Donchian Predictive Channel (Zeiierman)█ Overview
Donchian Predictive Channel (Zeiierman) extends the classic Donchian framework into a predictive structure. It does not just track where the range has been; it projects where the Donchian mid, high, and low boundaries are statistically likely to move based on recent directional bias and volatility regime.
By quantifying the linear drift of the Donchian midline and the expansion or compression rate of the Donchian range, the indicator generates a forward propagation cone that reflects the prevailing trend and volatility state. This produces a cleaner, more analytically grounded projection of future price corridors, and it remains fully aligned with the signal precision of the underlying Donchian logic.
█ How It Works
⚪ Donchian Core
The script first computes a standard Donchian Channel over a configurable Length:
Upper Band (dcHi) – highest high over the lookback.
Lower Band (dcLo) – lowest low over the lookback.
Midline (dcMd) – simple midpoint of upper and lower: (dcHi + dcLo)/ 2.
f_getDonchian(length) =>
hi = ta.highest(high, length)
lo = ta.lowest(low, length)
md = (hi + lo) * 0.5
= f_getDonchian(lenDC)
⚪ Slope Estimation & Range Dynamics
To turn the Donchian Channel into a predictive model, the script measures how both the midline and the range are changing over time:
Midline Slope (mSl) – derived from a 1-bar difference in linear regression of the midline.
Range Slope (rSl) – derived from a 1-bar difference in linear regression of the Donchian range (dcHi − dcLo).
This pair describes both directional drift (uptrend vs. downtrend) and range expansion/compression (volatility regime).
f_getSlopes(midLine, rngVal, length) =>
mSl = ta.linreg(midLine, length, 0) - ta.linreg(midLine, length, 1)
rSl = ta.linreg(rngVal, length, 0) - ta.linreg(rngVal, length, 1)
⚪ Forward Projection Engine
At the last bar, the indicator constructs a set of forward points for the mid, upper, and lower projections over Forecast Bars:
The midline is projected linearly using the midline slope per bar.
The range is adjusted using the range slope per bar, creating either a widening cone (expansion) or a tightening cone (compression).
Upper and lower projections are then anchored around the projected midline, with logic that keeps the structure consistent and prevents pathological flips when slope changes sign.
f_generatePoints(hi0, md0, lo0, steps, midSlp, rngSlp) =>
upPts = array.new()
mdPts = array.new()
dnPts = array.new()
fillPts = array.new()
hi_vals = array.new_float()
md_vals = array.new_float()
lo_vals = array.new_float()
curHiLocal = hi0
curLoLocal = lo0
curMidLocal = md0
segBars = math.floor(steps / 3)
segBars := segBars < 1 ? 1 : segBars
for b = 0 to steps
mdProj = md0 + midSlp * b
prevRange = curHiLocal - curLoLocal
rngProj = prevRange + rngSlp * b
hiTemp = 0.0
loTemp = 0.0
if midSlp >= 0
hiTemp := math.max(curHiLocal, mdProj + rngProj * 0.5)
loTemp := math.max(curLoLocal, mdProj - rngProj * 0.5)
else
hiTemp := math.min(curHiLocal, mdProj + rngProj * 0.5)
loTemp := math.min(curLoLocal, mdProj - rngProj * 0.5)
hiProj = hiTemp < mdProj ? curHiLocal : hiTemp
loProj = loTemp > mdProj ? curLoLocal : loTemp
if b % segBars == 0
curHiLocal := hiProj
curLoLocal := loProj
curMidLocal := mdProj
array.push(hi_vals, curHiLocal)
array.push(md_vals, curMidLocal)
array.push(lo_vals, curLoLocal)
array.push(upPts, chart.point.from_index(bar_index + b, curHiLocal))
array.push(mdPts, chart.point.from_index(bar_index + b, curMidLocal))
array.push(dnPts, chart.point.from_index(bar_index + b, curLoLocal))
ptSet.new(upPts, mdPts, dnPts)
⚪ Rejection Signals
The script also tracks failed Donchian breakouts and marks them as potential reversal/reversion cues:
Signal Down: Triggered when price makes an attempt above the upper Donchian band but then pulls back inside and closes above the midline, provided enough bars have passed since the last signal.
Signal Up: Triggered when price makes an attempt below the lower Donchian band but then snaps back inside and closes below the midline, also requiring sufficient spacing from the previous signal.
// Base signal conditions (unfiltered)
bearCond = high < dcHi and high >= dcHi and close > dcMd and bar_index - lastMarker >= lenDC
bullCond = low > dcLo and low <= dcLo and close < dcMd and bar_index - lastMarker >= lenDC
// Apply MA filter if enabled
if signalfilter
bearCond := bearCond and close < ma // Bearish only below MA
bullCond := bullCond and close > ma // Bullish only above MA
signalUp := false
signalDn := false
if bearCond
lastMarker := bar_index
signalDn := true
if bullCond
lastMarker := bar_index
signalUp := true
█ How to Use
The Donchian Predictive Channel is designed to outline possible future price trajectories. Treat it as a directional guide, not a fixed prediction tool.
⚪ Map Future Support & Resistance
Use the projected upper and lower paths as dynamic future reference levels:
Projected upper band ≈ is likely a resistance corridor if the current trend and volatility persist.
Projected lower band ≈ likely support corridor or expected downside range.
⚪ Trend Path & Volatility Cone
Because the projection is driven by midline and range slopes, the channel behaves like a trend + volatility cone:
Steep positive midline slope + expanding range → accelerating, high-volatility trend.
Flat midline + compressing range → coiling/contracting regime ahead of potential expansion.
This helps you distinguish between a gentle drift and an aggressive move that likely needs more risk buffer.
⚪ Reversion & Rejection Signals
The Donchian-based signals are especially useful for mean-reversion and fade-style trades.
A Signal Down near the upper band can mark a failed breakout and a potential rotation back toward the midline or the lower projected band.
A Signal Up near the lower band can flag a failed breakdown and a potential snap-back up the channel.
When Filter Signals is enabled, these signals are only generated when they align with the chart’s directional bias as defined by the moving average. Bullish signals are allowed only when the price is above the MA, and bearish signals only when the price is below it.
This reduces noise and helps ensure that reversions occur in harmony with the prevailing trend environment.
█ Settings
Length – Donchian lookback length. Higher values produce a smoother channel with fewer but more stable signals. Lower values make the channel more reactive and increase sensitivity at the cost of more noise.
Forecast Bars – Number of bars used for projecting the Donchian channel forward.
Higher values create a broader, longer-term projection. Lower values focus on short-horizon price path scenarios.
Filter Signals – Enables directional filtering of Donchian signals using the selected moving average. When ON, bullish signals only trigger when the price is above the MA, and bearish signals only trigger when the price is below it. This helps reduce noise and aligns reversions with the broader trend context.
Moving Average Type – The type of moving average used for signal filtering and optional plotting.
Choose between SMA, EMA, WMA, or HMA depending on desired responsiveness. Faster averages (EMA, HMA) react quickly, while slower ones (SMA, WMA) smooth out short-term noise.
Moving Average Length – Lookback length of the moving average. Higher values create a slower, more stable trend filter. Lower values track price more tightly and can flip the directional bias more frequently.
-----------------
Disclaimer
The content provided in my scripts, indicators, ideas, algorithms, and systems is for educational and informational purposes only. It does not constitute financial advice, investment recommendations, or a solicitation to buy or sell any financial instruments. I will not accept liability for any loss or damage, including without limitation any loss of profit, which may arise directly or indirectly from the use of or reliance on such information.
All investments involve risk, and the past performance of a security, industry, sector, market, financial product, trading strategy, backtest, or individual's trading does not guarantee future results or returns. Investors are fully responsible for any investment decisions they make. Such decisions should be based solely on an evaluation of their financial circumstances, investment objectives, risk tolerance, and liquidity needs.
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RSI Divergence (Regular + Hidden, @darshakssc)This indicator detects regular and hidden divergence between price and RSI, using confirmed swing highs and swing lows (pivots) on both series. It is designed as a visual analysis tool, not as a signal generator or trading system.
The goal is to highlight moments where price action and RSI momentum move in different directions, which some traders study as potential early warnings of trend exhaustion or trend continuation. All divergence signals are only drawn after a pivot is fully confirmed, helping to avoid repainting.
The script supports four divergence types:
Regular Bullish Divergence
Regular Bearish Divergence
Hidden Bullish Divergence
Hidden Bearish Divergence
Each type is drawn with a different color and labeled clearly on the chart.
Core Concepts Used
1. RSI (Relative Strength Index)
The script uses standard RSI, calculated on a configurable input source (default: close) and length (default: 14).
RSI is treated purely as a momentum oscillator – the script does not enforce oversold/overbought interpretations.
2. Pivots / Swings
The indicator defines swing highs and swing lows using ta.pivothigh() and ta.pivotlow():
A swing high forms when a bar’s high is higher than a specified number of bars to the left and to the right.
A swing low forms when a bar’s low is lower than a specified number of bars to the left and to the right.
The same pivot logic is applied to both price and RSI.
Because pivots require “right side” bars to form, the indicator:
Waits for the full pivot to be confirmed (no forward-looking referencing beyond the rightBars parameter).
Only then considers that pivot for divergence detection.
This helps prevent repainting of divergence signals.
How Divergence Is Detected
The script always uses the two most recent confirmed pivots for both price and RSI. It tracks:
Last two swing lows in price and RSI
Last two swing highs in price and RSI
Their pivot bar indexes and values
A basic minimum distance filter between the pivots (in bars) is also applied to reduce noise.
1. Regular Bullish Divergence
Condition:
Price makes a lower low (LL) between the last two lows
RSI makes a higher low (HL) over the same two pivot lows
The RSI difference between the two lows is greater than or equal to the user-defined minimum (Min RSI Difference)
The two low pivots are separated by at least Min Bars Between Swings
Interpretation:
Some traders view this as bearish momentum weakening while price prints a new low. The script only marks this structure; it does not assume any outcome.
On the chart:
Drawn between the previous and current price swing lows
Labeled: “Regular Bullish”
Color: Green (by default in the script)
2. Regular Bearish Divergence
Condition:
Price makes a higher high (HH) between the last two highs
RSI makes a lower high (LH) over the same two pivot highs
RSI difference exceeds Min RSI Difference
Pivots are separated by at least Min Bars Between Swings
Interpretation:
Some traders see this as bullish momentum weakening while price prints a new high. Again, the indicator simply highlights this divergence.
On the chart:
Drawn between the previous and current price swing highs
Labeled: “Regular Bearish”
Color: Red
3. Hidden Bullish Divergence
Condition:
Price makes a higher low (HL) between the last two lows
RSI makes a lower low (LL) over the same two lows
RSI difference exceeds Min RSI Difference
Pivots meet the minimum distance requirement
Interpretation:
Some traders interpret hidden bullish divergence as a potential trend continuation signal within an existing uptrend. The indicator does not classify trends; it just tags the pattern when price and RSI pivots meet the conditions.
On the chart:
Drawn between the previous and current price swing lows
Labeled: “Hidden Bullish”
Color: Teal
4. Hidden Bearish Divergence
Condition:
Price makes a lower high (LH) between the last two highs
RSI makes a higher high (HH) over those highs
RSI difference exceeds Min RSI Difference
Pivots meet the minimum distance filter
Interpretation:
Some traders associate hidden bearish divergence with potential downtrend continuation, but again, this script only visualizes the structure.
On the chart:
Drawn between the previous and current price swing highs
Labeled: “Hidden Bearish”
Color: Orange
Inputs and Settings
1. RSI Settings
RSI Source – Price source for RSI (default: close).
RSI Length – Period for RSI calculation (default: 14).
These control the responsiveness of the RSI. Shorter lengths may show more frequent divergence; longer lengths smooth the signal.
2. Swing / Pivot Settings
Left Swing Bars (leftBars)
Right Swing Bars (rightBars)
These define how strict the pivot detection is:
Higher values → fewer, more significant swings
Lower values → more swings, more signals
Because the script uses ta.pivothigh / ta.pivotlow, a pivot is only confirmed once rightBars candles have closed after the candidate bar. This is an intentional design to reduce repainting and make pivots stable.
