Kalman Trailing Stop (KTS)█ OVERVIEW
The Kalman Trailing Stop (KTS) is an advanced, math-driven trend-following system designed to keep you in winning trades longer while dynamically filtering out market noise.
Instead of relying on static moving averages or basic ATR multipliers, KTS utilizes a 2D Kalman Filter combined with Statistical Digital Signal Processing (DSP) and Williams Market Structure. It adapts to volatility and volume in real-time, effectively distinguishing between genuine trend shifts and temporary liquidity sweeps.
█ CORE MECHANICS
1. 2D Kalman Adaptive Trailing Stop
At the heart of the indicator is a robust 2D Kalman filter that tracks both price level and velocity.
Volume-Weighted Variance: The trailing stop becomes highly responsive during high-volume pushes (high trust) and flattens out during low-volume consolidation (low trust), preventing premature stop-outs.
Sigmoid Smoothing & Structural Anchoring: Instead of jagged, abrupt jumps, the stop uses sigmoid transitions to smoothly glide to new structural floors/ceilings derived from recent Intermediate-Term Highs and Lows (ITH/ITL).
Slope Confirmation: The trailing stop will only flip its directional bias if the underlying Kalman baseline slope confirms the reversal, neutralizing fake-outs.
2. Statistical Plunger Logic (Liquidity Sweeps)
Markets frequently sweep liquidity beyond technical levels before reversing. The "Plunger" logic mathematically identifies these traps.
Dynamic Sweep Multiplier: By tracking the kurtosis (fat-tail distribution) of price returns, the script dynamically expands its sweep threshold during periods of wild volatility.
Wick Filtering: It detects deep wicks that pierce the Kalman bands and close strongly back within the bar's range, highlighting statistically validated exhaustion points.
3. Algorithmic Pyramiding & Volatility Warnings
Scale-In Detection: KTS monitors volume footprints to identify safe zones to add to your position. It looks for a sequence of volume "dry-up" during a pullback, followed by a volume-backed breakout past recent market structure.
Livermore Ejector Concept: The indicator flags abnormal, massive range expansions that occur against the prevailing trend, acting as an early warning system for sudden momentum shifts.
4. Built-in Risk & Performance Engine
Dynamic Position Sizing: Automatically calculates raw position and pyramid sizes based on your account equity, risk percentage, and maximum leverage.
Live Performance Dashboard: A built-in HUD tracks both the Global and Recent Profit Factor (PF) of the main trend signals, alongside the real-time distance to your trailing stop.
█ VISUAL GUIDE
Colored Gradient Band: The main Kalman Trailing Stop. Green indicates an active long trend; Red indicates an active short trend.
Large Diamonds (♦️): Main Trend Entries. Triggered when price breaks the Kalman Stop with slope confirmation.
Small Triangles (🔼/🔽): Bullish and Bearish Plunger signals. These indicate deep liquidity sweeps and wick rejections at statistical extremes.
Small Crosses (➕): Algorithmic Pyramid signals. Opportunities to scale into the current trend based on volume dry-ups and structural breakouts.
Yellow X-Crosses (❌): Abnormal Reaction Warnings. Signals a massive volatility spike moving against your active position.
█ SETTINGS
Kalman Trailing Stop Settings
Kalman Responsiveness: Adjusts how quickly the system reacts to price changes (1-100).
Trailing Stop Distance (SD): Sets the baseline width of the trailing stop from the Kalman-smoothed price, measured in standard deviations of the True Range. A higher value (e.g., 3.0) gives the trade more breathing room, while a lower value tightens the stop.
Disclaimer
This script is designed for educational and informational purposes only. Trading involves significant risk. The built-in performance table is an un-optimized raw calculation and should not be used as a guarantee of future system profitability. インジケーター
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インジケーター
Flipped Inverted Z-Score (Subpane)Flipped Inverted Z-Score (Subpane) Indicator
What It Does
This indicator measures how far an asset's current price deviates from its long-term average, expressed as a Z-Score — a statistical measure of standard deviations from the mean.
The description "flipped inverted" means the score rises when price is above its long-term average (bullish territory) and falls when price is below it (bearish territory), making it intuitive to read at a glance.
The indicator also highlights when an asset is overheated (orange) and when the asset has cooled off significantly (blue). Oftentimes when an asset is overheated investors are taking profit, and when an asset is oversold investors are accumulating. It's important though to note that an asset can be overbought or oversold for a long period of time (or may in fact never return to prior highs or lows). The z-score highlights bright green and bright red at extreme values, further enhancing these overbought and oversold areas.
The indicator occupies a separate subpane below your main chart, so it never clutters your price action.
Core Calculations
Three values drive everything:
1-Year Moving Average (MA) — the long-term baseline representing "fair value"
Standard Deviation Proxy MA — a shorter MA used to normalize the deviation, making the score comparable across different assets and price ranges
Flipped Z-Score — computed as -(1Y MA - Price) / Std Dev MA, so positive = price above fair value, negative = price below
The Z-Score is dimensionless and asset-agnostic, meaning it works equally well on Bitcoin at $100k or a stock at $15. This normalization is the key benefit over a plain moving average crossover indicator.
Visual Elements
Z-Score Line
The main line changes color dynamically:
🟢 Lime — Strongly above threshold (bullish momentum)
🟩 Green — Mildly positive (above zero, below threshold)
🟥 Maroon — Mildly negative (below zero, above threshold)
🔴 Red — Strongly below threshold (bearish momentum)
Slow & Fast Moving Averages of the Z-Score
Two smoothed MAs are overlaid on the Z-Score line itself, helping filter noise and identify trend direction within the indicator. Both turn green above zero and red below zero.
Background Highlighting (Hot/Cold Zones)
An optional orange or blue background appears when conditions align for potentially overbought or oversold readings:
🟠 Orange background — Z-Score is elevated, above both MAs, and exceeds the hot threshold → potential overbought/overheated zone
🔵 Blue background — Z-Score is depressed, below both MAs, and exceeds the cold threshold → potential oversold/undervalued zone
Crossover Dots (Optional Alerts)
Small colored dots mark moments when the Z-Score crosses above or below the Slow MA — useful as entry/exit signal triggers or for setting TradingView alerts.
Baseline Reference Line
A horizontal line at zero marks the dividing line between price being above or below long-term fair value. (Additional lines can be added to help as references. You may find that certain assets are less volatile, and therefore deviate less from the base reference line. This difference may also occur over time for example in the case of a new asset versus a more mature asset.)
User-Configurable Settings
Setting Default — What It Controls
Price Source (Close) — Which OHLCV value drives the calculation
1-Year MA Period (365 bars) — Long-term "fair value" baseline length
Std Dev Proxy Period (150 bars) — Normalization window, shorter = more sensitive
Z-Score Deviation Threshold (±SD) (0.50) — Where the line color flips from mild to strong
Background Hot Threshold (0.34) — Minimum Z-Score to trigger orange background
Background Cold Threshold (0.40) — Minimum Z-Score depth to trigger blue background
Enable Background Highlighting (On) — Toggle hot/cold background on or off
Show Horizontal Reference Lines (On) — Toggle the zero baseline line
Show Z-Score Moving Averages (On) — Toggle the slow and fast MA lines
Slow MA Period (50 bars) — Smoothing period for the trend-following MA
Fast MA Period (3 bars) — Smoothing period for the responsive MA
Show Crossover Dots (Off) — Toggle the MA crossover signal dots
Practical Use Cases
Macro cycle positioning — on daily/weekly charts with default 365-bar settings, the score gives a birds-eye view of where an asset sits in its broader cycle, useful for sizing positions larger or smaller
Overbought/oversold screening — orange and blue backgrounds highlight historically stretched conditions worth watching for reversals
Trend confirmation — when the Z-Score, Slow MA, and Fast MA are all aligned on the same side of zero, it confirms the broader trend direction
Cross-asset comparison — because the score is normalized, you can apply identical settings to BTC, ETH, SPY, or any stock and compare readings directly
Alert triggers — crossover dots (when enabled) give discrete signal events you can attach TradingView alerts to, removing the need to watch the chart constantly
Tips for Tuning
Shorter timeframes (1H, 4H): consider reducing the 1-Year MA period and Std Dev period proportionally, and uncomment the threshold lines in the source code for finer visual guidance
More sensitive signals: lower the Fast MA period toward 1–2 and tighten the deviation threshold
Reduce noise: raise the Slow MA period and increase the hot/cold thresholds so backgrounds only appear during truly extreme readings
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VWAP TrendVWAP Trend & Daily Map Execution by erdensedat
Description:
VWAP Trend is an advanced day-trading engine and market mapping tool designed for intra-day execution using purely objective price action metrics. Instead of relying on lagging oscillators, this indicator fuses VWAP (Volume Weighted Average Price) deviations, Daily Open levels, and an automated Previous Day High/Low (PDH/PDL) targeting system.
