BullTrader - ParabolicSARFlipSignals(NonRepainting)🧠 Concept & Purpose
This indicator isolates the confirmed trend‑change events produced by the Parabolic SAR and turns them into direct, non‑repainting trade signals.
Instead of plotting every SAR dot as a potential entry, it marks only the bars where price has closed across the SAR line, confirming a genuine flip from bullish → bearish or vice versa.
Each confirmed flip is displayed with a single triangle on the chart and can be connected to alerts.
The design is intentionally minimal: one simple but reliable algorithmic definition of “the trend just turned.”
⚙️ How It Works
1. The script calculates the standard Parabolic SAR value using the built‑in ta.sar() function.
2. When a candle closes above a SAR dot that was previously above price → uptrend starts (Buy Signal).
3. When a candle closes below a SAR dot that was previously below price → downtrend starts (Sell Signal).
4. Signals are confirmed only after the bar closes (barstate.isconfirmed), guaranteeing no repainting.
5. Each event can trigger an alert or simply serve as a visual reversal marker.
📈 Chart Elements
Element Description
🟠 Orange cross dots Standard Parabolic SAR trail.
🟢 Triangle below bar Confirmed SAR flip up → new bullish phase.
🔴 Triangle above bar Confirmed SAR flip down → new bearish phase.
Optional green/red background Highlights bars where a confirmed flip occurred.
🔔 Alerts
Use buySignalFinal for Buy alerts and sellSignalFinal for Sell alerts.
Set alerts to “Once per bar close” to match the non‑repainting confirmation logic.
📊 Best Use
* Identifying clear trend reversals.
* As an entry / exit overlay for manual trading.
* As a base signal for automated or alert‑driven systems.
This version keeps the indicator fast, reproducible, and completely non‑repainting — ideal for traders who prefer transparent and verifiable signals derived directly from Per J. Wilder’s original Parabolic SAR formula.
חפש סקריפטים עבור "algo"
DEMA Flow [Alpha Extract]A sophisticated trend identification system that combines Double Exponential Moving Average methodology with advanced HL median filtering and ATR-based band detection for precise trend confirmation. Utilizing dual-layer smoothing architecture and volatility-adjusted breakout zones, this indicator delivers institutional-grade flow analysis with minimal lag while maintaining exceptional noise reduction. The system's intelligent band structure with asymmetric ATR multipliers provides clear trend state classification through price position analysis relative to dynamic threshold levels.
🔶 Advanced DEMA Calculation Engine
Implements double exponential moving average methodology using cascaded EMA calculations to significantly reduce lag compared to traditional moving averages. The system applies dual smoothing through sequential EMA processing, creating a responsive yet stable trend baseline that maintains sensitivity to genuine market structure changes while filtering short-term noise.
// Core DEMA Framework
dema(src, length) =>
EMA1 = ta.ema(src, length)
EMA2 = ta.ema(EMA1, length)
DEMA_Value = 2 * EMA1 - EMA2
DEMA_Value
// Primary Calculation
DEMA = dema(close, DEMA_Length)
2H
🔶 HL Median Filter Smoothing Architecture
Features sophisticated high-low median filtering using rolling window analysis to create ultra-smooth trend baselines with outlier resistance. The system constructs dynamic arrays of recent DEMA values, sorts them for median extraction, and handles both odd and even window lengths for optimal smoothing consistency across all market conditions.
// HL Median Filter Logic
hlMedian(src, length) =>
window = array.new_float()
for i = 0 to length - 1
array.push(window, src)
array.sort(window)
// Median Extraction
lenW = array.size(window)
median = lenW % 2 == 1 ?
array.get(window, lenW / 2) :
(array.get(window, lenW/2 - 1) + array.get(window, lenW/2)) / 2
// Smooth DEMA Calculation
Smooth_DEMA = hlMedian(DEMA_Value, HL_Filter_Length)
🔶 ATR Band Construction Framework
Implements volatility-adaptive band structure using Average True Range calculations with asymmetric multiplier configuration for optimal trend identification. The system creates upper and lower threshold bands around the smoothed DEMA baseline with configurable ATR multipliers, enabling precise trend state determination through price breakout analysis.
