Indicateur
Volatility Reversion Bands Pro [JOAT]VOLATILITY REVERSION BANDS PRO
A two-layer reversion envelope: inner Bollinger band for the normal volatility envelope, outer ATR-extended band for the extreme envelope. Signals only fire when price has reached the outer ring — the inner band is context, the outer band is the trigger. The result is a clean mean-reversion engine that respects the difference between "stretched" and "actually stretched".
Two envelopes, one principle
Inner band — classic Bollinger: basis (SMA or EMA) ± stdev × multiplier. The familiar 20-period, 2-sigma defaults are preserved.
Outer reversion band — the outer envelope extends inner band ± ATR × multiplier . This is the band that triggers signals. Setting the ATR multiplier high makes signals rarer but deeper; setting it low makes them frequent and shallower.
Reversion bands using stdev alone collapse in low-volatility regimes (too many false signals) and explode in high-volatility regimes (signals come too late). The ATR extension on top of stdev fixes both: ATR adds a constant-floor protection in quiet markets and scales the outer band proportionally in loud ones.
Strong vs weak signals
Two signal tiers from a single channel-ratio read (close position within the outer band, normalised 0–1):
Strong signals — fire on the outer band itself (ratio ≤ 0 or ≥ 1). The high-conviction reversion read.
Weak signals — fire when ratio reaches a configurable near-band threshold (default 0.10 / 0.90). The "approaching outer band" read — useful for traders who want earlier hints. Easily disabled.
A signal cooldown suppresses same-side repetition; an exhaustion arrow prints when N consecutive bars (default 3) all live in the outer-band zone — a configurable escalating-glyph string ("^", "^^", "^^^"…) makes the run length visible at a glance.
Volatility regime classification
Independent of signals, the script classifies the current volatility regime by comparing current stdev to its own rolling average over a long lookback (default 100 bars):
Low regime — stdev / avgStdev below the low threshold (default 1.0×). Reversion is more reliable here.
High regime — above the high threshold (default 2.0×). Reversion is less reliable here; trends become dominant.
Normal regime — in between. Default mode.
Background tinting (toggleable, transparency-controlled) paints the chart by regime so the trader can see at a glance whether the current environment is suitable for reversion. This is the "do not fight the tape" filter — when the background is hot, every reversion signal is lower-conviction by definition.
Visual system
Bar gradient — bars are coloured by their position-in-band ratio (bull → mid → bear via plasma palette). At a glance you can see where price is sitting in the channel without reading the value.
Inner band fill — toggleable shoulder fill between BB and outer reversal bands with configurable transparency.
Inner BB lines and basis line are each independently toggleable for traders who want a minimalist or full envelope view.
Signal label style — Glyph (compact), Text (verbose), or Both.
A locked Plasma palette (yellow bull, magenta bear, violet mid) on a deep-void background gives the chart a distinctive look without competing with price action.
Dashboard
Monospaced table, positionable to any of nine corners, with togglable legend footer. Rows surface current basis, inner band values, outer reversion band values, channel ratio %, stdev / avgStdev ratio, regime label, last signal direction with age, and an exhaustion run counter.
Alerts
Four alert conditions, each independently controllable:
Strong Long / Short (outer band touch reversion)
Weak Long / Short (near-band threshold)
Vol Regime Change
Exhaustion Arrow (consecutive bars in outer-band zone)
How to read it
Two reads, in order of conviction:
Strong signal in a Low or Normal regime — the script's intended sweet spot. The outer band has been touched, price is statistically far from its mean, and the volatility environment supports the idea of mean-reversion.
Exhaustion arrow — when 3+ bars sit in the outer band, you usually have either a genuine breakout (the bands themselves will start to expand) or an exhaustion (the next reversal candle will be the signal). Either way, the next move is meaningful.
In a High regime, treat strong signals as cautionary at best — the bars are coloured by ratio for a reason; the gradient will tell you when one side is dominating.
Suggested settings
Defaults (length 20, stdev mult 2.0, ATR mult 1.5) are tuned to 1H–4H on liquid markets — the classical Bollinger settings plus a 1.5-ATR outer cushion. For 5m–15m, drop length to 14 and ATR multiplier to 1.0. For daily and above, raise length to 50 and ATR multiplier to 2.0. The regime thresholds (low 1.0×, high 2.0× of the long-run stdev average) are conservative — tighten the bands if your instrument is unusually quiet.
Originality / what's reused
Bollinger Bands and ATR are public-domain primitives. The implementation — the outer-band = inner-band ± ATR construction, the channel-ratio bar gradient, the regime classifier with auto-tinted background, the exhaustion-arrow consecutive-bar run logic, the weak/strong signal tiering, and the dashboard's monospaced regime-aware layout — is JOAT-original and tuned together. No third-party code reused.
Open source
Published open-source under the default Mozilla Public License 2.0. Section-headed source, tooltips on every input, helper functions documented inline. The band engine, the regime classifier, the exhaustion logic, and the dashboard are independent modules — fork or extend any single one without reading the whole file.
Limitations
Reversion bands are a counter-trend tool by construction. In sustained one-sided moves the outer band will be repeatedly touched without producing a profitable reversion — the High regime tint and the exhaustion-arrow run logic both exist to warn you when you are in this state. Signals are confirmed on bar close (non-repainting), so an intra-bar wick into the outer band that gets reabsorbed will not fire.
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-made with passion by jackofalltrades
Indicateur
Indicateur
Velox Structure Ribbon [JOAT]Velox Structure Ribbon
Introduction
Velox Structure Ribbon (VSR) is an open-source multi-band trend structure ribbon that uses a volatility-normalized, dynamically-spaced band system to visualize how far price has extended from its trend baseline and in which direction. The ribbon is anchored by a dual SMEMA core — a fast and slow double-smoothed moving average — and radiates six equidistant bands above and below the baseline, with spacing determined by the smoothed average candle range. Each band that price has penetrated adds one point to a 0-3 bull or bear structure score. A 0-100 composite trend strength score combines band penetration with RSI momentum. Volume confirmation and RSI filters are available to sharpen signal quality.
The problem VSR solves is that standard envelopes and Bollinger Bands use fixed or volatility-scaled offsets that can cluster bands too tightly in low-volatility environments and spread them too far in high-volatility ones. VSR normalizes band spacing using the market's own smoothed candle range, meaning band width automatically contracts in quiet markets and expands in active ones. This keeps the structure score meaningful across all conditions: three bands penetrated in a quiet market represents the same degree of extension relative to current volatility as three bands penetrated in a volatile market.
Core Concepts
1. SMEMA Ribbon Core
The ribbon center uses two SMEMA lines — slow (full period, default 20) and fast (half period). The slow SMEMA defines trend direction: sloping upward means the trend is bullish, downward means bearish. The fill between fast and slow creates a visual ribbon that contracts during consolidation and expands during trends:
float smemaSlow = smema(close, smemaLen)
float smemaFast = smema(close, math.max(int(smemaLen / 2), 3))
bool trendUp = smemaSlow > smemaSlow
bool trendDn = smemaSlow < smemaSlow
2. Volatility-Normalized Band Spacing
The step unit for band placement is SMEMA applied to the high-low range over a long smoothing period (default 100 bars). This produces an adaptive measure of the average candle body size. Each of the six bands is placed at integer multiples of this step above and below the slow SMEMA:
float step = smema(high - low, stepSmooth)
float up1 = smemaSlow + step * 1
float up2 = smemaSlow + step * 2
float up3 = smemaSlow + step * 3
Because the step automatically adjusts to market volatility, the bands always represent meaningful structural extensions rather than arbitrary percentage offsets.
3. Bull and Bear Structure Scoring
Each bar, the indicator counts how many upper bands price has broken through (bullish penetration) and how many lower bands (bearish penetration). Each penetrated band adds one point to the respective score:
int bullStr = (above1 ? 1 : 0) + (above2 ? 1 : 0) + (above3 ? 1 : 0)
int bearStr = (below1 ? 1 : 0) + (below2 ? 1 : 0) + (below3 ? 1 : 0)
A score of 0 means price is between the baseline and first band — neutral zone. Score of 1 means first structural extension. Score of 3 means full breakout beyond all three bands in that direction.