3. Divergence Filters
Min Bars Between Swings (Min Bars Between Swings)
Requires a minimum bar distance between the two pivots used to form divergence.
Helps avoid clutter from pivots that are too close to each other.
Min RSI Difference (Min RSI Difference)
Requires a minimum absolute difference between RSI values at the two pivots.
Filters out very minor changes in RSI that may not be meaningful.
4. Visibility Toggles
Show Regular Divergence
Show Hidden Divergence
You can choose to display:
Both regular and hidden divergence, or
Only regular divergence, or
Only hidden divergence
This is useful if you prefer to focus on one type of structure.
5. Alerts
Enable Alerts
When enabled, the script exposes four alert conditions:
Regular Bullish Divergence Confirmed
Regular Bearish Divergence Confirmed
Hidden Bullish Divergence Confirmed
Hidden Bearish Divergence Confirmed
Each alert fires after the corresponding divergence has been fully confirmed based on the pivot and bar confirmation logic. The script does not issue rapid or intrabar signals; it uses confirmed historical conditions.
You can set these in the TradingView Alerts dialog by choosing this indicator and selecting the desired condition.
Visual Elements
On the main price chart, the indicator:
Draws a line between the two price pivots involved in the divergence.
Adds a small label at the latest pivot, describing the divergence type.
Colors are used to differentiate divergence categories (Green/Red/Teal/Orange).
This makes it easy to visually scan the chart for zones where price and RSI have diverged.
What to Look For (Analytical Use)
This indicator is intended as a visual helper, especially when:
You want to quickly see where price made new highs or lows while RSI did not confirm them in the same way.
You are studying momentum exhaustion, shifts, or continuation using RSI divergence as one of many tools.
You want to compare divergence occurrences across different timeframes or instruments.
Important:
The indicator does not tell you when to enter or exit trades.
It does not rank or validate the “quality” of a divergence.
Divergence can persist or fail; it is not a guarantee of reversal or continuation.
Many traders combine divergence analysis with:
Higher timeframe context
Trend filters (moving averages, structure)
Support/resistance zones or liquidity areas
Volume, structure breaks, or other confirmations
Disclaimer
This script is provided for educational and analytical purposes only.
It does not constitute financial advice, trading advice, or investment recommendations.
No part of this indicator is intended to suggest, encourage, or guarantee any specific trading outcome.
Users are solely responsible for their own decisions and risk management.
Quantura - Fair Value GapIntroduction
“Quantura – Fair Value Gap” is a precision-engineered institutional concept indicator designed to automatically identify, visualize, and manage Fair Value Gaps (FVGs) across any market or timeframe. It enables traders to observe price inefficiencies, potential liquidity voids, and retracement areas that often act as magnets for price rebalancing.
Originality & Value
Unlike many public FVG scripts that only highlight candle gaps, this indicator integrates dynamic filters and adaptive logic to determine the strength and reliability of each gap. It merges overlapping zones intelligently and optionally extends valid imbalances forward for ongoing reference.
Its value lies in:
Dynamic statistical filtering based on gap standard deviation.
Optional volume confirmation for high-confidence FVGs.
Automatic merging of overlapping or adjacent gaps for clean visualization.
Support for both bullish and bearish imbalances.
Signal alerts when gaps are filled or rebalanced by price.
Functionality & Core Logic
Detects Fair Value Gaps by comparing candle-to-candle price displacement.
Applies a Gap Filter (standard deviation-based) to qualify valid gaps.
Optionally validates gaps formed under significant volume conditions.
Draws color-coded boxes to mark bullish (discount) and bearish (premium) inefficiencies.
Monitors each FVG until price fills the gap, at which point the box is visually closed.
Provides optional signal markers (“▲” or “▼”) when rebalancing occurs.
Parameters & Customization
Gap Filter: Sets the minimum statistical deviation required for a valid FVG. Higher values detect fewer, stronger gaps.
Volume Filter: Toggles additional validation using relative volume strength.
Volume Sensitivity: Adjusts how much above-average volume must be present to confirm a gap.
Bullish/Bearish Colors: Customize color schemes for imbalance zones.
Extend Gaps: Optionally extend open gaps forward for better confluence tracking.
Signals: Enables or disables gap-fill signal markers.
Visualization & Display
Bullish FVGs: Appear in blue-tinted boxes, indicating potential demand-side inefficiencies.
Bearish FVGs: Appear in red-tinted boxes, representing potential supply-side inefficiencies.
Overlapping zones are merged automatically to maintain clarity.
Filled gaps remain visible for historical context, allowing for post-event analysis.
Optional signal arrows display when price returns to rebalance an FVG.
Use Cases
Identify institutional inefficiencies and liquidity voids.
Detect premium and discount levels in trending markets.
Combine with market structure or order block indicators for confluence.
Track when price rebalances inefficiencies to refine entry/exit points.
Build FVG-based algorithmic strategies that rely on structural imbalance resolution.
Limitations & Recommendations
The indicator detects structural imbalances but does not predict future direction or guarantee profitability.
Volume filters may behave differently across brokers due to data-source differences.
Use alongside structure or liquidity tools for enhanced decision-making.
Extreme volatility or illiquid assets may generate temporary invalid gaps.
Markets & Timeframes
Compatible with all markets (crypto, forex, equities, indices, futures) and all timeframes. Recommended for multi-timeframe confluence analysis — e.g., detecting higher-timeframe FVGs and refining lower-timeframe entries.
Author & Access
Developed 100% by Quantura. Published as a Open-source script indicator. Access is free.
Compliance Note
This description adheres fully to TradingView’s House Rules and Script Publishing Requirements . It provides a detailed explanation of originality, core logic, limitations, and appropriate use — with no unrealistic or misleading performance claims.
Multi Pivot Trend [BigBeluga]🔵 OVERVIEW
The Multi Pivot Trend is an advanced market-structure-driven trend engine that evaluates trend strength by scanning multiple pivot breakouts simultaneously.
Instead of relying on a single swing length, it tracks breakouts across ten increasing pivot lengths — then averages their behavior to produce a smooth, reliable trend reading.
Mitigation logic (close, wick, or HL2 touches) controls how breakouts are confirmed, giving traders institutional-style flexibility similar to BOS/CHoCH validation rules.
This indicator not only colors candles based on trend strength, but also extends trend strength and volatility-scaled projection candles to show where trend pressure may expand next.
Pivot breakout lines and labels mark key changes, making the trend transitions extremely clear.
🔵 CONCEPTS
Market trend strength is reflected by multiple pivot breakouts, not just one.
The indicator analyzes ten pivot structures from smaller to larger swings.
Each bullish or bearish pivot breakout contributes to trend score.
Mitigation options (close / wick / HL2) imitate smart-money breakout confirmation logic.
Trend score is averaged and translated into colors and extension bars.
Neutral regime ≈ weak trend or transition zone (trend compression).
🔵 FEATURES
Multi-Pivot Engine — tracks 10 pivot-based trend signals simultaneously.
Mitigation Modes :
• Close — breakout requires candle close beyond pivot
• Wicks — breakout requires wick violation
• HL2 — breakout confirmed when average (H+L)/2 crosses level
Dynamic Color System :
• Blue → confirmed bullish rotation
• Red → confirmed bearish rotation
• Orange → neutral / transition state
Breakout Visualization — draws pivot breakout lines in real-time.
Trend Labels — prints trend %.
Trend Volatility-Scaled Extension Candles — ATR/trend strength based candle projections show momentum continuation strength.
Gradient Pivot Encoding — higher pivot lengths = deeper structure considered.
🔵 HOW TO USE
Use strong blue/red periods to follow dominant structural trend.
Watch for color transition into orange — possible trend change or consolidation.
Pivot breakout lines help validate structure shifts without clutter.
Wick mitigation catches aggressive liquidity-sweep based breaks.
Close/HL2 mitigation catches cleaner market structure rotations.
Extension bars visualize trend pressure — large extensions = strong push.
Best paired with volume or volatility confirmation tools.
🔵 CONCLUSION
The Multi Pivot Trend is a structural trend recognition system that blends multiple pivot breakouts into one clean trend score — with institutional-style mitigation logic and volatility-projected trend extensions.
It gives traders a powerful, visually intuitive way to track momentum, spot trend rotations early, and understand true structural flow beyond simple MA-based approaches.
Use it to stay aligned with the dominant swing direction while avoiding noise and false flips.
Range Opening (ADX)▶ OVERVIEW
Range Opening (ADX) dynamically detects market opening ranges triggered by ADX (Average Directional Index) momentum shifts. Upon a user-defined ADX crossover or crossunder event, it builds a volume-based range box that tracks high and low prices over a fixed bar length and visualizes order flow pressure with delta volume and breakout buffer zones.
▶ RANGE TRIGGER VIA ADX CROSSOVER
The range begins when ADX crosses a custom threshold, indicating a shift in trend strength:
Users choose between ADX crossover or crossunder as the trigger.
Once triggered, the indicator starts collecting price and volume data for the specified “Range Opening Length.”
The ADX plot on the subchart is colored dynamically using a green-to-magenta gradient based on its strength.
A small label marks the ADX crossover/crossunder event visually.
▶ RANGE DEVELOPMENT BOX
While the range is forming:
Price highs and lows over the defined period are collected and stored.
A temporary gray box is drawn between the maximum high and minimum low, showing the developing range.
At each bar, delta volume is updated:
Positive if close > open
Negative if close < open
A total delta volume value is shown inside the developing box for real-time monitoring.
▶ RANGE COMPLETION & BREAKOUT LINES
Once the range completes (after the defined bar count):
The gray box is replaced with a finalized, color-coded range box.
Color Logic:
Green box if delta volume is positive (bullish bias)
Magenta box if delta is negative (bearish bias)
Two solid horizontal lines are drawn:
Top line from the range high
Bottom line from the range low
Two dashed lines are added above and below the range using ATR-based buffers, acting as buffer zones.
These lines extend until a new ADX trigger occurs, helping track future price interaction with the range.
▶ INFO PANEL & STATUS MONITORING
A compact data table appears in the top-right corner, offering quick insight:
ADX: Current value, color-coded to strength.
Threshold: User-defined trigger level.
Range Status:
Shows a green diamond when range is still forming.
Shows a magenta diamond after the range has completed.
Tooltip updates to “Developing” or “Formatted” based on stage.
▶ USAGE
Traders can use Range Opening (ADX) to:
Identify periods of strength expansion and price consolidation using ADX signals.
Track breakout potential and liquidity zones formed during opening-type setups.
Monitor delta volume to gauge buying/selling bias inside short-term ranges.
Use ATR buffer zones for breakout confirmation or fade setups.
Visually mark where the most recent structured range was defined.
▶ CONCLUSION
Range Opening (ADX) offers a systematic method to detect and monitor market ranges triggered by volatility surges. With real-time delta volume insight, persistent breakout levels, and ADX-driven logic, it serves as a versatile tool for both breakout traders and range strategists looking to capitalize on momentum-based setups.
Volume Order Block Scanner [BOSWaves]Volume Order Block Scanner - Dynamic Detection of High-Volume Supply and Demand Zones
Overview
The Volume Order Block Scanner introduces a refined approach to institutional zone mapping, combining volume-weighted order flow, structural displacement, and ATR-based proportionality to identify regions of aggressive participation from large entities.
Unlike static zone mapping or simplistic body-size filters, this framework dynamically evaluates each candle through a multi-layer model of relative volume, candle structure, and volatility context to isolate genuine order block formations while filtering out market noise.
Each identified zone represents a potential institutional footprint, defined by significant volume surges and efficient body-to-ATR relationships that indicate purposeful positioning. Once mapped, each order block is dynamically adjusted for volatility and tracked throughout its lifecycle - from creation to mitigation to potential invalidation - producing an evolving liquidity map that adapts with price.
This adaptive behavior allows traders to visualize where liquidity was absorbed and where it remains unfilled, revealing the structural foundation of institutional intent across timeframes.
Theoretical Foundation
At its core, the Volume Order Block Scanner is built on the interaction between volume displacement and structural imbalance. Traditional order block systems often rely on fixed candle formations or simple engulfing logic, neglecting the fundamental driver of institutional activity: volume concentration relative to volatility.
This framework redefines that approach. Each candle is filtered through two comparative ratios:
Relative Volume Ratio (RVR) - the candle’s volume compared to its rolling average, confirming genuine transactional surges.
