Indicator
Nadaraya-Watson Envelope [Gabremoku]Nadaraya-Watson Envelope
This indicator builds a non-repainting Nadaraya-Watson envelope using a one-sided Gaussian kernel, so every value is computed from the current bar and past bars only. The goal is to provide a smoother adaptive baseline than a standard moving average while keeping the script operationally honest and suitable for live use.
What makes this script different:
- The central basis is a kernel-weighted Nadaraya-Watson estimate, not a classic SMA/EMA baseline.
- The main envelope is not built from standard deviation by default. It uses kernel-weighted mean absolute deviation (MAD), which is generally less sensitive to single-bar outliers and often produces a more stable channel.
- Standard deviation bands can still be enabled as an optional overlay, so users can compare MAD-based and Stdev-based dispersion around the same kernel basis.
- Signal logic is configurable. Breakout labels can be triggered by close crossing the band, wick piercing the band, or full body breakout, which makes the visual behavior easier to align with the trader’s interpretation.
How it works:
The script applies Gaussian weights to past bars inside the selected window. More recent bars receive the highest weight, while older bars progressively contribute less. The Bandwidth input controls how fast those weights decay. In practice, the effective lookback is usually much shorter than the full Window setting when Bandwidth is low. A practical rule of thumb is that the effective lookback is about 3 × Bandwidth bars, capped by the Window value.
The indicator computes:
1. A kernel-weighted mean, used as the Nadaraya-Watson basis.
2. A kernel-weighted MAD, used as the primary envelope width.
3. An optional kernel-weighted standard deviation, displayed only when the comparison bands are enabled.
The upper and lower MAD bands are then filled with a gradient that increases in strength as price moves away from the basis toward the envelope edges. This makes the visual intensity reflect displacement magnitude, not just bullish or bearish direction.
Compression logic:
The compression zone is based on min-max normalization of envelope width over a lookback period. This is not a statistical percentile rank. A threshold of 0.15 means the current envelope width is near the lower end of the observed width range over the selected compression lookback.
Signal modes:
- Close Cross: triggers only when the close crosses a band.
- Wick Pierce: triggers when the candle’s high or low exceeds a band.
- Body Breakout: triggers when the candle body exceeds a band.
Use Wick Pierce if you want signal labels to match the visible moment where candles extend outside the envelope.
How to use it:
- Use the basis as an adaptive trend reference.
- Use the MAD envelope to judge whether price is stretched relative to recent kernel-weighted behavior.
- Watch compression zones for narrow-range conditions that may precede expansion.
- Compare MAD and Stdev bands when you want to evaluate whether recent volatility is dominated by isolated spikes or by broader dispersion.
Practical notes:
- This script is non-repainting by construction because it does not use centered calculations or future bars.
- Low Bandwidth values create a more reactive basis and shorter effective memory.
- High Bandwidth values create a smoother basis and wider historical influence.
- Increasing Window far beyond roughly 3 × Bandwidth usually has little additional effect.
- Signal labels are state-machine filtered, so they are designed to mark sequence transitions rather than every repeated touch outside the bands.
This indicator is intended as a visual decision-support tool, not as a standalone trading system. It helps traders study adaptive trend, envelope displacement, compression, and breakout structure in a cleaner way than a standard volatility channel. Indicator
Smooths VWAP SuiteTitle: Smooth's VWAP Suite: Advanced Futures Context & Filtered Signals
Description:
Overview & Purpose
Smooth's VWAP Suite is a comprehensive volume-weighted average price toolkit engineered specifically for futures traders (e.g., NQ, ES).
The primary justification for combining these specific elements—Daily VWAP, Standard Deviation Bands, Session AVWAPs (Overnight, RTH, Weekly), and dynamic signals—into a single script is to solve the problem of "context fragmentation." Futures markets respect multiple volume anchors simultaneously. Rather than cluttering a chart with five individual, unlinked indicators, this suite unites micro (intraday) and macro (weekly) volume levels into one cohesive map. Furthermore, it introduces a custom "Current Day Only" filter mathematically anchored to the 18:00 EST futures open, fixing the common issue where standard indicators rely on the midnight calendar-day rollover.
How It Works: Underlying Concepts & Logic
This script calculates the Volume-Weighted Average Price by maintaining a cumulative running total of Price × Volume, divided by Total Volume.
Session AVWAPs & Previous Day: The script calculates distinct VWAPs based on specific time anchors. It automatically tracks the Weekly open, the Regular Trading Hours (RTH) open, and the Overnight (OVN) session. It also statically plots the Previous Day's closing VWAP value, acting as a critical pivot for the current session.
Standard Deviation Variance: The bands surrounding the Daily VWAP are calculated using the mathematical square root of volume-weighted variance. This provides dynamic, mathematically sound support and resistance zones based on current market volatility, plotted at user-defined multipliers (defaulting to 1.0, 2.0, and 3.0 SD).
Signal Engine & EMA Filter: The built-in signals are not basic crossovers. To prevent false signals in chopping ranging markets, the script requires an EMA (Exponential Moving Average) directional filter to confirm the trend.
Reversal/Cross Signals: Trigger when price straddles the VWAP, closes on the opposite side, is aligned with the EMA slope, and is positioned correctly relative to the Weekly VWAP.
Continuation Signals: Trigger when price pushes into a Standard Deviation band (e.g., SD 1 or SD 2) and actively rejects it, closing back toward the trend direction while maintaining the EMA slope.
How Traders Can Use It
This suite is designed for trend identification, mean-reversion targeting, and precise entry confirmation.
Macro Context Alignment: Use the Weekly and Previous Day VWAP lines to determine the broader bias. If the current Daily VWAP is trading above both, the macro trend is bullish.
Mean Reversion: When price extends into the SD 2 or SD 3 bands, the asset is statistically overextended based on current volume. Traders can look for price action weakness at these extremes to target a reversion back to the Daily VWAP (the mean).
Signal Execution: Utilize the script's visual markers (Arrows/Triangles) for entry confirmations. A bullish signal firing after a bounce off the lower SD 1 band, while the Daily VWAP remains above the Weekly VWAP, offers a high-probability continuation setup.
Chart Decluttering: For active day traders, toggle the "Current Day Only" setting. This utilizes custom logic to sever all historical visual data prior to the exact 18:00 EST futures anchor, keeping your screen entirely focused on the current session's price action.
Customization
Every element is modular. Traders can toggle specific bands, adjust standard deviation multipliers, change the EMA filter length for signals, and customize the visual offsets of the price labels to fit their specific screen layout. Indicator
Structural Deviation Compass [JOAT]Structural Deviation Compass
Introduction
The Structural Deviation Compass is an overlay indicator designed to map where price stands relative to its own statistical history. Rather than drawing fixed-distance envelopes or relying on a single moving average, it constructs a hybrid centerline from two distinct low-lag moving average types, then wraps that centerline in volatility-adaptive bands derived from Z-score normalization. A secondary oscillator layer — applied to RSI — creates a dual-confirmation signal gate that fires only when both price deviation and momentum reach simultaneous extremes. Shadow bands built from the Average True Range provide additional spatial context across three volatility tiers.
The indicator does not predict future price. It identifies statistically unusual deviations from an estimated mean structure and flags conditions where a reversion or continuation setup may be forming, subject to confirmation from the trader's own process.
Core Concepts
The ComboMA Centerline
The foundation of the indicator is a composite moving average called the ComboMA, formed by averaging two lines:
ALMA (Arnaud Legoux Moving Average): Uses a Gaussian-weighted kernel positioned asymmetrically along the lookback window. The offset and sigma parameters control how far toward the recent end the weight mass sits and how tightly it is concentrated. This produces a smooth line that tracks price closely while suppressing noise better than a simple EMA of the same length.
ZLMA (Zero-Lag Moving Average): Constructed by doubling a base EMA and subtracting a second EMA of that EMA — a technique that estimates and removes the inherent lag of an exponential average. The result is then smoothed once more to reduce the noise amplification that zero-lag constructions can introduce.
