Daily VWAP Deviation MapDaily VWAP Deviation Map plots the current exchange day's VWAP and volume-weighted standard-deviation bands around it.
The purpose of this script is to show how far price is trading from the day's volume-weighted mean. Distance is displayed in price units, percent, and sigma distance. This is a context and visualization tool. It does not provide trade-action instructions and it is not a trading system.
What it shows
- Daily VWAP based on the selected source, default hlc3.
- Inner, outer, and optional tail deviation bands.
- Sigma distance from the current day's VWAP.
- A neutral state model that describes price location relative to VWAP.
- A compact dashboard with state, sigma distance, percent distance, VWAP, and volume mode.
- Optional non-arrow event markers for factual band-crossing events.
How it works
At the start of each exchange day, the calculation resets and begins accumulating volume-weighted sums from the current chart bars.
The script maintains:
- cumulative volume
- cumulative price times volume
- cumulative price squared times volume
- session bar count
From these values, it calculates:
VWAP = cumulative price times volume / cumulative volume
variance = cumulative price squared times volume / cumulative volume - VWAP squared
sigma = square root of variance, guarded against rounding noise
The script then calculates:
- raw distance from VWAP
- percent distance from VWAP
- sigma distance from VWAP
All calculations use current chart bars only. The script does not use request.security(), lookahead, or future data. Historical values are not recalculated with future information.
Daily anchoring
The daily reset follows the chart symbol's exchange day and timezone. This reset is used only to anchor the VWAP calculation to the current day. It is not a session highlighter and it does not shade Tokyo, London, New York, or other trading sessions.
Deviation states
The dashboard uses neutral descriptive states:
- Warming up
- Near VWAP
- Inner range
- One-sigma edge
- Two-sigma extension
- Outer tail
These states describe current price location. They do not imply future reversal or continuation.
Bands and multipliers
The inner, outer, and tail band multipliers are user-configurable. The active outer tier is kept above the active inner tier, and the active tail tier is kept above the outer tier. Event markers and alerts follow the active inner and outer band tiers so they remain aligned with the displayed bands when users customize the multipliers.
Volume handling
When usable volume is available, the calculation is volume-weighted. If volume is missing or not positive and fallback is enabled, the script uses an equal-weight fallback so the display can remain continuous. The dashboard discloses this clearly.
The dashboard volume mode can show:
- Volume-weighted
- Equal-weight fallback
- No usable volume
On some symbols, especially certain FX or CFD feeds, volume may represent tick volume or may not be available. This affects how VWAP and deviation bands should be interpreted.
Events and alerts
Event markers are small, neutral, non-arrow plotshape markers. They describe factual events only, such as:
- crossed above the upper inner band
- crossed below the lower inner band
- crossed above the upper outer band
- crossed below the lower outer band
- returned inside from an upper or lower extension
- crossed VWAP
Alerts use the same neutral event logic. The default setting evaluates events on confirmed bars only to reduce intrabar repainting.
Customization
Users can adjust the dashboard position, layout density, text size, plot colors, table colors, marker colors, and transparency settings.
The default dashboard position is Top right padded. It keeps the panel in the upper-right area while using subtle internal spacing to reduce clutter near the chart's right-side price-scale labels. Users can switch to standard Top right or any other available table anchor.
The default layout is Compact for a clean chart. Standard and Detailed layouts are available for users who want more information.
Intended use
This indicator is designed for intraday charts. On daily or higher timeframes, the script avoids showing misleading daily VWAP deviation bands and displays an intraday-use notice instead.
Limitations
This script is not financial advice and not a trading system.
Distance from VWAP does not guarantee reversal or continuation.
Default settings are starting points, not optimized settings.
Early-session VWAP and sigma readings can be sensitive because fewer bars have been accumulated.
Volume quality differs across markets and symbols.
Japanese notes
当日VWAPと出来高加重標準偏差バンドを使って、価格が当日の平均価格からどれだけ乖離しているかを表示します。状況把握用の可視化ツールであり、売買判断や将来の値動きを示すものではありません。出来高が使えない銘柄では等加重フォールバック、または No usable volume を表示します。イントラデイ向けです。 Indicator
Indicator
Indicator
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. Indicator
Session VWAP + StdDev Bands [ChartPrime]🔶 OVERVIEW
Session VWAP + StdDev Bands is a professional-grade anchored VWAP system that resets on a user-defined higher timeframe and builds a full standard deviation band structure around it. Unlike a rolling VWAP, this indicator recalculates from the first bar of each new session, giving you a clean, unbiased volume-weighted price reference that reflects exactly where the market has traded relative to volume since the session opened.
The tool goes beyond a simple VWAP line by tracking how many times price has retested each individual band, using that retest count to dynamically intensify the color of each line — the more a level is tested, the more significant it becomes visually. Cumulative volume at each retest is also tracked and displayed, giving traders institutional-grade context directly on the chart.
• Anchored VWAP with configurable higher timeframe reset (Daily, Weekly, Monthly, etc.)
• Three independent standard deviation band pairs (1σ, 2σ, 3σ)
• Per-line retest counter with dynamic color intensity — more retests = brighter line
• Cumulative volume tracking per band displayed in live edge labels
• High/Low wick-based band touch signals with cooldown control
• Clean session break with automatic label and state reset
🔶 CORE CONCEPT — ANCHORED VWAP WITH VOLUME-WEIGHTED STANDARD DEVIATION
Standard VWAP indicators use session time as the anchor. This indicator uses a higher timeframe bar close as the reset trigger, giving you full control over the session definition:
• Anchored Reset: When the selected higher timeframe (e.g. Weekly) closes a new bar, the VWAP and all standard deviation calculations reset from zero. This ensures the VWAP always reflects the current session's volume distribution.
• True StdDev Bands: Bands are calculated using a volume-weighted variance formula — not ATR, not simple standard deviation. This means the bands expand and contract based on how dispersed price has been relative to volume, not just raw price movement.
• Dynamic Color Intensity: Each of the seven lines (VWAP + 6 band lines) tracks its own retest count independently. As price crosses a line more times, its transparency decreases and the line becomes fully saturated — a visual heatmap of the most contested price levels in the session.
🔶 RETEST COUNTING & VOLUME TRACKING
The intelligence of this indicator lives in its per-line memory system:
Independent Counters: Every line — VWAP, 1σ Upper, 1σ Lower, 2σ Upper, 2σ Lower, 3σ Upper, 3σ Lower — has its own retest counter that increments on every close-based cross.
Color Intensity Mapping: Each retest reduces the line's transparency by 10 points. A line with 0 retests starts at 100% transparent (invisible). After 10 retests it reaches full opacity. This creates a natural visual hierarchy where the most-tested levels stand out.
Cumulative Volume: Every time a line is crossed, the bar's volume is added to that line's running total. The edge label displays both the retest count and the total volume that flowed through that level — e.g. "1σ↑ 4 (vol. 2.3M)".
Session Reset: All counters, volumes, and labels reset cleanly at the start of each new session.
🔶 BAND TOUCH SIGNALS
Signal shapes fire when price wicks into a band rather than waiting for a close-based cross, making them more responsive to intrabar reactions at key levels:
Bull Signal (Blue Diamond): The bar's low drops to or below a band line while the previous bar's low was above it — a wick touch from above, indicating potential support reaction.
Bear Signal (Orange Diamond): The bar's high reaches or exceeds a band line while the previous bar's high was below it — a wick touch from below, indicating potential resistance reaction.
Cooldown Filter: A configurable cooldown (default 20 bars) prevents signal clusters at the same level. Once a signal fires, the same direction cannot fire again until the cooldown expires.
🔶 LIVE EDGE LABELS
Each band line carries a floating label anchored to the right edge of the chart that updates every bar:
Labels display the band name, retest count, and cumulative volume in a compact single-line format.
Label text color matches the line's current dynamic color — as the line intensifies, the label text intensifies with it.
Labels reset and reposition automatically on each new session, always staying aligned with the current band price level.
Label size is fully configurable from Tiny to Huge to suit any screen or timeframe.
🔶 HOW TO USE
Identifying Key Levels: Watch which bands accumulate the most retests during a session. A 1σ band with 6+ retests and high cumulative volume is a high-conviction support or resistance zone — treat it like a volume node.
Trend Bias: Price consistently closing above VWAP signals bullish session bias. Price consistently closing below signals bearish bias. Use the VWAP retest count to gauge how contested the mean is.
Breakout Confirmation: When price breaks through a 2σ or 3σ band with a strong close, the band color will begin to intensify on subsequent retests. A bright outer band that holds as support after a breakout is a high-probability continuation signal.
Fading Extremes: Bear signals at 2σ or 3σ upper bands and bull signals at 2σ or 3σ lower bands are mean-reversion opportunities, especially when cumulative volume at those levels is low (few retests, thin volume).