Key Features:
Dynamic Bias Engine: The indicator measures real-time alignment between the Daily VWAP and the Daily Open price. A "BULLISH PRESSURE" signal fires when price reclaims both key metrics, while a "BEARISH PRESSURE" signal fires when price breaks below them.
Smart Time Filter: Automatically ignores high-volatility chop during the initial hours of a session (default is set to hide major text signals before 07:00 exchange time).
Automated PDH/PDL Liquidity Targets: Previous Day Highs and Lows are tracked with a "Cut-on-Touch" system. When a signal is active, these levels act as objective take-profit zones. Once touched, the level is cut, and a "TARGET REACHED" label is placed automatically.
Multi-Timeframe Macro Dashboard: An unobtrusive, dark-mode compatible panel displays the macro environment (EMA 200 Main Trend, Weekly Bias, Weekly VWAP, Daily Bias) alongside live target levels.
Clean UI & 'Only Today' Mode: Avoid chart clutter. The indicator features an "Only Today" toggle that completely erases previous days' lines, bands, and signals every day at midnight, leaving you with a perfectly clean chart for the current session.
How to Use:
Observe the Main Dashboard for Macro Alignment (Weekly Bias & EMA 200).
Wait for the designated trading hour to begin (e.g., 07:00).
Look for a Bullish / Bearish Pressure alert (indicated by clean, background-free text and arrow markers).
Target the active PDH or PDL lines shown on the chart.
Alerts:
Includes a single, unified alert condition ("VWAP Trend Signal") that dynamically pushes "Bullish Pressure" or "Bearish Pressure" notification text upon bar close.
Disclaimer:
Disclaimer: The "VWAP Trend" indicator by erdensedat is provided for educational and informational purposes only. It is not financial advice, and you should not construct it as such. Trading in financial markets (including cryptocurrencies, forex, and equities) involves a significant risk of loss and is not suitable for all investors. Past performance of any trading system or methodology is not necessarily indicative of future results. Always conduct your own research and manage your risk. インジケーター
Daily Return Z-Score / OutlierDaily Return Z-Score / Outlier
What this indicator does
Daily Return Z-Score / Outlier measures how unusual today's daily return is relative to the instrument's own historical return distribution. It converts the current return into a Z-Score (standard-deviation scale) and colours the bars according to whether the return sits in the normal range, a warning zone, or an extreme zone (fat-tail event).
The goal is to make statistical outliers visible — days on which the price move is materially larger than the recent history would suggest.
How it works
Data basis (daily context): Daily returns are sampled on the daily timeframe ("D") via request.security, independent of the chart timeframe currently displayed. This keeps the statistical reference consistent.
Return calculation: Either simple percentage returns (close − close ) / close or log returns ln(close / close ).
Distribution statistics over a rolling window (default: 252 trading days ≈ 1 year). Two methods are available:
MAD (robust): Median and median absolute deviation. Insensitive to individual extreme values. The Z-Score is computed as 0.6745 · (return − median) / MAD (scaled to the normal distribution).
Classic: Mean and standard deviation. Z = (return − mean) / stdev. More reactive to, and distorted by, extreme values.
Empirical percentiles: In addition to the Z-Score, warning and extreme thresholds are derived directly from the observed percentiles of the return distribution (e.g. 5% / 95% for warning, 1% / 99% for extreme). Bar colour follows these empirical percentiles rather than normality assumptions.
Live return: The running return is computed against yesterday's daily close, so the classification updates intraday as the current day develops.
Display
Histogram of the Z-Score on a common sigma scale.
Reference lines at 0, ±1, ±2 and ±3 sigma for visual orientation.
Live label showing the current Z-Score on the last bar.
Values table (optional, bottom-right) with Z-Score, band classification, selected method, today's return, the dispersion measure (MAD or stdev), warning/extreme thresholds, and the effective sample size.
Colour logic
Normal — return within the warning percentiles.
Warn + / − — return beyond the warning percentile.
EXTREME + / − — return beyond the extreme percentile (fat tail).
Settings
Method: MAD (robust) or Classic (mean/stdev).
Lookback (days): Length of the statistics window (5–1000).
Log returns: Log instead of percentage returns.
Warning percentile % and Extreme percentile %: Colouring thresholds.
Colours for bullish/bearish warning and extreme zones.
Show values table.
Alerts
Extreme outlier UP — daily return beyond the upper extreme percentile.
Extreme outlier DOWN — daily return beyond the lower extreme percentile.
Extreme outlier (both directions) — combined condition.
How to use it
The indicator helps highlight days with a statistically notable move — for example to add context to news days, to watch for volatility clustering, or as a filter alongside an existing strategy. The MAD method is recommended when the history contains isolated strong outliers.
Notes
A Z-Score measures how unusual a move is, not its direction as a forecast.
Significance depends on a sufficiently large sample (see the "Sample" field in the table).
This script is an analysis tool and does not constitute financial advice. Past distributions are no guarantee of future behaviour.
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Daily Return Z-Score / Outlier — Deutsch
Was macht dieser Indikator?
Daily Return Z-Score / Outlier misst, wie ungewöhnlich der heutige Tages-Return im Vergleich zur eigenen historischen Verteilung des Wertpapiers ist. Der Indikator wandelt den aktuellen Return in einen Z-Score (Standardabweichungs-Skala) um und färbt die Balken danach ein, ob sich der Return im normalen Bereich, in einer Warn-Zone oder in einer Extrem-Zone (Fat-Tail-Ereignis) befindet.
Ziel ist es, statistische Ausreisser sichtbar zu machen — also Tage, an denen die Kursbewegung deutlich grösser ausfällt, als es die jüngste Historie nahelegt.
Wie es funktioniert
Datenbasis (Daily-Kontext): Über request.security werden die Tages-Returns auf dem Tages-Timeframe ("D") erhoben, unabhängig vom aktuell angezeigten Chart-Timeframe. So bleibt der statistische Bezug konsistent.
Return-Berechnung: Wahlweise einfache prozentuale Returns (close − close ) / close oder Log-Returns ln(close / close ).
Verteilungsstatistik über ein rollierendes Fenster (Standard: 252 Handelstage ≈ 1 Jahr). Zwei Methoden stehen zur Wahl:
MAD (robust): Median und Median-Absolutabweichung. Unempfindlich gegen einzelne Extremwerte. Der Z-Score wird als 0.6745 · (Return − Median) / MAD berechnet (skaliert auf die Normalverteilung).
Klassisch: Mittelwert und Standardabweichung. Z = (Return − Mean) / Stdev. Reagiert stärker auf Extremwerte und wird von diesen verzerrt.
Empirische Perzentile: Zusätzlich zum Z-Score werden Warn- und Extrem-Schwellen direkt aus den beobachteten Perzentilen der Return-Verteilung gebildet (z. B. 5% / 95% für Warnung, 1% / 99% für Extrem). Die Balkenfarbe richtet sich nach diesen empirischen Perzentilen, nicht nach Normalverteilungs-Annahmen.
Live-Return: Der laufende Return wird gegen den gestrigen Tages-Schluss berechnet, sodass die Einordnung schon während des laufenden Tages aktualisiert wird.
Anzeige
Histogramm des Z-Scores auf einer gemeinsamen Sigma-Skala.
Referenzlinien bei 0, ±1, ±2 und ±3 Sigma zur visuellen Orientierung.
Live-Label mit dem aktuellen Z-Score am letzten Balken.
