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Volume Weighted Volatility RegimeThe Volume-Weighted Volatility Regime (VWVR) is a market analysis tool that dissects total volatility to classify the current market 'character' or 'regime'. Using a Linear Regression model, it decomposes volatility into Trend, Residual (mean-reversion), and Within-Bar (noise) components.
Key Features:
Seven-Stage Regime Classification: The indicator's primary output is a regime value from -3 to +3, identifying the market state:
+3 (Strong Bull Trend): High directional, upward volatility.
+2 (Choppy Bull): Moderate upward trend with noise.
+1 (Quiet Bull): Low volatility, slight upward drift.
0 (Neutral): No clear directional bias.
-1 (Quiet Bear): Low volatility, slight downward drift.
-2 (Choppy Bear): Moderate downward trend with noise.
-3 (Strong Bear Trend): High directional, downward volatility.
Advanced Volatility Decomposition: The regime is derived from a three-component volatility model that separates price action into Trend (momentum), Residual (mean-reversion), and Within-Bar (noise) variance. The classification is determined by comparing the 'Trend' ratio against the user-defined 'Trend Threshold' and 'Quiet Threshold'.
Dual-Level Analysis: The indicator analyzes market character on two levels simultaneously:
Inter-Bar Regime (Background Color): Based on the main StdDev Length, showing the overall market character.
Intra-Bar Regime (Column Color): Based on a high-resolution analysis within each single bar ('Intra-Bar Timeframe'), showing the micro-structural character.
Calculation Options:
Statistical Model: The 'Estimate Bar Statistics' option (enabled by default) uses a statistical model ('Estimator') to perform the decomposition. (Assumption: In this mode, the Source input is ignored, and an estimated mean for each bar is used instead).
Normalization: An optional 'Normalize Volatility' setting calculates an Exponential Regression Curve (log-space).
Volume Weighting: An option (Volume weighted) applies volume weighting to all volatility calculations.
Multi-Timeframe (MTF) Capability: The entire dual-level analysis can be run on a higher timeframe (using the Timeframe input), with standard options to handle gaps (Fill Gaps) and prevent repainting (Wait for...).
Integrated Alerts: Includes 22 comprehensive alerts that trigger whenever the 'Inter-Bar Regime' or the 'Intra-Bar Regime' crosses one of the key thresholds (e.g., 'Regime crosses above Neutral Line'), or when the 'Intra-Bar Dominance' crosses the 50% mark.
Caution: Real-Time Data Behavior (Intra-Bar Repainting) This indicator uses high-resolution intra-bar data. As a result, the values on the current, unclosed bar (the real-time bar) will update dynamically as new intra-bar data arrives. This behavior is normal and necessary for this type of analysis. Signals should only be considered final after the main chart bar has closed.
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 LR Standard DeviationThis indicator analyzes market character by decomposing total volatility into three distinct, interpretable components based on a Linear Regression model.
Key Features:
Three-Component Volatility Decomposition: The indicator separates volatility based on the 'Estimate Bar Statistics' option.
Standard Mode (Estimate Bar Statistics = OFF): Calculates volatility based on the selected Source (dies führt hauptsächlich zu 'Trend'- und 'Residual'-Volatilität).
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 separates volatility into:
Trend Volatility (Green/Red): Volatility explained by the regression's slope (Momentum).
Residual Volatility (Yellow): Volatility from price oscillating around the regression line (Mean-Reversion).
Within-Bar Volatility (Blue): Volatility from the high-low range of each bar (Noise/Choppiness).
Dual Display Modes: The indicator offers two modes to visualize this decomposition:
Absolute Mode: Displays the total standard deviation as a stacked area chart, partitioned by the variance ratio of the three components.
Normalized Mode: Displays the direct variance ratio (proportion) of each component relative to the total (0-1), ideal for identifying the dominant market character.
Calculation Options:
Normalization: An optional 'Normalize Volatility' setting calculates an Exponential Regression Curve (log-space), making the analysis suitable for growth assets.
Volume Weighting: An option (Volume weighted) applies volume weighting to all regression and volatility calculations.
Multi-Component Pivot Detection: Includes a pivot detector that identifies significant turning points (highs and lows) in both the Total Volatility and the Trend Volatility Ratio. (Note: These pivots are only plotted when 'Plot Mode' is set to 'Absolute').
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 9 comprehensive alerts for:
Volatility character changes (e.g., 'Character Change from Noise to Trend').
Dominant character emerging (e.g., 'Bullish Trend Character Emerging').
Total Volatility pivot (High/Low) detection.
Trend Volatility pivot (High/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.
Volume Weighted Intra Bar LR Standard DeviationThis indicator analyzes market character by providing a detailed view of volatility. It applies a Linear Regression model to intra-bar price action, dissecting the total volatility of each bar into three distinct components.
Key Features:
Three-Component Volatility Decomposition: By analyzing a lower timeframe ('Intra-Bar Timeframe'), the indicator separates each bar's volatility into:
Trend Volatility (Green/Red): Volatility explained by the intra-bar linear regression slope (Momentum).
Residual Volatility (Yellow): Volatility from price oscillating around the intra-bar trendline (Mean-Reversion).
Within-Bar Volatility (Blue): Volatility derived from the range of each intra-bar candle (Noise/Choppiness).
Layered Column Visualization: The indicator plots these components as a layered column chart. The size of each colored layer visually represents the dominance of each volatility character.
Dual Display Modes: The indicator offers two modes to visualize this decomposition:
Absolute Mode: Displays the total standard deviation as the column height, showing the absolute magnitude of volatility and the contribution of each component.
Normalized Mode: Displays the components as a 100% stacked column chart (scaled from 0 to 1), focusing purely on the percentage ratio of Trend, Residual, and Noise.
Calculation Options:
Statistical Model: The 'Estimate Bar Statistics' option (enabled by default) uses a statistical model ('Estimator') to perform the decomposition. (Assumption: In this mode, the Source input is ignored, and an estimated mean for each bar is used instead).
Normalization: An optional 'Normalize Volatility' setting calculates an Exponential Regression Curve (log-space).
Volume Weighting: An option (Volume weighted) applies volume weighting to all intra-bar calculations.
Multi-Component Pivot Detection: Includes a pivot detector that identifies significant turning points (highs and lows) in both the Total Volatility and the Trend Volatility Ratio. (Note: These pivots are only plotted when 'Plot Mode' is set to 'Absolute').
