible, on occasion, for TradingView to issue a "Runtime error: modify_study_limit_exceeding" or similar. This can cause the indicator to temporarily stop updating or display errors.
Recommended Approach : When adjusting settings, it is advisable to wait a brief moment (a few seconds) after each significant change. This allows the indicator to reprocess and update on the chart before another change is made
Error Recovery : Should such a runtime error occur, making a minor, different adjustment in the settings (e.g., toggling a checkbox off and then on again) and waiting briefly will typically allow the indicator to recover and resume correct operation. This behavior is related to platform limitations when handling complex scripts with many inputs and drawing objects.
Multi-Timeframe (MTF/HTF) Data and Behavior
HTF FVG Confirmation is Essential: : For an FVG from a higher timeframe (MTF or HTF) to be identified and displayed on your current chart (LTF), the three-bar pattern forming the FVG on that higher timeframe must consist of fully closed bars. The indicator does not draw speculative FVGs based on incomplete/forming bars from higher timeframes.
Data Retrieval and LTF Processing: The indicator may use techniques like lookahead = barmerge.lookahead_on for timely data retrieval from higher timeframes. However, the actual detection of an FVG occurs after all its constituent bars on the HTF have closed.
Appearance Timing on LTF (1 LTF Candle Delay): As a natural consequence of this, an FVG that is confirmed on an HTF (i.e., its third bar closes) will typically become visible on your LTF chart one LTF bar after its confirmation on the HTF.
Example: Assume an FVG forms on a 30-minute chart at 15:30 (i.e., with the close of the 30-minute bar that covers the 15:00-15:30 period). If you are monitoring this FVG on a 15-minute chart, the indicator will detect this newly formed 30-minute FVG while processing the data for the 15-minute bar that starts at 15:30 and closes at 15:45. Therefore, the 30-minute FVG will become visible on your 15-minute chart at the earliest by 15:45 (i.e., with the close of that relevant 15-minute LTF candle). This means the HTF FVG is reflected on the LTF chart with a delay equivalent to one LTF candle.
FVG Detection and Display Logic
Fair Value Gaps (FVGs) on the current chart timeframe (LTF) are detected based on barstate.isconfirmed. This means the three-bar pattern must be complete with closed bars before an FVG is identified. This confirmation method prevents FVGs from being prematurely identified on the forming bar.
Alerts
Alert Setup : To receive alerts from this indicator, you must first ensure you have enabled the specific alert conditions you are interested in within the indicator's own settings (see 'Comprehensive Alert System' under the 'FEATURES' section). Once configured, open TradingView's 'Create Alert' dialog. In the 'Condition' tab, select this indicator's name, and crucially, choose the 'Any alert() function call' option from the dropdown list. This setup allows the indicator to trigger alerts based on the precise event conditions you have activated in its settings
Alert Frequency : Alerts are designed to trigger once per bar close (alert.freq_once_per_bar_close) for the specific event.
User Interface (UI) Tips
Settings Group Icons: In the indicator settings menu, timeframe-specific groups are marked with star icons for easier navigation: 🌟 for LTF (Current Chart Timeframe), 🌟🌟 for MTF (Medium Timeframe), and 🌟🌟🌟 for HTF (High Timeframe).
Dependent Inputs: Some input settings are dependent on others being enabled. These dependencies are visually indicated in the settings menu using symbols like "↳" (dependent setting on the next line), "⟷" (mutually exclusive inline options), or "➜" (directly dependent inline option).
Settings Layout Overview: The indicator settings are organized into logical groups for ease of use. Key global display controls – such as toggles for MTF FVGs, HTF FVGs (along with their respective timeframe selectors), and the Information Panel – are conveniently located at the very top within the '⚙️ General Settings' group. This placement allows for quick access to frequently adjusted settings. Other sections provide detailed customization options for each timeframe (LTF, MTF, HTF), specific FVG components, and alert configurations.
█ FOR Pine Script® CODERS
This section provides a high-level overview of the FVG Premium indicator's internal architecture, data flow, and the interaction between its various library components. It is intended for Pine Script™ programmers who wish to understand the indicator's design, potentially extend its functionality, or learn from its structure.
System Architecture and Modular Design
The indicator is architected moduarly, leveraging several custom libraries to separate concerns and enhance code organization and reusability. Each library has a distinct responsibility:
FvgTypes: Serves as the foundational data definition layer. It defines core User-Defined Types (UDTs) like fvgObject (for storing all attributes of an FVG) and drawSettings (for visual configurations), along with enumerations like tfType.
CommonUtils: Provides utility functions for common tasks like mapping user string inputs (e.g., "Dashed" for line style) to their corresponding Pine Script™ constants (e.g., line.style_dashed) and formatting timeframe strings for display.
FvgCalculations: Contains the core logic for FVG detection (both LTF and MTF/HTF via requestMultiTFBarData), FVG classification (Large FVGs based on ATR), and checking FVG interactions with price (mitigation, partial fill).
FvgObject: Implements an object-oriented approach by attaching methods to the fvgObject UDT. These methods manage the entire visual lifecycle of an FVG on the chart, including drawing, updating based on state changes (e.g., mitigation), and deleting drawing objects. It's responsible for applying the visual configurations defined in drawSettings.
FvgPanel: Manages the creation and dynamic updates of the on-chart information panel, which displays key FVG levels.
The main indicator script acts as the orchestrator, initializing these libraries, managing user inputs, processing data flow between libraries, and handling the main event loop (bar updates) for FVG state management and alerts.
Core Data Flow and FVG Lifecycle Management
The general data flow and FVG lifecycle can be summarized as follows:
Input Processing: User inputs from the "Settings" dialog are read by the main indicator script. Visual style inputs (colors, line styles, etc.) are consolidated into a types.drawSettings object (defined in FvgTypes). Other inputs (timeframes, filter settings, alert toggles) control the behavior of different modules. CommonUtils assists in mapping some string inputs to Pine constants.
FVG Detection:
For the current chart timeframe (LTF), FvgCalculations.detectFvg() identifies potential FVGs based on bar patterns.
For MTF/HTF, the main indicator script calls FvgCalculations.requestMultiTFBarData() to fetch necessary bar data from higher timeframes, then FvgCalculations.detectMultiTFFvg() identifies FVGs.
Newly detected FVGs are instantiated as types.fvgObject and stored in arrays within the main script. These objects also undergo classification (e.g., Large FVG) by FvgCalculations.
State Update & Interaction: On each bar, the main indicator script iterates through active FVG objects to manage their state based on price interaction:
Initially, the main script calls FvgCalculations.fvgInteractionCheck() to efficiently determine if the current bar's price might be interacting with a given FVG.
If a potential interaction is flagged, the main script then invokes methods directly on the fvgObject instance (e.g., updateMitigation(), updatePartialFill(), checkMidlineTouch(), which are part of FvgObject).
These fvgObject methods are responsible for the detailed condition checking and the actual modification of the FVG's state. For instance, the updateMitigation() and updatePartialFill() methods internally utilize specific helper functions from FvgCalculations (like checkMitigation() and checkPartialMitigation()) to confirm the precise nature of the interaction before updating the fvgObject’s state fields (such as isMitigated, currentTop, currentBottom, or isMidlineTouched).
Visual Rendering:
The FvgObject.updateDrawings() method is called for each fvgObject. This method is central to drawing management; it creates, updates, or deletes chart drawings (boxes, lines, labels) based on the FVG's current state, its prev_* (previous bar state) fields for optimization, and the visual settings passed via the drawSettings object.
Information Panel Update: The main indicator script determines the nearest FVG levels, populates a panelData object (defined in FvgPanelLib), and calls FvgPanel.updatePanel() to refresh the on-chart display.
Alert Generation: Based on the updated FVG states and user-enabled alert settings, the main indicator script constructs and triggers alerts using Pine Script's alert() function."
Key Design Considerations
UDT-Centric Design: The fvgObject UDT is pivotal, acting as a stateful container for all information related to a single FVG. Most operations revolve around creating, updating, or querying these objects.
State Management: To optimize drawing updates and manage FVG lifecycles, fvgObject instances store their previous bar's state (e.g., prevIsVisible, prevCurrentTop). The FvgObject.updateDrawings() method uses this to determine if a redraw is necessary, minimizing redundant drawing calls.
Settings Object: A drawSettings object is populated once (or when inputs change) and passed to drawing functions. This avoids repeatedly reading numerous input() values on every bar or within loops, improving performance.
Dynamic Arrays for FVG Storage: Arrays are used to store collections of fvgObject instances, allowing for dynamic management (adding new FVGs, iterating for updates).
Nef33-Volume Footprint ApproximationDescription of the "Volume Footprint Approximation" Indicator
Purpose
The "Volume Footprint Approximation" indicator is a tool designed to assist traders in analyzing market volume dynamics and anticipating potential trend changes in price. It is inspired by the concept of a volume footprint chart, which visualizes the distribution of trading volume across different price levels. However, since TradingView does not provide detailed intrabar data for all users, this indicator approximates the behavior of a footprint chart by using available volume and price data (open, close, volume) to classify volume as buy or sell, calculate volume delta, detect imbalances, and generate trend change signals.
The indicator is particularly useful for identifying areas of high buying or selling activity, imbalances between supply and demand, delta divergences, and potential reversal points in the market. It provides specific signals for bullish and bearish trend changes, making it suitable for traders looking to trade reversals or confirm trends.
How It Works
The indicator uses volume and price data from each candlestick to perform the following calculations:
Volume Classification:
Classifies the volume of each candlestick as "buy" or "sell" based on price movement:
If the closing price is higher than the opening price (close > open), the volume is classified as "buy."
If the closing price is lower than the opening price (close < open), the volume is classified as "sell."
If the closing price equals the opening price (close == open), it compares with the previous close to determine the direction:
If the current close is higher than the previous close, it is classified as "buy."
If the current close is lower than the previous close, it is classified as "sell."
If the current close equals the previous close, the classification from the previous bar is used.
Delta Calculation:
Calculates the volume delta as the difference between buy volume and sell volume (buyVolume - sellVolume).
A positive delta indicates more buy volume; a negative delta indicates more sell volume.
Imbalance Detection:
Identifies imbalances between buy and sell volume:
A buy imbalance occurs when buy volume exceeds sell volume by a defined percentage (default is 300%).
A sell imbalance occurs when sell volume exceeds buy volume by the same percentage.
Delta Divergence Detection:
Positive Delta Divergence: Occurs when the price is falling (for at least 2 bars) but the delta is increasing or becomes positive, indicating that buyers are entering despite the price decline.
Negative Delta Divergence: Occurs when the price is rising (for at least 2 bars) but the delta is decreasing or becomes negative, indicating that sellers are entering despite the price increase.
Trend Change Signals:
Bullish Signal (trendChangeBullish): Generated when the following conditions are met:
There is a positive delta divergence.
The delta has moved from a negative value (e.g., -500) to a positive value (e.g., +200) over the last 3 bars.
There is a buy imbalance.
The price is near a historical support level (approximated as the lowest low of the last 50 bars).
Bearish Signal (trendChangeBearish): Generated when the following conditions are met:
There is a negative delta divergence.
The delta has moved from a positive value (e.g., +500) to a negative value (e.g., -200) over the last 3 bars.
There is a sell imbalance.
The price is near a historical resistance level (approximated as the highest high of the last 50 bars).
Visual Elements
The indicator is displayed in a separate panel below the price chart (overlay=false) and includes the following elements:
Volume Histograms:
Buy Volume: Represented by a green histogram. Shows the volume classified as "buy."
Sell Volume: Represented by a red histogram. Shows the volume classified as "sell."
Note: The histograms overlap, and the last plotted histogram (red) takes visual precedence, meaning the sell volume may cover the buy volume if it is larger.
Delta Line:
Delta Volume: Represented by a blue line. Shows the difference between buy and sell volume.
A line above zero indicates more buy volume; a line below zero indicates more sell volume.
A dashed gray horizontal line marks the zero level for easier interpretation.
Imbalance Backgrounds:
Buy Imbalance: Light green background when buy volume exceeds sell volume by the defined percentage.
Sell Imbalance: Light red background when sell volume exceeds buy volume by the defined percentage.
Divergence Backgrounds:
Positive Delta Divergence: Lime green background when a positive delta divergence is detected.
Negative Delta Divergence: Fuchsia background when a negative delta divergence is detected.
Trend Change Signals:
Bullish Signal: Green label with the text "Bullish Trend Change" when the conditions for a bullish trend change are met.
Bearish Signal: Red label with the text "Bearish Trend Change" when the conditions for a bearish trend change are met.
Information Labels:
Below each bar, a label displays:
Total Vol: The total volume of the bar.
Delta: The delta volume value.
Alerts
The indicator generates the following alerts:
Positive Delta Divergence: "Positive Delta Divergence Detected! Price is falling, but delta is increasing."
Negative Delta Divergence: "Negative Delta Divergence Detected! Price is rising, but delta is decreasing."
Bullish Trend Change Signal: "Bullish Trend Change Signal! Positive Delta Divergence, Delta Rise, Buy Imbalance, and Near Support."
Bearish Trend Change Signal: "Bearish Trend Change Signal! Negative Delta Divergence, Delta Drop, Sell Imbalance, and Near Resistance."
These alerts can be configured in TradingView to receive real-time notifications.
Adjustable Parameters
The indicator allows customization of the following parameters:
Imbalance Threshold (%): The percentage required to detect an imbalance between buy and sell volume (default is 300%).
Lookback Period for Divergence: Number of bars to look back for detecting price and delta trends (default is 2 bars).
Support/Resistance Lookback Period: Number of bars to look back for identifying historical support and resistance levels (default is 50 bars).
Delta High Threshold (Bearish): Minimum delta value 2 bars ago for the bearish signal (default is +500).
Delta Low Threshold (Bearish): Maximum delta value in the current bar for the bearish signal (default is -200).
Delta Low Threshold (Bullish): Maximum delta value 2 bars ago for the bullish signal (default is -500).
Delta High Threshold (Bullish): Minimum delta value in the current bar for the bullish signal (default is +200).
Practical Use
The indicator is useful for the following purposes:
Identifying Trend Changes:
The trend change signals (trendChangeBullish and trendChangeBearish) indicate potential price reversals. For example, a bullish signal near a support level may be an opportunity to enter a long position.
Detecting Divergences:
Delta divergences (positive and negative) can anticipate trend changes by showing a disagreement between price movement and underlying buying/selling pressure.
Finding Key Levels:
Imbalances (green and red backgrounds) often coincide with support and resistance levels, helping to identify areas where the market might react.
Confirming Trends:
A consistently positive delta in an uptrend or a negative delta in a downtrend can confirm the strength of the trend.
Identifying Failed Auctions:
Although not detected automatically, you can manually identify failed auctions by observing a price move to new highs/lows with decreasing volume in the direction of the move.
Limitations
Intrabar Data: It does not use detailed intrabar data, making it less precise than a native footprint chart.
Approximations: Volume classification and support/resistance detection are approximations, which may lead to false signals.
Volume Dependency: It requires reliable volume data, so it may be less effective on assets with inaccurate volume data (e.g., some forex pairs).
False Signals: Divergences and imbalances do not always indicate a trend change, especially in strongly trending markets.
Recommendations
Combine with Other Indicators: Use tools like RSI, MACD, support/resistance levels, or candlestick patterns to confirm signals.
Trade on Higher Timeframes: Signals are more reliable on higher timeframes like 1-hour or 4-hour charts.
Perform Backtesting: Evaluate the indicator's accuracy on historical data to adjust parameters and improve effectiveness.
Adjust Parameters: Modify thresholds (e.g., imbalanceThreshold or supportResistanceLookback) based on the asset and timeframe you are trading.
Conclusion
The "Volume Footprint Approximation" indicator is a powerful tool for analyzing volume dynamics and anticipating price trend changes. By classifying volume, calculating delta, detecting imbalances and divergences, and generating trend change signals, it provides traders with valuable insights into market buying and selling pressure. While it has limitations due to the lack of intrabar data, it can be highly effective when used in combination with other technical analysis tools and on assets with reliable volume data.
IPO Date ScreenerThis script, the IPO Date Screener, allows traders to visually identify stocks that are relatively new, based on the number of bars (days) since their IPO. The user can set a custom threshold for the number of days (bars) after the IPO, and the script will highlight new stocks that fall below that threshold.
Key Features:
Customizable IPO Days Threshold: Set the threshold for considering a stock as "new." Since Pine screener limits number bars to 500, it will work for stocks having trading days below 500 since IPO which almost 2 years.
Column Days since IPO: Sort this column from low to high to see newest to oldest STOCK with 500 days of trading.
Since a watchlist is limited to 1000 stocks, use this pines script to screen stocks within the watch list having trading days below 500 or user can select lower number of days from settings.
This is not helpful to add on chart, this is to use on pine screener as utility.
Non-Psychological Levels🟩 Non-Psychological Levels is a structural analysis tool that segments price action into objective ranges, identifying Broken and Unbroken levels without relying on psychological or time-based assumptions. By emphasizing mechanically derived price behavior, it provides traders with a clear framework for analyzing support and resistance in a consistent and unbiased manner across various market conditions.
This indicator introduces a new approach to understanding market structure by focusing on price movement within defined segments, free from behavioral patterns, round numbers, or specific time intervals. While the indicator is time-agnostic in design, it works within the natural time progression of the chart, ensuring that segmentation aligns with the inherent structure of price movement. Broken levels, where price has breached a structural boundary, and Unbroken levels, which remain intact, are visualized with horizontal lines. These structural zones are complemented by dynamically boxed segments that contextualize both historical and ongoing price behavior.
By offering an objective perspective, the Non-Psychological Levels indicator complements psychology-based tools, helping traders explore market dynamics from multiple angles. When structural levels align with psychological zones, they reinforce critical price areas; when they differ, they provide opportunities to analyze price behavior from an alternative lens. This indicator is designed as both an educational framework and a practical tool, encouraging a deeper understanding of structural price behavior in technical analysis.
⭕ THEORY AND CONCEPT ⭕
The Non-Psychological Levels indicator is grounded in the principle of analyzing price behavior without reliance on psychological assumptions or time-based factors. Its primary purpose is to provide a structural framework for identifying support and resistance levels by focusing solely on price movement within mechanically defined segments. By removing external influences such as sentiment, time intervals, or market sessions, the indicator offers an unbiased lens through which traders can observe price dynamics.
Non-psychology, as defined here, refers to an approach that excludes behavioral and emotional patterns—like fear, greed, or herd mentality—from price analysis. Traditional tools often depend on these patterns to identify zones such as pivots or Fibonacci retracements, but these methods can be inconsistent in volatile markets. In contrast, the Non-Psychological Levels indicator focuses entirely on what price is doing, free from assumptions about trader behavior or external time constraints.
The indicator’s time-agnostic and mechanically driven design segments price action into consistent ranges, highlighting "Broken" levels (where price breaches structural boundaries) and "Unbroken" levels (where price holds). These structural zones remain unaffected by subjective or external influences, ensuring clarity and consistency across different markets and timeframes. By doing so, the indicator reveals a pure view of price structure, independent of psychological biases.
Importantly, the Non-Psychological Levels indicator is not intended to replace psychology-based tools but to complement them. When its structural levels align with psychological zones like round numbers or session highs/lows, the significance of these areas is reinforced. Conversely, when the levels differ, the contrast provides traders with alternative insights into market dynamics. This dual perspective—blending mechanical objectivity with behavioral analysis—enhances the depth and flexibility of market evaluation.
The following principles outline the theoretical foundation of the indicator and its unique contribution to structural price analysis:
Time-Agnostic Design : The indicator avoids reliance on time-based factors like daily opens, session intervals, or specific events. Instead, it segments price action using bar indexes, ensuring that structural levels are identified independently of external time variables. While the x-axis of a chart inherently represents time, this indicator abstracts away its influence, allowing traders to focus purely on price movement without the bias of temporal context.
Mechanical and Neutral Framework : Every calculation within the indicator is predetermined by a set of mechanical rules, ensuring no subjective input or interpretation affects the results. This objectivity guarantees that levels are derived solely from observed price behavior, providing a reliable framework that traders can trust to remain consistent across different assets, timeframes, and market conditions.
Broken and Unbroken Levels : Broken levels represent zones where price has breached a structural boundary, while Unbroken levels highlight areas where price has consistently respected its range. This distinction provides a clear and systematic method for identifying key support and resistance levels, offering insights into where future price interactions are most likely to occur.
Neutral Price Behavior : By dividing price action into equal segments, the indicator removes the influence of external factors like trader sentiment or psychological expectations. Each segment independently determines significant levels based purely on price action, enabling a structural view of the market that abstracts away behavioral or emotional biases.
Complement to Psychological Tools : While the indicator itself avoids behavioral assumptions, its levels can align with psychological zones like round numbers, pivots, or Fibonacci levels. When these structural and psychological levels overlap, it reinforces the importance of key areas, while divergences offer opportunities to examine price behavior from a new perspective.
Educational Value : The indicator encourages traders to explore the contrast between structural and psychological analysis. By introducing a framework that isolates price behavior from external influences, it challenges traditional methods of technical analysis, fostering deeper insights into market structure and behavior.
🔍 UNDERSTANDING STRUCTURAL LEVELS 🔍
The Non-Psychological Levels indicator offers a straightforward yet powerful way to understand market structure by segmenting price action into mechanically defined ranges. This segmentation highlights two key elements: "Broken" levels, where price has breached structural boundaries, and "Unbroken" levels, which remain intact and respected by price action. Together, these components create a framework for identifying potential areas of support and resistance.
Broken Levels : These are structural boundaries that price has surpassed, indicating areas where previous support or resistance failed. Broken levels often signal transitions in price behavior, such as shifts in momentum or the start of trending movements. They provide insight into zones where price has already tested and moved beyond.
Unbroken Levels : These levels remain intact within a given price segment, marking areas where price has consistently respected boundaries. Unbroken levels are particularly useful for identifying potential reversal points or zones of continued support or resistance. Their persistence across price action often makes them reliable indicators of market structure.
The visual segmentation of price action into distinct ranges allows traders to observe how price transitions between structural zones. For example:
- Clusters of Unbroken levels near the current price may suggest strong support or resistance, offering areas of interest for reversals or breakouts.
- Gaps between Unbroken levels highlight areas of price inefficiency or low interaction, which may become significant if revisited.
By focusing solely on structural price behavior, the Non-Psychological Levels indicator enables traders to analyze price independently of time or psychological factors. This makes it a valuable tool for understanding price dynamics objectively, whether used on its own or alongside other indicators.
🛠️ SETTINGS 🛠️
The Non-Psychological Levels indicator offers various customizable settings to help users tailor its visualization to their specific trading style and market conditions. These settings allow adjustments to sensitivity, level projection, and the source of price calculations (e.g., wicks or closing prices). Below, we outline each setting and its impact on the chart, along with examples to illustrate their functionality.
Custom Settings
Sensitivity : This setting adjusts the balance between detailed and broader structural levels by controlling the number of segments. Higher values result in more segments, revealing finer price levels, while lower values consolidate segments to highlight major price movements.
Source : Allows the user to choose between 'Wick' or 'Close' for detecting levels. Selecting 'Wick' emphasizes the absolute highs and lows of price action, while 'Close' focuses on closing prices within each segment.