4. Composite Trend Strength Score (0-100)
The strength score combines two inputs: the band penetration score converted to a 0-50 scale (each band = 16.7 points) and the RSI deviation from 50 on a 0-50 scale. The combination rewards moves that have both structural extension (price has pushed through multiple bands) and momentum confirmation (RSI is moving away from neutral):
float bandScore = math.min(float(math.max(bullStr, bearStr)) * 16.7, 50.0)
float rsiScore = math.min(math.abs(rsiVal - 50.0), 50.0)
int strScore = int(math.min(bandScore + rsiScore, 100.0))
5. Distance-Based Band Coloring
Each band receives a gradient color whose intensity scales with how far price is from that band relative to its historical range. Bands that price has recently broken through or is pressing against are rendered more vividly. Bands far from price are nearly transparent. This creates a visual heat-map effect showing where structural tension exists:
bandColor(float src, color col) =>
float dist = math.abs(close - src)
float pctNorm = ta.percentile_linear_interpolation(dist, 400, 100)
float colSize = pctNorm > 0 ? dist / pctNorm : 0.0
showBands ? color.from_gradient(colSize, 0, 0.5, color(na), col) : color(na)
Features
Six-Band Structure Grid: Three bands above and three below the slow SMEMA baseline, dynamically spaced by the smoothed candle range
Dual SMEMA Core Ribbon: Fast and slow baseline with gradient fill, colored by trend direction
Trend Direction Diamond: A small diamond marker on the baseline at every trend flip (when the slow SMEMA changes slope direction)
Bull / Bear Structure Score (0-3): Real-time count of penetrated upper or lower bands displayed in signal labels and the dashboard
Composite Strength Score (0-100): Combined band penetration and RSI momentum score with Strong/Moderate/Weak label
RSI Momentum Filter: Optional filter requiring RSI alignment before a signal is confirmed (configurable threshold, default 52)
Volume Filter: Optional filter requiring above-average volume (configurable multiplier, default 1.1x the 20-bar SMA). Auto-disables on volume-free instruments
Signal Labels: Small numeric labels at bull and bear signal bars showing the structure score (1, 2, or 3)
Strength Bar (Bottom Right): A visual bar table showing filled cells proportional to the current bull or bear structure score
Candle Coloring: Bar colors reflect trend direction at reduced opacity
9-Row Dashboard (Top Right): Trend direction, last signal and bars-since count, strength score with label, bull and bear band counts, RSI value, timeframe, and version
Watermark: JackOfAllTrades signature at chart center-bottom
Alerts: Bull signal, bear signal, and trend-flip alertconditions with optional JSON webhook format
Input Parameters
Ribbon Engine:
SMEMA Length: Core period for the slow baseline (default: 20). Fast = L/2
Step Smoothing: SMA period for the candle-range volatility step (default: 100)
Filters:
RSI Length: Momentum confirmation period (default: 14)
RSI Threshold: Minimum RSI for bull signal confirmation (default: 52). Bear mirror = 100 - threshold
Volume Filter: Enable/disable volume confirmation (default: off)
Volume Multiplier: Required volume multiple of the 20-bar SMA (default: 1.1)
Visuals / Dashboard:
Theme: Auto, Dark, or Light
Show Distance Bands: Toggle the six structural bands
Show Core Ribbon: Toggle the fast/slow SMEMA ribbon and fill
Show Signals: Toggle the numeric signal labels
Show Strength Bar: Toggle the bottom-right score visualization
Show Dashboard: Toggle the 9-row information panel
Color Palette: Bull, Bear, and Neutral colors are individually customizable
How to Use This Indicator
Step 1: Read Trend Direction from the Ribbon
When the ribbon is green and sloping upward, the baseline trend is bullish. When red and sloping downward, bearish. A flat ribbon in neutral color indicates a non-trending market.
Step 2: Use Structure Score for Entry Timing
A bull signal fires when price is above the first upper band (score 1+) and the trend slope is upward with RSI and volume confirmation. A score of 2 or 3 indicates deeper structural extension — potentially overextended for entry, better for trailing a position.
Step 3: Watch for Pullbacks to the Ribbon
After a bull signal, price often pulls back toward the ribbon (slow SMEMA) before continuing. Entries from the ribbon during an active bull structure are higher-probability than chasing at the outer bands.
Step 4: Scale Position with Strength Score
A strength score above 70 (labeled Strong) indicates both structural extension and momentum alignment — use for higher conviction. Below 40 (Weak) may indicate a fading move or early-stage structure not worth full position sizing.
Indicator Limitations
The warmup period (SMEMA length x3 or step smoothing + 50, whichever is larger) means the indicator is inactive for the first several dozen bars on any chart
The band spacing adapts to the smoothed candle range with a 100-bar lookback. On instruments with sharp volatility regime changes, the bands may lag behind the new volatility environment for many bars
The volume filter is automatically disabled when volume data is unavailable (e.g., indices, some forex pairs). In those cases, volume confirmation is effectively always true regardless of the toggle setting
Signal labels fire on every bull or bear structure bar — this can be frequent in strongly trending markets. The labels are informational, not entry triggers, and users should apply their own discretion for entry timing
Originality Statement
VSR is original in its use of the SMEMA-smoothed candle range as the band spacing unit. This indicator is published because:
The volatility-normalized step unit (SMEMA of high-low range) is a unique approach to band spacing that differs from standard ATR envelopes, Bollinger Bands (which use standard deviation), and Keltner Channels (which use raw ATR). The SMEMA smoothing produces a more stable, noise-resistant step unit than raw ATR
The 0-3 integer band-penetration scoring is a discrete structural measure that complements continuous oscillators. It quantifies how far price has extended structurally rather than how fast it has moved
The distance-based gradient coloring using percentile normalization creates an adaptive visual heat-map — the same visual logic is computationally novel within the band-coloring approach
The composite strength score combining band penetration with RSI deviation creates a measure that rewards both structural extension and momentum alignment simultaneously
Disclaimer
This indicator is provided for educational and informational purposes only. It is not financial advice or a recommendation to buy or sell any financial instrument. Trading involves substantial risk of loss. Band structure scores are based on historical price position relative to smoothed averages and do not predict future price movement. A score of 3 (maximum bullish extension) can increase further or reverse immediately. Always use proper risk management. The author is not responsible for any trading losses resulting from the use of this indicator.
-Made with passion by jackofalltrades
Indicateur
Meridian Scaffold [JOAT]Meridian Scaffold
Introduction
Meridian Scaffold is an advanced open-source volatility band structure that builds adaptive price envelopes around a Jurik Moving Average (JMA) baseline with integrated range-lock dampening. Unlike standard Bollinger Bands or Keltner Channels that use fixed statistical measures, this indicator constructs its bands using ATR-Fibonacci expansion levels with auto-calibrating width, overlays a ZEMA trend bias system, and includes a full volatility regime classification engine with hysteresis state transitions. The result is a band structure that adapts its behavior to the current market phase — compressing tightly during consolidation, expanding proportionally during trends, and providing clearly defined reaction levels at Fibonacci-derived distances from the adaptive baseline.
This indicator addresses a core problem with conventional band indicators: they treat all market conditions the same. A Bollinger Band expands and contracts based on standard deviation alone, with no awareness of whether the market is trending, compressing, or in a whipsaw phase. Meridian Scaffold solves this by fusing a volatility regime classifier (compression, normal, expansion) with adaptive band construction, so the bands behave differently depending on the detected market phase. During compression, the baseline locks to a simple average to prevent false signals. During expansion, the bands widen using Fibonacci ratios to project realistic target levels.
Core Concepts
1. JMA Adaptive Baseline with Range-Lock Dampening
The centerline of the band structure is a Jurik Moving Average — an adaptive filter that tracks price closely during fast moves and smooths aggressively during noise. The JMA implementation includes a full volatility tracking system that measures the relative volatility of the input signal:
// Relative volatility determines JMA responsiveness
float rv = math.min(math.max(avgVolty > 0 ? volty / avgVolty : 1.0, 1.0), maxPow)
float adaptiveAlpha = math.pow(beta, math.pow(rv, pow1))
When relative volatility drops below a configurable threshold (the "range lock" condition), the indicator switches from the JMA to a simple moving average. This prevents the baseline from oscillating during low-volatility chop, producing a flat, stable reference line that clearly communicates "no trend present." When volatility returns, the JMA resumes tracking.
2. ATR-Fibonacci Expansion Levels
Rather than using standard deviation (which assumes normal distribution) or fixed ATR multiples, the bands are constructed at Fibonacci-derived distances from the baseline. The ATR is first smoothed using a ZEMA technique (double-EMA extrapolation) to remove noise from the volatility measure itself:
float atrZ1 = ta.ema(atrRaw, 21)
float atrZ2 = ta.ema(atrZ1, 21)
float atrSmooth = atrZ1 + (atrZ1 - atrZ2)
This ZEMA-smoothed ATR is then multiplied by configurable inner and outer factors to create the band levels. The default inner band at 1.5x ATR captures normal price oscillation; the outer band at 2.8x ATR marks extended moves. Additional Fibonacci extension levels at 1.618x and 2.618x ATR provide projection targets for breakout moves.
3. Volatility Regime Classification
The indicator classifies the current volatility environment into three states using a hysteresis state machine:
Compression: ATR is significantly below its long-term average (ratio < 0.6). Bands contract, baseline locks. This phase often precedes breakouts
Normal: ATR is near its average. Standard band behavior applies
Expansion: ATR is significantly above its long-term average (ratio > 1.5). Bands widen, momentum signals are prioritized
The hysteresis mechanism prevents rapid switching between states. Entry into expansion requires a ratio above 1.5, but exit only occurs when the ratio drops below 1.2. This creates stable regime classifications that don't flicker on every bar.
4. ZEMA Trend Bias
A Zero-Lag EMA calculated on the baseline provides directional bias. When the baseline is above its ZEMA, the bias is bullish; below, bearish. The spread between the baseline and ZEMA quantifies the strength of the directional conviction. This bias colors the baseline and bands to provide immediate visual feedback on trend direction.
5. Band Squeeze Detection
The indicator monitors bandwidth (the percentage distance between outer bands relative to the baseline) against its own rolling average and standard deviation. When bandwidth drops below the average minus half a standard deviation, a squeeze condition is flagged. Squeezes represent compressed volatility that statistically tends to resolve with an expansion move.
Features
Slope-Aware Baseline Glow: The baseline renders with a multi-layer glow effect whose intensity scales with the normalized slope. Steeper trends produce more vivid glow; flat periods produce subtle, muted rendering
Regime-Adaptive Band Coloring: Band colors shift automatically based on the volatility regime — compression phases use iris/purple tones, expansion phases use ember/warm tones, and normal phases use neutral slate
Kaufman Efficiency Scoring: The Kaufman Efficiency Ratio (net price movement divided by total path length) is calculated and displayed, providing a 0-1 measure of how efficiently price is moving. Values above 0.4 indicate strong directional movement; below 0.2 indicates chop
Mean Reversion Signals: When price touches or exceeds the outer band and then re-enters the inner band, the indicator generates a mean-reversion signal. These are most reliable during normal and compression regimes
Breakout Signals: When price closes beyond the outer band during an expansion regime with volume confirmation, a breakout signal is generated. These indicate potential trend continuation
Trend Strength Composite: A composite score combining slope strength, Kaufman efficiency, R-squared linearity, and regime alignment provides a single 0-100 measure of overall trend quality
16-Row Dashboard: Displays baseline value, regime state, trend bias, bandwidth, squeeze status, Kaufman ER, slope strength, R-squared, trend composite score, band levels, regime duration, and position relative to bands
Input Parameters
Baseline:
JMA Period: Adaptive baseline smoothing length (default: 21)
JMA Phase: Lead/lag adjustment (default: 0)
JMA Power: Responsiveness curve (default: 0.45)
Range Lock Threshold: Relative volatility below which the baseline locks flat (default: 0.55)
Bands:
ATR Length: Period for ATR calculation (default: 14)
Inner Band Multiplier: ATR multiple for inner band (default: 1.5)
Outer Band Multiplier: ATR multiple for outer band (default: 2.8)
Regime:
Regime Lookback: Period for volatility regime classification (default: 50)
Visuals:
Toggles for bands, Fibonacci extensions, glow effects, squeeze markers, regime background, bar coloring, and dashboard
Zone opacity control for band fill transparency
How to Use This Indicator
Step 1: Identify the Volatility Regime
Check the dashboard or observe the band coloring. Compression (purple/iris bands) means prepare for a breakout — avoid trend-following entries. Expansion (warm/ember bands) means trend-following setups are favored. Normal (slate bands) means standard analysis applies.