Werte-Tabelle (optional, unten rechts) mit Z-Score, Band-Einstufung, gewählter Methode, heutigem Return, Streuungsmass (MAD bzw. Stdev), Warn-/Extrem-Schwellen sowie der effektiven Stichprobengrösse.
Farb-Logik
Normal — Return innerhalb der Warn-Perzentile.
Warn + / − — Return jenseits des Warn-Perzentils.
EXTREM + / − — Return jenseits des Extrem-Perzentils (Fat Tail).
Einstellungen
Methode: MAD (robust) oder Klassisch (mean/stdev).
Lookback (Tage): Länge des Statistik-Fensters (5–1000).
Log-Returns: Log- statt prozentuale Returns.
Warn-Perzentil % und Extrem-Perzentil %: Schwellen für die Färbung.
Farben für bullische/bärische Warn- und Extrem-Zonen.
Werte-Tabelle anzeigen.
Alerts
Extrem-Ausreisser HOCH — Tagesreturn jenseits des oberen Extrem-Perzentils.
Extrem-Ausreisser RUNTER — Tagesreturn jenseits des unteren Extrem-Perzentils.
Extrem-Ausreisser (beide Richtungen) — kombinierte Bedingung.
Verwendung
Der Indikator eignet sich, um Tage mit statistisch auffälliger Bewegung hervorzuheben — etwa zur Kontext-Einordnung von News-Tagen, zur Beobachtung von Volatilitäts-Clustern oder als Filter neben einer bestehenden Strategie. Die MAD-Methode wird empfohlen, wenn die Historie einzelne starke Ausreisser enthält.
Hinweise
Ein Z-Score misst die Ungewöhnlichkeit einer Bewegung, nicht deren Richtung im Sinne einer Prognose.
Die Aussagekraft hängt von einer ausreichend grossen Stichprobe ab (siehe Feld "Sample" in der Tabelle).
Dieses Skript ist ein Analyse-Werkzeug und stellt keine Anlageberatung dar. Vergangene Verteilungen sind keine Garantie für zukünftiges Verhalten.
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Equilibrium Deviation Engine [LB]
Concept
The Equilibrium Deviation Engine is a session-resetting, volume-weighted equilibrium model that builds a dynamic fair value basis from accumulated price and volume since the last anchor point (daily by default). Around this basis, it constructs multiple deviation bands and an independent extreme contrarian channel whose width varies inversely with short-term volatility — expanding during quiet markets and contracting during turbulent ones.
Mathematical Foundation
At each new session (e.g., daily open), the engine resets three accumulators and recalculates them bar by bar :
PV = SUM(Price * Volume)
V = SUM(Volume)
P2V = SUM(Price^2 * Volume)
The equilibrium basis is the volume-weighted average price since reset :
Basis = PV / V
The standard deviation of price around this basis is derived from the variance :
Var = max( (P2V / V) - Basis^2 , 0 )
Dev = sqrt(Var)
Three main bands are then computed by applying adaptive multipliers to this deviation. The adaptation uses two independent weights :
TWAP Weight — compares the basis to a hidden TWAP. The larger the gap relative to the deviation, the more the bands widen, capturing potential mean-reversion targets.
HV Weight — compares current historical volatility (HV) to its own smoothed baseline. When HV expands, bands widen ; when HV contracts, bands narrow.
The final band width for level k is :
D_k = Dev * Mult_k * TWAP_Weight * HV_Weight
The Extreme Contrarian Channel
A separate channel is built using an inverse volatility weight. Instead of expanding with rising HV, it contracts :
InvWeight = clamp( 1 / (HV_contrarian / HV_contrarian_baseline) , min, max )
This creates a structural envelope that is widest during low-volatility regimes (where price tends to range) and tightens during high-volatility regimes (where price breaks through normal boundaries). The inner and outer levels use user-defined sigma multipliers.
What Problem Does It Solve ?
Traditional deviation bands (Bollinger, Keltner, VWAP bands) use fixed lookback windows and a single volatility metric. They do not reset at session boundaries, nor do they distinguish between different volatility regimes for mean-reversion versus breakout scenarios. The Equilibrium Deviation Engine solves this by :
- Resetting accumulators at each session (e.g., daily), producing a true volume-weighted equilibrium for the current period.
- Adapting band width to both the TWAP gap (directional drift) and HV regime (market excitement).
- Adding a separate contrarian channel using inverse volatility, specifically designed to identify exhaustion zones where low volatility precedes expansion, or where extreme HV signals climax conditions.
How To Interpret
Basis line (white) — the real-time volume-weighted fair value for the current session. Price above basis signals session bullishness ; price below signals session bearishness.
Deviation bands 1, 2, 3 — graduated zones of overextension from the basis. Price reaching Band 3 represents an extreme statistical deviation from the session's equilibrium, often preceding reversion.
Extreme contrarian channel — a separate envelope that behaves inversely to short-term HV. When this channel is wide (low HV, quiet market), price tends to oscillate within it, making the boundaries attractive mean-reversion levels. When the channel narrows sharply (high HV, excited market), it signals compression before a potential breakout.
Band expansion vs contraction — widening bands indicate increasing dispersion and adaptive uncertainty ; narrowing bands indicate consolidation and equilibrium tightening.
Parameters
LB Engine
Source — price field used for calculations (default HLC3).
Reset TF — timeframe at which accumulators reset (default Daily).
Hidden TWAP Length — period for the TWAP used in the TWAP gap weight.
Historical Volatility Length — period for HV calculation (main bands).
HV Smoothing — smoothing period for the HV baseline.
LB Bands
Deviation 1, 2, 3 — base multipliers for the three main deviation levels.
LB Contrarian Channel
Extreme Channel Inner/Outer — sigma multipliers for the contrarian channel.
Use Main HV Weight — applies the main HV weight to the contrarian channel.
Use Hidden TWAP Weight — applies the TWAP gap weight to the contrarian channel.
Contrarian Inverse HV Length — period for the HV used in the inverse weighting.
Contrarian Inverse HV Smooth — smoothing period for the contrarian HV baseline.
Contrarian Inverse HV Min/Max — clamping limits for the inverse weight.
LB Style
Show Basis, Show Main Fills, Color Bars — visual toggles.
Basis Width, Band Width, Extreme Channel Width — line thickness controls.
Reference
This indicator is a proprietary design by Luis Barlier. It synthesises concepts from session volume-weighted average price (VWAP), adaptive volatility bands, and inverse volatility regime detection. It does not correspond to a single academic publication. インジケーター
Z-Score Source MonitorZ-Score Source Monitor
What this script does:
Z-Score Source Monitor calculates a rolling Z-Score on any external indicator line connected via the source input. It answers one question: how statistically extreme is the current reading of any oscillating indicator relative to its recent history?
A Z-Score of 0 means the source is exactly at its rolling mean. A reading of ±1 is within normal range. A reading beyond ±2 occurs roughly 5% of the time statistically, and beyond ±3 less than 1% of the time. These are the levels where statistical exhaustion tends to occur.
What makes this script original:
Most Z-Score indicators on TradingView calculate the Z-Score on price. This script is built around a generic input.source — meaning it can calculate the Z-Score on any indicator plot, not just price. This makes it a universal statistical layer that can be placed on top of momentum oscillators, volume indicators, custom signals, or any other plotted line.
The volatility calculation uses EWMA (Exponentially Weighted Moving Average) variance rather than a fixed rolling standard deviation. This means the script adapts faster to changes in the statistical behavior of the source, without waiting for the full lookback window to shift. In fast-moving or regime-changing markets this produces a more responsive and accurate measure of statistical extension.
How to use it:
Connect any external indicator plot to the Source input. The script will calculate and display:
Smoothed Z-Score as histogram and line, color-coded by zone
Raw Z-Score as a reference behind the smoothed line
Reference lines at ±1σ, ±2σ and ±3σ
Dashboard showing current Z-Score, zone classification, direction and raw Z value
The example chart uses the Fast Line from Bjorgum's TSI indicator as the source input, demonstrating how the Z-Score identifies statistical extremes on a momentum oscillator.