Level Labels : Configures the visual representation of price levels, allowing users to toggle between price values, symbols (▲ ▼), or disabling labels altogether. This setting ensures clarity in how Broken and Unbroken levels are displayed on the chart.
Unbroken Levels : - - - Users can customize the colors and label styles for Unbroken levels, which highlight areas where price has respected structural boundaries.
Broken Levels : -|- Similar to Unbroken levels, users can specify the visual appearance of Broken levels, including color customization for Broken highs and lows. These settings help distinguish areas where price has breached a structural boundary.
Projection Options : This setting allows users to control how broken and unbroken levels are visually extended on the chart. The Future option projects lines forward to the right of the current price, showing potential future relevance of levels. The All option extends lines both forward and backward, providing a comprehensive view of how levels align with historical and potential future price action. The None option disables projections, keeping the chart focused solely on current segment levels without any extensions.
Segments : Includes options for customizing the segment visualization:
- Live Segment : Toggles the display of a highlighted box representing the current developing segment, helping users focus on ongoing price action.
- Boxes : Allows users to display filled boxes around each segment for additional visual emphasis.
- Segment Colors : Users can define separate colors for support (lower) and resistance (upper) segments, making it easier to interpret directional trends.
- Boundaries : Enables or disables vertical lines to mark segment boundaries, providing a clearer view of structural divisions.
Repaint : This setting allows users to enable or disable triangle labels within the live segment. When enabled, the triangles dynamically update to reflect real-time price behavior during the live bar but will repaint until the bar is fully confirmed. Disabling this option prevents the triangles from appearing during the live bar, reducing potential confusion as they may otherwise flash on and off during price updates. This setting ensures users can choose their preferred visualization while maintaining clarity in real-time analysis.
Color Settings : Offers extensive customization for all visual elements, including Broken and Unbroken levels, segment boundaries, and live segments. These settings ensure the indicator can adapt to individual preferences for chart readability.
🖼️ CHART EXAMPLES 🖼️
The following chart examples illustrate different configurations and features of the Non-Psychological Levels indicator. These examples highlight how the indicator’s settings influence the visualization of structural price behavior, helping traders understand its functionality in various scenarios.
Broken and Unbroken Levels : Orange prices are Broken HIghs. Blue prices are Broken Lows. Green and Red are Unbroken.
Boundaries : Enable Boundaries to visualize segments.
High Sensitivity Setting : A high sensitivity setting produces fewer segments and levels, emphasizing broader price ranges and major structural zones. This configuration is better suited for higher timeframes or identifying overarching trends.
Low Sensitivity Setting : A low sensitivity setting results in a greater number of segments and levels, offering a granular view of price structure. This configuration is ideal for analyzing detailed price movements on lower timeframes.
Live Segment with Triangles Enabled : This example shows the live segment box with triangle labels enabled. These triangles update dynamically during the live bar but may repaint until the bar is confirmed, helping traders observe real-time price behavior.
Broken and Unbroken Levels : This example highlights Broken levels (where price has breached structural boundaries and are drawn through subsequent price action) and Unbroken levels (where price has respected structural boundaries). These distinctions visually identify areas of potential support and resistance.
Broken and Unbroken Levels with Projection: All : This example demonstrates the "Project All" feature, where broken and unbroken levels are extended both forward and backward on the chart. This visualization highlights historical and potential future support and resistance zones, helping traders better understand how price interacts with these structural levels over time.
Segment Boxes with Boundaries : Filled boxes around individual segments visually distinguish each price interval, offering clarity in observing structural price transitions.
📊 SUMMARY 📊
The Non-Psychological Levels indicator provides a unique framework for analyzing structural price behavior through the identification of Broken and Unbroken levels. These levels act as a mechanical representation of support and resistance, independent of psychological biases or time-based factors. By focusing purely on price movement within defined segments, the indicator offers a neutral and consistent approach to understanding market dynamics.
This method complements traditional tools by providing an unbiased perspective. When structural levels align with psychological zones—such as round numbers or session-based highs and lows—they reinforce the significance of these areas as key price zones. When they diverge, the indicator introduces an alternative view, prompting further exploration of price behavior. This dual perspective enhances the depth of analysis by combining the mechanical and behavioral aspects of price action.
The Non-Psychological Levels indicator is not designed to generate trading signals or predict future price movements but serves as a visual and educational tool. Its adaptability across all markets and timeframes allows traders to integrate it into their broader strategies. By highlighting structural price dynamics, the indicator offers a fresh perspective on market analysis while remaining compatible with other technical tools.
⚙️ COMPATIBILITY AND LIMITATIONS ⚙️
Asset Compatibility :
The Non-Psychological Levels indicator is compatible with all asset classes, including cryptocurrencies, forex, stocks, and commodities. It can be applied to any chart or timeframe, making it a flexible tool for structural price analysis. Users should adjust the Sensitivity setting to ensure the segmentation aligns with the price behavior of the specific asset being analyzed. For instance, higher sensitivity values are more suitable for assets with large price ranges, while lower values work well for assets with tighter ranges.
Visual Range Dependency :
The indicator is optimized to perform calculations only within the visible range of the chart. This is a significant advantage, as it prevents unnecessary calculations and maintains efficient performance. However, because of this dependency, levels may appear to "recalculate" when the chart is zoomed in or out quickly or shifted abruptly. While this does not affect the integrity of the levels, it may cause a temporary lag as the indicator adjusts to the new visual range.
Persistence of Levels Beyond Visibility :
Even if levels are not visible on the chart due to zoom or scroll settings, they still exist in the background and are recalculated when revisited. This ensures that the structural price analysis remains consistent, regardless of the chart view.
Box Limitations in Pine Script :
The indicator is subject to Pine Script's inherent limitation of 500 boxes. This means that no more than 500 segments or level boxes can be drawn on the chart simultaneously. For most configurations, this limitation is mitigated by focusing on the visual range, but users employing very low sensitivity settings may exceed the limit. In such cases, only the most recent 500 boxes will be displayed, potentially omitting earlier segments.
Lag with Low Sensitivity Settings :
When sensitivity is set to a low value, the indicator creates many more segments, resulting in finer granularity and a higher number of boxes. While this provides detailed structural levels, it may increase the likelihood of exceeding Pine Script’s 500-box limit or cause a temporary lag when rendering a dense set of boxes over a wide visual range. Users should adjust sensitivity to balance detail with performance, especially on assets with high volatility or broad price ranges.
Live Segment Caution :
The live segment box updates in real time to reflect price movements as the segment is still developing. Since the segment high and segment low are not yet finalized, users should interpret this feature as a dynamic visualization of current price behavior rather than a definitive structural analysis. This ensures clarity during ongoing price action while maintaining the integrity of the indicator's framework.
Cross-Market Versatility :
The indicator’s time-agnostic and mechanical design ensures that it functions identically across all markets and timeframes. However, users should consider the unique characteristics of different markets when interpreting the results, as certain assets (e.g., highly volatile cryptocurrencies) may require sensitivity adjustments for optimal segmentation.
Visual Range Dependency: Levels recalculate efficiently within the chart's visible range but may lag temporarily when zooming or scrolling quickly.
These considerations ensure that the Non-Psychological Levels indicator remains robust and versatile while highlighting some inherent limitations of Pine Script and real-time recalculations. Users can mitigate these constraints by carefully adjusting sensitivity and understanding how the visual range dependency affects performance.
⚠️ DISCLAIMER ⚠️
The Non-Psychological Levels indicator is a visual analysis tool and is not designed as a predictive or trading signal indicator. Its primary purpose is to highlight structural price levels, providing an objective framework for understanding support and resistance within mechanically segmented price action.
The indicator operates within the visible range of the chart to ensure efficiency and adaptiveness, but this recalculation should not be interpreted as a forecast of future price behavior. While the structural levels may align with significant price zones in hindsight, they are purely a reflection of observed price dynamics and should not be used as standalone trading signals.
This indicator is intended as an educational and visual aid to complement other analysis methods. Users are encouraged to integrate it into a broader trading strategy and make adjustments to the settings based on their individual needs and market conditions.
🧠 BEYOND THE CODE 🧠
The Non-Psychological Levels indicator, like other xxattaxx indicators , is designed with education and community collaboration in mind. Its open-source nature encourages exploration, experimentation, and the development of new approaches to price analysis. By focusing on structural price behavior rather than psychological or time-based factors, this indicator introduces a fresh perspective for users to study.
Beyond its visual utility, the indicator serves as an educational framework for understanding the concept of non-psychological analysis. It offers traders an opportunity to explore price dynamics in a purely mechanical way, challenging conventional methods and fostering deeper insights into structural behavior. This approach is especially valuable for those interested in exploring new concepts or seeking alternative perspectives on market analysis.
Your comments, suggestions, and discussions are invaluable in shaping the future of this project. We actively encourage your feedback and contributions, which will directly help us refine and improve the Non-Psychological Levels indicator. We look forward to seeing the creative ways in which you use and enhance this tool. MVS
Industry Group StrengthThe Industry Group Strength indicator is designed to help traders identify the best-performing stocks within specific industry groups. The movement of individual stocks is often closely tied to the overall performance of their industry. By focusing on industry groups, this indicator allows you to find the top-performing stocks within an industry.
Thanks to a recent Pine Script update, an indicator like this is now possible. Special thanks to @PineCoders for introducing the dynamic requests feature.
How this indicator works:
The indicator contains predefined lists of stocks for each industry group. To be included in these lists, stocks must meet the following basic filters:
Market capitalization over 2B
Price greater than $10
Primary listing status
Once the relevant stocks are filtered, the indicator automatically recognizes the industry group of the current stock displayed on the chart. It then retrieves and displays data for that entire industry group.
Data Points Available:
The user can choose between three different data points to rank and compare stocks:
YTD (Year-To-Date) Return: Measures how much a stock has gained or lost since the start of the year.
RS Rating: A relative strength rating for a user-selected lookback period (explained below).
% Return: The percentage return over a user-selected lookback period.
Stock Ranking:
Stocks are ranked based on their performance within their respective industry groups, allowing users to easily identify which stocks are leading or lagging behind others in the same sector.
Visualization:
The indicator presents stocks in a table format, with performance metrics displayed both as text labels and color-coded lines. The color gradient represents the percentile rank, making it visually clear which stocks are outperforming or underperforming within their industry group.
Relative Strength (RS):
Relative Strength (RS) measures a stock’s performance relative to a benchmark, typically the S&P 500 (the default setting). It is calculated by dividing the closing price of the stock by the closing price of the S&P 500.
If the stock rises while the S&P 500 falls, or if the stock rises more sharply than the S&P 500, the RS value increases. Conversely, if the stock falls while the S&P 500 rises, the RS value decreases. This indicator normalizes the RS value into a range from 1 to 99, allowing for easier comparison across different stocks, regardless of their raw performance. This normalized RS value helps traders quickly assess how a stock is performing relative to others.
SP500 RatiosThe "SP500 Ratios" indicator is a powerful tool developed for the TradingView platform, allowing users to access a variety of financial ratios and inflation-adjusted data related to the S&P 500 index. This indicator integrates with Nasdaq Data Link (formerly known as Quandl) to retrieve historical data, providing a comprehensive overview of key financial metrics associated with the S&P 500.
Key Features
Price to Sales Ratio: Quarterly ratio of price to sales (revenue) for the S&P 500.
Dividend Yield: Monthly dividend yield based on 12-month dividend per share.
Price Earnings Ratio (PE Ratio): Monthly price-to-earnings ratio based on trailing twelve-month reported earnings.
CAPE Ratio (Shiller PE Ratio): Monthly cyclically adjusted PE ratio, based on average inflation-adjusted earnings over the past ten years.
Earnings Yield: Monthly earnings yield, the inverse of the PE ratio.
Price to Book Ratio: Quarterly ratio of price to book value.
Inflation Adjusted S&P 500: Monthly S&P 500 level adjusted for inflation.
Revenue Per Share: Quarterly trailing twelve-month sales per share, not adjusted for inflation.
Earnings Per Share: Monthly real earnings per share, adjusted for inflation.
User Configuration
The indicator offers flexibility through user-configurable options. You can choose to display or hide each metric according to your analysis needs. Users can also adjust the line width for better visibility on the chart.
Visualization
The selected data is plotted on the chart with distinct colors for each metric, facilitating visual analysis. A dynamic legend table is also generated in the top-right corner of the chart, listing the currently displayed metrics with their associated colors.
This indicator is ideal for traders and analysts seeking detailed insights into the financial performance and valuations of the S&P 500, while benefiting from the customization flexibility offered by TradingView.
Volatility Projection Levels (VPL)### Indicator Name: **Volatility Projection Levels (VPL)**
### Description:
The **Volatility Projection Levels (VPL)** indicator is a powerful tool designed to help traders anticipate key support and resistance levels for the E-mini S&P 500 (ES) by leveraging the CBOE Volatility Index (^VIX). This indicator utilizes historical volatility data to project potential price movements for the upcoming month, offering clear visual cues that enhance swing trading strategies.
### Key Features:
- **Volatility-Based Projections**: The VPL indicator uses the previous month’s closing value of the VIX, normalizing it for monthly analysis by dividing by the square root of 12. This calculated percentage is then applied to the E-mini S&P 500’s closing price from the last day of the previous month.
- **Upper and Lower Projection Levels**: The indicator calculates two essential levels:
- **Upper Projection Level**: The previous month’s closing price of the E-mini S&P 500 plus the calculated volatility percentage.
- **Lower Projection Level**: The previous month’s closing price of the E-mini S&P 500 minus the calculated volatility percentage.
- **Continuous Visualization**: The VPL indicator plots these projection levels on the chart throughout the entire month, providing traders with a consistent reference for potential support and resistance zones. This continuous visualization allows for better anticipation of market movements.
- **Previous Month's Close Reference**: Additionally, the indicator plots the previous month’s closing price as a reference point, offering further context for current price action.
### Use Cases:
- **Swing Trading**: The VPL indicator is ideal for swing traders looking to exploit predicted price ranges within a monthly timeframe.
- **Support & Resistance Identification**: It aids traders in identifying critical levels where the market may encounter support or resistance, thus informing entry and exit decisions.
- **Risk Management**: By forecasting potential price levels, traders can set more strategic stop-loss and take-profit levels, enhancing risk management.
### Summary:
The **Volatility Projection Levels (VPL)** indicator equips traders with a forward-looking tool that incorporates volatility data into market analysis. By projecting key price levels based on historical VIX data, the VPL indicator enhances decision-making, helping traders anticipate market movements and optimize their trading strategies.
Made by Serpenttrading
Market Breadth - AsymmetrikMarket Breadth - Asymmetrik User Manual
Overview
The Market Breadth - Asymmetrik is a script designed to provide insights into the overall market condition by plotting three key indicators based on stocks within the S&P 500 index. It helps traders assess market momentum and strength through visual cues and is especially useful for understanding the proportion of stocks trading above their respective moving averages.
Features
1. Market Breadth Indicators:
- Breadth 20D (green line): Represents the percentage of stocks in the S&P 500 that are above their 20-day moving average.
- Breadth 50D (yellow line): Represents the percentage of stocks in the S&P 500 that are above their 50-day moving average.
- Breadth 100D (red line): Represents the percentage of stocks in the S&P 500 that are above their 100-day moving average.
2. Horizontal Lines for Context:
- Green line at 10%
- Lighter green line at 20%
- Grey line at 50%
- Light red line at 80%
- Dark red line at 90%
3. Background Color Alerts:
- Green background when all three indicators are under 20%, indicating a potential oversold market condition.
- Red background when all three indicators are over 80%, indicating a potential overbought market condition.
Interpreting the Indicator
- Market Breadth Lines: Observe the plotted lines to assess the percentage of stocks above their moving averages.
- Horizontal Lines: Use the horizontal lines to quickly identify important threshold levels.
- Background Colors: Pay attention to background colors for quick insights:
- Green: All indicators suggest a potentially oversold market condition (below 20).
- Red: All indicators suggest a potentially overbought market condition (above 80).
Troubleshooting
- If the indicator does not appear as expected, please contact me.
- This indicator works only on daily and weekly timeframes.
Conclusion
This Market Breadth Indicator offers a visual representation of market momentum and strength through three key indicators, helping you identify potential buying and selling zones.
Earnings Yield & Dividend Yield (vs SP500, treasury, IG)# What's this script?
I created this because I wanted to compare the Earnings/Dividend yield of SP500 and the symbol with the time period of the chart.
Plot the following yields.
Earnings Yield of S&P500.
Calculated using S&P 500 Earnings by Month provided by Nasdaq date link.
(data.nasdaq.com)
Dividend Yield of S&P500.
Calculated using S&P 500 Dividend by Month provided by Nasdaq date link.
(data.nasdaq.com)
Earnings Yield of the displayed symbol.
Dividend Yield of the displayed symbol.
Treasury constant maturity rate. default is 10Y(FRED:DGS10).
Investment grade corporate bond yields by Moody's.
Grades from Aaa to Baa are represented by color bands.
Investment grade bond yields by BofA.
Grades from AAA to BBB are represented by color bands.
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◇これなに？
request.quandl()を用いてSP500の益回りと配当利回りが得られますが
月間データなのでチャートの時間間隔でみたかったのと、
SP500とシンボルの益回りや配当利回りを比較したかったのでつくりました。
下記を表示します
- SP500の益回りと配当利回り
- 表示シンボルの益回りや配当利回り
- 設定画面で指定した財務省債券（デフォルトは10年）
- 投資適格社債（MoodysとBofAでかなり違ったので両方）をカラーバンドで表示
かんたんなものですけど、おやくにたてればさいわいです
Rsi strategy for BTC with (Rsi SPX)
I hope this strategy is just an idea and a starting point, I use the correlation of the Sp500 with the Btc, this does not mean that this correlation will exist forever!. I love Trading view and I'm learning to program, I find correlations very interesting and here is a simple strategy.
This is a trading strategy script written in Pine Script language for use in TradingView. Here is a brief overview of the strategy:
The script uses the RSI (Relative Strength Index) technical indicator with a period of 14 on two securities: the S&P 500 (SPX) and the symbol corresponding to the current chart (presumably Bitcoin, based on the variable name "Btc_1h_fixed"). The RSI is plotted on the chart for both securities.
The script then sets up two trading conditions using the RSI values:
A long entry condition: when the RSI for the current symbol crosses above the RSI for the S&P 500, a long trade is opened using the "strategy.entry" function.
A short entry condition: when the RSI for the current symbol crosses below the RSI for the S&P 500, a short trade is opened using the "strategy.entry" function.
The script also includes a take profit input parameter that allows the user to set a percentage profit target for closing the trade. The take profit is set using the "strategy.exit" function.
Overall, the strategy aims to take advantage of divergences in RSI values between the current symbol and the S&P 500 by opening long or short trades accordingly. The take profit parameter allows the user to set a specific profit target for each trade. However, the script does not include any stop loss or risk management features, which should be considered when implementing the strategy in a real trading scenario.
BTC/USD - RSIIF RSI (14) reaches 68 ... sell 1 lot size ( with TP 250 points and SL 500 points)
IF RSI (14) reaches 27 ... buy 1 lot size ( with TP 250points and SL 500 points)
IF RSI (14) reaches 80 ... sell 1 lot size ( with TP 250 points and SL 500 points)
IF RSI (14) reaches 18 ... buy 1 lot size ( with TP 250points and SL 500 points)
VIX MTF MomentumSweet little momentum gadget to track the VIX Index.
What is the VIX?
The CBOE S&P 500 Volatility Index (VIX) is known as the 'Fear Index' which can measure how worried traders are that the S&P 500 might suddenly drop within the next 30 days.
When the VIX starts moving higher, it is telling you that traders are getting nervous. When the VIX starts moving lower, it is telling you that traders are gaining confidence.
VIX calculation?
The Chicago Board of Options Exchange Market Volatility Index (VIX) is a measure of implied volatility (Of the S&P 500 securities options), based on the prices of a basket of S&P 500 Index options with 30 days to expiration.
How to use:
If VIX Momentum is above 0 (RED) traders are getting nervous.
If VIX Momentum is below 0 (GREEN) traders are gaining confidence.
Follow to get updates and new scripts: www.tradingview.com
Open Interest Rank-BuschiEnglish:
One part of the "Commitment of Traders-Report" is the Open Interest which is shown in this indicator (source: Quandl database).
Unlike my also published indicator "Open Interest-Buschi", the values here are not absolute but in a ranking system from 0 to 100 with individual time frames-
The following futures are included:
30-year Bonds (ZB)
10-year Notes ( ZN )
Soybeans (ZS)
Soybean Meal (ZM)
Soybean Oil (ZL)
Corn ( ZC )
Soft Red Winter Wheat (ZW)
Hard Red Winter Wheat (KE)
Lean Hogs (HE)
Live Cattle ( LE )
Gold ( GC )
Silver (SI)
Copper (HG)
Crude Oil ( CL )
Heating Oil (HO)
RBOB Gasoline ( RB )
Natural Gas ( NG )
Australian Dollar (A6)
British Pound (B6)
Canadian Dollar (D6)
Euro (E6)
Japanese Yen (J6)
Swiss Franc (S6)
Sugar ( SB )
Coffee (KC)
Cocoa ( CC )
Cotton ( CT )
S&P 500 E-Mini (ES)
Russell 2000 E-Mini (RTY)
Dow Jones Industrial Mini (YM)
Nasdaq 100 E-Mini (NQ)
Platin (PL)
Palladium (PA)
Aluminium (AUP)
Steel ( HRC )
Ethanol (AEZ)
Brent Crude Oil (J26)
Rice (ZR)
Oat (ZO)
Milk (DL)
Orange Juice (JO)
Lumber (LS)
Feeder Cattle (GF)
S&P 500 ( SP )
Dow Jones Industrial Average Index (DJIA)
New Zealand Dollar (N6)
Deutsch:
Ein Bestandteil des "Commitment of Traders-Report" ist das Open Interest, das in diesem Indikator dargestellt wird (Quelle: Quandl Datenbank).
Anders als in meinem ebenfalls veröffentlichten Indikator "Open Interest-Buschi" werden hier nicht die absoluten Werte dargestellt, sondern in einem Ranking-System von 0 bis 100 mit individuellen Zeitrahmen.
Folgende Futures sind enthalten:
30-jährige US-Staatsanleihen (ZB)
10-jährige US-Staatsanleihen ( ZN )
Sojabohnen(ZS)
Sojabohnen-Mehl (ZM)
Sojabohnen-Öl (ZL)
Mais( ZC )
Soft Red Winter-Weizen (ZW)
Hard Red Winter-Weizen (KE)
Magerschweine (HE)
Lebendrinder ( LE )
Gold ( GC )
Silber (SI)
Kupfer(HG)
Rohöl ( CL )
Heizöl (HO)
Benzin ( RB )
Erdgas ( NG )
Australischer Dollar (A6)
Britisches Pfund (B6)
Kanadischer Dollar (D6)
Euro (E6)
Japanischer Yen (J6)
Schweizer Franken (S6)
Zucker ( SB )
Kaffee (KC)
Kakao ( CC )
Baumwolle ( CT )
S&P 500 E-Mini (ES)
Russell 2000 E-Mini (RTY)
Dow Jones Industrial Mini (YM)
Nasdaq 100 E-Mini (NQ)
Platin (PL)
Palladium (PA)
Aluminium (AUP)
Stahl ( HRC )
Ethanol (AEZ)
Brent Rohöl (J26)
Reis (ZR)
Hafer (ZO)
Milch (DL)
Orangensaft (JO)
Holz (LS)
Mastrinder (GF)
S&P 500 ( SP )
Dow Jones Industrial Average Index (DJIA)
Neuseeland Dollar (N6)
Open Interest-Buschi
English:
One part of the "Commitment of Traders-Report" is the Open Interest which is shown in this indicator (source: Quandl database).
