Volume Weighted Standard DeviationThis indicator calculates the Standard Deviation and decomposes total volatility into its core components, allowing to analyze the underlying character of the market.
Key Features:
Volatility Decomposition: The indicator separates volatility based on the 'Estimate Bar Statistics' option.
Standard Mode (Estimate Bar Statistics = OFF): Calculates a simple (Volume-Weighted) Standard Deviation of the selected Source.
Decomposition Mode (Estimate Bar Statistics = ON): The indicator uses a statistical model ('Estimator') to calculate within-bar volatility (choppiness, noise) and between-bar volatility (trending moves). (Assumption: In this mode, the Source input is ignored, and an estimated mean for each bar is used instead).
Dual Display Modes: The indicator offers two modes to visualize this information:
Absolute Mode: Plots the total standard deviation as a stacked area chart, showing the proportional contribution of the 'Between' and 'Within' components.
Normalized Mode: Plots the direct ratio of each component's variance (from 0 to 1), making it easy to identify which character is dominant.
Calculation Options: The volatility calculation can be optionally Volume weighted. An optional Normalize Volatility setting performs the calculation in logarithmic space, making volatility comparable across different price scales.
Volatility Pivot Detection: Includes a built-in pivot detector that identifies significant turning points (highs and lows) in the total volatility line. (Note: This is only visible in 'Absolute Mode').
Note on Confirmation (Lag): Pivot signals are confirmed using a lookback method. A pivot is only plotted after the Pivot Right Bars input has passed, which introduces an inherent lag.
Multi-Timeframe (MTF) Capability:
MTF Volatility Lines: The volatility lines can be calculated on a higher timeframe, with standard options to handle gaps (Fill Gaps) and prevent repainting (Wait for...).
Limitation: The Pivot detection (Calculate Pivots) is disabled if a Higher Timeframe (HTF) is selected.
Integrated Alerts: Includes 6 alerts for:
Volatility character changes (e.g., 'Trend Character Emerging', 'Character Change from Trend to Choppy').
Volatility pivot (high or low) detection.
DISCLAIMER
For Informational/Educational Use Only: This indicator is provided for informational and educational purposes only. It does not constitute financial, investment, or trading advice, nor is it a recommendation to buy or sell any asset.
Use at Your Own Risk: All trading decisions you make based on the information or signals generated by this indicator are made solely at your own risk.
No Guarantee of Performance: Past performance is not an indicator of future results. The author makes no guarantee regarding the accuracy of the signals or future profitability.
No Liability: The author shall not be held liable for any financial losses or damages incurred directly or indirectly from the use of this indicator.
Signals Are Not Recommendations: The alerts and visual signals (e.g., crossovers) generated by this tool are not direct recommendations to buy or sell. They are technical observations for your own analysis and consideration.
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Volume Weighted Average True RangeThis indicator calculates a customizable version of the Average True Range (ATR), a tool for measuring market volatility. It enhances the standard ATR with volume weighting, a dual-smoothing process, normalization, and volatility pivot detection.
Key Features:
Volume Weighting: An option (Volume weighted) allows for volume to be incorporated into the volatility calculation. This provides a measure of "volume-adjusted" volatility that is more responsive to significant market activity.
Dual Smoothing Process: For noise reduction, the indicator employs a two-stage smoothing process. It first calculates a smoothed True Range (TR) over a user-defined period (TR Length) before applying the final ATR moving average (ATR Length & ATR Smooth).
Normalization (Percentage Volatility): An optional 'Normalize' mode calculates the ATR as a percentage of the price. This allows for consistent volatility comparison across different assets and over long time periods.
Volatility Pivot Detection: The indicator includes a built-in pivot detector that identifies significant turning points (highs and lows) in the ATR line itself, signaling potential shifts in volatility.
Note on Confirmation (Lag): Pivot signals are confirmed using a lookback method. A pivot is only plotted after the Pivot Right Bars input has passed. This is essential for ensuring the signal is non-repainting but introduces an inherent lag.
Multi-Timeframe (MTF) Capability:
MTF ATR Line: The ATR line itself can be calculated on a different timeframe, with standard options to handle gaps (Fill Gaps) and prevent repainting (Wait for...).
Limitation: The Pivot detection (Calculate Pivots) is disabled if a Higher Timeframe (HTF) is selected.
Integrated Alerts: Includes alerts that trigger when a new volatility pivot (high or low) is detected in the ATR line.
DISCLAIMER
For Informational/Educational Use Only: This indicator is provided for informational and educational purposes only. It does not constitute financial, investment, or trading advice, nor is it a recommendation to buy or sell any asset.
Use at Your Own Risk: All trading decisions you make based on the information or signals generated by this indicator are made solely at your own risk.
No Guarantee of Performance: Past performance is not an indicator of future results. The author makes no guarantee regarding the accuracy of the signals or future profitability.
No Liability: The author shall not be held liable for any financial losses or damages incurred directly or indirectly from the use of this indicator.
Signals Are Not Recommendations: The alerts and visual signals (e.g., crossovers) generated by this tool are not direct recommendations to buy or sell. They are technical observations for your own analysis and consideration.
Volume Weighted Price OscillatorThis indicator calculates the Percentage Price Oscillator (PPO), a momentum oscillator similar to the MACD. It displays the distance between two moving averages as a percentage, making it comparable across different assets. This implementation enhances the PPO with optional volume weighting and a built-in divergence engine.
Key Features:
Customizable MA & Volume Weighting: Both the fast and slow moving averages (and the signal line) can be customized using different MA types (e.g., EMA, SMA, WMA). An option (Volume weighted) applies volume weighting to all three MAs.
MACD-Style Display: Provides the three core components: the PPO line (momentum), a signal line (trigger), and a histogram (momentum acceleration). The histogram is color-coded to show increasing or decreasing momentum.
Full Divergence Suite (Class A, B, C): A built-in divergence engine automatically detects and plots all three major divergence classes between price and the PPO line:
Regular (A): Signals potential trend reversals.
Hidden (B): Signals potential trend continuations.
Exaggerated (C): Signals weakness at double tops/bottoms.
Divergence Filtering and Visualization:
Price Tolerance Filter: Divergence detection is enhanced with a percentage-based price tolerance (pivPrcTol) to filter out insignificant market noise.
Persistent Visualization: Divergence markers are plotted for the entire duration of the signal and are visually anchored to the PPO level of the confirming pivot.
Note on Confirmation (Lag): Divergence signals rely on a pivot confirmation method to ensure they do not repaint.
The Start of a- divergence is only detected after the confirming pivot is fully formed (a delay based on Pivot Right Bars).
The End of a divergence is detected either instantly (if the signal is invalidated by price action) or with a delay (when a new, non-divergent pivot is confirmed).
Multi-Timeframe (MTF) Capability:
MTF PPO Lines: The PPO, signal line, and histogram can be calculated on a higher timeframe, with standard options to handle gaps (Fill Gaps) and prevent repainting (Wait for...).
Limitation: The Divergence detection engine (pivDiv) is disabled if a timeframe other than the chart's timeframe is selected. Divergences are only calculated on the active chart timeframe.
Integrated Alerts: Includes 18 comprehensive alerts for:
The start and end of all 6 divergence types.
The PPO line crossing its signal line.
The PPO line crossing the zero line.
The histogram changing direction (reverting).
DISCLAIMER
For Informational/Educational Use Only: This indicator is provided for informational and educational purposes only. It does not constitute financial, investment, or trading advice, nor is it a recommendation to buy or sell any asset.
Use at Your Own Risk: All trading decisions you make based on the information or signals generated by this indicator are made solely at your own risk.
No Guarantee of Performance: Past performance is not an indicator of future results. The author makes no guarantee regarding the accuracy of the signals or future profitability.
No Liability: The author shall not be held liable for any financial losses or damages incurred directly or indirectly from the use of this indicator.
Signals Are Not Recommendations: The alerts and visual signals (e.g., crossovers) generated by this tool are not direct recommendations to buy or sell. They are technical observations for your own analysis and consideration.
Volume Weighted Stochastic RSIThis indicator calculates the Stochastic RSI, enhanced with optional Volume Weighting (VWStochRSI). It measures the level of a (Volume-Weighted) RSI relative to its high-low range over a set period, providing a sensitive momentum oscillator.
Key Features:
Volume-Weighted Core: The indicator is built on a Relative Strength Index (RSI) that can be optionally volume-weighted (Volume weighted).
Customizable Smoothing: The %K and %D lines are smoothed using a customizable moving average. The MA type (Smooth Method) can be selected (e.g., EMA, SMA, WMA) and will also be volume-weighted if the main Volume weighted option is enabled.
Full Divergence Suite (Class A, B, C): The primary feature is the integrated divergence engine. It automatically detects and plots all three major types of divergences:
Regular (A): Signals potential trend reversals.
Hidden (B): Signals potential trend continuations.
Exaggerated (C): Signals weakness at double tops/bottoms.
Divergence Filtering and Visualization:
Price Tolerance Filter: Divergence detection is enhanced with a percentage-based price tolerance (pivPrcTol) to filter out insignificant market noise.
Persistent Visualization: Divergence markers are plotted for the entire duration of the signal and are visually anchored to the %K line level of the confirming pivot.
Note on Confirmation (Lag): Divergence signals rely on a pivot confirmation method to ensure they do not repaint.
The Start of a- divergence is only detected after the confirming pivot is fully formed (a delay based on Pivot Right Bars).
The End of a divergence is detected either instantly (if the signal is invalidated by price action) or with a delay (when a new, non-divergent pivot is confirmed).
Multi-Timeframe (MTF) Capability:
MTF VWStochRSI Lines: The %K and %D lines can be calculated on a higher timeframe, with standard options to handle gaps (Fill Gaps) and prevent repainting (Wait for...).
Limitation: The Divergence detection engine (pivDiv) is disabled if a timeframe other than the chart's timeframe is selected. Divergences are only calculated on the active chart timeframe.
Integrated Alerts: Includes 20 comprehensive alerts for:
The start and end of all 6 divergence types.
The %K line crossing the %D line.
The %K line crossing the Overbought, Oversold, or 50-level lines.