Settings
Source: connect any external indicator plot
Lookback: number of bars for the rolling mean (default 20)
EWMA Half-Life: controls how quickly the volatility measure adapts to recent behavior (default 15)
Z-Score Smoothing: EMA smoothing applied to the raw Z-Score to reduce noise (default 3)
How to read the zones :
Gray: neutral, source near its mean
Light blue / light orange: mild extension beyond ±1σ
Blue / red: statistically extended beyond ±2σ — observe closely
Dark blue / dark red: rare extreme beyond ±3σ
Important note:
This script is an observation tool. It identifies statistical extremes but does not generate buy or sell signals. Always use it as additional context alongside your own analysis. Past statistical extremes do not guarantee future reversals. インジケーター
V-AEMA VMR [LB]Concept
The V-AEMA VMR (Volume-Adaptive Exponential Moving Average with Volatility-Modulated Regime) is a hybrid trend-following indicator that combines an EMA baseline with a volatility-based drift component. It produces a dynamic core line whose colour reflects the trend regime, surrounded by two levels of adaptive bands that expand or contract based on volume intensity. The indicator generates directional entry signals when price breaks the first band in the direction of the trend, and projects take-profit zones when price fully exits both bands.
Mathematical Foundation
The core line (Hybrid Line) is a weighted blend of a standard EMA and a volatility-shifted version of that same EMA :
HybridLine = EMA * W + (EMA + Drift) * (1 - W)
where the drift is derived from the Z-Score of price relative to the EMA, scaled by ATR :
Drift = Z_Score * ATR * 0.35
Z_Score = (Price - EMA) / StdDev(Price, L_vola)
Band width starts from a base volatility measure combining standard deviation and ATR :
BaseWidth = StdDev * 0.65 + ATR * 0.35
This base is then adjusted by a volume ratio and user-defined multipliers :
UpperWidth = BaseWidth * (BaseUpMult + (VolRatio - 1) * VolImpactUp)
LowerWidth = BaseWidth * (BaseDnMult + (VolRatio - 1) * VolImpactDn)
where VolRatio = min(max(Volume / SMA(Volume, L_vol), 0.35), 2.50) .
Two band levels are generated : Band 1 at HybridLine +/- Width, and Band 2 (extreme) at HybridLine +/- Width * 1.55 (upper) / 1.40 (lower).
What Problem Does It Solve ?
Conventional envelope indicators (Bollinger Bands, Keltner Channels) apply fixed multipliers to a single volatility metric and ignore volume dynamics. The V-AEMA VMR adapts its band width to both volatility and volume surges, producing wider bands during high-participation moves and narrower bands during quiet periods. The hybrid core line reduces pure EMA lag by incorporating a volatility offset, while the dual-band structure filters signals by strength : a break of Band 1 triggers an entry, while a break of Band 2 confirms an explosive move and projects a take-profit zone.
How To Interpret
Core line colour – cyan/green indicates the hybrid line is rising (bull regime) ; magenta/red indicates it is falling (bear regime).
Cloud and bands – the area between Band 1 and Band 2 forms a halo that thickens when volume expands. Narrow bands suggest low conviction or consolidation.
Entry signals – a triangle appears below the bar when price crosses above Upper Band 1 while the hybrid line is rising (long). A triangle appears above the bar when price crosses below Lower Band 1 while the hybrid line is falling (short). These signals are confirmed by the trend direction.
Take-profit zones – when the entire bar (high and low for shorts, low and high for longs) clears the extreme band (Band 2) in the direction of the signal, a coloured box is projected forward. The box represents a potential target zone based on the breakout amplitude and ATR, scaled by the TP Factor.
Info panel – displays the current regime (BULL/BEAR), the volume ratio (values above 1.0 indicate above-average participation), and the current upper/lower deviation values in price units.
Parameters
EMA Length – period of the base exponential moving average (default 55).
Volatility Length – period for the standard deviation used in the Z-Score calculation (default 34).
Volume Length – period for the volume moving average used in the volume ratio (default 34).
EMA Weight – blend ratio between the pure EMA and the volatility-drifted version. Higher values produce a smoother line ; lower values make it more reactive to volatility (default 0.80).
Upper Base Deviation – core multiplier for the upper band width before volume adjustment (default 1.55).
Lower Base Deviation – core multiplier for the lower band width before volume adjustment (default 1.05).
Volume Impact Upper/Lower – sensitivity of the upper and lower bands to the volume ratio. Higher values make bands expand more aggressively when volume surges (default 0.95 / 0.55).
ATR Length – period of the Average True Range used in band width and TP zone calculations (default 14).
Show Cloud – toggles the filled areas between bands.
Show Info Panel – toggles the real-time dashboard.
Show Signals – toggles the entry triangles.
Show TP Zones – toggles the take-profit projection boxes.
TP Projection Bars – how many bars forward the TP zone extends.
TP Factor – scales the height of the TP zone relative to the breakout range.
Max Historical TP Zones – limits the number of TP boxes kept on the chart.
Reference
This indicator is a proprietary design synthesising concepts from adaptive moving averages (Kaufman, Ehlers), volatility envelopes (Bollinger, Keltner), and volume-weighted band models. It does not correspond to a single academic publication. インジケーター
Bollinger Band [scoopup]Overview
A Bollinger Bands–based indicator that shows trend direction (up/down) through the basis line color, displays band width (volatility) as a percentage, and marks the most recent meaningful lows (demand zones) on the weekly and daily timeframes as boxes. It lets you view statistical volatility and the real low zones where buying previously stepped in — all on a single chart.
Default settings are Length 21 and StdDev 1.618, based on the Fibonacci number (21) and the golden ratio (1.618).
Components
1. Bollinger Bands (Upper / Basis / Lower)
Defaults: Length 21, StdDev 1.618
Upper band, basis (middle), and lower band. The bands widen and narrow with volatility.
2. Basis Line Trend Color (Daily-based)
The color of the middle basis line indicates trend direction.
Logic: over a set lookback, it compares the cumulative size of the "close-to-lower" area (red) versus the "upper-to-close" area (green).
Red area dominant → uptrend → basis line GREEN
Green area dominant → downtrend → basis line RED
The longer the close stays near the lower band (larger red area), the more it is read as base-building before a move higher.
This color is always calculated from Daily data, regardless of the chart timeframe. Whether you view it on the 15m, 1h, or 4h chart, the daily trend color stays consistent.
3. Fill
Upper band ↔ close: semi-transparent green
Close ↔ lower band: semi-transparent red
Lets you quickly read where the close sits within the bands.
4. Band Width (%)
Formula: (Upper − Lower) / Basis × 100
Displays the current band width in a corner table as Band Width: X.XX%.
Lower = volatility contraction (squeeze) → often precedes a large move; higher = volatility expansion.
The Data Window also shows band width % and band width (price difference), including on historical bars.
5. Recent Lows
Weekly recent low = yellow box / Daily recent low = red box
Shows only the most recent pivot (swing) low that sits below the current close. (Lows above the close are skipped; if the latest low is above the close, the prior low is used instead.)
Box height spans the low ↔ the close at that point, and extends to the right to show a still-valid support/demand zone.
How to Read It
Basis green + close near the lower band → watch for a potential bounce after base-building.
Basis red + close near the upper band → watch for overextension/pullback risk.
Band Width % contracting (squeeze) → watch for an upcoming volatility expansion.
Recent low boxes (yellow/red) act as first support candidates on a pullback. A close below the box signals support failure.
Key Settings
Bollinger Bands: Source, Length (default 21), StdDev (default 1.618), Band Color / Width / Style
Basis Line: Show Basis, Basis Width, Ratio Length, Up / Down Color
Fill: Show Fill, Upper / Lower Fill Transparency
Band Width: Show Band Width %, Table Position, Text Size
Recent Lows: weekly/daily toggles, Pivot Length, Box Color
Tips
This is a supporting tool for reading trend direction + volatility + support zones together, not a standalone trade signal.
Reliability increases when the daily trend color and a recent low box line up in the same area.
Adjust StdDev and Ratio Length to fit each instrument's volatility.
Disclaimer
This indicator is for reference only and does not guarantee trading profits. All trading decisions and responsibility rest solely with the user. インジケーター
Intermarket Flow OscillatorAdvanced Macro Regime Tracking & Apex Reversal Detection
What is the Intermarket Flow Oscillator (IFO)?