Timeframe Selection: Use Weekly reset on daily charts for swing trading context. Use Daily reset on intraday charts for intraday VWAP analysis. Use Monthly reset on daily or weekly charts for macro-level value area mapping.
🔶 CONCLUSION
Session VWAP + StdDev Bands turns a standard VWAP into a living, session-aware price map. By combining anchored volume-weighted calculations with per-line retest memory and cumulative volume tracking, it gives traders a clear picture of where the market has spent the most energy — and which levels are likely to matter most as the session develops. Indicator
Orion Regression Field [JOAT]Orion Regression Field
Introduction
Orion Regression Field builds a weighted regression valuation field with standard error bands, curvature options, compression detection, and reprice signals.
This open-source indicator is designed as a context tool, not a standalone trading system. It focuses on explaining the current market state with restrained visuals and confirmed-bar logic where signals are used.
Core Concepts
1. Weighted Regression
Recent bars can receive more influence while still preserving a full model window.
2. Standard Error Bands
Inner and outer bands show statistical distance from the modeled path.
3. Curvature and Confidence
Optional curvature and R2-style confidence control when the field is considered reliable.
4. Pinch and Reprice
Compression and outer-band reactions create filtered reprice events.
mid = weightedRegression(close, len); band = standardError * multiplier
Features
Weighted regression midline
Inner and outer SEE bands
Optional curvature
Pinch shading and projection field
Filtered reprice labels
Input Parameters
Regression window and projection bars
Curvature toggle and weight floor
Minimum R2 confidence
Inner and outer band multipliers
Pinch ratio and cooldown
How to Use This Script
Use the field as statistical fair-value context. Outer band interaction means stretch, not automatic reversal.
Limitations
The script uses historical OHLCV data and cannot know future prices.
Signals and states can be late during fast reversals because confirmed-bar logic is used to reduce repainting.
Model outputs should be interpreted with market context, risk controls, and independent analysis.
No visual state should be treated as a certain trade outcome.
Originality Statement
Orion is original in combining weighted regression, curvature, standard error fields, compression context, and filtered reprice logic.
Disclaimer
This indicator is provided for educational and informational purposes only. It is not financial advice, investment advice, or a recommendation to buy or sell any financial instrument. All calculations are derived from historical market data and may produce inaccurate readings in some market conditions. No indicator can predict future market behavior. Use proper risk management and independent judgment.
-Made with passion by jackofalltrades
Indicator
Sigma Structure [RWCS]What it is:
Sigma Structure is a confluence-based trading indicator that unifies three distinct analytical layers into a single, cohesive view: a Z-Score oscillator measuring price deviation from its 20 EMA, a normalized MACD histogram for momentum context, and an Order Block detection engine that identifies structural demand and supply zones directly on the price chart. The result is an indicator that tells you not just when price is statistically extended, but where that extension is occurring relative to meaningful price structure — giving every signal a location and every location a statistical weight.
How it works:
1. Z-Score layer: Price is measured as the number of standard deviations it sits above or below its 20-period EMA. This produces an oscillator that reads consistently across any asset or timeframe — a reading of +2 on Bitcoin means the same thing structurally as +2 on the S&P or EURUSD. The line color intensifies from faded to full aqua as it moves above zero, and faded to full fuchsia below, so the degree of extension is immediately legible at a glance. Fixed bands at ±1, ±2, and ±3 sigma define the statistical landscape.
2. MACD layer: A standard MACD histogram is computed normally, then linearly scaled so its rolling peak aligns with the ±3σ band. No calculation is modified — only the display axis is shared with the Z-Score. This means crossovers, divergences, and momentum shifts read identically to a standard MACD, but now live in the same visual space as the bands, letting you see momentum and mean-reversion context simultaneously.
3. Order Block layer: The indicator scans for order blocks using a sequential candle method — a bearish candle followed by a configurable number of consecutive bullish candles (demand), or a bullish candle followed by consecutive bearish candles (supply). Detected zones are drawn directly on the price chart as shaded regions with solid top boundaries and dashed bottom boundaries, color-coded aqua for demand and fuchsia for supply. Zones extend rightward bar by bar and self-invalidate the moment price closes through them, so what you see on the chart is always live and relevant.
4. Confluence signals: Two signal types fire when the Z-Score and Order Block layers align. An OB Reversal label appears when price is inside an Order Block while the Z-Score is at or beyond ±2σ — the statistical extension and the structural level are confirming each other as a fade opportunity. An OB Continuation label appears when price pulls back into an Order Block and the Z-Score reclaims zero — the trend is reasserting after a mean-reversion dip into demand or supply.
5. Volatility divergence: A background highlight layer compares price's rolling highs and lows against the rolling highs and lows of realized volatility (standard deviation of log returns). When price makes a new low without a corresponding expansion in realized volatility, a bullish divergence is flagged. The inverse flags bearish divergence. These are not entry signals on their own — they indicate moments where price action and volatility are telling different stories and warrant closer attention.
Possible ways to use it:
1. Reversal setups: When the Z-Score reaches ±2σ or beyond and price simultaneously tags an active Order Block zone, the statistical extension and structural level are aligned. The OB Reversal label marks these bars. Look for MACD histogram compression or a zero cross in the same window for additional confirmation before acting.
2. Trend continuation entries: In trending markets, price frequently pulls back into demand or supply zones and finds support exactly where it should. When the Z-Score crosses back through zero inside an active zone, the OB Continuation label fires — this is your structural retest with momentum confirmation.
3. Divergence as a filter: The volatility divergence highlights flag potential exhaustion in price moves that lack volatility confirmation. Use these as a reason to tighten risk or wait for the OB/Z-Score confluence before entering, rather than chasing the move.
4. EMA trend bias: The fast and slow EMA overlay on the price chart provides a quick structural read. Aligning your OB Reversal or Continuation signals in the direction of the EMA cross adds a higher-timeframe trend filter without requiring a second indicator.
5. Alert-driven scanning: Three configurable alerts cover the ±2σ Trade Zone cross, OB Reversal confluence, and OB Continuation setup. Set these across a watchlist to surface actionable conditions without manual chart monitoring.
Settings guide:
1. EMA / Std Dev Length: Both default to 20, matching a standard Bollinger Band configuration. Increase for smoother, slower signals on higher timeframes.
2. MACD Norm Lookback: Controls how far back the indicator looks to find the MACD histogram's peak for scaling. Higher values produce more stable scaling; lower values make the histogram more reactive to recent momentum.
3. Sequential Candles for OB: The number of consecutive candles required after the origin candle to confirm a block. Higher values produce fewer, higher-quality zones.
4. Max Active Zones: How many demand and supply zones can coexist on each side. Older zones are removed when the limit is reached.
5. Divergence Lookback: The rolling window for comparing price extremes against volatility extremes. Shorter values produce more frequent signals; longer values are more selective.
Disclaimer:
This indicator is published for educational and informational purposes only. Nothing presented here constitutes financial advice, a solicitation, or a recommendation to buy or sell any financial instrument. All trading involves risk, including the possible loss of principal. Past performance of any indicator or methodology is not indicative of future results. You are solely responsible for your own trading decisions. Always conduct your own research and consult a qualified financial professional before making any investment decisions. Indicator
Mean Reversion Corridors [AGPro Series]Mean Reversion Corridors
🔹 Overview
Mean Reversion Corridors is a volatility-adaptive deviation framework that maps how far price has stretched from a chosen fair-value center and classifies that stretch into two actionable zones. An inner corridor marks the early reversion band where price is meaningfully extended but not yet extreme; an outer corridor marks statistical exhaustion where continuation becomes less probable under normal conditions. A higher-timeframe trend filter separates controlled mean reversion from failure-continuation expansions, so traders can tell fading the edge from respecting a real break — all from a single clean overlay.
🔸 Unique Edge
Most band systems (Bollinger, Keltner, ATR channels) offer a single width engine and a single band pair, leaving the trader to guess whether a tag is an exhaustion or a breakout. Mean Reversion Corridors is built around three ideas that work together:
- A dual-engine width unit that linearly blends ATR (range-based) and Standard Deviation (dispersion-based) so the corridor is stable on both gap-heavy and low-dispersion regimes.
- A two-layer corridor with distinct roles — inner for early stretch, outer for exhaustion — rendered as transparent zones you can read at a glance.
- A regime-aware state machine that uses a higher-timeframe trend filter to reclassify outer tags as either reversion candidates or failure-continuation, tracked as explicit REV and FAIL states with a bounded confirmation window.
🧠 Methodology
- Center Model — user choice of EMA, VWMA (volume-aware, default) or HMA (responsive), calculated on chart closes.
- Width Unit — the current volatility unit is a linear blend: (1 − blend) × ATR + blend × StDev, protected against empty volatility periods.