// ATR Band Calculation
atrBands(src, atr_length, upper_mult, lower_mult) =>
ATR = ta.atr(atr_length)
Upper_Band = src + upper_mult * ATR
Lower_Band = src - lower_mult * ATR
// Band Generation
= atrBands(Smooth_DEMA, ATR_Length, Upper_ATR_Mult, Lower_ATR_Mult)
15min
🔶 Intelligent Flow Signal Engine
Generates binary trend states through band breakout detection, transitioning to bullish flow when price exceeds upper band and bearish flow when price breaches lower band. The system maintains flow state persistence until opposing band breakout occurs, providing clear trend classification without whipsaw signals during normal volatility fluctuations.
🔶 Comprehensive Visual Architecture
Provides multi-dimensional flow visualization through color-coded DEMA line, trend-synchronized candle coloring, and bar color overlay for complete chart integration. The system uses institutional color scheme with neon green for bullish flow, neon red for bearish flow, and neutral gray for undefined states with configurable band visibility.
🔶 Asymmetric Band Configuration
Features intelligent asymmetric ATR multiplier system with default upper multiplier of 2.1 and lower multiplier of 1.5, optimizing for market dynamics where upside breakouts often require stronger momentum confirmation than downside breaks. This configuration reduces false signals while maintaining sensitivity to genuine flow changes.
🔶 Dual-Layer Smoothing Methodology
Combines DEMA's inherent lag reduction with HL median filtering to create exceptional smoothing without sacrificing responsiveness. The system first applies double exponential smoothing for initial noise reduction, then applies median filtering to eliminate outliers and create ultra-clean flow baseline suitable for high-frequency and institutional trading applications.
🔶 Alert Integration System
Features comprehensive alert framework for flow state transitions with customizable notifications for bullish and bearish flow confirmations. The system provides real-time alerts on crossover events with clear directional indicators and exchange/ticker integration for multi-symbol monitoring capabilities.
🔶 Performance Optimization Framework
Utilizes efficient array management with optimized median calculation algorithms and minimal variable overhead for smooth operation across all timeframes. The system includes intelligent bar indexing for median filter initialization and streamlined flow state tracking for consistent performance during extended analysis periods.
🔶 Why Choose DEMA Flow ?
This indicator delivers sophisticated flow identification through dual-layer smoothing architecture and volatility-adaptive band methodology. By combining DEMA's reduced-lag characteristics with HL median filtering and ATR-based breakout zones, it provides institutional-grade flow analysis with exceptional noise reduction and minimal false signals. The system's asymmetric band structure and comprehensive visual integration make it essential for traders seeking systematic trend-following approaches across cryptocurrency, forex, and equity markets with clear entry/exit signals and comprehensive alert capabilities for automated trading strategies.
Quantura - Session High/LowIntroduction
“Quantura – Session High/Low” is a professional-grade session mapping indicator that automatically identifies and visualizes the highs, lows, and ranges of key global trading sessions — London, New York, and Asia. It helps traders understand when and where liquidity tends to accumulate, allowing for better market structure analysis and session-based strategy alignment.
Originality & Value
This indicator unifies the three most influential global sessions into a single, adaptive visualization tool. Unlike typical session indicators, it dynamically updates live session highs and lows in real time while marking session boundaries and transitions. Its multi-session management system allows for immediate recognition of overlapping liquidity zones — a crucial feature for institutional and intraday traders.
The value and originality come from:
Real-time tracking of session highs, lows, and developing ranges.
Simultaneous visualization of multiple global sessions.
Optional vertical range lines for clearer visual segmentation.
Customizable session times, colors, and time zone offset for global accuracy.
Automatically extending and updating lines as each session progresses.
Functionality & Core Logic
Detects the start and end of each trading session (London, New York, Asia) using built-in time logic and user-defined UTC offsets.
Initializes session-specific high and low variables at the start of each new session.
Continuously updates session high/low levels as new candles form.
Draws color-coded horizontal lines for each session’s high and low.
Optionally adds vertical dotted lines to visually connect session range extremes.
Locks each session’s range once it ends, preserving historical structure for review.
Parameters & Customization
New York Session: Enable/disable, customize time (default 15:30–21:30), and set color.
London Session: Enable/disable, customize time (default 09:00–16:30), and set color.
Asia Session: Enable/disable, customize time (default 02:30–08:00), and set color.
Vertical Line: Toggle dotted vertical lines connecting session high and low levels.
UTC Offset: Adjust session timing to align with your chart’s local time zone.