The Intermarket Flow Oscillator (IFO) is a quantitative momentum tool designed to track capital rotation between risk-on assets (growth, equities) and risk-off assets (defensives, bonds, safe havens). By utilizing advanced statistical normalization and John Ehlers' digital signal processing, the IFO visualizes structural market regimes and pinpoints high-probability exhaustion reversals.
Whether you are trading swing setups on the daily chart or monitoring intraday capital flows, the IFO acts as a macro compass to keep you on the right side of institutional money.
The Mathematical Engine
Traditional spread indicators suffer from noise and asymmetric scaling. The IFO solves this using a two-step quantitative process:
Z-Score Normalization: The script calculates the natural log ratio of a Risk Asset versus a Safe Haven asset, then applies a rolling Z-Score. This transforms the intermarket spread into a stationary stochastic process, making standard deviation thresholds mathematically reliable.
John Ehlers' 2-Pole SuperSmoother: To eliminate high-frequency market noise without introducing the severe phase lag typical of moving averages, the Z-Score is passed through an advanced DSP filter.
How to Read the Signals
Trend Shifts & Structural Regimes (The Zero-Line)
The smoothed oscillator crossing the zero equilibrium line indicates a macro shift in capital allocation.
Green Cloud (IFO > 0): Structural Risk-On Regime. Institutions are accumulating risk/growth. Traders should look for long momentum setups and favor high-beta assets.
Red Cloud (IFO < 0): Structural Risk-Off Regime. Capital is fleeing to safety. Traders should focus on cash preservation, defensive value, or short setups.
Apex Mean-Reversion Turns (▲ and ▼)
The script calculates the first derivative (Velocity) of the smoothed capital flow. When the oscillator reaches extreme statistical exhaustion thresholds (default ±1.5 standard deviations) and the velocity flips, the IFO prints a high-contrast triangle.
Bullish Apex (▲): Occurs deep in negative territory (panic/capitulation). Represents a mathematically optimal exhaustion point where selling pressure is dying. Excellent for buying the bottom in growth stocks.
Bearish Apex (▼): Occurs high in positive territory (euphoria). Represents exhaustion in risk-taking and serves as an early warning to take profits or look for short entries.
Practical Trading Application: Sector Rotation (XLK vs. XLP)
While the default script pairs S&P 500 Futures (ES) against 10-Year Treasuries (ZN), the true power of the IFO shines in sector rotation.
The Setup: Set the Risk Asset to XLK (Technology) and the Safe Haven to XLP (Consumer Staples).
The Logic: XLK represents high-beta, duration-sensitive growth (Apple, Microsoft, Nvidia). XLP represents inelastic consumer demand (Procter & Gamble, Walmart). This spread is the ultimate risk-on/risk-off gauge.
Key Features & Customization
Customizable Pairs: Fully adjustable inputs to test different macro pairs (e.g., BTC vs. Gold, BTCUSDT.P vs. USDT, Discretionary vs. Utilities, High Yield Bonds vs. Treasuries).
Dynamic Coloring: The oscillator line shifts between bright/faded colors based on momentum velocity, giving you a visual cue before a crossover even happens.
インジケーター
Median ATR SD OscillatorMedian ATR SD Oscillator
Median ATR SD Oscillator is a trend-following volatility oscillator that measures the distance between price and two independent reference levels — an ATR band and a standard deviation band — both anchored to a percentile-based median. The asymmetric design uses different volatility measures for long and short signals, creating a natural bias toward staying in bullish trends longer while reacting quickly to breakdowns.
The result is an area oscillator that expands above zero in a confirmed bullish state and contracts below zero in a bearish state, with a white EMA line as a momentum confluence filter.
How It Works
A percentile median is calculated from a configurable price source — giving a robust, noise-resistant central reference level that adapts to recent price behavior.
Two independent volatility bands are then derived from this median:
ATR Band — median plus ATR multiplied by a configurable factor. The short condition uses the ATR band — price must fall below it to confirm a bearish state
SD Band — median plus the standard deviation of close. The long condition uses the standard deviation band — price must break above it to confirm a bullish state
Once a directional state is confirmed, the oscillator measures the distance between price and its reference level. An EMA of this distance acts as a confluence filter — the final signal only confirms when the distance is not only positive or negative but also above or below its own EMA, ensuring momentum is genuinely building in that direction.
Why This Approach Works
Most oscillators use a single volatility measure for both long and short signals. The Median ATR SD Oscillator deliberately uses two different measures — ATR for shorts and SD for longs — because they capture different market dynamics and create a natural asymmetry between entries and exits.
This asymmetric design reflects the structural reality of markets like crypto — price spends more time trending upward than downward. Longs require a statistically significant breakout above the SD band, while shorts only need price to fall back below the ATR band. The result is a system that stays in bullish trends longer while reacting quickly when momentum fades.
Settings
Median Source — Price source for the percentile median calculation (default: hl2)
Median Length — Lookback period for the percentile median (default: 63)
ATR Length — Lookback period for the ATR calculation (default: 4)
ATR Factor — Controls the width of the ATR band (default: 1.0)
SD Length — Lookback period for the standard deviation calculation (default: 29)
Use EMA — Enables the EMA confluence filter (default: true)
EMA Length — Lookback period for the EMA confluence filter (default: 35)
Use Bar Coloring — Colors bars based on the current state (default: true)
Color Background — Enables background coloring of the chart based on the current state (default: false)
Background Transparency — Controls the transparency of the background color (default: 85)
How to trade it
Long — when the oscillator expands above zero and the area turns blue, a bullish state has been confirmed. This is the signal to look for long entries or to hold existing long positions
Short / Cash — when the oscillator contracts below zero and the area turns red, the momentum has faded. This is the signal to exit longs, move to cash, or look for short entries depending on your strategy
EMA line — when the area is above the white EMA line momentum is building, when it crosses below momentum is weakening
Recommended Usage
Best used on the 1D timeframe for clean and reliable signal generation
Should not be used alone for trade entries — combine with an additional confirmation indicator for best results
The asymmetric ATR/SD design makes this oscillator particularly well suited for bullish-biased markets like crypto
Higher ATR Factor values make short exits more sensitive — lower values make them less reactive
Higher SD Length values create more stable long signals — lower values make them more reactive to short-term price movements
All signals are confirmed on bar close. インジケーター
Miner Profitability Index | Astral Vision Miner Profitability Index | Astral Vision 🌠💠
This indicator constructs a measure of Bitcoin miner profitability per unit of mining difficulty, then applies Z-Score normalization in log space to quantify how statistically extreme current profitability conditions are relative to their own history. Miner profitability is a structurally important on-chain signal because miners are one of the few participants with predictable and measurable cost structures: when profitability collapses, miners are forced to sell reserves to cover operational costs, creating persistent sell pressure; when profitability is exceptionally high, miners tend to accumulate and expand capacity, which historically precedes periods of increased hash rate and eventually difficulty adjustment that compresses margins back toward equilibrium.
Calculation ⚙️
The daily miner revenue in USD is computed from three components: the number of blocks mined that day (computed as the difference between consecutive daily block height readings from Glassnode), the block subsidy in BTC (derived from the block height using the halving schedule: 50 BTC before block 210,000, halving at each subsequent 210,000-block interval), and the current Bitcoin price in USD. The formula is: miner revenue = blocks per day × block reward × BTC price.
This revenue figure is then divided by the current mining difficulty to produce the efficiency ratio: miner revenue / difficulty. Difficulty represents the computational work required to mine a block and serves as a proxy for the aggregate energy and capital expenditure of the mining network. Dividing revenue by difficulty produces a measure of how many dollars miners earn per unit of computational difficulty, normalizing for the expanding size of the mining network over time. Without this normalization, absolute revenue would grow indefinitely simply due to price appreciation and hash rate expansion, making historical comparisons meaningless.
The efficiency ratio is smoothed with a configurable EMA to reduce the noise introduced by day-to-day variation in block count. The natural logarithm is then taken before applying the Z-Score, which is necessary because the efficiency ratio follows an approximately log-normal distribution: in raw space it would be heavily right-skewed, making the standard deviation an unreliable measure of typical deviation. In log space the distribution is much more symmetric and the Z-Score thresholds carry consistent statistical meaning across all periods.