The following futures are included:
30-year Bonds (ZB)
10-year Notes (ZN)
Soybeans (ZS)
Soybean Meal (ZM)
Soybean Oil (ZL)
Corn (ZC)
Soft Red Winter Wheat (ZW)
Hard Red Winter Wheat(KE)
Lean Hogs (HE)
Live Cattle (LE)
Gold (GC)
Silver (SI)
Copper (HG)
Crude Oil (CL)
Heating Oil (HO)
RBOB Gasoline (RB)
Natural Gas (NG)
Australian Dollar (A6)
British Pound (B6)
Canadian Dollar (D6)
Euro (E6)
Japanese Yen (J6)
Swiss Franc (S6)
Sugar (SB)
Coffee (KC)
Cocoa (CC)
Cotton (CT)
S&P 500 E-Mini (ES)
Russell 2000 E-Mini (RTY)
Dow Jones Industrial Mini (YM)
Nasdaq 100 E-Mini (NQ)
Platin (PL)
Palladium (PA)
Aluminium (AUP)
Steel (HRC)
Ethanol (AEZ)
Brent Crude Oil (J26)
Rice (ZR)
Oat (ZO)
Milk (DL)
Orange Juice (JO)
Lumber (LS)
Feeder Cattle (GF)
S&P 500 (SP)
Dow Jones Industrial Average Index (DJIA)
New Zealand Dollar (N6)
Deutsch:
Ein Bestandteil des "Commitment of Traders-Report" ist das Open Interest, das in diesem Indikator dargestellt wird (Quelle: Quandl Datenbank).
Folgende Futures sind enthalten:
30-jährige US-Staatsanleihen (ZB)
10-jährige US-Staatsanleihen (ZN)
Sojabohnen(ZS)
Sojabohnen-Mehl (ZM)
Sojabohnen-Öl (ZL)
Mais(ZC)
Soft Red Winter-Weizen (ZW)
Hard Red Winter-Weizen (KE)
Magerschweine (HE)
Lebendrinder (LE)
Gold (GC)
Silber (SI)
Kupfer(HG)
Rohöl (CL)
Heizöl (HO)
Benzin (RB)
Erdgas (NG)
Australischer Dollar (A6)
Britisches Pfund (B6)
Kanadischer Dollar (D6)
Euro (E6)
Japanischer Yen (J6)
Schweizer Franken (S6)
Zucker (SB)
Kaffee (KC)
Kakao (CC)
Baumwolle (CT)
S&P 500 E-Mini (ES)
Russell 2000 E-Mini (RTY)
Dow Jones Industrial Mini (YM)
Nasdaq 100 E-Mini (NQ)
Platin (PL)
Palladium (PA)
Aluminium (AUP)
Stahl (HRC)
Ethanol (AEZ)
Brent Rohöl (J26)
Reis (ZR)
Hafer (ZO)
Milch (DL)
Orangensaft (JO)
Holz (LS)
Mastrinder (GF)
S&P 500 (SP)
Dow Jones Industrial Average Index (DJIA)
Neuseeland Dollar (N6)
HSM KILLZONE//@version=5
indicator('HSM KILLZONE', 'HSM KILLZONE', overlay=true, max_bars_back=500, explicit_plot_zorder=true)
import boitoki/AwesomeColor/4 as ac
import boitoki/Utilities/3 as util
///////////////
// Groups
///////////////
g0 = 'GENERAL'
g1_01 = '♯1 SESSION'
g1_02 = '♯2 SESSION'
g1_03 = '♯3 SESSION'
g1_04 = '♯4 SESSION'
g4 = 'BOX'
g6 = 'LABELS'
g5 = 'OPENING RANGE'
g7 = 'FIBONACCI LEVELS'
g8 = 'OPTIONS'
g11 = 'CANDLE'
g10 = 'Alerts visualized'
///////////////
// Defined
///////////////
max_bars = 500
option_yes = 'Yes'
option_no = '× No'
option_extend1 = 'Yes'
option_hide = '× Hide'
option_border_style1 = '────'
option_border_style2 = '- - - - - -'
option_border_style3 = '•••••••••'
option_chart_x = '× No'
option_chart_1 = 'Bar color'
option_chart_2 = 'Candles'
fmt_price = '{0,number,#.#####}'
fmt_pips = '{0,number,#.#}'
icon_separator = ' • '
color_none = color.new(color.black, 100)
color_text = color.new(color.white, 0)
///////////////
// Functions
///////////////
f_get_time_by_bar(bar_count) => timeframe.multiplier * bar_count * 60 * 1000
f_border_style (_style) =>
switch _style
option_border_style1 => line.style_solid
option_border_style2 => line.style_dashed
option_border_style3 => line.style_dotted
=> _style
f_get_period (_session, _start, _lookback) =>
result = math.max(_start, 1)
for i = result to _lookback
if na(_session ) and _session
result := i+1
break
result
f_get_label_position (_y, _side) =>
switch _y
'top' => _side == 'outside' ? label.style_label_lower_left : label.style_label_upper_left
'bottom' => _side == 'outside' ? label.style_label_upper_left : label.style_label_lower_left
f_get_started (_session) => na(_session ) and _session
f_get_ended (_session) => na(_session) and _session
f_message_limit_bars (_v) => '⚠️ This box\'s right position exceeds 500 bars(' + str.tostring(_v) + '). This box is not displayed correctly.'
f_set_line_x1 (_line, _x) =>
if (line.get_x1(_line) != _x)
line.set_x1(_line, _x)
f_set_line_x2 (_line, _x) =>
if (line.get_x2(_line) != _x)
line.set_x2(_line, _x)
f_set_box_right (_box, _x) =>
if box.get_right(_box) != _x
box.set_right(_box, _x)
///////////////
// Inputs
///////////////
// Timezone
i_tz = input.string('GMT-4', title='Timezone', options= , tooltip='e.g. \'America/New_York\', \'Asia/Tokyo\', \'GMT-4\', \'GMT+9\'...', group=g0)
i_history_period = input.int(10, 'History', minval=0, group=g0)
i_show = i_history_period > 0
i_lookback = 12 * 60
// Sessions
i_show_sess1 = input.bool(true, 'Session 1 ', group=g1_01, inline='session1_1') and i_show
i_sess1_label = input.string('New York AM', '', group=g1_01, inline='session1_1')
i_sess1_color = input.color(#0a0a0a, '', group=g1_01, inline='session1_1')
i_sess1_barcolor1 = input.color(#0a0a0a, '•', group=g1_01, inline='session1_1')
i_sess1_barcolor2 = input.color(#0a0a0a, '', group=g1_01, inline='session1_1')
i_sess1 = input.session('0700-1100', 'Time', group=g1_01)
i_sess1_extend = input.string(option_no, 'Extend', options= , group=g1_01)
i_sess1_fib = input.string(option_no, 'Fibonacci levels', group=g1_01, options= ) != option_no
i_sess1_op = input.string(option_no, 'Opening range', group=g1_01, options= ) != option_no and i_show
i_sess1_chart = input.string(option_chart_x, 'Bar', options= , group=g1_01)
i_sess1_barcolor = i_sess1_chart == option_chart_1
i_sess1_plotcandle = i_sess1_chart == option_chart_2
i_show_sess2 = input.bool(true, 'Session 2 ', group=g1_02, inline='session2_1') and i_show
i_sess2_label = input.string('New York PM', '', group=g1_02, inline='session2_1')
i_sess2_color = input.color(#0a0a0a, '', group=g1_02, inline='session2_1')
i_sess2_barcolor1 = input.color(#0a0a0a, '•', group=g1_02, inline='session2_1')
i_sess2_barcolor2 = input.color(#0a0a0a, '', group=g1_02, inline='session2_1')
i_sess2 = input.session('1300-1600', 'Time', group=g1_02)
i_sess2_extend = input.string(option_no, 'Extend', options= , group=g1_02)
i_sess2_fib = input.string(option_no, 'Fibonacci levels', group=g1_02, options= ) != option_no
i_sess2_op = input.string(option_no, 'Opening range', group=g1_02, options= ) != option_no and i_show
i_sess2_chart = input.string(option_chart_x, 'Bar', options= , group=g1_02)
i_sess2_barcolor = i_sess2_chart == option_chart_1
i_sess2_plotcandle = i_sess2_chart == option_chart_2
i_show_sess3 = input.bool(true, 'Session 3 ', group=g1_03, inline='session3_1') and i_show
i_sess3_label = input.string('Asian Sesh', '', group=g1_03, inline='session3_1')
i_sess3_color = input.color(#0a0a0a, '', group=g1_03, inline='session3_1')
i_sess3_barcolor1 = input.color(#0a0a0a, '•', group=g1_03, inline='session3_1')
i_sess3_barcolor2 = input.color(#0a0a0a, '', group=g1_03, inline='session3_1')
i_sess3 = input.session('2000-0000', 'Time', group=g1_03)
i_sess3_extend = input.string(option_no, 'Extend', options= , group=g1_03)
i_sess3_fib = input.string(option_no, 'Fibonacci levels', group=g1_03, options= ) != option_no
i_sess3_op = input.string(option_no, 'Opening range', group=g1_03, options= ) != option_no and i_show
i_sess3_chart = input.string(option_chart_x, 'Bar', options= , group=g1_03)
i_sess3_barcolor = i_sess3_chart == option_chart_1
i_sess3_plotcandle = i_sess3_chart == option_chart_2
i_show_sess4 = input.bool(true, 'Session 4 ', group=g1_04, inline='session4_1') and i_show
i_sess4_label = input.string('London', '', group=g1_04, inline='session4_1')
i_sess4_color = input.color(#0a0a0a, '', group=g1_04, inline='session4_1')
i_sess4_barcolor1 = input.color(#0a0a0a, '•', group=g1_04, inline='session4_1')
i_sess4_barcolor2 = input.color(#0a0a0a, '', group=g1_04, inline='session4_1')
i_sess4 = input.session('0200-0500', 'Time', group=g1_04)
i_sess4_extend = input.string(option_no, 'Extend', options= , group=g1_04)
i_sess4_fib = input.string(option_no, 'Fibonacci levels', group=g1_04, options= ) != option_no
i_sess4_op = input.string(option_no, 'Opening range', group=g1_04, options= ) != option_no and i_show
i_sess4_chart = input.string(option_chart_x, 'Bar', options= , group=g1_04)
i_sess4_barcolor = i_sess4_chart == option_chart_1
i_sess4_plotcandle = i_sess4_chart == option_chart_2
// Show & Styles
i_sess_box_style = input.string('Box', 'Style', options= , group=g4)
i_sess_border_style = f_border_style(input.string(option_border_style2, 'Line style', options= , group=g4))
i_sess_border_width = input.int(1, 'Thickness', minval=0, group=g4)
i_sess_bgopacity = input.int(94, 'Transp', minval=0, maxval=100, step=1, group=g4, tooltip='Setting the 100 is no background color')
// Candle
option_candle_body = 'OC'
option_candle_wick = 'OHLC'
i_candle = input.string(option_hide, 'Display', options= , group=g11)
i_candle_border_width = input.int(2, 'Thickness', minval=0, group=g11)
i_show_candle = (i_candle != option_hide) and (i_candle_border_width > 0)
i_show_candle_wick = i_candle == option_candle_wick
option_candle_color1 = 'Session\'s'
option_candle_color2 = 'Red • Green'
i_candle_color = input.string(option_candle_color2, 'Color ', options= , group=g11, inline='candle_color')
i_candle_color_g = input.color(#A6E22E, '', group=g11, inline='candle_color')
i_candle_color_r = input.color(#F92672, '', group=g11, inline='candle_color')
// Labels
i_label_show = input.bool(true, 'Labels', inline='label_show', group=g6) and i_show
i_label_size = str.lower(input.string('Small', '', options= , inline='label_show', group=g6))
i_label_position_y = str.lower(input.string('Top', '', options= , inline='label_show', group=g6))
i_label_position_s = str.lower(input.string('Outside', '', options= , inline='label_show', group=g6))
i_label_position = f_get_label_position(i_label_position_y, i_label_position_s)
i_label_format_name = input.bool(true, 'Name', inline='label_format', group=g6)
i_label_format_day = input.bool(false, 'Day', inline='label_format', group=g6)
i_label_format_price = input.bool(false, 'Price', inline='label_format', group=g6)
i_label_format_pips = input.bool(false, 'Pips', inline='label_format', group=g6)
// Fibonacci levels
i_f_linestyle = f_border_style(input.string(option_border_style1, title="Style", options= , group=g7))
i_f_linewidth = input.int(1, title="Thickness", minval=1, group=g7)
// Opening range
i_o_minutes = input.int(15, title='Periods (minutes)', minval=1, step=1, group=g5)
i_o_minutes := math.max(i_o_minutes, timeframe.multiplier + 1)
i_o_transp = input.int(88, title='Transp', minval=0, maxval=100, step=1, group=g5)
// Alerts
i_alert1_show = input.bool(false, 'Alerts - Sessions stard/end', group=g10)
i_alert2_show = input.bool(false, 'Alerts - Opening range breakouts', group=g10)
i_alert3_show = input.bool(false, 'Alerts - Price crossed session\'s High/Low after session closed', group=g10)
// ------------------------
// Drawing labels
// ------------------------
f_render_label (_show, _session, _is_started, _color, _top, _bottom, _text, _labels) =>
var label my_label = na
var int start_time = na
v_position_y = (i_label_position_y == 'top') ? _top : _bottom
v_label = array.new_string()
v_chg = _top - _bottom
if _is_started
start_time := time
if i_label_format_name and not na(_text)
array.push(v_label, _text)
if i_label_format_day
array.push(v_label, util.get_day(dayofweek(start_time, i_tz)))
if i_label_format_price
array.push(v_label, str.format(fmt_price, v_chg))
if i_label_format_pips
array.push(v_label, str.format(fmt_pips, util.toPips(v_chg)) + ' pips')
if _show
if _is_started
my_label := label.new(bar_index, v_position_y, array.join(v_label, icon_separator), textcolor=_color, color=color_none, size=i_label_size, style=i_label_position)
array.push(_labels, my_label)
util.clear_labels(_labels, i_history_period)
else if _session
label.set_y(my_label, v_position_y)
label.set_text(my_label, array.join(v_label, icon_separator))
// ------------------------
// Drawing Fibonacci levels
// ------------------------
f_render_fibonacci (_show, _session, _is_started, _x1, _x2, _color, _top, _bottom, _level, _width, _style, _is_extend, _lines) =>
var line my_line = na
if _show
y = (_top - _bottom) * _level + _bottom
if _is_started
my_line := line.new(_x1, y, _x2, y, width=_width, color=color.new(_color, 30), style=_style)
array.push(_lines, my_line)
if _is_extend
line.set_extend(my_line, extend.right)
else if _session
line.set_y1(my_line, y)
line.set_y2(my_line, y)
f_set_line_x2(my_line, _x2)
// ------------------------
// Drawing Opening range
// ------------------------
f_render_oprange (_show, _session, _is_started, _x1, _x2, _color, _max, _is_extend, _boxes) =>
var int start_time = na
var box my_box = na
top = ta.highest(high, _max)
bottom = ta.lowest(low, _max)
is_crossover = ta.crossover(close, box.get_top(my_box))
is_crossunder = ta.crossunder(close, box.get_bottom(my_box))
if _show
if _is_started
util.clear_boxes(_boxes, math.max(0, i_history_period - 1))
start_time := time
my_box := na
else if _session
time_op = start_time + (i_o_minutes * 60 * 1000)
time_op_delay = time_op - f_get_time_by_bar(1)
if time <= time_op and time > time_op_delay
my_box := box.new(_x1, top, _x2, bottom, border_width=0, bgcolor=color.new(_color, i_o_transp))
array.push(_boxes, my_box)
if _is_extend
box.set_extend(my_box, extend.right)
my_box
else
f_set_box_right(my_box, _x2)
if is_crossover
alert('Price crossed over the opening range', alert.freq_once_per_bar)
if i_alert2_show
label.new(bar_index, box.get_top(my_box), "×", color=color.blue, textcolor=ac.tradingview('blue'), style=label.style_none, size=size.large)
if is_crossunder
alert('Price crossed under the opening range', alert.freq_once_per_bar)
if i_alert2_show
label.new(bar_index, box.get_bottom(my_box), "×", color=color.red, textcolor=ac.tradingview('red'), style=label.style_none, size=size.large)
my_box
// ------------------------
// Drawing candle
// ------------------------
f_render_candle (_show, _session, _is_started, _is_ended, _color, _top, _bottom, _open, _x1, _x2, _boxes, _lines) =>
var box body = na
var line wick1 = na
var line wick2 = na
border_width = i_candle_border_width
cx = math.round(math.avg(_x2, _x1)) - math.round(border_width / 2)
body_color = i_candle_color == option_candle_color2 ? close > _open ? i_candle_color_g : i_candle_color_r : _color
if _show
if _is_started
body := box.new(_x1, _top, _x2, _bottom, body_color, border_width, line.style_solid, bgcolor=color.new(color.black, 100))
wick1 := i_show_candle_wick ? line.new(cx, _top, cx, _top, color=_color, width=border_width, style=line.style_solid) : na
wick2 := i_show_candle_wick ? line.new(cx, _bottom, cx, _bottom, color=_color, width=border_width, style=line.style_solid) : na
array.push(_boxes, body)
array.push(_lines, wick1)
array.push(_lines, wick2)
util.clear_boxes(_boxes, i_history_period)
util.clear_lines(_lines, i_history_period * 2)
else if _session
top = math.max(_open, close)
bottom = math.min(_open, close)
box.set_top(body, top)
box.set_bottom(body, bottom)
box.set_right(body, _x2)
box.set_border_color(body, body_color)
line.set_y1(wick1, _top)
line.set_y2(wick1, top)
f_set_line_x1(wick1, cx)
f_set_line_x2(wick1, cx)
line.set_color(wick1, body_color)
line.set_y1(wick2, _bottom)
line.set_y2(wick2, bottom)
f_set_line_x1(wick2, cx)
f_set_line_x2(wick2, cx)
line.set_color(wick2, body_color)
else if _is_ended
box.set_right(body, bar_index)
// ------------------------
// Rendering limit message
// ------------------------
f_render_limitmessage (_show, _session, _is_started, _is_ended, _x, _y, _rightbars) =>
var label my_note = na
if _show
if _is_started
if _rightbars > max_bars
my_note := label.new(_x, _y, f_message_limit_bars(_rightbars), style=label.style_label_upper_left, color=color.yellow, textalign=text.align_left, yloc=yloc.price)
else if _session
if _rightbars > max_bars
label.set_y(my_note, _y)
label.set_text(my_note, f_message_limit_bars(_rightbars))
else
label.delete(my_note)
else if _is_ended
label.delete(my_note)
true
// Rendering session
//
f_render_sessionrange (_show, _session, _is_started, _is_ended, _color, _top, _bottom, _x1, _x2, _is_extend, _lines) =>
var line above_line = na
var line below_line = na
if _show
if _is_started
above_line := line.new(_x1, _top, _x2, _top, width=i_sess_border_width, style=i_sess_border_style, color=_color)
below_line := line.new(_x1, _bottom, _x2, _bottom, width=i_sess_border_width, style=i_sess_border_style, color=_color)
linefill.new(above_line, below_line, color.new(_color, i_sess_bgopacity))
array.push(_lines, above_line)
array.push(_lines, below_line)
util.clear_lines(_lines, i_history_period * 2)
if _is_extend
line.set_extend(above_line, extend.right)
line.set_extend(below_line, extend.right)
else if _session
line.set_y1(above_line, _top)
line.set_y2(above_line, _top)
line.set_x2(above_line, _x2)
line.set_y1(below_line, _bottom)
line.set_y2(below_line, _bottom)
line.set_x2(below_line, _x2)
true
else if _is_ended
true
true
// ------------------------
// Rendering session box
// ------------------------
f_render_session (_show, _session, _is_started, _is_ended, _color, _top, _bottom, _x1, _x2, _is_extend, _boxes) =>
var box my_box = na
if _show
if _is_started
my_box := box.new(_x1, _top, _x2, _bottom, _color, i_sess_border_width, i_sess_border_style, bgcolor=color.new(_color, i_sess_bgopacity))
array.push(_boxes, my_box)
util.clear_boxes(_boxes, i_history_period)
if _is_extend
box.set_extend(my_box, extend.right)
else if _session
box.set_top(my_box, _top)
box.set_bottom(my_box, _bottom)
f_set_box_right(my_box, _x2)
else if _is_ended
box.set_right(my_box, bar_index)
my_box
// ------------------------
// Drawing market
// ------------------------
f_render_main (_show, _session, _is_started, _is_ended, _color, _top, _bottom) =>
var box my_box = na
var label my_note = na
var x1 = 0
var x2 = 0
var session_open = 0.0
var session_high = 0.0
var session_low = 0.0
x0_1 = ta.valuewhen(na(_session ) and _session, bar_index, 1)
x0_2 = ta.valuewhen(na(_session) and _session , bar_index, 0)
x0_d = math.abs(x0_2 - x0_1)
limit_bars = max_bars
rightbars = x0_d
if _show
if _is_started
x1 := bar_index
x2 := bar_index + (math.min(x0_d, limit_bars))
session_open := open
session_high := _top
session_low := _bottom
else if _session
true_x2 = x1 + x0_d
rightbars := true_x2 - bar_index
limit_bars := bar_index + max_bars
x2 := math.min(true_x2, limit_bars)
session_high := _top
session_low := _bottom
else if _is_ended
session_open := na
// ------------------------
// Drawing
// ------------------------
draw (_show, _session, _color, _label, _extend, _show_fib, _show_op, _lookback, _boxes_session, _lines_session, _boxes_candle_body, _lines_candle_wick, _boxes_op, _lines_fib, _labels) =>
max = f_get_period(_session, 1, _lookback)
top = ta.highest(high, max)
bottom = ta.lowest(low, max)
is_started = f_get_started(_session)
is_ended = f_get_ended(_session)
is_extend = _extend != option_no
= f_render_main(_show, _session, is_started, is_ended, _color, top, bottom)
if i_sess_box_style == 'Box'
f_render_session(_show, _session, is_started, is_ended, _color, top, bottom, x1, x2, is_extend, _boxes_session)
if i_sess_box_style == 'Sandwich'
f_render_sessionrange(_show, _session, is_started, is_ended, _color, top, bottom, x1, x2, is_extend, _lines_session)
if i_show_candle
f_render_candle(_show, _session, is_started, is_ended, _color, top, bottom, _open, x1, x2, _boxes_candle_body, _lines_candle_wick)
if i_label_show
f_render_label(_show, _session, is_started, _color, top, bottom, _label, _labels)