- Corridors — inner band at ±(width × inner multiplier), outer band at ±(width × outer multiplier). Stretch is reported in width-unit sigma.
- Trend Filter — the same center model is evaluated on a higher-timeframe via request.security with lookahead off, and its slope is normalized by ATR so the "strong" threshold is volatility-aware, not symbol-specific.
- State Machine — tracks the most recent outer-band extreme with a rolling 20-bar confirmation window. A reversion is confirmed only when price closes back inside the inner corridor and the trend filter is not strongly aligned with the original stretch. When the trend is strongly aligned, the outer break is reclassified as corridor failure (continuation).
- All conditions evaluate on confirmed bars to avoid repainting behavior.
⚡ Signals & Alerts
On-chart markers:
- REV — reversion confirmed back through the inner band after an outer extreme, trend-filtered.
- FAIL — corridor failure / trend-aligned continuation beyond the outer band.
Six bar-close alert conditions:
- Inner corridor entered — upside stretch
- Inner corridor entered — downside stretch
- Outer corridor hit — upside exhaustion
- Outer corridor hit — downside exhaustion
- Reversion confirmed
- Corridor failure (continuation)
⚙️ Key Inputs
- Center Model — EMA / VWMA / Hull
- Center Length and Volatility Length — independent lookbacks
- ATR ↔ StDev Blend — balance between range and dispersion engines
- Inner Corridor Width and Outer Corridor Width — in volatility units
- Trend Filter — enable, timeframe, length, strength threshold
- Visuals — outer-only mode, center line, fills, edge tags, state labels, label size
- Info Panel — show/hide, position (six options), font size
- Alerts — individually toggleable for each of the six events
📖 How to Use
- Start with the defaults on your main chart timeframe. The 34-period VWMA center, balanced blend and 1.0 / 2.2 inner/outer multipliers are chosen to work as a neutral starting point across liquid markets.
- Inner corridor tags are early stretch cues — they flag that price is extended, not that a turn is due. Use them as context for setups, not as standalone signals.
- Outer corridor tags with the trend filter neutral or opposed are the primary mean reversion setup; wait for a REV confirmation back inside the inner band before acting.
- When FAIL appears, the stretch is trend-aligned; treat the outer band as continuation, not resistance. This is the signal to stop fading.
- Use the Info Panel to read current state, reversion bias, trend regime and stretch magnitude in sigma at a glance.
⚠️ Limitations & Transparency
- This is an analytical tool, not a trading strategy or financial advice. It does not predict future price.
- Band-based classification assumes statistical behavior; during shocks, news events or illiquid sessions the width engine can lag.
- The trend filter uses a higher-timeframe slope — it reacts slower than short-term momentum by design, which is the intended behavior.
- Signals are evaluated on confirmed bars; intrabar crosses are not counted as events.
- Past behavior of any indicator does not guarantee future results. Always apply your own risk management. Indicator
Adaptive Velocity Oscillator [UAlgo]Adaptive Velocity Oscillator is a momentum and reversal framework built around the rate of change of an Adaptive Moving Average. Instead of using a fixed smoothing engine, the script first creates a Kaufman style adaptive average whose responsiveness changes according to market efficiency, then measures how fast that adaptive baseline is moving from one bar to the next. That velocity becomes the core oscillator.
The main idea is straightforward. When the adaptive average starts accelerating upward, the oscillator rises above zero. When the adaptive average starts decelerating or turning lower, the oscillator falls below zero. This gives the user a direct view of directional pressure, but in a way that remains sensitive to changing market conditions because the underlying average itself is adaptive rather than static.
To make the oscillator more practical, the script surrounds the velocity with dynamic filter bands derived from the standard deviation of the AMA series. These bands act like a contextual noise threshold. Small fluctuations inside the band are treated as less important, while stronger moves through the band can be interpreted as meaningful directional expansion or reversal activity.
The script also supports two signal styles. Standard mode reacts to velocity transitions through the regular filter band. Extreme Reversal mode requires a deeper stretch into an expanded threshold before signaling a reversal style response. Optional price confirmation can then require bullish candle structure for buy signals and bearish candle structure for sell signals. A cooldown filter is added on top so the same type of signal cannot repeat too rapidly.
The result is an oscillator that can be used for trend context, reversal spotting, and momentum transition analysis. It is especially useful for traders who want something more adaptive than a traditional moving average crossover or a simple rate of change calculation.
🔹 Features
🔸 Adaptive AMA Core
The script uses an adaptive moving average whose smoothing constant changes according to the Efficiency Ratio. When price is moving efficiently in one direction, the average becomes more responsive. When price is noisy and directionless, the average becomes slower and more stable.
🔸 Velocity Based Oscillator
The oscillator is not built from price directly. It is built from the bar to bar change of the adaptive average. This means the indicator measures how quickly the smoothed baseline itself is moving, which creates a cleaner momentum signal than raw price change alone.
🔸 Dynamic Filter Bands
A statistical filter band is calculated from the standard deviation of the AMA series and then scaled by the user selected gamma value. This creates a noise threshold that expands and contracts with market conditions.
🔸 Standard and Extreme Reversal Modes
In Standard mode, signals are generated when velocity crosses back through the regular filter threshold. In Extreme Reversal mode, the script requires a deeper stretch using an expanded band before a signal can trigger. This gives the user a choice between more responsive and more selective behavior.
🔸 Optional Price Confirmation
Signals can require candle confirmation. Bullish signals may be restricted to bars where close is above open, and bearish signals may be restricted to bars where close is below open. This can help reduce signals that appear without supportive candle structure.
🔸 Cooldown Protection
A built in cooldown logic prevents repeated same side signals from firing too close together. This helps reduce clustering during noisy or oscillatory phases.
🔸 Trend State From Zero Crosses
The script also tracks velocity crosses through zero. These zero transitions can be interpreted as broader positive or negative momentum regime shifts.
🔸 Visual Context Through Color and Bands
The histogram and line coloring change according to whether velocity is strongly positive, strongly negative, or neutral relative to the filter zone. This makes the oscillator easy to read at a glance.
🔸 Signal Labels and Alerts
The indicator places buy and sell labels around qualifying signal bars and includes alert conditions for bullish signals, bearish signals, positive trend shifts, and negative trend shifts.
🔹 Calculations
1) AMA State Container
type AMACalculator
float value = na
float value_prev = na
float velocity = 0.0
float filterBand = 0.0
This object stores the internal state of the adaptive average engine.
value holds the latest AMA value.
value_prev stores the previous AMA value.
velocity stores the bar to bar change of that AMA.
filterBand stores the active dynamic threshold used later for signal filtering.
So before any signal logic begins, the script already has a dedicated structure for the adaptive average, its momentum, and its statistical band.
2) Efficiency Ratio Calculation
float change = math.abs(src - src )
float volatility = math.sum(math.abs(src - src ), lengthER)
float ER = volatility == 0 ? 0 : change / volatility
This is the first major step inside the AMA calculation.
The script compares two quantities.
change measures the net directional move from the current price back to the price lengthER bars ago.
volatility measures the total path traveled during that same interval by summing all absolute bar to bar changes.
The Efficiency Ratio is then:
ER = change / volatility
If price moved smoothly in one direction, net change will be large relative to total movement, and ER will be high. If price moved in a noisy back and forth way, total movement will be large but net change will be smaller, so ER will be low.
This ratio tells the AMA how efficiently price has been moving, which directly controls how responsive the adaptive average should become.
3) Building the Adaptive Smoothing Constant
float fastest = 2.0 / (fastLen + 1)
float slowest = 2.0 / (slowLen + 1)
float sc = math.pow(ER * (fastest - slowest) + slowest, 2)
This block converts the Efficiency Ratio into a smoothing constant.
First, the script computes the EMA style constants for the chosen fast and slow lengths. Then it blends between them using ER. When ER is high, the result moves closer to the fast setting. When ER is low, the result stays closer to the slow setting.
Finally, the blended value is squared. This is a classic AMA technique that makes the adaptive response more sensitive to efficiency changes.
So the smoothing constant automatically shifts between fast and slow behavior depending on market structure.
4) Updating the Adaptive Moving Average
this.value_prev := this.value
float prevAma = na(this.value_prev) ? src : this.value_prev
this.value := prevAma + sc * (src - prevAma)
This is the actual AMA update formula.
The script first stores the previous AMA value. If no previous value exists yet, it uses the current source as the starting point.
Then it updates the average using:
new AMA = previous AMA + smoothing constant × (source minus previous AMA)
So the adaptive average moves toward price, but the speed of that movement depends entirely on the previously calculated smoothing constant.
When the market is efficient, the average reacts more quickly. When the market is noisy, it reacts more slowly.
5) Computing Velocity
this.velocity := this.value - prevAma
This single line is the core of the oscillator.