DISCLAIMER
For Informational/Educational Use Only: This indicator is provided for informational and educational purposes only. It does not constitute financial, investment, or trading advice, nor is it a recommendation to buy or sell any asset.
Use at Your Own Risk: All trading decisions you make based on the information or signals generated by this indicator are made solely at your own risk.
No Guarantee of Performance: Past performance is not an indicator of future results. The author makes no guarantee regarding the accuracy of the signals or future profitability.
No Liability: The author shall not be held liable for any financial losses or damages incurred directly or indirectly from the use of this indicator.
Signals Are Not Recommendations: The alerts and visual signals (e.g., crossovers) generated by this tool are not direct recommendations to buy or sell. They are technical observations for your own analysis and consideration.
Volume Weighted Relative Strength IndexThis indicator calculates the Relative Strength Index (RSI) and enhances it with optional volume weighting (VWRSI). It also includes a customizable signal line and a built-in divergence detection engine.
Key Features:
Volume-Weighted Calculation: An option (Volume weighted) allows for volume to be incorporated into the calculation of both the RSI itself and its moving average signal line, making the oscillator more sensitive to high-volume price changes.
Customizable Signal Line: Includes an optional moving average of the VWRSI, which serves as a signal line. The type of MA (Smooth Method) and its length can be customized.
Full Divergence Suite (Class A, B, C): The primary feature is the integrated divergence engine. It automatically detects and plots all three major types of divergences:
Regular (A): Signals potential trend reversals.
Hidden (B): Signals potential trend continuations.
Exaggerated (C): Signals weakness at double tops/bottoms.
Divergence Filtering and Visualization:
Price Tolerance Filter: Divergence detection is enhanced with a percentage-based price tolerance (pivPrcTol) to filter out insignificant market noise.
Persistent Visualization: Divergence markers are plotted for the entire duration of the signal and are visually anchored to the VWRSI level of the confirming pivot.
Note on Confirmation (Lag): Divergence signals rely on a pivot confirmation method to ensure they do not repaint.
The Start of a- divergence is only detected after the confirming pivot is fully formed (a delay based on Pivot Right Bars).
The End of a divergence is detected either instantly (if the signal is invalidated by price action) or with a delay (when a new, non-divergent pivot is confirmed).
Multi-Timeframe (MTF) Capability:
MTF VWRSI Line: The VWRSI and its signal line can be calculated on a higher timeframe, with standard options to handle gaps (Fill Gaps) and prevent repainting (Wait for...).
Limitation: The Divergence detection engine (pivDiv) is disabled if a timeframe other than the chart's timeframe is selected. Divergences are only calculated on the active chart timeframe.
Integrated Alerts: Includes 20 comprehensive alerts for:
The start and end of all 6 divergence types.
The VWRSI crossing its signal line.
The VWRSI crossing the Overbought, Oversold, or 50-level lines.
DISCLAIMER
For Informational/Educational Use Only: This indicator is provided for informational and educational purposes only. It does not constitute financial, investment, or trading advice, nor is it a recommendation to buy or sell any asset.
Use at Your Own Risk: All trading decisions you make based on the information or signals generated by this indicator are made solely at your own risk.
No Guarantee of Performance: Past performance is not an indicator of future results. The author makes no guarantee regarding the accuracy of the signals or future profitability.
No Liability: The author shall not be held liable for any financial losses or damages incurred directly or indirectly from the use of this indicator.
Signals Are Not Recommendations: The alerts and visual signals (e.g., crossovers) generated by this tool are not direct recommendations to buy or sell. They are technical observations for your own analysis and consideration.
Relative Distance to Moving AverageThis indicator calculates the Relative Distance to a Moving Average (RDMA), a momentum oscillator that measures how overextended a price is from its moving average baseline. It expresses this distance as a percentage, oscillating around a zero line. High positive values may indicate overbought conditions, while large negative values may suggest oversold conditions.
Key Features:
Customizable MA Baseline: The oscillator's baseline is a moving average. Users can select from a wide range of MA types (e.g., EMA, SMA, WMA) and apply volume weighting (Volume weighted) for enhanced responsiveness.
Normalization (Geometric Average): Includes an optional 'Normalize' mode. When enabled, the indicator uses a Geometric Moving Average (GMA) as its baseline and measures the percentage distance from this compound growth average, making it suitable for exponential markets.
Full Divergence Suite (Class A, B, C): The indicator's primary feature is its integrated divergence engine. It automatically detects and plots all three major divergence classes between price and the RDMA:
Regular (A): Signals potential trend exhaustion and reversals.
Hidden (B): Signals potential trend continuations during pullbacks.
Exaggerated (C): Signals weakness at double tops/bottoms.
Divergence Filtering and Visualization:
Price Tolerance Filter: Divergence detection is enhanced with a percentage-based price tolerance (pivPrcTol) to filter out insignificant market noise.
Persistent Visualization: Divergence markers are plotted for the entire duration of the signal and are visually anchored to the RDMA level of the confirming pivot.
Note on Confirmation (Lag): Divergence signals rely on a pivot confirmation method to ensure they do not repaint.
The Start of a- divergence is only detected after the confirming pivot is fully formed (a delay based on Pivot Right Bars).
The End of a divergence is detected either instantly (if the signal is invalidated by price action) or with a delay (when a new, non-divergent pivot is confirmed).
Multi-Timeframe (MTF) Capability:
MTF RDMA Line: The RDMA oscillator itself can be calculated on a higher timeframe, with standard options to handle gaps (Fill Gaps) and prevent repainting (Wait for...).
Limitation: The Divergence detection engine (pivDiv) is disabled if a timeframe other than the chart's timeframe is selected. Divergences are only calculated on the active chart timeframe.
Integrated Alerts: Includes 14 comprehensive alerts for:
The start and end of all 6 divergence types.
The RDMA oscillator crossing the zero line.
DISCLAIMER
For Informational/Educational Use Only: This indicator is provided for informational and educational purposes only. It does not constitute financial, investment, or trading advice, nor is it a recommendation to buy or sell any asset.
Use at Your Own Risk: All trading decisions you make based on the information or signals generated by this indicator are made solely at your own risk.
No Guarantee of Performance: Past performance is not an indicator of future results. The author makes no guarantee regarding the accuracy of the signals or future profitability.
No Liability: The author shall not be held liable for any financial losses or damages incurred directly or indirectly from the use of this indicator.
Signals Are Not Recommendations: The alerts and visual signals (e.g., crossovers) generated by this tool are not direct recommendations to buy or sell. They are technical observations for your own analysis and consideration.
Chaikin Money FlowThis indicator provides an implementation of the classic Chaikin Money Flow (CMF), a volume-weighted oscillator designed to measure money flow pressure. It is enhanced with a customizable signal line and a built-in divergence detection engine.
Key Features:
Full Divergence Suite (Class A, B, C): The primary feature is the integrated divergence engine. It automatically detects and plots all three major types of divergences:
Regular (A): Signals potential trend reversals.
Hidden (B): Signals potential trend continuations.
Exaggerated (C): Signals weakness at double tops/bottoms.
Divergence Filtering and Visualization:
Price Tolerance Filter: Divergence detection is enhanced with a percentage-based price tolerance (pivPrcTol) to filter out insignificant market noise, leading to more robust signals.
Persistent Visualization: Divergence markers are plotted for the entire duration of the signal and are visually anchored to the CMF level of the confirming pivot.
Customizable Signal Line: Includes an optional moving average of the CMF, which serves as a signal line. The type of MA (Signal Smoothing) and its length can be customized. This signal line can also be optionally volume-weighted (Volume weighted).
Note on Confirmation (Lag): Divergence signals rely on a pivot confirmation method to ensure they do not repaint.
The Start of a- divergence is only detected after the confirming pivot is fully formed (a delay based on Pivot Right Bars).
The End of a divergence is detected either instantly (if the signal is invalidated by price action) or with a delay (when a new, non-divergent pivot is confirmed).
Multi-Timeframe (MTF) Capability:
MTF CMF & Signal Lines: The CMF and its signal line can be calculated on a higher timeframe, with standard options to handle gaps (Fill Gaps) and prevent repainting (Wait for...).
Limitation: The Divergence detection engine (pivDiv) is disabled if a timeframe other than the chart's timeframe is selected. Divergences are only calculated on the active chart timeframe.
Integrated Alerts: Includes 16 comprehensive alerts for:
The start and end of all 6 divergence types.
The CMF crossing its signal line.
The CMF crossing the zero line.
DISCLAIMER
For Informational/Educational Use Only: This indicator is provided for informational and educational purposes only. It does not constitute financial, investment, or trading advice, nor is it a recommendation to buy or sell any asset.
Use at Your Own Risk: All trading decisions you make based on the information or signals generated by this indicator are made solely at your own risk.
No Guarantee of Performance: Past performance is not an indicator of future results. The author makes no guarantee regarding the accuracy of the signals or future profitability.
No Liability: The author shall not be liable for any financial losses or damages incurred directly or indirectly from the use of this indicator.
Signals Are Not Recommendations: The alerts and visual signals (e.g., crossovers) generated by this tool are not direct recommendations to buy or sell. They are technical observations for your own analysis and consideration.
Accumulation Distribution LineThis indicator provides an implementation of the classic Accumulation/Distribution Line (ADL). It enhances the standard indicator with a built-in divergence detection engine.
Key Features:
Full Divergence Suite (Class A, B, C): The primary feature is the integrated divergence engine. It automatically detects and plots all three major types of divergences:
Regular (A): Signals potential trend reversals.
Hidden (B): Signals potential trend continuations.
Exaggerated (C): Signals weakness at double tops/bottoms.
Divergence Filtering and Visualization:
Price Tolerance Filter: Divergence detection is enhanced with a percentage-based price tolerance (pivPrcTol) to filter out insignificant market noise, leading to more robust signals.
Persistent Visualization: Divergence markers are plotted for the entire duration of the signal and are visually anchored to the ADL level of the confirming pivot.
Note on Confirmation (Lag): Divergence signals rely on a pivot confirmation method to ensure they do not repaint.
The Start of a- divergence is only detected after the confirming pivot is fully formed (a delay based on Pivot Right Bars).
The End of a divergence is detected either instantly (if the signal is invalidated by price action) or with a delay (when a new, non-divergent pivot is confirmed).