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 Analysis: The entire intra-bar analysis can be run on a higher timeframe (using the Timeframe input), 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 9 comprehensive alerts for:
Volatility character changes (e.g., 'Character Change from Noise to Trend').
Dominant character emerging (e.g., 'Bullish Trend Character Emerging').
Total Volatility pivot (High/Low) detection.
Trend Volatility pivot (High/Low) detection.
Caution! Real-Time Data Behavior (Intra-Bar Repainting) This indicator uses high-resolution intra-bar data. As a result, the values on the current, unclosed bar (the real-time bar) will update dynamically as new intra-bar data arrives. This behavior is normal and necessary for this type of analysis. Signals should only be considered final after the main chart bar has closed.
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 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.
Volume Weighted Intra Bar Standard DeviationThis indicator provides a high-resolution analysis of market volatility by dissecting each bar on the chart into its fundamental components. It uses data from a lower, intra-bar timeframe to separate the total volatility of a single bar into its 'directional' and 'non-directional' parts.
Key Features:
Intra-Bar Volatility Decomposition: For each bar on the chart, the indicator analyzes the underlying price action on a smaller timeframe ('Intra-Bar Timeframe') and quantifies two types of volatility:
Between-Bar Volatility (Directional): Calculated from price movements between the intra-bar candles. This component represents the directional, trending price action within the main bar.
Within-Bar Volatility (Non-Directional): Calculated from price fluctuations inside each intra-bar candle. This component represents the choppy, noisy, or ranging price action.
Dual Display Modes: The indicator offers two modes to visualize this information:
Absolute Mode: Plots the total standard deviation as a stacked column chart, showing the absolute magnitude of volatility and the contribution of each component.
Normalized Mode: Plots the components as a 100% stacked column chart (scaled from 0 to 1), focusing purely on the percentage ratio of 'between-bar' (trending) and 'within-bar' (choppy) volatility.
Calculation Options:
Statistical Model: The 'Estimate Bar Statistics' option (enabled by default) uses a statistical model ('Estimator') to perform the decomposition. (Assumption: In this mode, the Source input is ignored, and an estimated mean for each bar is used instead).
Normalization: An optional 'Normalize Volatility' setting calculates volatility in percentage terms (log-space).
Volume Weighting: An option (Volume weighted) applies volume weighting to all intra-bar volatility calculations.
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 Analysis Lines: The entire intra-bar analysis can be run on a higher timeframe (using the Timeframe input), 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., 'Character Change from Choppy to Trend').
Dominant character emerging (e.g., 'Trend Character Emerging').
Total Volatility pivot (High/Low) detection.
Caution: Real-Time Data Behavior (Intra-Bar Repainting) This indicator uses high-resolution intra-bar data. As a result, the values on the current, unclosed bar (the real-time bar) will update dynamically as new intra-bar data arrives. This behavior is normal and necessary for this type of analysis. Signals should only be considered final after the main chart bar has closed.
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.
Statistical Price Deviation Index (MAD/VWMA)SPDI is a statistical oscillator designed to detect potential price reversal zones by measuring how far price deviates from its typical behavior within a defined rolling window.
Instead of using momentum or moving averages like traditional indicators, SPDI applies robust statistics - a rolling median and Mean Absolute Deviation (MAD) - to calculate a normalized measure of price displacement. This normalization keeps the output bounded (from −1 to +1 by default), producing a stable and consistent oscillator that adapts to changing volatility conditions.
The second line in SPDI uses a Volume-Weighted Moving Average (VWMA) instead of a simple price median. This creates a complementary oscillator showing statistically weighted deviations based on traded volume. When both oscillators align in their extremes, strong confluence reversal signals are generated.
How It Works
For each bar, SPDI calculates the median price of the last N bars (default 100).
It then measures how far the current bar’s midpoint deviates from that rolling median.
The Mean Absolute Deviation (MAD) of those distances defines a “normal” range of fluctuation.
The deviation is normalized and compressed via a tanh mapping, keeping the oscillator in fixed boundaries (−1 to +1).
The same logic is applied to the VWMA line to gauge volume-weighted deviations.
How to Use
The blue line (Price MAD) represents pure price deviation.
The green line (VWMA Disp) shows the volume-weighted deviation.
Overbought (red) zones indicate statistically extreme upward deviation -> potential short-term overextension.
Oversold (green) zones indicate statistically extreme downward deviation -> potential rebound area.
Confluence signals (both lines hitting the same extreme) often mark strong reversal points.
Settings Tips
Lookback length controls how much historical data defines “normal” behavior. Larger = smoother, smaller = more sensitive.
Smoothing (RMA length) can reduce noise without changing the overall statistical logic.
Output scale can be set to either −1..+1 or 0..100, depending on your visual preference.
Alerts and color fills are fully customizable in the Style tab.
Summary:
SPDI transforms raw price and volume data into a statistically bounded deviation index. When both Price MAD and VWMA Disp reach joint extremes, it highlights probable market turning points - offering traders a clean, data-driven way to spot potential reversals ahead of time.
Double Median SD Bands | MisinkoMasterThe Double Median SD Bands (DMSDB) is a trend-following tool designed to capture market direction in a way that balances responsiveness and smoothness, filtering out excessive noise without introducing heavy lag.
Think of it like a house:
A jail (too restrictive) makes you miss opportunities.
No house at all (too unsafe) leaves you exposed to false signals.
DMSDB acts like a comfortable house with windows—protecting you from the noise while still letting you see what’s happening in the market.
🔎 Methodology
The script works in the following steps:
Standard Deviation (SD) Calculation
Computes the standard deviation of the selected price source (ohlc4 by default).
The user can choose whether to use biased (sample) or unbiased (population) standard deviation.
Raw Bands Construction
Upper Band = source + (SD × multiplier)
Lower Band = source - (SD × multiplier)
The multiplier can be adjusted for tighter or looser bands.
First Median Smoothing
Applies a median filter over half of the length (len/2) to both bands.
This reduces noise without creating excessive lag.
Second Median Smoothing
Applies another median filter over √len to the already smoothed bands.
This produces a balance:
Cutting the length → maintains responsiveness.
Median smoothing → reduces whipsaws.
The combination creates a fast yet clean band system ideal for trend detection.
📈 Trend Logic
The trend is detected based on price crossing the smoothed bands:
Long / Bullish (Purple) → when price crosses above the upper band.
Short / Bearish (Gold) → when price crosses below the lower band.