Averaging the two produces a centerline that carries reduced lag from the ZLMA side while retaining the smooth, noise-filtered character of the ALMA side. Neither line alone fully satisfies both goals; together they produce a more balanced result.
Z-Score Price Bands
Rather than plotting bands at a fixed multiple of a standard deviation (as Bollinger Bands do using a rolling standard deviation of price itself), the SDC first computes the deviation of close from the ComboMA, then Z-score normalizes that deviation series over a separate lookback window. The bands are then placed back on the price chart by multiplying the rolling standard deviation of deviations by the chosen Z-score threshold values.
The practical effect is that the band width reflects how unusual the current deviation is relative to the recent distribution of deviations — not simply how wide price has swung in a raw sense. Two threshold levels are provided, creating an inner and outer band pair on each side of the ComboMA.
RSI Z-Score
RSI is computed in the standard way, then subjected to the same Z-score normalization: the RSI value is compared to its own rolling mean and expressed in standard deviations. This removes the fixed-level bias of RSI (where 30/70 thresholds mean different things in different market regimes) and produces a momentum reading that is self-calibrating to recent RSI behavior.
Dual Z-Score Signal Gate
A long signal requires all of the following simultaneously:
Price Z-score below the negative trigger threshold (price is statistically far below the ComboMA)
RSI Z-score below the negative trigger threshold (momentum is statistically depressed)
RSI EMA below 38 (confirming a bearish momentum context rather than a pullback within strength)
The current bar closed above the prior bar's close (a micro-confirmation that selling pressure may be easing)
The bar is confirmed (signal does not repaint on the forming bar)
Short signals apply the mirror logic. The requirement for extremes in both dimensions simultaneously is intentionally strict — it filters out the many cases where price is extended but momentum is not, or vice versa.
ATR Shadow Bands
Three pairs of shadow bands are drawn around the ComboMA at 1x, 2x, and 3x of a rolling ATR. These are not signal bands — they serve as a spatial reference, helping to contextualize how far price has traveled from the estimated mean in volatility-adjusted terms. A move to the 3x ATR shadow in a low-volatility environment carries different significance than the same move in a high-volatility environment.
RGB Smooth Color Transition
The ComboMA line color transitions smoothly between a bull and bear palette by independently blending the red, green, and blue channels via EMA. Each channel tracks a target value set by the current bull/bear state, and converges toward it gradually. This avoids abrupt color flips and gives a visual sense of momentum continuity.
Gradient Bar Coloring
Individual bars are colored based on where the close sits within the band range relative to the ComboMA. Bars near the upper bands trend toward the bull color; bars near the lower bands trend toward the bear color. Bars near the ComboMA receive a neutral tone. This is a visual aid only and does not constitute a signal.
Information Table
A 9-row table displays the current readings for: market regime, price Z-score, RSI Z-score, RSI EMA, band width, signal strength, active signal, and ComboMA value. This gives a snapshot of the indicator's internal state without requiring the trader to hover over each plotted element.
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Features
Hybrid ComboMA centerline combining ALMA and ZLMA
Volatility-adaptive Z-score bands at two threshold levels (inner and outer)
RSI Z-score normalization for regime-independent momentum reading
Dual Z-score signal gate requiring simultaneous extremes in price and momentum
Three-layer ATR shadow bands for spatial volatility context
Smooth RGB channel blending on the ComboMA line color
Gradient bar coloring based on position within band range
Real-time information table with 9 indicator state readings
Non-repainting signals (barstate.isconfirmed)
Fully toggleable visual components
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Input Parameters
MA Length: Base length for the ZLMA and ATR calculations
ALMA Offset: Controls asymmetric weight positioning within the ALMA window (0 = old end, 1 = recent end)
ALMA Sigma: Controls weight concentration; lower values spread the weight, higher values tighten it
Z-Score Lookback: Rolling window for computing the mean and standard deviation of price deviations (default: 50)
Inner Band Threshold: Z-score level for the inner band pair (default: 1.5σ)
Outer Band Threshold: Z-score level for the outer band pair (default: 2.5σ)
RSI Length: Period for RSI calculation (default: 14)
RSI Z-Score Lookback: Rolling window for normalizing RSI
Signal Trigger: Z-score threshold required in both dimensions to generate a signal (default: 1.8σ)
ATR Multipliers: Multipliers for the three shadow band tiers (1x, 2x, 3x)
Visual Toggles: Individual on/off controls for bands, shadows, bar coloring, table, and signals
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How to Use
Reading the centerline: The ComboMA acts as the estimated mean structure. Price consistently above it with a bull-colored line suggests sustained upward bias; price oscillating around it suggests a ranging environment.
Reading the bands: The inner bands (±1.5σ by default) represent moderately unusual deviations. The outer bands (±2.5σ by default) represent statistically rare deviations. A touch or breach of the outer band does not by itself mean a reversal is due — it means the move is statistically uncommon and warrants attention.
Reading the shadow bands: Use the ATR shadows to understand how far, in volatility-adjusted terms, price has moved from the ComboMA. Price at the 3x shadow while also at the outer Z-score band is a more notable condition than either reading alone.
Acting on signals: The dual Z-score signals flag confluent extremes. They should be used as an alert layer within a broader trading framework — not as standalone entry triggers. Consider the broader trend context, the timeframe, and supporting structure before acting.
Using the table: Monitor the signal strength reading to understand how close the current state is to triggering a signal. This is useful for watching a developing setup in real time.
Timeframe notes: The indicator functions on any timeframe. Higher timeframes produce fewer but more structurally significant signals. Lower timeframes will produce more signals, many of which will be noise. Adjust the Z-score lookback and trigger threshold accordingly.
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Limitations
This indicator does not predict future price movement. All readings are descriptive of past and current bar data.
The ComboMA, like all moving averages, will lag price during sharp trend changes. The ZLMA component reduces but does not eliminate this lag.
Z-score bands assume that price deviations are approximately normally distributed. In instruments with fat-tailed distributions or during extreme events, the statistical thresholds will underestimate the probability of outlier moves.
Signals are non-repainting on confirmed bars but will update on the forming bar until it closes. Always wait for bar close before acting on a signal.
A signal firing does not mean price will reverse. Trending markets can sustain extreme Z-score readings for extended periods.
The RSI EMA threshold (38 for longs) is a fixed filter that may not suit all instruments or regimes. It should be adjusted or disabled if it is filtering out valid setups in the instrument being traded.
The ATR shadow bands are informational only and carry no predictive weight.
Past signal performance on a given instrument is not indicative of future performance.
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Originality Statement
The ALMA and ZLMA are established concepts. The ComboMA is not either of them — it is a blended centerline that takes the asymmetric-weight smoothness of ALMA and the lag-reduction property of ZLMA and produces a composite that neither achieves individually. The Z-score normalization of price deviations is a statistical adaptation that makes the bands self-calibrating to the instrument's deviation distribution rather than fixed. Applying the same normalization independently to RSI produces a momentum reading that is self-referential to recent RSI behavior rather than anchored to universal threshold levels. The signal gate that requires simultaneous Z-score extremes in both price deviation and RSI — not one or the other — creates a logical AND condition that is substantially stricter than conventional oscillator crossovers or single-band-touch triggers. The three ATR shadow tiers, smooth RGB color blending, and gradient bar coloring are supporting visual constructs that serve interpretation rather than adding trading logic. The combination of these elements into a single overlay tool — ComboMA centerline, adaptive Z-score bands, normalized momentum gate, ATR spatial context, and state table — represents an original integration not replicated by any standard built-in indicator.
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Disclaimer
This indicator is provided for educational and informational purposes only. It does not constitute financial advice, investment advice, or a recommendation to buy or sell any financial instrument. Trading involves substantial risk of loss. Past performance of any indicator or strategy is not indicative of future results. Always conduct your own research and consult a qualified financial professional before making any trading decisions.
-Made with passion by officialjackofalltrades
Indicator
Indicator
Standard Deviation Channel (4x)Standard Deviation Channel (4x)
A linear regression channel with up to 4 standard deviation bands on each side, plus built-in moving averages and high/low levels from higher timeframes. Basically everything I need on one indicator without cluttering my chart with 5 different scripts.