Visualization & Display
Each session is color-coded for quick identification (default: blue for London, red for New York, green for Asia).
Horizontal lines track evolving session highs and lows in real time.
Once a session closes, the lines remain fixed to mark historical range boundaries.
Vertical dotted lines (optional) visually connect the session’s high and low for clarity.
Supports full overlay display without interfering with other technical indicators.
Use Cases
Identify liquidity zones and range extremes formed during active trading sessions.
Observe session overlaps (London–New York) to anticipate volatility spikes.
Combine with volume or market structure tools for session-based confluence.
Track how price interacts with prior session highs/lows to detect potential reversals.
Analyze session-specific performance patterns for algorithmic or discretionary systems.
Limitations & Recommendations
The indicator is designed for intraday analysis and may not provide meaningful output on daily or higher timeframes.
Adjust session times and UTC offset based on your broker’s or exchange’s timezone.
Does not provide trading signals — it visualizes session structure only.
Combine with liquidity and volatility indicators for full contextual understanding.
Markets & Timeframes
Compatible with all asset classes — including crypto, forex, indices, and commodities — and optimized for intraday timeframes (1m–4h). Particularly useful for traders analyzing session overlaps and volatility transitions.
Author & Access
Developed 100% by Quantura. Published as a Open-source script indicator. Access is free.
Compliance Note
This description fully complies with TradingView’s Script Publishing Rules and House Rules . It provides a detailed explanation of functionality, parameters, and realistic use cases without making any performance or predictive claims.
Quantura - Liquidity Sweep & Run LevelsIntroduction
“Quantura – Liquidity Sweep & Run Levels” is a structural price-action indicator designed to automatically detect swing-based liquidity zones and visualize potential sweep and run events. It helps traders identify areas where liquidity has likely been taken (sweep) or released (run), improving precision in market structure analysis and timing of entries or exits.
Originality & Value
This tool translates institutional liquidity concepts into an automated visual framework. Instead of simply marking highs and lows, it dynamically monitors swing points, tracks their breaches, and identifies subsequent reactions. The indicator is built to highlight the liquidity dynamics that often precede reversals or continuations.
Its originality lies in:
Automatic identification and tracking of swing highs and lows.
Real-time detection of broken levels and liquidity sweeps.
Distinction between “Run” and “Sweep” modes for different market behaviors.
Persistent historical visualization of liquidity levels using clean line structures.
Configurable signal markers for bullish and bearish sweep confirmations.
Functionality & Core Logic
Detects swing highs and lows using a user-defined Swing Length parameter.
Stores and updates all swing levels dynamically with arrays for efficient memory handling.
Draws horizontal lines from each detected swing point to visualize potential liquidity zones.
Monitors when price breaks a swing level and marks that event as “broken.”
Generates signals when the market either sweeps above/below or runs away from those levels, depending on the chosen mode.
Provides optional visual signal markers (“▲” for bullish sweeps, “▼” for bearish sweeps).
Parameters & Customization
Mode: Choose between “Sweep” (detects liquidity grabs) or “Run” (detects breakout continuations).
Swing Length: Sets the sensitivity for detecting swing highs/lows. A higher value focuses on larger structures, while smaller values detect micro liquidity points.
Bullish Color / Bearish Color: Customize color themes for sweep/run lines and signal markers.
Signals: Enables or disables visual up/down markers for confirmed events.
Visualization & Display
Horizontal lines represent potential liquidity levels (unbroken swing highs/lows).
Once broken, lines automatically stop extending, marking the moment liquidity is taken.
Depending on the selected mode:
“Sweep” mode identifies false breaks or stop-hunt behavior.
“Run” mode highlights breakouts that continue the trend.
Colored arrows indicate the direction and type of liquidity reaction.
Clean, non-intrusive visualization suitable for overlaying on price charts.
Use Cases
Detect liquidity sweeps before major reversals.
Identify breakout continuations after liquidity runs.
Combine with Supply/Demand or FVG indicators for multi-layered confirmation.
Validate liquidity bias in algorithmic or discretionary strategies.
Analyze market manipulation patterns and institutional stop-hunting behavior.
Limitations & Recommendations
This indicator identifies structural behavior but does not guarantee trade direction or profitability.
Works best on liquid markets with clear swing structures (e.g., crypto, forex, indices).