Neutral → when price remains between the bands.
🎨 Visualization
Upper and lower bands are plotted as colored lines.
The area between the bands is filled with a transparent zone that reflects the current bias:
Purple shading = Bullish zone.
Golden shading = Bearish zone.
This creates a visual tunnel for trend confirmation, helping traders quickly identify whether price action is trending or consolidating.
⚡ Features
Adjustable Length parameter (len) for dynamic control.
Adjustable Band Multiplier for volatility adaptation.
Choice between biased vs. unbiased standard deviation.
Double median smoothing for clarity + responsiveness.
Works well on cryptocurrencies (e.g., BTCUSD) but is flexible enough for stocks, forex, and indices.
✅ Use Cases
Trend Following → Ride trends by staying on the correct side of the bands.
Entry Timing → Use crossovers above/below bands for entry triggers.
Filter for Other Strategies → Can serve as a directional filter to avoid trading against the trend.
⚠️ Limitations & Notes
This is a trend-following tool, so it will perform best in trending conditions.
In sideways or choppy markets, whipsaws may still occur (although smoothing reduces them significantly).
The indicator is not a standalone buy/sell system. For best results, combine with volume, momentum, or higher-timeframe confluence.
All of this makes for a really unique & original tool, as it removes noise but keeps good responsitivity, using methods from many different principles which make for a smooth a very useful tool
Implied Volatility RangeThe Implied Volatility Range is a forward-looking tool that transforms option market data into probability ranges for future prices. Based on the lognormal distribution of asset prices assumed in modern option pricing models, it converts the implied volatility curve into a volatility cone with dynamic labels that show the market’s expectations for the price distribution at a specific point in time. At the selected future date, it displays projected price levels and their percentage change from today’s close across 1, 2, and 3 standard deviation (σ) ranges:
1σ range = ~68.2% probability the price will remain within this range.
2σ range = ~95.4% probability the price will remain within this range.
3σ range = ~99.7% probability the price will remain within this range.
What makes this indicator especially useful is its ability to incorporate implied volatility skew. When only ATM IV (%) is entered, the indicator displays the standard Black–Scholes lognormal distribution. By adding High IV (%) and Low IV (%) values tied to strikes above and below the current price, the indicator interpolates between these inputs to approximate the implied volatility skew. This adjustment produces a market-implied probability distribution that indicates whether the option market is leaning bullish or bearish, based on the data entered in the menu:
ATM IV (%) = Implied volatility at the current spot price (at-the-money).
High IV (%) = Implied volatility at a strike above the current spot price.
High Strike = Strike price corresponding to the High IV input (OTM call).
Low IV (%) = Implied volatility at a strike below the current spot price.
Low Strike = Strike price corresponding to the Low IV input (OTM put).
Expiration (Day, Month, Year) = Option expiration date for the projection.
Once these inputs are entered, the indicator calculates implied probability ranges and, if both High IV and Low IV values are provided, adjusts for skew to approximate the option market’s distribution. If no implied volatility data is supplied, the indicator defaults to a lognormal distribution based on historical volatility, using past realized volatility over the same forward horizon. This keeps the tool functional even without implied volatility inputs, though in that case the output represents only an approximation of ATM IV, not the actual market view.
In summary, the Implied Volatility Range is a powerful tool that translates implied volatility inputs into a clear and practical estimate of the market’s expectations for future prices. It allows traders to visualize the probability of price ranges while also highlighting directional bias, a dimension often difficult to interpret from traditional implied volatility charts. It should be emphasized, however, that this tool reflects only the market’s expectations at a specific point in time, which may change as new information and trading activity reshape implied volatility.
CandelaCharts - Projections 📝 Overview
Projections turns a hand-picked swing window into clean, forward price levels. You pick a time range and an anchor (wick or body); the tool finds that window’s reference extremes (Level 0 & Level 1) and then projects directional extensions (e.g., −1, −2, −2.5, −4) in the chosen bias (Auto / Bullish / Bearish). It draws flat lines across the chart with optional labels so you can plan targets, fade zones, or continuation levels at a glance.
📦 Features
This section highlights the core capabilities you’ll rely on most.
Window-based engine — Define a start/end time; the script records open/high/low/close inside that window and builds levels from those extremes.
Two anchor styles — Project from Wick extremes (Hi/Lo) or Body extremes (max/min of OHLC at the high/low bars).
Directional bias — Auto (up if net up; doji resolves by wick dominance), or force Bullish/Bearish for one-sided extensions.
Default & Custom levels — Toggle pre-sets (−1/−2/−2.5/−4) or enter your own comma-separated list (decimals supported).
Readable drawings — Per-level colors (defaults) or unified bull/bear color (custom), with label size, line style, and width controls.
⚙️ Settings
Use these controls to define the window, pick the projection style, and customize the visuals.
Settings (Core)
From / To — Start and end timestamps of the capture window (everything is computed from this segment).
Bias — Auto / Bullish / Bearish. Guides which way negative levels extend (up for bull, down for bear).
Anchor — Wick uses Hi/Lo; Body uses the body extremes at the high/low bars.
Levels
Levels = Default — Enable any of −1, −2, −2.5, −4 and set each color.
Levels = Custom — Provide your own list (e.g., “−0.5, −1, −1.5, −3”) and pick Bullish/Bearish colors. (Custom uses one color per side.)
Style
Labels — Show/Hide the numeric level tag at the line’s right edge; choose label size.
Lines — Pick solid/dashed/dotted and line width.
⚡️ Showcase
Bearish Projection
Bullish Projection
📒 Usage
Follow these steps to set the window, generate levels, and turn them into a trade plan.
1) Mark the window — Set From/To around the swing you want to project (e.g., prior day, news impulse, weekly move).
2) Choose bias — Auto adapts; or lock Bullish/Bearish if you only want upside or downside projections.
3) Pick anchor — Wick = raw extremes; Body = more conservative reference. Body helps when single-print wicks distort levels.
4) Select levels — Toggle defaults or add a custom list. Negative values (−1, −2, …) extend beyond the reference extreme in the bias direction. (Level 0 and 1 are always drawn as the reference pair.)
5) Style it — Turn labels on, adjust size, and set line style/width for visibility on your timeframe.
6) Trade plan — Treat projections as reaction/continuation zones: scale out into −1/−2/−2.5, watch for fades back into the band, or ride continuation when price accepts beyond a level.
🚨 Alerts
There are no built-in alerts in this version.