Body-ATR Ratio (BAR) - a measure of displacement efficiency relative to recent volatility, ensuring structural strength.
Only when both conditions align is an order block validated, marking a displacement event significant enough to create a lasting imbalance.
By embedding this logic within a volatility-adjusted environment, the system maintains scalability across asset classes and volatility regimes - equally effective in crypto, forex, or index markets.
How It Works
The Volume Order Block Scanner operates through a structured multi-stage process:
Displacement Detection - Identifies candles whose body and volume exceed dynamic thresholds derived from ATR and rolling volume averages. These represent the origin points of institutional aggression.
Zone Construction - Each qualified candle generates an order block with ATR-proportional dimensions to ensure consistency across instruments and timeframes. The zone includes two regions: Body Zone (the precise initiation point of displacement) and Wick Imbalance (the residual inefficiency representing unfilled liquidity).
Lifecycle Tracking - Each zone is continuously monitored for market interaction. Reactions within a defined window are classified as respected, mitigated, or invalidated, giving traders a data-driven sense of ongoing institutional relevance.
Volume Confirmation Layer - Reinforces signal integrity by ensuring that all detected blocks correspond with meaningful increases in transactional activity.
Temporal Decay Control - Zones that remain untested beyond a set period gradually lose visual and analytical weight, maintaining chart clarity and contextual precision.
Interpretation
The Volume Order Block Scanner visualizes how institutional participants interact with the market through zones of accumulation and distribution.
Bullish order blocks denote demand imbalances where price displaced upward under high volume; bearish order blocks signify supply regions formed by concentrated selling pressure.
Price revisiting these areas often reflects institutional re-entry or liquidity rebalancing, offering actionable insights for both continuation and reversal scenarios.
By continuously monitoring interaction and expiry, the framework enables traders to distinguish between active institutional footprints and historical liquidity artifacts.
Strategy Integration
The Volume Order Block Scanner integrates naturally into advanced structural and order-flow methodologies:
Liquidity Mapping : Identify high-volume regions that are likely to influence future price reactions.
Break-of-Structure Confirmation : Validate BOS and CHOCH signals through aligned order block behavior.
Volume Confluence : Combine with BOSWaves volume or momentum indicators to confirm real institutional intent.
Smart-Money Frameworks : Utilize order block retests as precision entry zones within SMC-based setups.
Trend Continuation : Filter zones in line with higher-timeframe bias to maintain directional integrity.
Technical Implementation Details
Core Engine : Dual-filter mechanism using Relative Volume Ratio (RVR) and Body-ATR Ratio (BAR).
Volatility Framework : ATR-based scaling for cross-asset proportionality.
Zone Composition : Body and wick regions plotted independently for visual clarity of imbalance.
Lifecycle Logic : Real-time monitoring of reaction, mitigation, and invalidation states.
Directional Coloring : Distinct bullish and bearish shading with adjustable transparency.
Computation Efficiency : Lightweight structure suitable for multi-timeframe or multi-asset environments.
Optimal Application Parameters
Timeframe Guidance:
5m - 15m : Reactive intraday zones for short-term liquidity engagement.
1H - 4H : Medium-term structures for swing or intraday trend mapping.
Daily - Weekly : Macro accumulation and distribution footprints.
Suggested Configuration:
Relative Volume Threshold : 1.5× - 2.0× average volume.
Body-ATR Threshold : 0.8× - 1.2× for valid displacement.
Zone Expiry : 5 - 10 bars for intraday use, 15 - 30 for swing/macro contexts.
Parameter optimization should be asset-specific, tuned to volatility conditions and liquidity depth.
Performance Characteristics
High Effectiveness:
Markets exhibiting clear displacement and directional flow.
Environments with consistent volume expansion and liquidity inefficiencies.
Reduced Effectiveness:
Range-bound markets with frequent false impulses.
Low-volume sessions lacking institutional participation.
Integration Guidelines
Confluence Framework : Pair with structure-based BOS or liquidity tools for validation.
Risk Management : Treat active order blocks as contextual areas of interest, not guaranteed reversal points.
Multi-Timeframe Logic : Derive bias from higher-timeframe blocks and execute from refined lower-timeframe structures.
Volume Verification : Confirm each reaction with concurrent volume acceleration to avoid false liquidity cues.
Disclaimer
The Volume Order Block Scanner is a quantitative mapping framework designed for professional traders and analysts. It is not a predictive or guaranteed system of profit.
Performance depends on correct configuration, market conditions, and disciplined risk management. BOSWaves recommends using this indicator as part of a comprehensive analytical process - integrating structural, volume, and liquidity context for accurate interpretation.
ICT Macro Time WindowsICT Macro Time Windows - Master institutional market timing with automated 'Macro' trading session tracking.
What are 'Macros'?
In ICT terminology, 'Macros' refer to the key institutional trading windows throughout the day where major banks and liquidity providers are most active. These specific time frames see heightened volatility, liquidity, and strategic positioning.
Perfect Timing Automation:
• 8 Critical Macro Sessions:
London 1: 02:33-03:00 EST
London 2: 04:03-04:30 EST
NY AM1: 08:50-09:10 EST
NY AM2: 09:50-10:10 EST
NY AM3: 10:50-11:10 EST
Lunch: 11:50-12:10 EST
PM: 13:10-13:40 EST
Close: 15:15-15:45 EST
• Fully customizable time zones and session times
• Real-time session detection with visual zones & labels
• Automatic High/Low range tracking within each window
• Boxes, lines, and labels for clear visual reference
• Never miss optimal entry/exit timing again
Trade when institutions trade - stop guessing and start timing your setups with precision during these key liquidity windows! All session times are easily adjustable in settings to match your preferred trading hours.
Perfect for Forex, Futures, and Index traders following ICT concepts and institutional flow analysis.
ORBs, EMAs, SMAs, AVWAPThis is an update to a previously published script. In short the difference is the added capability to adjust the length of EMAs. Also added 3 customizable SMAs. Enjoy! Let me know what you think of the script please. This is only second one I have ever done. Through practice and people like @LuxAlgo and other Pinescripters this isn't possible. Tedious hrs with ChatGPT to correct nuances, who doesnt seem to learn from (insert pronoun) mistakes
This all-in-one indicator combines key institutional tools into a unified framework for intraday and swing trading. Designed for traders who use multi-session analysis and dynamic levels, it automatically maps out global session breakouts, moving averages, and volume-weighted anchors with high clarity.
Features include:
🕓 Tokyo, London, and New York ORBs (Opening Range Breakouts) — 30-minute configurable range boxes that persist until the next New York open.
📈 Anchored VWAP with Standard Deviation Bands — dynamically anchorable to session, week, or month for institutional-grade price tracking.
📊 Exponential Moving Averages (9, 20, 113, 200) — for short-, mid-, and long-term momentum structure.
📉 Simple Moving Averages (20, 50, 100) — fully customizable lengths, colors, and visibility toggles for trend confirmation.
🏁 Prior High/Low Levels (PDH/PDL, PWH/PWL, PMH/PML) — automatically plotted from previous day, week, and month, with labels placed at each session’s midpoint.
🎛️ Session-Aligned Time Logic — all time calculations use New York session anchors with DST awareness.
💡 Clean Visualization Options — every component can be toggled on/off, recolored, or customized for your workflow.
Best used for:
ORB break-and-retest setups
VWAP and EMA rejections
Confluence-based trading around key session levels
Multi-session momentum tracking
SuperBandsI've been seeing a lot of volatility band indicators pop up recently, and after watching this trend for a while, I figured it was time to throw my two chips in. The original spark for this idea came years ago from RicardoSantos's Vector Flow Channel script, which used decay channels with timed events in an interesting way. That concept stuck with me, and I kept thinking about how to build something that captured the same kind of dynamic envelope behavior but with a different mathematical foundation. What I ended up with is a hybrid that takes the core logic of supertrend trailing stops, smooths them heavily with exponential moving averages, and wraps them in Donchian-style filled bands with momentum-based color gradients.
The basic mechanism here is pretty straightforward. Standard supertrend calculates a trailing stop based on ATR offset from price, then flips direction when price crosses the trail. This implementation does the same thing but adds EMA smoothing to the trail calculation itself, which removes a lot of the choppiness you get from raw supertrend during sideways periods. The smoothing period is adjustable, so you can tune how reactive versus stable you want the bands to be. Lower smoothing values make the bands track price more aggressively, higher values create wider, slower-moving envelopes that only respond to sustained directional moves.
Where this diverges from typical supertrend implementations is in the visual presentation and the separate treatment of bullish and bearish conditions. Instead of a single flipping line, you get persistent upper and lower bands that each track their own trailing stops independently. The bullish band trails below price and stays active as long as price doesn't break below it. The bearish band trails above price and remains active until price breaks above. Both bands can be visible simultaneously, which gives you a dynamic channel that adapts to volatility on both sides of price action. When price is trending strongly, one band will dominate and the other will disappear. During consolidation, both bands tend to compress toward price.
The color gradients are calculated by measuring the rate of change in each band's position and converting that delta into an angle using arctangent scaling. Steeper angles, which correspond to the band moving quickly to catch up with accelerating price, get brighter colors. Flatter angles, where the band is moving slowly or staying relatively stable, fade toward more muted tones. This gives you a visual sense of momentum within the bands themselves, not just from price movement. A rapidly brightening band often precedes expansion or breakout conditions, while fading colors suggest the trend is losing steam or entering consolidation.
The filled regions between price and each band serve a similar function to Donchian channels or Keltner bands, creating clearly defined zones that represent normal price behavior relative to recent volatility. When price hugs one band and the fill area compresses, you're in a strong directional regime. When price bounces between both bands and the fills expand, you're in a ranging environment. The transparency gradients in the fills make it easier to see when price is near the edge of the envelope versus safely inside it.
Configuration is split between bullish and bearish settings, which lets you asymmetrically tune the indicator if you find that your market or timeframe has different characteristics in uptrends versus downtrends. You can adjust ATR period, ATR multiplier, and smoothing independently for each direction. This flexibility is useful for instruments that exhibit different volatility profiles during bull and bear phases, or for strategies that want tighter trailing on longs than shorts, or vice versa.
The ATR period controls the lookback window for volatility measurement. Shorter periods make the bands react quickly to recent volatility spikes, which can be beneficial in fast-moving markets but also leads to more frequent whipsaws. Longer periods smooth out volatility estimates and create more stable bands at the cost of slower adaptation. The multiplier scales the ATR offset, directly controlling how far the bands sit from price. Smaller multipliers keep the bands tight, triggering more frequent direction changes. Larger multipliers create wider envelopes that give price more room to move without breaking the trail.
One thing to note is that this indicator doesn't generate explicit buy or sell signals in the traditional sense. It's a regime filter and envelope tool. You can use band breaks as directional cues if you want, but the primary value comes from understanding the current volatility environment and whether price is respecting or violating its recent behavioral boundaries. Pairing this with momentum oscillators or volume analysis tends to work better than treating band breaks as standalone entries.
From an implementation perspective, the supertrend state machine tracks whether each direction's trail is active, handles resets when price breaks through, and manages the EMA smoothing on the trail points themselves rather than just post-processing the supertrend output. This means the smoothing is baked into the trailing logic, which creates a different response curve than if you just applied an EMA to a standard supertrend line. The angle calculations use RMS estimation for the delta normalization range, which adapts to changing volatility and keeps the color gradients responsive across different market conditions.
What this really demonstrates is that there are endless ways to combine basic technical concepts into something that feels fresh without reinventing mathematics. ATR offsets, trailing stops, EMA smoothing, and Donchian fills are all standard building blocks, but arranging them in a particular way produces behavior that's distinct from each component alone. Whether this particular arrangement works better than other volatility band systems depends entirely on your market, timeframe, and what you're trying to accomplish. For me, it scratched the itch I had from seeing Vector Flow years ago and wanting to build something in that same conceptual space using tools I'm more comfortable with.
RSI Divergence Screener [Pineify]RSI Divergence Screener
Key Features
Multi-symbol and multi-timeframe support for advanced market screening.
Real-time detection and visualization of bullish and bearish RSI divergences.
Seamless integration with core technical indicators and custom divergences.