What it does
The core is a standard deviation channel based on linear regression. You get the regression line (base) and can enable up to 4 deviation levels above and below (±1σ, ±2σ, ±3σ, ±4σ). Each level can be toggled independently and the multipliers are adjustable if you want something like 1.5 or 2.5 instead of whole numbers. The fills between bands help visualize the zones.
Pearson's R is available if you want to see the correlation strength of the regression.
Moving Averages
6 MAs included, each fully configurable:
- Type: SMA, EMA, WMA, VWMA, RMA, HMA, DEMA, TEMA
- Custom length and source
- Individual colors
High/Low Levels
Shows horizontal lines at:
- Weekly High/Low
- Monthly High/Low
- Yearly High/Low
- Previous Week/Month/Year High/Low
Useful for spotting key levels without switching timeframes. Labels included so you know which line is which.
Alerts
- Deviation band breaks (all 8 levels)
- MA crossovers (price crossing above/below)
- High/Low level breaks
Settings
Everything is off by default except the ±1σ and ±2σ bands. Enable what you need, disable what you don't. Colors are fully customizable. Indicator
Indicator
Kijun Sen Standard Deviation | QuantLapse SystemsOverview
The Kijun Sen Standard Deviation indicator by QuantLapse Systems is a volatility-aware trend-following framework that combines the structural equilibrium of the Kijun Sen (基準線) with statistically adaptive standard deviation bands.
By anchoring trend detection to market structure and confirming direction through volatility expansion, the indicator delivers a cleaner, more reliable regime classification across varying market conditions.
Rather than reacting to short-term noise, the system focuses on identifying statistically justified trend phases , making it well-suited for disciplined, rule-based trading.
Technical Composition, Calculation, Key Components & Features
📌 Kijun Sen (基準線) – Structural Trend Baseline
Calculated as the midpoint between the highest high and lowest low over a user-defined period.
Represents market equilibrium and structural balance rather than short-term momentum.
Naturally adapts to expanding and contracting price ranges.
Provides a stable baseline for regime detection and volatility validation.
Acts as the anchor for deviation bands and persistent trend-state logic.
Unlike fast or reactive moving averages, the Kijun Sen emphasizes price structure and equilibrium , making it especially effective for higher-quality trend confirmation.
📌 Volatility Adjustment – Standard Deviation Bands
Standard deviation is calculated over a configurable lookback to measure current price dispersion.
Upper and lower envelopes are formed by applying a deviation multiplier to the Kijun Sen.
Band width expands during volatility surges and contracts during consolidation.
Creates proportional, volatility-aware thresholds instead of static offsets.
Visually represents market energy through expanding and compressing channels.
These adaptive bands ensure that trend signals only occur when volatility supports directional movement.
📌 Trend Signal & Regime Calculation
Bullish Trend is confirmed when price closes above the upper deviation band.
Bearish Trend is confirmed when price closes below the lower deviation band.
Once established, the trend state persists until an opposing volatility break occurs.
This persistence reduces whipsaws and improves regime stability.
Trend state is reinforced with color-coded lines, envelopes, and background shading.
This volatility-confirmed persistence model is visible in the chart, where trends remain intact through minor pullbacks and only flip on decisive expansion.
How It Works in Trading
✅ Volatility-Confirmed Trend Detection – Requires expansion beyond deviation bands.
✅ Noise Suppression – Filters low-energy price movement within volatility envelopes.
✅ Regime Persistence – Maintains trend state until statistical invalidation.
✅ Immediate Visual Context – Direction, strength, and transitions are clear at a glance.
Visual Representation
Trend signals are displayed directly on price using both line and background context:
🟢 Green / Teal Kijun & Envelope → Confirmed bullish regime.
🔴 Red / Pink Kijun & Envelope → Confirmed bearish regime.
Semi-transparent band fill visualizes volatility expansion and compression.
Buy and Sell labels appear only on confirmed regime transitions.
The lower panel includes:
Strategy equity curve based on trend exposure.
Buy & Hold equity for performance comparison.
Background regime shading synchronized with trend state.
Features and User Inputs
The Kijun Sen Standard Deviation framework offers a focused yet powerful set of configurable inputs:
Kijun Sen Length – Controls structural trend sensitivity.
Standard Deviation Controls – Adjust lookback length and multiplier for regime strictness.
Backtesting & Date Filters – Define evaluation periods and starting conditions.
Display Options – Toggle labels, equity curves, and background shading.
Color Customization – Fully configurable buy/sell colors for trends and equity curves.
These controls allow users to balance responsiveness, stability, and clarity without overfitting.
Practical Applications
The Kijun Sen Standard Deviation indicator is designed for traders who prioritize structure, volatility confirmation, and regime awareness.
Primary Trend Filtering – Identify and stay aligned with dominant market direction.
Volatility-Aware Trend Following – Participate only when price expansion confirms intent.
Risk-Managed Exposure – Avoid chop during compression and transitional phases.
Systematic Strategy Development – Use as a regime engine or higher-timeframe filter.
Performance Evaluation – Compare trend-following equity against buy-and-hold benchmarks.
This framework bridges classical Ichimoku structure with modern statistical validation.
Conclusion
The Kijun Sen Standard Deviation indicator by QuantLapse Systems represents a refined evolution of Ichimoku-based trend analysis.
By integrating the structural equilibrium of the Kijun Sen with adaptive standard deviation confirmation, the system delivers clearer regime classification, reduced noise, and more reliable trend participation.
Rather than attempting to predict price, it focuses on confirming when trends are statistically justified .
Who should use Kijun Sen Standard Deviation:
📊 Trend-Following Traders – Stay aligned with dominant market structure.
⚡ Momentum & Swing Traders – Enter only on volatility-backed expansions.
🤖 Systematic & Algorithmic Traders – Ideal as a regime filter or trend-state engine.
Past performance is not indicative of future results.
Disclaimer: All trading involves risk, and no indicator can guarantee profitability.
Strategic Advice: Always backtest thoroughly, optimize parameters responsibly, and align settings with your timeframe, asset class, and risk tolerance before live deployment. Indicator
Consolidation Zones Volume Delta | Flux ChartsGENERAL OVERVIEW:
The Consolidation Zones Volume Delta | Flux Charts indicator is designed to identify and visualize consolidation zones on the chart. Rather than only outlining areas of sideways price movement, the indicator analyzes volume activity occurring inside each consolidation zone. This is done by aggregating lower-timeframe volume data into the higher-timeframe consolidation range, allowing users to see how buying and selling activity evolves while price remains in a range.
What is the theory behind the indicator?:
The indicator is built around three core analytical concepts that guide how consolidation zones are detected and evaluated.
1. Consolidation as a structural phase
Periods of consolidation are characterized by reduced directional movement and compressed price ranges. During these phases, price action often alternates within a defined high–low boundary, creating a structure that can be objectively measured and tracked over time.
2. Volume behavior inside consolidation
While price may appear balanced within a consolidation range, volume activity inside that range can vary. The indicator evaluates volume contributions occurring within the vertical boundaries of the consolidation zone by using lower-timeframe data and weighting each candle’s volume based on its overlap with the zone. This produces an internal volume delta profile that reflects how buying and selling volume accumulates throughout the consolidation.
Delta behavior inside a zone may show:
Persistent dominance of buying or selling volume
Alternating shifts between buyers and sellers
Periods of relatively balanced participation
3. Markets consolidate in multiple ways, one detection method is not enough
Markets do not consolidate in a single, uniform way. To account for this, the indicator includes three distinct consolidation detection methods. Each method is calculated objectively, does not repaint, and targets a different type of sideways or low-expansion price behavior:
Candle Compression
ADX Low Trend Strength
Visual Range Boundaries
CONSOLIDATION ZONES VOLUME DELTA FEATURES:
The Consolidation Zones Volume Delta indicator includes 4 main features:
Consolidation Zones
Volume Delta
Standard Deviation Bands
Alerts
CONSOLIDATION ZONES:
🔹What is a Consolidation Zone?