Multi-Timeframe (MTF) Capability:
MTF ADL Line: The ADL line itself can be calculated on a higher timeframe, with standard options to handle gaps (Fill Gaps) and prevent repainting (Wait for...).
Limitation: The Divergence detection engine (pivDiv) is disabled if a timeframe other than the chart's timeframe is selected. Divergences are only calculated on the active chart timeframe.
Integrated Alerts: Includes 12 comprehensive alerts that trigger on the start and end of all 6 divergence types (e.g., "Regular Bullish Started", "Regular Bullish Ended").
DISCLAIMER
For Informational/Educational Use Only: This indicator is provided for informational and educational purposes only. It does not constitute financial, investment, or trading advice, nor is it a recommendation to buy or sell any asset.
Use at Your Own Risk: All trading decisions you make based on the information or signals generated by this indicator are made solely at your own risk.
No Guarantee of Performance: Past performance is not an indicator of future results. The author makes no guarantee regarding the accuracy of the signals or future profitability.
No Liability: The author shall not be held liable for any financial losses or damages incurred directly or indirectly from the use of this indicator.
Signals Are Not Recommendations: The alerts and visual signals (e.g., crossovers) generated by this tool are not direct recommendations to buy or sell. They are technical observations for your own analysis and consideration.
On Balance VolumeThis indicator provides an implementation of the classic On Balance Volume (OBV) momentum indicator, enhanced with a built-in divergence detection engine.
Key Features:
Full Divergence Suite (Class A, B, C): The primary feature is the integrated divergence engine. It automatically detects and plots all three major types of divergences:
Regular (A): Signals potential trend reversals.
Hidden (B): Signals potential trend continuations.
Exaggerated (C): Signals weakness at double tops/bottoms.
Divergence Filtering and Visualization:
Price Tolerance Filter: Divergence detection is enhanced with a percentage-based price tolerance (pivPrcTol) to filter out insignificant market noise, leading to more robust signals.
Persistent Visualization: Divergence markers are plotted for the entire duration of the signal and are visually anchored to the OBV level of the confirming pivot.
Note on Confirmation (Lag): Divergence signals rely on a pivot confirmation method to ensure they do not repaint.
The Start of a- divergence is only detected after the confirming pivot is fully formed (a delay based on Pivot Right Bars).
The End of a divergence is detected either instantly (if the signal is invalidated by price action) or with a delay (when a new, non-divergent pivot is confirmed).
Multi-Timeframe (MTF) Capability:
MTF OBV Line: The OBV line itself can be calculated on a higher timeframe, with standard options to handle gaps (Fill Gaps) and prevent repainting (Wait for...).
Limitation: The Divergence detection engine (pivDiv) is disabled if a timeframe other than the chart's timeframe is selected. Divergences are only calculated on the active chart timeframe.
Integrated Alerts: Includes 12 comprehensive alerts that trigger on the start and end of all 6 divergence types (e.g., "Regular Bullish Started", "Regular Bullish Ended").
DISCLAIMER
For Informational/Educational Use Only: This indicator is provided for informational and educational purposes only. It does not constitute financial, investment, or trading advice, nor is it a recommendation to buy or sell any asset.
Use at Your Own Risk: All trading decisions you make based on the information or signals generated by this indicator are made solely at your own risk.
No Guarantee of Performance: Past performance is not an indicator of future results. The author makes no guarantee regarding the accuracy of the signals or future profitability.
No Liability: The author shall not be held liable for any financial losses or damages incurred directly or indirectly from the use of this indicator.
Signals Are Not Recommendations: The alerts and visual signals (e.g., crossovers) generated by this tool are not direct recommendations to buy or sell. They are technical observations for your own analysis and consideration.
Market Structure Pivots TrendThis indicator identifies and visualizes key market structure by plotting confirmed, non-repainting pivot points. It goes beyond simple markers by classifying the pivots, extending dynamic support/resistance lines, and providing a visual representation of the current trend state.
Key Features:
Non-Repainting Pivot Detection:
Uses a standard lookback method (left and right bars) to identify historical pivot points.
Note on Confirmation: Pivots are only confirmed after the Pivot Right Bars input has passed. This is essential for ensuring the signal is non-repainting, but it introduces an inherent lag.
Automatically classifies the sequence of pivots according to Dow Theory: Higher Highs (HH), Higher Lows (HL), Lower Highs (LH), and Lower Lows (LL).
Pivot Classification Filter:
Price Tolerance Filter: A user-defined percentage tolerance filters out insignificant market noise. A pivot is only classified as 'Higher' or 'Lower' if its price exceeds the previous one by more than the set tolerance, leading to more robust signals.
Equal Pivot Detection: The tolerance also enables the detection of Equal Highs (EH) and Equal Lows (EL), highlighting consolidation zones.
Dynamic Support & Resistance Lines:
When enabled, the indicator extends a horizontal line from the most recent confirmed pivot high and low.
These lines update in real-time, providing clear S/R levels.
Lines automatically terminate if the price decisively breaks through them or if a new pivot of the same type is formed.
Trend State Visualization:
A built-in state machine analyzes the sequence of pivots and breaks to determine the current market trend (Uptrend, Downtrend, or Neutral).
Plots a dynamic step-line based on recent highs/lows to visually represent the current trend state.
Full Customization & Alerts:
Display Options: Choose between simple triangles or detailed text labels that show the pivot type, price, and the absolute or relative change from the previous pivot of the same type.
Visual Styling: Full control over colors for all six pivot types (HH, LH, EH, LL, HL, EL) and line styles.
Comprehensive Alerts: Set up alerts for every new pivot formation (e.g., HH, LL), for S/R line breaks, and for changes in the overall trend state (Up, Down, Neutral).
DISCLAIMER
For Informational/Educational Use Only: This indicator is provided for informational and educational purposes only. It does not constitute financial, investment, or trading advice, nor is it a recommendation to buy or sell any asset.
Use at Your Own Risk: All trading decisions you make based on the information or signals generated by this indicator are made solely at your own risk.
No Guarantee of Performance: Past performance is not an indicator of future results. The author makes no guarantee regarding the accuracy of the signals or future profitability.
No Liability: The author shall not be held liable for any financial losses or damages incurred directly or indirectly from the use of this indicator.
Signals Are Not Recommendations: The alerts and visual signals (e.g., crossovers) generated by this tool are not direct recommendations to buy or sell. They are technical observations for your own analysis and consideration.
Volume Weighted Average PriceThis indicator provides an implementation of the Volume Weighted Average Price (VWAP), extended with layered standard deviation bands that decompose total market volatility relative to the VWAP anchor period.
Key Features:
Volatility Decomposition: The indicator's primary feature is its ability to separate volatility, controlled by the 'Estimate Bar Statistics' option.
Standard Mode (Estimate Bar Statistics = OFF): Plots a single set of bands representing the standard deviation of the Source price relative to the VWAP.
Decomposition Mode (Estimate Bar Statistics = ON): The indicator uses a statistical model ('Estimator') to calculate within-bar volatility. (Assumption: In this mode, the Source input is ignored, and an estimated mean for each bar is used instead). This mode displays two sets of bands:
Inner Bands: Show only the contribution of the 'between-bar' volatility.
Outer Bands: Show the total volatility (the sum of between-bar and within-bar components).
Periodic & Customizable Anchor: The VWAP calculation is session-based and resets at the beginning of a new period. The anchor timeframe (Anchor Timeframe) can be detected automatically (e.g., 'Session', 'Week') or specified manually.
Weighting Mechanism: The indicator has two levels of weighting:
The baseline is always a VWAP (Volume-Weighted Average Price).
The Volume weighted input additionally applies volume weighting to the volatility (standard deviation) calculation for the bands.
Multi-Timeframe (MTF) Engine: The indicator includes an MTF conversion block. When a Higher Timeframe (HTF) is selected, advanced options become available: Fill Gaps handles data gaps, and Wait for timeframe to close prevents repainting by ensuring the indicator only updates when the HTF bar closes.
Integrated Alerts: Includes a full set of built-in alerts for the source price crossing over or under the central VWAP line and the outermost calculated volatility band.
DISCLAIMER
For Informational/Educational Use Only: This indicator is provided for informational and educational purposes only. It does not constitute financial, investment, or trading advice, nor is it a recommendation to buy or sell any asset.
Use at Your Own Risk: All trading decisions you make based on the information or signals generated by this indicator are made solely at your own risk.
No Guarantee of Performance: Past performance is not an indicator of future results. The author makes no guarantee regarding the accuracy of the signals or future profitability.
No Liability: The author shall not be held liable for any financial losses or damages incurred directly or indirectly from the use of this indicator.
Signals Are Not Recommendations: The alerts and visual signals (e.g., crossovers) generated by this tool are not direct recommendations to buy or sell. They are technical observations for your own analysis and consideration.
Volume Weighted Linear Regression BandThe Volume-Weighted Linear Regression Band (VWLRBd) is a volatility channel that uses a Linear Regression line as its dynamic baseline. Its primary feature is the decomposition of total volatility into two distinct components, visualized as layered bands.
Key Features:
Volatility Decomposition: The indicator separates volatility based on the 'Estimate Bar Statistics' option.
Standard Mode (Estimate Bar Statistics = OFF): The indicator functions as a standard (Volume-Weighted) Linear Regression Channel. It plots a single set of bands based on the standard deviation of the residuals (the error between the Source price and the regression line).
Decomposition Mode (Estimate Bar Statistics = ON): The indicator uses a statistical model ('Estimator') to calculate within-bar volatility. (Assumption: In this mode, the Source input is ignored, and an estimated mean for each bar is used for the regression). This mode displays two sets of bands:
Inner Bands: Show only the contribution of the 'residual' (trend noise) volatility, calculated proportionally.
Outer Bands: Show the total volatility (the sum of residual and within-bar components).
Regression Baseline (Linear / Exponential): The central line is a (Volume-Weighted) Linear Regression curve. An optional 'Normalize' mode performs all calculations in logarithmic space, transforming the baseline into an Exponential Regression Curve and the bands into constant percentage deviations, suitable for analyzing growth assets.