Highly customizable parameters for precise adaptation to personal trading strategies.
Comprehensive screener table for swift asset comparison and analysis.
How It Works
The RSI Divergence Screener leverages the power of Relative Strength Index (RSI) to systematically track momentum shifts across cryptocurrencies and their respective timeframes. By monitoring both fast and slow RSI calculations, the screener isolates divergence signals—key reversal points that often precede major price moves.
The indicator calculates two RSI values for each selected asset: one with a short lookback (Fast RSI) and another with a longer period (Slow RSI).
It runs a comparative algorithm to find divergences—whenever Fast RSI deviates significantly from Slow RSI, it flags the signal as bullish or bearish.
All detected divergences are dynamically presented in a table view, allowing traders to scan symbols and timeframes for optimal trading setups.
Trading Ideas and Insights
Spot early momentum reversals and preempt major price swings via divergence signals.
Combine multiple symbols and timeframes for cross-market trending opportunities.
Identify high-probability scalping and swing trading setups informed by RSI divergence logic.
Quickly compare crypto asset strength and trend exhaustion across short and long-term horizons.
How Multiple Indicators Work Together
This screener’s edge lies in its synergistic use of multi-setting RSI calculations and customizable input groups.
The dual-RSI approach (Fast vs. Slow) isolates subtle trend shifts missed by traditional single-period RSI.
Safe and reliable divergences arise only when the mathematical difference between Fast RSI and Slow RSI meets predefined thresholds, minimizing false positives.
Divergences are contextualized using tailored color codes and backgrounds, rendering insights immediately actionable.
You can expand analysis with additional moving average filters or overlays for further confirmation.
Unique Aspects
First-of-its-kind screener dedicated solely to RSI divergence, designed especially for crypto volatility.
Efficient screening of up to eight assets and multiple timeframes in one compact dashboard.
Intuitive iconography, color logic, and table layouts optimized for rapid decision-making.
Advanced input group design for fine-tuning indicator settings per symbol, timeframe, and source.
How to Use
Select up to eight cryptocurrency symbols to screen for divergence signals.
Assign individual timeframes and source prices for each asset to customize analysis.
Set Fast RSI and Slow RSI lengths according to your preferred strategy (e.g., scalping, swing, or trend following).
Review the screener table: colored cells highlight actionable bullish (green) and bearish (red) divergences.
Confirm trade setups with additional indicators or price action for robust risk management.
Customization
Symbols: Choose any crypto pair or ticker for dynamic divergence tracking.
Timeframes: Scan across 1m, 5m, 10m, 30m, and more for full market coverage.
RSI lengths: Configure Fast and Slow RSI periods based on volatility and trading style.
Visuals: Tailor table colors, fonts, and alert backgrounds per your preference.
Conclusion
The RSI Divergence Screener is a versatile, original TradingView indicator that empowers traders to scan, compare, and act on divergence signals with speed and precision. Its multi-symbol design, robust logic, and extensive customization options set a new standard for market screening tools. Integrate it into your crypto trading process to capture actionable opportunities ahead of the crowd and optimize your technical analysis workflow.
Crypto ETFs AUM📘 Description: BTC ETFs AUM Tracker
This indicator tracks the Assets Under Management (AUM) and daily inflows/outflows of the main U.S.-listed Bitcoin ETFs, allowing you to visualize institutional capital movement into Bitcoin products over time. It helps traders correlate institutional capital movement with Bitcoin price behavior.
🧩 Overview
The script adds up the daily AUM changes from selected Bitcoin ETFs to estimate the total net inflow/outflow of capital into spot BTC funds. It also accumulates those flows over time to display the total aggregated AUM balance, giving you a clearer sense of market direction and institutional sentiment. Two display modes are available: Balance view: plots the cumulative sum of net inflows (total ETF AUM). Inflows view: shows daily inflows (green) and outflows (red) as histogram columns, together with a smoothed moving average line.
⚙️ Inputs
Explained Base Settings Base Multiplier (base_multi) – Scaling factor applied to all AUM values. Leave at 1 for USD units, or adjust to display values in millions (1e6) or billions (1e9). Smoothing (c_smoothing) – Period length for the simple moving average used to calculate the smoothed mean inflow/outflow line. Show Balance (showBalance) – When enabled, displays the total cumulative AUM balance (sum of all net inflows over time). Show Inflows (showInflows) – When enabled, displays the daily inflows/outflows as colored columns. ETF Selection You can toggle which ETFs are included in the calculation:
BIT (BlackRock)
GBTC (Grayscale)
FBTC (Fidelity)
ARKB (ARK/21Shares)
BITB (Bitwise)
EZBC (Franklin Templeton)
BTCW (WisdomTree)
BTCO (Invesco Galaxy)
BRRR (Valkyrie)
HODL (VanEck)
Each switch determines whether the ETF’s AUM and daily flow data are included in the total calculation.
📊 Displayed Values Green Columns → Positive daily net inflows (AUM increased). Red Columns → Negative daily net outflows (AUM decreased). Orange Line → Smoothed moving average of net flows, used to identify persistent inflow/outflow trends. Blue Line (if enabled) → Total cumulative AUM balance (sum of all historical flows).
💡 Usage Notes Works best on daily timeframe, since ETF data is typically updated once per trading day. Not all ETFs have identical data history; missing data points are automatically skipped. The indicator doesn’t represent official fund NAV or guarantee data accuracy — it visualizes TradingView’s public financial feed. You can combine this tool with price action or on-chain metrics to analyze institutional Bitcoin flows.
Note: Some ETF data may not be available to all users depending on their TradingView data subscription or market access. Missing values are automatically skipped.
🧠 Disclaimer This script is for educational and analytical purposes only. It is not financial advice, and no investment decisions should be based solely on this indicator. Data accuracy depends on TradingView’s financial data sources and exchange reporting frequency.
VWAP Deviation Oscillator [BackQuant]VWAP Deviation Oscillator
Introduction
The VWAP Deviation Oscillator turns VWAP context into a clean, tradeable oscillator that works across assets and sessions. It adapts to your workflow with four VWAP regimes plus two rolling modes, and three deviation metrics: Percent, Absolute, and Z-Score. Colored zones, optional standard deviation rails, and flexible plot styles make it fast to read for both trend following and mean reversion.
What it does
This tool measures how far price is from a chosen VWAP and expresses that gap as an oscillator. You can view the deviation as raw price units, percent, or standardized Z-Score. The plot can be a histogram or a line with optional fills and sigma bands, so you can quickly spot polarity shifts, overbought and oversold conditions, and strength of extension.
VWAP modes track a session VWAP that resets (4H, Daily, Weekly) or a rolling VWAP that updates continuously over a fixed number of bars or days.
Deviation modes let you choose the lens: Percent, Absolute, or Z-Score. Each highlights different aspects of stretch and mean pressure.
Visual encoding uses a 10-zone color palette to grade the magnitude of deviation on both sides of zero.
Volatility guards compute mode-specific sigma so thresholds are stable even when volatility compresses.
Why this works
VWAP is a high signal anchor used by institutions to gauge fair participation. Deviations around VWAP cluster in regimes: mild oscillations within a band, decisive pushes that signal imbalance, and standardized extremes that often precede either continuation or snapback. Expressing that distance as a single time series adds clarity: bias is the oscillator’s sign, risk context is its magnitude, and regime is the way it behaves around sigma lines.
How to use it
Trend following
Favor the side of the zero line. Bullish when the oscillator is above zero and making higher swing highs. Bearish when below zero and making lower swing lows. Use +1 sigma and +2 sigma in your mode as strength tiers. Pullbacks that hold above zero in uptrends, or below zero in downtrends, are often continuation entries.
Mean reversion
Fade stretched readings when structure supports it. Look for tests of +2 sigma to +3 sigma that fail to progress and roll back toward zero, or the mirror on the downside. Z-Score mode is best when you want standardized gates across assets. Percent mode is intuitive for intraday scalps where a given percent stretch tends to mean revert.
Session playbook
Use Daily or Weekly VWAP for intraday or swing context. Rolling modes help when the asset lacks clean session boundaries or when you want a continuous anchor that adapts to liquidity shifts.
Key settings
VWAP computation
VWAP Mode = 4 Hours, Daily, Weekly, Rolling (Bars), Rolling (Days). Session modes reset the VWAP when a new session begins. Rolling modes compute VWAP over a fixed trailing window.
Rolling (Lookback: Bars) controls the trailing bar count when using Rolling (Bars).
Rolling (Lookback: Days) converts days to bars at runtime and uses that trailing span.
Use Close instead of HLC3 switches the price reference. HLC3 is smoother. Close makes the anchor track settlement more tightly.
Deviation measurement
Deviation Mode
Percent : 100 * (Price / VWAP - 1). Good for uniform scaling across instruments.
Absolute : Price - VWAP. Good when price units themselves matter.
Z-Score : Standardizes the absolute residual by its own mean and standard deviation over Z/Std Window . Ideal for cross-asset comparability and regime studies.
Z/Std Window sets the mean and standard deviation window for Z-Score mode.
Volatility controls
Percent Mode Volatility Lookback estimates sigma for percent deviations.
Absolute Mode Volatility Lookback estimates sigma for absolute deviations.
Minimum Sigma Guard (pct pts) prevents the percent sigma from collapsing to near zero in extremely quiet markets.
Visualization
Plot Type = Histogram or Line. Histogram emphasizes impulse and polarity changes. Line emphasizes trend waves and divergences.
Positive Color / Negative Color define the palette for line mode. Histogram uses a 10-bucket gradient automatically.
Show Standard Deviations plots symmetric rails at ±1, ±2, ±3 sigma in the current mode’s units.
Fill Line Oscillator and Fill Opacity add a soft bias band around zero for line mode.
Line Width affects both the oscillator and the sigma rails.
Reading the zones
The oscillator’s color and height map deviation to nine graded buckets on each side of zero, with deeper greens above and deeper reds below. In Percent and Absolute modes, those buckets are scaled by their mode-specific sigma. In Z-Score mode the bucket edges are fixed at 0.5, 1.0, 2.0, and 2.8.
0 to +1 sigma weak positive bias, usually rotational.
+1 to +2 sigma constructive impulse. Pullbacks that hold above zero often continue.
+2 to +3 sigma strong expansion. Watch for either trend continuation or exhaustion tells.
Beyond +3 sigma statistical extreme. Requires structure to avoid fading too soon.
Mirror logic applies on the negative side.
Suggested workflows
Trend continuation checklist
Pick a session VWAP that matches your timeframe, for example Daily for intraday or Weekly for position trades.
Wait for the oscillator to hold the correct side of zero and for a sequence of higher swing lows in the oscillator (uptrend) or lower swing highs (downtrend).
Buy pullbacks that stabilize between zero and +1 sigma in an uptrend. Sell rallies that stabilize between zero and -1 sigma in a downtrend.
Use the next sigma band or a prior price swing as your target reference.
Mean reversion checklist
Switch to Z-Score mode for standardized thresholds.
Identify tests of ±2 sigma to ±3 sigma that fail to extend while price meets support or resistance.
Enter on a polarity change through the prior histogram bar or a small hook in line mode.
Fade back to zero or to the opposite inner band, then reassess.
Notes on the three modes
Percent is easy to reason about when you care about proportional stretch. It is well suited to intraday and multi-asset dashboards.
Absolute tracks cash distance from VWAP. This is useful when instruments have tight ticks and you plan risk in price units.
Z-Score standardizes the residual and is best for quant studies, cross-asset comparisons, and threshold research that must be scale invariant.
What the alerts can tell you
Polarity changes at zero can mark the start or end of a leg.
Crosses of ±1 sigma identify overbought or oversold in the current mode’s units.
Zone changes signal an upgrade or downgrade in deviation strength.
Troubleshooting and edge cases
If your instrument has long flat periods, keep Minimum Sigma Guard above zero in Percent mode so the rails do not vanish.
In Rolling modes, very short windows will respond quickly but can whip around. Session modes smooth this by resetting at well known boundaries.
If Z-Score looks erratic, increase Z/Std Window to stabilize the estimate of mean and sigma for the residual.
Final thoughts
VWAP is the anchor. The deviation oscillator is the narrative. By separating bias, magnitude, and regime into a simple stream you can execute faster and review cleaner. Pick the VWAP mode that matches your horizon, choose the deviation lens that matches your risk framework, and let the color graded zones guide your decisions.