if _show_op
f_render_oprange(_show, _session, is_started, x1, x2, _color, max, is_extend, _boxes_op)
if _show_fib
f_render_fibonacci(_show, _session, is_started, x1, x2, _color, top, bottom, 0.500, 2, line.style_solid, is_extend, _lines_fib)
f_render_fibonacci(_show, _session, is_started, x1, x2, _color, top, bottom, 0.628, i_f_linewidth, i_f_linestyle, is_extend, _lines_fib)
f_render_fibonacci(_show, _session, is_started, x1, x2, _color, top, bottom, 0.382, i_f_linewidth, i_f_linestyle, is_extend, _lines_fib)
util.clear_lines(_lines_fib, i_history_period * 3)
f_render_limitmessage(_show, _session, is_started, is_ended, x1, bottom, _rightbars)
///////////////////
// Calculating
///////////////////
string tz = (i_tz == option_no or i_tz == '') ? na : i_tz
int sess1 = time(timeframe.period, i_sess1, tz)
int sess2 = time(timeframe.period, i_sess2, tz)
int sess3 = time(timeframe.period, i_sess3, tz)
int sess4 = time(timeframe.period, i_sess4, tz)
///////////////////
// Plotting
///////////////////
var sess1_box = array.new()
var sess2_box = array.new()
var sess3_box = array.new()
var sess4_box = array.new()
var sess1_line = array.new()
var sess2_line = array.new()
var sess3_line = array.new()
var sess4_line = array.new()
var sess1_op = array.new()
var sess2_op = array.new()
var sess3_op = array.new()
var sess4_op = array.new()
var sess1_fib = array.new()
var sess2_fib = array.new()
var sess3_fib = array.new()
var sess4_fib = array.new()
var sess1_candle_body = array.new()
var sess2_candle_body = array.new()
var sess3_candle_body = array.new()
var sess4_candle_body = array.new()
var sess1_candle_wick = array.new()
var sess2_candle_wick = array.new()
var sess3_candle_wick = array.new()
var sess4_candle_wick = array.new()
var sess1_labels = array.new()
var sess2_labels = array.new()
var sess3_labels = array.new()
var sess4_labels = array.new()
= draw(i_show_sess1, sess1, i_sess1_color, i_sess1_label, i_sess1_extend, i_sess1_fib, i_sess1_op, i_lookback, sess1_box, sess1_line, sess1_candle_body, sess1_candle_wick, sess1_op, sess1_fib, sess1_labels)
= draw(i_show_sess2, sess2, i_sess2_color, i_sess2_label, i_sess2_extend, i_sess2_fib, i_sess2_op, i_lookback, sess2_box, sess2_line, sess2_candle_body, sess2_candle_wick, sess2_op, sess2_fib, sess2_labels)
= draw(i_show_sess3, sess3, i_sess3_color, i_sess3_label, i_sess3_extend, i_sess3_fib, i_sess3_op, i_lookback, sess3_box, sess3_line, sess3_candle_body, sess3_candle_wick, sess3_op, sess3_fib, sess3_labels)
= draw(i_show_sess4, sess4, i_sess4_color, i_sess4_label, i_sess4_extend, i_sess4_fib, i_sess4_op, i_lookback, sess4_box, sess4_line, sess4_candle_body, sess4_candle_wick, sess4_op, sess4_fib, sess4_labels)
is_positive_bar = close > open
color c_barcolor = na
color c_plotcandle = na
c_sess1_barcolor = (is_sess1) ? (is_positive_bar ? i_sess1_barcolor1 : i_sess1_barcolor2) : na
c_sess2_barcolor = (is_sess2) ? (is_positive_bar ? i_sess2_barcolor1 : i_sess2_barcolor2) : na
c_sess3_barcolor = (is_sess3) ? (is_positive_bar ? i_sess3_barcolor1 : i_sess3_barcolor2) : na
c_sess4_barcolor = (is_sess4) ? (is_positive_bar ? i_sess4_barcolor1 : i_sess4_barcolor2) : na
if (i_sess1_chart != option_chart_x) and is_sess1
c_barcolor := i_sess1_barcolor ? c_sess1_barcolor : na
c_plotcandle := i_sess1_plotcandle ? c_sess1_barcolor : na
if (i_sess2_chart != option_chart_x) and is_sess2
c_barcolor := i_sess2_barcolor ? c_sess2_barcolor : na
c_plotcandle := i_sess2_plotcandle ? c_sess2_barcolor : na
if (i_sess3_chart != option_chart_x) and is_sess3
c_barcolor := i_sess3_barcolor ? c_sess3_barcolor : na
c_plotcandle := i_sess3_plotcandle ? c_sess3_barcolor : na
if (i_sess4_chart != option_chart_x) and is_sess4
c_barcolor := i_sess4_barcolor ? c_sess4_barcolor : na
c_plotcandle := i_sess4_plotcandle ? c_sess4_barcolor : na
barcolor(c_barcolor)
plotcandle(open, high, low, close, color=is_positive_bar ? color_none : c_plotcandle, bordercolor=c_plotcandle, wickcolor=c_plotcandle)
////////////////////
// Alerts
////////////////////
// Session alerts
sess1_started = is_sess1 and not is_sess1 , sess1_ended = not is_sess1 and is_sess1
sess2_started = is_sess2 and not is_sess2 , sess2_ended = not is_sess2 and is_sess2
sess3_started = is_sess3 and not is_sess3 , sess3_ended = not is_sess3 and is_sess3
sess4_started = is_sess4 and not is_sess4 , sess4_ended = not is_sess4 and is_sess4
alertcondition(sess1_started, 'Session #1 started')
alertcondition(sess1_ended, 'Session #1 ended')
alertcondition(sess2_started, 'Session #2 started')
alertcondition(sess2_ended, 'Session #2 ended')
alertcondition(sess3_started, 'Session #3 started')
alertcondition(sess3_ended, 'Session #3 ended')
alertcondition(sess4_started, 'Session #4 started')
alertcondition(sess4_ended, 'Session #4 ended')
alertcondition((not is_sess1) and ta.crossover(close, sess1_high), 'Session #1 High crossed (after session closed)')
alertcondition((not is_sess1) and ta.crossunder(close, sess1_low), 'Session #1 Low crossed (after session closed)')
alertcondition((not is_sess2) and ta.crossover(close, sess2_high), 'Session #2 High crossed (after session closed)')
alertcondition((not is_sess2) and ta.crossunder(close, sess2_low), 'Session #2 Low crossed (after session closed)')
alertcondition((not is_sess3) and ta.crossover(close, sess3_high), 'Session #3 High crossed (after session closed)')
alertcondition((not is_sess3) and ta.crossunder(close, sess3_low), 'Session #3 Low crossed (after session closed)')
alertcondition((not is_sess4) and ta.crossover(close, sess4_high), 'Session #4 High crossed (after session closed)')
alertcondition((not is_sess4) and ta.crossunder(close, sess4_low), 'Session #4 Low crossed (after session closed)')
// Alerts visualized
if i_alert1_show
if i_show_sess1
if sess1_started
label.new(bar_index, close, 'Start', yloc=yloc.abovebar, color=i_sess1_color, textcolor=color_text, size=size.small, style=label.style_label_down)
if sess1_ended
label.new(bar_index, close, 'End' , yloc=yloc.abovebar, color=i_sess1_color, textcolor=color_text, size=size.small, style=label.style_label_down)
if i_show_sess2
if sess2_started
label.new(bar_index, close, 'Start', yloc=yloc.abovebar, color=i_sess2_color, textcolor=color_text, size=size.small, style=label.style_label_down)
if sess2_ended
label.new(bar_index, close, 'End' , yloc=yloc.abovebar, color=i_sess2_color, textcolor=color_text, size=size.small, style=label.style_label_down)
if i_show_sess3
if sess3_started
label.new(bar_index, close, 'Start', yloc=yloc.abovebar, color=i_sess3_color, textcolor=color_text, size=size.small, style=label.style_label_down)
if sess3_ended
label.new(bar_index, close, 'End' , yloc=yloc.abovebar, color=i_sess3_color, textcolor=color_text, size=size.small, style=label.style_label_down)
if i_show_sess4
if sess4_started
label.new(bar_index, close, 'Start', yloc=yloc.abovebar, color=i_sess4_color, textcolor=color_text, size=size.small, style=label.style_label_down)
if sess4_ended
label.new(bar_index, close, 'End' , yloc=yloc.abovebar, color=i_sess4_color, textcolor=color_text, size=size.small, style=label.style_label_down)
plot(i_alert3_show ? sess1_high : na, 'sess1_high', style=plot.style_linebr, color=i_sess1_color)
plot(i_alert3_show ? sess1_low : na, 'sess1_low' , style=plot.style_linebr, color=i_sess1_color, linewidth=2)
plot(i_alert3_show ? sess2_high : na, 'sess2_high', style=plot.style_linebr, color=i_sess2_color)
plot(i_alert3_show ? sess2_low : na, 'sess2_low' , style=plot.style_linebr, color=i_sess2_color, linewidth=2)
plot(i_alert3_show ? sess3_high : na, 'sess3_high', style=plot.style_linebr, color=i_sess3_color)
plot(i_alert3_show ? sess3_low : na, 'sess3_low' , style=plot.style_linebr, color=i_sess3_color, linewidth=2)
plot(i_alert3_show ? sess4_high : na, 'sess4_high', style=plot.style_linebr, color=i_sess4_color)
plot(i_alert3_show ? sess4_low : na, 'sess4_low' , style=plot.style_linebr, color=i_sess4_color, linewidth=2)
plotshape(i_alert3_show and (not is_sess1) and ta.crossover(close, sess1_high) ? sess1_high : na, 'cross sess1_high', color=i_sess1_color, style=shape.triangleup, location=location.absolute, size=size.tiny)
plotshape(i_alert3_show and (not is_sess1) and ta.crossunder(close, sess1_low) ? sess1_low : na, 'cross sess1_low', color=i_sess1_color, style=shape.triangledown, location=location.absolute, size=size.tiny)
plotshape(i_alert3_show and (not is_sess2) and ta.crossover(close, sess2_high) ? sess2_high : na, 'cross sess2_high', color=i_sess2_color, style=shape.triangleup, location=location.absolute, size=size.tiny)
plotshape(i_alert3_show and (not is_sess2) and ta.crossunder(close, sess2_low) ? sess2_low : na, 'cross sess2_low', color=i_sess2_color, style=shape.triangledown, location=location.absolute, size=size.tiny)
plotshape(i_alert3_show and (not is_sess3) and ta.crossover(close, sess3_high) ? sess3_high : na, 'cross sess3_high', color=i_sess3_color, style=shape.triangleup, location=location.absolute, size=size.tiny)
plotshape(i_alert3_show and (not is_sess3) and ta.crossunder(close, sess3_low) ? sess3_low : na, 'cross sess3_low', color=i_sess3_color, style=shape.triangledown, location=location.absolute, size=size.tiny)
plotshape(i_alert3_show and (not is_sess4) and ta.crossover(close, sess4_high) ? sess4_high : na, 'cross sess4_high', color=i_sess4_color, style=shape.triangleup, location=location.absolute, size=size.tiny)
plotshape(i_alert3_show and (not is_sess4) and ta.crossunder(close, sess4_low) ? sess4_low : na, 'cross sess4_low', color=i_sess4_color, style=shape.triangledown, location=location.absolute, size=size.tiny)
HSM MACROS//@version=5
indicator('HSM MACROS', 'HSM MACROS', overlay=true, max_bars_back=500, explicit_plot_zorder=true)
import boitoki/AwesomeColor/4 as ac
import boitoki/Utilities/3 as util
///////////////
// Groups
///////////////
g0 = 'GENERAL'
g1_01 = '♯1 SESSION'
g1_02 = '♯2 SESSION'
g1_03 = '♯3 SESSION'
g1_04 = '♯4 SESSION'
g4 = 'BOX'
g6 = 'LABELS'
g5 = 'OPENING RANGE'
g7 = 'FIBONACCI LEVELS'
g8 = 'OPTIONS'
g11 = 'CANDLE'
g10 = 'Alerts visualized'
///////////////
// Defined
///////////////
max_bars = 500
option_yes = 'Yes'
option_no = '× No'
option_extend1 = 'Yes'
option_hide = '× Hide'
option_border_style1 = '────'
option_border_style2 = '- - - - - -'
option_border_style3 = '•••••••••'
option_chart_x = '× No'
option_chart_1 = 'Bar color'
option_chart_2 = 'Candles'
fmt_price = '{0,number,#.#####}'
fmt_pips = '{0,number,#.#}'
icon_separator = ' • '
color_none = color.new(color.black, 100)
color_text = color.new(color.white, 0)
///////////////
// Functions
///////////////
f_get_time_by_bar(bar_count) => timeframe.multiplier * bar_count * 60 * 1000
f_border_style (_style) =>
switch _style
option_border_style1 => line.style_solid
option_border_style2 => line.style_dashed
option_border_style3 => line.style_dotted
=> _style
f_get_period (_session, _start, _lookback) =>
result = math.max(_start, 1)
for i = result to _lookback
if na(_session ) and _session
result := i+1
break
result
f_get_label_position (_y, _side) =>
switch _y
'top' => _side == 'outside' ? label.style_label_lower_left : label.style_label_upper_left
'bottom' => _side == 'outside' ? label.style_label_upper_left : label.style_label_lower_left
f_get_started (_session) => na(_session ) and _session
f_get_ended (_session) => na(_session) and _session
f_message_limit_bars (_v) => '⚠️ This box\'s right position exceeds 500 bars(' + str.tostring(_v) + '). This box is not displayed correctly.'
f_set_line_x1 (_line, _x) =>
if (line.get_x1(_line) != _x)
line.set_x1(_line, _x)
f_set_line_x2 (_line, _x) =>
if (line.get_x2(_line) != _x)
line.set_x2(_line, _x)
f_set_box_right (_box, _x) =>
if box.get_right(_box) != _x
box.set_right(_box, _x)
///////////////
// Inputs
///////////////
// Timezone
i_tz = input.string('GMT-4', title='Timezone', options= , tooltip='e.g. \'America/New_York\', \'Asia/Tokyo\', \'GMT-4\', \'GMT+9\'...', group=g0)
i_history_period = input.int(10, 'History', minval=0, group=g0)
i_show = i_history_period > 0
i_lookback = 12 * 60
// Sessions
i_show_sess1 = input.bool(true, 'Session 1 ', group=g1_01, inline='session1_1') and i_show
i_sess1_label = input.string('MC1', '', group=g1_01, inline='session1_1')
i_sess1_color = input.color(#0a0a0a, '', group=g1_01, inline='session1_1')
i_sess1_barcolor1 = input.color(#0a0a0a, '•', group=g1_01, inline='session1_1')
i_sess1_barcolor2 = input.color(#0a0a0a, '', group=g1_01, inline='session1_1')
i_sess1 = input.session('0820-0830', 'Time', group=g1_01)
i_sess1_extend = input.string(option_no, 'Extend', options= , group=g1_01)
i_sess1_fib = input.string(option_no, 'Fibonacci levels', group=g1_01, options= ) != option_no
i_sess1_op = input.string(option_no, 'Opening range', group=g1_01, options= ) != option_no and i_show
i_sess1_chart = input.string(option_chart_x, 'Bar', options= , group=g1_01)
i_sess1_barcolor = i_sess1_chart == option_chart_1
i_sess1_plotcandle = i_sess1_chart == option_chart_2
i_show_sess2 = input.bool(true, 'Session 2 ', group=g1_02, inline='session2_1') and i_show
i_sess2_label = input.string('MC2', '', group=g1_02, inline='session2_1')
i_sess2_color = input.color(#0a0a0a, '', group=g1_02, inline='session2_1')
i_sess2_barcolor1 = input.color(#0a0a0a, '•', group=g1_02, inline='session2_1')
i_sess2_barcolor2 = input.color(#0a0a0a, '', group=g1_02, inline='session2_1')
i_sess2 = input.session('0920-0930', 'Time', group=g1_02)
i_sess2_extend = input.string(option_no, 'Extend', options= , group=g1_02)
i_sess2_fib = input.string(option_no, 'Fibonacci levels', group=g1_02, options= ) != option_no
i_sess2_op = input.string(option_no, 'Opening range', group=g1_02, options= ) != option_no and i_show
i_sess2_chart = input.string(option_chart_x, 'Bar', options= , group=g1_02)
i_sess2_barcolor = i_sess2_chart == option_chart_1
i_sess2_plotcandle = i_sess2_chart == option_chart_2
i_show_sess3 = input.bool(true, 'Session 3 ', group=g1_03, inline='session3_1') and i_show
i_sess3_label = input.string('MC3', '', group=g1_03, inline='session3_1')
i_sess3_color = input.color(#0a0a0a, '', group=g1_03, inline='session3_1')
i_sess3_barcolor1 = input.color(#0a0a0a, '•', group=g1_03, inline='session3_1')
i_sess3_barcolor2 = input.color(#0a0a0a, '', group=g1_03, inline='session3_1')
i_sess3 = input.session('0950-1010', 'Time', group=g1_03)
i_sess3_extend = input.string(option_no, 'Extend', options= , group=g1_03)
i_sess3_fib = input.string(option_no, 'Fibonacci levels', group=g1_03, options= ) != option_no
i_sess3_op = input.string(option_no, 'Opening range', group=g1_03, options= ) != option_no and i_show
i_sess3_chart = input.string(option_chart_x, 'Bar', options= , group=g1_03)
i_sess3_barcolor = i_sess3_chart == option_chart_1
i_sess3_plotcandle = i_sess3_chart == option_chart_2
i_show_sess4 = input.bool(true, 'Session 4 ', group=g1_04, inline='session4_1') and i_show
i_sess4_label = input.string('MC4', '', group=g1_04, inline='session4_1')
i_sess4_color = input.color(#0a0a0a, '', group=g1_04, inline='session4_1')
i_sess4_barcolor1 = input.color(#0a0a0a, '•', group=g1_04, inline='session4_1')
i_sess4_barcolor2 = input.color(#0a0a0a, '', group=g1_04, inline='session4_1')
i_sess4 = input.session('1050-1110', 'Time', group=g1_04)
i_sess4_extend = input.string(option_no, 'Extend', options= , group=g1_04)
i_sess4_fib = input.string(option_no, 'Fibonacci levels', group=g1_04, options= ) != option_no
i_sess4_op = input.string(option_no, 'Opening range', group=g1_04, options= ) != option_no and i_show
i_sess4_chart = input.string(option_chart_x, 'Bar', options= , group=g1_04)
i_sess4_barcolor = i_sess4_chart == option_chart_1
i_sess4_plotcandle = i_sess4_chart == option_chart_2
// Show & Styles
i_sess_box_style = input.string('Box', 'Style', options= , group=g4)
i_sess_border_style = f_border_style(input.string(option_border_style2, 'Line style', options= , group=g4))
i_sess_border_width = input.int(1, 'Thickness', minval=0, group=g4)
i_sess_bgopacity = input.int(94, 'Transp', minval=0, maxval=100, step=1, group=g4, tooltip='Setting the 100 is no background color')
// Candle
option_candle_body = 'OC'
option_candle_wick = 'OHLC'
i_candle = input.string(option_hide, 'Display', options= , group=g11)
i_candle_border_width = input.int(2, 'Thickness', minval=0, group=g11)
i_show_candle = (i_candle != option_hide) and (i_candle_border_width > 0)
i_show_candle_wick = i_candle == option_candle_wick
option_candle_color1 = 'Session\'s'
option_candle_color2 = 'Red • Green'
i_candle_color = input.string(option_candle_color2, 'Color ', options= , group=g11, inline='candle_color')
i_candle_color_g = input.color(#A6E22E, '', group=g11, inline='candle_color')
i_candle_color_r = input.color(#F92672, '', group=g11, inline='candle_color')
// Labels
i_label_show = input.bool(true, 'Labels', inline='label_show', group=g6) and i_show
i_label_size = str.lower(input.string('Small', '', options= , inline='label_show', group=g6))
i_label_position_y = str.lower(input.string('Top', '', options= , inline='label_show', group=g6))
i_label_position_s = str.lower(input.string('Outside', '', options= , inline='label_show', group=g6))
i_label_position = f_get_label_position(i_label_position_y, i_label_position_s)
i_label_format_name = input.bool(true, 'Name', inline='label_format', group=g6)
i_label_format_day = input.bool(false, 'Day', inline='label_format', group=g6)
i_label_format_price = input.bool(false, 'Price', inline='label_format', group=g6)
i_label_format_pips = input.bool(false, 'Pips', inline='label_format', group=g6)
// Fibonacci levels
i_f_linestyle = f_border_style(input.string(option_border_style1, title="Style", options= , group=g7))
i_f_linewidth = input.int(1, title="Thickness", minval=1, group=g7)
// Opening range
i_o_minutes = input.int(15, title='Periods (minutes)', minval=1, step=1, group=g5)
i_o_minutes := math.max(i_o_minutes, timeframe.multiplier + 1)
i_o_transp = input.int(88, title='Transp', minval=0, maxval=100, step=1, group=g5)
// Alerts
i_alert1_show = input.bool(false, 'Alerts - Sessions stard/end', group=g10)
i_alert2_show = input.bool(false, 'Alerts - Opening range breakouts', group=g10)
i_alert3_show = input.bool(false, 'Alerts - Price crossed session\'s High/Low after session closed', group=g10)
// ------------------------
// Drawing labels
// ------------------------
f_render_label (_show, _session, _is_started, _color, _top, _bottom, _text, _labels) =>
var label my_label = na
var int start_time = na
v_position_y = (i_label_position_y == 'top') ? _top : _bottom
v_label = array.new_string()
v_chg = _top - _bottom
if _is_started
start_time := time
if i_label_format_name and not na(_text)
array.push(v_label, _text)
if i_label_format_day
array.push(v_label, util.get_day(dayofweek(start_time, i_tz)))
if i_label_format_price
array.push(v_label, str.format(fmt_price, v_chg))
if i_label_format_pips
array.push(v_label, str.format(fmt_pips, util.toPips(v_chg)) + ' pips')
if _show
if _is_started
my_label := label.new(bar_index, v_position_y, array.join(v_label, icon_separator), textcolor=_color, color=color_none, size=i_label_size, style=i_label_position)
array.push(_labels, my_label)
util.clear_labels(_labels, i_history_period)
else if _session