⚠️ Disclaimer
Trading involves significant risk, and many participants may incur losses. The content on this site is not intended as financial advice and should not be interpreted as such. Decisions to buy, sell, hold, or trade securities, commodities, or other financial instruments carry inherent risks and are best made with guidance from qualified financial professionals. Past performance is not indicative of future results.
Extreme Zone Volume ProfileExtreme Zone Volume Profile (EZVP)
Originality & Innovation
The Extreme Zone Volume Profile (EZVP) revolutionizes traditional volume profile analysis by applying statistical zone classification to volume distribution. Unlike standard volume profiles that display raw volume data, EZVP segments the price range into statistically meaningful zones based on percentile thresholds, allowing traders to instantly identify where volume concentration suggests strong support/resistance versus areas of potential breakout.
Technical Methodology
Core Algorithm:
Distributes volume across user-defined bins (20-200) over a lookback period
Calculates volume-weighted price levels for each bin
Applies percentile-based zone classification to the price range (not volume ranking)
Zone B (extreme zones): Outer percentile tails representing potential rejection areas
Zone A (significant zones): Secondary percentile bands indicating strong interest levels
Center Zone: Bulk trading range where most price discovery occurs
Mathematical Foundation:
The script uses price-range percentiles rather than volume percentiles. If the total price range is divided into 100%, Zone B captures the extreme price tails (default 2.5% each end ≈ 2 standard deviations), Zone A captures the next significant bands (default 14% each ≈ 1 standard deviation), leaving the center for normal distribution trading.
Key Calculations:
POC (Point of Control): Price level with maximum volume accumulation
Volume-weighted mean price: Total volume × price / total volume
Median price: Geometric center of the price range
Rightward-projected bars: Volume bars extend forward from current time to avoid historical chart clutter
Trading Applications
Zone Interpretation:
Zone B (Red/Green): Extreme price levels where volume suggests strong rejection potential. Price reaching these zones often indicates overextension and possible reversal points.
Zone A (Orange/Teal): Significant support/resistance areas with substantial volume interest. These levels often act as intermediate targets or consolidation zones.
Center (Gray): Fair value area where most trading occurs. Price tends to return to this range during normal market conditions.
Strategic Usage:
Reversal Trading: Look for rejection signals when price enters Zone B areas
Breakout Confirmation: Volume expansion beyond Zone B boundaries suggests genuine breakouts
Support/Resistance: Zone A boundaries often provide reliable entry/exit levels
Mean Reversion: Price tends to gravitate toward the volume-weighted mean and POC lines
Unique Value Proposition
EZVP addresses three key limitations of traditional volume profiles:
Visual Clarity: Standard profiles can be cluttered and difficult to interpret quickly. EZVP's color-coded zones provide instant visual feedback about price significance.
Statistical Framework: Rather than relying on subjective interpretation of volume nodes, EZVP applies objective percentile-based classification, making support/resistance identification more systematic.
Forward-Looking Display: Rightward-projecting bars keep historical price action clean while maintaining current market structure visibility.
Configuration Guide
Lookback Period (10-1000): Controls the historical depth of volume calculation. Shorter periods for intraday scalping, longer for swing trading.
Number of Bins (20-200): Resolution of volume distribution. Higher values provide more granular analysis but may create noise on lower timeframes.
Zone Percentages:
Zone B: Extreme threshold (default 2.5% = ~2σ statistical significance)
Zone A: Significant threshold (default 14% = ~1σ statistical significance)
Visual Controls: Toggle individual elements (POC, median, mean, zone lines) to customize display complexity for your trading style.
Technical Requirements
Pine Script v6 compatible
Maximum bars back: 5000 (ensures sufficient historical data)
Maximum boxes: 500 (supports high-resolution bin counts)
Maximum lines: 50 (accommodates all zone and reference lines)
This indicator synthesizes volume profile theory with statistical zone analysis, providing a quantitative framework for identifying high-probability support/resistance levels based on volume distribution patterns rather than arbitrary price levels.
StdDev Supply/Demand Zone RefinerThis indicator uses standard deviation bands to identify statistically significant price extremes, then validates these levels through volume analysis and market structure. It employs a proprietary "Zone Refinement" technique that dynamically adjusts zones based on price interaction and volume concentration, creating increasingly precise support/resistance areas.
Key Features:
Statistical Extremes Detection: Identifies when price reaches 2+ standard deviations from mean
Volume-Weighted Zone Creation: Only creates zones at extremes with abnormal volume
Dynamic Zone Refinement: Automatically tightens zones based on touch points and volume nodes
Point of Control (POC) Identification: Finds the exact price with maximum volume within each zone
Volume Profile Visualization: Shows horizontal volume distribution to identify key liquidity levels
Multi-Factor Validation: Combines volume imbalance, zone strength, and touch count metrics
Unlike traditional support/resistance indicators that use arbitrary levels, this system:
Self-adjusts based on market volatility (standard deviation)
Refines zones through machine-learning-like feedback from price touches
Weights by volume to show where real money was positioned
Tracks zone decay - older, untested zones automatically fade
Realized Volatility (StdDev of Returns, %)📌 Realized Volatility (StdDev of Returns, %)
This indicator measures realized volatility directly from price returns, instead of the common but misleading approach of calculating standard deviation around a moving average.
🔹 How it works:
Computes close-to-close log returns (the most common way volatility is measured in finance).
Calculates the standard deviation of these returns over a chosen lookback period (default = 200 bars).
Converts results into percentages for easier interpretation.
Provides three key volatility measures:
Daily Realized Vol (%) – raw standard deviation of returns.
Annualized Vol (%) – scaled by √250 trading days (market convention).
Horizon Vol (%) – volatility over a custom horizon (default = 5 days, i.e. weekly).
🔹 Why use this indicator?
Shows true realized volatility from historical returns.
More accurate than measuring deviation around a moving average.
Useful for traders analyzing risk, position sizing, and comparing realized vs implied volatility.
⚠️ Note:
It is best used on the Daily Chart!
By default, this uses log returns (which are additive and standard in quant finance).
If you prefer, you can easily switch to simple % returns in the code.
Volatility estimates depend on your chosen lookback length and may vary across timeframes.
Fabian Z-ScoreFabian Z-Score — % Distance & Z-Scores for SPX / DJI / XLU
What it does
This indicator measures how far three market proxies are from a moving average and standardizes those distances into z-scores so you can spot stretch/mean-reversion and relative out/under-performance.