Velocity here is simply the difference between the current AMA value and the previous AMA value.
If the adaptive average is rising, velocity is positive.
If the adaptive average is falling, velocity is negative.
If the adaptive average is barely moving, velocity stays close to zero.
So the oscillator is not measuring price change directly. It is measuring the momentum of the adaptive baseline itself.
6) Creating the Dynamic Filter Band
float amaGlobalSeries = amaObj.value
float sigma = ta.stdev(amaGlobalSeries, n)
amaObj.filterBand := gamma * sigma
After the AMA is calculated, the script builds a dynamic filter threshold from its standard deviation.
sigma measures how much the AMA has been varying over the selected period.
That value is then scaled by gamma to create the final filter band.
So the band expands when the adaptive average becomes more variable and contracts when the average becomes quieter.
This creates a context aware threshold that helps separate meaningful momentum movement from smaller background fluctuations.
7) Regular Band and Extreme Band
float currentVelocity = amaObj.velocity
float currentFilter = amaObj.filterBand
float extremeBand = currentFilter * extMulti
This block prepares the two signal thresholds used later.
currentFilter is the normal band.
extremeBand is a larger band created by multiplying the normal band by the user selected extreme multiplier.
So the script supports two layers of selectivity:
a regular threshold for Standard mode,
and a deeper threshold for Extreme Reversal mode.
8) Raw Signal Logic
bool rawBullSignal = sigMode == "Standard" ? ta.crossover(currentVelocity, -currentFilter) : ta.crossover(currentVelocity, -extremeBand)
bool rawBearSignal = sigMode == "Standard" ? ta.crossunder(currentVelocity, currentFilter) : ta.crossunder(currentVelocity, extremeBand)
This is the primary signal engine.
In Standard mode:
a bullish signal appears when velocity crosses upward through the negative regular filter level.
a bearish signal appears when velocity crosses downward through the positive regular filter level.
In Extreme Reversal mode:
a bullish signal requires velocity to recover upward through the deeper negative extreme band.
a bearish signal requires velocity to fall downward through the deeper positive extreme band.
The important idea is that signals are not based on zero line crosses alone. They are based on velocity reentering from stretched territory. That makes the logic more reversal oriented than a simple trend flip model.
9) Optional Price Confirmation
if reqPriceConf
rawBullSignal := rawBullSignal and close > open
rawBearSignal := rawBearSignal and close < open
This block adds an extra candle structure filter.
If price confirmation is enabled:
bullish signals are only allowed when the bar closes above its open.
bearish signals are only allowed when the bar closes below its open.
This can help reduce signals that occur mathematically in the oscillator but do not have supportive price behavior on the actual candle.
So the oscillator can be used either in pure indicator form or with a stricter candle aligned confirmation layer.
10) Cooldown Filter Logic
method filterSignal(array arr, bool cond, int waitBars) =>
bool isValid = false
if cond
int lastSignalBar = arr.size() > 0 ? arr.get(0) : -waitBars - 1
if (bar_index - lastSignalBar) >= waitBars
isValid := true
arr.unshift(bar_index)
if arr.size() > 2
arr.pop()
isValid
This method prevents signals from firing too frequently.
When a new raw signal appears, the script looks at the most recent stored signal bar for that direction. If enough bars have passed since the previous signal, the new one is accepted. Otherwise it is ignored.
The accepted signal bar index is then stored at the front of the array. Only a small recent history is kept.
So this method acts as a timing gate that stops repetitive same side signals during choppy conditions.
11) Final Signal Construction
var array lastBull = array.new()
var array lastBear = array.new()
bool finalBullSignal = lastBull.filterSignal(rawBullSignal, cooldown)
bool finalBearSignal = lastBear.filterSignal(rawBearSignal, cooldown)
This is where raw signals become final trade style signals.
Bullish signals are passed through the bullish cooldown array.
Bearish signals are passed through the bearish cooldown array.
That means buy and sell signals are filtered independently. A recent bullish signal only blocks another bullish signal, and a recent bearish signal only blocks another bearish signal.
So the script maintains clean directional spacing for both sides.
12) Histogram Coloring Logic
color histColor = currentVelocity > currentFilter ? color.new(colorUp, 20) :
currentVelocity < -currentFilter ? color.new(colorDn, 20) :
currentVelocity > 0 ? color.new(colorUp, 70) :
color.new(colorDn, 70)
This block assigns visual meaning to oscillator strength.
If velocity is above the upper regular filter, the histogram uses a stronger bullish color.
If velocity is below the lower regular filter, it uses a stronger bearish color.
If velocity is still positive but inside the filter region, it uses a softer bullish color.
If velocity is negative but inside the filter region, it uses a softer bearish color.
So the color logic tells the user both direction and intensity at the same time.
13) Drawing the Filter Bands
plot(currentFilter, "Upper Filter Band", color=color.new(colorDn, 40), linewidth=1, style=plot.style_line)
plot(-currentFilter, "Lower Filter Band", color=color.new(colorUp, 40), linewidth=1, style=plot.style_line)
plot(extremeBand, "Upper Extreme Band", color=color.new(colorDn, 60), linewidth=1, style=plot.style_line, display=sigMode == "Extreme Reversal" ? display.all : display.none)
plot(-extremeBand, "Lower Extreme Band", color=color.new(colorUp, 60), linewidth=1, style=plot.style_line, display=sigMode == "Extreme Reversal" ? display.all : display.none)
These plots create the visual threshold system.
The regular upper and lower filter bands are always shown.
The wider extreme bands are shown only when Extreme Reversal mode is selected.
This makes it easy to see whether current velocity is operating inside the neutral zone, beyond the regular band, or at deeper stretch levels.
14) Filling the Neutral Filter Region
p_upper = plot(currentFilter, display=display.none)
p_lower = plot(-currentFilter, display=display.none)
fill(p_upper, p_lower, color=color.new(colorNeu, 95), title="Filter Band Fill")
This block shades the area between the upper and lower regular filter bands.
The filled zone visually represents the neutral or lower conviction region. When velocity remains inside this zone, momentum is more muted relative to recent adaptive average behavior.
So the fill acts as a quick background cue for whether velocity is still inside normal fluctuation territory.
15) Plotting Velocity as Histogram and Line
plot(currentVelocity, "AMA Velocity", color=histColor, style=plot.style_columns)
plot(currentVelocity, "Velocity Line", color=histColor, linewidth=2)
The same velocity value is drawn in two forms.
The column plot gives a strong histogram style momentum read.
The line plot overlays the same data as a smoother continuous path.
Using both together makes the oscillator easier to read because the columns highlight amplitude while the line emphasizes turning points and transitions.
16) Signal Label Placement
if finalBullSignal
label.new(x=bar_index, y=math.min(0, currentVelocity) - math.abs(sigMode == "Extreme Reversal" ? extremeBand : currentFilter) - (math.abs(currentFilter) * 1.5),
text="▲ BUY",
color=color.new(color.white, 100),
textcolor=colorUp,
style=label.style_none,
size=size.small)
if finalBearSignal
label.new(x=bar_index, y=math.max(0, currentVelocity) + math.abs(sigMode == "Extreme Reversal" ? extremeBand : currentFilter) + (math.abs(currentFilter) * 1.5),
text="SELL ▼",
color=color.new(color.white, 100),
textcolor=colorDn,
style=label.style_none,
size=size.small)
These blocks place the signal labels outside the oscillator body rather than directly on top of the bars.
For bullish signals, the label is positioned below the relevant lower threshold area.
For bearish signals, the label is positioned above the relevant upper threshold area.
This helps keep the chart readable and visually separates the signal from the oscillator itself.
17) Alert Conditions
alertcondition(finalBullSignal, "Buy Signal", "AMA Velocity Buy Signal")
alertcondition(finalBearSignal, "Sell Signal", "AMA Velocity Sell Signal")
bool posTrend = ta.crossover(currentVelocity, 0)
bool negTrend = ta.crossunder(currentVelocity, 0)
alertcondition(posTrend, "Positive Trend", "AMA Velocity crossed above zero")
alertcondition(negTrend, "Negative Trend", "AMA Velocity crossed below zero")
The script provides four alert types.
The first two alert on final buy and sell signals after all filters and cooldown checks are applied.
The second two alert when velocity crosses the zero line, which can be interpreted as broader momentum regime shifts.
So the indicator supports both reversal style event monitoring and general trend transition monitoring. Indicator
LSMA SD | GForgeLSMA SD | GForge
LSMA SD is a trend-following oscillator built for swing trading on higher timeframes. It generates rules-based long and exit signals by measuring where price sits within a statistically-defined volatility envelope anchored to a regression-based trend line.