The Z-Score is computed as: (log(efficiency) - SMA(log(efficiency), N)) / StDev(log(efficiency), N), where N is the configurable lookback window. This expresses how many standard deviations the current log-efficiency sits above or below its rolling historical mean. Two pairs of thresholds define moderate and severe extreme zones on each side.
Plots 📊
Z-Score oscillator colored by zone: two upper levels and two lower levels with graduated opacity
Two upper and two lower threshold lines
Zero midline
Fill highlights when Z-Score is beyond the outer thresholds
Static zone fills between inner and outer thresholds on both sides
Background color on the price chart with four gradient levels reflecting zone severity
Inputs 🎛️
Z-Score Lookback: rolling window for mean and standard deviation normalization
Smoothing: EMA period applied to the raw efficiency ratio before log transformation
Upper Z 1 and Upper Z 2: configurable inner and outer upper threshold levels
Lower Z 1 and Lower Z 2: configurable inner and outer lower threshold levels
Colors 🎨
5 Astral Vision presets + custom override. Default: Futura.
Purpose 🎯
Standard miner revenue charts display absolute USD earnings, which grow indefinitely with price and provide no statistical context for whether current conditions are extreme or normal. Dividing by difficulty removes the network size effect, and normalizing with a Z-Score in log space makes readings directly comparable across all market cycles including early periods when absolute revenue was tiny. The dual threshold system separates mild deviations from statistically severe conditions, providing a more granular signal than a single overbought/oversold level.
Disclaimer ⭕️
This indicator is for informational and educational purposes only. It does not constitute financial advice. Past performance is not indicative of future results. Always do your own research before making investment decisions. インジケーター
Whale Accumulation Index | Astral Vision Whale Accumulation Index | Astral Vision 🌠💠
This indicator tracks the proportion of Bitcoin's total on-chain transaction volume attributable to large transactions, using CoinMetrics data to separate whale-scale activity from retail-scale activity, then applies two different analytical lenses to that ratio to identify when large holders are accumulating or distributing at statistically unusual rates.
Calculation ⚙️
The base input is the ratio of large transaction volume to total transaction volume in USD, both fetched from CoinMetrics on a daily timeframe. Large transaction volume measures the aggregate USD value of all on-chain transactions above a defined size threshold, while total transaction volume covers all on-chain activity. Dividing the two produces a ratio between 0 and 1 that measures what fraction of all Bitcoin moved on-chain each day was moved by large participants. A rising ratio means whale activity is growing as a share of total network flow; a falling ratio means retail activity is proportionally dominant. This ratio is smoothed with a configurable SMA before all subsequent calculations.
The indicator offers two modes that address different analytical questions.
Z-Score mode normalizes the smoothed ratio against its own rolling mean and standard deviation over a configurable lookback window. The formula is: Z = (ratio - mean(ratio, N)) / stdev(ratio, N). This produces a reading that measures how statistically unusual the current whale dominance level is relative to its own history. A positive Z-Score means whale share of volume is elevated above its historical norm; a negative Z-Score means it is depressed. The thresholds mark the statistically extreme zones where readings have historically been rare.
Conviction mode computes a divergence signal between whale momentum and price momentum. For each series, the rate of change over a configurable lookback is computed as (current - past) / abs(past), producing a proportional momentum measure. Both the price ROC and the whale ratio ROC are then independently Z-Score normalized, and the conviction signal is the difference: whale Z-Score minus price Z-Score. A positive conviction reading means whale activity is accelerating faster than price, historically associated with accumulation ahead of price moves. A negative reading means price is running ahead of whale activity, historically associated with distribution or weak institutional participation in the current price move.
Plots 📊
Main oscillator in Z-Score or Conviction mode, colored by threshold zone
Overbought and oversold threshold lines
Fill highlight when oscillator enters either extreme zone
Background color on the price chart when oscillator is in extreme zones
Inputs 🎛️
Mode: Z-Score or Conviction
OB Threshold Z-Score and Conviction: configurable upper extreme levels per mode
OS Threshold Z-Score and Conviction: configurable lower extreme levels per mode
Z-Score Window: normalization lookback for both modes
Smoothing: SMA period applied to the raw whale ratio before calculations
Conviction ROC Length: lookback for the rate of change in Conviction mode
Colors 🎨
5 Astral Vision presets + custom override. Default: Inferno.
Purpose 🎯
Standard volume indicators measure total on-chain or exchange volume without distinguishing between the size of individual transactions, treating a single $100 million transfer the same as ten thousand $10,000 transfers in aggregate volume terms. This indicator isolates the large-transaction component specifically, making it possible to detect when whale-scale capital is disproportionately active on-chain relative to its historical baseline. The Conviction mode adds a second dimension by measuring whether whale activity is leading or lagging price, separating periods where large holders are front-running price moves from periods where they are simply responding to them.
Disclaimer ⭕️
This indicator is for informational and educational purposes only. It does not constitute financial advice. Past performance is not indicative of future results. Always do your own research before making investment decisions. インジケーター
OTHERS/USDT.D Z-Score | Astral Vision OTHERS/USDT.D Z-Score | Astral Vision 🌠💠
This indicator constructs a ratio between the OTHERS market cap dominance and USDT dominance, then applies Z-Score normalization in log space to measure how statistically extreme the current positioning of altcoin capital relative to stablecoin dry powder is compared to its own history.
OTHERS dominance tracks the combined market cap share of all cryptocurrencies excluding Bitcoin, Ethereum, and the top few large caps, making it a direct proxy for altcoin season conditions. USDT dominance measures the share of total crypto market cap held in Tether, which rises when capital exits risk assets into stablecoins and falls when stablecoin capital is deployed into crypto assets.
Calculation ⚙️
The ratio is computed as OTHERS dominance divided by USDT dominance on a daily timeframe. A high ratio means altcoin capital is large relative to stablecoin reserves, indicating that available dry powder has been deployed and the altcoin market is extended. A low ratio means stablecoin dominance is high relative to altcoin exposure, indicating that capital has retreated to safety and dry powder is accumulating.
The natural logarithm of this ratio is then taken before all subsequent calculations. Working in log space normalizes the exponential growth of both series across different market cycles, ensuring that a ratio change from 2 to 4 is treated as equivalent in magnitude to a change from 4 to 8, which is the correct treatment for proportional dominance relationships.
A simple moving average and standard deviation are computed over the configurable Z-Score lookback window, producing the Z-Score as: (log ratio minus mean) / standard deviation. This expresses the current ratio in units of standard deviations above or below its own historical average, making readings directly comparable across cycles regardless of the absolute dominance levels involved.
In Trend mode, an EMA of configurable length is applied to the Z-Score itself, functioning as a signal line. When the Z-Score is above its EMA, the momentum of the ratio is positive and altcoin conditions are improving relative to stablecoin reserves; when below, the momentum is negative.
Plots 📊
Z-Score oscillator colored by mode and regime
Two upper threshold lines marking statistically elevated altcoin exposure (Extremes mode)
Two lower threshold lines marking statistically depressed altcoin exposure (Extremes mode)
Fill highlights when Z-Score enters the outer extreme zones
Zero baseline
EMA signal line (Trend mode)
Background color on the price chart when Z-Score enters the outer extreme zones (Extremes mode)
Candle coloring on the price chart reflecting current regime in both modes
Inputs 🎛️
Visualization: Extremes or Trend
Z-Score Lookback: normalization window for mean and standard deviation
Upper Z 1 and Upper Z 2: configurable inner and outer upper threshold levels
Lower Z 1 and Lower Z 2: configurable inner and outer lower threshold levels
EMA Length: smoothing period for the trend signal line (Trend mode)
Colors 🎨
5 Astral Vision presets + custom override. Default: Futura.
Purpose 🎯
Standard altcoin season indicators use fixed dominance thresholds or simple moving average crossovers on raw dominance values, which are not statistically normalized and behave differently across cycles as the total crypto market cap grows. This indicator normalizes the ratio in log space over a long rolling window, making a Z-Score of +2.0 in 2021 and a Z-Score of +2.0 in 2024 carry equivalent statistical weight despite the absolute dominance percentages being different. The dual threshold system further separates moderate elevated conditions from statistically severe ones, allowing a more nuanced reading than a single overbought/oversold line can provide.