Universe: S&P 500 (SPX), Dow Jones (DJI) and Utilities (XLU). You can change any of these in Inputs.
Anchor MA: user-selectable MA type (SMA/EMA/RMA/WMA/VWMA/HMA/LSMA/ALMA) and length (default 39; a popular weekly anchor).
Outputs
% from MA: 100 × (𝐶𝑙𝑜𝑠𝑒 − 𝑀𝐴) / 𝑀𝐴
Time-series Z: z-score of the last N % distances (default 39) → “how stretched vs its own history?”
Cross-sectional Z: z-score of each % distance within the trio on this bar → “who’s strongest vs the others right now?”
A compact mini table (top-right) shows the latest values for each symbol: % from MA, Z(ts) and Z(xsec).
Panels & Visualization
Toggle what you want to see in View:
Plot % distance — raw % above/below the MA (0% line shown).
Plot time-series Z — standardized stretch with ±Threshold guides (default ±2σ).
Plot cross-sectional Z — relative z across SPX, DJI, XLU (0 = at the trio’s mean).
Smoothing — optional light MA on the plotted series (set to 1 for none).
A price-panel Moving Average is drawn with your chosen type/length for visual context.
Colors: SPX = teal, DJI = orange, XLU = purple.
Alerts
Two built-in alert conditions (time-series Z only):
“Z(ts) crosses up +Thr” — any of the three crosses above +Threshold.
“Z(ts) crosses down -Thr” — any crosses below −Threshold.
When enabled, the chart background tints faint green (up cross) or red (down cross) on those bars.
How to use (ideas, not advice)
On weekly charts, a 39-length MA/Z lookback often captures major risk-on/off swings. (Fabian Timing)
Deep negative Z(ts) (e.g., ≤ −2σ or −3σ) frequently accompanies panic and mean-reversion setups.
High positive Z(ts) suggests over-extension; watch for momentum fades.
Cross-sectional Z helps rank leadership today:
Z(xsec) > 0 → stronger than the trio’s mean this bar; Z(xsec) < 0 → weaker.
Utilities (XLU) turning positive x-sec while the others are negative can hint at defensive rotation.
If all 3 are above 0, go long, if below 0 go cash.
Combine: look for extreme Z(ts) aligning with lead/lag Z(xsec) to time entries/exits or hedges.
Inputs (quick reference)
Symbols: SPX / DJI / XLU (editable).
MA type & length: SMA, EMA, RMA, WMA, VWMA, HMA, LSMA, ALMA; default EMA(39).
Z-score lookback (ts): default 39.
Smoothing on plots: default 1 (off).
Z threshold (±): default 2.0 (guide lines & alerts).
Relative Volatility Mass [SciQua]The ⚖️ Relative Volatility Mass (RVM) is a volatility-based tool inspired by the Relative Volatility Index (RVI) .
While the RVI measures the ratio of upward to downward volatility over a period, RVM takes a different approach:
It sums the standard deviation of price changes over a rolling window, separating upward volatility from downward volatility .
The result is a measure of the total “volatility mass” over a user-defined period, rather than an average or normalized ratio.
This makes RVM particularly useful for identifying sustained high-volatility conditions without being diluted by averaging.
────────────────────────────────────────────────────────────
╭────────────╮
How It Works
╰────────────╯
1. Standard Deviation Calculation
• Computes the standard deviation of the chosen `Source` over a `Standard Deviation Length` (`stdDevLen`).
2. Directional Separation
• Volatility on up bars (`chg > 0`) is treated as upward volatility .
• Volatility on down bars (`chg < 0`) is treated as downward volatility .
3. Rolling Sum
• Over a `Sum Length` (`sumLen`), the upward and downward volatilities are summed separately using `math.sum()`.
4. Relative Volatility Mass
• The two sums are added together to get the total volatility mass for the rolling window.
Formula:
RVM = Σ(σ up) + Σ(σ down)
where σ is the standard deviation over `stdDevLen`.
╭────────────╮
Key Features
╰────────────╯
Directional Volatility Tracking – Differentiates between volatility during price advances vs. declines.
Rolling Volatility Mass – Shows the total standard deviation accumulation over a given period.
Optional Smoothing – Multiple MA types, including SMA, EMA, SMMA (RMA), WMA, VWMA.
Bollinger Band Overlay – Available when SMA is selected, with adjustable standard deviation multiplier.
Configurable Source – Apply RVM to `close`, `open`, `hl2`, or any custom source.
╭─────╮
Usage
╰─────╯
Trend Confirmation: High RVM values can confirm strong trending conditions.
Breakout Detection: Spikes in RVM often precede or accompany price breakouts.
Volatility Cycle Analysis: Compare periods of contraction and expansion.
RVM is not bounded like the RVI, so absolute values depend on market volatility and chosen parameters.
Consider normalizing or using smoothing for easier visual comparison.
╭────────────────╮
Example Settings
╰────────────────╯
Short-term volatility detection: `stdDevLen = 5`, `sumLen = 10`
Medium-term trend volatility: `stdDevLen = 14`, `sumLen = 20`
Enable `SMA + Bollinger Bands` to visualize when volatility is unusually high or low relative to recent history.
╭───────────────────╮
Notes & Limitations
╰───────────────────╯
Not a directional signal by itself — use alongside price structure, volume, or other indicators.
Higher `sumLen` will smooth short-term fluctuations but reduce responsiveness.
Because it sums, not averages, values will scale with both volatility and chosen window size.
╭───────╮
Credits
╰───────╯
Based on the Relative Volatility Index concept by Donald Dorsey (1993).
TradingView
SciQua - Joshua Danford
Dollar Volume + SD [ZTD]### So, What's the Big Deal with SD Dollar Volume?
TL:DR
What you see:
1. $ Volume = (Price * Volume) / 1M (we divide it by 1M by default so you don't have to look at 12 digits but you can select between 100k/1M/10M)
2. User selected M.A. period with difference sources
3. Up to 4 Standard Deviation from that M.A.
4. Color coded (explained below)
That's it, no fancy useless multi color rainbows. Functional, bringing depth and clarity to your analysis based on reality not optical illusion.
--------------
The Long version
You know how we've always looked at volume? It's a classic, but it's got a blind spot. A million shares traded when a stock is at $10 is a completely different ballgame from a million shares traded when it's at $200. The first is $10M in action; the second is $200M. Traditional volume treats them the same, but they are not the same story.