Step 2: Read the Baseline Bias
The baseline color and ZEMA relationship tell you the directional bias. Only look for long setups when the baseline is above ZEMA (bullish bias) and short setups when below (bearish bias).
Step 3: Use Bands as Context Levels
The inner band defines the normal oscillation range. Price consistently above the inner upper band indicates strong bullish momentum. The outer band marks extended territory where mean-reversion risk increases. Fibonacci extensions at 1.618x and 2.618x provide projection targets for breakout moves.
Step 4: Trade Squeezes
When a squeeze is detected (gold dots on the baseline), wait for the squeeze to release. The direction of the first strong move out of the squeeze often sets the trend for the next phase. Combine with the ZEMA bias for directional confirmation.
Step 5: Monitor Trend Quality
The trend strength composite score tells you how clean the current trend is. Scores above 60 indicate high-quality trends worth riding. Scores below 30 suggest choppy conditions where band-based mean-reversion strategies may work better.
Indicator Limitations
The JMA baseline, while adaptive, still lags price during sharp reversals. The range-lock feature helps during consolidation but cannot eliminate lag during genuine trend changes
ATR-based bands assume volatility is relatively stable over the measurement period. During news events or gap openings, the bands may not accurately reflect the new volatility environment for several bars
The volatility regime classifier uses hysteresis which creates stability but also delays regime transitions. A compression-to-expansion shift may be identified several bars after the breakout begins
Fibonacci extension levels are mathematical projections, not guaranteed targets. Price may reverse before reaching them or blow through them entirely
Squeeze detection identifies compressed volatility but does not predict the direction of the subsequent expansion. Additional directional analysis is required
The indicator works best on liquid instruments with consistent volatility patterns. Thinly traded instruments may produce unreliable regime classifications
Originality Statement
This indicator is original in its integration of adaptive baseline technology with regime-aware band construction. While ATR bands and JMA are established concepts, this indicator is justified because:
The JMA range-lock mechanism that switches to SMA during low-volatility periods is a novel approach to preventing false baseline oscillations in chop — standard JMA implementations do not include this feature
ZEMA-smoothed ATR for band construction removes noise from the volatility measure itself, producing cleaner band edges than raw ATR
The three-state volatility regime classifier with hysteresis transitions provides context-aware band behavior not available in standard Bollinger or Keltner implementations
Fibonacci-derived expansion levels integrate harmonic ratio theory with volatility measurement, providing mathematically grounded projection targets
The trend strength composite score synthesizes multiple independent quality measures (slope, efficiency, linearity, regime) into a single actionable metric
Slope-aware glow rendering and regime-adaptive coloring provide instant visual feedback on market conditions without requiring dashboard reading
Disclaimer
This indicator is provided for educational and informational purposes only. It is not financial advice or a recommendation to buy or sell any financial instrument. Trading involves substantial risk of loss. Band levels, regime classifications, and signals are mathematical calculations based on historical data and do not predict future price movement. Squeeze conditions do not guarantee subsequent breakouts, and breakout signals do not guarantee trend continuation. Always use proper risk management and conduct your own analysis. The author is not responsible for any losses incurred from using this indicator.
-Made with passion by officialjackofalltrades
Indicateur
VWAP Volatility Bands [BOSWaves]VWAP Volatility Bands - T3-Smoothed VWAP System with Dynamically Scaled Volatility Bands
Overview
VWAP Volatility Bands is a tension-aware trend following system that anchors directional bias to a T3-smoothed Volume Weighted Average Price, where volatility bands dynamically scale with to reflect real market conditions and automatically generate directional signals when price interacts with band extremes.
Instead of relying on raw VWAP lines or static envelope channels, trend state, band visibility, and signal generation are determined through T3-smoothed VWAP direction, ATR-normalized band construction, and score-based logic that surfaces only the most relevant visual context for the current trend.
This creates dynamic volatility boundaries that reflect actual price tension relative to the volume-weighted mean rather than arbitrary fixed offsets - compressing during low-volatility conditions, expanding during high-volatility periods, and capturing overextension signals at band extremes where price demonstrates significant deviation from fair value.
Price is therefore evaluated relative to bands that adapt to volatility dynamics and volume-weighted equilibrium rather than conventional price-only moving averages.
Conceptual Framework
VWAP Volatility Bands is founded on the principle that meaningful trend signals emerge when price maintains position relative to a T3-smoothed VWAP that filters short-term noise, while significant overextension zones form at ATR-scaled distances that reflect genuine volatility rather than static multipliers.
Traditional VWAP approaches plot raw cumulative values without smoothing, making them reactive to short-term volume spikes and difficult to read in trend context. This framework replaces raw VWAP plotting as the primary reference with T3-smoothed VWAP direction, using the raw line only as an optional secondary reference for confluence.
Three core principles guide the design:
Trend direction should be determined by the slope of T3-smoothed VWAP, filtering noise inherent in raw cumulative VWAP readings.
Volatility bands should scale dynamically with ATR, ensuring band distances represent statistically meaningful deviations across varying market conditions.
Only directionally relevant bands should be displayed at any time - bullish bands below during uptrends, bearish bands above during downtrends - reducing visual noise and reinforcing directional context.
This shifts VWAP analysis from a single reference line into a full tension-aware volatility framework with intelligent band management.
Theoretical Foundation
The indicator combines anchored VWAP accumulation, T3 exponential smoothing, Average True Range volatility measurement, slope-based score logic, and overextension signal detection methodology.
A user-configurable VWAP anchor (Session, Week, Month) provides the volume-weighted price reference that resets at meaningful market boundaries, while T3 smoothing applies a six-stage EMA cascade with configurable volume factor to eliminate noise without introducing excessive lag. ATR measurement provides volatility-normalized scaling for band construction. Score logic encodes T3 slope direction into a persistent state that governs band visibility and bar coloring.
Four internal systems operate in tandem:
VWAP Accumulation Engine : Computes cumulative volume-weighted typical price across the selected anchor period, resetting at session, weekly, or monthly boundaries.
T3 Smoothing System : Applies six-stage EMA cascade with configurable length and volume factor to produce a smooth, low-lag trend baseline from raw VWAP.
ATR Band Construction : Scales four band pairs above and below T3 baseline using fixed ATR multipliers (0.5, 1.0, 1.5, 2.2) to define volatility zones of increasing significance.
Score and Signal Engine : Tracks T3 slope direction as a persistent score state, governs which band set is displayed, generates entry diamonds at slope changes, and fires TP signals at band extreme crossovers.
This design allows volatility boundaries to reflect actual market tension relative to volume-weighted fair value rather than reacting mechanically to price-only calculations.
How It Works
VWAP Volatility Bands evaluates price through a sequence of volume-weighted, tension-aware processes:
Anchor Reset Detection : System identifies session, weekly, or monthly boundaries and resets cumulative volume and volume-weighted price accumulators accordingly.
VWAP Accumulation : Typical price multiplied by volume accumulates alongside raw volume across the anchor period, producing a continuously updating raw VWAP value.
T3 Smoothing : Raw VWAP passes through a six-EMA T3 cascade using configurable length and factor parameters, producing a smooth directional baseline.
ATR Calculation : 14-period ATR provides volatility-normalized distance measurement for all band construction.
Band Calculation : Four upper and four lower bands are computed at 0.5, 1.0, 1.5, and 2.2 ATR distances from the T3 baseline.
Score Assignment : T3 slope is evaluated each bar; rising slope sets score to +1 (bullish), falling slope sets score to -1 (bearish), flat slope persists prior state.
Directional Band Display : Score +1 renders lower bands only; score -1 renders upper bands only, ensuring only contextually relevant zones are visible.
Gradient Fill Construction : Progressive opacity fills between band pairs create a visual tension gradient, with outer fill intensity scaling dynamically based on price proximity to the extreme band.
Entry Signal Generation : T3 slope crossover (bullish) plots a diamond at the lower extreme band; T3 slope crossunder (bearish) plots a diamond at the upper extreme band.
TP Signal Generation : Price closing beyond the outer band against the current trend direction triggers a take-profit marker, identifying overextension relative to the volatility envelope.
Bar Coloring : Each bar is tinted based on trend score and distance from T3 baseline, with intensity scaling proportionally to deviation up to the outer band distance.
Together, these elements form a continuously updating volatility framework anchored in volume-weighted price dynamics and ATR-normalized tension measurement.
Interpretation
VWAP Volatility Bands should be interpreted as volume-anchored volatility boundaries with automated overextension detection:
Bullish Trend State (Green) : Established when T3-smoothed VWAP slope is rising, with lower volatility bands displayed as dynamic support zones beneath price.
Bearish Trend State (Red) : Established when T3-smoothed VWAP slope is falling, with upper volatility bands displayed as dynamic resistance zones above price.
Elastic Cloud : Progressive gradient fills between band pairs create a visual tension zone, with outer fill darkening as price pushes toward the extreme band.
Raw VWAP Line : Optional dotted reference displaying the unsmoothed cumulative VWAP for confluence analysis against the T3 baseline.
Tension Dynamics : Price operating near T3 baseline indicates low tension and equilibrium; price near outer bands (2.2 ATR) indicates high tension and potential overextension.