Volume Weighting: An option (Volume weighted) allows for volume to be incorporated into the calculation of both the regression baseline and the volatility decomposition, giving more influence to high-participation bars.
Multi-Timeframe (MTF) Engine: The indicator includes an MTF conversion block. When a Higher Timeframe (HTF) is selected, advanced options become available: Fill Gaps handles data gaps, and Wait for timeframe to close prevents repainting by ensuring the indicator only updates when the HTF bar closes.
Integrated Alerts: Includes a full set of built-in alerts for the source price crossing over or under the central regression line and the outermost calculated volatility band.
DISCLAIM_
For Informational/Educational Use Only: This indicator is provided for informational and educational purposes only. It does not constitute financial, investment, or trading advice, nor is it a recommendation to buy or sell any asset.
Use at Your Own Risk: All trading decisions you make based on the information or signals generated by this indicator are made solely at your own risk.
No Guarantee of Performance: Past performance is not an indicator of future results. The author makes no guarantee regarding the accuracy of the signals or future profitability.
No Liability: The author shall not be held liable for any financial losses or damages incurred directly or indirectly from the use of this indicator.
Signals Are Not Recommendations: The alerts and visual signals (e.g., crossovers) generated by this tool are not direct recommendations to buy or sell. They are technical observations for your own analysis and consideration.
Volume Weighted Linear Regression ChannelThis indicator plots a dynamic channel around a Linear Regression trendline. It provides a framework for identifying the prevailing trend and assessing price extremes based on volatility.
Key Features:
Linear Regression Baseline: The channel's centerline is a (Volume-Weighted) Linear Regression line. This line represents the 'best fit' for the recent price action, serving as a responsive baseline for the trend.
Volatility Decomposition: The indicator's primary feature is its ability to decompose volatility, controlled by the 'Estimate Bar Statistics' option.
Standard Mode (Estimate Bar Statistics = OFF): Calculates a standard linear regression channel. The bands represent the standard deviation of the residuals (the error) between the Source price and the regression line.
Decomposition Mode (Estimate Bar Statistics = ON): The indicator uses a statistical model ('Estimator') to calculate within-bar volatility. (Assumption: In this mode, the Source input is ignored, and an estimated mean for each bar is used for the regression). This mode displays two sets of bands:
Inner Bands: Show only the contribution of the 'residual' (trend noise) volatility, calculated proportionally.
Outer Bands: Show the total volatility (the sum of residual and within-bar components).
Volume Weighting: An option (Volume weighted) allows for volume to be incorporated into the calculation of both the linear regression and the volatility decomposition, giving more influence to high-participation bars.
Trend Projection: The calculated channel is plotted as a projection, which can be extended forward (Extend Forward) and backward (Extend Backward) in time to provide a visual guide for potential support and resistance.
Integrated Alerts: Includes a full set of built-in alerts for the Source price crossing over or under the calculated upper band, lower band, and the central regression line.
DISCLAIMER
For Informational/Educational Use Only: This indicator is provided for informational and educational purposes only. It does not constitute financial, investment, or trading advice, nor is it a recommendation to buy or sell any asset.
Use at Your Own Risk: All trading decisions you make based on the information or signals generated by this indicator are made solely at your own risk.
No Guarantee of Performance: Past performance is not an indicator of future results. The author makes no guarantee regarding the accuracy of the signals or future profitability.
No Liability: The author shall not be held liable for any financial losses or damages incurred directly or indirectly from the use of this indicator.
Signals Are Not Recommendations: The alerts and visual signals (e.g., crossovers) generated by this tool are not direct recommendations to buy or sell. They are technical observations for your own analysis and consideration.
Volume Weighted Bollinger BandsThis indicator provides a customizable version of Bollinger Bands, enhanced with optional volume weighting and a method for decomposing market volatility.
Key Features:
Volatility Decomposition: The indicator's primary feature is its ability to separate total volatility, controlled by the 'Estimate Bar Statistics' option.
Standard Mode (Estimate Bar Statistics = OFF): The indicator functions as a customizable Bollinger Band. It calculates the standard deviation of the user-selected Source and plots a single set of bands.
Decomposition Mode (Estimate Bar Statistics = ON): The indicator uses a statistical model ('Estimator') to calculate within-bar volatility. (Assumption: In this mode, the Source input is ignored, and an estimated mean for each bar is used instead). This mode displays two sets of bands:
Inner Bands: Show only the contribution of the 'between-bar' volatility.
Outer Bands: Show the total volatility (the sum of between-bar and within-bar components).
Customizable Construction: The indicator is a hybrid:
Basis Line: The central line is calculated using a selectable Moving Average type (e.g., EMA, SMA, WMA).
Volume Weighting: An option (Volume weighted) allows for volume to be incorporated into the calculation of both the basis MA and the volatility decomposition.
Logarithmic Scaling: An optional 'Normalize' mode calculates the bands on a logarithmic scale. This results in bands that maintain a constant percentage distance from the basis, suitable for analyzing exponential markets.
Multi-Timeframe (MTF) Engine: The indicator includes an MTF conversion block. When a Higher Timeframe (HTF) is selected, advanced options become available: Fill Gaps handles data gaps, and Wait for timeframe to close prevents repainting by ensuring the indicator only updates when the HTF bar closes.
Integrated Alerts: Includes a full set of built-in alerts for the source price crossing over or under the central MA line and the outermost calculated volatility band.
DISCLAIMER
For Informational/Educational Use Only: This indicator is provided for informational and educational purposes only. It does not constitute financial, investment, or trading advice, nor is it a recommendation to buy or sell any asset.
Use at Your Own Risk: All trading decisions you make based on the information or signals generated by this indicator are made solely at your own risk.
No Guarantee of Performance: Past performance is not an indicator of future results. The author makes no guarantee regarding the accuracy of the signals or future profitability.
No Liability: The author shall not be held liable for any financial losses or damages incurred directly or indirectly from the use of this indicator.
Signals Are Not Recommendations: The alerts and visual signals (e.g., crossovers) generated by this tool are not direct recommendations to buy or sell. They are technical observations for your own analysis and consideration.
Firex Data Trade 5* SetupIdentifies Boring, Quiet, No Supply / No Demand candles. "
+ "Highlights potential 5★ setups for trading confirmation when price breaks candle highs/lows. "
+ "Helps traders spot low-volume turning points and breakout opportunities
Volume Weighted Keltner ChannelThis indicator provides a customizable implementation of Keltner Channels (KC), a volatility-based envelope designed to identify trend direction and potential reversal or breakout zones. It allows deep control over its core components and calculation methods.
Key Features:
Customizable Components: This implementation allows for full control over the channel's construction:
Basis Line: Choose from a wide range of moving average types (e.g., EMA, SMA, WMA) for the central line.
Volatility Bands: Select the volatility measure used to construct the bands: Average True Range (ATR), True Range (TR), or bar Range (High-Low).
Volume Weighting: An option (Volume weighted) allows for volume to be incorporated into the calculation of both the basis moving average and the selected volatility measure (e.g., creating a Volume-Weighted ATR). This makes the channel more responsive to moves backed by high market participation.
Logarithmic Scaling: The indicator includes an optional 'Normalize' mode that calculates the channel on a logarithmic scale. This creates bands that represent a constant percentage distance from the basis, making it a suitable tool for analyzing long-term trends in exponential markets.
Multi-Timeframe (MTF) Engine: The indicator includes an MTF conversion block. When a Higher Timeframe (HTF) is selected, advanced options become available: Fill Gaps handles data gaps, and Wait for timeframe to close prevents repainting by ensuring the indicator only updates when the HTF bar closes.
Integrated Alerts: Includes a full set of built-in alerts for the source price crossing over or under the upper band, lower band, and the central basis line.
DISCLAIMER
For Informational/Educational Use Only: This indicator is provided for informational and educational purposes only. It does not constitute financial, investment, or trading advice, nor is it a recommendation to buy or sell any asset.
Use at Your Own Risk: All trading decisions you make based on the information or signals generated by this indicator are made solely at your own risk.
No Guarantee of Performance: Past performance is not an indicator of future results. The author makes no guarantee regarding the accuracy of the signals or future profitability.
No Liability: The author shall not be held liable for any financial losses or damages incurred directly or indirectly from the use of this indicator.
Signals Are Not Recommendations: The alerts and visual signals (e.g., crossovers) generated by this tool are not direct recommendations to buy or sell. They are technical observations for your own analysis and consideration.
Versatile Moving AverageThe Versatile Moving Average (VMA) is a comprehensive, all-in-one tool for trend analysis. It is designed to act as a central hub for advanced MA calculations by combining a wide selection of average types, calculation modes, and a multi-timeframe engine.
Key Features:
Comprehensive MA Selection: Provides a wide variety of moving average types (e.g., EMA, SMA, WMA, HMA, and their volume-weighted counterparts). Allows full customization of length, source, and offset.
Advanced Calculation Modes:
Volume Weighting: Optionally weights the selected MA calculation by volume, making it more responsive to market participation.
Normalization (Geometric Average): A key feature is the optional 'Normalize' mode. When enabled, the indicator calculates a Geometric Moving Average by averaging the logarithms of the source price. This measures the average compound growth rate, making it well-suited for analyzing assets with exponential price behavior.
Multi-Timeframe (MTF) Engine: The indicator includes an MTF conversion block. When a Higher Timeframe (HTF) is selected, advanced options become available: Fill Gaps handles data gaps, and Wait for timeframe to close prevents repainting by ensuring the indicator only updates when the HTF bar closes.
Integrated Alerts: Comes with built-in alerts for the source price crossing over or under the calculated VMA, allowing for timely notifications.
DISCLAIMER
For Informational/Educational Use Only: This indicator is provided for informational and educational purposes only. It does not constitute financial, investment, or trading advice, nor is it a recommendation to buy or sell any asset.
Use at Your Own Risk: All trading decisions you make based on the information or signals generated by this indicator are made solely at your.
No Guarantee of Performance: Past performance is not an indicator of future results. The author makes no guarantee regarding the accuracy of the signals or future profitability.
No Liability: The author shall not be held liable for any financial losses or damages incurred directly or indirectly from the use of this indicator.
Signals Are Not Recommendations: The alerts and visual signals (e.g., crossovers) generated by this tool are not direct recommendations to buy or sell. They are technical observations for your own analysis and consideration.