A consolidation zone is a defined price range where market movement becomes compressed and price remains contained within clear upper and lower boundaries for a sustained period of time. During this phase, price does not establish a strong directional trend and instead oscillates within a relatively narrow range.
🔹Consolidation Zone Detection
The indicator automatically detects consolidation zones using three independent, rule-based methods. Each method evaluates a different market condition and can be selected individually depending on how you want consolidation to be defined. Regardless of the method used, all zones are calculated objectively and finalized once confirmed.
◇ Candles (Candle Compression)
The Candles method identifies consolidation by detecting periods of candle compression and reduced range expansion. A candle is considered part of a consolidation sequence when:
The candle body is small relative to its total range
The candle’s high–low range is smaller than the short-term Average True Range (ATR)
ATR is calculated using a 4-period average true range and is used as a volatility reference. If consecutive candles continue to meet these compression conditions, the indicator increments an internal count.
Under the Consolidation Candles section in the settings, you’ll find two controls.
Min. Consolidation Candles setting
This defines how many consecutive compressed candles are required before a consolidation zone is confirmed. Candle compression is determined using candle structure and short-term ATR, ensuring that only periods of reduced range expansion are counted. Once the minimum threshold is reached, the indicator creates a consolidation zone using the highest high and lowest low formed during the compressed sequence.
Mark Consolidation Candles
When enabled, the indicator highlights candles that meet the compression criteria, making it easy to visually identify which candles contributed to the formation of the consolidation zone.
◇ ADX (Low Trend Strength)
The ADX method identifies consolidation based on weak or declining trend strength rather than candle structure. This method uses the Average Directional Index (ADX) to determine when directional movement is reduced.
ADX is calculated using directional movement values that are smoothed over time. When ADX remains below a user-defined threshold, price is treated as being in a low-trend market. While this condition persists, the indicator tracks the highest high and lowest low formed during the low-trend period.
Under the ADX Settings section in the settings, you’ll find the following controls.
ADX Length
Defines the lookback period used to calculate directional movement for ADX.
ADX Smoothing
Controls the smoothing applied to the ADX calculation.
ADX Threshold
Sets the level below which ADX must remain for the market to be considered consolidating.
Consolidation Strength
Defines how many consecutive candles’ ADX must stay below the threshold before a consolidation zone is confirmed. Once this requirement is met, the indicator creates a consolidation zone using the accumulated high and low from the low-trend window.
Mark Candles Below Threshold
When enabled, the indicator highlights candles where ADX remains below the threshold.
◇ Visual Range
The Visual Range method identifies consolidation by detecting clearly defined horizontal price ranges where price remains contained for a sustained period of time. The indicator continuously tracks the rolling highest high and lowest low across recent candles. When price remains inside the same high–low boundaries without breaking above or below the range, an internal counter advances.
Under the Visual Range section in the settings, you’ll find the following control.
Min. Candles in Range
Defines how many consecutive candles must remain fully contained within the same high–low range before a consolidation zone is confirmed. Once this requirement is met, the indicator creates a consolidation zone using the established range boundaries.
🔹Consolidation Zone Settings
◇ Invalidation Method
Users can choose how Consolidation Zones are invalidated, selecting between Close Break or Wick Break.
Close Break: A Consolidation Zone is invalidated when a candle closes above/below the zone.
Wick Break: A Consolidation Zone is invalidated when a candle’s wick goes above/below the zone.
◇ Merge Overlapping Zones
When enabled, overlapping Consolidation Zones are automatically combined into one unified zone.
◇ Show Last
This setting determines how many Consolidation Zones are displayed on your chart. For example, setting this to 5 will display the 5 most recent zones.
VOLUME DELTA:
Delta Volume visualizes how buying and selling volume accumulates inside each consolidation zone. Instead of using the full candle volume, the indicator isolates only the volume that occurs within the vertical boundaries of the zone. This allows you to see whether bullish or bearish volume is dominating while price remains range-bound. The visualization updates in real time while the zone is active and reflects cumulative participation rather than individual candles.
🔹How Volume Delta is Calculated
Delta Volume is calculated using lower-timeframe data and applied to the higher-timeframe consolidation zone.
Each candle’s volume is split into bullish or bearish volume based on candle direction.
Lower-timeframe candles are pulled using the selected delta timeframe.
For each lower-timeframe candle, only the portion of volume that vertically overlaps the consolidation zone is counted.
Volume is weighted by the amount of overlap between the candle’s range and the zone’s range.
Bullish and bearish volume are accumulated over time to form a running, cumulative delta profile for the zone.
🔹Volume Delta Settings
◇ Enable
Turns the Delta Volume visualization on or off. Consolidation zones continue to plot when disabled.
◇ Show Delta %
Displays the percentage breakdown of bullish versus bearish volume inside the consolidation zone. Percentages are derived from cumulative volume totals.
◇ 3D Visual
When enabled, the delta blocks are extended diagonally using a depth offset derived from the instrument’s daily ATR. This creates visible side faces and top faces for the delta blocks, simulating depth without altering any calculations. The 3D effect is purely visual. It does not change how volume is calculated, weighted, or accumulated.
Users can control the intensity of the 3D effect choosing a value between 1 and 5. Increasing this value increases:
The horizontal offset of the delta blocks
The vertical depth projection applied to the volume faces
Higher values produce a more pronounced 3D appearance by pushing the delta visualization further away from the consolidation box. Lower values keep the visualization flatter and closer to the box boundaries. The depth scaling is normalized using ATR, so the effect adapts proportionally to the instrument’s volatility.
◇ Volume Delta Display Style
Controls how bullish and bearish volume are displayed inside the Consolidation Zone:
Horizontal: Volume is split top-to-bottom within the zone
Vertical: Volume is split left-to-right across the zone
◇ Timeframe
Defines the lower timeframe used for Volume Delta calculations. When a timeframe is selected, the indicator pulls lower-timeframe price and volume data and maps it into the higher-timeframe consolidation zone. Each lower-timeframe candle is evaluated individually. Only the portion of its volume that vertically overlaps the consolidation zone is included, and that volume is weighted based on the candle’s overlap with the zone’s price range. If the Timeframe field is left empty, the indicator defaults to using the chart’s current timeframe for delta calculations.
Using a lower timeframe increases the granularity of the delta calculation, allowing volume changes inside the zone to be measured more precisely. Using a higher timeframe produces a smoother, less granular delta profile.
Please Note: Delta rendering is automatically limited to available lower-timeframe data to prevent incomplete or distorted visuals when historical lower-timeframe volume is unavailable due to PulseWire data limits.
STANDARD DEVIATION BANDS:
Standard Deviation Bands project measured price distance away from a confirmed consolidation zone using the size of that zone as the reference unit. Rather than calculating volatility from historical price dispersion, the bands are derived directly from the height of the consolidation range itself. Each band represents a fixed multiple of the consolidation zone’s height and is plotted symmetrically above and below the zone.
🔹How the bands are calculated
Once a consolidation zone is finalized, the indicator calculates the zone height as:
Zone Height = Zone High − Zone Low
This value becomes the base measurement for all deviation calculations. For each enabled band:
Upper bands are placed above the consolidation zone’s high
Lower bands are placed below the consolidation zone’s low
The distance of each band from the zone is calculated by multiplying the zone height by the selected band multiplier. These band levels are fixed relative to the consolidation zone and do not recalculate based on future price movement.
🔹Standard Deviation Band Settings
◇ Band 1
Enables the first deviation band above and below the consolidation zone. The Band 1 multiplier defines how far the band is placed from the zone in terms of zone height. For example, a multiplier of 1 plots the band one full zone height above and below the consolidation range.
◇ Band 2
Enables a second deviation band at a greater distance from the consolidation zone. Band 2 uses its own multiplier and is calculated independently of Band 1, allowing multiple expansion levels to be displayed simultaneously.
◇ Fill Bands
When enabled, the area between the consolidation zone and each deviation band is filled with a semi-transparent color. Upper fills apply to bands above the zone, and lower fills apply to bands below the zone. Fills are static and tied directly to the consolidation zone boundaries.