Volume Based Sampling [BackQuant]Volume Based Sampling
What this does
This indicator converts the usual time-based stream of candles into an event-based stream of “synthetic” bars that are created only when enough trading activity has occurred . You choose the activity definition:
Volume bars : create a new synthetic bar whenever the cumulative number of shares/contracts traded reaches a threshold.
Dollar bars : create a new synthetic bar whenever the cumulative traded dollar value (price × volume) reaches a threshold.
The script then keeps an internal ledger of these synthetic opens, highs, lows, closes, and volumes, and can display them as candles, plot a moving average calculated over the synthetic closes, mark each time a new sample is formed, and optionally overlay the native time-bars for comparison.
Why event-based sampling matters
Markets do not release information on a clock: activity clusters during news, opens/closes, and liquidity shocks. Event-based bars normalize for that heteroskedastic arrival of information: during active periods you get more bars (finer resolution); during quiet periods you get fewer bars (coarser resolution). Research shows this can reduce microstructure pathologies and produce series that are closer to i.i.d. and more suitable for statistical modeling and ML. In particular:
Volume and dollar bars are a common event-time alternative to time bars in quantitative research and are discussed extensively in Advances in Financial Machine Learning (AFML). These bars aim to homogenize information flow by sampling on traded size or value rather than elapsed seconds.
The Volume Clock perspective models market activity in “volume time,” showing that many intraday phenomena (volatility, liquidity shocks) are better explained when time is measured by traded volume instead of seconds.
Related market microstructure work on flow toxicity and liquidity highlights that the risk dealers face is tied to information intensity of order flow, again arguing for activity-based clocks.
How the indicator works (plain English)
Choose your bucket type
Volume : accumulate volume until it meets a threshold.
Dollar Bars : accumulate close × volume until it meets a dollar threshold.
Pick the threshold rule
Dynamic threshold : by default, the script computes a rolling statistic (mean or median) of recent activity to set the next bucket size. This adapts bar size to changing conditions (e.g., busier sessions produce more frequent synthetic bars).
Fixed threshold : optionally override with a constant target (e.g., exactly 100,000 contracts per synthetic bar, or $5,000,000 per dollar bar).
Build the synthetic bar
While a bucket fills, the script tracks:
o_s: first price of the bucket (synthetic open)
h_s: running maximum price (synthetic high)
l_s: running minimum price (synthetic low)
c_s: last price seen (synthetic close)
v_s: cumulative native volume inside the bucket
d_samples: number of native bars consumed to complete the bucket (a proxy for “how fast” the threshold filled)
Emit a new sample
Once the bucket meets/exceeds the threshold, a new synthetic bar is finalized and stored. If overflow occurs (e.g., a single native bar pushes you past the threshold by a lot), the code will emit multiple synthetic samples to account for the extra activity.
Maintain a rolling history efficiently
A ring buffer can overwrite the oldest samples when you hit your Max Stored Samples cap, keeping memory usage stable.
Compute synthetic-space statistics
The script computes an SMA over the last N synthetic closes and basic descriptors like average bars per synthetic sample, mean and standard deviation of synthetic returns, and more. These are all in event time , not clock time.
Inputs and options you will actually use
Data Settings
Sampling Method : Volume or Dollar Bars.
Rolling Lookback : window used to estimate the dynamic threshold from recent activity.
Filter : Mean or Median for the dynamic threshold. Median is more robust to spikes.
Use Fixed? / Fixed Threshold : override dynamic sizing with a constant target.
Max Stored Samples : cap on synthetic history to keep performance snappy.
Use Ring Buffer : turn on to recycle storage when at capacity.
Indicator Settings
SMA over last N samples : moving average in synthetic space . Because its index is sample count, not minutes, it adapts naturally: more updates in busy regimes, fewer in quiet regimes.
Visuals
Show Synthetic Bars : plot the synthetic OHLC candles.
Candle Color Mode :
Green/Red: directional close vs open
Volume Intensity: opacity scales with synthetic size
Neutral: single color
Adaptive: graded by how large the bucket was relative to threshold
Mark new samples : drop a small marker whenever a new synthetic bar prints.
Comparison & Research
Show Time Bars : overlay the native time-based candles to visually compare how the two sampling schemes differ.
How to read it, step by step
Turn on “Synthetic Bars” and optionally overlay “Time Bars.” You will see that during high-activity bursts, synthetic bars print much faster than time bars.
Watch the synthetic SMA . Crosses in synthetic space can be more meaningful because each update represents a roughly comparable amount of traded information.
Use the “Avg Bars per Sample” in the info table as a regime signal. Falling average bars per sample means activity is clustering, often coincident with higher realized volatility.
Try Dollar Bars when price varies a lot but share count does not; they normalize by dollar risk taken in each sample. Volume Bars are ideal when share count is a better proxy for information flow in your instrument.
Quant finance background and citations
Event time vs. clock time : Easley, López de Prado, and O’Hara advocate measuring intraday phenomena on a volume clock to better align sampling with information arrival. This framing helps explain volatility bursts and liquidity droughts and motivates volume-based bars.
Flow toxicity and dealer risk : The same authors show how adverse selection risk changes with the intensity and informativeness of order flow, further supporting activity-based clocks for modeling and risk management.
AFML framework : In Advances in Financial Machine Learning , event-driven bars such as volume, dollar, and imbalance bars are presented as superior sampling units for many ML tasks, yielding more stationary features and fewer microstructure distortions than fixed time bars. ( Alpaca )
Practical use cases
1) Regime-aware moving averages
The synthetic SMA in event time is not fooled by quiet periods: if nothing of consequence trades, it barely updates. This can make trend filters less sensitive to calendar drift and more sensitive to true participation.
2) Breakout logic on “equal-information” samples
The script exposes simple alerts such as breakout above/below the synthetic SMA . Because each bar approximates a constant amount of activity, breakouts are conditioned on comparable informational mass, not arbitrary time buckets.
3) Volatility-adaptive backtests
If you use synthetic bars as your base data stream, most signal rules become self-paced : entry and exit opportunities accelerate in fast markets and slow down in quiet regimes, which often improves the realism of slippage and fill modeling in research pipelines (pair this indicator with strategy code downstream).
4) Regime diagnostics
Avg Bars per Sample trending down: activity is dense; expect larger realized ranges.
Return StdDev (synthetic) rising: noise or trend acceleration in event time; re-tune risk.
Interpreting the info panel
Method : your sampling choice and current threshold.
Total Samples : how many synthetic bars have been formed.
Current Vol/Dollar : how much of the next bucket is already filled.
Bars in Bucket : native bars consumed so far in the current bucket.
Avg Bars/Sample : lower means higher trading intensity.
Avg Return / Return StdDev : return stats computed over synthetic closes .
Research directions you can build from here
Imbalance and run bars
Extend beyond pure volume or dollar thresholds to imbalance bars that trigger on directional order flow imbalance (e.g., buy volume minus sell volume), as discussed in the AFML ecosystem. These often further homogenize distributional properties used in ML. alpaca.markets
Volume-time indicators
Re-compute classical indicators (RSI, MACD, Bollinger) on the synthetic stream. The premise is that signals are updated by traded information , not seconds, which may stabilize indicator behavior in heteroskedastic regimes.
Liquidity and toxicity overlays
Combine synthetic bars with proxies of flow toxicity to anticipate spread widening or volatility clustering. For instance, tag synthetic bars that surpass multiples of the threshold and test whether subsequent realized volatility is elevated.
Dollar-risk parity sampling for portfolios
Use dollar bars to align samples across assets by notional risk, enabling cleaner cross-asset features and comparability in multi-asset models (e.g., correlation studies, regime clustering). AFML discusses the benefits of event-driven sampling for cross-sectional ML feature engineering.
Microstructure feature set
Compute duration in native bars per synthetic sample , range per sample , and volume multiple of threshold as inputs to state classifiers or regime HMMs . These features are inherently activity-aware and often predictive of short-horizon volatility and trend persistence per the event-time literature. ( Alpaca )
Tips for clean usage
Start with dynamic thresholds using Median over a sensible lookback to avoid outlier distortion, then move to Fixed thresholds when you know your instrument’s typical activity scale.
Compare time bars vs synthetic bars side by side to develop intuition for how your market “breathes” in activity time.
Keep Max Stored Samples reasonable for performance; the ring buffer avoids memory creep while preserving a rolling window of research-grade data.
BayesStack RSI [CHE]BayesStack RSI — Stacked RSI with Bayesian outcome stats and gradient visualization
Summary
BayesStack RSI builds a four-length RSI stack and evaluates it with a simple Bayesian success model over a rolling window. It highlights bull and bear stack regimes, colors price with magnitude-based gradients, and reports per-regime counts, wins, and estimated win rate in a compact table. Signals seek to be more robust through explicit ordering tolerance, optional midline gating, and outcome evaluation that waits for events to mature by a fixed horizon. The design focuses on readable structure, conservative confirmation, and actionable context rather than raw oscillator flips.
Motivation: Why this design?
Classical RSI signals flip frequently in volatile phases and drift in calm regimes. Pure threshold rules often misclassify shallow pullbacks and stacked momentum phases. The core idea here is ordered, spaced RSI layers combined with outcome tracking. By requiring a consistent order with a tolerance and optionally gating by the midline, regime identification becomes clearer. A horizon-based maturation check and smoothed win-rate estimate provide pragmatic feedback about how often a given stack has recently worked.
What’s different vs. standard approaches?
Reference baseline: Traditional single-length RSI with overbought and oversold rules or simple crossovers.
Architecture differences:
Four fixed RSI lengths with strict ordering and a spacing tolerance.
Optional requirement that all RSI values stay above or below the midline for bull or bear regimes.
Outcome evaluation after a fixed horizon, then rolling counts and a prior-smoothed win rate.
Dispersion measurement across the four RSIs with a percent-rank diagnostic.
Gradient coloring of candles and wicks driven by stack magnitude.
A last-bar statistics table with counts, wins, win rate, dispersion, and priors.
Practical effect: Charts emphasize sustained momentum alignment instead of single-length crosses. Users see when regimes start, how strong alignment is, and how that regime has recently performed for the chosen horizon.
How it works (technical)
The script computes RSI on four lengths and forms a “stack” when they are strictly ordered with at least the chosen tolerance between adjacent lengths. A bull stack requires a descending set from long to short with positive spacing. A bear stack requires the opposite. Optional gating further requires all RSI values to sit above or below the midline.
For evaluation, each detected stack is checked again after the horizon has fully elapsed. A bull event is a success if price is higher than it was at event time after the horizon has passed. A bear event succeeds if price is lower under the same rule. Rolling sums over the training window track counts and successes; a pair of priors stabilizes the win-rate estimate when sample sizes are small.
Dispersion across the four RSIs is measured and converted to a percent rank over a configurable window. Gradients for bars and wicks are normalized over a lookback, then shaped by gamma controls to emphasize strong regimes. A statistics table is created once and updated on the last bar to minimize overhead. Overlay markers and wick coloring are rendered to the price chart even though the indicator runs in a separate pane.
Parameter Guide
Source — Input series for RSI. Default: close. Tips: Use typical price or hlc3 for smoother behavior.
Overbought / Oversold — Guide levels for context. Defaults: seventy and thirty. Bounds: fifty to one hundred, zero to fifty. Tips: Narrow the band for faster feedback.
Stacking tolerance (epsilon) — Minimum spacing between adjacent RSIs to qualify as a stack. Default: zero point twenty-five RSI points. Trade-off: Higher values reduce false stacks but delay entries.
Horizon H — Bars ahead for outcome evaluation. Default: three. Trade-off: Longer horizons reduce noise but delay success attribution.
Rolling window — Lookback for counts and wins. Default: five hundred. Trade-off: Longer windows stabilize the win rate but adapt more slowly.
Alpha prior / Beta prior — Priors used to stabilize the win-rate estimate. Defaults: one and one. Trade-off: Larger priors reduce variance with sparse samples.
Show RSI 8/13/21/34 — Toggle raw RSI lines. Default: on.
Show consensus RSI — Weighted combination of the four RSIs. Default: on.