◆ Entry Signals : Green diamond at lower band marks T3 slope turning bullish; red diamond at upper band marks T3 slope turning bearish, indicating directional momentum shifts.
⬨ TP Signals : Take-profit markers appear when price closes beyond the outer band against the prevailing trend direction, signaling potential exhaustion and mean reversion opportunity.
Colored Candles : Bar tinting reflects current trend state and distance from T3 baseline, with gray bars near the baseline and full-color bars at maximum tension distance.
T3 slope direction, band interaction, and tension proximity outweigh isolated price movements when interpreting the indicator.
Signal Logic & Visual Cues
VWAP Volatility Bands presents three primary interaction signals:
Buy Signal (◆) : Green diamond appears at the lower extreme band when T3-smoothed VWAP slope crosses upward, suggesting bullish momentum shift with lower volatility bands now acting as dynamic support structure.
Sell Signal (◆) : Red diamond displays at the upper extreme band when T3-smoothed VWAP slope crosses downward, indicating bearish momentum shift with upper volatility bands now acting as dynamic resistance structure.
Take Profit Signal (⬨) : Small markers appear when price crosses beyond the outer extreme band against the prevailing trend direction, identifying overextension relative to the ATR-normalized volatility envelope and suggesting potential mean reversion back toward the T3 baseline.
Band gradient intensity provides continuous visual feedback on tension buildup without requiring separate oscillator panels.
Alert generation covers trend state switches (bullish/bearish entry signals) and take-profit occurrences for systematic monitoring.
Strategy Integration
VWAP Volatility Bands fits within adaptive trend-following and volatility-envelope approaches:
Band-Based Position Management : Use inner bands (0.5–1.0 ATR) as continuation zones and outer bands (1.5–2.2 ATR) as overextension warnings during active trends.
TP Signal Profit-Taking : Scale out of positions when price triggers outer band TP signals, as these mark statistically significant deviation from the volume-weighted mean.
T3 Baseline Re-entry : Look for re-entry opportunities when price pulls back toward T3 baseline during trending conditions without breaching trend direction.
Raw VWAP Confluence : Use optional raw VWAP display alongside T3 baseline to identify alignment between smoothed and unsmoothed references as higher-confidence zones.
Tension-Aware Sizing : Reduce position sizing when price operates near outer bands as overextension conditions carry elevated mean-reversion risk.
Anchor Period Selection : Match VWAP anchor to trading timeframe - Session for intraday, Week for swing, Month for position trading - to ensure volume weighting reflects relevant market participation.
Multi-Timeframe Confirmation : Apply higher-timeframe VWAP Volatility Bands trend state as directional filter for lower-timeframe entry precision, entering only when T3 slopes align across timeframes.
Technical Implementation Details
Core Engine : Anchored VWAP accumulation with configurable reset boundary (Session, Week, Month) and T3-smoothed baseline
Smoothing Model : Six-stage EMA cascade (T3) with configurable length and volume factor parameters
Band Model : Four ATR-scaled band pairs at fixed multipliers (0.5, 1.0, 1.5, 2.2) from T3 baseline
Score System : Persistent slope-based directional state with single-bar crossover detection
Visualization : Progressive gradient fills with dynamic outer opacity, directional bar coloring scaling with tension distance
Signal Logic : Slope crossover entry diamonds at outer band level, outer band breach TP markers with directional filtering
Performance Profile : Optimized for real-time execution across all timeframes with efficient cumulative accumulation logic
Optimal Application Parameters
Timeframe Guidance:
1 - 5 min : Intraday scalping with Session anchor and responsive T3 length settings
15 - 60 min : Intraday momentum following with Session or Week anchor for balanced band behavior
4H - Daily : Swing-level trend identification with Week or Month anchor for sustained volatility context
Suggested Baseline Configuration:
VWAP Anchor : Session
T3 Length : 28
T3 Factor : 0.7
ATR Length : 14
Show Raw VWAP : Enabled
Show TP Signals : Enabled
Color Bars : Enabled
Bullish Color : Bright Green (#00FF44)
Bearish Color : Pink-Red (#FF0066)
These suggested parameters should be used as a baseline; their effectiveness depends on the asset's volatility profile, trending characteristics, and anchor period alignment with the trading timeframe, so fine-tuning is expected for optimal performance.
Parameter Calibration Notes
Use the following adjustments to refine behavior without altering the core logic:
T3 too slow/fast : Adjust T3 Length to control smoothing speed - lower values produce a more responsive baseline with earlier slope changes, higher values create a smoother baseline with more persistent trend states.
T3 too smooth/jagged : Adjust T3 Factor between 0.0 and 1.0 - higher values increase smoothness with additional lag, lower values reduce lag at the cost of more noise in the baseline.
Bands too wide/narrow : Adjust ATR Length to control band scaling - lower values make bands more reactive to recent volatility, higher values produce more stable band distances.
Too many TP signals : TP signals fire at the 2.2 ATR outer band by design; if frequency is excessive, consider increasing ATR Length to stabilize the outer band distance.
VWAP anchor misaligned : Switch anchor period to match the dominant trading session or timeframe - Session for intraday, Week for multi-day swing, Month for longer-term positioning.
Excessive bar color noise : Disable Color Bars to remove tinting and focus purely on band and signal interaction without bar-level visual feedback.
Raw VWAP divergence : Large gaps between raw VWAP and T3 baseline indicate high smoothing lag; reduce T3 Length or Factor to bring baseline closer to raw VWAP in fast-moving conditions.
Adjustments should be incremental and evaluated across multiple session types rather than isolated market conditions.
Performance Characteristics
High Effectiveness:
Trending markets with sustained directional movement away from the volume-weighted mean
Instruments with consistent intraday volume profiles where VWAP anchoring provides meaningful fair value reference
Momentum continuation strategies using inner bands as dynamic support/resistance during active trends
Overextension identification approaches benefiting from ATR-normalized outer band signals at tension extremes
Session-based trading where VWAP anchor resets align with institutional volume participation boundaries
Reduced Effectiveness:
Choppy, range-bound markets with frequent T3 slope reversals producing whipsaw entry signals
Low-volume instruments where VWAP accumulation becomes distorted by thin participation and erratic volume spikes
Pre-market or extended-hours sessions where volume profiles differ significantly from regular session dynamics
Highly gapped markets where price discontinuities bypass band interaction logic between sessions
Consolidation and sideways price action where trend-following methodologies inherently struggle due to lack of sustained directional movement
Integration Guidelines
Confluence : Combine with BOSWaves structure analysis, momentum oscillators, or volume profile tools for multi-factor confirmation
Band Respect : Honor outer band TP signals as primary overextension alerts - consider reducing exposure when price reaches 2.2 ATR deviation from T3 baseline
Baseline Awareness : Monitor price relationship to T3 baseline as the primary equilibrium reference - sustained distance indicates trend conviction, proximity indicates consolidation
Tension Monitoring : Track band gradient intensity to identify building tension conditions that may precede acceleration or reversal
Anchor Discipline : Maintain consistent anchor period selection aligned with the primary trading timeframe rather than switching anchors to fit recent price behavior
State Discipline : Maintain directional bias aligned with current T3 slope state until a confirmed slope reversal occurs
Multi-Timeframe Alignment : Use higher timeframe T3 slope direction as a filter for lower timeframe entries to ensure confluence across time horizons
Disclaimer
VWAP Volatility Bands is a professional-grade trend following and volatility band system. It uses T3-smoothed VWAP with ATR-normalized band construction but does not predict future price movements. Results depend on market conditions, volatility characteristics, anchor period selection, and disciplined execution. BOSWaves recommends deploying this indicator within a broader analytical framework that incorporates price structure, volume context, and comprehensive risk management. Indicateur
Neural Probability Channel [AlgoPoint]The Neural Probability Channel (NPC) is a next-generation volatility and trend analysis tool designed to overcome the limitations of traditional bands (like Bollinger Bands) and smoothing filters (like standard Moving Averages).
Unlike traditional indicators that rely on linear deviation or simple averages, the NPC utilizes a Rational Quadratic Kernel—a concept derived from machine learning regression models—to calculate a non-repainting, highly adaptive baseline (Fair Value). This allows the indicator to distinguish between market noise and genuine trend shifts with superior accuracy.
The volatility bands are dynamically calculated using a hybrid of Standard Error (Mean Deviation) and ATR, ensuring the channels adapt organically to market conditions—expanding during high-impact moves and contracting during consolidation.
How It Works
- The Neural Baseline (Center Line): Instead of a standard Moving Average, the NPC uses a Rational Quadratic Kernel weighting system. This assigns "importance" to price data based on both recency and similarity. It acts as a "Center of Gravity" for price, providing a smoother yet responsive trend detection line without the lag associated with SMAs or EMAs.
Crucially, the math is causal (no lookahead), meaning it does not repaint.
- Adaptive Volatility Bands: The channel width is not fixed. It uses a Hybrid Volatility Model:
- Inner Channel: Represents the "Probability Zone" (approx. 70% confidence). Price staying here indicates a stable trend.
- Outer Channel: Represents "Extreme Deviation" (Statistical Anomalies). When price touches or breaches these outer bands, it is statistically overextended (Overbought/Oversold).
Signal Generation:
- Reversion Signals: Generated when price breaches the Outer Bands and closes back inside. This suggests a "Snap-back" or Mean Reversion event.
- Trend Confirmation: The color of the baseline and the fill zones changes based on the slope of the Kernel, giving an instant visual read on market bias.
How to Use It
- Mean Reversion Strategy: Look for price action extending beyond the Outer Bands (Thinner lines). If price leaves a wick and closes back inside, it signals a high-probability reversal toward the Neural Baseline.
- Green Signal: Potential Long (Reversal from Lows).
- Red Signal: Potential Short (Reversal from Highs).
- Trend Following: Use the Neural Baseline (Thick Center Line) as a dynamic support/resistance level.
If price is holding above the baseline and the cloud is green, the trend is Bullish.
If price is holding below the baseline and the cloud is red, the trend is Bearish.