◇ Color Customization
Each deviation band has independent color controls for:
Upper band lines and fills
Lower band lines and fills
This allows users to visually distinguish between bullish and bearish extensions as well as between multiple deviation levels.
ALERTS:
Users can create alerts for the following:
New Consolidation Zone Formed
Consolidation Zone Break
UNIQUENESS:
This indicator combines multiple consolidation detection methods with lower-timeframe volume delta analysis inside each consolidation zone. It visualizes bullish and bearish volume using weighted overlap logic and optional 3D rendering for improved clarity. Users can choose how volume is displayed, apply structure-based deviation bands, and enable alerts for new zones and zone breaks. All features are rule-based, configurable, and designed to work together within a single framework. Indicator
SMC Statistical Liquidity Walls [PhenLabs]📊 SMC Statistical Liquidity Walls
Version: PineScript™ v6
📌 Description
The SMC Statistical Liquidity Walls indicator is designed to visualize market volatility and potential reversal zones using advanced statistical modeling. Unlike traditional Bollinger Bands that use simple lines, this script utilizes an “Inverted Sigmoid” opacity function to create a “fog of war” effect. This visualizes the density of liquidity: the further price moves from the equilibrium (mean), the “harder” the liquidity wall becomes.
This tool solves the problem of over-trading in low-probability areas. By automatically mapping “Premium” (Resistance) and “Discount” (Support) zones based on Standard Deviation (SD), traders can instantly see when price is overextended. The result is a clean, intuitive overlay that helps you identify high-probability mean reversion setups without cluttering your chart with manual drawings.
🚀 Points of Innovation
Inverted Sigmoid Logic: A custom mathematical function maps Standard Deviation to opacity, creating a realistic “wall” density effect rather than linear gradients.
Dynamic “Solidity”: The indicator is transparent at the center (Equilibrium) and becomes visually solid at the edges, mimicking physical resistance.
Separated Directional Bias: distinct Red (Premium) and Green (Discount) coding helps SMC traders instantly recognize expensive vs. cheap pricing.
Smart “Safe” Deviation: Includes fallback logic to handle calculation errors if deviation hits zero, ensuring the indicator never crashes during data gaps.
🔧 Core Components
Basis Calculation: Uses a Simple Moving Average (SMA) to determine the market’s equilibrium point.
Standard Deviation Zones: Calculates 1SD, 2SD, and 3SD levels to define the statistical extremes of price action.
Sigmoid Alpha Calculation: Converts the SD distance into a transparency value (0-100) to drive the visual gradient.
🔥 Key Features
Automated Premium/Discount Zones: Red zones indicate overbought (Premium) areas; Green zones indicate oversold (Discount) areas.
Customizable Density: Users can adjust the “Steepness” and “Midpoint” of the sigmoid curve to control how fast the walls become solid.
Integrated Alerts: Built-in alert conditions trigger when price hits the “Solid” wall (2SD or higher), perfect for automated trading or notifications.
Visual Clarity: The center of the chart remains clear (high transparency) to keep focus on price action where it matters most.
🎨 Visualization
Equilibrium Line: A gray line representing the mean price.
Gradient Fills: The space between bands fills with color that increases in opacity as it moves outward.
Premium Wall: Upper zones fade from transparent red to solid red.
Discount Wall: Lower zones fade from transparent green to solid green.
📖 Usage Guidelines
Range Period: Default 20. Controls the lookback period for the SMA and Standard Deviation calculation.
Source: Default Close. The price data used for calculations.
Center Transparency: Default 100 (Clear). Controls how transparent the middle of the chart is.
Edge Transparency: Default 45 (Solid). Controls the opacity of the outermost liquidity wall.
Wall Steepness: Default 2.5. Adjusts how aggressively the gradient transitions from clear to solid.
Wall Start Point: Default 1.5 SD. The deviation level where the gradient shift begins to accelerate.
✅ Best Use Cases
Mean Reversion Trading: Enter trades when price hits the solid 2SD or 3SD wall and shows rejection wicks.
Take Profit Targets: Use the Equilibrium (Gray Line) as a logical first target for reversal trades.
Trend Filtering: Do not initiate new long positions when price is deep inside the Red (Premium) wall.
⚠️ Limitations
Lagging Nature: As a statistical tool based on Moving Averages, the walls react to past price data and may lag during sudden volatility spikes.
Trending Markets: In strong parabolic trends, price can “ride” the bands for extended periods; mean reversion should be used with caution in these conditions.
💡 What Makes This Unique
Physics-Based Visualization: We treat liquidity as a physical barrier that gets denser the deeper you push, rather than just a static line on a chart.
🔬 How It Works
Step 1: The script calculates the mean (SMA) and the Standard Deviation (SD) of the source price.
Step 2: It defines three zones above and below the mean (1SD, 2SD, 3SD).
Step 3: The custom `get_inverted_sigmoid` function calculates an Alpha (transparency) value based on the SD distance.
Step 4: Plot fills are colored dynamically, creating a seamless gradient that hardens at the extremes to visualize the “Liquidity Wall.”
💡 Note
For best results, combine this indicator with Price Action confirmation (such as pin bars or engulfing candles) when price touches the solid walls. Indicator
Z-EMA Fusion BandsDesigned with crypto markets in mind, particularly Bitcoin , it builds on the concept that the 1-Week 50 EMA often serves as a long-term bull/bear market threshold — an area where institutional bias, momentum shifts, and cyclical rotations tend to occur.
🔹 Core Components & Synergies:
1. 1W 50 EMA (Higher Timeframe)
- This EMA is calculated on a weekly timeframe, regardless of your current chart.
- In crypto, price above the 1W 50 EMA typically aligns with long-term bull market phases, while extended periods below can signify bearish macro structure.
- The slope of the EMA is also analyzed to add directional confidence to trend strength.
2. ±1 Standard Deviation Bands
- Surrounding the 50 EMA, these bands visualize normal price dispersion relative to trend.
- When price consistently hugs or breaks outside these bands, it often reflects market expansion, volatility events, or mean-reversion opportunity.
3. Z-Score Gradient Fill
- The area between the bands is filled using a Z-score-based gradient, which dynamically adjusts color based on how far price is from the EMA (in terms of standard deviations).
- Color shifts from aqua (near EMA) to fuchsia (far from EMA) help you spot price compression, equilibrium, or overextension at a glance.
- The fill also uses transparency scaling, making it fade as price stretches further, emphasizing the core structure.
4. Directional EMA Coloring
- The EMA line itself is colored based on:
- The slope of the EMA (rising/falling)
- Whether the HTF candle is bullish or bearish
- This provides intuitive color-coded confirmation of momentum alignment or potential exhaustion.
5. Price/EMA Divergence Detection
- The script detects bullish and bearish divergence between price and the EMA (rather than using a traditional oscillator).
- Bullish Divergence: Price makes a lower low, EMA makes a higher low.
- Bearish Divergence: Price makes a higher high, EMA makes a lower high.
- These signals often mark transitional zones where momentum fades before a trend reversal or correction.
📊 Suggested Uses:
🔸 Swing and Position Trading:
- Use the 1W 50 EMA as a macro-trend anchor.
- Stay long-biased when price is above with positive slope, and short-biased when below.
- Consider entries near band edges for mean-reversion plays, especially if confluence forms with divergence signals.
🔸 Volatility-Based Filtering:
- Use the Z-score fill to identify volatility compression (near EMA) or expansion (edge of bands).
- Combine this with breakout strategies or dynamic position sizing.
🔸 Divergence Confirmation:
- Combine divergence markers with HTF EMA slope for high-probability setups.
- Bullish div + EMA flattening/rising can signal the start of accumulation after a macro dip.
🔸 Multi-Timeframe Analysis:
- Works well as a structural overlay on intraday charts (1H, 4H, 1D).
- Use this indicator to track long-term bias while executing lower timeframe trades.
⚠️ Disclaimer:
This indicator is designed for educational and informational purposes only. It does not constitute financial advice or a recommendation to buy or sell any asset.