Show OB/OS zones — Draw overbought, oversold, and midline. Default: on.
Background regime — Pane background tint during bull or bear stacks. Default: on.
Overlay regime markers — Entry markers on price when a stack forms. Default: on.
Show statistics table — Last-bar table with counts, wins, win rate, dispersion, priors, and window. Default: on.
Bull requires all above fifty / Bear requires all below fifty — Midline gate. Defaults: both on. Trade-off: Stricter regimes, fewer but cleaner signals.
Enable gradient barcolor / wick coloring — Gradient visuals mapped to stack magnitude. Defaults: on. Trade-off: Clearer regime strength vs. extra rendering cost.
Collection period — Normalization window for gradients. Default: one hundred. Trade-off: Shorter values react faster but fluctuate more.
Gamma bars and shapes / Gamma plots — Curve shaping for gradients. Defaults: zero point seven and zero point eight. Trade-off: Higher values compress weak signals and emphasize strong ones.
Gradient and wick transparency — Visual opacity controls. Defaults: zero.
Up/Down colors (dark and neon) — Gradient endpoints. Defaults: green and red pairs.
Fallback neutral candles — Directional coloring when gradients are off. Default: off.
Show last candles — Limit for gradient squares rendering. Default: three hundred thirty-three.
Dispersion percent-rank length / High and Low thresholds — Window and cutoffs for dispersion diagnostics. Defaults: two hundred fifty, eighty, and twenty.
Table X/Y, Dark theme, Text size — Table anchor, theme, and typography. Defaults: right, top, dark, small.
Reading & Interpretation
RSI stack lines: Alignment and spacing convey regime quality. Wider spacing suggests stronger alignment.
Consensus RSI: A single line that summarizes the four lengths; use as a smoother reference.
Zones: Overbought, oversold, and midline provide context rather than standalone triggers.
Background tint: Indicates active bull or bear stack.
Markers: “Bull Stack Enter” or “Bear Stack Enter” appears when the stack first forms.
Gradients: Brighter tones suggest stronger stack magnitude; dull tones suggest weak alignment.
Table: Count and Wins show sample size and successes over the window. P(win) is a prior-stabilized estimate. Dispersion percent rank near the high threshold flags stretched alignment; near the low threshold flags tight clustering.
Practical Workflows & Combinations
Trend following: Enter only on new stack markers aligned with structure such as higher highs and higher lows for bull, or lower lows and lower highs for bear. Use the consensus RSI to avoid chasing into overbought or oversold extremes.
Exits and stops: Consider reducing exposure when dispersion percent rank reaches the high threshold or when the stack loses ordering. Use the table’s P(win) as a context check rather than a direct signal.
Multi-asset and multi-timeframe: Defaults travel well on liquid assets from intraday to daily. Combine with higher-timeframe structure or moving averages for regime confirmation. The script itself does not fetch higher-timeframe data.
Behavior, Constraints & Performance
Repaint and confirmation: Stack markers evaluate on the live bar and can flip until close. Alert behavior follows TradingView settings. Outcome evaluation uses matured events and does not look into the future.
HTF and security: Not used. Repaint paths from higher-timeframe aggregation are avoided by design.
Resources: max bars back is two thousand. The script uses rolling sums, percent rank, gradient rendering, and a last-bar table update. Shapes and colored wicks add draw overhead.
Known limits: Lag can appear after sharp turns. Very small windows can overfit recent noise. P(win) is sensitive to sample size and priors. Dispersion normalization depends on the collection period.
Sensible Defaults & Quick Tuning
Start with the shipped defaults.
Too many flips: Increase stacking tolerance, enable midline gates, or lengthen the collection period.
Too sluggish: Reduce stacking tolerance, shorten the collection period, or relax midline gates.
Sparse samples: Extend the rolling window or increase priors to stabilize P(win).
Visual overload: Disable gradient squares or wick coloring, or raise transparency.
What this indicator is—and isn’t
This is a visualization and context layer for RSI stack regimes with simple outcome statistics. It is not a complete trading system, not predictive, and not a signal generator on its own. Use it with market structure, risk controls, and position management that fit your process.
Metadata
- Pine version: v6
- Overlay: false (price overlays are drawn via forced overlay where applicable)
- Primary outputs: Four RSI lines, consensus line, OB/OS guides, background tint, entry markers, gradient bars and wicks, statistics table
- Inputs with defaults: See Parameter Guide
- Metrics and functions used: RSI, rolling sums, percent rank, dispersion across RSI set, gradient color mapping, table rendering, alerts
- Special techniques: Ordered RSI stacking with tolerance, optional midline gating, horizon-based outcome maturation, prior-stabilized win rate, gradient normalization with gamma shaping
- Performance and constraints: max bars back two thousand, rendering of shapes and table on last bar, no higher-timeframe data, no security calls
- Recommended use-cases: Regime confirmation, momentum alignment, post-entry management with dispersion and recent outcome context
- Compatibility: Works across assets and timeframes that support RSI
- Limitations and risks: Sensitive to parameter choices and market regime changes; not a standalone strategy
- Diagnostics: Statistics table, dispersion percent rank, gradient intensity
Disclaimer
The content provided, including all code and materials, is strictly for educational and informational purposes only. It is not intended as, and should not be interpreted as, financial advice, a recommendation to buy or sell any financial instrument, or an offer of any financial product or service. All strategies, tools, and examples discussed are provided for illustrative purposes to demonstrate coding techniques and the functionality of Pine Script within a trading context.
Any results from strategies or tools provided are hypothetical, and past performance is not indicative of future results. Trading and investing involve high risk, including the potential loss of principal, and may not be suitable for all individuals. Before making any trading decisions, please consult with a qualified financial professional to understand the risks involved.
By using this script, you acknowledge and agree that any trading decisions are made solely at your discretion and risk.
Best regards and happy trading
Chervolino.
Do not use this indicator on Heikin-Ashi, Renko, Kagi, Point-and-Figure, or Range charts, as these chart types can produce unrealistic results for signal markers and alerts.
Mongoose Global Conflict Risk Index v1Overview
The Mongoose Global Conflict Risk Index v1 is a multi-asset composite indicator designed to track the early pricing of geopolitical stress and potential conflict risk across global markets. By combining signals from safe havens, volatility indices, energy markets, and emerging market equities, the index provides a normalized 0–10 score with clear bias classifications (Neutral, Caution, Elevated, High, Shock).
This tool is not predictive of headlines but captures when markets are clustering around conflict-sensitive assets before events are widely recognized.
Methodology
The indicator calculates rolling rate-of-change z-scores for eight conflict-sensitive assets:
Gold (XAUUSD) – classic safe haven
US Dollar Index (DXY) – global reserve currency flows
VIX (Equity Volatility) – S&P 500 implied volatility
OVX (Crude Oil Volatility Index) – energy stress gauge
Crude Oil (CL1!) – WTI front contract
Natural Gas (NG1!) – energy security proxy, especially Europe
EEM (Emerging Markets ETF) – global risk capital flight
FXI (China ETF) – Asia/China proxy risk
Rules:
Safe havens and vol indices trigger when z-score > threshold.
Energy triggers when z-score > threshold.
Risk assets trigger when z-score < –threshold.
Each trigger is assigned a weight, summed, normalized, and scaled 0–10.
Bias classification:
0–2: Neutral
2–4: Caution
4–6: Elevated
6–8: High
8–10: Conflict Risk-On
How to Use
Timeframes:
Daily (1D) for strategic signals and early warnings.
4H for event shocks (missiles, sanctions, sudden escalations).
Weekly (1W) for sustained trends and macro build-ups.
What to Look For:
A single trigger (for example, Gold ON) may be noise.
A cluster of 2–3 triggers across Gold, USD, VIX, and Energy often marks early stress pricing.
Elevated readings (>4) = caution; High (>6) = rotation into havens; Shock (>8) = market conviction of conflict risk.
Practical Application:
Monitor as a heatmap of global stress.
Combine with fundamental or headline tracking.
Use alert conditions at ≥4, ≥6, ≥8 for systematic monitoring.
Notes
This indicator is for informational and educational purposes only.
It is not financial advice and should be used in conjunction with other analysis methods.
cd_indiCATor_CxGeneral:
This indicator is the redesigned, simplified, and feature-enhanced version of the previously shared indicators:
cd_cisd_market_Cx, cd_HTF_Bias_Cx, cd_sweep&cisd_Cx, cd_SMT_Sweep_CISD_Cx, and cd_RSI_divergence_Cx.
Within the holistic setup, the indicator tracks:
• HTF bias
• Market structure (trend) in the current timeframe
• Divergence between selected pairs (SMT)
• Divergence between price and RSI values
• Whether the price is in an important area (FVG, iFVG, and Volume Imbalance)
• Whether the price is at a key level
• Whether the price is within a user-defined special timeframe
The main condition and trigger of the setup is an HTF sweep with CISD confirmation on the aligned timeframe.
When the main condition occurs, the indicator provides the user with a real-time market status summary, enriched with other data.
________________________________________
What’s new?
-In the SMT module:
• Triad SMT analysis (e.g.: NQ1!, ES1!, and YM1!)
• Dyad SMT analysis (e.g.: EURUSD, GBPUSD)
• Alternative pair definition and divergence analysis for non-correlated assets
o For crypto assets (xxxUSDT <--> xxxUSDT.P) (e.g.: SOLUSDT.P, SOLUSDT)
o For stocks, divergence analysis by comparing the asset with its value in another currency
(BIST:xxx <--> BIST:xxx / EURTRY), (BAT:xxx <--> BAT:xxx / EURUSD)
-Special timeframe definition
-Configurable multi-option alarm center
-Alternative summary presentation (check list / status table / stickers)
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Details and usage:
The user needs to configure four main sections:
• Pair and correlated pairs
• Timeframes (Auto / Manual)
• Alarm center
• Visual arrangement and selections
Pair Selections:
The user should adjust trading pairs according to their trade preferences.
Examples:
• Triad: NQ1!-ES1!-YM1!, BTC-ETH-Total3
• Dyad: NAS100-US500, XAUUSD-XAGUSD, XRPUSDT-XLMUSDT
Single pairs:
-Crypto Assets:
If crypto assets are not in the triad or dyad list, they are automatically matched as:
Perpetual <--> Spot (e.g.: DOGEUSDT.P <--> DOGEUSDT)
If the asset is already defined in a dyad list (e.g., DOGE – SHIB), the dyad definition takes priority.
________________________________________
-Stocks:
If stocks are defined in the dyad list (e.g.: BIST:THYAO <--> BIST:PGSUS), the dyad definition takes priority.
If not defined, the stock is compared with its value in the selected currency.
For example, in the Turkish Stock Exchange:
BIST:FENER stock, if EUR is chosen from the menu, is compared as BIST:FENER / OANDA:EURTRY.
Here, “OANDA” and the stock market currency (TRY) are automatically applied for the exchange rate.
For NYSE:XOM, its pair will be NYSE:XOM / EURUSD.
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Timeframes:
By default, the menu is set to “Auto.” In this mode, aligned timeframes are automatically selected.
Aligned timeframes (LTF-HTF):
1m-15m, 3m-30m, 5m-1h, 15m-4h, 1h-D, 4h-W, D-M
Example: if monitoring the chart on 5m:
• 1h sweep + 5m CISD confirmation
• D sweep + 1h CISD confirmation (bias)
• 5m market structure
• 1h SMT and 1h RSI divergence analysis
For manual selections, the user must define the timeframes for Sweep and HTF bias.
FVG, iFVG, and Volume Imbalance timeframes must be manually set in both modes.
________________________________________
Alarm Center:
The user can choose according to preferred criteria.
Each row has options.
“Yes” → included in alarm condition.
“No” → not included in alarm condition.
If special timeframe criteria are added to the alarm, the hour range must also be entered in the same row, and the “Special Zone” tab (default: -4) should be checked.
Key level timeframes and plot options must be set manually.
Example alarm setup:
Alongside the main Sweep + CISD condition, if we also want HTF bias + Trend alignment + key level (W, D) and special timeframe (09:00–11:00), we should set up the menu as follows:
________________________________________
Visual Arrangement and Selections:
Users can control visibility with checkboxes according to their preferences.
In the Table & Sticker tab, table options and labels can be controlled.