- Squeeze Detection: When the Inner and Outer bands compress significantly, it indicates low volatility and often precedes an explosive breakout.
Settings
- Lookback Window: Determines the depth of the Kernel analysis.
- Smoothness (Bandwidth): Higher values create a smoother baseline (better for trends), while lower values make it more reactive (better for scalping).
- Regression Alpha: Controls the weight distribution of the Kernel.
- Channel Multipliers: Adjust the width of the Inner and Outer bands to fit your specific asset's volatility profile. Indicateur
Linear Regression Channel With Pearson's R (Multi Sigma & MTF)This indicator applies multi‑sigma linear regression across multiple institutional time horizons to quantify the line of best fit in equities and index markets. By combining multi‑timeframe presets with statistically derived deviation bands, it highlights trend structure, volatility expansion, and regime transitions with clarity.
What’s New in This Update
The original version of the indicator produced a linear regression channel with multiple deviation bands. However, the statistical values it displayed were not mathematically valid. The value labeled “r” was not Pearson’s correlation coefficient and could not be used to derive R² or any formal regression diagnostics.
This update introduces a fully correct statistical engine based on ordinary least squares (OLS).
NEW STATISTICAL OUTPUTS
• True Pearson’s r
• True R² (coefficient of determination)
• RSS (Residual Sum of Squares)
• TSS (Total Sum of Squares)
These values are mathematically valid, bounded, and directly tied to the regression line.
KEY IMPROVEMENTS
• Correct OLS intercept (removes the erroneous +slope term)
• Proper predicted values using ŷ = b₀ + b₁x
• Correct centering around the actual mean of the data
• Removal of correlation logic from the deviation engine
• Clean separation between statistical computation and volatility computation
• Regression channel visuals remain identical, but the underlying math is now fully accurate
These changes ensure that r and R² reflect true trend strength and model fit, enabling more reliable interpretation of long‑term and short‑term trend regimes.
CORE FEATURES (UNCHANGED)
• Auto‑Multi‑Timeframe presets aligned with institutional trend horizons
• Multi‑Sigma bands (+/‑1σ, +/‑2σ, +/‑3σ) for volatility structure and statistical extremes
• True least‑squares regression recalculated each bar
• Deviation mode toggle (Standard Deviation vs. Max Deviation)
• Full documentation and institutional use‑case examples available on GitHub
More information can be found here:
github.com Indicateur
Linear Regression Channel with Multi Sigma and Multi Time FrameThis indicator applies multi-sigma linear regression across multiple institutional time horizons to quantify the line of best fit in equities and index markets. By combining multi-timeframe presets with statistically derived deviation bands, it highlights trend structure, volatility expansion, and regime transitions with clarity.
Features
Auto-Multi-Timeframe presets map directly to institutional trend horizons (daily, weekly, monthly) for accurate regime detection.
Multi-Sigma bands (+/-1, +/-2, +/-3) reveal volatility structure, trend strength, and statistical extremes.
The regression line uses a true least-squares calculation, recalculated each bar for precise trend alignment.
Deviation mode allows switching between standard deviation and max deviation to support different volatility models.
A linked PDF on GitHub provides full documentation, derivations, and institutional use-case examples.
More Information Can Be Found Here:
github.com Indicateur
VDUB Bands - MTF WMA+ATR Volatility Lanes (6 Alerts)VDUB Bands draws volatility-scaled “trend lanes” around a Weighted Moving Average (WMA) using ATR (or a WMA of True Range). It can display up to four tiers (L1–L4), with higher tiers sourced from higher timeframes to show local structure → higher-timeframe structure on a single chart.
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1. What it does (plain English)
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Think of each tier as a lane system around the trend:
• Inner rails = “normal volatility lane” around the WMA
• Outer rails = “extension / extreme zone” for that tier
• Higher tiers (L3/L4) show bigger structure
• Lower tiers (L1/L2) show active lane behavior
Typical interpretation:
• Price inside inner rails → normal variance around the trend lane
• Between inner and outer → stretched, but not extreme
• Outside outer rails → extended vs that tier’s volatility band
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2) Why it’s useful (and why it’s not a mashup)
────────────────────────────────────────
This is not a bundle of unrelated indicators. Everything serves one cohesive purpose:
• Visualize trend + volatility lanes across multiple time horizons
• Keep rails consistent and readable (levels, fills, outlines)
• Optional multi-timeframe aggregation for structure context
• A compact 6-alert set to catch key transitions without alert spam
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3) What you see on the chart
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For each level (L1–L4), you can show:
• Upper/Lower Inner rails
• Upper/Lower Outer rails
• Optional center fill (between outer rails) = operating range
• Optional MA line per tier (off by default to reduce clutter)
• Base WMA line (L1 MA) if enabled
Suggested workflow:
• Start with L1 + L2 only
• Add L3/L4 once you like the structure view
• Use Dynamic Opacity if the chart feels crowded
────────────────────────────────────────
4) How it works (transparent formula)
────────────────────────────────────────
For each tier:
• MA = WMA(source, baseLen × levelMultiplier)
• ATR_like = Wilder ATR (default)
OR WMA(TrueRange, atrLen × levelMultiplier)
Inner rails:
• upperInner = MA + ATR_like × innerMult
• lowerInner = MA - ATR_like × innerMult
Outer rails:
• upperOuter = MA + ATR_like × outerMult
• lowerOuter = MA - ATR_like × outerMult
Tier behavior:
• L1 uses the chart timeframe
• L2–L4 can use user-selected HTFs (defaults: 4H / D / W)
or optional auto-selection
────────────────────────────────────────
5) Multi-timeframe behavior + interpolation
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• L2–L4 use request.security() with lookahead OFF (no future data).
• HTF bands naturally “step” when the HTF candle confirms.
• Interpolate HTF Bands (optional): visually blends from the prior confirmed HTF value to the current confirmed HTF value to reduce stepping. This is display smoothing, not prediction.
Repaint note:
• If Live Interp (Repaints) is enabled, the HTF lines can update intrabar and may repaint. Keep it OFF for strict non-repainting behavior.
────────────────────────────────────────
6) Auto-select L2/L3/L4 (optional)
────────────────────────────────────────
Two modes:
A) Ladder (deterministic)
• Picks “bigger” timeframes relative to the chart (simple and fast).
B) Score (data-driven)
• Tests candidate timeframes and scores them using:
• Coverage: % of closes inside the OUTER band over Score Lookback
• Width: average outer-band width as a fraction of MA
• Targets: Target Coverage + Target Width
• Weights: Coverage Weight + Width Weight
Performance notes:
• Score mode is heavier (many candidates).
• “Lock auto-select after first pick” is recommended to reduce load and avoid platform limits.
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7) Alerts (6 total, aggregated across L1–L4)
────────────────────────────────────────
Alerts trigger if ANY tier meets the condition:
• Cross ABOVE an OUTER band
• Cross BELOW an OUTER band
• Cross ABOVE an INNER band
• Cross BELOW an INNER band
• Price is OUTSIDE ABOVE an OUTER band
• Price is OUTSIDE BELOW an OUTER band
These are intentionally aggregated to keep the alert count small while catching meaningful transitions.
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8) Limitations & transparency
────────────────────────────────────────
• Indicator only (not a strategy). No performance claims.
• MTF values update when the higher timeframe candle confirms.
• Interpolation is visual smoothing; it does not forecast.
• Non-standard chart types (Heikin Ashi/Renko/etc) may behave differently from standard candles.
• If you enable repainting options, signals/levels may change intrabar.
────────────────────────────────────────
9) Credits/reuse disclosure
────────────────────────────────────────
• Conceptual inspiration: VDUB and the community “VDUB_BINARY_PRO_3_V2” idea of WMA ± TR/ATR × multipliers.
• This version is a reimplementation + extension, adding:
o Multi-tier architecture (L1–L4)
o Higher-timeframe sourcing + optional interpolation
o Optional scoring-based timeframe selection
o Dynamic opacity + streamlined plotting
o Aggregated 6-alert set
No code was copied directly from the older script; this is a rewritten implementation with additional features and different structure.
www.tradingview.com
Indicateur
Zero Lag Trend Signals (MTF) [AlgoAlpha]Zero Lag Trend Signals 🚀📈
Ready to take your trend-following strategy to the next level? Say hello to Zero Lag Trend Signals , a precision-engineered Pine Script™ indicator designed to eliminate lag and provide rapid trend insights across multiple timeframes. 💡 This tool blends zero-lag EMA (ZLEMA) logic with volatility bands, trend-shift markers, and dynamic alerts. The result? Timely signals with minimal noise for clearer decision-making, whether you're trading intraday or on longer horizons. 🔄
🟢 Zero-Lag Trend Detection : Uses a zero-lag EMA (ZLEMA) to smooth price data while minimizing delay.
⚡ Multi-Timeframe Signals : Displays trends across up to 5 timeframes (from 5 minutes to daily) on a sleek table.
📊 Volatility-Based Bands : Adaptive upper and lower bands, helping you identify trend reversals with reduced false signals.
🔔 Custom Alerts : Get notified of key trend changes instantly with built-in alert conditions.
🎨 Color-Coded Visualization : Bullish and bearish signals pop with clear color coding, ensuring easy chart reading.
⚙️ Fully Configurable : Modify EMA length, band multiplier, colors, and timeframe settings to suit your strategy.
How to Use 📚
⭐ Add the Indicator : Add the indicator to favorites by pressing the star icon. Set your preferred EMA length and band multiplier. Choose your desired timeframes for multi-frame trend monitoring.
💻 Watch the Table & Chart : The top-right table dynamically updates with bullish or bearish signals across multiple timeframes. Colored arrows on the chart indicate potential entry points when the price crosses the ZLEMA with confirmation from volatility bands.
🔔 Enable Alerts : Configure alerts for real-time notifications when trends shift—no need to monitor charts constantly.