Always use proper risk management, and combine with your own analysis, tools, and strategy. Performance in past market conditions does not guarantee future results. Indicator
VWAP Composites📊 VWAP Composite - Advanced Multi-Period Volume Weighted Average Price Indicator
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🎯 OVERVIEW
VWAP Composite is an advanced volume-weighted average price (VWAP) indicator that goes beyond traditional single-period VWAP calculations by offering composite multi-period analysis and unprecedented customization. This indicator solves a common problem traders face: traditional VWAP resets at arbitrary intervals (session start, day, week), but significant price action and volume accumulation often spans multiple periods. VWAP Composite allows you to anchor VWAP calculations to any timeframe—or combine multiple periods into a single composite VWAP—giving you a true representation of average price weighted by volume across the exact periods that matter to your analysis.
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⚙️ HOW IT WORKS - CALCULATION METHODOLOGY
📌 CORE VWAP CALCULATION
The indicator calculates VWAP using the standard volume-weighted formula:
• Typical Price = (High + Low + Close) / 3
• VWAP = Σ(Typical Price × Volume) / Σ(Volume)
This calculation is performed across user-defined time periods, ensuring each bar's contribution to the average is proportional to its trading volume.
📌 STANDARD DEVIATION BANDS
The indicator calculates volume-weighted standard deviation to measure price dispersion around the VWAP:
• Variance = Σ / Σ(Volume)
• Standard Deviation = √Variance
• Upper Band = VWAP + (StdDev × Multiplier)
• Lower Band = VWAP - (StdDev × Multiplier)
These bands help identify overbought/oversold conditions relative to the volume-weighted mean, with high-volume price excursions having greater impact on band width than low-volume moves.
📌 COMPOSITE PERIOD METHODOLOGY (Auto Mode)
Unlike traditional VWAP that resets at fixed intervals, Auto Mode creates composite VWAPs by combining the current period with N previous periods:
• Period Span = 1: Current period only (standard VWAP behavior)
• Period Span = 2: Current period + 1 previous period combined
• Period Span = 3: Current period + 2 previous periods combined
• And so on...
Example: A 3-period Weekly composite VWAP calculates from the start of 2 weeks ago through the current week's end, creating a single VWAP that represents 21 days of continuous price and volume data. This provides context about where price stands relative to the volume-weighted average over multiple weeks, not just the current week.
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🔧 KEY FEATURES & ORIGINALITY
✅ DUAL OPERATING MODES
1️⃣ MANUAL MODE (5 Independent VWAPs)
Define up to 5 separate VWAP calculations with custom start/end times:
• Perfect for anchoring VWAP to specific events (earnings, Fed announcements, major reversals)
• Each VWAP has independent color settings for lines and deviation band backgrounds
• Individual control over calculation extension and visual extension (explained below)
• Useful for tracking multiple institutional accumulation/distribution zones simultaneously
2️⃣ AUTO MODE (Composite Period VWAP)
Automatically calculates VWAP across combined time periods:
• Supported periods: Daily, Weekly, Monthly, Quarterly, Yearly
• Configurable period span (1-20 periods)
• Always up-to-date, recalculates on each new bar
• Ideal for systematic analysis across consistent timeframes
✅ DUAL EXTENSION SYSTEM (Manual Mode Innovation)
Most VWAP indicators only offer "on/off" for extending calculations. This indicator provides two distinct extension options:
🔹 EXTEND CALCULATION TO CURRENT BAR
When enabled, continues including new bars in the VWAP calculation after the defined end time. The VWAP value updates dynamically as new volume enters the market.
Use case: You anchored VWAP to a major low 3 weeks ago. You want the VWAP to continue evolving with new volume data to track ongoing institutional positioning.
🔹 EXTEND VISUAL LINE ONLY
When enabled (and calculation extension is disabled), projects the "frozen" VWAP value forward as a reference line. The VWAP value remains fixed at what it was at the end time, but the line and deviation bands visually extend to current price.
Use case: You want to see how price is behaving relative to the VWAP that existed at a specific point in time (e.g., "Where is price now vs. the 5-day VWAP that existed at last Friday's close?").
This dual system gives you unprecedented control over whether you're tracking a "living" VWAP that incorporates new data or using historical VWAP levels as static reference points.
✅ CUSTOMIZABLE STANDARD DEVIATION BANDS
• Adjustable multiplier (0.1 to 5.0)
• Independent background colors with opacity control for each VWAP
• Dashed band lines for easy visual distinction from main VWAP
• Bands extend when visual extension is enabled, maintaining zone visibility
✅ COMPREHENSIVE LABELING SYSTEM
Each VWAP displays:
• Current VWAP value
• Upper deviation band value (High)
• Lower deviation band value (Low)
• Extension status indicator (Calc Extended / Visual Extended)
• Color-coded for quick identification
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📖 HOW TO USE THIS INDICATOR
🎯 SCENARIO 1: EVENT-ANCHORED VWAP (Manual Mode)
Use case: A stock gaps down 15% on earnings and you want to track where institutions are positioning during the recovery.
Setup:
1. Switch to Manual Mode
2. Enable VWAP 1
3. Set Start Time to the earnings gap bar
4. Set End Time to current time (or leave far in future)
5. Enable "Extend Calculation to Current Bar"
6. Watch how price respects the VWAP as a dynamic support/resistance
Interpretation:
• Price above VWAP = buyers in control since the event
• Price testing VWAP from above = potential support
• Volume-weighted standard deviation bands show normal price range
• Price outside bands = potential exhaustion/mean reversion setup
🎯 SCENARIO 2: MULTI-WEEK INSTITUTIONAL ACCUMULATION ZONE (Auto Mode)
Use case: You trade swing setups and want to identify where institutions have been accumulating over the past 3 weeks.
Setup:
1. Switch to Auto Mode
2. Select "Weekly" period type
3. Set Period Span to 3
4. Enable standard deviation bands
Interpretation:
• 3-week composite VWAP shows the true average institutional entry
• Price bouncing off VWAP repeatedly = strong support (institutions defending their average)
• Price breaking below VWAP on high volume = potential distribution
• Deviation bands contracting = consolidation; expanding = volatility increase
🎯 SCENARIO 3: COMPARING MULTIPLE TIME HORIZONS (Manual Mode)
Use case: You want to see short-term vs medium-term vs long-term VWAP alignments.
Setup:
1. Switch to Manual Mode
2. VWAP 1: Last 5 trading days (blue)
3. VWAP 2: Last 10 trading days (orange)
4. VWAP 3: Last 20 trading days (purple)
5. Enable "Extend Calculation" for all
6. Set different background colors for visual separation
Interpretation:
• All VWAPs aligned upward = strong trend across all timeframes
• Price between VWAPs = finding equilibrium between different trader timeframes
• Short-term VWAP crossing long-term VWAP = momentum shift
• Price rejecting at higher-timeframe VWAP = that timeframe's traders defending their average
🎯 SCENARIO 4: HISTORICAL VWAP REFERENCE LEVELS (Manual Mode)
Use case: You want to see where the 1-month VWAP was at each month-end as static reference levels.