LibVPrfLibrary "LibVPrf"
This library provides an object-oriented framework for volume
profile analysis in Pine Script®. It is built around the `VProf`
User-Defined Type (UDT), which encapsulates all data, settings,
and statistical metrics for a single profile, enabling stateful
analysis with on-demand calculations.
Key Features:
1. **Object-Oriented Design (UDT):** The library is built around
the `VProf` UDT. This object encapsulates all profile data
and provides methods for its full lifecycle management,
including creation, cloning, clearing, and merging of profiles.
2. **Volume Allocation (`AllotMode`):** Offers two methods for
allocating a bar's volume:
- **Classic:** Assigns the entire bar's volume to the close
price bucket.
- **PDF:** Distributes volume across the bar's range using a
statistical price distribution model from the `LibBrSt` library.
3. **Buy/Sell Volume Splitting (`SplitMode`):** Provides methods
for classifying volume into buying and selling pressure:
- **Classic:** Classifies volume based on the bar's color (Close vs. Open).
- **Dynamic:** A specific model that analyzes candle structure
(body vs. wicks) and a short-term trend factor to
estimate the buy/sell share at each price level.
4. **Statistical Analysis (On-Demand):** Offers a suite of
statistical metrics calculated using a "Lazy Evaluation"
pattern (computed only when requested via `get...` methods):
- **Central Tendency:** Point of Control (POC), VWAP, and Median.
- **Dispersion:** Value Area (VA) and Population Standard Deviation.
- **Shape:** Skewness and Excess Kurtosis.
- **Delta:** Cumulative Volume Delta, including its
historical high/low watermarks.
5. **Structural Analysis:** Includes a parameter-free method
(`getSegments`) to decompose a profile into its fundamental
unimodal segments, allowing for modality detection (e.g.,
identifying bimodal profiles).
6. **Dynamic Profile Management:**
- **Auto-Fitting:** Profiles set to `dynamic = true` will
automatically expand their price range to fit new data.
- **Manipulation:** The resolution, price range, and Value Area
of a dynamic profile can be changed at any time. This
triggers a resampling process that uses a **linear
interpolation model** to re-bucket existing volume.
- **Assumption:** Non-dynamic profiles are fixed and will throw
a `runtime.error` if `addBar` is called with data
outside their initial range.
7. **Bucket-Level Access:** Provides getter methods for direct
iteration and analysis of the raw buy/sell volume and price
boundaries of each individual price bucket.
---
**DISCLAIMER**
This library is provided "AS IS" and for informational and
educational purposes only. It does not constitute financial,
investment, or trading advice.
The author assumes no liability for any errors, inaccuracies,
or omissions in the code. Using this library to build
trading indicators or strategies is entirely at your own risk.
As a developer using this library, you are solely responsible
for the rigorous testing, validation, and performance of any
scripts you create based on these functions. The author shall
not be held liable for any financial losses incurred directly
or indirectly from the use of this library or any scripts
derived from it.
create(buckets, rangeUp, rangeLo, dynamic, valueArea, allot, estimator, cdfSteps, split, trendLen)
Construct a new `VProf` object with fixed bucket count & range.
Parameters:
buckets (int) : series int number of price buckets ≥ 1
rangeUp (float) : series float upper price bound (absolute)
rangeLo (float) : series float lower price bound (absolute)
dynamic (bool) : series bool Flag for dynamic adaption of profile ranges
valueArea (int) : series int Percentage of total volume to include in the Value Area (1..100)
allot (series AllotMode) : series AllotMode Allocation mode `classic` or `pdf` (default `classic`)
estimator (series PriceEst enum from AustrianTradingMachine/LibBrSt/1) : series LibBrSt.PriceEst PDF model when `model == PDF`. (deflault = 'uniform')
cdfSteps (int) : series int even #sub-intervals for Simpson rule (default 20)
split (series SplitMode) : series SplitMode Buy/Sell determination (default `classic`)
trendLen (int) : series int Look‑back bars for trend factor (default 3)
Returns: VProf freshly initialised profile
method clone(self)
Create a deep copy of the volume profile.
Namespace types: VProf
Parameters:
self (VProf) : VProf Profile object to copy
Returns: VProf A new, independent copy of the profile
method clear(self)
Reset all bucket tallies while keeping configuration intact.
Namespace types: VProf
Parameters:
self (VProf) : VProf profile object
Returns: VProf cleared profile (chaining)
method merge(self, srcABuy, srcASell, srcRangeUp, srcRangeLo, srcCvd, srcCvdHi, srcCvdLo)
Merges volume data from a source profile into the current profile.
If resizing is needed, it performs a high-fidelity re-bucketing of existing
volume using a linear interpolation model inferred from neighboring buckets,
preventing aliasing artifacts and ensuring accurate volume preservation.
Namespace types: VProf
Parameters:
self (VProf) : VProf The target profile object to merge into.
srcABuy (array) : array The source profile's buy volume bucket array.
srcASell (array) : array The source profile's sell volume bucket array.
srcRangeUp (float) : series float The upper price bound of the source profile.
srcRangeLo (float) : series float The lower price bound of the source profile.
srcCvd (float) : series float The final Cumulative Volume Delta (CVD) value of the source profile.
srcCvdHi (float) : series float The historical high-water mark of the CVD from the source profile.
srcCvdLo (float) : series float The historical low-water mark of the CVD from the source profile.
Returns: VProf `self` (chaining), now containing the merged data.
method addBar(self, offset)
Add current bar’s volume to the profile (call once per realtime bar).
classic mode: allocates all volume to the close bucket and classifies
by `close >= open`. PDF mode: distributes volume across buckets by the
estimator’s CDF mass. For `split = dynamic`, the buy/sell share per
price is computed via context-driven piecewise s(u).
Namespace types: VProf
Parameters:
self (VProf) : VProf Profile object
offset (int) : series int To offset the calculated bar
Returns: VProf `self` (method chaining)
method setBuckets(self, buckets)
Sets the number of buckets for the volume profile.
Behavior depends on the `isDynamic` flag.
- If `dynamic = true`: Works on filled profiles by re-bucketing to a new resolution.
- If `dynamic = false`: Only works on empty profiles to prevent accidental changes.
Namespace types: VProf
Parameters:
self (VProf) : VProf Profile object
buckets (int) : series int The new number of buckets
Returns: VProf `self` (chaining)
method setRanges(self, rangeUp, rangeLo)
Sets the price range for the volume profile.
Behavior depends on the `dynamic` flag.
- If `dynamic = true`: Works on filled profiles by re-bucketing existing volume.
- If `dynamic = false`: Only works on empty profiles to prevent accidental changes.
Namespace types: VProf
Parameters:
self (VProf) : VProf Profile object
rangeUp (float) : series float The new upper price bound
rangeLo (float) : series float The new lower price bound
Returns: VProf `self` (chaining)
method setValueArea(self, valueArea)
Set the percentage of volume for the Value Area. If the value
changes, the profile is finalized again.
Namespace types: VProf
Parameters:
self (VProf) : VProf Profile object
valueArea (int) : series int The new Value Area percentage (0..100)
Returns: VProf `self` (chaining)
method getBktBuyVol(self, idx)
Get Buy volume of a bucket.
Namespace types: VProf
Parameters:
self (VProf) : VProf Profile object
idx (int) : series int Bucket index
Returns: series float Buy volume ≥ 0
method getBktSellVol(self, idx)
Get Sell volume of a bucket.
Namespace types: VProf
Parameters:
self (VProf) : VProf Profile object
idx (int) : series int Bucket index
Returns: series float Sell volume ≥ 0
method getBktBnds(self, idx)
Get Bounds of a bucket.
Namespace types: VProf
Parameters:
self (VProf) : VProf Profile object
idx (int) : series int Bucket index
Returns:
up series float The upper price bound of the bucket.
lo series float The lower price bound of the bucket.
method getPoc(self)
Get POC information.
Namespace types: VProf
Parameters:
self (VProf) : VProf Profile object
Returns:
pocIndex series int The index of the Point of Control (POC) bucket.
pocPrice. series float The mid-price of the Point of Control (POC) bucket.
method getVA(self)
Get Value Area (VA) information.
Namespace types: VProf
Parameters:
self (VProf) : VProf Profile object
Returns:
vaUpIndex series int The index of the upper bound bucket of the Value Area.
vaUpPrice series float The upper price bound of the Value Area.
vaLoIndex series int The index of the lower bound bucket of the Value Area.
vaLoPrice series float The lower price bound of the Value Area.
method getMedian(self)
Get the profile's median price and its bucket index. Calculates the value on-demand if stale.
Namespace types: VProf
Parameters:
self (VProf) : VProf Profile object.
Returns:
medianIndex series int The index of the bucket containing the Median.
medianPrice series float The Median price of the profile.
method getVwap(self)
Get the profile's VWAP and its bucket index. Calculates the value on-demand if stale.
Namespace types: VProf
Parameters:
self (VProf) : VProf Profile object.
Returns:
vwapIndex series int The index of the bucket containing the VWAP.
vwapPrice series float The Volume Weighted Average Price of the profile.
method getStdDev(self)
Get the profile's volume-weighted standard deviation. Calculates the value on-demand if stale.
Namespace types: VProf
Parameters:
self (VProf) : VProf Profile object.
Returns: series float The Standard deviation of the profile.
method getSkewness(self)
Get the profile's skewness. Calculates the value on-demand if stale.
Namespace types: VProf
Parameters:
self (VProf) : VProf Profile object.
Returns: series float The Skewness of the profile.
method getKurtosis(self)
Get the profile's excess kurtosis. Calculates the value on-demand if stale.
Namespace types: VProf
Parameters:
self (VProf) : VProf Profile object.
Returns: series float The Kurtosis of the profile.
method getSegments(self)
Get the profile's fundamental unimodal segments. Calculates on-demand if stale.
Uses a parameter-free, pivot-based recursive algorithm.
Namespace types: VProf
Parameters:
self (VProf) : VProf The profile object.
Returns: matrix A 2-column matrix where each row is an pair.
method getCvd(self)
Cumulative Volume Delta (CVD) like metric over all buckets.