Core Calculation
The basis line is a Least Squares Moving Average. Unlike a standard moving average which weights past prices, LSMA computes the mathematically optimal straight-line fit across a defined lookback window. This means the basis reflects the actual gradient of a trend — its slope tells you the rate and direction of price movement, not a smoothed echo of where price has been. A short EMA pass is applied to the raw LSMA output as a robustness measure, absorbing single-bar snap artifacts that occur when outlier candles enter or exit the regression window. This is not a smoothing aesthetic — it directly addresses a known fragility in raw LinReg endpoints.
The default source is hlc3 — the average of high, low, and close — rather than close alone. This distributes the regression input across the full bar range, reducing sensitivity to end-of-session price mechanics such as stop runs and last-minute order flow that can distort the trend line without reflecting genuine directional movement.
A Standard Deviation envelope is then constructed around the LSMA basis at a fixed multiplier. The band width is driven entirely by actual price volatility — it widens during high-volatility periods and tightens during quiet ones. There is no secondary adaptive scaling layer. This is intentional: additional dynamic scaling introduces a second noisy signal on top of the basis movement, which in practice degrades signal quality.
The Oscillator
The oscillator expresses where price currently sits within the SD bands on a 0–100 scale. A reading of 0 means price is at the lower band. A reading of 100 means price is at the upper band. A reading of 50 means price is sitting directly on the LSMA trend line itself — the neutral zone between the two signal thresholds represents price consolidating around the regression basis.
Long signals fire when the oscillator crosses above the long threshold (default 74), meaning price has broken decisively into the upper band zone — a momentum confirmation in the direction of the trend, not a mean-reversion trigger. Exit and short signals fire when the oscillator crosses below the short threshold (default 33).
This is a trend-continuation system, not a reversal indicator.
Parameters
The indicator is intentionally low-parameter. LSMA Length sets the regression window. StdDev Length sets the band width lookback and can differ from the LSMA length. StdDev Multiplier sets the fixed band scale. Endpoint Smoothing controls how aggressively window-edge artifacts are absorbed — setting it to 1 disables it entirely. Fewer parameters means less surface area for curve-fitting to historical data.
Default settings are optimised for BTC on the 1D timeframe. Optimize thresholds and lengths for different assets and timeframes before use.
Risk Warning
This indicator is provided for informational and educational purposes only. Past performance, including any results visible on historical bars, does not guarantee or imply future returns. All trading involves risk. You should not make trading decisions based solely on any single indicator. Always apply independent analysis and appropriate risk management.
Developed by GForge Indicator
SmartVol SuperTrend | OquantOverview
The SmartVol SuperTrend is an evolution of the traditional SuperTrend indicator. While the standard SuperTrend uses Average True Range (ATR) to calculate volatility bands, this version utilizes Volume-Weighted Standard Deviation (VWSD).
By integrating volume into the volatility calculation, the indicator attempts to filter out "quiet" price movements and reacts more dynamically to price action supported by high trading activity.
How It Works
The script follows a multi-step process to define trend direction:
Smoothing: It applies a 5-period EMA to the source price to reduce minor noise before calculating the bands.
Volume-Weighted Volatility: Instead of a simple Standard Deviation, the script uses a custom volume standard deviation function. It measures the dispersion of price around its Volume Weighted Moving Average (VWMA), weighting each price point's contribution by the volume of that bar.
Recursive Band Logic: Like the classic SuperTrend, the bands are "locked" in place. The lower band can only move up, and the upper band can only move down, until price closes on the opposite side, triggering a trend flip.
Visuals: The script highlights the trend by coloring the candles and the space between the price and the trend line, providing a clear visual of the current market bias.
Usefulness
By using Volume-Weighted Standard Deviation, this indicator accounts for real market activity. Consequently, it expands its bands more aggressively during high-volume breakouts while dampening its reaction to price moves when volume fades, potentially offering more robust band levels anchored to true market participation.
How to Use
Trend Identification: When the line is green and below price, the trend is bullish. When the line is purple and above price, the trend is bearish.
Factor Adjustment: Increase the Factor (default 1.8) to reduce sensitivity and avoid whipsaws in volatile markets. Decrease it for tighter tracking.
EMA Length: Adjust the EMA length to change how much price smoothing is applied before the trend calculation.
Note on Signals
This indicator is designed for trend-following. Like all lagging indicators, it performs best in trending markets and may produce false signals during sideways consolidation.
Settings
Source: The price source used for calculations (default: Close).
EMA Length: The lookback for the initial price smoothing (default: 5).
VWSD Length: The period used to calculate the volume-weighted volatility (default: 30).
Factor: The multiplier applied to the VWSD to determine the distance of the bands (default 1.8).
⚠️ Disclaimer: This indicator is intended for educational and informational purposes only. Trading involves risk, and past performance does not guarantee future results. Always test and evaluate indicators/strategies before applying them in live markets. Use at your own risk. Indicator
Open Interest Weighted Average Price [Arjo]Open Interest Weighted Average Price , or OIWAP , is a simple visual indicator that shows the average price of an asset based on changes in open interest .
Instead of using trading volume like VWAP, this indicator gives more weight to prices where new futures contracts are being added or removed . This helps highlight the price levels where traders are actively building or closing positions.
The indicator shows:
A main line that represents the average price weighted by open interest changes.
Upper and lower bands (standard deviation bands) that show how far the price moves away from this average.
OIWAP is mainly useful for NSE futures markets , where open interest data is available. It helps traders visually understand where most market participation and positioning are taking place relative to price .
Concepts:
Applies statistical concepts, including weighted averaging and standard deviation, to open interest data
Uses the absolute change in open interest as a weighting factor for each price point
Creates a dynamic average that reflects where significant open interest activity has occurred during a given period
Standard deviation bands are computed from this weighted average to show the statistical spread of prices around the OIWAP line
Resets calculations based on user-selected time periods (daily, weekly, monthly, or session-based)
Allows for fresh analysis at regular intervals
Similar concept to volume-weighted average price (VWAP) indicators, but uses open interest changes as the weighting component
Features:
Weighted Average: Calculates a central line based on contract activity.
Flexible Anchors: Allows users to choose the reset period for the calculation.
Volatility Bands: Displays outer and mid-bands to visualize price stretches.
Data Check: Built-in alerts notify you if Open Interest data is missing for a symbol.
Visual Zones: Color-coded areas help identify price location at a glance.
How To Use
When you add the indicator to your chart, you will see:
A main OIWAP line — the open-interest-weighted price level
Mid-bands around the line (±0.5 standard deviations)
Outer bands farther away (±2.0 standard deviations)
Shaded background zones between these lines
You can:
Change the reset period to see how the average behaves over different time ranges
Adjust the timeframe for open-interest data
Turn mid-bands on or off
Adjust colors and styles to improve readability
Conclusion
The OIWAP indicator serves as an educational tool for visualizing the relationship between price movements and open interest activity in futures markets
Presents a weighted average price line along with statistical deviation bands
Offers a structured framework for chart analysis
Customizable settings allow users to adapt the display to their analytical preferences
Maintains focus on visual interpretation rather than directional predictions
Functions as a supplementary charting overlay that may complement other forms of technical and fundamental analysis
Disclaimer
This indicator is for educational and visual-analysis purposes only. It does not provide trading signals, financial advice, or guaranteed outcomes . You should perform your own research and consult a licensed financial professional when needed. All trading decisions are solely the responsibility of the user. Indicator
Uptrick: Dynamic Z-Score DivergenceIntroduction
Uptrick: Dynamic Z-Score Divergence is an oscillator that combines multiple momentum sources within a Z-Score framework, allowing for the detection of statistically significant mean-reversion setups, directional shifts, and divergence signals. It integrates a multi-source normalized oscillator, a slope-based signal engine, structured divergence logic, a slope-adaptive EMA with dynamic bands, and a modular bar coloring system. This script is designed to help traders identify statistically stretched conditions, evolving trend dynamics, and classical divergence behavior using a unified statistical approach.
Overview
At its core, this script calculates the Z-Score of three momentum sources—RSI, Stochastic RSI, and MACD—using a user-defined lookback period. These are averaged and smoothed to form the main oscillator line. This normalized oscillator reflects how far short-term momentum deviates from its mean, highlighting statistically extreme areas.
Signals are triggered when the oscillator reverses slope within defined inner zones, indicating a shift in direction while the signal remains in a statistically stretched state. These mean-reversion flips (referred to as TP signals) help identify turning points when price momentum begins to revert from extended zones.
In addition, the script includes a divergence detection engine that compares oscillator pivot points with price pivot points. It confirms regular bullish and bearish divergence by validating spacing between pivots and visualizes both the oscillator-side and chart-side divergences clearly.
A dynamic trend overlay system is included using a Slope Adaptive EMA (SA-EMA). This trend line becomes more responsive when Z-Score deviation increases, allowing the trend line to adapt to market conditions. It is paired with ATR-based bands that are slope-sensitive and selectively visible—offering context for dynamic support and resistance.