Signal interpretation should be combined with confluence tools such as volume, order flow, or structure-based filters.
Excessively small swing settings may cause over-signaling in volatile markets.
Markets & Timeframes
Optimized for all major asset classes — including crypto, Forex, indices, and equities — and for intraday to higher-timeframe structural analysis (5-minute up to daily charts).
Author & Access
Developed 100% by Quantura. Published as a Open-source script indicator. Access is free.
Compliance Note
This description fully complies with TradingView’s Script Publishing Rules and House Rules . It avoids performance claims, provides transparency on methodology, and clearly describes indicator behavior and limitations.
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.
Quantura - Average Intraday Candle VolumeIntroduction
“Quantura – Average Intraday Candle Volume” is a quantitative visualization tool that calculates and displays the average traded volume for each intraday time position based on a user-defined historical lookback period. It allows traders to analyze recurring intraday volume patterns, identify high-activity sessions, and detect liquidity shifts throughout the trading day.
Originality & Value
This indicator goes beyond standard volume averages by normalizing and aligning volume data according to the time of day. Instead of simply smoothing recent bars, it builds an intraday volume profile based on historical daily averages, enabling users to understand when during the day volume typically peaks or drops.
Its originality and usefulness come from:
Converting standard volume data into time-aligned intraday averages.
Visualization of historical intraday liquidity behavior, not just total daily volume.
Dynamic scaling using normalization and transparency to emphasize active and quiet periods.
Optional day-separator lines for precise intraday structure recognition.
Gradient-based coloring for better visual interpretation of volume intensity.
Functionality & Core Logic
The indicator divides each day into discrete intraday time positions (based on chart timeframe).
For each position, it stores and updates historical volume values across the selected number of days.
It calculates an average volume per time position by aggregating all stored values and dividing them by the number of valid days.
The result is plotted as a continuous histogram showing typical intraday volume distribution.
The bar colors and transparency dynamically reflect the relative intensity of volume at each point in the day.
Parameters & Customization
Number of Days for Averaging: Defines how many past days are included in the volume average calculation (default: 365).
UTC Offset: Allows synchronization of intraday cycles with local or exchange time zones.
Base Color: Sets the main color for plotted volume columns.
Color Mode: Choose between “Gradient” (transparency dynamically adjusts by intensity) or “Normal” (fixed opacity).
Day Line: Toggles dashed vertical lines marking the start of each trading day.
Visualization & Display
Volume is plotted as a series of histogram bars, each representing the average volume for a specific intraday time position.
A gradient color mode enhances readability by fading lower-intensity areas and highlighting high-volume regions.
Optional day-separator lines visually segment historical sessions for easy reference.
Works seamlessly across all chart timeframes that divide the 24-hour day into regular bar intervals.
Use Cases
Identify when trading activity typically peaks (e.g., session opens, news windows, or overlapping markets).
Compare current intraday volume to historical averages for early anomaly detection.
Enhance algorithmic or discretionary strategies that depend on volume-timing alignment.
Combine with volatility or price structure indicators to confirm market activity zones.
Evaluate session consistency across different time zones using the UTC offset parameter.
Limitations & Recommendations
The indicator requires intraday data (below 1D resolution) to function properly.
Volume behavior may vary across brokers and assets; adjust averaging period accordingly.
Does not predict price movement — it provides volume-based context for analysis.
Works best when combined with structure or momentum-based indicators.
Markets & Timeframes
Compatible with all intraday markets — including crypto, Forex, equities, and futures — and all intraday timeframes (from 1 minute to 4 hours). It is particularly valuable for analyzing assets with continuous 24-hour trading activity.
Author & Access
Developed 100% by Quantura. Published as a Open-source script indicator. Access is free.
Important
This description complies with TradingView’s Script Publishing and House Rules. It provides a clear explanation of the indicator’s originality, logic, and purpose, without any unrealistic performance or predictive claims.
MACD Overlay v1 [JopAlgo]Meet the MACD you can trade directly from the chart.
MACD Overlay v1 doesn’t just plot an oscillator somewhere below—
it puts value, momentum, and participation on your candles, and it refuses to fire inside chop.
When a triangle prints, it’s because energy released (expansion), not because the chart looked cute.
What it is:
An execution-ready MACD overlay with phase gating (Expansion-Only), participation gating (Weakness-Lite), and one-click Classic vs VW-MACD Compare—all adaptive, with minimal inputs.