label.set_y(my_label, v_position_y)
label.set_text(my_label, array.join(v_label, icon_separator))
// ------------------------
// Drawing Fibonacci levels
// ------------------------
f_render_fibonacci (_show, _session, _is_started, _x1, _x2, _color, _top, _bottom, _level, _width, _style, _is_extend, _lines) =>
var line my_line = na
if _show
y = (_top - _bottom) * _level + _bottom
if _is_started
my_line := line.new(_x1, y, _x2, y, width=_width, color=color.new(_color, 30), style=_style)
array.push(_lines, my_line)
if _is_extend
line.set_extend(my_line, extend.right)
else if _session
line.set_y1(my_line, y)
line.set_y2(my_line, y)
f_set_line_x2(my_line, _x2)
// ------------------------
// Drawing Opening range
// ------------------------
f_render_oprange (_show, _session, _is_started, _x1, _x2, _color, _max, _is_extend, _boxes) =>
var int start_time = na
var box my_box = na
top = ta.highest(high, _max)
bottom = ta.lowest(low, _max)
is_crossover = ta.crossover(close, box.get_top(my_box))
is_crossunder = ta.crossunder(close, box.get_bottom(my_box))
if _show
if _is_started
util.clear_boxes(_boxes, math.max(0, i_history_period - 1))
start_time := time
my_box := na
else if _session
time_op = start_time + (i_o_minutes * 60 * 1000)
time_op_delay = time_op - f_get_time_by_bar(1)
if time <= time_op and time > time_op_delay
my_box := box.new(_x1, top, _x2, bottom, border_width=0, bgcolor=color.new(_color, i_o_transp))
array.push(_boxes, my_box)
if _is_extend
box.set_extend(my_box, extend.right)
my_box
else
f_set_box_right(my_box, _x2)
if is_crossover
alert('Price crossed over the opening range', alert.freq_once_per_bar)
if i_alert2_show
label.new(bar_index, box.get_top(my_box), "×", color=color.blue, textcolor=ac.tradingview('blue'), style=label.style_none, size=size.large)
if is_crossunder
alert('Price crossed under the opening range', alert.freq_once_per_bar)
if i_alert2_show
label.new(bar_index, box.get_bottom(my_box), "×", color=color.red, textcolor=ac.tradingview('red'), style=label.style_none, size=size.large)
my_box
// ------------------------
// Drawing candle
// ------------------------
f_render_candle (_show, _session, _is_started, _is_ended, _color, _top, _bottom, _open, _x1, _x2, _boxes, _lines) =>
var box body = na
var line wick1 = na
var line wick2 = na
border_width = i_candle_border_width
cx = math.round(math.avg(_x2, _x1)) - math.round(border_width / 2)
body_color = i_candle_color == option_candle_color2 ? close > _open ? i_candle_color_g : i_candle_color_r : _color
if _show
if _is_started
body := box.new(_x1, _top, _x2, _bottom, body_color, border_width, line.style_solid, bgcolor=color.new(color.black, 100))
wick1 := i_show_candle_wick ? line.new(cx, _top, cx, _top, color=_color, width=border_width, style=line.style_solid) : na
wick2 := i_show_candle_wick ? line.new(cx, _bottom, cx, _bottom, color=_color, width=border_width, style=line.style_solid) : na
array.push(_boxes, body)
array.push(_lines, wick1)
array.push(_lines, wick2)
util.clear_boxes(_boxes, i_history_period)
util.clear_lines(_lines, i_history_period * 2)
else if _session
top = math.max(_open, close)
bottom = math.min(_open, close)
box.set_top(body, top)
box.set_bottom(body, bottom)
box.set_right(body, _x2)
box.set_border_color(body, body_color)
line.set_y1(wick1, _top)
line.set_y2(wick1, top)
f_set_line_x1(wick1, cx)
f_set_line_x2(wick1, cx)
line.set_color(wick1, body_color)
line.set_y1(wick2, _bottom)
line.set_y2(wick2, bottom)
f_set_line_x1(wick2, cx)
f_set_line_x2(wick2, cx)
line.set_color(wick2, body_color)
else if _is_ended
box.set_right(body, bar_index)
// ------------------------
// Rendering limit message
// ------------------------
f_render_limitmessage (_show, _session, _is_started, _is_ended, _x, _y, _rightbars) =>
var label my_note = na
if _show
if _is_started
if _rightbars > max_bars
my_note := label.new(_x, _y, f_message_limit_bars(_rightbars), style=label.style_label_upper_left, color=color.yellow, textalign=text.align_left, yloc=yloc.price)
else if _session
if _rightbars > max_bars
label.set_y(my_note, _y)
label.set_text(my_note, f_message_limit_bars(_rightbars))
else
label.delete(my_note)
else if _is_ended
label.delete(my_note)
true
// Rendering session
//
f_render_sessionrange (_show, _session, _is_started, _is_ended, _color, _top, _bottom, _x1, _x2, _is_extend, _lines) =>
var line above_line = na
var line below_line = na
if _show
if _is_started
above_line := line.new(_x1, _top, _x2, _top, width=i_sess_border_width, style=i_sess_border_style, color=_color)
below_line := line.new(_x1, _bottom, _x2, _bottom, width=i_sess_border_width, style=i_sess_border_style, color=_color)
linefill.new(above_line, below_line, color.new(_color, i_sess_bgopacity))
array.push(_lines, above_line)
array.push(_lines, below_line)
util.clear_lines(_lines, i_history_period * 2)
if _is_extend
line.set_extend(above_line, extend.right)
line.set_extend(below_line, extend.right)
else if _session
line.set_y1(above_line, _top)
line.set_y2(above_line, _top)
line.set_x2(above_line, _x2)
line.set_y1(below_line, _bottom)
line.set_y2(below_line, _bottom)
line.set_x2(below_line, _x2)
true
else if _is_ended
true
true
// ------------------------
// Rendering session box
// ------------------------
f_render_session (_show, _session, _is_started, _is_ended, _color, _top, _bottom, _x1, _x2, _is_extend, _boxes) =>
var box my_box = na
if _show
if _is_started
my_box := box.new(_x1, _top, _x2, _bottom, _color, i_sess_border_width, i_sess_border_style, bgcolor=color.new(_color, i_sess_bgopacity))
array.push(_boxes, my_box)
util.clear_boxes(_boxes, i_history_period)
if _is_extend
box.set_extend(my_box, extend.right)
else if _session
box.set_top(my_box, _top)
box.set_bottom(my_box, _bottom)
f_set_box_right(my_box, _x2)
else if _is_ended
box.set_right(my_box, bar_index)
my_box
// ------------------------
// Drawing market
// ------------------------
f_render_main (_show, _session, _is_started, _is_ended, _color, _top, _bottom) =>
var box my_box = na
var label my_note = na
var x1 = 0
var x2 = 0
var session_open = 0.0
var session_high = 0.0
var session_low = 0.0
x0_1 = ta.valuewhen(na(_session ) and _session, bar_index, 1)
x0_2 = ta.valuewhen(na(_session) and _session , bar_index, 0)
x0_d = math.abs(x0_2 - x0_1)
limit_bars = max_bars
rightbars = x0_d
if _show
if _is_started
x1 := bar_index
x2 := bar_index + (math.min(x0_d, limit_bars))
session_open := open
session_high := _top
session_low := _bottom
else if _session
true_x2 = x1 + x0_d
rightbars := true_x2 - bar_index
limit_bars := bar_index + max_bars
x2 := math.min(true_x2, limit_bars)
session_high := _top
session_low := _bottom
else if _is_ended
session_open := na
// ------------------------
// Drawing
// ------------------------
draw (_show, _session, _color, _label, _extend, _show_fib, _show_op, _lookback, _boxes_session, _lines_session, _boxes_candle_body, _lines_candle_wick, _boxes_op, _lines_fib, _labels) =>
max = f_get_period(_session, 1, _lookback)
top = ta.highest(high, max)
bottom = ta.lowest(low, max)
is_started = f_get_started(_session)
is_ended = f_get_ended(_session)
is_extend = _extend != option_no
= f_render_main(_show, _session, is_started, is_ended, _color, top, bottom)
if i_sess_box_style == 'Box'
f_render_session(_show, _session, is_started, is_ended, _color, top, bottom, x1, x2, is_extend, _boxes_session)
if i_sess_box_style == 'Sandwich'
f_render_sessionrange(_show, _session, is_started, is_ended, _color, top, bottom, x1, x2, is_extend, _lines_session)
if i_show_candle
f_render_candle(_show, _session, is_started, is_ended, _color, top, bottom, _open, x1, x2, _boxes_candle_body, _lines_candle_wick)
if i_label_show
f_render_label(_show, _session, is_started, _color, top, bottom, _label, _labels)
if _show_op
f_render_oprange(_show, _session, is_started, x1, x2, _color, max, is_extend, _boxes_op)
if _show_fib
f_render_fibonacci(_show, _session, is_started, x1, x2, _color, top, bottom, 0.500, 2, line.style_solid, is_extend, _lines_fib)
f_render_fibonacci(_show, _session, is_started, x1, x2, _color, top, bottom, 0.628, i_f_linewidth, i_f_linestyle, is_extend, _lines_fib)
f_render_fibonacci(_show, _session, is_started, x1, x2, _color, top, bottom, 0.382, i_f_linewidth, i_f_linestyle, is_extend, _lines_fib)
util.clear_lines(_lines_fib, i_history_period * 3)
f_render_limitmessage(_show, _session, is_started, is_ended, x1, bottom, _rightbars)
///////////////////
// Calculating
///////////////////
string tz = (i_tz == option_no or i_tz == '') ? na : i_tz
int sess1 = time(timeframe.period, i_sess1, tz)
int sess2 = time(timeframe.period, i_sess2, tz)
int sess3 = time(timeframe.period, i_sess3, tz)
int sess4 = time(timeframe.period, i_sess4, tz)
///////////////////
// Plotting
///////////////////
var sess1_box = array.new()
var sess2_box = array.new()
var sess3_box = array.new()
var sess4_box = array.new()
var sess1_line = array.new()
var sess2_line = array.new()
var sess3_line = array.new()
var sess4_line = array.new()
var sess1_op = array.new()
var sess2_op = array.new()
var sess3_op = array.new()
var sess4_op = array.new()
var sess1_fib = array.new()
var sess2_fib = array.new()
var sess3_fib = array.new()
var sess4_fib = array.new()
var sess1_candle_body = array.new()
var sess2_candle_body = array.new()
var sess3_candle_body = array.new()
var sess4_candle_body = array.new()
var sess1_candle_wick = array.new()
var sess2_candle_wick = array.new()
var sess3_candle_wick = array.new()
var sess4_candle_wick = array.new()
var sess1_labels = array.new()
var sess2_labels = array.new()
var sess3_labels = array.new()
var sess4_labels = array.new()
= draw(i_show_sess1, sess1, i_sess1_color, i_sess1_label, i_sess1_extend, i_sess1_fib, i_sess1_op, i_lookback, sess1_box, sess1_line, sess1_candle_body, sess1_candle_wick, sess1_op, sess1_fib, sess1_labels)
= draw(i_show_sess2, sess2, i_sess2_color, i_sess2_label, i_sess2_extend, i_sess2_fib, i_sess2_op, i_lookback, sess2_box, sess2_line, sess2_candle_body, sess2_candle_wick, sess2_op, sess2_fib, sess2_labels)
= draw(i_show_sess3, sess3, i_sess3_color, i_sess3_label, i_sess3_extend, i_sess3_fib, i_sess3_op, i_lookback, sess3_box, sess3_line, sess3_candle_body, sess3_candle_wick, sess3_op, sess3_fib, sess3_labels)
= draw(i_show_sess4, sess4, i_sess4_color, i_sess4_label, i_sess4_extend, i_sess4_fib, i_sess4_op, i_lookback, sess4_box, sess4_line, sess4_candle_body, sess4_candle_wick, sess4_op, sess4_fib, sess4_labels)
is_positive_bar = close > open
color c_barcolor = na
color c_plotcandle = na
c_sess1_barcolor = (is_sess1) ? (is_positive_bar ? i_sess1_barcolor1 : i_sess1_barcolor2) : na
c_sess2_barcolor = (is_sess2) ? (is_positive_bar ? i_sess2_barcolor1 : i_sess2_barcolor2) : na
c_sess3_barcolor = (is_sess3) ? (is_positive_bar ? i_sess3_barcolor1 : i_sess3_barcolor2) : na
c_sess4_barcolor = (is_sess4) ? (is_positive_bar ? i_sess4_barcolor1 : i_sess4_barcolor2) : na
if (i_sess1_chart != option_chart_x) and is_sess1
c_barcolor := i_sess1_barcolor ? c_sess1_barcolor : na
c_plotcandle := i_sess1_plotcandle ? c_sess1_barcolor : na
if (i_sess2_chart != option_chart_x) and is_sess2
c_barcolor := i_sess2_barcolor ? c_sess2_barcolor : na
c_plotcandle := i_sess2_plotcandle ? c_sess2_barcolor : na
if (i_sess3_chart != option_chart_x) and is_sess3
c_barcolor := i_sess3_barcolor ? c_sess3_barcolor : na
c_plotcandle := i_sess3_plotcandle ? c_sess3_barcolor : na
if (i_sess4_chart != option_chart_x) and is_sess4
c_barcolor := i_sess4_barcolor ? c_sess4_barcolor : na
c_plotcandle := i_sess4_plotcandle ? c_sess4_barcolor : na
barcolor(c_barcolor)
plotcandle(open, high, low, close, color=is_positive_bar ? color_none : c_plotcandle, bordercolor=c_plotcandle, wickcolor=c_plotcandle)
////////////////////
// Alerts
////////////////////
// Session alerts
sess1_started = is_sess1 and not is_sess1 , sess1_ended = not is_sess1 and is_sess1
sess2_started = is_sess2 and not is_sess2 , sess2_ended = not is_sess2 and is_sess2
sess3_started = is_sess3 and not is_sess3 , sess3_ended = not is_sess3 and is_sess3
sess4_started = is_sess4 and not is_sess4 , sess4_ended = not is_sess4 and is_sess4
alertcondition(sess1_started, 'Session #1 started')
alertcondition(sess1_ended, 'Session #1 ended')
alertcondition(sess2_started, 'Session #2 started')
alertcondition(sess2_ended, 'Session #2 ended')
alertcondition(sess3_started, 'Session #3 started')
alertcondition(sess3_ended, 'Session #3 ended')
alertcondition(sess4_started, 'Session #4 started')
alertcondition(sess4_ended, 'Session #4 ended')
alertcondition((not is_sess1) and ta.crossover(close, sess1_high), 'Session #1 High crossed (after session closed)')
alertcondition((not is_sess1) and ta.crossunder(close, sess1_low), 'Session #1 Low crossed (after session closed)')
alertcondition((not is_sess2) and ta.crossover(close, sess2_high), 'Session #2 High crossed (after session closed)')
alertcondition((not is_sess2) and ta.crossunder(close, sess2_low), 'Session #2 Low crossed (after session closed)')
alertcondition((not is_sess3) and ta.crossover(close, sess3_high), 'Session #3 High crossed (after session closed)')
alertcondition((not is_sess3) and ta.crossunder(close, sess3_low), 'Session #3 Low crossed (after session closed)')
alertcondition((not is_sess4) and ta.crossover(close, sess4_high), 'Session #4 High crossed (after session closed)')
alertcondition((not is_sess4) and ta.crossunder(close, sess4_low), 'Session #4 Low crossed (after session closed)')
// Alerts visualized
if i_alert1_show
if i_show_sess1
if sess1_started
label.new(bar_index, close, 'Start', yloc=yloc.abovebar, color=i_sess1_color, textcolor=color_text, size=size.small, style=label.style_label_down)
if sess1_ended
label.new(bar_index, close, 'End' , yloc=yloc.abovebar, color=i_sess1_color, textcolor=color_text, size=size.small, style=label.style_label_down)
if i_show_sess2
if sess2_started
label.new(bar_index, close, 'Start', yloc=yloc.abovebar, color=i_sess2_color, textcolor=color_text, size=size.small, style=label.style_label_down)
if sess2_ended
label.new(bar_index, close, 'End' , yloc=yloc.abovebar, color=i_sess2_color, textcolor=color_text, size=size.small, style=label.style_label_down)
if i_show_sess3
if sess3_started
label.new(bar_index, close, 'Start', yloc=yloc.abovebar, color=i_sess3_color, textcolor=color_text, size=size.small, style=label.style_label_down)
if sess3_ended
label.new(bar_index, close, 'End' , yloc=yloc.abovebar, color=i_sess3_color, textcolor=color_text, size=size.small, style=label.style_label_down)
if i_show_sess4
if sess4_started
label.new(bar_index, close, 'Start', yloc=yloc.abovebar, color=i_sess4_color, textcolor=color_text, size=size.small, style=label.style_label_down)
if sess4_ended
label.new(bar_index, close, 'End' , yloc=yloc.abovebar, color=i_sess4_color, textcolor=color_text, size=size.small, style=label.style_label_down)
plot(i_alert3_show ? sess1_high : na, 'sess1_high', style=plot.style_linebr, color=i_sess1_color)
plot(i_alert3_show ? sess1_low : na, 'sess1_low' , style=plot.style_linebr, color=i_sess1_color, linewidth=2)
plot(i_alert3_show ? sess2_high : na, 'sess2_high', style=plot.style_linebr, color=i_sess2_color)
plot(i_alert3_show ? sess2_low : na, 'sess2_low' , style=plot.style_linebr, color=i_sess2_color, linewidth=2)
plot(i_alert3_show ? sess3_high : na, 'sess3_high', style=plot.style_linebr, color=i_sess3_color)
plot(i_alert3_show ? sess3_low : na, 'sess3_low' , style=plot.style_linebr, color=i_sess3_color, linewidth=2)
plot(i_alert3_show ? sess4_high : na, 'sess4_high', style=plot.style_linebr, color=i_sess4_color)
plot(i_alert3_show ? sess4_low : na, 'sess4_low' , style=plot.style_linebr, color=i_sess4_color, linewidth=2)
plotshape(i_alert3_show and (not is_sess1) and ta.crossover(close, sess1_high) ? sess1_high : na, 'cross sess1_high', color=i_sess1_color, style=shape.triangleup, location=location.absolute, size=size.tiny)
plotshape(i_alert3_show and (not is_sess1) and ta.crossunder(close, sess1_low) ? sess1_low : na, 'cross sess1_low', color=i_sess1_color, style=shape.triangledown, location=location.absolute, size=size.tiny)
plotshape(i_alert3_show and (not is_sess2) and ta.crossover(close, sess2_high) ? sess2_high : na, 'cross sess2_high', color=i_sess2_color, style=shape.triangleup, location=location.absolute, size=size.tiny)
plotshape(i_alert3_show and (not is_sess2) and ta.crossunder(close, sess2_low) ? sess2_low : na, 'cross sess2_low', color=i_sess2_color, style=shape.triangledown, location=location.absolute, size=size.tiny)
plotshape(i_alert3_show and (not is_sess3) and ta.crossover(close, sess3_high) ? sess3_high : na, 'cross sess3_high', color=i_sess3_color, style=shape.triangleup, location=location.absolute, size=size.tiny)
plotshape(i_alert3_show and (not is_sess3) and ta.crossunder(close, sess3_low) ? sess3_low : na, 'cross sess3_low', color=i_sess3_color, style=shape.triangledown, location=location.absolute, size=size.tiny)
plotshape(i_alert3_show and (not is_sess4) and ta.crossover(close, sess4_high) ? sess4_high : na, 'cross sess4_high', color=i_sess4_color, style=shape.triangleup, location=location.absolute, size=size.tiny)
plotshape(i_alert3_show and (not is_sess4) and ta.crossunder(close, sess4_low) ? sess4_low : na, 'cross sess4_low', color=i_sess4_color, style=shape.triangledown, location=location.absolute, size=size.tiny)
HSM BULLET//@version=5
indicator('HSM BULLET', 'HSM BULLET', overlay=true, max_bars_back=500, explicit_plot_zorder=true)
import boitoki/AwesomeColor/4 as ac
import boitoki/Utilities/3 as util
///////////////
// Groups
///////////////
g0 = 'GENERAL'
g1_01 = '♯1 SESSION'
g1_02 = '♯2 SESSION'
g1_03 = '♯3 SESSION'
g1_04 = '♯4 SESSION'
g4 = 'BOX'
g6 = 'LABELS'
g5 = 'OPENING RANGE'
g7 = 'FIBONACCI LEVELS'
g8 = 'OPTIONS'
g11 = 'CANDLE'
g10 = 'Alerts visualized'
///////////////
// Defined
///////////////
max_bars = 500
option_yes = 'Yes'
option_no = '× No'
option_extend1 = 'Yes'
option_hide = '× Hide'
option_border_style1 = '────'
option_border_style2 = '- - - - - -'
option_border_style3 = '•••••••••'
option_chart_x = '× No'
option_chart_1 = 'Bar color'
option_chart_2 = 'Candles'
fmt_price = '{0,number,#.#####}'
fmt_pips = '{0,number,#.#}'
icon_separator = ' • '
color_none = color.new(color.black, 100)
color_text = color.new(color.white, 0)
///////////////
// Functions
///////////////
f_get_time_by_bar(bar_count) => timeframe.multiplier * bar_count * 60 * 1000
f_border_style (_style) =>
switch _style
option_border_style1 => line.style_solid
option_border_style2 => line.style_dashed
option_border_style3 => line.style_dotted
=> _style
f_get_period (_session, _start, _lookback) =>
result = math.max(_start, 1)
for i = result to _lookback
if na(_session ) and _session
result := i+1
break
result
f_get_label_position (_y, _side) =>
switch _y
'top' => _side == 'outside' ? label.style_label_lower_left : label.style_label_upper_left
'bottom' => _side == 'outside' ? label.style_label_upper_left : label.style_label_lower_left
f_get_started (_session) => na(_session ) and _session
f_get_ended (_session) => na(_session) and _session
f_message_limit_bars (_v) => '⚠️ This box\'s right position exceeds 500 bars(' + str.tostring(_v) + '). This box is not displayed correctly.'