Disclaimer ⭕️
This indicator is for informational and educational purposes only. It does not constitute financial advice. Past performance is not indicative of future results. Always do your own research before making investment decisions. インジケーター
Bitcoin vs VUG/VTV Rolling Ratio Analysis | Astral Vision Bitcoin vs VUG/VTV Rolling Ratio Analysis | Astral Vision 🌠💠
This indicator measures the relative momentum of Bitcoin against the VUG/VTV ratio, which is the price of Vanguard's Growth ETF divided by Vanguard's Value ETF. This ratio is one of the most direct and liquid expressions of the growth-versus-value rotation dynamic in institutional equity markets: when VUG outperforms VTV the ratio rises, signaling that markets are rewarding high-multiple, long-duration assets; when VTV outperforms, the ratio falls, signaling a rotation toward defensive, cash-flow-heavy assets typically associated with tightening liquidity or rising rates.
Bitcoin is itself a long-duration, high-beta asset with structural similarities to growth equities: it tends to expand during the same liquidity-driven environments that favor VUG over VTV, and contract during the same risk-off environments that favor VTV over VUG. Tracking the VUG/VTV ratio alongside Bitcoin's own momentum reveals whether the macro environment is confirming or diverging from Bitcoin's price action, which historically has been a more reliable framework for identifying regime shifts than price-only signals.
The indicator operates in three modes.
Average Valuation mode averages the normalized momentum of Bitcoin and the VUG/VTV ratio into a single composite score, comparing it against configurable overbought and oversold percentile thresholds to identify when both are simultaneously extended or depressed.
Average Trend mode compares the composite score against its own midpoint to determine whether aggregate momentum is in its upper or lower historical half.
Double Signal mode plots Bitcoin and the VUG/VTV ratio momentum separately on the same normalized scale, making divergences between the two directly visible.
This is a cross-asset macro momentum and rotation indicator suited for swing trading and position trading on daily timeframes , functioning as a regime filter that connects Bitcoin's price action to one of the most closely watched equity style rotation signals in institutional markets.
How it differs from standard relative strength tools
A standard BTC/VUG ratio chart divides prices directly, producing a series with no statistical normalization and no connection to VTV. This indicator uses percentage returns normalized over a rolling window, making readings statistically consistent across different periods, and compares Bitcoin not against a single equity ETF but against the growth-value spread, which is a second-order signal capturing the macro liquidity regime rather than a single sector's performance. The three-mode architecture further distinguishes it from a simple ratio overlay by providing composite valuation, trend, and component-level views within a single indicator.
Plots 📊
Averaged normalized momentum oscillator with overbought and oversold threshold lines (Average Valuation mode)
Averaged normalized momentum with fill against the 50 midline (Average Trend mode)
Bitcoin and VUG/VTV normalized momentum plotted separately (Double Signal mode)
Overbought and oversold threshold lines (Average Valuation and Double Signal modes)
50 midline reference
Background color on the price chart when average enters extreme zones (Average Valuation mode)
Candle coloring on the price chart reflecting current regime in all three modes
Inputs 🎛️
Mode: Average Valuation, Average Trend, or Double Signal
Normalization Period: rolling window for the min-max normalization of returns
Lookback Period: return calculation window for both Bitcoin and the VUG/VTV ratio
Overbought Threshold: upper percentile level for extreme zone detection
Oversold Threshold: lower percentile level for extreme zone detection
Transparency: opacity of the background color highlight
Colors 🎨
5 Astral Vision presets + custom override. Default: Paradiso.
Disclaimer ⭕️
This indicator is for informational and educational purposes only. It does not constitute financial advice. Past performance is not indicative of future results. Always do your own research before making investment decisions. インジケーター
Bitcoin vs Inverted DXY Regime | Astral Vision Bitcoin vs Inverted DXY Regime | Astral Vision 🌠💠
Inspired by: @JackGreenCrypto
This indicator plots the Z-Score of Bitcoin's log price and the inverted Z-Score of the DXY Dollar Index on the same scale, shifted forward in time by a configurable lag, to visualize the historical inverse relationship between dollar strength and Bitcoin price and to identify divergences between the two series before they resolve in price.
Calculation ⚙️
Both Bitcoin and DXY are first transformed by taking their natural logarithm. Working in log space is essential for two reasons: Bitcoin has moved across several orders of magnitude, so raw price differences between 2015 and 2024 are not comparable; and the inverse relationship between DXY and Bitcoin is proportional rather than linear, meaning a 10% move in DXY has a proportionally similar impact regardless of absolute price level.
The Z-Score is then computed independently for each series using the same formula: subtract the simple moving average of the log series over the lookback window from the current log value, then divide by the standard deviation of the same window. The result for each series is: Z = (log(price) - SMA(log(price), N)) / StDev(log(price), N), where N is the configurable Z-Score lookback. This expresses each series in units of standard deviations above or below its own rolling mean, making the two series directly comparable on the same scale regardless of their absolute price differences.
The DXY Z-Score is then multiplied by -1 to invert it. Since DXY and Bitcoin historically move in opposite directions, the uninverted DXY Z-Score would mirror Bitcoin rather than track it. After inversion, the two series should theoretically overlap or move together during periods of normal inverse correlation. Divergences, where Bitcoin's Z-Score moves in one direction while the inverted DXY Z-Score moves in the other, signal a breakdown in the typical relationship that has historically tended to resolve by one series catching up to the other.
The inverted DXY line is plotted with a configurable forward offset in bars. This operationalizes the observed lag between dollar index movements and their full transmission into Bitcoin price, allowing the DXY signal to be read as a leading indicator rather than a coincident one.
Plots 📊
Bitcoin log Z-Score over the configurable lookback window
Inverted DXY log Z-Score shifted forward by the configurable lag
Inputs 🎛️
Z-Score Lookback: rolling window for mean and standard deviation applied to both series
DXY Lag: bars to shift the inverted DXY signal forward in time
Colors 🎨
5 Astral Vision presets + custom override. Default: Paradiso.
Purpose 🎯
Standard correlation tools between Bitcoin and DXY operate on raw prices or percentage returns, which are distorted by the enormous scale difference between the two assets and by Bitcoin's exponential growth trend. Computing both in log space and normalizing via Z-Score removes these distortions entirely, placing both series on equal statistical footing. The forward shift on the DXY line turns a coincident correlation chart into a directional leading signal: when the inverted DXY is rising ahead of Bitcoin's Z-Score, it suggests dollar weakness is building that has not yet fully priced into Bitcoin, and vice versa.
Disclaimer ⭕️
This indicator is for informational and educational purposes only. It does not constitute financial advice. Past performance is not indicative of future results. Always do your own research before making investment decisions. インジケーター
インジケーター
TimeWarp BatmanSPX Batman 1DTE — Strike Signal & Alert Tool
This indicator identifies end-of-day entry conditions for the SPX Batman spread, a two-legged options structure consisting of a long call butterfly placed out of the money above spot and a long put butterfly placed out of the money below spot. Neither fly shares legs. Both are sized and positioned independently.
What the Batman spread is
The Batman is a defined-risk, direction-neutral options trade designed to profit from a pin near expiry. It is not a straddle or strangle. Each leg is a long butterfly. The long call fly is entered OTM above spot at the close, targeting next-day expiry or Monday for Friday entries. The long put fly is entered OTM below spot on the same terms. The structure earns maximum profit if the underlying pins near either body at expiry. Max loss on each fly is limited to the debit paid.
How this indicator works
At 3:55 PM ET each session the indicator calculates proposed strike levels for both flies based on three inputs. Wing width is derived from VIX in dynamic mode or set manually, widening at elevated volatility. Body offset starts at 65 points plus the wing width from spot, rounded to the nearest 5-point SPX strike. Target debit range is calculated from your reward-to-risk inputs. A 1:15 to 1:20 target corresponds to a debit of approximately 4.8% to 6.25% of wing width per fly.