Namespace types: VProf
Parameters:
self (VProf) : VProf Profile object.
Returns:
cvd series float The final Cumulative Volume Delta (Total Buy Vol - Total Sell Vol).
cvdHi series float The running high-water mark of the CVD as volume was added.
cvdLo series float The running low-water mark of the CVD as volume was added.
VProf
VProf Bucketed Buy/Sell volume profile plus meta information.
Fields:
buckets (series int) : int Number of price buckets (granularity ≥1)
rangeUp (series float) : float Upper price range (absolute)
rangeLo (series float) : float Lower price range (absolute)
dynamic (series bool) : bool Flag for dynamic adaption of profile ranges
valueArea (series int) : int Percentage of total volume to include in the Value Area (1..100)
allot (series AllotMode) : AllotMode Allocation mode `classic` or `pdf`
estimator (series PriceEst enum from AustrianTradingMachine/LibBrSt/1) : LibBrSt.PriceEst Price density model when `model == PDF`
cdfSteps (series int) : int Simpson integration resolution (even ≥2)
split (series SplitMode) : SplitMode Buy/Sell split strategy per bar
trendLen (series int) : int Look‑back length for trend factor (≥1)
maxBkt (series int) : int User-defined number of buckets (unclamped)
aBuy (array) : array Buy volume per bucket
aSell (array) : array Sell volume per bucket
cvd (series float) : float Final Cumulative Volume Delta (Total Buy Vol - Total Sell Vol).
cvdHi (series float) : float Running high-water mark of the CVD as volume was added.
cvdLo (series float) : float Running low-water mark of the CVD as volume was added.
poc (series int) : int Index of max‑volume bucket (POC). Is `na` until calculated.
vaUp (series int) : int Index of upper Value‑Area bound. Is `na` until calculated.
vaLo (series int) : int Index of lower value‑Area bound. Is `na` until calculated.
median (series float) : float Median price of the volume distribution. Is `na` until calculated.
vwap (series float) : float Profile VWAP (Volume Weighted Average Price). Is `na` until calculated.
stdDev (series float) : float Standard Deviation of volume around the VWAP. Is `na` until calculated.
skewness (series float) : float Skewness of the volume distribution. Is `na` until calculated.
kurtosis (series float) : float Excess Kurtosis of the volume distribution. Is `na` until calculated.
segments (matrix) : matrix A 2-column matrix where each row is an pair. Is `na` until calculated.
LibBrStLibrary "LibBrSt"
This is a library for quantitative analysis, designed to estimate
the statistical properties of price movements *within* a single
OHLC bar, without requiring access to tick data. It provides a
suite of estimators based on various statistical and econometric
models, allowing for analysis of intra-bar volatility and
price distribution.
Key Capabilities:
1. **Price Distribution Models (`PriceEst`):** Provides a selection
of estimators that model intra-bar price action as a probability
distribution over the range. This allows for the
calculation of the intra-bar mean (`priceMean`) and standard
deviation (`priceStdDev`) in absolute price units. Models include:
- **Symmetric Models:** `uniform`, `triangular`, `arcsine`,
`betaSym`, and `t4Sym` (Student-t with fat tails).
- **Skewed Models:** `betaSkew` and `t4Skew`, which adjust
their shape based on the Open/Close position.
- **Model Assumptions:** The skewed models rely on specific
internal constants. `betaSkew` uses a fixed concentration
parameter (`BETA_SKEW_CONCENTRATION = 4.0`), and `t4Sym`/`t4Skew`
use a heuristic scaling factor (`T4_SHAPE_FACTOR`)
to map the distribution.
2. **Econometric Log-Return Estimators (`LogEst`):** Includes a set of
econometric estimators for calculating the volatility (`logStdDev`)
and drift (`logMean`) of logarithmic returns within a single bar.
These are unit-less measures. Models include:
- **Parkinson (1980):** A High-Low range estimator.
- **Garman-Klass (1980):** An OHLC-based estimator.
- **Rogers-Satchell (1991):** An OHLC estimator that accounts
for non-zero drift.
3. **Distribution Analysis (PDF/CDF):** Provides functions to work
with the Probability Density Function (`pricePdf`) and
Cumulative Distribution Function (`priceCdf`) of the
chosen price model.
- **Note on `priceCdf`:** This function uses analytical (exact)
calculations for the `uniform`, `triangular`, and `arcsine`
models. For all other models (e.g., `betaSkew`, `t4Skew`),
it uses **numerical integration (Simpson's rule)** as
an approximation of the cumulative probability.
4. **Mathematical Functions:** The library's Beta distribution
models (`betaSym`, `betaSkew`) are supported by an internal
implementation of the natural log-gamma function, which is
based on the Lanczos approximation.
---
**DISCLAIMER**
This library is provided "AS IS" and for informational and
educational purposes only. It does not constitute financial,
investment, or trading advice.
The author assumes no liability for any errors, inaccuracies,
or omissions in the code. Using this library to build
trading indicators or strategies is entirely at your own risk.
As a developer using this library, you are solely responsible
for the rigorous testing, validation, and performance of any
scripts you create based on these functions. The author shall
not be held liable for any financial losses incurred directly
or indirectly from the use of this library or any scripts
derived from it.
priceStdDev(estimator, offset)
Estimates **σ̂** (standard deviation) *in price units* for the current
bar, according to the chosen `PriceEst` distribution assumption.
Parameters:
estimator (series PriceEst) : series PriceEst Distribution assumption (see enum).
offset (int) : series int To offset the calculated bar
Returns: series float σ̂ ≥ 0 ; `na` if undefined (e.g. zero range).
priceMean(estimator, offset)
Estimates **μ̂** (mean price) for the chosen `PriceEst` within the
current bar.
Parameters:
estimator (series PriceEst) : series PriceEst Distribution assumption (see enum).
offset (int) : series int To offset the calculated bar
Returns: series float μ̂ in price units.
pricePdf(estimator, price, offset)
Probability-density under the chosen `PriceEst` model.
**Returns 0** when `p` is outside the current bar’s .
Parameters:
estimator (series PriceEst) : series PriceEst Distribution assumption (see enum).
price (float) : series float Price level to evaluate.
offset (int) : series int To offset the calculated bar
Returns: series float Density value.
priceCdf(estimator, upper, lower, steps, offset)
Cumulative probability **between** `upper` and `lower` under
the chosen `PriceEst` model. Outside-bar regions contribute zero.
Uses a fast, analytical calculation for Uniform, Triangular, and
Arcsine distributions, and defaults to numerical integration
(Simpson's rule) for more complex models.
Parameters:
estimator (series PriceEst) : series PriceEst Distribution assumption (see enum).
upper (float) : series float Upper Integration Boundary.
lower (float) : series float Lower Integration Boundary.
steps (int) : series int # of sub-intervals for numerical integration (if used).
offset (int) : series int To offset the calculated bar.
Returns: series float Probability mass ∈ .
logStdDev(estimator, offset)
Estimates **σ̂** (standard deviation) of *log-returns* for the current bar.
Parameters:
estimator (series LogEst) : series LogEst Distribution assumption (see enum).
offset (int) : series int To offset the calculated bar
Returns: series float σ̂ (unit-less); `na` if undefined.
logMean(estimator, offset)
Estimates μ̂ (mean log-return / drift) for the chosen `LogEst`.
The returned value is consistent with the assumptions of the
selected volatility estimator.
Parameters:
estimator (series LogEst) : series LogEst Distribution assumption (see enum).
offset (int) : series int To offset the calculated bar
Returns: series float μ̂ (unit-less log-return).
LibPvotLibrary "LibPvot"
This is a library for advanced technical analysis, specializing
in two core areas: the detection of price-oscillator
divergences and the analysis of market structure. It provides
a back-end engine for signal detection and a toolkit for
indicator plotting.
Key Features:
1. **Complete Divergence Suite (Class A, B, C):** The engine detects
all three major types of divergences, providing a full spectrum of
analytical signals:
- **Regular (A):** For potential trend reversals.
- **Hidden (B):** For potential trend continuations.
- **Exaggerated (C):** For identifying weakness at double tops/bottoms.
2. **Advanced Signal Filtering:** The detection logic uses a
percentage-based price tolerance (`prcTol`). This feature
enables the practical detection of Exaggerated divergences
(which rarely occur at the exact same price) and creates a
"dead zone" to filter insignificant noise from triggering
Regular divergences.
3. **Pivot Synchronization:** A bar tolerance (`barTol`) is used
to reliably match price and oscillator pivots that do not
align perfectly on the same bar, preventing missed signals.
4. **Signal Invalidation Logic:** Features two built-in invalidation
rules:
- An optional `invalidate` parameter automatically terminates
active divergences if the price or the oscillator breaks
the level of the confirming pivot.
- The engine also discards 'half-pivots' (e.g., a price pivot)
if a corresponding oscillator pivot does not appear within
the `barTol` window.
5. **Stateful Plotting Helpers:** Provides helper functions
(`bullDivPos` and `bearDivPos`) that abstract away the
state management issues of visualizing persistent signals.
They generate gap-free, accurately anchored data series
ready to be used in `plotshape` functions, simplifying
indicator-side code.
6. **Rich Data Output:** The core detection functions (`bullDiv`, `bearDiv`)
return a comprehensive 9-field data tuple. This includes the
boolean flags for each divergence type and the precise
coordinates (price, oscillator value, bar index) of both the
starting and the confirming pivots.
7. **Market Structure & Trend Analysis:** Includes a
`marketStructure` function to automatically identify pivot
highs/lows, classify their relationship (HH, LH, LL, HL),
detect structure breaks, and determine the current trend
state (Up, Down, Neutral) based on pivot sequences.
---
**DISCLAIMER**
This library is provided "AS IS" and for informational and
educational purposes only. It does not constitute financial,
investment, or trading advice.
The author assumes no liability for any errors, inaccuracies,
or omissions in the code. Using this library to build
trading indicators or strategies is entirely at your own risk.
As a developer using this library, you are solely responsible
for the rigorous testing, validation, and performance of any
scripts you create based on these functions. The author shall
not be held liable for any financial losses incurred directly
or indirectly from the use of this library or any scripts
derived from it.
bullDiv(priceSrc, oscSrc, leftLen, rightLen, depth, barTol, prcTol, persist, invalidate)
Detects bullish divergences (Regular, Hidden, Exaggerated) based on pivot lows.