f_set_line_x1 (_line, _x) =>
if (line.get_x1(_line) != _x)
line.set_x1(_line, _x)
f_set_line_x2 (_line, _x) =>
if (line.get_x2(_line) != _x)
line.set_x2(_line, _x)
f_set_box_right (_box, _x) =>
if box.get_right(_box) != _x
box.set_right(_box, _x)
///////////////
// Inputs
///////////////
// Timezone
i_tz = input.string('GMT-4', title='Timezone', options= , tooltip='e.g. \'America/New_York\', \'Asia/Tokyo\', \'GMT-4\', \'GMT+9\'...', group=g0)
i_history_period = input.int(10, 'History', minval=0, group=g0)
i_show = i_history_period > 0
i_lookback = 12 * 60
// Sessions
i_show_sess1 = input.bool(true, 'Session 1 ', group=g1_01, inline='session1_1') and i_show
i_sess1_label = input.string('London Silver', '', group=g1_01, inline='session1_1')
i_sess1_color = input.color(#0a0a0a, '', group=g1_01, inline='session1_1')
i_sess1_barcolor1 = input.color(#0a0a0a, '•', group=g1_01, inline='session1_1')
i_sess1_barcolor2 = input.color(#0a0a0a, '', group=g1_01, inline='session1_1')
i_sess1 = input.session('0300-0400', 'Time', group=g1_01)
i_sess1_extend = input.string(option_no, 'Extend', options= , group=g1_01)
i_sess1_fib = input.string(option_no, 'Fibonacci levels', group=g1_01, options= ) != option_no
i_sess1_op = input.string(option_no, 'Opening range', group=g1_01, options= ) != option_no and i_show
i_sess1_chart = input.string(option_chart_x, 'Bar', options= , group=g1_01)
i_sess1_barcolor = i_sess1_chart == option_chart_1
i_sess1_plotcandle = i_sess1_chart == option_chart_2
i_show_sess2 = input.bool(true, 'Session 2 ', group=g1_02, inline='session2_1') and i_show
i_sess2_label = input.string('NY AM Bullet', '', group=g1_02, inline='session2_1')
i_sess2_color = input.color(#0a0a0a, '', group=g1_02, inline='session2_1')
i_sess2_barcolor1 = input.color(#0a0a0a, '•', group=g1_02, inline='session2_1')
i_sess2_barcolor2 = input.color(#0a0a0a, '', group=g1_02, inline='session2_1')
i_sess2 = input.session('1000-1100', 'Time', group=g1_02)
i_sess2_extend = input.string(option_no, 'Extend', options= , group=g1_02)
i_sess2_fib = input.string(option_no, 'Fibonacci levels', group=g1_02, options= ) != option_no
i_sess2_op = input.string(option_no, 'Opening range', group=g1_02, options= ) != option_no and i_show
i_sess2_chart = input.string(option_chart_x, 'Bar', options= , group=g1_02)
i_sess2_barcolor = i_sess2_chart == option_chart_1
i_sess2_plotcandle = i_sess2_chart == option_chart_2
i_show_sess3 = input.bool(true, 'Session 3 ', group=g1_03, inline='session3_1') and i_show
i_sess3_label = input.string('NY PM Bullet', '', group=g1_03, inline='session3_1')
i_sess3_color = input.color(#0a0a0a, '', group=g1_03, inline='session3_1')
i_sess3_barcolor1 = input.color(#0a0a0a, '•', group=g1_03, inline='session3_1')
i_sess3_barcolor2 = input.color(#0a0a0a, '', group=g1_03, inline='session3_1')
i_sess3 = input.session('1400-1500', 'Time', group=g1_03)
i_sess3_extend = input.string(option_no, 'Extend', options= , group=g1_03)
i_sess3_fib = input.string(option_no, 'Fibonacci levels', group=g1_03, options= ) != option_no
i_sess3_op = input.string(option_no, 'Opening range', group=g1_03, options= ) != option_no and i_show
i_sess3_chart = input.string(option_chart_x, 'Bar', options= , group=g1_03)
i_sess3_barcolor = i_sess3_chart == option_chart_1
i_sess3_plotcandle = i_sess3_chart == option_chart_2
i_show_sess4 = input.bool(true, 'Session 4 ', group=g1_04, inline='session4_1') and i_show
i_sess4_label = input.string(' ', '', group=g1_04, inline='session4_1')
i_sess4_color = input.color(#0a0a0a, '', group=g1_04, inline='session4_1')
i_sess4_barcolor1 = input.color(#0a0a0a, '•', group=g1_04, inline='session4_1')
i_sess4_barcolor2 = input.color(#0a0a0a, '', group=g1_04, inline='session4_1')
i_sess4 = input.session('1000-1000', 'Time', group=g1_04)
i_sess4_extend = input.string(option_no, 'Extend', options= , group=g1_04)
i_sess4_fib = input.string(option_no, 'Fibonacci levels', group=g1_04, options= ) != option_no
i_sess4_op = input.string(option_no, 'Opening range', group=g1_04, options= ) != option_no and i_show
i_sess4_chart = input.string(option_chart_x, 'Bar', options= , group=g1_04)
i_sess4_barcolor = i_sess4_chart == option_chart_1
i_sess4_plotcandle = i_sess4_chart == option_chart_2
// Show & Styles
i_sess_box_style = input.string('Box', 'Style', options= , group=g4)
i_sess_border_style = f_border_style(input.string(option_border_style2, 'Line style', options= , group=g4))
i_sess_border_width = input.int(1, 'Thickness', minval=0, group=g4)
i_sess_bgopacity = input.int(94, 'Transp', minval=0, maxval=100, step=1, group=g4, tooltip='Setting the 100 is no background color')
// Candle
option_candle_body = 'OC'
option_candle_wick = 'OHLC'
i_candle = input.string(option_hide, 'Display', options= , group=g11)
i_candle_border_width = input.int(2, 'Thickness', minval=0, group=g11)
i_show_candle = (i_candle != option_hide) and (i_candle_border_width > 0)
i_show_candle_wick = i_candle == option_candle_wick
option_candle_color1 = 'Session\'s'
option_candle_color2 = 'Red • Green'
i_candle_color = input.string(option_candle_color2, 'Color ', options= , group=g11, inline='candle_color')
i_candle_color_g = input.color(#A6E22E, '', group=g11, inline='candle_color')
i_candle_color_r = input.color(#F92672, '', group=g11, inline='candle_color')
// Labels
i_label_show = input.bool(true, 'Labels', inline='label_show', group=g6) and i_show
i_label_size = str.lower(input.string('Small', '', options= , inline='label_show', group=g6))
i_label_position_y = str.lower(input.string('Top', '', options= , inline='label_show', group=g6))
i_label_position_s = str.lower(input.string('Outside', '', options= , inline='label_show', group=g6))
i_label_position = f_get_label_position(i_label_position_y, i_label_position_s)
i_label_format_name = input.bool(true, 'Name', inline='label_format', group=g6)
i_label_format_day = input.bool(false, 'Day', inline='label_format', group=g6)
i_label_format_price = input.bool(false, 'Price', inline='label_format', group=g6)
i_label_format_pips = input.bool(false, 'Pips', inline='label_format', group=g6)
// Fibonacci levels
i_f_linestyle = f_border_style(input.string(option_border_style1, title="Style", options= , group=g7))
i_f_linewidth = input.int(1, title="Thickness", minval=1, group=g7)
// Opening range
i_o_minutes = input.int(15, title='Periods (minutes)', minval=1, step=1, group=g5)
i_o_minutes := math.max(i_o_minutes, timeframe.multiplier + 1)
i_o_transp = input.int(88, title='Transp', minval=0, maxval=100, step=1, group=g5)
// Alerts
i_alert1_show = input.bool(false, 'Alerts - Sessions stard/end', group=g10)
i_alert2_show = input.bool(false, 'Alerts - Opening range breakouts', group=g10)
i_alert3_show = input.bool(false, 'Alerts - Price crossed session\'s High/Low after session closed', group=g10)
// ------------------------
// Drawing labels
// ------------------------
f_render_label (_show, _session, _is_started, _color, _top, _bottom, _text, _labels) =>
var label my_label = na
var int start_time = na
v_position_y = (i_label_position_y == 'top') ? _top : _bottom
v_label = array.new_string()
v_chg = _top - _bottom
if _is_started
start_time := time
if i_label_format_name and not na(_text)
array.push(v_label, _text)
if i_label_format_day
array.push(v_label, util.get_day(dayofweek(start_time, i_tz)))
if i_label_format_price
array.push(v_label, str.format(fmt_price, v_chg))
if i_label_format_pips
array.push(v_label, str.format(fmt_pips, util.toPips(v_chg)) + ' pips')
if _show
if _is_started
my_label := label.new(bar_index, v_position_y, array.join(v_label, icon_separator), textcolor=_color, color=color_none, size=i_label_size, style=i_label_position)
array.push(_labels, my_label)
util.clear_labels(_labels, i_history_period)
else if _session
label.set_y(my_label, v_position_y)
label.set_text(my_label, array.join(v_label, icon_separator))
// ------------------------
// Drawing Fibonacci levels
// ------------------------
f_render_fibonacci (_show, _session, _is_started, _x1, _x2, _color, _top, _bottom, _level, _width, _style, _is_extend, _lines) =>
var line my_line = na
if _show
y = (_top - _bottom) * _level + _bottom
if _is_started
my_line := line.new(_x1, y, _x2, y, width=_width, color=color.new(_color, 30), style=_style)
array.push(_lines, my_line)
if _is_extend
line.set_extend(my_line, extend.right)
else if _session
line.set_y1(my_line, y)
line.set_y2(my_line, y)
f_set_line_x2(my_line, _x2)
// ------------------------
// Drawing Opening range
// ------------------------
f_render_oprange (_show, _session, _is_started, _x1, _x2, _color, _max, _is_extend, _boxes) =>
var int start_time = na
var box my_box = na
top = ta.highest(high, _max)
bottom = ta.lowest(low, _max)
is_crossover = ta.crossover(close, box.get_top(my_box))
is_crossunder = ta.crossunder(close, box.get_bottom(my_box))
if _show
if _is_started
util.clear_boxes(_boxes, math.max(0, i_history_period - 1))
start_time := time
my_box := na
else if _session
time_op = start_time + (i_o_minutes * 60 * 1000)
time_op_delay = time_op - f_get_time_by_bar(1)
if time <= time_op and time > time_op_delay
my_box := box.new(_x1, top, _x2, bottom, border_width=0, bgcolor=color.new(_color, i_o_transp))
array.push(_boxes, my_box)
if _is_extend
box.set_extend(my_box, extend.right)
my_box
else
f_set_box_right(my_box, _x2)
if is_crossover
alert('Price crossed over the opening range', alert.freq_once_per_bar)
if i_alert2_show
label.new(bar_index, box.get_top(my_box), "×", color=color.blue, textcolor=ac.tradingview('blue'), style=label.style_none, size=size.large)
if is_crossunder
alert('Price crossed under the opening range', alert.freq_once_per_bar)
if i_alert2_show
label.new(bar_index, box.get_bottom(my_box), "×", color=color.red, textcolor=ac.tradingview('red'), style=label.style_none, size=size.large)
my_box
// ------------------------
// Drawing candle
// ------------------------
f_render_candle (_show, _session, _is_started, _is_ended, _color, _top, _bottom, _open, _x1, _x2, _boxes, _lines) =>
var box body = na
var line wick1 = na
var line wick2 = na
border_width = i_candle_border_width
cx = math.round(math.avg(_x2, _x1)) - math.round(border_width / 2)
body_color = i_candle_color == option_candle_color2 ? close > _open ? i_candle_color_g : i_candle_color_r : _color
if _show
if _is_started
body := box.new(_x1, _top, _x2, _bottom, body_color, border_width, line.style_solid, bgcolor=color.new(color.black, 100))
wick1 := i_show_candle_wick ? line.new(cx, _top, cx, _top, color=_color, width=border_width, style=line.style_solid) : na
wick2 := i_show_candle_wick ? line.new(cx, _bottom, cx, _bottom, color=_color, width=border_width, style=line.style_solid) : na
array.push(_boxes, body)
array.push(_lines, wick1)
array.push(_lines, wick2)
util.clear_boxes(_boxes, i_history_period)
util.clear_lines(_lines, i_history_period * 2)
else if _session
top = math.max(_open, close)
bottom = math.min(_open, close)
box.set_top(body, top)
box.set_bottom(body, bottom)
box.set_right(body, _x2)
box.set_border_color(body, body_color)
line.set_y1(wick1, _top)
line.set_y2(wick1, top)
f_set_line_x1(wick1, cx)
f_set_line_x2(wick1, cx)
line.set_color(wick1, body_color)
line.set_y1(wick2, _bottom)
line.set_y2(wick2, bottom)
f_set_line_x1(wick2, cx)
f_set_line_x2(wick2, cx)
line.set_color(wick2, body_color)
else if _is_ended
box.set_right(body, bar_index)
// ------------------------
// Rendering limit message
// ------------------------
f_render_limitmessage (_show, _session, _is_started, _is_ended, _x, _y, _rightbars) =>
var label my_note = na
if _show
if _is_started
if _rightbars > max_bars
my_note := label.new(_x, _y, f_message_limit_bars(_rightbars), style=label.style_label_upper_left, color=color.yellow, textalign=text.align_left, yloc=yloc.price)
else if _session
if _rightbars > max_bars
label.set_y(my_note, _y)
label.set_text(my_note, f_message_limit_bars(_rightbars))
else
label.delete(my_note)
else if _is_ended
label.delete(my_note)
true
// Rendering session
//
f_render_sessionrange (_show, _session, _is_started, _is_ended, _color, _top, _bottom, _x1, _x2, _is_extend, _lines) =>
var line above_line = na
var line below_line = na
if _show
if _is_started
above_line := line.new(_x1, _top, _x2, _top, width=i_sess_border_width, style=i_sess_border_style, color=_color)
below_line := line.new(_x1, _bottom, _x2, _bottom, width=i_sess_border_width, style=i_sess_border_style, color=_color)
linefill.new(above_line, below_line, color.new(_color, i_sess_bgopacity))
array.push(_lines, above_line)
array.push(_lines, below_line)
util.clear_lines(_lines, i_history_period * 2)
if _is_extend
line.set_extend(above_line, extend.right)
line.set_extend(below_line, extend.right)
else if _session
line.set_y1(above_line, _top)
line.set_y2(above_line, _top)
line.set_x2(above_line, _x2)
line.set_y1(below_line, _bottom)
line.set_y2(below_line, _bottom)
line.set_x2(below_line, _x2)
true
else if _is_ended
true
true
// ------------------------
// Rendering session box
// ------------------------
f_render_session (_show, _session, _is_started, _is_ended, _color, _top, _bottom, _x1, _x2, _is_extend, _boxes) =>
var box my_box = na
if _show
if _is_started
my_box := box.new(_x1, _top, _x2, _bottom, _color, i_sess_border_width, i_sess_border_style, bgcolor=color.new(_color, i_sess_bgopacity))
array.push(_boxes, my_box)
util.clear_boxes(_boxes, i_history_period)
if _is_extend
box.set_extend(my_box, extend.right)
else if _session
box.set_top(my_box, _top)
box.set_bottom(my_box, _bottom)
f_set_box_right(my_box, _x2)
else if _is_ended
box.set_right(my_box, bar_index)
my_box
// ------------------------
// Drawing market
// ------------------------
f_render_main (_show, _session, _is_started, _is_ended, _color, _top, _bottom) =>
var box my_box = na
var label my_note = na
var x1 = 0
var x2 = 0
var session_open = 0.0
var session_high = 0.0
var session_low = 0.0
x0_1 = ta.valuewhen(na(_session ) and _session, bar_index, 1)
x0_2 = ta.valuewhen(na(_session) and _session , bar_index, 0)
x0_d = math.abs(x0_2 - x0_1)
limit_bars = max_bars
rightbars = x0_d
if _show
if _is_started
x1 := bar_index
x2 := bar_index + (math.min(x0_d, limit_bars))
session_open := open
session_high := _top
session_low := _bottom
else if _session
true_x2 = x1 + x0_d
rightbars := true_x2 - bar_index
limit_bars := bar_index + max_bars
x2 := math.min(true_x2, limit_bars)
session_high := _top
session_low := _bottom
else if _is_ended
session_open := na
// ------------------------
// Drawing
// ------------------------
draw (_show, _session, _color, _label, _extend, _show_fib, _show_op, _lookback, _boxes_session, _lines_session, _boxes_candle_body, _lines_candle_wick, _boxes_op, _lines_fib, _labels) =>
max = f_get_period(_session, 1, _lookback)
top = ta.highest(high, max)
bottom = ta.lowest(low, max)
is_started = f_get_started(_session)
is_ended = f_get_ended(_session)
is_extend = _extend != option_no
= f_render_main(_show, _session, is_started, is_ended, _color, top, bottom)
if i_sess_box_style == 'Box'
f_render_session(_show, _session, is_started, is_ended, _color, top, bottom, x1, x2, is_extend, _boxes_session)
if i_sess_box_style == 'Sandwich'
f_render_sessionrange(_show, _session, is_started, is_ended, _color, top, bottom, x1, x2, is_extend, _lines_session)
if i_show_candle
f_render_candle(_show, _session, is_started, is_ended, _color, top, bottom, _open, x1, x2, _boxes_candle_body, _lines_candle_wick)
if i_label_show
f_render_label(_show, _session, is_started, _color, top, bottom, _label, _labels)
if _show_op
f_render_oprange(_show, _session, is_started, x1, x2, _color, max, is_extend, _boxes_op)
if _show_fib
f_render_fibonacci(_show, _session, is_started, x1, x2, _color, top, bottom, 0.500, 2, line.style_solid, is_extend, _lines_fib)
f_render_fibonacci(_show, _session, is_started, x1, x2, _color, top, bottom, 0.628, i_f_linewidth, i_f_linestyle, is_extend, _lines_fib)
f_render_fibonacci(_show, _session, is_started, x1, x2, _color, top, bottom, 0.382, i_f_linewidth, i_f_linestyle, is_extend, _lines_fib)
util.clear_lines(_lines_fib, i_history_period * 3)
f_render_limitmessage(_show, _session, is_started, is_ended, x1, bottom, _rightbars)
///////////////////
// Calculating
///////////////////
string tz = (i_tz == option_no or i_tz == '') ? na : i_tz
int sess1 = time(timeframe.period, i_sess1, tz)
int sess2 = time(timeframe.period, i_sess2, tz)
int sess3 = time(timeframe.period, i_sess3, tz)
int sess4 = time(timeframe.period, i_sess4, tz)
///////////////////
// Plotting
///////////////////
var sess1_box = array.new()
var sess2_box = array.new()
var sess3_box = array.new()
var sess4_box = array.new()
var sess1_line = array.new()
var sess2_line = array.new()
var sess3_line = array.new()
var sess4_line = array.new()
var sess1_op = array.new()
var sess2_op = array.new()
var sess3_op = array.new()
var sess4_op = array.new()
var sess1_fib = array.new()
var sess2_fib = array.new()
var sess3_fib = array.new()
var sess4_fib = array.new()
var sess1_candle_body = array.new()
var sess2_candle_body = array.new()
var sess3_candle_body = array.new()
var sess4_candle_body = array.new()
var sess1_candle_wick = array.new()
var sess2_candle_wick = array.new()
var sess3_candle_wick = array.new()
var sess4_candle_wick = array.new()
var sess1_labels = array.new()
var sess2_labels = array.new()
var sess3_labels = array.new()
var sess4_labels = array.new()
= draw(i_show_sess1, sess1, i_sess1_color, i_sess1_label, i_sess1_extend, i_sess1_fib, i_sess1_op, i_lookback, sess1_box, sess1_line, sess1_candle_body, sess1_candle_wick, sess1_op, sess1_fib, sess1_labels)
= draw(i_show_sess2, sess2, i_sess2_color, i_sess2_label, i_sess2_extend, i_sess2_fib, i_sess2_op, i_lookback, sess2_box, sess2_line, sess2_candle_body, sess2_candle_wick, sess2_op, sess2_fib, sess2_labels)
= draw(i_show_sess3, sess3, i_sess3_color, i_sess3_label, i_sess3_extend, i_sess3_fib, i_sess3_op, i_lookback, sess3_box, sess3_line, sess3_candle_body, sess3_candle_wick, sess3_op, sess3_fib, sess3_labels)
= draw(i_show_sess4, sess4, i_sess4_color, i_sess4_label, i_sess4_extend, i_sess4_fib, i_sess4_op, i_lookback, sess4_box, sess4_line, sess4_candle_body, sess4_candle_wick, sess4_op, sess4_fib, sess4_labels)
is_positive_bar = close > open
color c_barcolor = na
color c_plotcandle = na
c_sess1_barcolor = (is_sess1) ? (is_positive_bar ? i_sess1_barcolor1 : i_sess1_barcolor2) : na
c_sess2_barcolor = (is_sess2) ? (is_positive_bar ? i_sess2_barcolor1 : i_sess2_barcolor2) : na
c_sess3_barcolor = (is_sess3) ? (is_positive_bar ? i_sess3_barcolor1 : i_sess3_barcolor2) : na
c_sess4_barcolor = (is_sess4) ? (is_positive_bar ? i_sess4_barcolor1 : i_sess4_barcolor2) : na
if (i_sess1_chart != option_chart_x) and is_sess1
c_barcolor := i_sess1_barcolor ? c_sess1_barcolor : na
c_plotcandle := i_sess1_plotcandle ? c_sess1_barcolor : na
if (i_sess2_chart != option_chart_x) and is_sess2
c_barcolor := i_sess2_barcolor ? c_sess2_barcolor : na
c_plotcandle := i_sess2_plotcandle ? c_sess2_barcolor : na
if (i_sess3_chart != option_chart_x) and is_sess3
c_barcolor := i_sess3_barcolor ? c_sess3_barcolor : na
c_plotcandle := i_sess3_plotcandle ? c_sess3_barcolor : na
if (i_sess4_chart != option_chart_x) and is_sess4
c_barcolor := i_sess4_barcolor ? c_sess4_barcolor : na
c_plotcandle := i_sess4_plotcandle ? c_sess4_barcolor : na
barcolor(c_barcolor)
plotcandle(open, high, low, close, color=is_positive_bar ? color_none : c_plotcandle, bordercolor=c_plotcandle, wickcolor=c_plotcandle)
////////////////////
// Alerts
////////////////////
// Session alerts
sess1_started = is_sess1 and not is_sess1 , sess1_ended = not is_sess1 and is_sess1
sess2_started = is_sess2 and not is_sess2 , sess2_ended = not is_sess2 and is_sess2
sess3_started = is_sess3 and not is_sess3 , sess3_ended = not is_sess3 and is_sess3
sess4_started = is_sess4 and not is_sess4 , sess4_ended = not is_sess4 and is_sess4
alertcondition(sess1_started, 'Session #1 started')
alertcondition(sess1_ended, 'Session #1 ended')
alertcondition(sess2_started, 'Session #2 started')
alertcondition(sess2_ended, 'Session #2 ended')
alertcondition(sess3_started, 'Session #3 started')
alertcondition(sess3_ended, 'Session #3 ended')
alertcondition(sess4_started, 'Session #4 started')
alertcondition(sess4_ended, 'Session #4 ended')
alertcondition((not is_sess1) and ta.crossover(close, sess1_high), 'Session #1 High crossed (after session closed)')
alertcondition((not is_sess1) and ta.crossunder(close, sess1_low), 'Session #1 Low crossed (after session closed)')
alertcondition((not is_sess2) and ta.crossover(close, sess2_high), 'Session #2 High crossed (after session closed)')
alertcondition((not is_sess2) and ta.crossunder(close, sess2_low), 'Session #2 Low crossed (after session closed)')
alertcondition((not is_sess3) and ta.crossover(close, sess3_high), 'Session #3 High crossed (after session closed)')
alertcondition((not is_sess3) and ta.crossunder(close, sess3_low), 'Session #3 Low crossed (after session closed)')
alertcondition((not is_sess4) and ta.crossover(close, sess4_high), 'Session #4 High crossed (after session closed)')
alertcondition((not is_sess4) and ta.crossunder(close, sess4_low), 'Session #4 Low crossed (after session closed)')
// Alerts visualized
if i_alert1_show
if i_show_sess1
if sess1_started
label.new(bar_index, close, 'Start', yloc=yloc.abovebar, color=i_sess1_color, textcolor=color_text, size=size.small, style=label.style_label_down)
if sess1_ended
label.new(bar_index, close, 'End' , yloc=yloc.abovebar, color=i_sess1_color, textcolor=color_text, size=size.small, style=label.style_label_down)
if i_show_sess2
if sess2_started
label.new(bar_index, close, 'Start', yloc=yloc.abovebar, color=i_sess2_color, textcolor=color_text, size=size.small, style=label.style_label_down)
if sess2_ended
label.new(bar_index, close, 'End' , yloc=yloc.abovebar, color=i_sess2_color, textcolor=color_text, size=size.small, style=label.style_label_down)
if i_show_sess3
if sess3_started
label.new(bar_index, close, 'Start', yloc=yloc.abovebar, color=i_sess3_color, textcolor=color_text, size=size.small, style=label.style_label_down)
if sess3_ended
label.new(bar_index, close, 'End' , yloc=yloc.abovebar, color=i_sess3_color, textcolor=color_text, size=size.small, style=label.style_label_down)
if i_show_sess4
if sess4_started
label.new(bar_index, close, 'Start', yloc=yloc.abovebar, color=i_sess4_color, textcolor=color_text, size=size.small, style=label.style_label_down)
if sess4_ended
label.new(bar_index, close, 'End' , yloc=yloc.abovebar, color=i_sess4_color, textcolor=color_text, size=size.small, style=label.style_label_down)
plot(i_alert3_show ? sess1_high : na, 'sess1_high', style=plot.style_linebr, color=i_sess1_color)
plot(i_alert3_show ? sess1_low : na, 'sess1_low' , style=plot.style_linebr, color=i_sess1_color, linewidth=2)
plot(i_alert3_show ? sess2_high : na, 'sess2_high', style=plot.style_linebr, color=i_sess2_color)
plot(i_alert3_show ? sess2_low : na, 'sess2_low' , style=plot.style_linebr, color=i_sess2_color, linewidth=2)
plot(i_alert3_show ? sess3_high : na, 'sess3_high', style=plot.style_linebr, color=i_sess3_color)
plot(i_alert3_show ? sess3_low : na, 'sess3_low' , style=plot.style_linebr, color=i_sess3_color, linewidth=2)
plot(i_alert3_show ? sess4_high : na, 'sess4_high', style=plot.style_linebr, color=i_sess4_color)
plot(i_alert3_show ? sess4_low : na, 'sess4_low' , style=plot.style_linebr, color=i_sess4_color, linewidth=2)
plotshape(i_alert3_show and (not is_sess1) and ta.crossover(close, sess1_high) ? sess1_high : na, 'cross sess1_high', color=i_sess1_color, style=shape.triangleup, location=location.absolute, size=size.tiny)
plotshape(i_alert3_show and (not is_sess1) and ta.crossunder(close, sess1_low) ? sess1_low : na, 'cross sess1_low', color=i_sess1_color, style=shape.triangledown, location=location.absolute, size=size.tiny)
plotshape(i_alert3_show and (not is_sess2) and ta.crossover(close, sess2_high) ? sess2_high : na, 'cross sess2_high', color=i_sess2_color, style=shape.triangleup, location=location.absolute, size=size.tiny)
plotshape(i_alert3_show and (not is_sess2) and ta.crossunder(close, sess2_low) ? sess2_low : na, 'cross sess2_low', color=i_sess2_color, style=shape.triangledown, location=location.absolute, size=size.tiny)
plotshape(i_alert3_show and (not is_sess3) and ta.crossover(close, sess3_high) ? sess3_high : na, 'cross sess3_high', color=i_sess3_color, style=shape.triangleup, location=location.absolute, size=size.tiny)
plotshape(i_alert3_show and (not is_sess3) and ta.crossunder(close, sess3_low) ? sess3_low : na, 'cross sess3_low', color=i_sess3_color, style=shape.triangledown, location=location.absolute, size=size.tiny)
plotshape(i_alert3_show and (not is_sess4) and ta.crossover(close, sess4_high) ? sess4_high : na, 'cross sess4_high', color=i_sess4_color, style=shape.triangleup, location=location.absolute, size=size.tiny)
plotshape(i_alert3_show and (not is_sess4) and ta.crossunder(close, sess4_low) ? sess4_low : na, 'cross sess4_low', color=i_sess4_color, style=shape.triangledown, location=location.absolute, size=size.tiny)
Advanced Volume Profile Pro Delta + POC + VAH/VAL# Advanced Volume Profile Pro - Delta + POC + VAH/VAL Analysis System
## WHAT THIS SCRIPT DOES
This script creates a comprehensive volume profile analysis system that combines traditional volume-at-price distribution with delta volume calculations, Point of Control (POC) identification, and Value Area (VAH/VAL) analysis. Unlike standard volume indicators that show only total volume over time, this script analyzes volume distribution across price levels and estimates buying vs selling pressure using multiple calculation methods to provide deeper market structure insights.