Setup:
1. Switch to Manual Mode
2. VWAP 1: Set to last month's start/end dates
3. VWAP 2: Set to 2 months ago start/end dates
4. VWAP 3: Set to 3 months ago start/end dates
5. Disable "Extend Calculation"
6. Enable "Extend Visual Line Only"
Interpretation:
• Each VWAP represents the volume-weighted average for that complete month
• These become static support/resistance levels
• Price returning to old monthly VWAPs = institutional memory/gap fill behavior
• Useful for identifying longer-term value areas
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🎨 CUSTOMIZATION OPTIONS
GENERAL SETTINGS
• Show/hide labels
• Line style: Solid, Dashed, or Dotted
• Standard deviation multiplier (impacts band width)
• Toggle standard deviation bands on/off
MANUAL MODE (Per VWAP)
• Custom start and end times
• Line color picker
• Background color picker (with transparency control)
• Extend calculation option
• Extend visual option
• Show/hide individual VWAPs
AUTO MODE
• Period type selection (Daily/Weekly/Monthly/Quarterly/Yearly)
• Period span (1-20 periods)
• Line color
• Background color (with transparency control)
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💡 TRADING APPLICATIONS
✓ Mean Reversion: Use deviation bands to identify stretched prices likely to return to VWAP
✓ Trend Confirmation: Price sustained above VWAP = bullish bias; below = bearish bias
✓ Support/Resistance: VWAP often acts as dynamic S/R, especially on higher volume periods
✓ Institutional Positioning: Multi-day/week VWAPs show where large players have established positions
✓ Entry Timing: Wait for pullbacks to VWAP in trending markets
✓ Stop Placement: Use VWAP ± standard deviation as volatility-adjusted stop levels
✓ Breakout Confirmation: Breakouts from consolidation with price reclaiming VWAP = stronger signal
✓ Multi-Timeframe Analysis: Compare short vs long-period VWAPs to gauge momentum alignment
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⚠️ IMPORTANT NOTES
• The indicator redraws on each bar to maintain accurate visual representation (uses `barstate.islast`)
• Maximum lookback is limited to 5000 bars for performance optimization
• Time range calculations work across all timeframes but are most effective on intraday to daily charts
• Standard deviation bands assume volume-weighted distribution; extreme events may violate assumptions
• Auto mode always calculates to current bar; use Manual mode for fixed historical periods
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This indicator is open-source. Feel free to examine the code, learn from it, and adapt it to your needs.
Indicator
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.
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How It Works
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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`.
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Key Features
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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.
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Usage
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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.
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Example Settings
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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.
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Notes & Limitations
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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.
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Credits
╰───────╯
Based on the Relative Volatility Index concept by Donald Dorsey (1993).
PulseWire
SciQua - Joshua Danford
Indicator
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.
Indicator
Spent Output Profit Ratio (SOPR) Z-Score | [DeV]SOPR Z-Score
The Spent Output Profit Ratio (SOPR) is an advanced on-chain metric designed to provide deep insights into Bitcoin market dynamics by measuring the ratio between the combined USD value of all Bitcoin outputs spent on a given day and their combined USD value at the time of creation (typically, their purchase price). As a member of the Realized Profit/Loss family of metrics, SOPR offers a window into aggregate seller behavior, effectively representing the USD amount received by sellers divided by the USD amount they originally paid. This indicator enhances this metric by normalizing it into a Z-Score, enabling a statistically robust analysis of market sentiment relative to historical trends, augmented by a suite of customizable features for precision and visualization.
SOPR Settings -
Lookback Length (Default: 150 days): Determines the historical window for calculating the Z-Score’s mean and standard deviation. A longer lookback captures broader market cycles, providing a stable baseline for identifying extreme deviations, which is particularly valuable for long-term strategic analysis.
Smoothing Period (Default: 100 days): Applies an EMA to the raw SOPR, balancing responsiveness to recent changes with noise reduction. This extended smoothing period ensures the indicator focuses on sustained shifts in seller behavior, ideal for institutional-grade trend analysis.
Moving Average Settings -
MA Lookback Length (Default: 90 days): Sets the period for the Z-Score’s moving average, offering a shorter-term trend signal relative to the 150-day Z-Score lookback. This contrast enhances the ability to detect momentum shifts within the broader context.
MA Type (Default: EMA): Provides six moving average types, from the simple SMA to the volume-weighted VWMA. The default EMA strikes an optimal balance between smoothness and responsiveness, while alternatives like HMA (Hull) or VWMA (volume-weighted) allow for specialized applications, such as emphasizing recent price action or incorporating volume dynamics.
Display Settings -
Show Moving Average (Default: True): Toggles the visibility of the Z-Score MA plot, enabling users to focus solely on the raw Z-Score when preferred.
Show Background Colors (Default: True): Activates dynamic background shading, enhancing visual interpretation of market regimes.
Background Color Source (Default: SOPR): Allows users to tie the background color to either the SOPR Z-Score’s midline (reflecting adjustedZScore > 0) or the MA’s trend direction (zScoreMA > zScoreMA ). This dual-source option provides flexibility to align the visual context with the primary analytical focus.
Analytical Applications -
Bear Market Resistance: When the Z-Score approaches or exceeds zero (raw SOPR near 1), it often signals resistance as sellers rush to exit at break-even, a pattern historically observed during downtrends. A rising Z-Score MA crossing zero can confirm this pressure.
Bull Market Support: Conversely, a Z-Score dropping below zero in uptrends indicates reluctance to sell at a loss, forming support as sell pressure diminishes. The MA’s bullish coloring reinforces confirmation of renewed buying interest.
Extreme Deviations: Values significantly above or below zero highlight overbought or oversold conditions, respectively, offering opportunities for contrarian positioning when paired with other on-chain or price-based metrics.
Indicator
Standard Deviation (fadi)The Standard Deviation indicator uses standard deviation to map out price movements. Standard deviation measures how much prices stray from their average—small values mean steady trends, large ones mean wild swings. Drawing from up to 20 years of data, it plots key levels using customizable Fibonacci lines tied to that standard deviation, giving traders a snapshot of typical price behavior.
These levels align with a bell curve: about 68% of price moves stay within 1 standard deviation, 95% within roughly 2, and 99.7% within roughly 3. When prices break past the 1 StDev line, they’re outliers—only 32% of moves go that far. Prices often snap back to these lines or the average, though the reversal might not happen the same day.
How Traders Use It
If prices surge past the 1 StDev line, traders might wait for momentum to fade, then trade the pullback to that line or the average, setting a target and stop.
If prices dip below, they might buy, anticipating a bounce—sometimes a day or two later. It’s a tool to spot overstretched prices likely to revert and/or measure the odds of continuation.
Settings
Higher Timeframe: Sets the Higher Timeframe to calculate the Standard Deviation for
Show Levels for the Last X Days: Displays levels for the specified number of days.
Based on X Period: Number of days to calculate standard deviation (e.g., 20 years ≈ 5,040 days). Larger periods smooth out daily level changes.
Mirror Levels on the Other Side: Plots symmetric positive and negative levels around the average.
Fibonacci Levels Settings: Defines which levels and line styles to show. With mirroring, negative values aren’t needed.
Background Transparency: Turn on Background color derived from the level colors with the specified transparency
Overrides: Lets advanced users input custom standard deviations for specific tickers (e.g., NQ1! at 0.01296).
Indicator
Daily Standard Deviation (fadi)The Daily Standard Deviation indicator uses standard deviation to map out daily price movements. Standard deviation measures how much prices stray from their average—small values mean steady trends, large ones mean wild swings. Drawing from up to 20 years of data, it plots key levels using customizable Fibonacci lines tied to that standard deviation, giving traders a snapshot of typical price behavior.
These levels align with a bell curve: about 68% of price moves stay within 1 standard deviation, 95% within roughly 2, and 99.7% within roughly 3. When prices break past the 1 StDev line, they’re outliers—only 32% of moves go that far. Prices often snap back to these lines or the average, though the reversal might not happen the same day.
How Traders Use It
If prices surge past the 1 StDev line, traders might wait for momentum to fade, then trade the pullback to that line or the average, setting a target and stop.
If prices dip below, they might buy, anticipating a bounce—sometimes a day or two later. It’s a tool to spot overstretched prices likely to revert and/or measure the odds of continuation.
Settings
Open Hour: Sets the trading day’s start (default: 18:00 EST).
Show Levels for the Last X Days: Displays levels for the specified number of days.
Based on X Period: Number of days to calculate standard deviation (e.g., 20 years ≈ 5,040 days). Larger periods smooth out daily level changes.
Mirror Levels on the Other Side: Plots symmetric positive and negative levels around the average.
Fibonacci Levels Settings: Defines which levels and line styles to show. With mirroring, negative values aren’t needed.