A label fires on the chart at signal time showing all six strike levels, the target debit range in points, and the expiry type. Strike lines remain visible through the next session. If the underlying trades through an outer wing a background highlight fires and a separate alert is available.
How to use it
Add the indicator to a 1-minute or 5-minute SPX chart. At the signal, open your broker's options chain for the next-day expiry. Locate the proposed call fly and put fly strikes. Walk the body strikes up or down in 5-point increments until the actual debit falls within the displayed target range. Enter both flies and manage through expiry.
Set alerts on Batman 1DTE Entry and Batman 3DTE Entry to be notified at signal time without watching the chart.
Inputs
VIX Symbol sets the data source for volatility-based width calculation.
Wing Width Mode switches between dynamic
VIX-scaled sizing and fixed widths of 20, 25, or 30 points.
Fixed Width sets the manual width when not using dynamic mode.
Min Reward to Risk and Max Reward to Risk define the acceptable debit range for each fly, defaulting to 1:15 and 1:20.
Important
This is a signal and visualization tool. It does not model options P&L, implied volatility, or time decay. TradingView cannot accurately backtest multi-leg options structures and this indicator makes no attempt to do so. All fills, debit verification, and risk management occur in your broker. Past signal frequency is not indicative of future profitability.
インジケーター
インジケーター
Cadence Reversion Cartography [JOAT]Cadence Reversion Cartography
Introduction
Cadence Reversion Cartography is an open-source mean-reversion and exhaustion overlay designed to locate stretched conditions around an EMA envelope and anchored VWAP framework. It focuses on mapping where price has moved too far from local balance, then grades whether a return toward value has enough supporting evidence to matter.
The problem this script solves is selective reversal timing. Price can stay overextended for longer than expected, so simple band-touch logic is not enough. Cadence Reversion Cartography combines envelope stretch, VWAP stretch, RSI exhaustion, volume impulse, rejection-candle behavior, reclaim logic, and projected response boxes so the user can distinguish weak touches from stronger reversion candidates.
Core Concepts
1. Dual Stretch Model
Price is compared to both an EMA deviation envelope and an anchored VWAP deviation layer. A long-side exhaustion condition requires price to stretch below both lower references. A short-side exhaustion condition requires price to stretch above both upper references.
2. Exhaustion Quality Filters
RSI can require oversold or overbought context, volume can require impulse relative to average participation, and candle structure can require a visible rejection profile.
3. Reclaim And Signal Grading
A setup becomes actionable only after price closes back inside the envelope on a confirmed bar. The script then scores the setup by counting how many filters aligned and promotes stronger signals to a prime grade.
4. Projection Mapping
When a setup forms, the script can draw a forward projection with a risk box, reward box, signal zone, and reclaim line. This is meant to show the structure of the reversion idea rather than acting as a promise of outcome.
Features
EMA reversion envelope: Basis plus statistical deviation bands
Anchored VWAP stretch layer: Secondary value reference around VWAP
RSI exhaustion filter: Optional momentum exhaustion gate
Volume impulse filter: Optional participation confirmation
Rejection-candle filter: Optional candle-structure confirmation
Signal grading: Standard and prime long or short responses
Signal zones and reclaim lines: On-chart response structure around the active setup
Risk and reward projection boxes: Optional forward mapping of stop and target structure
Context candle coloring: Candles can tint with stretch state
Dashboard: Displays stretch, setup bias, and active context
Input Parameters
Reversion Envelope:
Channel Length
Deviation Multiplier
VWAP Stretch Multiplier
Filters And Display:
RSI settings
Volume average and impulse multiplier
Rejection-candle requirement
Projection-box toggle, stop percent, reward multiple, projection length, and signal cooldown
Dashboard, background, candle-color, and signal-zone toggles
How to Use This Indicator
Step 1: Wait for price to stretch beyond both the EMA envelope and the VWAP stretch layer.
Step 2: Check whether RSI, volume, and rejection filters support the move.
Step 3: Wait for confirmed re-entry back inside the envelope instead of fading the first touch.
Step 4: Use the signal grade and projection structure to judge whether the setup is marginal or stronger.
Step 5: Use the basis and reclaim line as the first balance reference after entry.
Indicator Limitations
Strong directional trends can keep price stretched for extended periods and delay reversion
Volume-based confirmation is less meaningful on symbols with irregular volume reporting
Projection boxes are planning tools, not guaranteed outcomes
This script is designed for reversion analysis and is not intended to replace broader trend context
Originality Statement
Cadence Reversion Cartography is original in how it coordinates envelope stretch, VWAP stretch, filter-based exhaustion grading, and forward projection structure inside one reversion workflow. The components are combined to answer one analytical problem: not just whether price is stretched, but whether the stretch is mature enough to support a structured return toward value.
Disclaimer
This indicator is provided for educational and informational purposes only. It is not financial advice. Reversion setups can fail during strong trends or regime expansion, so all signals should be used with independent confirmation and risk management.
-Made with passion by jackofalltrades
インジケーター
Opening Range + Session Windows + Volume ProfileOpening Range + Session Windows + Volume Profile
This is a revised repost of my previous script version that trended on the TradingView community indicators page. The script has been rewritten, renamed, and cleaned up so the publication follows TradingView House Rules more closely.
The goal of this indicator is to make intraday session structure easier to read from one chart.
Opening range levels can be useful, but they are much more useful when viewed with nearby volume-based context. A move away from the opening range is not always the same type of move. It can be moving into an area where volume previously built, away from an area where volume was thin, or toward a level where participation has already concentrated.
This script is built to help show that context visually.
📊 What the script shows
• Opening range high, low, and range box
• Configurable session windows
• Current session volume profile
• Previous session volume profile
• POC, HVN, and LVN levels
• Live and prior session node labels
• A terminal-style HUD for session state, trend, range size, POC, HVN, LVN, and impulse counts
• A pressure meter based on session volume standard deviation
• Filtered buy-volume and sell-volume impulse labels
🧠 Why it was built this way
The script is designed around one main idea: the opening range should not be viewed in isolation.
A breakout, rejection, or rotation around the opening range can look completely different depending on where volume is sitting around price. If price is moving into a high-volume area, that can suggest a different type of environment than price moving through a thinner low-volume area. If a prior POC or volume node is nearby, that may also change how a trader studies the move.
This indicator does not try to replace analysis. It simply brings the important intraday structure into one clean visual layout so the user can study the session with more context.
⚙️ How to use it
1. Set the main session and opening range times in the settings.
2. Use the opening range box to mark the first part of the session.
3. Watch how price behaves around the current and prior volume nodes.
4. Use POC, HVN, LVN, and session levels as structure references.
5. Use the HUD to quickly read session state, trend, range size, and active nodes.
6. Use the volume gauge and impulse labels to study stronger participation events.
7. Adjust the session windows to match the market and timezone you trade.
🔁 Current vs prior levels
Live session levels are labeled as LIVE .
Previous session levels are labeled as PRIOR .
This makes it easier to separate developing session structure from levels carried forward from the last completed session.
⚡ Volume impulse labels
The volume impulse labels are intentionally filtered. They are not meant to appear on every volume increase. The script only prints them when participation is stronger than normal based on the selected settings.
This helps keep the chart cleaner and prevents the indicator from turning into a label-heavy mess.
🕒 Session windows
The session windows are visual time references only. They are fully configurable from the settings and can be adjusted, enabled, or disabled depending on the market being viewed.
⚠️ Important notes
This is not a trading system.
This script does not place trades, issue alerts to buy or sell, provide financial advice, or tell the user what action to take. It is a decision-support tool for studying intraday structure, volume location, session context, and participation.
FOR PINECODERS TEAM: Promotional references, branding, and unclear wording have been removed, and this description has been expanded so users can understand the purpose of the tool without needing to read the Pine code. I cannot, within reason, direct users any further regarding specific use of this indicator as to avoid providing any form of financial advice. It is a framework tool for various use-cases outlined above.
The user is responsible for their own analysis, risk management, and execution decisions.
✅ Best used on
Intraday charts where opening range structure and volume context matter, including index futures, stocks, ETFs, and other liquid instruments with meaningful volume data. インジケーター