The script includes configurable bar coloring logic, allowing users to color candles based on oscillator slope, last confirmed divergence, or the most recent signal of any type. A full alert system is also built-in for key signals.
Originality
The script is based on the well-known concept of Z-Score valuation, which is a standard statistical method for identifying how far a signal deviates from its mean. This foundation—normalizing momentum values such as RSI or MACD to measure relative strength or weakness—is not unique to this script and is widely used in quantitative analysis.
What makes this implementation original is how it expands the Z-Score foundation into a fully featured, signal-producing system. First, it introduces a multi-source composite oscillator by combining three momentum inputs—RSI, Stochastic RSI, and MACD—into a unified Z-Score stream. Second, it builds on that stream with a directional slope logic that identifies turning points inside statistical zones.
The most distinctive additions are the layered features placed on top of this normalized oscillator:
A structured divergence detection engine that compares oscillator pivots with price pivots to validate regular bullish and bearish divergence using precise spacing and timing filters.
A fully integrated slope-adaptive EMA overlay, where the smoothing dynamically adjusts based on real-time Z-Score movement of RSI, allowing the trend line to become more reactive during high-momentum environments and slower during consolidation.
ATR-based dynamic bands that adapt to slope direction and offer real-time visual zones for support and resistance within trend structures.
These features are not typically found in standard Z-Score indicators and collectively provide a unique approach that bridges statistical normalization, structure detection, and adaptive trend modeling within one script.
Features
Z-Score-based oscillator combining RSI, StochRSI, and MACD
Configurable smoothing for stable composite signal output
Buy/Sell TP signals based on slope flips in defined zones
Background highlighting for extreme outer bands
Inner and outer zones with fill logic for statistical context
Pivot-based divergence detection (regular bullish/bearish)
Divergence markers on oscillator and price chart
Slope-Adaptive EMA (SA-EMA) with real-time adaptivity based on RSI Z-Score
ATR-based upper and lower bands around the SA-EMA, visibility tied to slope direction
Configurable bar coloring (oscillator slope, divergence, or most recent signal)
Alerts for TP signals and confirmed divergences
Optional fixed Y-axis scaling for consistent oscillator view
The full setup mode can be seen below:
Input Parameters
General Settings
Full Setup: Enables rendering of the full visual system (lines, bands, signals)
Z-Score Lookback: Lookback period for normalization (mean and standard deviation)
Main Line Smoothing: EMA length applied to the averaged Z-Score
Slope Detection Index: Used to calculate directional flips for signal logic
Enable Background Highlighting: Enables visual region coloring in
overbought/oversold areas
Force Visible Y-Axis Scale: Forces max/min bounds for a consistent oscillator range
Divergence Settings
Enable Divergence Detection: Toggles divergence logic
Pivot Lookback Left / Right: Defines the structure of oscillator pivot points
Minimum / Maximum Bars Between Pivots: Controls the allowed spacing range for divergence validation
Bar Coloring Settings
Bar Coloring Mode:
➜ Line Color: Colors bars based on oscillator slope
➜ Latest Confirmed Signal: Colors bars based on the most recent confirmed divergence
➜ Any Latest Signal: Colors based on the most recent signal (TP or divergence)
SA-EMA Settings
RSI Length: RSI period used to determine adaptivity
Z-Score Length: Lookback for normalizing RSI in adaptive logic
Base EMA Length: Base length for smoothing before adaptivity
Adaptivity Intensity: Scales the smoothing responsiveness based on RSI deviation
Slope Index: Determines slope direction for coloring and band logic
Band ATR Length / Band Multiplier: Controls the width and responsiveness of the trend-following bands
Alerts
The script includes the following alert conditions:
Buy Signal (TP reversal detected in oversold zone)
Sell Signal (TP reversal detected in overbought zone)
Confirmed Bullish Divergence (oscillator HL, price LL)
Confirmed Bearish Divergence (oscillator LH, price HH)
These alerts allow integration into automation systems or signal monitoring setups.
Summary
Uptrick: Dynamic Z-Score Divergence is a statistically grounded trading indicator that merges normalized multi-momentum analysis with real-time slope logic, divergence detection, and adaptive trend overlays. It helps traders identify mean-reversion conditions, divergence structures, and evolving trend zones using a modular system of statistical and structural tools. Its alert system, layered visuals, and flexible input design make it suitable for discretionary traders seeking to combine quantitative momentum logic with structural pattern recognition.
Disclaimer
This script is for educational and informational purposes only. No indicator can guarantee future performance, and trading involves risk. Always use risk management and test strategies in a simulated environment before deploying with live capital.
Indicator
Indicator
Kernel Regression Bands SuiteMulti-Kernel Regression Bands
A versatile indicator that applies kernel regression smoothing to price data, then dynamically calculates upper and lower bands using a wide variety of deviation methods. This tool is designed to help traders identify trend direction, volatility, and potential reversal zones with customizable visual styles.
Key Features
Multiple Kernel Types: Choose from 17+ kernel regression styles (Gaussian, Laplace, Epanechnikov, etc.) for smoothing.
Flexible Band Calculation: Select from 12+ deviation types including Standard Deviation, Mean/Median Absolute Deviation, Exponential, True Range, Hull, Parabolic SAR, Quantile, and more.
Adaptive Bands: Bands are calculated around the kernel regression line, with a user-defined multiplier.
Signal Logic: Trend state is determined by crossovers/crossunders of price and bands, coloring the regression line and band fills accordingly.
Custom Color Modes: Six unique color palettes for visual clarity and personal preference.
Highly Customizable Inputs: Adjust kernel type, lookback, deviation method, band source, and more.
How to Use
Trend Identification: The regression line changes color based on the detected trend (up/down)
Volatility Zones: Bands expand/contract with volatility, helping spot breakouts or mean-reversion opportunities.
Visual Styling: Use color modes to match your chart theme or highlight specific market states.
Credits:
Kernel regression logic adapted from:
ChartPrime | Multi-Kernel-Regression-ChartPrime (Link in the script)
Disclaimer
This script is for educational and informational purposes only. Not financial advice. Use at your own risk. Indicator
Standard Deviation (fadi)The Standard Deviation indicator uses standard deviation to map out price movements. Standard deviation measures how much prices stray from their average—small values mean steady trends, large ones mean wild swings. Drawing from up to 20 years of data, it plots key levels using customizable Fibonacci lines tied to that standard deviation, giving traders a snapshot of typical price behavior.
These levels align with a bell curve: about 68% of price moves stay within 1 standard deviation, 95% within roughly 2, and 99.7% within roughly 3. When prices break past the 1 StDev line, they’re outliers—only 32% of moves go that far. Prices often snap back to these lines or the average, though the reversal might not happen the same day.
How Traders Use It
If prices surge past the 1 StDev line, traders might wait for momentum to fade, then trade the pullback to that line or the average, setting a target and stop.
If prices dip below, they might buy, anticipating a bounce—sometimes a day or two later. It’s a tool to spot overstretched prices likely to revert and/or measure the odds of continuation.
Settings
Higher Timeframe: Sets the Higher Timeframe to calculate the Standard Deviation for
Show Levels for the Last X Days: Displays levels for the specified number of days.
Based on X Period: Number of days to calculate standard deviation (e.g., 20 years ≈ 5,040 days). Larger periods smooth out daily level changes.
Mirror Levels on the Other Side: Plots symmetric positive and negative levels around the average.
Fibonacci Levels Settings: Defines which levels and line styles to show. With mirroring, negative values aren’t needed.
Background Transparency: Turn on Background color derived from the level colors with the specified transparency
Overrides: Lets advanced users input custom standard deviations for specific tickers (e.g., NQ1! at 0.01296).
Indicator
Volume Block Order AnalyzerCore Concept
The Volume Block Order Analyzer is a sophisticated Pine Script strategy designed to detect and analyze institutional money flow through large block trades. It identifies unusually high volume candles and evaluates their directional bias to provide clear visual signals of potential market movements.
How It Works: The Mathematical Model
1. Volume Anomaly Detection
The strategy first identifies "block trades" using a statistical approach:
```
avgVolume = ta.sma(volume, lookbackPeriod)
isHighVolume = volume > avgVolume * volumeThreshold
```
This means a candle must have volume exceeding the recent average by a user-defined multiplier (default 2.0x) to be considered a significant block trade.
2. Directional Impact Calculation
For each block trade identified, its price action determines direction:
- Bullish candle (close > open): Positive impact
- Bearish candle (close < open): Negative impact
The magnitude of impact is proportional to the volume size:
```
volumeWeight = volume / avgVolume // How many times larger than average
blockImpact = (isBullish ? 1.0 : -1.0) * (volumeWeight / 10)
```
This creates a normalized impact score typically ranging from -1.0 to 1.0, scaled by dividing by 10 to prevent excessive values.