What’s in v1 (feature set)
Overlay ribbon on price: Fast/Slow MACD value rendered as a price-level ribbon with contextual fill and optional candle tint.
Dual value model: Classic MA-MACD (EMA/SMA) and VW-MACD (Rolling VWAP fast/slow).
Compare mode: A/B Classic vs VW-MACD with a VW ghost ribbon.
Weakness-Lite (1-bar, adaptive): Gates/fades low-participation crosses using
RVOL deficit, Effort-vs-Result failure, and over-extension vs value/ATR (Strict adds wick pressure).
Expansion-Only (Impulse/Squeeze): Triangles print only when a cross coincides with a true-range burst and a histogram-slope ignition out of compression.
Signal hygiene: ±1-bar proximity around crosses, slope awareness, 2-bar debounce.
Explainable filtering: Tiny gray dots show crosses that were intentionally filtered (weak and/or no expansion).
How to use:
Use defaults: Mode Classic, Gate by Weakness ON, Expansion-Only ON, Sensitivity Auto.
Read signals fast:
Solid triangle = cross + expansion confirmed (+ not weak if gate is ON).
Faded triangle = cross + expansion but weak participation (visible only when gate is OFF).
Gray dot = there was a cross, but it was filtered (no genuine expansion or weak & gated).
Validate quickly: Flip Compare to check VW-MACD agreement. Classic + VW alignment usually improves confidence.
Why overlay > sub-pane oscillator
You see where the cross occurs: relative to value, local structure, and S/R, right on price.
The ribbon exposes regime shifts; tint hints expansion vs contraction at a glance.
Execution becomes more context-aware and less “signal-in-a-vacuum.”
Signals & visuals
Triangles (solid): MACD crossed Signal and market showed expansion out of compression; if Gate by Weakness is ON, triangle prints only with acceptable participation.
Triangles (faded): Same as above but weak (shown only when you turn the gate OFF).
Gray dots: Crosses that were filtered (no expansion and/or Weakness gate).
Ribbon: Fast vs Slow value (Classic or VW, according to Mode). Fill and candle tint reflect expansion/contraction.
Inputs
Calculation Mode: Classic | VW | Compare
VW uses Rolling VWAP fast/slow.
Compare: Classic is primary; VW shows as a ghost ribbon for A/B checks.
Gate triangles by Weakness: ON/OFF
Uses RVOL, Effort-vs-Result, extension vs value/ATR (Strict adds wick-pressure).
Sensitivity: Off / Auto / Strict (default Auto).
Expansion-Only (Impulse/Squeeze): ON/OFF
Requires compression → release: tight ribbon + flat momentum, then TR/ATR burst with hist slope flip / cross proximity.
Display: Ribbon / Candle Tint / Weakness Markers.
Advanced (optional): Evaluate Weakness only near signals, Channel (k × |MACD|), Style Preset.
No numeric thresholds to tune—all filters self-calibrate from rolling stats.
Best practices
4H crypto: Defaults are strong—Auto, Gate ON, Expansion-Only ON.
Clean trends: If you feel you miss some tidy resumptions, briefly toggle Expansion-Only OFF.
Choppy regimes: Set Sensitivity → Strict to cut more noise without adding lag.
Confirmation: Use Compare; Classic + VW alignment typically yields better follow-through.
Alerts
MACD Signal Cross Up/Down — execution-grade (use Once per bar close).
Weakness-Lite Flag — optional context alert to help audit filtered crosses.
Attribution & License
Attribution: Based on the algorithmic concept of TradingView’s built-in MACD (fast MA – slow MA, signal, histogram).
No original TradingView source code is redistributed; overlay rendering, VW-MACD, Weakness-Lite, Expansion-Only, gating visuals, and UX are new work.
License: MPL-2.0. Educational purposes only—not financial advice.
LibVPrfLibrary "LibVPrf"
This library provides an object-oriented framework for volume
profile analysis in Pine Script®. It is built around the `VProf`
User-Defined Type (UDT), which encapsulates all data, settings,
and statistical metrics for a single profile, enabling stateful
analysis with on-demand calculations.
Key Features:
1. **Object-Oriented Design (UDT):** The library is built around
the `VProf` UDT. This object encapsulates all profile data
and provides methods for its full lifecycle management,
including creation, cloning, clearing, and merging of profiles.