How It Works 🧠
The script calculates the zero-lag EMA (ZLEMA) by compensating for data lag, giving traders more responsive moving averages. It checks for volatility shifts using the Average True Range (ATR), multiplied to create upper and lower deviation bands. If the price crosses above or below these bands, it marks the start of new trends. Additionally, the indicator aggregates trend data from up to five configurable timeframes and displays them in a neat summary table. This helps you confirm trends across different intervals—ideal for multi-timeframe analysis. The visual signals include upward and downward arrows on the chart, denoting potential entries or exits when trends align across timeframes. Traders can use these cues to make well-timed trades and avoid lag-related pitfalls. Indicateur
Curved Price Channels (Zeiierman)█ Overview
The Curved Price Channels (Zeiierman) is designed to plot dynamic channels around price movements, much like the traditional Donchian Channels, but with a key difference: the channels are curved instead of straight. This curvature allows the channels to adapt more fluidly to price action, providing a smoother representation of the highest high and lowest low levels.
Just like Donchian Channels, the Curved Price Channels help identify potential breakout points and areas of trend reversal. However, the curvature offers a more refined approach to visualizing price boundaries, making it potentially more effective in capturing price trends and reversals in markets that exhibit significant volatility or price swings.
The included trend strength calculation further enhances the indicator by offering insight into the strength of the current trend.
█ How It Works
The Curved Price Channels are calculated based on the asset's average true range (ATR), scaled by the chosen length and multiplier settings. This adaptive size allows the channels to expand and contract based on recent market volatility. The central trendline is calculated as the average of the upper and lower curved bands, providing a smoothed representation of the overall price trend.
Key Calculations:
Adaptive Size: The ATR is used to dynamically adjust the width of the channels, making them responsive to changes in market volatility.
Upper and Lower Bands: The upper band is calculated by taking the maximum close value and adjusting it downward by a factor proportional to the ATR and the multiplier. Similarly, the lower band is calculated by adjusting the minimum close value upward.
Trendline: The trendline is the average of the upper and lower bands, representing the central tendency of the price action.
Trend Strength
The Trend Strength feature in the Curved Price Channels is a powerful feature designed to help traders gauge the strength of the current trend. It calculates the strength of a trend by analyzing the relationship between the price's position within the curved channels and the overall range of the channels themselves.
Range Calculation:
The indicator first determines the distance between the upper and lower curved channels, known as the range. This range represents the overall volatility of the price within the given period.
Range = Upper Band - Lower Band
Relative Position:
The next step involves calculating the relative position of the closing price within this range. This value indicates where the current price sits in relation to the overall range.
RelativePosition = (Close - Trendline) / Range
Normalization:
To assess the trend strength over time, the current range is normalized against the maximum and minimum ranges observed over a specified look-back period.
NormalizedRange = (Range - Min Range) / (Max Range - Min Range)
Trend Strength Calculation:
The final Trend Strength is calculated by multiplying the relative position by the normalized range and then scaling it to a percentage.
TrendStrength = Relative Position * Normalized Range * 100
This approach ensures that the Trend Strength not only reflects the direction of the trend but also its intensity, providing a more comprehensive view of market conditions.
█ Comparison with Donchian Channels
Curved Price Channels offer several advantages over Donchian Channels, particularly in their ability to adapt to changing market conditions.
⚪ Adaptability vs. Fixed Structure
Donchian Channels: Use a fixed period to plot straight lines based on the highest high and lowest low. This can be limiting because the channels do not adjust to volatility; they remain the same width regardless of how much or how little the price is moving.
Curved Price Channels: Adapt dynamically to market conditions using the Average True Range (ATR) as a measure of volatility. The channels expand and contract based on recent price movements, providing a more accurate reflection of the market's current state. This adaptability allows traders to capture both large trends and smaller fluctuations more effectively.
⚪ Sensitivity to Market Movements
Donchian Channels: Are less sensitive to recent price action because they rely on a fixed look-back period. This can result in late signals during fast-moving markets, as the channels may not adjust quickly enough to capture new trends.
Curved Price Channels: Respond more quickly to changes in market volatility, making them more sensitive to recent price action. The multiplier setting further allows traders to adjust the channel's sensitivity, making it possible to capture smaller price movements during periods of low volatility or filter out noise during high volatility.
⚪ Enhanced Trend Strength Analysis
Donchian Channels: Do not provide direct insight into the strength of a trend. Traders must rely on additional indicators or their judgment to gauge whether a trend is strong or weak.
Curved Price Channels: Includes a built-in trend strength calculation that takes into account the distance between the upper and lower channels relative to the trendline. A broader range between the channels typically indicates a stronger trend, while a narrower range suggests a weaker trend. This feature helps traders not only identify the direction of the trend but also assess its potential longevity and strength.
⚪ Dynamic Support and Resistance
Donchian Channels: Offer static support and resistance levels that may not accurately reflect changing market dynamics. These levels can quickly become outdated in volatile markets.
Curved Price Channels: Offer dynamic support and resistance levels that adjust in real-time, providing more relevant and actionable trading signals. As the channels curve to reflect price movements, they can help identify areas where the price is likely to encounter support or resistance, making them more useful in volatile or trending markets.
█ How to Use
Traders can use the Curved Price Channels in similar ways to Donchian Channels but with the added benefits of the adaptive, curved structure:
Breakout Identification:
Just like Donchian Channels, when the price breaks above the upper curved band, it may signal the start of a bullish trend, while a break below the lower curved band could indicate a bearish trend. The curved nature of the channels helps in capturing these breakouts more precisely by adjusting to recent volatility.
Volatility:
The width of the price channels in the Curved Price Channels indicator serves as a clear indicator of current market volatility. A wider channel indicates that the market is experiencing higher volatility, as prices are fluctuating more dramatically within the period. Conversely, a narrower channel suggests that the market is in a lower volatility state, with price movements being more subdued.
Typically, higher volatility is observed during negative trends, where market uncertainty or fear drives larger price swings. In contrast, lower volatility is often associated with positive trends, where prices tend to move more steadily and predictably. The adaptive nature of the Curved Price Channels reflects these volatility conditions in real time, allowing traders to assess the market environment quickly and adjust their strategies accordingly.
Support and Resistance:
The trend line act as dynamic support and resistance levels. Due to it's adaptive nature, this level is more reflective of the current market environment than the fixed level of Donchian Channels.
Trend Direction and Strength:
The trend direction and strength are highlighted by the trendline and the directional candle within the Curved Price Channels indicator. If the price is above the trendline, it indicates a positive trend, while a price below the trendline signals a negative trend. This directional bias is visually represented by the color of the directional candle, making it easy for traders to quickly identify the current market trend.
In addition to the trendline, the indicator also displays Max and Min values. These represent the highest and lowest trend strength values within the lookback period, providing a reference point for understanding the current trend strength relative to historical levels.
Max Value: Indicates the highest recorded trend strength during the lookback period. If the Max value is greater than the Min value, it suggests that the market has generally experienced more positive (bullish) conditions during this time frame.
Min Value: Represents the lowest recorded trend strength within the same period. If the Min value is greater than the Max value, it indicates that the market has been predominantly negative (bearish) over the lookback period.
By assessing these Max and Min values, traders gain an immediate understanding of the underlying trend. If the current trend strength is close to the Max value, it indicates a strong bullish trend. Conversely, if the trend strength is near the Min value, it suggests a strong bearish trend.
█ Settings
Trend Length: Defines the number of bars used to calculate the core trendline and adaptive size. A length of 200 will create a smooth, long-term trendline that reacts slowly to price changes, while a length of 20 will create a more responsive trendline that tracks short-term movements.
Multiplier: Adjusts the width of the curved price channels. A higher value tightens the channels, making them more sensitive to price movements, while a lower value widens the channels. A multiplier of 10 will create tighter channels that are more sensitive to minor price fluctuations, which is useful in low-volatility markets. A multiplier of 2 will create wider channels that capture larger trends and are better suited for high-volatility markets.
Trend Strength Length: Defines the period over which the maximum and minimum ranges are calculated to normalize the trend strength. A length of 200 will smooth out the trend strength readings, providing a stable indication of trend health, whereas a length of 50 will make the readings more reactive to recent price changes.
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Disclaimer
The information contained in my Scripts/Indicators/Ideas/Algos/Systems does not constitute financial advice or a solicitation to buy or sell any securities of any type. I will not accept liability for any loss or damage, including without limitation any loss of profit, which may arise directly or indirectly from the use of or reliance on such information.
All investments involve risk, and the past performance of a security, industry, sector, market, financial product, trading strategy, backtest, or individual's trading does not guarantee future results or returns. Investors are fully responsible for any investment decisions they make. Such decisions should be based solely on an evaluation of their financial circumstances, investment objectives, risk tolerance, and liquidity needs.
My Scripts/Indicators/Ideas/Algos/Systems are only for educational purposes!
Indicateur
Trend Continuation Signals [AlgoAlpha]Introducing the Trend Continuation Signals by AlgoAlpha 🌟🚀
Elevate your trading game with this multipurpose indicator, designed to pinpoint trend continuation opportunities as well as highlight volatility and oversold/overbought conditions. Whether you're a trading novice or a seasoned market veteran, this tool offers intuitive visual cues to boost your decision-making and enhance your market analysis. Let's explore the key features, how to use it effectively, and delve into the operational mechanics that make this tool a game-changer in your trading arsenal:
Key Features:
🔥 Advanced Trend Detection : Leverages the Hull Moving Average (HMA) for superior trend tracking as compared to other MAs, offering unique insights into market momentum.
🌈 Volatility Bands : Implements adjustable bands around the trend line, which evolve with market conditions to highlight potential trading opportunities.
⚡ Trend Continuation Signals : Identifies bullish and bearish continuation signals, equipping you with actionable signals to exploit the prevailing market trend.
🎨 Intuitive Color Coding : Employs a vibrant color scheme to distinguish between uptrends, downtrends, and neutral phases, facilitating easy interpretation of the indicator's insights.
🛠 How to Use "Trend Continuation Signals ":
🔍 Setting Up : Incorporate the indicator onto your chart and customize the indicator to suite your preferences.