That's the whole idea behind the **Dollar Volume Standard Deviation (SD $VVOLUME)** indicator. Instead of just counting shares, it tracks the **actual dollar amount** ( also refered as Dollar Volume) changing hands. This gives you a much clearer picture of the real financial power behind a price move. It helps you see when the "big money" is truly stepping in or backing off.
Think about it this way: after a 20% drop on earnings, you might see a 10% volume increase and think, "Wow, buyers are stepping in!" But if you look at the *value traded*, it might actually be lower than the day before because the share price is so much cheaper. This indicator cuts through that noise.
What about that smaller stock you bought that suddenly doubles in prices in a matter of months. Do you really thing the volume you are looking at carries any meaning anymore?
On longer time frame? Think about Volume traded vs Value Traded on NVDA for example. Looking at volume alone on those charts is absolutely meaningless. I even wonder why volume alone ever existed in the first place as an indicator.
### How to Use It in Your Trading
This isn't just theory; here’s how you can actually use it to make better decisions.
#### Reading the Indicator
The indicator is designed to be visual and intuitive. Here’s what you're looking at:
* **The Bars:** Each bar on the indicator represents the total dollar value traded during that period. Bigger bar, more money moved.
* **The White Line:** This is your baseline—the moving average of the value traded. It shows you the normal level of money flow for that stock.
* **Bar Colors (The Important Part):**
* **Direction:** **Green** means the stock closed higher in that period. **Red** means it closed lower. Simple enough.
* **Intensity:** This is the real magic. The brightness or intensity of the color tells you how significant that money flow was. A dull, faded bar means the value traded was pretty average. A **bright, intense bar** means the value was way above normal (usually 1 or 2 standard deviations away from the average). *That's* when you need to pay attention.
#### Actionable Signals for Your Strategy
* **Spotting High-Conviction Moves:** When you see a bright, intense red or green bar that towers over the others, that's a signal of major conviction. Big players are making a decisive move, either buying up everything in sight or dumping their positions. This is your cue that something significant is happening.
* **Confirming a Trend's Strength:** Are you in a strong uptrend? Look for a consistent pattern of bright green bars. This tells you that significant capital is flowing in to support the rising price. It's confirmation that the trend has legs.
* **Catching a Weakening Trend (Divergence):** This is a powerful one. Imagine the stock price is grinding out new highs, but on the SD
V
VOLUME
indicator, the bars are getting smaller and less intense. That's a major red flag. It shows that even though the price is inching up, the real money isn't following. There's no conviction, and the trend could be about to reverse.
* **Gauging Liquidity:** If the bars are consistently low and dull, it's a sign that interest in the stock is drying up. It's a good way to spot illiquid conditions and avoid getting trapped in a stock that's hard to get out of.
Ultimately, SD SEED_YASHALGO_NSE_BREADTH:VOLUME helps you see the market from a different angle. It's not just about the noise of shares being traded; it's about following the money.
Fat Tails Analyzer🧠 Fat Tails Analyzer — Analysis of Anomalous ("Fat-Tailed") Movements
📌 Description
Fat Tails Analyzer is a tool for analyzing "fat tails" in the distribution of returns. Unlike normal distribution, financial markets often exhibit frequent extreme movements. This indicator identifies and visualizes such events by analyzing logarithmic returns, deviations from normal distribution, and excess kurtosis.
🔬 Methodology
Logarithmic returns (ln(Close / Close )) are calculated for accurate aggregation and symmetry.
Moving average and standard deviation of returns are computed over a specified period.
"Fat-tailed" events are identified when returns exceed μ ± k·σ, where k is user-defined.
Normal distribution bands (±2σ) and kurtosis (a measure of tail "heaviness") are displayed for clarity.
📊 What It Displays
📈 Histogram of Returns: Green for positive, red for negative.
🟣 Fat Tail Threshold Lines: Marking extreme events.
⚪ Silver Normal Distribution Bands: ±2σ boundaries.
🔵 Kurtosis Line: If enabled.
📋 Table with Key Metrics: Mean, σ, kurtosis.
⚙️ Parameters
Lookback Period (Bars): Analysis period (default: 252).
Fat Tail Threshold (Std Devs): Deviation for extreme events (k, default: 2.5).
Show Normal Distribution Bands: Toggle ±2σ boundaries.
Show Kurtosis: Enable kurtosis analysis mode.
📌 Interpretation
Excess Kurtosis > 0: More extreme events than predicted by normal distribution.
Returns beyond fat-tail thresholds: Potential signals of panic, shock, or exceptional news.
Consistently high kurtosis: Unstable or speculative asset.
🧪 Applications
📉 Identify extreme risks in assets (especially cryptocurrencies and derivatives).
🧠 Study market behavior and dispersion.
🛡 Support risk analysis, stop-loss settings, and systemic risk assessment.
🔎 Compare assets by the "normality" of their behavior.
🧭 Live Metrics Table
Displayed in the bottom-right corner:
Mean return
Standard deviation
Excess kurtosis (color-coded by value)
🧠 Good to Know
Normal distribution has kurtosis = 0.
> 0: "Fat tails" (more extreme values).
< 0: "Thin tails" (values close to the mean).
Alma SD SuperTrend | OquantAlma SD SuperTrend | Oquant
The "Alma SD SuperTrend | Oquant" is a trend-following indicator that integrates the Arnaud Legoux Moving Average (ALMA) with a SuperTrend calculation based on standard deviation (SD). Designed to quickly identify and follow market trends while reducing noise, this script provides buy and sell signals for traders across various assets and timeframes.
This script offers a unique approach by combining ALMA with a SuperTrend framework that uses standard deviation instead of the traditional Average True Range (ATR). This implementation focuses on fast trend detection with minimized noise, making it suitable for trend-following or swing trading strategies. The script’s customizable parameters allow traders to adapt it to their preferred trading style.
How It Works
Arnaud Legoux Moving Average (ALMA): ALMA is an advanced moving average that applies a Gaussian filter to smooth price data, reducing market noise while preserving responsiveness to price changes. It uses three parameters:
Length: Sets the lookback period for smoothing. Longer periods produce smoother results.
Offset: Shifts the moving average toward recent prices. Higher offsets emphasize newer data for faster trend detection.
Sigma controls the smoothness and lag of the Alma by adjusting the spread of the Gaussian distribution used in the calculation.