• Summary Table has two options: Check list and Status Table
• From the HTF bias section, real-time bias and HTF sweep zone (optional) are displayed
• The RSI divergence section only shows divergence analysis results
• The SMT 2 sub-section only functions when triad is selected
Labels are shown on the bar where the sweep + CISD condition occurs, displaying the current situation.
With the Check box option, all criteria’s real-time status is shown (True/False).
Status Table provides a real-time summary table.
Although the menu may look crowded, most settings only need to be adjusted once during initial use.
________________________________________
What’s next?
• Suggestions from users
• Standard deviation projection
• Mitigation/order blocks (cd special mtg)
• PSP /TPD
________________________________________
Final note:
Every additional criterion in the alarm settings will affect alarm frequency.
Multiple conditions occurring at the same time is not, by itself, sufficient to enter a trade—you should always apply your own judgment.
Looking forward to your feedback and suggestions.
Happy trading! 🎉
Structural Liquidity Signals [BullByte]Structural Liquidity Signals (SFP, FVG, BOS, AVWAP)
Short description
Detects liquidity sweeps (SFPs) at pivots and PD/W levels, highlights the latest FVG, tracks AVWAP stretch, arms percentile extremes, and triggers after confirmed micro BOS.
Full description
What this tool does
Structural Liquidity Signals shows where price likely tapped liquidity (stop clusters), then waits for structure to actually change before it prints a trigger. It spots:
Liquidity sweeps (SFPs) at recent pivots and at prior day/week highs/lows.
The latest Fair Value Gap (FVG) that often “pulls” price or serves as a reaction zone.
How far price is stretched from two VWAP anchors (one from the latest impulse, one from today’s session), scaled by ATR so it adapts to volatility.
A “percentile” extreme of an internal score. At extremes the script “arms” a setup; it only triggers after a small break of structure (BOS) on a closed bar.
Originality and design rationale, why it’s not “just a mashup”
This is not a mashup for its own sake. It’s a purpose-built flow that links where liquidity is likely to rest with how structure actually changes:
- Liquidity location: We focus on areas where stops commonly cluster—recent pivots and prior day/week highs/lows—then detect sweeps (SFPs) when price wicks beyond and closes back inside.
- Displacement context: We track the last Fair Value Gap (FVG) to account for recent inefficiency that often acts as a magnet or reaction zone.
- Stretch measurement: We anchor VWAP to the latest N-bar impulse and to the Daily session, then normalize stretch by ATR to assess dislocation consistently across assets/timeframes.
- Composite exhaustion: We combine stretch, wick skew, and volume surprise, then bend the result with a tanh transform so extremes are bounded and comparable.
- Dynamic extremes and discipline: Rather than triggering on every sweep, we “arm” at statistical extremes via percent-rank and only fire after a confirmed micro Break of Structure (BOS). This separates “interesting” from “actionable.”
Key concepts
SFP (liquidity sweep): A candle briefly trades beyond a level (where stops sit) and closes back inside. We detect these at:
Pivots (recent swing highs/lows confirmed by “left/right” bars).
Prior Day/Week High/Low (PDH/PDL/PWH/PWL).
FVG (Fair Value Gap): A small 3‑bar gap (bar2 high vs bar1 low, or vice versa). The latest gap often acts like a magnet or reaction zone. We track the most recent Up/Down gap and whether price is inside it.
AVWAP stretch: Distance from an Anchored VWAP divided by ATR (volatility). We use:
Impulse AVWAP: resets on each new N‑bar high/low.
Daily AVWAP: resets each new session.
PR (Percentile Rank): Where the current internal score sits versus its own recent history (0..100). We arm shorts at high PR, longs at low PR.
Micro BOS: A small break of the recent high (for longs) or low (for shorts). This is the “go/no‑go” confirmation.
How the parts work together
Find likely liquidity grabs (SFPs) at pivots and PD/W levels.
Add context from the latest FVG and AVWAP stretch (how far price is from “fair”).
Build a bounded score (so different markets/timeframes are comparable) and compute its percentile (PR).
Arm at extremes (high PR → short candidate; low PR → long candidate).
Only print a trigger after a micro BOS, on a closed bar, with spacing/cooldown rules.
What you see on the chart (legend)
Lines:
Teal line = Impulse AVWAP (resets on new N‑bar extreme).
Aqua line = Daily AVWAP (resets each session).
PDH/PDL/PWH/PWL = prior day/week levels (toggle on/off).
Zones:
Greenish box = latest Up FVG; Reddish box = latest Down FVG.
The shading/border changes after price trades back through it.
SFP labels:
SFP‑P = SFP at Pivot (dotted line marks that pivot’s price).
SFP‑L = SFP at Level (at PDH/PDL/PWH/PWL).
Throttle: To reduce clutter, SFPs are rate‑limited per direction.
Triggers:
Triangle up = long trigger after BOS; triangle down = short trigger after BOS.
Optional badge shows direction and PR at the moment of trigger.
Optional Trigger Zone is an ATR‑sized box around the trigger bar’s close (for visualization only).
Background:
Light green/red shading = a long/short setup is “armed” (not a trigger).
Dashboard (Mini/Pro) — what each item means
PR: Percentile of the internal score (0..100). Near 0 = bullish extreme, near 100 = bearish extreme.
Gauge: Text bar that mirrors PR.
State: Idle, Armed Long (with a countdown), or Armed Short.
Cooldown: Bars remaining before a new setup can arm after a trigger.
Bars Since / Last Px: How long since last trigger and its price.
FVG: Whether price is in the latest Up/Down FVG.
Imp/Day VWAP Dist, PD Dist(ATR): Distance from those references in ATR units.
ATR% (Gate), Trend(HTF): Status of optional regime filters (volatility/trend).
How to use it (step‑by‑step)
Keep the Safety toggles ON (default): triggers/visuals on bar‑close, optional confirmed HTF for trend slope.
Choose timeframe:
Intraday (5m–1h) or Swing (1h–4h). On very fast/thin charts, enable Performance mode and raise spacing/cooldown.
Watch the dashboard:
When PR reaches an extreme and an SFP context is present, the background shades (armed).
Wait for the trigger triangle:
It prints only after a micro BOS on a closed bar and after spacing/cooldown checks.
Use the Trigger Zone box as a visual reference only:
This script never tells you to buy/sell. Apply your own plan for entry, stop, and sizing.
Example:
Bullish: Sweep under PDL (SFP‑L) and reclaim; PR in lower tail arms long; BOS up confirms → long trigger on bar close (ATR-sized trigger zone shown).
Bearish: Sweep above PDH/pivot (SFP‑L/P) and reject; PR in upper tail arms short; BOS down confirms → short trigger on bar close (ATR-sized trigger zone shown).
Settings guide (with “when to adjust”)
Safety & Stability (defaults ON)
Confirm triggers at bar close, Draw visuals at bar close: Keep ON for clean, stable prints.
Use confirmed HTF values: Applies to HTF trend slope only; keeps it from changing until the HTF bar closes.
Performance mode: Turn ON if your chart is busy or laggy.
Core & Context
ATR Length: Bigger = smoother distances; smaller = more reactive.
Impulse AVWAP Anchor: Larger = fewer resets; smaller = resets more often.
Show Daily AVWAP: ON if you want session context.
Use last FVG in logic: ON to include FVG context in arming/score.
Show PDH/PDL/PWH/PWL: ON to see prior day/week levels that often attract sweeps.
Liquidity & Microstructure
Pivot Left/Right: Higher values = stronger/rarer pivots.
Min Wick Ratio (0..1): Higher = only more pronounced SFP wicks qualify.
BOS length: Larger = stricter BOS; smaller = quicker confirmations.
Signal persistence: Keeps SFP context alive for a few bars to avoid flicker.
Signal Gating
Percent‑Rank Lookback: Larger = more stable extremes; smaller = more reactive extremes.
Arm thresholds (qHi/qLo): Move closer to 0.5 to see more arms; move toward 0/1 to see fewer arms.
TTL, Cooldown, Min bars and Min ATR distance: Space out triggers so you’re not reacting to minor noise.
Regime Filters (optional)
ATR percentile gate: Only allow triggers when volatility is at/above a set percentile.
HTF trend gate: Only allow longs when the HTF slope is up (and shorts when it’s down), above a minimum slope.
Visuals & UX
Only show “important” SFPs: Filters pivot SFPs by Volume Z and |Impulse stretch|.
Trigger badges/history and Max badge count: Control label clutter.
Compact labels: Toggle SFP‑P/L vs full names.
Dashboard mode and position; Dark theme.
Reading PR (the built‑in “oscillator”)
PR ~ 0–10: Potential bullish extreme (long side can arm).
PR ~ 90–100: Potential bearish extreme (short side can arm).
Important: “Armed” ≠ “Enter.” A trigger still needs a micro BOS on a closed bar and spacing/cooldown to pass.
Repainting, confirmations, and HTF notes
By default, prints wait for the bar to close; this reduces repaint‑like effects.
Pivot SFPs only appear after the pivot confirms (after the chosen “right” bars).
PD/W levels come from the prior completed candles and do not change intraday.
If you enable confirmed HTF values, the HTF slope will not change until its higher‑timeframe bar completes (safer but slightly delayed).
Performance tips
If labels/zones clutter or the chart lags:
Turn ON Performance mode.
Hide FVG or the Trigger Zone.
Reduce badge history or turn badge history off.
If price scaling looks compressed:
Keep optional “score”/“PR” plots OFF (they overlay price and can affect scaling).
Alerts (neutral)
Structural Liquidity: LONG TRIGGER
Structural Liquidity: SHORT TRIGGER
These fire when a trigger condition is met on a confirmed bar (with defaults).
Limitations and risk
Not every sweep/extreme reverses; false triggers occur, especially on thin markets and low timeframes.
This indicator does not provide entries, exits, or position sizing—use your own plan and risk control.
Educational/informational only; no financial advice.
License and credits
© BullByte - MPL 2.0. Open‑source for learning and research.
Built from repeated observations of how liquidity runs, imbalance (FVG), and distance from “fair” (AVWAPs) combine, and how a small BOS often marks the moment structure actually shifts.
DCA Cost Basis (with Lump Sum)DCA Cost Basis (with Lump Sum) — Pine Script v6
This indicator simulates a Dollar Cost Averaging (DCA) plan directly on your chart. Pick a start date, choose how often to buy (daily/weekly/monthly), set the per-buy amount, optionally add a one-time lump sum on the first date, and visualize your evolving average cost as a VWAP-style line.
Features
Customizable DCA Plan — Set Start Date , buy Frequency (Daily / Weekly / Monthly), and Recurring Amount (in quote currency, e.g., USD).
Lump Sum Option — Add a one-time lump sum on the very first eligible date; recurring DCA continues automatically after that.
Cost Basis Line — Plots the live average price (Total Cost / Total Units) as a smooth, VWAP-style line for instant breakeven awareness.
Buy Markers — Optional triangles below bars to show when simulated buys occur.
Performance Metrics — Tracks:
Total Invested (quote)
Total Units (base)
Cost Basis (avg entry)
Current Value (mark-to-market)
CAGR (Annualized) from first buy to current bar
On-Chart Summary Table — Displays Start Date, Plan Type (Lump + DCA or DCA only), Total Invested, and CAGR (Annualized).
Data Window Integration — All key values also appear in the Data Window for deeper inspection.
Why use it?
Visualize long-term strategies for Bitcoin, crypto, or stocks.
See how a lump sum affects your average entry over time.
Gauge breakeven at a glance and evaluate historical performance.
Note: This tool is for educational/simulation purposes. Results are based on bar closes and do not represent live orders or fees.
Parabolic Move Indicator for catching moves with Penny Stocks.
Catch the day’s first big moves! Track premarket gap-ups or gap-downs, then spot early momentum shifts using volume, RSI, VWAP, EMAs, and breakout levels—perfect for acting on strong intraday setups right at market open.
**Description:**
The Parabolic Move Scanner + VWAP Bands + EMAs indicator helps traders identify **high-probability intraday moves**, particularly immediately after market open. It is ideal for stocks that **gap up or down premarket, pull back slightly, and then show renewed strength or weakness** once regular trading begins.
The indicator combines multiple components for precise signals:
* **Relative Volume Filter: ** Highlights bars with unusually high activity to ensure signals are backed by real participation.