👀 Reading the Signals : Pay attention to the color-coded trend lines and volatility bands. Green indicates an uptrend, red signifies a downtrend, and gray denotes a neutral market condition.
📈 Identifying Entry Points : Look for bullish (▲) and bearish (▼) continuation icons below or above the price bars as signals for potential entry points for long or short positions, respectively.
🔄 Confirmation : Validate your trades with further analysis or other indicators. The Trend Continuation Signals are most effective when complemented by other technical analysis tools or fundamental insights.
📉 Risk Management : Implement stop-loss orders in line with your risk appetite and adjust them based on the volatility bands provided by the indicator to safeguard your investments.
How It Operates:
The essence of the indicator is captured through the hull moving averages for both the primary and secondary lines, set at periods of 93 and 50, respectively, to reflect market trends and pullbacks that trigger the continuation signals every time price recovers from a detected pullback.
Volatility is quantified through the standard deviation of the midline, magnified by a factor, establishing the upper and lower trend band boundaries.
Further volatility bands are plotted around the main volatility band, providing a granular view of market volatility and potential breakout or breakdown zones.
Market trend direction is determined by comparing the HMA line's current position to its previous value, enhanced by the secondary line to identify continuation patterns.
Embrace the power of the Trend Continuation Signals to enhance your trading strategy! It is important to note that all indicators are best used in confluence with other forms of analysis, happy trading! 📊💥 Indicateur
Volatility Trend (Zeiierman)█ Overview
The Volatility Trend (Zeiierman) is an indicator designed to help traders identify and analyze market trends based on price volatility. By calculating a dynamic trend line and volatility-adjusted bands, the indicator provides visual cues to understand the current market direction, potential reversal points and volatility.
█ How It Works
The indicator uses a weighted moving average of historical prices to create a responsive trend line that is adjusted for volatility using standard deviation. The indicator sets upper and lower bands at intervals of two standard deviations, acting as markers for potential overbought or oversold conditions. Additionally, by comparing current and previous trend line values, the indicator identifies the trend direction, providing crucial insights for traders.
█ How to Use
Trend Identification
Use the trend line to identify the overall market direction. An upward-sloping line indicates an uptrend, while a downward-sloping line indicates a downtrend.
Volatility Assessment
Use the distance between the upper and lower bands to gauge market volatility. Wider bands indicate higher volatility, while narrower bands indicate lower volatility.
Overbought/Oversold
If the price reaches or exceeds the upper or lower bands, it may be in an overbought or oversold condition, respectively.
█ Settings
Trend Control: Adjusts the sensitivity and smoothness of the trend line. Lower values make the trend more responsive, while higher values make it smoother.
Trend Dynamic: Controls how quickly the trend adjusts to price changes. Higher values result in a slower adjustment.
Volatility: Consists of two parts - the scaling factor for volatility and the sensitivity for volatility adjustment. Adjusting these settings alters the distance between the trend lines and the price, as well as how sensitive the bands are to changes in volatility.
Squeeze Control: Influences the degree to which market squeeze is considered in the calculation, with higher values increasing sensitivity.
Enable Scalping Trend: A toggle that, when activated, makes the indicator focus on short-term trends, which is particularly useful for scalping strategies.
█ Related scripts with the same calculation philosophy
TrendCylinder
TrendSphere
Predictive Trend and Structure
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Disclaimer
The information contained in my Scripts/Indicators/Ideas/Algos/Systems does not constitute financial advice or a solicitation to buy or sell any securities of any type. I will not accept liability for any loss or damage, including without limitation any loss of profit, which may arise directly or indirectly from the use of or reliance on such information.
All investments involve risk, and the past performance of a security, industry, sector, market, financial product, trading strategy, backtest, or individual's trading does not guarantee future results or returns. Investors are fully responsible for any investment decisions they make. Such decisions should be based solely on an evaluation of their financial circumstances, investment objectives, risk tolerance, and liquidity needs.
My Scripts/Indicators/Ideas/Algos/Systems are only for educational purposes! Indicateur
Indicateur
Z-Score Based Momentum Zones with Advanced Volatility ChannelsThe indicator "Z-Score Based Momentum Zones with Advanced Volatility Channels" combines various technical analysis components, including volatility, price changes, and volume correction, to calculate Z-Scores and determine momentum zones and provide a visual representation of price movements and volatility based on multi timeframe highest high and lowest low values.
Note: THIS IS A IMPROVEMNT OF "Multi Time Frame Composite Bands" INDICATOR OF MINE WITH MORE EMPHASIS ON MOMENTUM ZONES CALULATED BASED ON Z-SCORES
Input Options
look_back_length: This input specifies the look-back period for calculating intraday volatility. correction It is set to a default value of 5.
lookback_period: This input sets the look-back period for calculating relative price change. The default value is 5.
zscore_period: This input determines the look-back period for calculating the Z-Score. The default value is 500.
avgZscore_length: This input defines the length of the momentum block used in calculations, with a default value of 14.
include_vc: This is a boolean input that, if set to true, enables volume correction in the calculations. By default, it is set to false.
1. Volatility Bands (Composite High and Low):
Composite High and Low: These are calculated by combining different moving averages of the high prices (high) and low prices (low). Specifically:
a_high and a_low are calculated as the average of the highest (ta.highest) and lowest (ta.lowest) high and low prices over various look-back periods (5, 8, 13, 21, 34) to capture short and long-term trends.
b_high and b_low are calculated as the simple moving average (SMA) of the high and low prices over different look-back periods (5, 8, 13) to smooth out the trends.
high_c and low_c are obtained by averaging a_high with b_high and a_low with b_low respectively.
IDV Correction Calulation : In this script the Intraday Volatility (IDV) is calculated as the simple moving average (SMA) of the daily high-low price range divided by the closing price. This measures how much the price fluctuates in a given period.
Composite High and Low with Volatility: The final c_high and c_low values are obtained by adjusting high_c and low_c with the calculated intraday volatility (IDV). These values are used to create the "Composite High" and "Composite Low" plots.
Composite High and Low with Volatility Correction: The final c_high and c_low values are obtained by adjusting high_c and low_c with the calculated intraday volatility (IDV). These values are used to create the "Composite High" and "Composite Low" plots.
2. Momentum Blocks Based on Z-Score:
Relative Price Change (RPC):
The Relative Price Change (rpdev) is calculated as the difference between the current high-low-close average (hlc3) and the previous simple moving average (psma_hlc3) of the same quantity. This measures the change in price over time.
Additionally, std_hlc3 is calculated as the standard deviation of the hlc3 values over a specified look-back period. The standard deviation quantifies the dispersion or volatility in the price data.
The rpdev is then divided by the std_hlc3 to normalize the price change by the volatility. This normalization ensures that the price change is expressed in terms of standard deviations, which is a common practice in quantitative analysis.
Essentially, the rpdev represents how many standard deviations the current price is away from the previous moving average.
Volume Correction (VC): If the include_vc input is set to true, volume correction is applied by dividing the trading volume by the previous simple moving average of the volume (psma_volume). This accounts for changes in trading activity.
Volume Corrected Relative Price Change (VCRPD): The vcrpd is calculated by multiplying the rpdev by the volume correction factor (vc). This incorporates both price changes and volume data.
Z-Scores: The Z-scores are calculated by taking the difference between the vcrpd and the mean (mean_vcrpd) and then dividing it by the standard deviation (stddev_vcrpd). Z-scores measure how many standard deviations a value is away from the mean. They help identify whether a value is unusually high or low compared to its historical distribution.
Momentum Blocks: The "Momentum Blocks" are essentially derived from the Z-scores (avgZScore). The script assigns different colors to the "Fill Area" based on predefined Z-score ranges. These colored areas represent different momentum zones:
Positive Z-scores indicate bullish momentum, and different shades of green are used to fill the area.
Negative Z-scores indicate bearish momentum, and different shades of red are used.
Z-scores near zero (between -0.25 and 0.25) suggest neutrality, and a yellow color is used. Indicateur
Volatility-Based Mean Reversion BandsThe Volatility-Based Mean Reversion Bands indicator is a powerful tool designed to identify potential mean reversion trading opportunities based on market volatility. The indicator consists of three lines: the mean line, upper band, and lower band. These bands dynamically adjust based on the average true range (ATR) and act as reference levels for identifying overbought and oversold conditions.
The calculation of the indicator involves several steps. The average true range (ATR) is calculated using a specified lookback period. The ATR measures the market's volatility by considering the range between high and low prices over a given period. The mean line is calculated as a simple moving average (SMA) of the closing prices over the same lookback period. The upper band is derived by adding the product of the ATR and a multiplier to the mean line, while the lower band is derived by subtracting the product of the ATR and the same multiplier from the mean line.
Interpreting the indicator is relatively straightforward. When the price approaches or exceeds the upper band, it suggests that the market is overbought and may be due for a potential reversal to the downside. On the other hand, when the price approaches or falls below the lower band, it indicates that the market is oversold and may be poised for a potential reversal to the upside. Traders can look for opportunities to enter short positions near the upper band and long positions near the lower band, anticipating the price to revert back towards the mean line.
The bar color and background color play a crucial role in visualizing the indicator's signals and market conditions. Lime-colored bars are used when the price is above the upper band, indicating a potential bearish mean reversion signal. Conversely, fuchsia-colored bars are employed when the price is below the lower band, suggesting a potential bullish mean reversion signal. This color scheme helps traders quickly identify the prevailing market condition and potential reversal zones. The background color complements the bar color by providing further context. Lime-colored background indicates a potential bearish condition, while fuchsia-colored background suggests a potential bullish condition. The transparency level of the background color is set to 80% to avoid obscuring the price chart while still providing a visual reference.
To provide additional confirmation for mean reversion setups, the indicator incorporates the option to use the Relative Strength Index (RSI) as a confluence factor. The RSI is a popular momentum oscillator that measures the speed and change of price movements. When enabled, the indicator checks if the RSI is in overbought territory (above 70) or oversold territory (below 30), providing additional confirmation for potential mean reversion setups.