3. Cumulative Impact with Time Decay
The key innovation is the cumulative impact calculation with decay:
```
cumulativeImpact := cumulativeImpact * impactDecay + blockImpact
```
This mathematical model has important properties:
- Recent block trades have stronger influence than older ones
- Impact gradually "fades" at rate determined by decay factor (default 0.95)
- Sustained directional pressure accumulates over time
- Opposing pressure gradually counteracts previous momentum
Trading Logic
Signal Generation
The strategy generates trading signals based on momentum shifts in institutional order flow:
1. Long Entry Signal: When cumulative impact crosses from negative to positive
```
if ta.crossover(cumulativeImpact, 0)
strategy.entry("Long", strategy.long)
```
*Logic: Institutional buying pressure has overcome selling pressure, indicating potential upward movement*
2. Short Entry Signal: When cumulative impact crosses from positive to negative
```
if ta.crossunder(cumulativeImpact, 0)
strategy.entry("Short", strategy.short)
```
*Logic: Institutional selling pressure has overcome buying pressure, indicating potential downward movement*
3. Exit Logic: Positions are closed when the cumulative impact moves against the position
```
if cumulativeImpact < 0
strategy.close("Long")
```
*Logic: The original signal is no longer valid as institutional flow has reversed*
Visual Interpretation System
The strategy employs multiple visualization techniques:
1. Color Gradient Bar System:
- Deep green: Strong buying pressure (impact > 0.5)
- Light green: Moderate buying pressure (0.1 < impact ≤ 0.5)
- Yellow-green: Mild buying pressure (0 < impact ≤ 0.1)
- Yellow: Neutral (impact = 0)
- Yellow-orange: Mild selling pressure (-0.1 < impact ≤ 0)
- Orange: Moderate selling pressure (-0.5 < impact ≤ -0.1)
- Red: Strong selling pressure (impact ≤ -0.5)
2. Dynamic Impact Line:
- Plots the cumulative impact as a line
- Line color shifts with impact value
- Line movement shows momentum and trend strength
3. Block Trade Labels:
- Marks significant block trades directly on the chart
- Shows direction and volume amount
- Helps identify key moments of institutional activity
4. Information Dashboard:
- Current impact value and signal direction
- Average volume benchmark
- Count of significant block trades
- Min/Max impact range
Benefits and Use Cases
This strategy provides several advantages:
1. Institutional Flow Detection: Identifies where large players are positioning themselves
2. Early Trend Identification: Often detects institutional accumulation/distribution before major price movements
3. Market Context Enhancement: Provides deeper insight than simple price action alone
4. Objective Decision Framework: Quantifies what might otherwise be subjective observations
5. Adaptive to Market Conditions: Works across different timeframes and instruments by using relative volume rather than absolute thresholds
Customization Options
The strategy allows users to fine-tune its behavior:
- Volume Threshold: How unusual a volume spike must be to qualify
- Lookback Period: How far back to measure average volume
- Impact Decay Factor: How quickly older trades lose influence
- Visual Settings: Labels and line width customization
This sophisticated yet intuitive strategy provides traders with a window into institutional activity, helping identify potential trend changes before they become obvious in price action alone.
Strategy
Daily Standard Deviation (fadi)The Daily Standard Deviation indicator uses standard deviation to map out daily price movements. Standard deviation measures how much prices stray from their average—small values mean steady trends, large ones mean wild swings. Drawing from up to 20 years of data, it plots key levels using customizable Fibonacci lines tied to that standard deviation, giving traders a snapshot of typical price behavior.
These levels align with a bell curve: about 68% of price moves stay within 1 standard deviation, 95% within roughly 2, and 99.7% within roughly 3. When prices break past the 1 StDev line, they’re outliers—only 32% of moves go that far. Prices often snap back to these lines or the average, though the reversal might not happen the same day.
How Traders Use It
If prices surge past the 1 StDev line, traders might wait for momentum to fade, then trade the pullback to that line or the average, setting a target and stop.
If prices dip below, they might buy, anticipating a bounce—sometimes a day or two later. It’s a tool to spot overstretched prices likely to revert and/or measure the odds of continuation.
Settings
Open Hour: Sets the trading day’s start (default: 18:00 EST).
Show Levels for the Last X Days: Displays levels for the specified number of days.
Based on X Period: Number of days to calculate standard deviation (e.g., 20 years ≈ 5,040 days). Larger periods smooth out daily level changes.
Mirror Levels on the Other Side: Plots symmetric positive and negative levels around the average.
Fibonacci Levels Settings: Defines which levels and line styles to show. With mirroring, negative values aren’t needed.
Overrides: Lets advanced users input custom standard deviations for specific tickers (e.g., NQ1! at 0.01296). Indicator
Prime Bands [ChartPrime]The Prime Standard Deviation Bands indicator uses custom-calculated bands based on highest and lowest price values over specific period to analyze price volatility and trend direction. Traders can set the bands to 1, 2, or 3 standard deviations from a central base, providing a dynamic view of price behavior in relation to volatility. The indicator also includes color-coded trend signals, standard deviation labels, and mean reversion signals, offering insights into trend strength and potential reversal points.
⯁ KEY FEATURES AND HOW TO USE
⯌ Standard Deviation Bands :
The indicator plots upper and lower bands based on standard deviation settings (1, 2, or 3 SDs) from a central base, allowing traders to visualize volatility and price extremes. These bands can be used to identify overbought and oversold conditions, as well as potential trend reversals.
Example of 3-standard-deviation bands around price:
⯌ Dynamic Trend Indicator :
The midline of the bands changes color based on trend direction. If the midline is rising, it turns green, indicating an uptrend. When the midline is falling, it turns orange, suggesting a downtrend. This color coding provides a quick visual reference to the current trend.
Trend color examples for rising and falling midlines:
⯌ Standard Deviation Labels :
At the end of the bands, the indicator displays labels with price levels for each standard deviation level (+3, 0, -3, etc.), helping traders quickly reference where price is relative to its statistical boundaries.
Price labels at each standard deviation level on the chart:
⯌ Mean Reversion Signals :
When price moves beyond the upper or lower bands and then reverts back inside, the indicator plots mean reversion signals with diamond icons. These signals indicate potential reversal points where the price may return to the mean after extreme moves.
Example of mean reversion signals near bands:
⯌ Standard Deviation Scale on Chart :
A visual scale on the right side of the chart shows the current price position in relation to the bands, expressed in standard deviations. This scale provides an at-a-glance view of how far price has deviated from the mean, helping traders assess risk and volatility.
⯁ USER INPUTS
Length : Sets the number of bars used in the calculation of the bands.
Standard Deviation Level : Allows selection of 1, 2, or 3 standard deviations for upper and lower bands.
Colors : Customize colors for the uptrend and downtrend midline indicators.
⯁ CONCLUSION
The Prime Standard Deviation Bands indicator provides a comprehensive view of price volatility and trend direction. Its customizable bands, trend coloring, and mean reversion signals allow traders to effectively gauge price behavior, identify extreme conditions, and make informed trading decisions based on statistical boundaries. Indicator
HMA Gaussian Volatility AdjustedOverview
The "HMA Gaussian Volatility Adjusted" indicator introduces a unique combination of HMA smoothing with a Gaussian filter and two components to measure volatility (Average True Range (ATR) and Standard Deviation (SD)). This tool provides traders with a stable and accurate measure of price trends by integrating a Gaussian Filter smoothed using HMA with a customized calculation of volatility. This innovative approach allows for enhanced sensitivity to market fluctuations while filtering out short-term price noise.
Technical Composition and Calculation
The "HMA Gaussian Volatility Adjusted" indicator incorporates HMA smoothing and dynamic standard deviation calculations to build upon traditional volatility measures.
HMA & Gaussian Smoothing:
HMA Calculation (HMA_Length): The script applies a Hull Moving Average (HMA) to smooth the price data over a user-defined period, reducing noise and helping focus on broader market trends.
Gaussian Filter Calculation (Length_Gaussian): The smoothed HMA data is further refined by putting it into a Gaussian filter to incorporate a normal distribution.
Volatility Measurement:
ATR Calculation (ATR_Length, ATR_Factor): The indicator incorporates the Average True Range (ATR) to measure market volatility. The user-defined ATR multiplier is applied to this value to calculate upper and lower trend bands around the Gaussian, providing a dynamic measure of potential price movement based on recent volatility.
Standard Deviation Calculation (SD_Length): The script calculates the standard deviation of the price over a user-defined length, providing another layer of volatility measurement. The upper and lower standard deviation bands (SDD, SDU) act as additional indicators of price extremes.