## WHY THIS COMBINATION IS ORIGINAL AND USEFUL
**The Problem Solved:** Traditional volume indicators show when volume occurs but not where price finds acceptance or rejection. Standalone volume profiles lack directional bias information, while basic delta calculations don't provide structural context. Traders need to understand both volume distribution AND directional sentiment at key price levels.
**The Solution:** This script implements an integrated approach that:
- Maps volume distribution across price levels using configurable row density
- Estimates delta (buying vs selling pressure) using three different methodologies
- Identifies Point of Control (highest volume price level) for key support/resistance
- Calculates Value Area boundaries where 70% of volume traded
- Provides real-time alerts for key level interactions and volume imbalances
**Unique Features:**
1. **Developing POC Visualization**: Real-time tracking of Point of Control migration throughout the session via blue dotted trail, revealing institutional accumulation/distribution patterns before they complete
2. **Multi-Method Delta Calculation**: Price Action-based, Bid/Ask estimation, and Cumulative methods for different market conditions
3. **Adaptive Timeframe System**: Auto-adjusts calculation parameters based on chart timeframe for optimal performance
4. **Flexible Profile Types**: N Bars Back (precise control), Days Back (calendar-based), and Session-based analysis modes
5. **Advanced Imbalance Detection**: Identifies and highlights significant buying/selling imbalances with configurable thresholds
6. **Comprehensive Alert System**: Monitors POC touches, Value Area entry/exit, and major volume imbalances
## HOW THE SCRIPT WORKS TECHNICALLY
### Core Volume Profile Methodology:
**1. Price Level Distribution:**
- Divides price range into user-defined rows (10-50 configurable)
- Calculates row height: `(Highest Price - Lowest Price) / Number of Rows`
- Distributes each bar's volume across price levels it touched proportionally
**2. Delta Volume Calculation Methods:**
**Price Action Method:**
```
Price Range = High - Low
Buy Pressure = (Close - Low) / Price Range
Sell Pressure = (High - Close) / Price Range
Buy Volume = Total Volume × Buy Pressure
Sell Volume = Total Volume × Sell Pressure
Delta = Buy Volume - Sell Volume
```
**Bid/Ask Estimation Method:**
```
Average Price = (High + Low + Close) / 3
Buy Volume = Close > Average ? Volume × 0.6 : Volume × 0.4
Sell Volume = Total Volume - Buy Volume
```
**Cumulative Method:**
```
Buy Volume = Close > Open ? Volume : Volume × 0.3
Sell Volume = Close ≤ Open ? Volume : Volume × 0.3
```
**3. Point of Control (POC) Identification:**
- Scans all price levels to find maximum volume concentration
- POC represents the price level with highest trading activity
- Acts as significant support/resistance level
- **Developing POC Feature**: Tracks POC evolution in real-time via blue dotted trail, showing how institutional interest migrates throughout the session. Upward POC migration indicates accumulation patterns, downward migration suggests distribution, providing early trend signals before price confirmation.
**4. Value Area Calculation:**
- Starts from POC and expands up/down to encompass 70% of total volume
- VAH (Value Area High): Upper boundary of value area
- VAL (Value Area Low): Lower boundary of value area
- Expansion algorithm prioritizes direction with higher volume
**5. Adaptive Range Selection:**
Based on profile type and timeframe optimization:
- **N Bars Back**: Fixed lookback period with performance optimization (20-500 bars)
- **Days Back**: Calendar-based analysis with automatic timeframe adjustment (1-365 days)
- **Session**: Current trading session or custom session times
### Performance Optimization Features:
- **Sampling Algorithm**: Reduces calculation load on large datasets while maintaining accuracy
- **Memory Management**: Clears previous drawings to prevent performance degradation
- **Safety Constraints**: Prevents excessive memory usage with configurable limits
## HOW TO USE THIS SCRIPT
### Initial Setup:
1. **Profile Configuration**: Select profile type based on trading style:
- N Bars Back: Precise control over data range
- Days Back: Intuitive calendar-based analysis
- Session: Real-time session development
2. **Row Density**: Set number of rows (30 default) - more rows = higher resolution, slower performance
3. **Delta Method**: Choose calculation method based on market type:
- Price Action: Best for trending markets
- Bid/Ask Estimate: Good for ranging markets
- Cumulative: Smoothed approach for volatile markets
4. **Visual Settings**: Configure colors, position (left/right), and display options
### Reading the Profile:
**Volume Bars:**
- **Length**: Represents relative volume at that price level
- **Color**: Green = net buying pressure, Red = net selling pressure
- **Intensity**: Darker colors indicate volume imbalances above threshold
**Key Levels:**
- **POC (Blue Line)**: Highest volume price - major support/resistance
- **VAH (Purple Dashed)**: Value Area High - upper boundary of fair value
- **VAL (Orange Dashed)**: Value Area Low - lower boundary of fair value
- **Value Area Fill**: Shaded region showing main trading range
**Developing POC Trail:**
- **Blue Dotted Lines**: Show real-time POC evolution throughout the session
- **Migration Patterns**: Upward trail indicates bullish accumulation, downward trail suggests bearish distribution
- **Early Signals**: POC movement often precedes price movement, providing advance warning of institutional activity
- **Institutional Footprints**: Reveals where smart money concentrated volume before final POC establishment
### Trading Applications:
**Support/Resistance Analysis:**
- POC acts as magnetic price level - expect reactions
- VAH/VAL provide intermediate support/resistance levels
- Profile edges show areas of low volume acceptance
**Developing POC Analysis:**
- **Upward Migration**: POC moving higher = institutional accumulation, bullish bias
- **Downward Migration**: POC moving lower = institutional distribution, bearish bias
- **Stable POC**: Tight clustering = balanced market, range-bound conditions
- **Early Trend Detection**: POC direction change often precedes price breakouts
**Entry Strategies:**
- Buy at VAL with POC as target (in uptrends)
- Sell at VAH with POC as target (in downtrends)
- Breakout plays above/below profile extremes
**Volume Imbalance Trading:**
- Strong buying imbalance (>60% threshold) suggests continued upward pressure
- Strong selling imbalance suggests continued downward pressure
- Imbalances near key levels provide high-probability setups
**Multi-Timeframe Context:**
- Use higher timeframe profiles for major levels
- Lower timeframe profiles for precise entries
- Session profiles for intraday trading structure
## SCRIPT SETTINGS EXPLANATION
### Volume Profile Settings:
- **Profile Type**: Determines data range for calculation
- N Bars Back: Exact number of bars (20-500 range)
- Days Back: Calendar days with timeframe adaptation (1-365 days)
- Session: Trading session-based (intraday focus)
- **Number of Rows**: Profile resolution (10-50 range)
- **Profile Width**: Visual width as chart percentage (10-50%)
- **Value Area %**: Volume percentage for VA calculation (50-90%, 70% standard)
- **Auto-Adjust**: Automatically optimizes for different timeframes
### Delta Volume Settings:
- **Show Delta Volume**: Enable/disable delta calculations
- **Delta Calculation Method**: Choose methodology based on market conditions
- **Highlight Imbalances**: Visual emphasis for significant volume imbalances
- **Imbalance Threshold**: Percentage for imbalance detection (50-90%)
### Session Settings:
- **Session Type**: Daily, Weekly, Monthly, or Custom periods
- **Custom Session Time**: Define specific trading hours
- **Previous Sessions**: Number of historical sessions to display
### Days Back Settings:
- **Lookback Days**: Number of calendar days to analyze (1-365)
- **Automatic Calculation**: Script automatically converts days to bars based on timeframe:
- Intraday: Accounts for 6.5 trading hours per day
- Daily: 1 bar per day
- Weekly/Monthly: Proportional adjustment
### N Bars Back Settings:
- **Lookback Bars**: Exact number of bars to analyze (20-500)
- **Precise Control**: Best for systematic analysis and backtesting
### Visual Customization:
- **Colors**: Bullish (green), Bearish (red), and level colors
- **Profile Position**: Left or Right side of chart
- **Profile Offset**: Distance from current price action
- **Labels**: Show/hide level labels and values
- **Smooth Profile Bars**: Enhanced visual appearance
### Alert Configuration:
- **POC Touch**: Alerts when price interacts with Point of Control
- **VA Entry/Exit**: Alerts for Value Area boundary interactions
- **Major Imbalance**: Alerts for significant volume imbalances
## VISUAL FEATURES
### Profile Display:
- **Horizontal Bars**: Volume distribution across price levels
- **Color Coding**: Delta-based coloring for directional bias
- **Smooth Rendering**: Optional smoothing for cleaner appearance
- **Transparency**: Configurable opacity for chart readability
### Level Lines:
- **POC**: Solid blue line with optional label
- **VAH/VAL**: Dashed colored lines with value displays
- **Extension**: Lines extend across relevant time periods
- **Value Area Fill**: Optional shaded region between VAH/VAL
### Information Table:
- **Current Values**: Real-time POC, VAH, VAL prices
- **VA Range**: Value Area width calculation
- **Positioning**: Multiple table positions available
- **Text Sizing**: Adjustable for different screen sizes
## IMPORTANT USAGE NOTES
**Realistic Expectations:**
- Volume profile analysis provides structural context, not trading signals
- Delta calculations are estimations based on price action, not actual order flow
- Past volume distribution does not guarantee future price behavior
- Combine with other analysis methods for comprehensive market view
**Best Practices:**
- Use appropriate profile types for your trading style:
- Day Trading: Session or Days Back (1-5 days)
- Swing Trading: Days Back (10-30 days) or N Bars Back
- Position Trading: Days Back (60-180 days)
- Consider market context (trending vs ranging conditions)
- Verify key levels with additional technical analysis
- Monitor profile development for changing market structure
**Performance Considerations:**
- Higher row counts increase calculation complexity
- Large lookback periods may affect chart performance
- Auto-adjust feature optimizes for most use cases
- Consider using session profiles for intraday efficiency
**Limitations:**
- Delta calculations are estimations, not actual transaction data
- Profile accuracy depends on available price/volume history
- Effectiveness varies across different instruments and market conditions
- Requires understanding of volume profile concepts for optimal use
**Data Requirements:**
- Requires volume data for accurate calculations
- Works best on liquid instruments with consistent volume
- May be less effective on very low volume or exotic instruments
This script serves as a comprehensive volume analysis tool for traders who need detailed market structure information with integrated directional bias analysis and real-time POC development tracking for informed trading decisions.
Active PMI Support/Resistance Levels [EdgeTerminal]The PMI Support & Resistance indicator revolutionizes traditional technical analysis by using Pointwise Mutual Information (PMI) - a statistical measure from information theory - to objectively identify support and resistance levels. Unlike conventional methods that rely on visual pattern recognition, this indicator provides mathematically rigorous, quantifiable evidence of price levels where significant market activity occurs.
- The Mathematical Foundation: Pointwise Mutual Information
Pointwise Mutual Information measures how much more likely two events are to occur together compared to if they were statistically independent. In our context:
Event A: Volume spikes occurring (high trading activity)
Event B: Price being at specific levels
The PMI formula calculates: PMI = log(P(A,B) / (P(A) × P(B)))
Where:
P(A,B) = Probability of volume spikes occurring at specific price levels
P(A) = Probability of volume spikes occurring anywhere
P(B) = Probability of price being at specific levels
High PMI scores indicate that volume spikes and certain price levels co-occur much more frequently than random chance would predict, revealing genuine support and resistance zones.
- Why PMI Outperforms Traditional Methods
Subjective interpretation: What one trader sees as significant, another might ignore
Confirmation bias: Tendency to see patterns that confirm existing beliefs
Inconsistent criteria: No standardized definition of "significant" volume or price action
Static analysis: Doesn't adapt to changing market conditions
No strength measurement: Can't quantify how "strong" a level truly is
PMI Advantages:
✅ Objective & Quantifiable: Mathematical proof of significance, not visual guesswork
✅ Statistical Rigor: Levels backed by information theory and probability
✅ Strength Scoring: PMI scores rank levels by statistical significance
✅ Adaptive: Automatically adjusts to different market volatility regimes
✅ Eliminates Bias: Computer-calculated, removing human interpretation errors
✅ Market Structure Aware: Reveals the underlying order flow concentrations
- How It Works
Data Processing Pipeline:
Volume Analysis: Identifies volume spikes using configurable thresholds
Price Binning: Divides price range into discrete levels for analysis
Co-occurrence Calculation: Measures how often volume spikes happen at each price level
PMI Computation: Calculates statistical significance for each price level
Level Filtering: Shows only levels exceeding minimum PMI thresholds
Dynamic Updates: Refreshes levels periodically while maintaining historical traces
Visual System:
Current Levels: Bright, thick lines with PMI scores - your actionable levels
Historical Traces: Faded previous levels showing market structure evolution
Strength Tiers: Line styles indicate PMI strength (solid/dashed/dotted)
Color Coding: Green for support, red for resistance
Info Table: Real-time display of strongest levels with scores
- Indicator Settings:
Core Parameters
Lookback Period (Default: 200)
Lower (50-100): More responsive to recent price action, catches short-term levels
Higher (300-500): Focuses on major historical levels, more stable but less responsive
Best for: Day trading (100-150), Swing trading (200-300), Position trading (400-500)
Volume Spike Threshold (Default: 1.5)
Lower (1.2-1.4): More sensitive, catches smaller volume increases, more levels detected
Higher (2.0-3.0): Only major volume surges count, fewer but stronger signals
Market dependent: High-volume stocks may need higher thresholds (2.0+), low-volume stocks lower (1.2-1.3)
Price Bins (Default: 50)
Lower (20-30): Broader price zones, less precise but captures wider areas
Higher (70-100): More granular levels, precise but may be overly specific
Volatility dependent: High volatility assets benefit from more bins (70+)
Minimum PMI Score (Default: 0.5)
Lower (0.2-0.4): Shows more levels including weaker ones, comprehensive view
Higher (1.0-2.0): Only statistically strong levels, cleaner chart
Progressive filtering: Start with 0.5, increase if too cluttered
Max Levels to Show (Default: 8)
Fewer (3-5): Clean chart focusing on strongest levels only
More (10-15): Comprehensive view but may clutter chart
Strategy dependent: Scalpers prefer fewer (3-5), swing traders more (8-12)
Historical Tracking Settings
Update Frequency (Default: 20 bars)
Lower (5-10): More frequent updates, captures rapid market changes
Higher (50-100): Less frequent updates, focuses on major structural shifts
Timeframe scaling: 1-minute charts need lower frequency (5-10), daily charts higher (50+)
Show Historical Levels (Default: True)
Enables the "breadcrumb trail" effect showing evolution of support/resistance
Disable for cleaner charts focusing only on current levels
Max Historical Marks (Default: 50)
Lower (20-30): Less memory usage, shorter history
Higher (100-200): Longer historical context but more resource intensive
Fade Strength (Default: 0.8)
Lower (0.5-0.6): Historical levels more visible
Higher (0.9-0.95): Historical levels very subtle
Visual Settings
Support/Resistance Colors: Choose colors that contrast well with your chart theme Line Width: Thicker lines (3-4) for better visibility on busy charts Show PMI Scores: Toggle labels showing statistical strength Label Size: Adjust based on screen resolution and chart zoom level
- Most Effective Usage Strategies
For Day Trading:
Setup: Lookback 100-150, Volume Threshold 1.8-2.2, Update Frequency 10-15
Use PMI levels as bounce/rejection points for scalp entries
Higher PMI scores (>1.5) offer better probability setups
Watch for volume spike confirmations at levels
For Swing Trading:
Setup: Lookback 200-300, Volume Threshold 1.5-2.0, Update Frequency 20-30
Enter on pullbacks to high PMI support levels
Target next resistance level with PMI score >1.0
Hold through minor levels, exit at major PMI levels
For Position Trading:
Setup: Lookback 400-500, Volume Threshold 2.0+, Update Frequency 50+
Focus on PMI scores >2.0 for major structural levels
Use for portfolio entry/exit decisions
Combine with fundamental analysis for timing
- Trading Applications:
Entry Strategies:
PMI Bounce Trades
Price approaches high PMI support level (>1.0)
Wait for volume spike confirmation (orange triangles)
Enter long on bullish price action at the level
Stop loss just below the PMI level
Target: Next PMI resistance level
PMI Breakout Trades
Price consolidates near high PMI level
Volume increases (watch for orange triangles)
Enter on decisive break with volume
Previous resistance becomes new support
Target: Next major PMI level
PMI Rejection Trades
Price approaches PMI resistance with momentum
Watch for rejection signals and volume spikes
Enter short on failure to break through
Stop above the PMI level
Target: Next PMI support level
Risk Management:
Stop Loss Placement
Place stops 0.1-0.5% beyond PMI levels (adjust for volatility)
Higher PMI scores warrant tighter stops
Use ATR-based stops for volatile assets
Position Sizing
Larger positions at PMI levels >2.0 (highest conviction)
Smaller positions at PMI levels 0.5-1.0 (lower conviction)
Scale out at multiple PMI targets
- Key Warning Signs & What to Watch For
Red Flags:
🚨 Very Low PMI Scores (<0.3): Weak statistical significance, avoid trading
🚨 No Volume Confirmation: PMI level without recent volume spikes may be stale
🚨 Overcrowded Levels: Too many levels close together suggests poor parameter tuning
🚨 Outdated Levels: Historical traces are reference only, not tradeable
Optimization Tips:
✅ Regular Recalibration: Adjust parameters monthly based on market regime changes
✅ Volume Context: Always check for recent volume activity at PMI levels
✅ Multiple Timeframes: Confirm PMI levels across different timeframes
✅ Market Conditions: Higher thresholds during high volatility periods
Interpreting PMI Scores
PMI Score Ranges:
0.5-1.0: Moderate statistical significance, proceed with caution
1.0-1.5: Good significance, reliable for most trading strategies
1.5-2.0: Strong significance, high-confidence trade setups
2.0+: Very strong significance, institutional-grade levels
Historical Context: The historical trace system shows how support and resistance evolve over time. When current levels align with multiple historical traces, it indicates persistent market memory at those prices, significantly increasing the level's reliability.
The Sequences of FibonacciThe Sequences of Fibonacci - Advanced Multi-Timeframe Confluence Analysis System
THEORETICAL FOUNDATION & MATHEMATICAL INNOVATION
The Sequences of Fibonacci represents a revolutionary approach to market analysis that synthesizes classical Fibonacci mathematics with modern adaptive signal processing. This indicator transcends traditional Fibonacci retracement tools by implementing a sophisticated multi-dimensional confluence detection system that reveals hidden market structure through mathematical precision.