* **RSI Momentum Change: ** Detects sudden momentum shifts to identify early strength or weakness.
* **Recent Highs/Lows Breakout: ** Confirms price is breaking short-term resistance or support.
* **VWAP & Standard Deviation Bands: ** Provides intraday trend reference points, with optional daily reset.
* **Exponential Moving Averages (EMAs): ** Tracks trend across short, medium, and long-term intraday periods.
* **Visual Signals: ** Background highlights and horizontal breakout lines make it easy to spot key bars.
* **Alerts: ** Configurable alerts notify you of bullish or bearish parabolic moves.
**Optimal Use Case: **
Use in the first 15–30 minutes after market open at 1 minute Time Frame. Best for **stocks showing a premarket gap followed by a pullback**, then resuming strength (bullish) or weakness (bearish). The combination of **volume, RSI, breakouts, VWAP, and EMAs** ensures you identify the **day’s biggest marktet open moves especially with penny stocks moves** with higher confidence.
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### **Recommended Settings**
**Component** | **Recommended Setting** | **Description / Purpose**
| **Volume Average Length** | 20 bars | Period for calculating average volume to detect relative spikes. |
| **Volume Multiplier** | 2.0 | Current bar volume must exceed 2× average to signal high activity. |
| **RSI Length** | 7 bars | Short-term RSI period to measure momentum changes. |
| **RSI Change Threshold** | 7 | Minimum RSI change required to trigger momentum signal. |
| **Recent Highs Lookback** | 5 bars | Number of bars to check for short-term breakout levels. |
| **Horizontal Line Length** | 10 bars | Length of horizontal breakout line drawn on the chart. |
| **Horizontal Line Color** | Green (bullish) / Red (bearish) | Visual identification of breakout levels. |
| **Horizontal Line Thickness** | 1 | Line width for breakout visualization. |
| **VWAP Source** | hlc3 | Price source for VWAP calculation. |
| **VWAP Bands Multipliers** | 1×, 2×, 3× | Standard deviation multiples for intraday bands.
| **VWAP Daily Reset** | Enabled | Resets VWAP at the start of each trading day.
| **EMA Lengths** | 9, 13, 20, 33, 50 | Short, medium, and long-term EMAs to track intraday trend. |
| **Enable Bearish Signals** | True | Allows detection of bearish parabolic moves. |
|
Theil-Sen Line Filter [BackQuant]Theil-Sen Line Filter
A robust, median-slope baseline that tracks price while resisting outliers. Designed for the chart pane as a clean, adaptive reference line with optional candle coloring and slope-flip alerts.
What this is
A trend filter that estimates the underlying slope of price using a Theil-Sen style median of past slopes, then advances a baseline by a controlled fraction of that slope each bar. The result is a smooth line that reacts to real directional change while staying calm through noise, gaps, and single-bar shocks.
Why Theil-Sen
Classical moving averages are sensitive to outliers and shape changes. Ordinary least squares is sensitive to large residuals. The Theil-Sen idea replaces a single fragile estimate with the median of many simple slopes, which is statistically robust and less influenced by a few extreme bars. That makes the baseline steadier in choppy conditions and cleaner around regime turns.
What it plots
Filtered baseline that advances by a fraction of the robust slope each bar.
Optional candle coloring by baseline slope sign for quick trend read.
Alerts when the baseline slope turns up or down.
How it behaves (high level)
Looks back over a fixed window and forms many “current vs past” bar-to-bar slopes.
Takes the median of those slopes to get a robust estimate for the bar.
Optionally caps the magnitude of that per-bar slope so a single volatile bar cannot yank the line.
Moves the baseline forward by a user-controlled fraction of the estimated slope. Lower fractions are smoother. Higher fractions are more responsive.
Inputs and what they do
Price Source — the series the filter tracks. Typical is close; HL2 or HLC3 can be smoother.
Window Length — how many bars to consider for slopes. Larger windows are steadier and slower. Smaller windows are quicker and noisier.
Response — fraction of the estimated slope applied each bar. 1.00 follows the robust slope closely; values below 1.00 dampen moves.
Slope Cap Mode — optional guardrail on each bar’s slope:
None — no cap.
ATR — cap scales with recent true range.
Percent — cap scales with price level.
Points — fixed absolute cap in price points.
ATR Length / Mult, Cap Percent, Cap Points — tune the chosen cap mode’s size.
UI Settings — show or hide the line, paint candles by slope, choose long and short colors.
How to read it
Up-slope baseline and green candles indicate a rising robust trend. Pullbacks that do not flip the slope often resolve in trend direction.
Down-slope baseline and red candles indicate a falling robust trend. Bounces against the slope are lower-probability until proven otherwise.
Flat or frequent flips suggest a range. Increase window length or decrease response if you want fewer whipsaws in sideways markets.
Use cases
Bias filter — only take longs when slope is up, shorts when slope is down. It is a simple way to gate faster setups.
Stop or trail reference — use the line as a trailing guide. If price closes beyond the line and the slope flips, consider reducing exposure.
Regime detector — widen the window on higher timeframes to define major up vs down regimes for asset rotation or risk toggles.
Noise control — enable a cap mode in very volatile symbols to retain the line’s continuity through event bars.
Tuning guidance
Quick swing trading — shorter window, higher response, optionally add a percent cap to keep it stable on large moves.
Position trading — longer window, moderate response. ATR cap tends to scale well across cycles.
Low-liquidity or gappy charts — prefer longer window and a points or ATR cap. That reduces jumpiness around discontinuities.
Alerts included
Theil-Sen Up Slope — baseline’s one-bar change crosses above zero.
Theil-Sen Down Slope — baseline’s one-bar change crosses below zero.
Strengths
Robust to outliers through median-based slope estimation.
Continuously advances with price rather than re-anchoring, which reduces lag at turns.
User-selectable slope caps to tame shock bars without over-smoothing everything.
Minimal visuals with optional candle painting for fast regime recognition.
Notes
This is a filter, not a trading system. It does not account for execution, spreads, or gaps. Pair it with entry logic, risk management, and higher-timeframe context if you plan to use it for decisions.
Session & Swing Levels + Smart AlertsMulti-Timeframe Level Tracker with Advanced Alert System
This comprehensive indicator combines session-based trading levels with multi-timeframe swing analysis, for key level identification and alert management.
Key Features:
Session Analysis:
Asia Session (7:00 PM - 4:00 AM ET) - Tracks high/low levels during Asian market hours
London Session (3:00 AM - 11:00 AM ET) - Identifies key European session levels
Previous Day Levels - Displays prior day's high and low levels
Visual session backgrounds and customizable timezone support
Multi-Timeframe Swing Detection:
Up to 5 configurable timeframes (default: 15m, 1h, 4h, 1D, 1W)
Intelligent swing high/low identification using customizable pivot strength
Each timeframe uses distinct colors for easy identification
Advanced Alert System:
Anti-repainting protection - Alerts only trigger on confirmed bars for reliable live trading
Specific alert messages for each level type (Asia High, London Low, Previous Day levels, etc.)
Individual alert toggles for each session and timeframe
Timestamps in Eastern Time for consistency
Visual Customization:
Independent color schemes for sessions and timeframes
Configurable line styles (solid, dashed, dotted) and widths
Separate styling for active vs. mitigated levels
Optional line extension past mitigation points
📊 How It Works:
Level Creation: Automatically identifies and draws key levels at session closes
Mitigation Detection: Monitors price interaction with levels in real-time
Visual Updates: Changes line appearance when levels are crossed
Smart Alerts: Sends targeted notifications with level-specific information
Globex Overnight Futures ORB with FIB's by TenAMTrader📌 Globex Overnight Futures ORB with FIB’s – by TenAMTrader
This indicator is designed for futures traders who want to track the Globex Overnight Opening Range (ORB) and apply Fibonacci projections to anticipate potential support/resistance zones. It’s especially useful for traders who follow overnight sessions (such as ES, NQ, CL) and want to map out key levels before the U.S. regular session begins.
⚙️ How It Works
Primary Range (ORB):
You define a start and end time (default set to 18:00 – 18:15 EST). During this period, the script tracks the session high, low, and midpoint.
Opening Range Plots:
High Line (green)
Low Line (red)
Midpoint Line (yellow)
A shaded cloud between High–Mid and Mid–Low for easy visualization.
Fibonacci Projections:
Once the ORB is complete, the script calculates a full suite of Fibonacci retracements and extensions (e.g., 0.236, 0.382, 0.618, 1.0, 1.618, 2.0).
Standard key levels (0.618, 0.786, 1.0, etc.) are always shown if enabled.
Optional extended levels (1.236, 1.382, 1.5, 2.0, etc.) can be toggled on/off.
"Between Range" fibs (such as 0.382 and 0.618 inside the ORB) are also available for traders who like intra-range precision.
🔧 User Settings
Time Inputs: Choose your ORB start/end time.
Color Controls: Customize high, low, midpoint, and fib line colors.
Display Toggles: Turn on/off High, Low, Midpoint lines and Fibonacci projections.
Fib Extensions Toggle: Decide whether to show only major fibs or all extensions.
Alerts (Optional): Alerts can be set for crossing the ORB High, Low, or Midpoint.
📊 Practical Use Cases
Breakout Traders: Use the ORB high/low as breakout triggers.
Mean Reversion Traders: Watch for rejections near fib extension levels.
Overnight Futures Monitoring: Track Globex behavior to prepare for RTH open.
Risk Management: ORB and Fib levels make for natural stop/target placement zones.
⚠️ Disclaimer
This indicator is provided for educational and informational purposes only. It does not constitute financial advice, investment advice, or trading recommendations. Trading futures involves substantial risk of loss and may not be suitable for all investors. Always do your own due diligence and consult with a licensed financial professional before making trading decisions.
200 EMA w/ Ticker Memory200 EMA w/ Ticker Memory — Multi-Symbol & Multi-Timeframe EMA Tracker with Alerts
Overview
The 200 EMA w/ Ticker Memory indicator allows you to monitor the 200-period Exponential Moving Average (EMA) across multiple symbols and timeframes. Designed for traders managing multiple tickers, it provides customizable timeframe inputs per symbol and instant alerts on price touches of the 200 EMA.
Key Features
Multi-symbol support: Configure up to 20 different symbols, each with its own timeframe setting.
Flexible timeframe input: Assign specific timeframes per symbol or use a default timeframe fallback.
Accurate 200 EMA calculation: Uses request.security to fetch 200 EMA from the symbol-specific timeframe.
Visual EMA plots: Displays both the EMA on the selected timeframe and the EMA on the current chart timeframe for comparison.
Touch alerts: Configurable alerts when price “touches” the 200 EMA within a user-defined sensitivity percentage.
Ticker memory: Remembers your configured symbols and displays them in an on-chart table.
Compact info table: Displays current symbol status, alert settings, and timeframe in a clean, transparent table overlay.
How to Use
Configure Symbols and Timeframes:
Input your desired symbols (up to 20) and their respective timeframes under the “Symbol Settings” groups in the indicator’s settings pane.
Set Default Timeframe:
Choose a default timeframe to be used when no specific timeframe is assigned for a symbol.
Adjust Alert Settings:
Enable or disable alerts and set the touch sensitivity (% distance from EMA to trigger alerts).
Alerts
Alerts trigger once per bar when the price touches the 200 EMA within the defined sensitivity threshold.
Alert messages include:
Symbol / Current price / EMA value / EMA timeframe used / Chart timeframe / Timestamp
Customization
200 EMA Color: Change the line color for better visibility.
Touch Sensitivity: Fine-tune how close price must be to the EMA to count as a touch (default 0.1%).
Enable Touch Alerts: Turn on/off alert notifications easily.
For:
- Swing traders monitoring multiple stocks or assets.
- Day traders watching key EMA levels on different timeframes.
- Analysts requiring a quick visual and alert system for 200 EMA touches.
- Portfolio managers tracking key technical levels across various securities.
Limitations
Supports up to 20 configured symbols (can be extended manually if needed).
Works best on charts with reasonable bar frequency due to request.security usage.
Alert frequency is limited to once per bar for clarity.
Disclaimer
This indicator is provided “as-is” for educational and informational purposes only. It does not guarantee trading success or financial gain.