Momentum Calculation & Scoring
When the indicator signals SHORT:
Diff = Price - Upper Boundary of the Standard Deviation (calculated on a Gaussian filter).
When the indicator signals LONG:
Diff = Price - Upper Boundary of the ATR (calculated on a Gaussian filter).
The calculated Diff signals how close the indicator is to changing trends. An EMA is applied to the Diff to smooth the data. Positive momentum occurs when the Diff is above the EMA, and negative momentum occurs when the Diff is below the EMA.
Trend Detection
Trend Logic: The indicator uses the calculated bands to identify whether the price is moving within or outside the standard deviation and ATR bands. Crosses above or below these bands, combined with positive/negative momentum, signals potential uptrends or downtrends, offering traders a clear view of market direction.
Features and User Inputs
The "HMA Gaussian Volatility Adjusted" script offers a variety of user inputs to customize the indicator to suit traders' styles and market conditions:
HMA Length: Allows traders to adjust the sensitivity of the HMA smoothing to control the amount of noise filtered from the price data.
Gaussian Length: Users can define the length at which the Gaussian filter is applied.
ATR Length and Multiplier: These inputs let traders fine-tune the ATR calculation, affecting the size of the dynamic upper and lower bands to adjust for price volatility.
Standard Deviation Length: Controls how the standard deviation is calculated, allowing further customization in detecting price volatility.
EMA Confluence: This input lets traders determine the length of the EMA used to calculate price momentum.
Type of Plot Setting: Allows users to determine how the indicator signal is plotted on the chart (Background color, Trend Lines, BOTH (backgroung color and Trend Lines)).
Transparency: Provides users with customization of the background color's transparency.
Color Long/Short: Offers users the option to choose their preferred colors for both long and short signals.
Summary and Usage Tips
The "HMA Gaussian Volatility Adjusted" indicator is a powerful tool for traders looking to refine their analysis of market trends and volatility. Its combination of HMA smoothing, Gaussian filtering, and standard deviation analysis provides a nuanced view of market movements by incorporating various metrics to determine direction, momentum, and volatility. This helps traders make better-informed decisions. It's recommended to experiment with the various input parameters to optimize the indicator for specific needs.
Indicator
Dema Percentile Standard DeviationDema Percentile Standard Deviation
The Dema Percentile Standard Deviation indicator is a robust tool designed to identify and follow trends in financial markets.
How it works?
This code is straightforward and simple:
The price is smoothed using a DEMA (Double Exponential Moving Average).
Percentiles are then calculated on that DEMA.
When the closing price is below the lower percentile, it signals a potential short.
When the closing price is above the upper percentile and the Standard Deviation of the lower percentile, it signals a potential long.
Settings
Dema/Percentile/SD/EMA Length's: Defines the period over which calculations are made.
Dema Source: The source of the price data used in calculations.
Percentiles: Selects the type of percentile used in calculations (options include 60/40, 60/45, 55/40, 55/45). In these settings, 60 and 55 determine percentile for long signals, while 45 and 40 determine percentile for short signals.
Features
Fully Customizable
Fully Customizable: Customize colors to display for long/short signals.
Display Options: Choose to show long/short signals as a background color, as a line on price action, or as trend momentum in a separate window.
EMA for Confluence: An EMA can be used for early entries/exits for added signal confirmation, but it may introduce noise—use with caution!
Built-in Alerts.
Indicator on Diffrent Assets
INDEX:BTCUSD 1D Chart (6 high 56 27 60/45 14)
CRYPTO:SOLUSD 1D Chart (24 open 31 20 60/40 14)
CRYPTO:RUNEUSD 1D Chart (10 close 56 14 60/40 14)
Remember no indicator would on all assets with default setting so FAFO with setting to get your desired signal.
Indicator
STANDARD DEVIATION INDICATOR BY WISE TRADERWISE TRADER STANDARD DEVIATION SETUP: The Ultimate Volatility and Trend Analysis Tool
Unlock the power of STANDARD DEVIATIONS like never before with the this indicator, a versatile and comprehensive tool designed for traders who seek deeper insights into market volatility, trend strength, and price action. This advanced indicator simultaneously plots three sets of customizable Deviations, each with unique settings for moving average types, standard deviations, and periods. Whether you’re a swing trader, day trader, or long-term investor, the STANDARD DEVIATION indicator provides a dynamic way to spot potential reversals, breakouts, and trend-following opportunities.
Key Features:
STANDARD DEVIATIONS Configuration : Monitor three different Bollinger Bands at the same time, allowing for multi-timeframe analysis within a single chart.
Customizable Moving Average Types: Choose from SMA, EMA, SMMA (RMA), WMA, and VWMA to calculate the basis of each band according to your preferred method.
Dynamic Standard Deviations: Set different standard deviation multipliers for each band to fine-tune sensitivity for various market conditions.
Visual Clarity: Color-coded bands with adjustable thicknesses provide a clear view of upper and lower boundaries, along with fill backgrounds to highlight price ranges effectively.
Enhanced Trend Detection: Identify potential trend continuation, consolidation, or reversal zones based on the position and interaction of price with the three bands.
Offset Adjustment: Shift the bands forward or backward to analyze future or past price movements more effectively.
Why Use Triple STANDARD DEVIATIONS ?
STANDARD DEVIATIONS are a popular choice among traders for measuring volatility and anticipating potential price movements. This indicator takes STANDARD DEVIATIONS to the next level by allowing you to customize and analyze three distinct bands simultaneously, providing an unparalleled view of market dynamics. Use it to:
Spot Volatility Expansion and Contraction: Track periods of high and low volatility as prices move toward or away from the bands.
Identify Overbought or Oversold Conditions: Monitor when prices reach extreme levels compared to historical volatility to gauge potential reversal points.
Validate Breakouts: Confirm the strength of a breakout when prices move beyond the outer bands.
Optimize Risk Management: Enhance your strategy's risk-reward ratio by dynamically adjusting stop-loss and take-profit levels based on band positions.
Ideal For:
Forex, Stocks, Cryptocurrencies, and Commodities Traders looking to enhance their technical analysis.
Scalpers and Day Traders who need rapid insights into market conditions.
Swing Traders and Long-Term Investors seeking to confirm entry and exit points.
Trend Followers and Mean Reversion Traders interested in combining both strategies for maximum profitability.
Harness the full potential of STANDARD DEVIATIONS with this multi-dimensional approach. The "STANDARD DEVIATIONS " indicator by WISE TRADER will become an essential part of your trading arsenal, helping you make more informed decisions, reduce risks, and seize profitable opportunities.
Who is WISE TRADER ?
Wise Trader is a highly skilled trader who launched his channel in 2020 during the COVID-19 pandemic, quickly building a loyal following. With thousands of paid subscribed members and over 70,000 YouTube subscribers, Wise Trader has become a trusted authority in the trading world. He is known for his ability to navigate significant events, such as the Indian elections and stock market crashes, providing his audience with valuable insights into market movements and volatility. With a deep understanding of macroeconomics and its correlation to global stock markets, Wise Trader shares informed strategies that help traders make better decisions. His content covers technical analysis, trading setups, economic indicators, and market trends, offering a comprehensive approach to understanding financial markets. The channel serves as a go-to resource for traders who want to enhance their skills and stay informed about key market developments.
Indicator
E9 Bollinger RangeThe E9 Bollinger Range is a technical trading tool that leverages Bollinger Bands to track volatility and price deviations, along with additional trend filtering via EMAs.
The script visually enhances price action with a combination of trend-filtering EMAs, bar colouring for trend direction, signals to indicate potential buy and sell points based on price extension and engulfing patterns.
Here’s a breakdown of its key components:
Bollinger Bands: The strategy plots multiple Bollinger Band deviations to create different price levels. The furthest deviation bands act as warning signs for traders when price extends significantly, signaling potential overbought or oversold conditions.
Bar Colouring: Visual bar colouring is applied to clearly indicate trend direction: green bars for an uptrend and red bars for a downtrend.
EMA Filtering: Two EMAs (50 and 200) are used to help filter out false signals, giving traders a better sense of the underlying trend.
This combination of signals, visual elements, and trend filtering provides traders with a systematic approach to identifying price deviations and taking advantage of market corrections.
Brief History of Bollinger Bands
Bollinger Bands were developed by John Bollinger in the early 1980s as a tool to measure price volatility in financial markets. The bands consist of a moving average (typically 20 periods) with upper and lower bands placed two standard deviations away. These bands expand and contract based on market volatility, offering traders a visual representation of price extremes and potential reversal zones.
John Bollinger’s work revolutionized technical analysis by incorporating volatility into trend detection. His bands remain widely used across markets, including stocks, commodities, and cryptocurrencies. With the ability to highlight overbought and oversold conditions, Bollinger Bands have become a staple in many trading strategies. Indicator