Parameters:
priceSrc (float) : series float Price series to check for pivots (e.g., `low`).
oscSrc (float) : series float Oscillator series to check for pivots.
leftLen (int) : series int Number of bars to the left of a pivot (default 5).
rightLen (int) : series int Number of bars to the right of a pivot (default 5).
depth (int) : series int Maximum number of stored pivot pairs to check against (default 2).
barTol (int) : series int Maximum bar distance allowed between the price pivot and the oscillator pivot (default 3).
prcTol (float) : series float The percentage tolerance for comparing pivot prices. Used to detect Exaggerated
divergences and filter out market noise (default 0.05%).
persist (bool) : series bool If `true` (default), the divergence flag stays active for the entire duration of the signal.
If `false`, it returns a single-bar pulse on detection.
invalidate (bool) : series bool If `true` (default), terminates an active divergence if price or oscillator break
below the confirming pivot low.
Returns: A tuple containing comprehensive data for a detected bullish divergence.
regBull series bool `true` if a Regular bullish divergence (Class A) is active.
hidBull series bool `true` if a Hidden bullish divergence (Class B) is active.
exgBull series bool `true` if an Exaggerated bullish divergence (Class C) is active.
initPivotPrc series float Price value of the initial (older) pivot low.
initPivotOsz series float Oscillator value of the initial pivot low.
initPivotBar series int Bar index of the initial pivot low.
lastPivotPrc series float Price value of the last (confirming) pivot low.
lastPivotOsz series float Oscillator value of the last pivot low.
lastPivotBar series int Bar index of the last pivot low.
bearDiv(priceSrc, oscSrc, leftLen, rightLen, depth, barTol, prcTol, persist, invalidate)
Detects bearish divergences (Regular, Hidden, Exaggerated) based on pivot highs.
Parameters:
priceSrc (float) : series float Price series to check for pivots (e.g., `high`).
oscSrc (float) : series float Oscillator series to check for pivots.
leftLen (int) : series int Number of bars to the left of a pivot (default 5).
rightLen (int) : series int Number of bars to the right of a pivot (default 5).
depth (int) : series int Maximum number of stored pivot pairs to check against (default 2).
barTol (int) : series int Maximum bar distance allowed between the price pivot and the oscillator pivot (default 3).
prcTol (float) : series float The percentage tolerance for comparing pivot prices. Used to detect Exaggerated
divergences and filter out market noise (default 0.05%).
persist (bool) : series bool If `true` (default), the divergence flag stays active for the entire duration of the signal.
If `false`, it returns a single-bar pulse on detection.
invalidate (bool) : series bool If `true` (default), terminates an active divergence if price or oscillator break
above the confirming pivot high.
Returns: A tuple containing comprehensive data for a detected bearish divergence.
regBear series bool `true` if a Regular bearish divergence (Class A) is active.
hidBear series bool `true` if a Hidden bearish divergence (Class B) is active.
exgBear series bool `true` if an Exaggerated bearish divergence (Class C) is active.
initPivotPrc series float Price value of the initial (older) pivot high.
initPivotOsz series float Oscillator value of the initial pivot high.
initPivotBar series int Bar index of the initial pivot high.
lastPivotPrc series float Price value of the last (confirming) pivot high.
lastPivotOsz series float Oscillator value of the last pivot high.
lastPivotBar series int Bar index of the last pivot high.
bullDivPos(regBull, hidBull, exgBull, rightLen, yPos)
Calculates the plottable data series for bullish divergences. It manages
the complex state of a persistent signal's plotting window to ensure
gap-free and accurately anchored visualization.
Parameters:
regBull (bool) : series bool The regular bullish divergence flag from `bullDiv`.
hidBull (bool) : series bool The hidden bullish divergence flag from `bullDiv`.
exgBull (bool) : series bool The exaggerated bullish divergence flag from `bullDiv`.
rightLen (int) : series int The same `rightLen` value used in `bullDiv` for correct timing.
yPos (float) : series float The series providing the base Y-coordinate for the shapes (e.g., `low`).
Returns: A tuple of three `series float` for plotting bullish divergences.
regBullPosY series float Contains the static anchor Y-value for Regular divergences where a shape should be plotted; `na` otherwise.
hidBullPosY series float Contains the static anchor Y-value for Hidden divergences where a shape should be plotted; `na` otherwise.
exgBullPosY series float Contains the static anchor Y-value for Exaggerated divergences where a shape should be plotted; `na` otherwise.
bearDivPos(regBear, hidBear, exgBear, rightLen, yPos)
Calculates the plottable data series for bearish divergences. It manages
the complex state of a persistent signal's plotting window to ensure
gap-free and accurately anchored visualization.
Parameters:
regBear (bool) : series bool The regular bearish divergence flag from `bearDiv`.
hidBear (bool) : series bool The hidden bearish divergence flag from `bearDiv`.
exgBear (bool) : series bool The exaggerated bearish divergence flag from `bearDiv`.
rightLen (int) : series int The same `rightLen` value used in `bearDiv` for correct timing.
yPos (float) : series float The series providing the base Y-coordinate for the shapes (e.g., `high`).
Returns: A tuple of three `series float` for plotting bearish divergences.
regBearPosY series float Contains the static anchor Y-value for Regular divergences where a shape should be plotted; `na` otherwise.
hidBearPosY series float Contains the static anchor Y-value for Hidden divergences where a shape should be plotted; `na` otherwise.
exgBearPosY series float Contains the static anchor Y-value for Exaggerated divergences where a shape should be plotted; `na` otherwise.
marketStructure(highSrc, lowSrc, leftLen, rightLen, srcTol)
Analyzes the market structure by identifying pivot points, classifying
their sequence (e.g., Higher Highs, Lower Lows), and determining the
prevailing trend state.
Parameters:
highSrc (float) : series float Price series for pivot high detection (e.g., `high`).
lowSrc (float) : series float Price series for pivot low detection (e.g., `low`).
leftLen (int) : series int Number of bars to the left of a pivot (default 5).
rightLen (int) : series int Number of bars to the right of a pivot (default 5).
srcTol (float) : series float Percentage tolerance to consider two pivots as 'equal' (default 0.05%).
Returns: A tuple containing detailed market structure information.
pivType series PivType The type of the most recently formed pivot (e.g., `hh`, `ll`).
lastPivHi series float The price level of the last confirmed pivot high.
lastPivLo series float The price level of the last confirmed pivot low.
lastPiv series float The price level of the last confirmed pivot (either high or low).
pivHiBroken series bool `true` if the price has broken above the last pivot high.
pivLoBroken series bool `true` if the price has broken below the last pivot low.
trendState series TrendState The current trend state (`up`, `down`, or `neutral`).
LibTmFrLibrary "LibTmFr"
This is a utility library for handling timeframes and
multi-timeframe (MTF) analysis in Pine Script. It provides a
collection of functions designed to handle common tasks related
to period detection, session alignment, timeframe construction,
and time calculations, forming a foundation for
MTF indicators.
Key Capabilities:
1. **MTF Period Engine:** The library includes functions for
managing higher-timeframe (HTF) periods.
- **Period Detection (`isNewPeriod`):** Detects the first bar
of a given timeframe. It includes custom logic to handle
multi-month and multi-year intervals where
`timeframe.change()` may not be sufficient.
- **Bar Counting (`sinceNewPeriod`):** Counts the number of
bars that have passed in the current HTF period or
returns the final count for a completed historical period.
2. **Automatic Timeframe Selection:** Offers functions for building
a top-down analysis framework:
- **Automatic HTF (`autoHTF`):** Suggests a higher timeframe
(HTF) for broader context based on the current timeframe.
- **Automatic LTF (`autoLTF`):** Suggests an appropriate lower
timeframe (LTF) for granular intra-bar analysis.
3. **Timeframe Manipulation and Comparison:** Includes tools for
working with timeframe strings:
- **Build & Split (`buildTF`, `splitTF`):** Functions to
programmatically construct valid Pine Script timeframe
strings (e.g., "4H") and parse them back into their
numeric and unit components.
- **Comparison (`isHigherTF`, `isActiveTF`, `isLowerTF`):**
A set of functions to check if a given timeframe is
higher, lower, or the same as the script's active timeframe.
- **Multiple Validation (`isMultipleTF`):** Checks if a
higher timeframe is a practical multiple of the current
timeframe. This is based on the assumption that checking
if recent, completed HTF periods contained more than one
bar is a valid proxy for preventing data gaps.
4. **Timestamp Interpolation:** Contains an `interpTimestamp()`
function that calculates an absolute timestamp by
interpolating at a given percentage across a specified
range of bars (e.g., 50% of the way through the last
20 bars), enabling time calculations at a resolution
finer than the chart's native bars.
---
**DISCLAIMER**
This library is provided "AS IS" and for informational and
educational purposes only. It does not constitute financial,
investment, or trading advice.
The author assumes no liability for any errors, inaccuracies,
or omissions in the code. Using this library to build
trading indicators or strategies is entirely at your own risk.
As a developer using this library, you are solely responsible
for the rigorous testing, validation, and performance of any
scripts you create based on these functions. The author shall
not be held liable for any financial losses incurred directly
or indirectly from the use of this library or any scripts
derived from it.
buildTF(quantity, unit)
Builds a Pine Script timeframe string from a numeric quantity and a unit enum.
The resulting string can be used with `request.security()` or `input.timeframe`.
Parameters:
quantity (int) : series int Number to specifie how many `unit` the timeframe spans.
unit (series TFUnit) : series TFUnit The size category for the bars.
Returns: series string A Pine-style timeframe identifier, e.g.
"5S" → 5-seconds bars
"30" → 30-minute bars
"120" → 2-hour bars
"1D" → daily bars
"3M" → 3-month bars
"24M" → 2-year bars
splitTF(tf)
Splits a Pine‑timeframe identifier into numeric quantity and unit (TFUnit).
Parameters:
tf (string) : series string Timeframe string, e.g.
"5S", "30", "120", "1D", "3M", "24M".