2. **Volume Allocation (`AllotMode`):** Offers two methods for
allocating a bar's volume:
- **Classic:** Assigns the entire bar's volume to the close
price bucket.
- **PDF:** Distributes volume across the bar's range using a
statistical price distribution model from the `LibBrSt` library.
3. **Buy/Sell Volume Splitting (`SplitMode`):** Provides methods
for classifying volume into buying and selling pressure:
- **Classic:** Classifies volume based on the bar's color (Close vs. Open).
- **Dynamic:** A specific model that analyzes candle structure
(body vs. wicks) and a short-term trend factor to
estimate the buy/sell share at each price level.
4. **Statistical Analysis (On-Demand):** Offers a suite of
statistical metrics calculated using a "Lazy Evaluation"
pattern (computed only when requested via `get...` methods):
- **Central Tendency:** Point of Control (POC), VWAP, and Median.
- **Dispersion:** Value Area (VA) and Population Standard Deviation.
- **Shape:** Skewness and Excess Kurtosis.
- **Delta:** Cumulative Volume Delta, including its
historical high/low watermarks.
5. **Structural Analysis:** Includes a parameter-free method
(`getSegments`) to decompose a profile into its fundamental
unimodal segments, allowing for modality detection (e.g.,
identifying bimodal profiles).
6. **Dynamic Profile Management:**
- **Auto-Fitting:** Profiles set to `dynamic = true` will
automatically expand their price range to fit new data.
- **Manipulation:** The resolution, price range, and Value Area
of a dynamic profile can be changed at any time. This
triggers a resampling process that uses a **linear
interpolation model** to re-bucket existing volume.
- **Assumption:** Non-dynamic profiles are fixed and will throw
a `runtime.error` if `addBar` is called with data
outside their initial range.
7. **Bucket-Level Access:** Provides getter methods for direct
iteration and analysis of the raw buy/sell volume and price
boundaries of each individual price bucket.
---
**DISCLAIMER**
This library is provided "AS IS" and for informational and
educational purposes only. It does not constitute financial,
investment, or trading advice.
The author assumes no liability for any errors, inaccuracies,
or omissions in the code. Using this library to build
trading indicators or strategies is entirely at your own risk.
As a developer using this library, you are solely responsible
for the rigorous testing, validation, and performance of any
scripts you create based on these functions. The author shall
not be held liable for any financial losses incurred directly
or indirectly from the use of this library or any scripts
derived from it.
create(buckets, rangeUp, rangeLo, dynamic, valueArea, allot, estimator, cdfSteps, split, trendLen)
Construct a new `VProf` object with fixed bucket count & range.
Parameters:
buckets (int) : series int number of price buckets ≥ 1
rangeUp (float) : series float upper price bound (absolute)
rangeLo (float) : series float lower price bound (absolute)
dynamic (bool) : series bool Flag for dynamic adaption of profile ranges
valueArea (int) : series int Percentage of total volume to include in the Value Area (1..100)
allot (series AllotMode) : series AllotMode Allocation mode `classic` or `pdf` (default `classic`)
estimator (series PriceEst enum from AustrianTradingMachine/LibBrSt/1) : series LibBrSt.PriceEst PDF model when `model == PDF`. (deflault = 'uniform')
cdfSteps (int) : series int even #sub-intervals for Simpson rule (default 20)
split (series SplitMode) : series SplitMode Buy/Sell determination (default `classic`)
trendLen (int) : series int Look‑back bars for trend factor (default 3)
Returns: VProf freshly initialised profile
method clone(self)
Create a deep copy of the volume profile.
Namespace types: VProf
Parameters:
self (VProf) : VProf Profile object to copy
Returns: VProf A new, independent copy of the profile
method clear(self)
Reset all bucket tallies while keeping configuration intact.
Namespace types: VProf
Parameters:
self (VProf) : VProf profile object
Returns: VProf cleared profile (chaining)
method merge(self, srcABuy, srcASell, srcRangeUp, srcRangeLo, srcCvd, srcCvdHi, srcCvdLo)
Merges volume data from a source profile into the current profile.
If resizing is needed, it performs a high-fidelity re-bucketing of existing
volume using a linear interpolation model inferred from neighboring buckets,
preventing aliasing artifacts and ensuring accurate volume preservation.