Standard Deviation (SD) Calculation: The script calculates the standard deviation of the price over a specified period to measure volatility. SD measures how much the prices deviate from its mean, offering a statistical perspective on market volatility. This is used to create dynamic upper and lower bands around the ALMA line, adjusted by a user-defined factor. The bands expand in volatile markets and contract in stable conditions, helping in trend detection.
SuperTrend Logic: The script generates a SuperTrend line that dynamically tracks market trends by switching between upper and lower volatility bands based on price movement. Here's how it works:
The SuperTrend line is calculated using the ALMA (Arnaud Legoux Moving Average) as a baseline, with upper and lower bands created by adding and subtracting a multiple(Factor) of the standard deviation (SD) from the ALMA.
When the price moves above the upper band, the SuperTrend line shifts to the lower band, indicating a bullish trend (potential buy signal).
When the price falls below the lower band, the SuperTrend line switches to the upper band, signaling a bearish trend (potential sell signal).
To avoid quick, unreliable changes, this script intelligently adjusts the SuperTrend bands for stability. While the SuperTrend line dynamically follows market movements, it's designed to hold at its previous level if the price doesn't cross a band or confirm a new trend direction. This approach ensures the SuperTrend quickly identifies and follows genuine market trends, providing clear signals while effectively reducing false alerts from short-term price swings.
Differences from Traditional SuperTrend:
Baseline: The traditional SuperTrend typically uses a hl2((high + low)/2)as its baseline, while this script employs ALMA for a smoother, noise-filtered trend foundation.
Volatility Measure: Instead of ATR, this script uses standard deviation to calculate the bands. Standard deviation measures how much the prices vary or spread out from its mean.
Visualization: The script plots the SuperTrend line, colors candles to match the trend, and fills the area between the price and the SuperTrend line for visual clarity, helping traders quickly identify trend direction and strength (green for bullish, purple for bearish).
How to Use It
Add to Chart: Apply the indicator to any market and timeframe.
Interpret Signals:
Green Line and Candles: Bullish trend (price above the SuperTrend line). Consider long entries.
Purple Line and Candles: Bearish trend (price below the SuperTrend line). Consider short entries.
Filled Area: The shaded area between price and the SuperTrend line highlights trend direction(green for bullish, purple for bearish).
Adjust Inputs:
Source: Select the price data to use (e.g., close, open, high, low).
Factor: Adjusts band width. Higher values widen bands, reducing sensitivity.
SD Length: Period for calculating standard deviation. Longer periods smooth volatility.
ALMA Length: Period for ALMA. Longer periods increase smoothness.
Alma Offset: Shift the moving average toward recent or older prices. Higher offsets emphasize newer data for faster trend detection.
ALMA Sigma control the smoothness and lag of the Alma by adjusting the spread of the Gaussian distribution used in the calculation.
Alerts
This indicator includes optional built-in alert conditions that notify you when the signal crosses above 0 (long signal, price above upper band) or below 0 (short signal, price below lower band). Enable these alerts to get timely updates on potential trend shifts without constantly monitoring the chart.
⚠️ Disclaimer: This indicator is intended for educational and informational purposes only. Trading/investing involves risk, and past performance does not guarantee future results. Always test and evaluate indicators/strategies before applying them in live markets. Use at your own risk.
Volatility Strategy 01a quantitative volatility strategy (especially effective in trend direction on the 15min chart on the s&p-index)
the strategy is a rule-based setup, which dynamically adapts to the implied volatility structure (vx1!–vx2!)
context-dependent mean reversion strategy based on multiple timeframes in the vix index
a signal is provided under following conditions:
1. the vvix/vix spread has deviated significantly beyond one standard deviation
2. the vix is positioned above or below 3 moving averages on 3 minor timeframes
3. the trade direction is derived from the projected volatility regime, measured via vx1! and vx2! (cboe)
Volatility Zones (STDEV %)This indicator displays the relative volatility of an asset as a percentage, based on the standard deviation of price over a custom length.
🔍 Key features:
• Uses standard deviation (%) to reflect recent price volatility
• Classifies volatility into three zones:
Low volatility (≤2%) — highlighted in blue
Medium volatility (2–4%) — highlighted in orange
High volatility (>4%) — highlighted in red
• Supports visual background shading and colored line output
• Works on any timeframe and asset
📊 This tool is useful for identifying low-risk entry zones, periods of expansion or contraction in price behavior, and dynamic market regime changes.
You can adjust the STDEV length to suit your strategy or timeframe. Best used in combination with your entry logic or trend filters.
Adaptive Multi-MA OptimizerAdaptive Multi-MA Optimizer
This indicator provides a powerful, customizable solution for traders seeking dynamically optimized moving averages with precision and control. It integrates multiple custom-built moving average types, applies real-time volatility-based optimization, and includes an optional composite smoothing engine.
🧠 Key Features
Dynamic Optimization:
Automatically selects the optimal lookback length based on market volatility stability using a custom standard deviation differential model.
Multiple Custom MA Types:
Includes fully custom implementations of:
SMA (Simple Moving Average)
EMA (Exponential Moving Average)
WMA (Weighted Moving Average)
VWMA (Volume Weighted MA)
DEMA (Double EMA)
TEMA (Triple EMA)
Hull MA
ALMA (Arnaud Legoux MA)
Composite MA Option:
A unique "Composite" mode blends all supported MAs into a single average, then applies optional smoothing for enhanced signal clarity.
Dynamic Smoothing:
The composite mode supports volatility-adjusted smoothing (based on optimized lookback), making it adaptable to different market regimes.
Fully Custom Logic:
No built-in MA functions are used — every moving average is hand-coded for transparency and educational value.
⚙️ How It Works
Optimization:
The script evaluates a range of lengths (minLen to maxLen) using the standard deviation of price returns. It selects the length with the most stable recent volatility profile.
Calculation:
The selected MA type is calculated using that optimized length. If "Composite" is chosen, all MA types are averaged and smoothed dynamically.
Visualization:
The adaptive MA is plotted on the chart, changing color based on its position relative to price.
📌 Use Cases
Trend-following strategies that adapt to different market conditions.
Traders wanting a high-fidelity composite of multiple MAs.
Analysts interested in visualizing market smoothness without lag-heavy signals.
Coders looking to learn how to build custom indicators from scratch.
🧪 Inputs
MA Type: Choose from 8 MA types or a blended Composite.
Lookback Range: Control min/max and step size for optimization.
Source: Choose any price series (e.g., close, hl2).