Core Mathematical Framework
Dynamic Fibonacci Grid System:
Unlike static Fibonacci tools, this system calculates highest highs and lowest lows across true Fibonacci sequence periods (8, 13, 21, 34, 55 bars) creating a dynamic grid of mathematical support and resistance levels that adapt to market structure in real-time.
Multi-Dimensional Confluence Detection:
The engine employs advanced mathematical clustering algorithms to identify areas where multiple derived Fibonacci retracement levels (0.382, 0.500, 0.618) from different timeframe perspectives converge. These "Confluence Zones" are mathematically classified by strength:
- CRITICAL Zones: 8+ converging Fibonacci levels
- HIGH Zones: 6-7 converging levels
- MEDIUM Zones: 4-5 converging levels
- LOW Zones: 3+ converging levels
Adaptive Signal Processing Architecture:
The system implements adaptive Stochastic RSI calculations with dynamic overbought/oversold levels that adjust to recent market volatility rather than using fixed thresholds. This prevents false signals during changing market conditions.
COMPREHENSIVE FEATURE ARCHITECTURE
Quantum Field Visualization System
Dynamic Price Field Mathematics:
The Quantum Field creates adaptive price channels based on EMA center points and ATR-based amplitude calculations, influenced by the Unified Field metric. This visualization system helps traders understand:
- Expected price volatility ranges
- Potential overextension zones
- Mathematical pressure points in market structure
- Dynamic support/resistance boundaries
Field Amplitude Calculation:
Field Amplitude = ATR × (1 + |Unified Field| / 10)
The system generates three quantum levels:
- Q⁰ Level: 0.618 × Field Amplitude (Primary channel)
- Q¹ Level: 1.0 × Field Amplitude (Secondary boundary)
- Q² Level: 1.618 × Field Amplitude (Extreme extension)
Advanced Market Analysis Dashboard
Unified Field Analysis:
A composite metric combining:
- Price momentum (40% weighting)
- Volume momentum (30% weighting)
- Trend strength (30% weighting)
Market Resonance Calculation:
Measures price-volume correlation over 14 periods to identify harmony between price action and volume participation.
Signal Quality Assessment:
Synthesizes Unified Field, Market Resonance, and RSI positioning to provide real-time evaluation of setup potential.
Tiered Signal Generation Logic
Tier 1 Signals (Highest Conviction):
Require ALL conditions:
- Adaptive StochRSI setup (exiting dynamic OB/OS levels)
- Classic StochRSI divergence confirmation
- Strong reversal bar pattern (adaptive ATR-based sizing)
- Level rejection from Confluence Zone or Fibonacci level
- Supportive Unified Field context
Tier 2 Signals (Enhanced Opportunity Detection):
Generated when Tier 1 conditions aren't met but exceptional circumstances exist:
- Divergence candidate patterns (relaxed divergence requirements)
- Exceptionally strong reversal bars at critical levels
- Enhanced level rejection criteria
- Maintained context filtering
Intelligent Visualization Features
Fractal Matrix Grid:
Multi-layer visualization system displaying:
- Shadow Layer: Foundational support (width 5)
- Glow Layer: Core identification (width 3, white)
- Quantum Layer: Mathematical overlay (width 1, dotted)
Smart Labeling System:
Prevents overlap using ATR-based minimum spacing while providing:
- Fibonacci period identification
- Topological complexity classification (0, I, II, III)
- Exact price levels
- Strength indicators (○ ◐ ● ⚡)
Wick Pressure Analysis:
Dynamic visualization showing momentum direction through:
- Multi-beam projection lines
- Particle density effects
- Progressive transparency for natural flow
- Strength-based sizing adaptation
PRACTICAL TRADING IMPLEMENTATION
Signal Interpretation Framework
Entry Protocol:
1. Confluence Zone Approach: Monitor price approaching High/Critical confluence zones
2. Adaptive Setup Confirmation: Wait for StochRSI to exit adaptive OB/OS levels
3. Divergence Verification: Confirm classic or candidate divergence patterns
4. Reversal Bar Assessment: Validate strong rejection using adaptive ATR criteria
5. Context Evaluation: Ensure Unified Field provides supportive environment
Risk Management Integration:
- Stop Placement: Beyond rejected confluence zone or Fibonacci level
- Position Sizing: Based on signal tier and confluence strength
- Profit Targets: Next significant confluence zone or quantum field boundary
Adaptive Parameter System
Dynamic StochRSI Levels:
Unlike fixed 80/20 levels, the system calculates adaptive OB/OS based on recent StochRSI range:
- Adaptive OB: Recent minimum + (range × OB percentile)
- Adaptive OS: Recent minimum + (range × OS percentile)
- Lookback Period: Configurable 20-100 bars for range calculation
Intelligent ATR Adaptation:
Bar size requirements adjust to market volatility:
- High Volatility: Reduced multiplier (bars naturally larger)
- Low Volatility: Increased multiplier (ensuring significance)
- Base Multiplier: 0.6× ATR with adaptive scaling
Optimization Guidelines
Timeframe-Specific Settings:
Scalping (1-5 minutes):
- Fibonacci Rejection Sensitivity: 0.3-0.8
- Confluence Threshold: 2-3 levels
- StochRSI Lookback: 20-30 bars
Day Trading (15min-1H):
- Fibonacci Rejection Sensitivity: 0.5-1.2
- Confluence Threshold: 3-4 levels
- StochRSI Lookback: 40-60 bars
Swing Trading (4H-1D):
- Fibonacci Rejection Sensitivity: 1.0-2.0
- Confluence Threshold: 4-5 levels
- StochRSI Lookback: 60-80 bars
Asset-Specific Optimization:
Cryptocurrency:
- Higher rejection sensitivity (1.0-2.5) for volatile conditions
- Enable Tier 2 signals for increased opportunity detection
- Shorter adaptive lookbacks for rapid market changes
Forex Major Pairs:
- Moderate sensitivity (0.8-1.5) for stable trending
- Focus on Higher/Critical confluence zones
- Longer lookbacks for institutional flow detection
Stock Indices:
- Conservative sensitivity (0.5-1.0) for institutional participation
- Standard confluence thresholds
- Balanced adaptive parameters
IMPORTANT USAGE CONSIDERATIONS
Realistic Performance Expectations
This indicator provides probabilistic advantages based on mathematical confluence analysis, not guaranteed outcomes. Signal quality varies with market conditions, and proper risk management remains essential regardless of signal tier.
Understanding Adaptive Features:
- Adaptive parameters react to historical data, not future market conditions
- Dynamic levels adjust to past volatility patterns
- Signal quality reflects mathematical alignment probability, not certainty
Market Context Awareness:
- Strong trending markets may produce fewer reversal signals
- Range-bound conditions typically generate more confluence opportunities
- News events and fundamental factors can override technical analysis
Educational Value
Mathematical Concepts Introduced:
- Multi-dimensional confluence analysis
- Adaptive signal processing techniques
- Dynamic parameter optimization
- Mathematical field theory applications in trading
- Advanced Fibonacci sequence applications
Skill Development Benefits:
- Understanding market structure through mathematical lens
- Recognition of multi-timeframe confluence principles
- Appreciation for adaptive vs. static analysis methods
- Integration of classical Fibonacci with modern signal processing
UNIQUE INNOVATIONS
First-Ever Implementations
1. True Fibonacci Sequence Periods: First indicator using authentic Fibonacci numbers (8,13,21,34,55) for timeframe analysis
2. Mathematical Confluence Clustering: Advanced algorithm identifying true Fibonacci level convergence
3. Adaptive StochRSI Boundaries: Dynamic OB/OS levels replacing fixed thresholds
4. Tiered Signal Architecture: Democratic signal weighting with quality classification
5. Quantum Field Price Visualization: Mathematical field representation of price dynamics
Visualization Breakthroughs
- Multi-Layer Fibonacci Grid: Three-layer rendering with intelligent spacing
- Dynamic Confluence Zones: Strength-based color coding and sizing
- Adaptive Parameter Display: Real-time visualization of dynamic calculations
- Mathematical Field Effects: Quantum-inspired price channel visualization
- Progressive Transparency Systems: Natural visual flow without chart clutter
COMPREHENSIVE DASHBOARD SYSTEM
Multi-Size Display Options
Small Dashboard: Core metrics for mobile/limited screen space
Normal Dashboard: Balanced information density for standard desktop use
Large Dashboard: Complete analysis suite including adaptive parameter values
Real-Time Metrics Tracking
Market Analysis Section:
- Unified Field strength with visual meter
- Market Resonance percentage
- Signal Quality assessment with emoji indicators
- Market Bias classification (Bullish/Bearish/Neutral)
Confluence Intelligence:
- Total active zones count
- High/Critical zone identification
- Nearest zone distance and strength
- Price-to-zone ATR measurement
Adaptive Parameters (Large Dashboard):
- Current StochRSI OB/OS levels
- Active ATR multiplier for bar sizing
- Volatility ratio for adaptive scaling
- Real-time StochRSI positioning
TECHNICAL SPECIFICATIONS
Pine Script Version: v5 (Latest)
Calculation Method: Real-time with confirmed bar processing
Maximum Objects: 500 boxes, 500 lines, 500 labels
Dashboard Positions: 4 corner options with size selection
Visual Themes: Quantum, Holographic, Crystalline, Plasma
Alert Integration: Complete alert system for all signal types
Performance Optimizations:
- Efficient confluence zone calculation using advanced clustering
- Smart label spacing prevents overlap
- Progressive transparency for visual clarity
- Memory-optimized array management
EDUCATIONAL FRAMEWORK
Learning Progression
Beginner Level:
- Understanding Fibonacci sequence applications
- Recognition of confluence zone concepts
- Basic signal interpretation
- Dashboard metric comprehension
Intermediate Level:
- Adaptive parameter optimization
- Multi-timeframe confluence analysis
- Signal quality assessment techniques
- Risk management integration
Advanced Level:
- Mathematical field theory applications
- Custom parameter optimization strategies
- Market regime adaptation techniques
- Professional trading system integration
DEVELOPMENT ACKNOWLEDGMENT
Special acknowledgment to @AlgoTrader90 - the foundational concepts of this system came from him and we developed it through a collaborative discussions about multi-timeframe Fibonacci analysis. While the original framework came from AlgoTrader90's innovative approach, this implementation represents a complete evolution of the logic with enhanced mathematical precision, adaptive parameters, and sophisticated signal filtering to deliver meaningful, actionable trading signals.
CONCLUSION
The Sequences of Fibonacci represents a quantum leap in technical analysis, successfully merging classical Fibonacci mathematics with cutting-edge adaptive signal processing. Through sophisticated confluence detection, intelligent parameter adaptation, and comprehensive market analysis, this system provides traders with unprecedented insight into market structure and potential reversal points.
The mathematical foundation ensures lasting relevance while the adaptive features maintain effectiveness across changing market conditions. From the dynamic Fibonacci grid to the quantum field visualization, every component reflects a commitment to mathematical precision, visual elegance, and practical utility.
Whether you're a beginner seeking to understand market confluence or an advanced trader requiring sophisticated analytical tools, this system provides the mathematical framework for informed decision-making based on time-tested Fibonacci principles enhanced with modern computational techniques.
Trade with mathematical precision. Trade with the power of confluence. Trade with The Sequences of Fibonacci.
"Mathematics is the language with which God has written the universe. In markets, Fibonacci sequences reveal the hidden harmonies that govern price movement, and those who understand these mathematical relationships hold the key to anticipating market behavior."
* Galileo Galilei (adapted for modern markets)
— Dskyz, Trade with insight. Trade with anticipation.
DCA Investment Tracker Pro [tradeviZion]DCA Investment Tracker Pro: Educational DCA Analysis Tool
An educational indicator that helps analyze Dollar-Cost Averaging strategies by comparing actual performance with historical data calculations.
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💡 Why I Created This Indicator
As someone who practices Dollar-Cost Averaging, I was frustrated with constantly switching between spreadsheets, calculators, and charts just to understand how my investments were really performing. I wanted to see everything in one place - my actual performance, what I should expect based on historical data, and most importantly, visualize where my strategy could take me over the long term .
What really motivated me was watching friends and family underestimate the incredible power of consistent investing. When Napoleon Bonaparte first learned about compound interest, he reportedly exclaimed "I wonder it has not swallowed the world" - and he was right! Yet most people can't visualize how their $500 monthly contributions today could become substantial wealth decades later.
Traditional DCA tracking tools exist, but they share similar limitations:
Require manual data entry and complex spreadsheets
Use fixed assumptions that don't reflect real market behavior
Can't show future projections overlaid on actual price charts
Lose the visual context of what's happening in the market
Make compound growth feel abstract rather than tangible
I wanted to create something different - a tool that automatically analyzes real market history, detects volatility periods, and shows you both current performance AND educational projections based on historical patterns right on your TradingView charts. As Warren Buffett said: "Someone's sitting in the shade today because someone planted a tree a long time ago." This tool helps you visualize your financial tree growing over time.
This isn't just another calculator - it's a visualization tool that makes the magic of compound growth impossible to ignore.
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🎯 What This Indicator Does
This educational indicator provides DCA analysis tools. Users can input investment scenarios to study:
Theoretical Performance: Educational calculations based on historical return data
Comparative Analysis: Study differences between actual and theoretical scenarios
Historical Projections: Theoretical projections for educational analysis (not predictions)
Performance Metrics: CAGR, ROI, and other analytical metrics for study
Historical Analysis: Calculates historical return data for reference purposes
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🚀 Key Features
Volatility-Adjusted Historical Return Calculation
Analyzes 3-20 years of actual price data for any symbol
Automatically detects high-volatility stocks (meme stocks, growth stocks)
Uses median returns for volatile stocks, standard CAGR for stable stocks
Provides conservative estimates when extreme outlier years are detected
Smart fallback to manual percentages when data insufficient
Customizable Performance Dashboard
Educational DCA performance analysis with compound growth calculations
Customizable table sizing (Tiny to Huge text options)
9 positioning options (Top/Middle/Bottom + Left/Center/Right)
Theme-adaptive colors (automatically adjusts to dark/light mode)
Multiple display layout options
Future Projection System
Visual future growth projections
Timeframe-aware calculations (Daily/Weekly/Monthly charts)
1-30 year projection options
Shows projected portfolio value and total investment amounts
Investment Insights
Performance vs benchmark comparison
ROI from initial investment tracking
Monthly average return analysis
Investment milestone alerts (25%, 50%, 100% gains)
Contribution tracking and next milestone indicators
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📊 Step-by-Step Setup Guide
1. Investment Settings 💰
Initial Investment: Enter your starting lump sum (e.g., $60,000)
Monthly Contribution: Set your regular DCA amount (e.g., $500/month)
Return Calculation: Choose "Auto (Stock History)" for real data or "Manual" for fixed %
Historical Period: Select 3-20 years for auto calculations (default: 10 years)
Start Year: When you began investing (e.g., 2020)
Current Portfolio Value: Your actual portfolio worth today (e.g., $150,000)
2. Display Settings 📊
Table Sizes: Choose from Tiny, Small, Normal, Large, or Huge
Table Positions: 9 options - Top/Middle/Bottom + Left/Center/Right
Visibility Toggles: Show/hide Main Table and Stats Table independently
3. Future Projection 🔮
Enable Projections: Toggle on to see future growth visualization
Projection Years: Set 1-30 years ahead for analysis
Live Example - NASDAQ:META Analysis:
Settings shown: $60K initial + $500/month + Auto calculation + 10-year history + 2020 start + $150K current value
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🔬 Pine Script Code Examples
Core DCA Calculations:
// Calculate total invested over time
months_elapsed = (year - start_year) * 12 + month - 1
total_invested = initial_investment + (monthly_contribution * months_elapsed)
// Compound growth formula for initial investment
theoretical_initial_growth = initial_investment * math.pow(1 + annual_return, years_elapsed)
// Future Value of Annuity for monthly contributions
monthly_rate = annual_return / 12
fv_contributions = monthly_contribution * ((math.pow(1 + monthly_rate, months_elapsed) - 1) / monthly_rate)
// Total expected value
theoretical_total = theoretical_initial_growth + fv_contributions
Volatility Detection Logic:
// Detect extreme years for volatility adjustment
extreme_years = 0
for i = 1 to historical_years
yearly_return = ((price_current / price_i_years_ago) - 1) * 100
if yearly_return > 100 or yearly_return < -50
extreme_years += 1
// Use median approach for high volatility stocks
high_volatility = (extreme_years / historical_years) > 0.2
calculated_return = high_volatility ? median_of_returns : standard_cagr
Performance Metrics:
// Calculate key performance indicators
absolute_gain = actual_value - total_invested
total_return_pct = (absolute_gain / total_invested) * 100
roi_initial = ((actual_value - initial_investment) / initial_investment) * 100
cagr = (math.pow(actual_value / initial_investment, 1 / years_elapsed) - 1) * 100
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📊 Real-World Examples
See the indicator in action across different investment types:
Stable Index Investments:
AMEX:SPY (SPDR S&P 500) - Shows steady compound growth with standard CAGR calculations
Classic DCA success story: $60K initial + $500/month starting 2020. The indicator shows SPY's historical 10%+ returns, demonstrating how consistent broad market investing builds wealth over time. Notice the smooth theoretical growth line vs actual performance tracking.
MIL:VUAA (Vanguard S&P 500 UCITS) - Shows both data limitation and solution approaches
Data limitation example: VUAA shows "Manual (Auto Failed)" and "No Data" when default 10-year historical setting exceeds available data. The indicator gracefully falls back to manual percentage input while maintaining all DCA calculations and projections.
MIL:VUAA (Vanguard S&P 500 UCITS) - European ETF with successful 5-year auto calculation
Solution demonstration: By adjusting historical period to 5 years (matching available data), VUAA auto calculation works perfectly. Shows how users can optimize settings for newer assets. European market exposure with EUR denomination, demonstrating DCA effectiveness across different markets and currencies.
NYSE:BRK.B (Berkshire Hathaway) - Quality value investment with Warren Buffett's proven track record
Value investing approach: Berkshire Hathaway's legendary performance through DCA lens. The indicator demonstrates how quality companies compound wealth over decades. Lower volatility than tech stocks = standard CAGR calculations used.
High-Volatility Growth Stocks:
NASDAQ:NVDA (NVIDIA Corporation) - Demonstrates volatility-adjusted calculations for extreme price swings
High-volatility example: NVIDIA's explosive AI boom creates extreme years that trigger volatility detection. The indicator automatically switches to "Median (High Vol): 50%" calculations for conservative projections, protecting against unrealistic future estimates based on outlier performance periods.
NASDAQ:TSLA (Tesla) - Shows how 10-year analysis can stabilize volatile tech stocks
Stable long-term growth: Despite Tesla's reputation for volatility, the 10-year historical analysis (34.8% CAGR) shows consistent enough performance that volatility detection doesn't trigger. Demonstrates how longer timeframes can smooth out extreme periods for more reliable projections.
NASDAQ:META (Meta Platforms) - Shows stable tech stock analysis using standard CAGR calculations
Tech stock with stable growth: Despite being a tech stock and experiencing the 2022 crash, META's 10-year history shows consistent enough performance (23.98% CAGR) that volatility detection doesn't trigger. The indicator uses standard CAGR calculations, demonstrating how not all tech stocks require conservative median adjustments.
Notice how the indicator automatically detects high-volatility periods and switches to median-based calculations for more conservative projections, while stable investments use standard CAGR methods.
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📈 Performance Metrics Explained
Current Portfolio Value: Your actual investment worth today
Expected Value: What you should have based on historical returns (Auto) or your target return (Manual)
Total Invested: Your actual money invested (initial + all monthly contributions)
Total Gains/Loss: Absolute dollar difference between current value and total invested
Total Return %: Percentage gain/loss on your total invested amount
ROI from Initial Investment: How your starting lump sum has performed
CAGR: Compound Annual Growth Rate of your initial investment (Note: This shows initial investment performance, not full DCA strategy)
vs Benchmark: How you're performing compared to the expected returns
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⚠️ Important Notes & Limitations
Data Requirements: Auto mode requires sufficient historical data (minimum 3 years recommended)
CAGR Limitation: CAGR calculation is based on initial investment growth only, not the complete DCA strategy
Projection Accuracy: Future projections are theoretical and based on historical returns - actual results may vary
Timeframe Support: Works ONLY on Daily (1D), Weekly (1W), and Monthly (1M) charts - no other timeframes supported
Update Frequency: Update "Current Portfolio Value" regularly for accurate tracking
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📚 Educational Use & Disclaimer
This analysis tool can be applied to various stock and ETF charts for educational study of DCA mathematical concepts and historical performance patterns.
Study Examples: Can be used with symbols like AMEX:SPY , NASDAQ:QQQ , AMEX:VTI , NASDAQ:AAPL , NASDAQ:MSFT , NASDAQ:GOOGL , NASDAQ:AMZN , NASDAQ:TSLA , NASDAQ:NVDA for learning purposes.
EDUCATIONAL DISCLAIMER: This indicator is a study tool for analyzing Dollar-Cost Averaging strategies. It does not provide investment advice, trading signals, or guarantees. All calculations are theoretical examples for educational purposes only. Past performance does not predict future results. Users should conduct their own research and consult qualified financial professionals before making any investment decisions.
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© 2025 TradeVizion. All rights reserved.
$ADD LevelsThis Pine Script is designed to track and visualize the NYSE Advance-Decline Line (ADD). The Advance-Decline Line is a popular market breadth indicator, showing the difference between advancing and declining stocks on the NYSE. It’s often used to gauge overall market sentiment and strength.
1. //@version=5
This line tells TradingView to use Pine Script v5, the latest and most powerful version of Pine.
2. indicator(" USI:ADD Levels", overlay=false)
• This creates a new indicator called ” USI:ADD Levels”.
• overlay=false means it will appear in a separate pane, not on the main price chart.
3. add = request.security(...)
This fetches real-time data from the symbol USI:ADD (Advance-Decline Line) using a 1-minute timeframe. You can change the timeframe if needed.
add_symbol = input.symbol(" USI:ADD ", "Market Breadth Symbol")
add = request.security(add_symbol, "1", close)
4. Key Thresholds
These define the market sentiment zones:
Zone. Value. Meaning
Overbought +1500 Extremely bullish
Bullish +1000 Generally bullish trend
Neutral ±500 Choppy, unclear market
Bearish -1000 Generally bearish trend
Oversold -1500 Extremely bearish
5. Plot the ADD Line hline(...)
Draws static lines at +1500, +1000, +500, -500, -1000, -1500 for reference so you can visually assess where ADD stands.
6. Horizontal Threshold Lines bgcolor(...)
• Green background if ADD > +1500 → extremely bullish.
• Red background if ADD < -1500 → extremely bearish.
7. Background Highlights alertcondition(...)
• Green background if ADD > +1500 → extremely bullish.
• Red background if ADD < -1500 → extremely bearish.
8. Alert Conditions. alertcondition(...)
Lets you create automatic alerts for:
• USI:ADD being very high or low.
• Crosses above +1000 (bullish trigger).
• Crosses below -1000 (bearish trigger).
You can use these to trigger trades or monitor sentiment shifts.
Summary: When to Use It
• Use this script in a market breadth dashboard.
• Combine it with price action and volume analysis.
• Monitor for ADD crosses to signal potential market reversals or momentum.