Namespace types: VProf
Parameters:
self (VProf) : VProf The target profile object to merge into.
srcABuy (array) : array The source profile's buy volume bucket array.
srcASell (array) : array The source profile's sell volume bucket array.
srcRangeUp (float) : series float The upper price bound of the source profile.
srcRangeLo (float) : series float The lower price bound of the source profile.
srcCvd (float) : series float The final Cumulative Volume Delta (CVD) value of the source profile.
srcCvdHi (float) : series float The historical high-water mark of the CVD from the source profile.
srcCvdLo (float) : series float The historical low-water mark of the CVD from the source profile.
Returns: VProf `self` (chaining), now containing the merged data.
method addBar(self, offset)
Add current bar’s volume to the profile (call once per realtime bar).
classic mode: allocates all volume to the close bucket and classifies
by `close >= open`. PDF mode: distributes volume across buckets by the
estimator’s CDF mass. For `split = dynamic`, the buy/sell share per
price is computed via context-driven piecewise s(u).
Namespace types: VProf
Parameters:
self (VProf) : VProf Profile object
offset (int) : series int To offset the calculated bar
Returns: VProf `self` (method chaining)
method setBuckets(self, buckets)
Sets the number of buckets for the volume profile.
Behavior depends on the `isDynamic` flag.
- If `dynamic = true`: Works on filled profiles by re-bucketing to a new resolution.
- If `dynamic = false`: Only works on empty profiles to prevent accidental changes.
Namespace types: VProf
Parameters:
self (VProf) : VProf Profile object
buckets (int) : series int The new number of buckets
Returns: VProf `self` (chaining)
method setRanges(self, rangeUp, rangeLo)
Sets the price range for the volume profile.
Behavior depends on the `dynamic` flag.
- If `dynamic = true`: Works on filled profiles by re-bucketing existing volume.
- If `dynamic = false`: Only works on empty profiles to prevent accidental changes.
Namespace types: VProf
Parameters:
self (VProf) : VProf Profile object
rangeUp (float) : series float The new upper price bound
rangeLo (float) : series float The new lower price bound
Returns: VProf `self` (chaining)
method setValueArea(self, valueArea)
Set the percentage of volume for the Value Area. If the value
changes, the profile is finalized again.
Namespace types: VProf
Parameters:
self (VProf) : VProf Profile object
valueArea (int) : series int The new Value Area percentage (0..100)
Returns: VProf `self` (chaining)
method getBktBuyVol(self, idx)
Get Buy volume of a bucket.
Namespace types: VProf
Parameters:
self (VProf) : VProf Profile object
idx (int) : series int Bucket index
Returns: series float Buy volume ≥ 0
method getBktSellVol(self, idx)
Get Sell volume of a bucket.
Namespace types: VProf
Parameters:
self (VProf) : VProf Profile object
idx (int) : series int Bucket index
Returns: series float Sell volume ≥ 0
method getBktBnds(self, idx)
Get Bounds of a bucket.
Namespace types: VProf
Parameters:
self (VProf) : VProf Profile object
idx (int) : series int Bucket index
Returns:
up series float The upper price bound of the bucket.
lo series float The lower price bound of the bucket.
method getPoc(self)
Get POC information.
Namespace types: VProf
Parameters:
self (VProf) : VProf Profile object
Returns:
pocIndex series int The index of the Point of Control (POC) bucket.
pocPrice. series float The mid-price of the Point of Control (POC) bucket.
method getVA(self)
Get Value Area (VA) information.
Namespace types: VProf
Parameters:
self (VProf) : VProf Profile object
Returns:
vaUpIndex series int The index of the upper bound bucket of the Value Area.
vaUpPrice series float The upper price bound of the Value Area.
vaLoIndex series int The index of the lower bound bucket of the Value Area.
vaLoPrice series float The lower price bound of the Value Area.
method getMedian(self)
Get the profile's median price and its bucket index. Calculates the value on-demand if stale.
Namespace types: VProf
Parameters:
self (VProf) : VProf Profile object.
Returns:
medianIndex series int The index of the bucket containing the Median.
medianPrice series float The Median price of the profile.
method getVwap(self)
Get the profile's VWAP and its bucket index. Calculates the value on-demand if stale.
Namespace types: VProf
Parameters:
self (VProf) : VProf Profile object.