Returns:
quantity series int The numeric value of the timeframe (e.g., 15 for "15", 3 for "3M").
unit series TFUnit The unit of the timeframe (e.g., TFUnit.minutes, TFUnit.months).
Notes on strings without a suffix:
• Pure digits are minutes; if divisible by 60, they are treated as hours.
• An "M" suffix is months; if divisible by 12, it is converted to years.
autoHTF(tf)
Picks an appropriate **higher timeframe (HTF)** relative to the selected timeframe.
It steps up along a coarse ladder to produce sensible jumps for top‑down analysis.
Mapping → chosen HTF:
≤ 1 min → 60 (1h) ≈ ×60
≤ 3 min → 180 (3h) ≈ ×60
≤ 5 min → 240 (4h) ≈ ×48
≤ 15 min → D (1 day) ≈ ×26–×32 (regular session 6.5–8 h)
> 15 min → W (1 week) ≈ ×64–×80 for 30m; varies with input
≤ 1 h → W (1 week) ≈ ×32–×40
≤ 4 h → M (1 month) ≈ ×36–×44 (~22 trading days / month)
> 4 h → 3M (3 months) ≈ ×36–×66 (e.g., 12h→×36–×44; 8h→×53–×66)
≤ 1 day → 3M (3 months) ≈ ×60–×66 (~20–22 trading days / month)
> 1 day → 12M (1 year) ≈ ×(252–264)/quantity
≤ 1 week → 12M (1 year) ≈ ×52
> 1 week → 48M (4 years) ≈ ×(208)/quantity
= 1 M → 48M (4 years) ≈ ×48
> 1 M → error ("HTF too big")
any → error ("HTF too big")
Notes:
• Inputs in months or years are restricted: only 1M is allowed; larger months/any years throw.
• Returns a Pine timeframe string usable in `request.security()` and `input.timeframe`.
Parameters:
tf (string) : series string Selected timeframe (e.g., "D", "240", or `timeframe.period`).
Returns: series string Suggested higher timeframe.
autoLTF(tf)
Selects an appropriate **lower timeframe LTF)** for intra‑bar evaluation
based on the selected timeframe. The goal is to keep intra‑bar
loops performant while providing enough granularity.
Mapping → chosen LTF:
≤ 1 min → 1S ≈ ×60
≤ 5 min → 5S ≈ ×60
≤ 15 min → 15S ≈ ×60
≤ 30 min → 30S ≈ ×60
> 30 min → 60S (1m) ≈ ×31–×59 (for 31–59 minute charts)
≤ 1 h → 1 (1m) ≈ ×60
≤ 2 h → 2 (2m) ≈ ×60
≤ 4 h → 5 (5m) ≈ ×48
> 4 h → 15 (15m) ≈ ×24–×48 (e.g., 6h→×24, 8h→×32, 12h→×48)
≤ 1 day → 15 (15m) ≈ ×26–×32 (regular sessions ~6.5–8h)
> 1 day → 60 (60m) ≈ ×(26–32) per day × quantity
≤ 1 week → 60 (60m) ≈ ×32–×40 (≈5 sessions of ~6.5–8h)
> 1 week → 240 (4h) ≈ ×(8–10) per week × quantity
≤ 1 M → 240 (4h) ≈ ×33–×44 (~20–22 sessions × 6.5–8h / 4h)
≤ 3 M → D (1d) ≈ ×(20–22) per month × quantity
> 3 M → W (1w) ≈ ×(4–5) per month × quantity
≤ 1 Y → W (1w) ≈ ×52
> 1 Y → M (1M) ≈ ×12 per year × quantity
Notes:
• Ratios for D/W/M are given as ranges because they depend on
**regular session length** (typically ~6.5–8h, not 24h).
• Returned strings can be used with `request.security()` and `input.timeframe`.
Parameters:
tf (string) : series string Selected timeframe (e.g., "D", "240", or timeframe.period).
Returns: series string Suggested lower TF to use for intra‑bar work.
isNewPeriod(tf, offset)
Returns `true` when a new session-aligned period begins, or on the Nth bar of that period.
Parameters:
tf (string) : series string Target higher timeframe (e.g., "D", "W", "M").
offset (simple int) : simple int 0 → checks for the first bar of the new period.
1+ → checks for the N-th bar of the period.
Returns: series bool `true` if the condition is met.
sinceNewPeriod(tf, offset)
Counts how many bars have passed within a higher timeframe (HTF) period.
For daily, weekly, and monthly resolutions, the period is aligned with the trading session.
Parameters:
tf (string) : series string Target parent timeframe (e.g., "60", "D").
offset (simple int) : simple int 0 → Running count for the current period.
1+ → Finalized count for the Nth most recent *completed* period.
Returns: series int Number of bars.
isHigherTF(tf, main)
Returns `true` when the selected timeframe represents a
higher resolution than the active timeframe.
Parameters:
tf (string) : series string Selected timeframe.
main (bool) : series bool When `true`, the comparison is made against the chart's main timeframe
instead of the script's active timeframe. Optional. Defaults to `false`.
Returns: series bool `true` if `tf` > active TF; otherwise `false`.
isActiveTF(tf, main)
Returns `true` when the selected timeframe represents the
exact resolution of the active timeframe.
Parameters:
tf (string) : series string Selected timeframe.
main (bool) : series bool When `true`, the comparison is made against the chart's main timeframe
instead of the script's active timeframe. Optional. Defaults to `false`.
Returns: series bool `true` if `tf` == active TF; otherwise `false`.
isLowerTF(tf, main)
Returns `true` when the selected timeframe represents a
lower resolution than the active timeframe.
Parameters:
tf (string) : series string Selected timeframe.
main (bool) : series bool When `true`, the comparison is made against the chart's main timeframe
instead of the script's active timeframe. Optional. Defaults to `false`.
Returns: series bool `true` if `tf` < active TF; otherwise `false`.
isMultipleTF(tf)
Returns `true` if the selected timeframe (`tf`) is a practical multiple
of the active skript's timeframe. It verifies this by checking if `tf` is a higher timeframe
that has consistently contained more than one bar of the skript's timeframe in recent periods.
The period detection is session-aware.
Parameters:
tf (string) : series string The higher timeframe to check.
Returns: series bool `true` if `tf` is a practical multiple; otherwise `false`.
interpTimestamp(offStart, offEnd, pct)
Calculates a precise absolute timestamp by interpolating within a bar range based on a percentage.
This version works with RELATIVE bar offsets from the current bar.
Parameters:
offStart (int) : series int The relative offset of the starting bar (e.g., 10 for 10 bars ago).
offEnd (int) : series int The relative offset of the ending bar (e.g., 1 for 1 bar ago). Must be <= offStart.
pct (float) : series float The percentage of the bar range to measure (e.g., 50.5 for 50.5%).
Values are clamped to the range.
Returns: series int The calculated, interpolated absolute Unix timestamp in milliseconds.
LibVolmLibrary "LibVolm"
This library provides a collection of core functions for volume and
money flow analysis. It offers implementations of several classic
volume-based indicators, with a focus on flexibility
for applications like multi-timeframe and session-based analysis.
Key Features:
1. **Suite of Classic Volume Indicators:** Includes standard
implementations of several foundational indicators:
- **On Balance Volume (`obv`):** A momentum indicator that
accumulates volume based on price direction.
- **Accumulation/Distribution Line (`adLine`):** Measures cumulative
money flow using the close's position within the bar's range.
- **Chaikin Money Flow (`cmf`):** An oscillator version of the ADL
that measures money flow over a specified lookback period.
2. **Anchored/Resettable Indicators:** The library includes flexible,
resettable indicators ideal for cyclical analysis:
- **Anchored VWAP (`vwap`):** Calculates a Volume Weighted Average
Price that can be reset on any user-defined `reset` condition.
It returns both the VWAP and the number of bars (`prdBars`) in
the current period.
- **Resettable CVD (`cvd`):** Computes a Cumulative Volume Delta
that can be reset on a custom `reset` anchor. The function
also tracks and returns the highest (`hi`) and lowest (`lo`)
delta values reached within the current period.
(Note: The delta sign is determined by a specific logic:
it first checks close vs. open, then close vs. prior
close, and persists the last non-zero sign).
3. **Volume Sanitization:** All functions that use the built-in
`volume` variable automatically sanitize it via an internal
function. This process replaces `na` values with 0 and ensures
no negative volume values are used, providing stable calculations.
---
**DISCLAIMER**
This library is provided "AS IS" and for informational and
educational purposes only. It does not constitute financial,
investment, or trading advice.
The author assumes no liability for any errors, inaccuracies,
or omissions in the code. Using this library to build
trading indicators or strategies is entirely at your own risk.
As a developer using this library, you are solely responsible
for the rigorous testing, validation, and performance of any
scripts you create based on these functions. The author shall
not be held liable for any financial losses incurred directly
or indirectly from the use of this library or any scripts
derived from it.
obv(price)
Calculates the On Balance Volume (OBV) cumulative indicator.
Parameters:
price (float) : series float Source price series, typically the close.
Returns: series float Cumulative OBV value.
adLine()
Computes the Accumulation/Distribution Line (AD Line).
Returns: series float Cumulative AD Line value.
cmf(length)
Computes Chaikin Money Flow (CMF).
Parameters:
length (int) : series int Lookback length for the CMF calculation.
Returns: series float CMF value.
vwap(price, reset)
Calculates an anchored Volume Weighted Average Price (VWAP).
Parameters:
price (float) : series float Source price series (usually *close*).
reset (bool) : series bool A signal that is *true* on the bar where the
accumulation should be reset.
Returns:
vwap series float The calculated Volume Weighted Average Price for the current period.
prdBars series int The number of bars that have passed since the last reset.
cvd(reset)
Calculates a resettable, cumulative Volume Delta (CVD).
It accumulates volume delta and tracks its high/low range. The
accumulation is reset to zero whenever the `reset` condition is true.
This is useful for session-based analysis, intra-bar calculations,
or any other custom-anchored accumulation.
Parameters:
reset (bool) : series bool A signal that is *true* on the bar where the
accumulation should be reset.
Returns:
cum series float The current cumulative volume delta.
hi series float The highest peak the cumulative delta has reached in the current period.
lo series float The lowest trough the cumulative delta has reached in the current period.