Overrides: Lets advanced users input custom standard deviations for specific tickers (e.g., NQ1! at 0.01296). Indicator
Midnight Opening Ranges[TDL]Midnight Opening Range Indicator for PulseWire
Description:
The Midnight Opening Range Indicator as taught by Micheal J. Huddleston is a powerful tool designed for traders who want to analyze price action during the critical midnight to 00:30 timeframe. This indicator highlights the opening range for both the current day and previous days, providing valuable insights into market behavior during this specific period. It also calculates and displays deviations from the opening range, as well as allows for custom opening prices to be set, making it highly adaptable to your trading strategy.
Key Features:
Today's Opening Range (00:00 - 00:30):
The indicator plots the high and low of the price range between 00:00 and 00:30 for the current day.
This range is highlighted on the chart, making it easy to identify the initial market movement and potential support/resistance levels.
Previous Days' Opening Ranges:
The indicator also displays the opening ranges for previous days, allowing you to how price reacts off of previous days ranges not just todays.
This feature helps in identifying patterns or recurring behaviors in the market in which price uses this range and previous days ranges throughout the trading day.
Deviations from the Opening Range:
The indicator calculates and plots deviations from the opening range, both above and below the high and low of the range.
These deviations can be used to identify potential breakout or reversal points, giving you an edge in anticipating market moves.
Custom Opening Prices:
The indicator allows you to set custom opening prices, which can be useful if you want to analyze the market based on a specific reference point rather than the default midnight opening.
This feature is particularly useful for traders who follow alternative trading sessions or have specific entry criteria.
Customizable Visuals:
The indicator offers customizable colors and styles for the opening range, deviations, and custom opening prices, allowing you to tailor the visual representation to your preferences.
How to Use:
Identify Key Levels: Use the highlighted opening range to identify key support and resistance levels for the day.
Monitor Deviations: Watch for price movements beyond the opening range deviations to spot potential breakouts or reversals.
Previous Range Data: Use previous days to identify areas of potential AMD.
Set Custom Prices: Adjust the custom opening price to align with your trading strategy or session preferences.
Ideal For:
Day Traders: Perfect for traders who focus on the early hours of the market to capture initial momentum.
Swing Traders: Useful for identifying key levels that could influence price action over several days.
Algorithmic Traders: Can be integrated into automated trading systems to trigger trades based on the opening range and deviations.
Conclusion:
The Midnight Opening Range Indicator is an essential tool for any trader looking to gain an edge in the market by focusing on the critical midnight to 00:30 timeframe. With its ability to highlight opening ranges, calculate deviations, and accommodate custom opening prices, this indicator provides a comprehensive view of market behavior during this pivotal period. Whether you're a day trader, swing trader, or algorithmic trader, this indicator will help you make more informed trading decisions. Indicator
Correlation Coefficient Master TableThe Correlation Coefficient Master Table is a comprehensive tool designed to calculate and visualize the correlation coefficient between a selected base asset and multiple other assets over various time periods. It provides traders and analysts with a clear understanding of the relationships between assets, enabling them to analyze trends, diversification opportunities, and market dynamics. You can define key parameters such as the base asset’s data source (e.g., close price), the assets to compare against (up to six symbols), and multiple lookback periods for granular analysis.
The indicator calculates the covariance and normalizes it by the product of the standard deviations. The correlation coefficient ranges from -1 to +1, with +1 indicating a perfect positive relationship, -1 a perfect negative relationship, and 0 no relationship.
You can specify the lookback periods (e.g., 15, 30, 90, or 120 bars) to tailor the calculation to their analysis needs. The results are visualized as both a line plot and a table. The line plot shows the correlation over the primary lookback period (the Chart Length), which can be used to inspect a certain length close up, or could be used in conjunction with the table to provide you with five lookback periods at once for the same base asset. The dynamically created table provides a detailed breakdown of correlation values for up to six target assets across the four user-defined lengths. The table’s cells are formatted with rounded values and color-coded for easy interpretation.
This indicator is ideal for traders, portfolio managers, and market researchers who need an in-depth understanding of asset interdependencies. By providing both the numerical correlation coefficients and their visual representation, users can easily identify patterns, assess diversification strategies, and monitor correlations across multiple timeframes, making it a valuable tool for decision-making.
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Indicator
Truly Iterative Gaussian ChannelOVERVIEW
The Truly Iterative Gaussian Channel is a robust channeling system that integrates a Gaussian smoothing kernel with a rolling standard deviation to create dynamically adaptive upper and lower boundaries around price. This indicator provides a smooth, yet responsive representation of price movements while minimizing lag and dynamically adjusting channel width to reflect real-time market volatility. Its versatility makes it effective across various timeframes and trading styles, offering significant potential for experimentation and integration into advanced trading systems.
TRADING USES
The Gaussian indicator can be used for multiple trading strategies. Trend following relies on the middle Gaussian line to gauge trend direction: prices above this line indicate bullish momentum, while prices below signal bearish momentum. The upper and lower boundaries act as dynamic support and resistance levels, offering breakout or pullback entry opportunities. Mean reversion focuses on identifying reversal setups when price approaches or breaches the outer boundaries, aiming for a return to the Gaussian centerline. Volatility filtering helps assess market conditions, with narrow channels indicating low volatility or consolidation and suggesting fewer trading opportunities or an impending breakout. Adaptive risk management uses channel width to adjust for market volatility, with wider channels signaling higher risk and tighter channels indicating lower volatility and potentially safer entry points.
THEORY
Gaussian kernel smoothing, derived from the Gaussian normal distribution, is a cornerstone of probability and statistics, valued for its ability to reduce noise while preserving critical signal features. In this indicator, it ensures price movements are smoothed with precision, minimizing distortion while maintaining responsiveness to market dynamics.
The rolling standard deviation complements this by dynamically measuring price dispersion from the mean, enabling the channel to adapt in real time to changing market conditions. This combination leverages the mathematical correctness of both tools to balance smoothness and adaptability.
An iterative framework processes data efficiently, bar by bar, without recalculating historical value to ensure reliability and preventing repainting to create a mathematically grounded channel system suitable for a wide range of market environments.
The Gaussian channel excels at filtering noise while remaining responsive to price action, providing traders with a dependable tool for identifying trends, reversals, and volatility shifts with consistency and precision.
CALIBRATION
Calibration of the Gaussian channel involves adjusting its length to modify sensitivity and adaptability based on trading style. Shorter lengths (e.g., 50-100) are ideal for intraday traders seeking quick responses to price fluctuations. Medium lengths (e.g., 150-200) cater to swing traders aiming to capture broader market trends. Longer lengths (e.g., 250-400+) are better suited for positional traders focusing on long-term price movements and stability.
MARKET USAGE
Stock, Forex, Crypto, Commodities, and Indices. Indicator
Indicator
Dema Percentile Standard DeviationDema Percentile Standard Deviation
The Dema Percentile Standard Deviation indicator is a robust tool designed to identify and follow trends in financial markets.
How it works?
This code is straightforward and simple:
The price is smoothed using a DEMA (Double Exponential Moving Average).
Percentiles are then calculated on that DEMA.
When the closing price is below the lower percentile, it signals a potential short.
When the closing price is above the upper percentile and the Standard Deviation of the lower percentile, it signals a potential long.
Settings
Dema/Percentile/SD/EMA Length's: Defines the period over which calculations are made.
Dema Source: The source of the price data used in calculations.
Percentiles: Selects the type of percentile used in calculations (options include 60/40, 60/45, 55/40, 55/45). In these settings, 60 and 55 determine percentile for long signals, while 45 and 40 determine percentile for short signals.
Features
Fully Customizable
Fully Customizable: Customize colors to display for long/short signals.
Display Options: Choose to show long/short signals as a background color, as a line on price action, or as trend momentum in a separate window.
EMA for Confluence: An EMA can be used for early entries/exits for added signal confirmation, but it may introduce noise—use with caution!
Built-in Alerts.
Indicator on Diffrent Assets
INDEX:BTCUSD 1D Chart (6 high 56 27 60/45 14)
CRYPTO:SOLUSD 1D Chart (24 open 31 20 60/40 14)
CRYPTO:RUNEUSD 1D Chart (10 close 56 14 60/40 14)
Remember no indicator would on all assets with default setting so FAFO with setting to get your desired signal.
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