In addition to visual signals, the indicator includes entry arrows above or below the bars to highlight the occurrence of short or long entries. When the price is above the upper band and the confluence condition is met, a fuchsia-colored triangle-up arrow is displayed above the bar, indicating a potential short entry signal. Similarly, when the price is below the lower band and the confluence condition is met, a lime-colored triangle-down arrow is displayed below the bar, indicating a potential long entry signal.
Traders can customize the indicator's parameters according to their trading preferences. The "Lookback Period" determines the number of periods used in calculating the mean line and the average true range (ATR). Adjusting this parameter can affect the sensitivity and responsiveness of the indicator. Smaller values make the indicator more reactive to short-term price movements, while larger values smooth out the indicator and make it less responsive to short-term fluctuations. The "Multiplier" parameter determines the distance between the mean line and the upper/lower bands. Increasing the multiplier widens the bands, indicating a broader range for potential mean reversion opportunities, while decreasing the multiplier narrows the bands, indicating a tighter range for potential mean reversion opportunities.
It's important to note that the Volatility-Based Mean Reversion Bands indicator is not a standalone trading strategy but rather a tool to assist traders in identifying potential mean reversion setups. Traders should consider using additional analysis techniques and risk management strategies to make informed trading decisions. Additionally, the indicator's performance may vary across different market conditions and instruments, so it's advisable to conduct thorough testing and analysis before integrating it into a trading strategy. Indicateur
+ Bollinger Bands WidthHere is my rendition of Bollinger Bands Width. If you are unfamiliar, Bollinger Bands Width is a measure of the distance between the top and bottom bands of Bollinger Bands. Bollinger Bands themselves being a measure of market volatility, BB Width is a simpler, cleaner way of determining the amount of volatility in the market. Myself, I found the original, basic version of BB Width a bit too basic, and I thought that by adding to it it might make for an improvement for traders over the original.
Simple things that I've done are adding a signal line; adding a 'baseline' using Donchian Channels (such as that which is in my Average Candle Bodies Range indicator); adding bar and background coloring; and adding alerts for increasing volatility, and baseline and signal line crosses. It really ends up making for a much improved version of the basic indicator.
A note on how I created the baseline:
First, what do I mean by 'baseline?' I think of it as an area of the indicator where if the BB Width is below you will not want to enter into any trades, and if the BB Width is above then you are free to enter trades based on your system. It's basically a volatility measure of the volatility indicator. Waddah Attar Explosion is a popular indicator that implements something similar. The baseline is calculated thus: make a Donchian Channel of the BB Width, and then use the basis as the baseline while not plotting the actual highs and lows of the Donchian Channel. Now, the basis of a Donchian Channel is the average of the highs and the lows. If we did that here we would have a baseline much too high, however, by making the basis adjustable with a divisor input it no longer must be plotted in the center of the channel, but may be moved much lower (unless you set the divisor to 2, but you wouldn't do that). This divisor is essentially a sensitivity adjustment for the indicator. Of course you don't have to use the baseline. You could ignore it and only use the signal line, or just use the rising and falling of the BB Width by itself as your volatility measure.
I should make note: the main image above at default settings is an 8 period lookback (so, yes, that is quite fast), and the signal line is a Hull MA set to 13. The background and bar coloring are simply set to the rising and falling of the BB Width. Images below will show some different settings, but definitely play with it yourself to determine if it might be a good fit for your system.
Above, settings are background and bar coloring tuned to BB Width being above the baseline, and also requiring that the BB Width be rising. Background coloring only highlights increasing volatility or volatility above a certain threshold. Grey candles are because the BB Width is above the baseline but falling. We'll see an example without the requirement of BB Width rising, below.
Here, we see that background highlights and aqua candles are more prevalent because I've checked off the requirement that BB Width be rising. The idea is that BB Width is above the baseline therefor there is sufficient volatility to enter trades if our indicators give us the go-ahead.
This here is set to BB Width being above the signal line and also requiring a rising BB Width. Keep in mind the signal line is a Hull MA.
And this fourth and final image uses a volume-weighted MA as the signal line. Bar coloring is turned off, and instead the checkboxes for volatility advancing and declining are turned on under the signal line options. BB Width crosses up the signal line is advancing volatility, while falling below it is declining volatility. Background highlights are set to baseline and not requiring a rising BB Width. This way, with a quick glance you can see if the rising volatility is legitimate, i.e., is the cross up of the signal line coupled with it being above the baseline.
Please enjoy. Indicateur
Indicateur
Adaptive Jurik Filter Volatility Bands [Loxx]Adaptive Jurik Filter Volatility Bands uses Jurik Volty and Adaptive, Double Jurik Filter Moving Average (AJFMA) to derive Jurik Filter smoothed volatility channels around an Adaptive Jurik Filter Moving Average. Bands are placed at 1, 2, and 3 deviations from the core basline.
What is Jurik Volty?
One of the lesser known qualities of Juirk smoothing is that the Jurik smoothing process is adaptive. "Jurik Volty" (a sort of market volatility ) is what makes Jurik smoothing adaptive. The Jurik Volty calculation can be used as both a standalone indicator and to smooth other indicators that you wish to make adaptive.
What is the Jurik Moving Average?
Have you noticed how moving averages add some lag (delay) to your signals? ... especially when price gaps up or down in a big move, and you are waiting for your moving average to catch up? Wait no more! JMA eliminates this problem forever and gives you the best of both worlds: low lag and smooth lines.
Ideally, you would like a filtered signal to be both smooth and lag-free. Lag causes delays in your trades, and increasing lag in your indicators typically result in lower profits. In other words, late comers get what's left on the table after the feast has already begun.
That's why investors, banks and institutions worldwide ask for the Jurik Research Moving Average ( JMA ). You may apply it just as you would any other popular moving average. However, JMA's improved timing and smoothness will astound you.
What is adaptive Jurik volatility?
One of the lesser known qualities of Juirk smoothing is that the Jurik smoothing process is adaptive. "Jurik Volty" (a sort of market volatility ) is what makes Jurik smoothing adaptive. The Jurik Volty calculation can be used as both a standalone indicator and to smooth other indicators that you wish to make adaptive.
What is an adaptive cycle, and what is Ehlers Autocorrelation Periodogram Algorithm?
From his Ehlers' book Cycle Analytics for Traders Advanced Technical Trading Concepts by John F. Ehlers , 2013, page 135:
"Adaptive filters can have several different meanings. For example, Perry Kaufman’s adaptive moving average ( KAMA ) and Tushar Chande’s variable index dynamic average ( VIDYA ) adapt to changes in volatility . By definition, these filters are reactive to price changes, and therefore they close the barn door after the horse is gone.The adaptive filters discussed in this chapter are the familiar Stochastic , relative strength index ( RSI ), commodity channel index ( CCI ), and band-pass filter.The key parameter in each case is the look-back period used to calculate the indicator. This look-back period is commonly a fixed value. However, since the measured cycle period is changing, it makes sense to adapt these indicators to the measured cycle period. When tradable market cycles are observed, they tend to persist for a short while.Therefore, by tuning the indicators to the measure cycle period they are optimized for current conditions and can even have predictive characteristics.
The dominant cycle period is measured using the Autocorrelation Periodogram Algorithm. That dominant cycle dynamically sets the look-back period for the indicators. I employ my own streamlined computation for the indicators that provide smoother and easier to interpret outputs than traditional methods. Further, the indicator codes have been modified to remove the effects of spectral dilation.This basically creates a whole new set of indicators for your trading arsenal."
Included
- UI options to shut off colors and bands Indicateur
Indicateur
+ Magic Carpet BandsFun name for an indicator, eh? Well, it is true, I think; they look like magic carpets. They're actually pretty simple actually. They're Keltner Channels smoothed with a moving average. If you go down to the lookback period for the bands and set it to 1, you'll recognize them immediately.
Digging a bit deeper you see there are four magic carpets on the chart. The inner ones are set to a multiplier of 2, and the outer to a multiplier of 4. Each "carpet" is composed of two smoothed upper or lower Keltner Channels bounds, both with an optional offset, one of which is set to 13, and the other to 0 by default; and an optional color fill between these. There is also a color fill between the outer and inner carpets which gives them an interesting 3-dimensional aspect at times. They can look a bit like tunnels by default.
My thinking around the idea of using an offset with the bands is that if we assume these things to provide a dynamic support and resistance, and previous support and resistance maintains status as support and resistance until proven otherwise, then by putting an offset to past data we are creating a more obvious visual indication of that support or resistance in the present. The default offset is set to 13 bars back, so if price found resistance at some point around 13 bars ago, and price is currently revisiting it we assume it is still resistance, and that offset band is there to give us a strong visual aid. Obviously it's not foolproof, but nothing is.
Beyond that most interesting part of the indicator you have a nice selection of moving averages which the bands are calculated off of. By default it's set to my UMA. The bands themselves also have a selection of moving averages for how the keltner channels are smoothed. And a note: because the UMA and RDMA are averages of different length MAs, they can not be adjusted other than via the multiplier that sets the distance from the moving average.
The indicator is multi-timeframe, and the moving average can be colored based on a higher timeframe as well.
I popped in the divergence indicator here too. You can choose from RSI and OBV, and the divergences will be plotted on the chart. Working on finding a way to be able to have the bands/MA set to a higher timeframe while plotting the divergences on the chart timeframe, but don't have an answer to that yet.
Alerts for moving average crosses, band touches, and divergences.
I like this one a lot. Enjoy!
Pictures below.
s3.tradingview.com
One interesting thing about this indicator is that band twists often occur at areas of support or resistance. Simply drawing horizontal lines from previous twisted points can provide places from which you may look for strength or weakness to enter into a trade, or which you might use as targets for taking profits. The vertical lines are just showing the point on the chart when the cross occurred.
s3.tradingview.com
Above is a Jurik MA with a bunch of adjustments made to the bands, and the moving average itself. Everything is super adjustable, so you can play around and have fun with them quite a bit.
s3.tradingview.com
Just a different MA and bands.
s3.tradingview.com
Indicateur
Indicateur