⚠️ Disclaimer
This indicator is for educational and informational purposes only and does not constitute financial advice, trading advice, or investment recommendations. Use of this script is at your own risk. Past performance does not guarantee future results. Always perform your own analysis and consult with a qualified financial advisor before making trading decisions.
Dynamic Laguerre Filter Bands | OttoThis indicator combines trend-following and volatility analysis by enhancing the traditional Laguerre filter with a dynamic, volatility-adjusted band system. Instead of using fixed thresholds, the bands adapt in real-time to changing market conditions by applying smoothed standard deviation calculations. This design keeps the indicator responsive to significant price movements while effectively filtering out short-term market noise, resulting in more accurate trend identification and breakout signals.
Core Concept
The indicator is built around the following key components:
Laguerre Filter:
The Laguerre filter is designed to smooth out price data by reducing market noise while still being quick enough to detect real changes in price direction. Its goal is to create a clear, smooth trend line that helps traders/investors focus on the overall market trend without getting distracted by small, random price swings.
It uses a parameter called gamma to control how it balances smoothness and responsiveness:
A lower gamma gives more weight to recent price data, making the filter react faster to new price changes. This means the trend line is more sensitive but may also be less smooth and more prone to small fluctuations.
A higher gamma gives more weight to past price data, making the filter smoother and less sensitive to quick changes. This helps reduce noise and produces a steadier trend line, but it also introduces more lag, meaning the filter reacts slower to new price moves.
By adjusting gamma, the Laguerre filter lets you choose the balance between following price changes quickly and having a stable, noise-free trend signal.
Standard Deviation:
shows how much price varies from the mean. In this indicator, it’s used to measure market volatility.
Volatility Bands: The upper and lower bands are based on an EMA-smoothed standard deviation of price. The EMA reduces sudden jumps in volatility, creating smoother and more stable bands that still respond to changing market conditions. These bands are plotted around the Laguerre filter line, expanding and contracting in a controlled way to stay aligned with real market movement while avoiding short-term noise.
Signal Logic:
A long signal is triggered when the close price crosses above the upper band.
A short signal occurs when the close price falls below the lower band.
⚙️ Inputs
Source: Price source used in calculations
Gamma: Adjusts how much the Laguerre filter responds to price changes. Lower gamma values make the filter react more to recent prices, while higher values give more influence to older data, making the line smoother but slower to respond.
Volatility Length: Period used to calculate standard deviation
Volatility Smoothing Length: EMA smoothing length for standard deviation
Multiplier: Scales the width of the bands based on volatility
📈 Visual Output
Laguerre Filter Line: Plots the laguerre filter line, colored dynamically based on signal direction (green for bullish, purple for bearish)
Upper & Lower Bands: Volatility-based bands that adjust with market conditions. (green for bullish, purple for bearish)
Glow Effect: Optional glow layer to enhance visibility of the laguerre filter trend line (green for bullish, purple for bearish)
Bar Coloring: Candlesticks and bar colors reflect the active signal state for fast visual interpretation (green for bullish, purple for bearish)
How to Use
Apply the indicator to your chart and monitor for signal events:
Long Signal: When price closes above the upper band
Short Signal: When price closes below the lower band
🔔 Alerts
This indicator supports optional alert conditions you can enable for:
Long Signal: Close price crossing above the upper band
Short Signal: Close price crossing below the lower band
⚠️ Disclaimer:
This indicator is intended for educational and informational purposes only. Trading/investing involves risk, and past performance does not guarantee future results. Always test and evaluate indicators/strategies before applying them in live markets. Use at your own risk.
Adaptive Normalized Global Liquidity OscillatorAdaptive Normalized Global Liquidity Oscillator
A dynamic, non-repainting oscillator built on real central bank balance sheet data. This tool visualizes global liquidity shifts by aggregating monetary asset flows from the world’s most influential central banks.
🔍 What This Script Does:
Aggregates Global Liquidity:
Includes Federal Reserve (FED) assets and subtracts liabilities like the Treasury General Account (TGA) and Reverse Repo Facility (RRP), combined with asset positions from the ECB, BOJ, PBC, BOE, and over 10 other central banks. All data is normalized into USD using FX rates.
Adaptive Normalization:
Optimizes the lookback period dynamically based on rate-of-change stability—no fixed lengths, enabling adaptation across macro conditions.
Self-Optimizing Weighting:
Applies inverse standard deviation to balance raw liquidity, smoothed momentum (HMA), and standardized deviation from the mean.
Percentile-Ranked Highlights:
Liquidity readings are ranked relative to history—extremes are visually emphasized using gradient color and adaptive transparency.
Non-Repainting Design:
Data is anchored with bar index awareness and offset techniques, ensuring no forward-looking bias. What you see is what was known at that time.
⚠️ Important Interpretation Note:
This is not a zero-centered oscillator like RSI or MACD. The signal line does not represent neutrality at zero.
Instead, a dynamic baseline is calculated using a rolling mean of scaled liquidity.
0 is irrelevant on its own—true directional signals come from crosses above or below this adaptive baseline.
Even negative values may signal strength if they are rising above the moving average of past liquidity conditions.
✅ What to Watch For:
Crossover Above Dynamic Baseline:
Indicates liquidity is expanding relative to recent conditions—supports a risk-on interpretation.
Crossover Below Dynamic Baseline:
Suggests deteriorating liquidity conditions—may align with risk-off shifts.
Percentile Extremes:
Readings near the top or bottom historical percentiles can act as contrarian or confirmation signals, depending on momentum.
⚙️ How It Works:
Bounded Normalization:
The final oscillator is passed through a tanh function, keeping values within and reducing distortion.
Adaptive Transparency:
The strength of deviations dynamically adjusts plot intensity—visually highlighting stronger liquidity shifts.
Fully Customizable:
Toggle which banks are included, adjust dynamic optimization ranges, and control visual display options for plot and background layers.
🧠 How to Use:
Trend Confirmation:
Sustained rises in the oscillator above baseline suggest underlying monetary support for asset prices.
Macro Turning Points:
Reversals or divergences, especially near OB/OS zones, can foreshadow broader risk regime changes.
Visual Context:
Use the dynamic baseline to see if liquidity is supportive or suppressive relative to its own adaptive history.
📌 Disclaimer:
This indicator is for educational and informational purposes only. It does not constitute financial advice. Past performance is not indicative of future results. Always consult a qualified financial advisor before making trading or investment decisions.