Returns:
vwapIndex series int The index of the bucket containing the VWAP.
vwapPrice series float The Volume Weighted Average Price of the profile.
method getStdDev(self)
Get the profile's volume-weighted standard deviation. Calculates the value on-demand if stale.
Namespace types: VProf
Parameters:
self (VProf) : VProf Profile object.
Returns: series float The Standard deviation of the profile.
method getSkewness(self)
Get the profile's skewness. Calculates the value on-demand if stale.
Namespace types: VProf
Parameters:
self (VProf) : VProf Profile object.
Returns: series float The Skewness of the profile.
method getKurtosis(self)
Get the profile's excess kurtosis. Calculates the value on-demand if stale.
Namespace types: VProf
Parameters:
self (VProf) : VProf Profile object.
Returns: series float The Kurtosis of the profile.
method getSegments(self)
Get the profile's fundamental unimodal segments. Calculates on-demand if stale.
Uses a parameter-free, pivot-based recursive algorithm.
Namespace types: VProf
Parameters:
self (VProf) : VProf The profile object.
Returns: matrix A 2-column matrix where each row is an pair.
method getCvd(self)
Cumulative Volume Delta (CVD) like metric over all buckets.
Namespace types: VProf
Parameters:
self (VProf) : VProf Profile object.
Returns:
cvd series float The final Cumulative Volume Delta (Total Buy Vol - Total Sell Vol).
cvdHi series float The running high-water mark of the CVD as volume was added.
cvdLo series float The running low-water mark of the CVD as volume was added.
VProf
VProf Bucketed Buy/Sell volume profile plus meta information.
Fields:
buckets (series int) : int Number of price buckets (granularity ≥1)
rangeUp (series float) : float Upper price range (absolute)
rangeLo (series float) : float Lower price range (absolute)
dynamic (series bool) : bool Flag for dynamic adaption of profile ranges
valueArea (series int) : int Percentage of total volume to include in the Value Area (1..100)
allot (series AllotMode) : AllotMode Allocation mode `classic` or `pdf`
estimator (series PriceEst enum from AustrianTradingMachine/LibBrSt/1) : LibBrSt.PriceEst Price density model when `model == PDF`
cdfSteps (series int) : int Simpson integration resolution (even ≥2)
split (series SplitMode) : SplitMode Buy/Sell split strategy per bar
trendLen (series int) : int Look‑back length for trend factor (≥1)
maxBkt (series int) : int User-defined number of buckets (unclamped)
aBuy (array) : array Buy volume per bucket
aSell (array) : array Sell volume per bucket
cvd (series float) : float Final Cumulative Volume Delta (Total Buy Vol - Total Sell Vol).
cvdHi (series float) : float Running high-water mark of the CVD as volume was added.
cvdLo (series float) : float Running low-water mark of the CVD as volume was added.
poc (series int) : int Index of max‑volume bucket (POC). Is `na` until calculated.
vaUp (series int) : int Index of upper Value‑Area bound. Is `na` until calculated.
vaLo (series int) : int Index of lower value‑Area bound. Is `na` until calculated.
median (series float) : float Median price of the volume distribution. Is `na` until calculated.
vwap (series float) : float Profile VWAP (Volume Weighted Average Price). Is `na` until calculated.
stdDev (series float) : float Standard Deviation of volume around the VWAP. Is `na` until calculated.
skewness (series float) : float Skewness of the volume distribution. Is `na` until calculated.
kurtosis (series float) : float Excess Kurtosis of the volume distribution. Is `na` until calculated.
segments (matrix) : matrix A 2-column matrix where each row is an pair. Is `na` until calculated.
LibWghtLibrary "LibWght"
This is a library of mathematical and statistical functions
designed for quantitative analysis in Pine Script. Its core
principle is the integration of a custom weighting series
(e.g., volume) into a wide array of standard technical
analysis calculations.
Key Capabilities:
1. **Universal Weighting:** All exported functions accept a `weight`
parameter. This allows standard calculations (like moving
averages, RSI, and standard deviation) to be influenced by an
external data series, such as volume or tick count.
2. **Weighted Averages and Indicators:** Includes a comprehensive
collection of weighted functions:
- **Moving Averages:** `wSma`, `wEma`, `wWma`, `wRma` (Wilder's),
`wHma` (Hull), and `wLSma` (Least Squares / Linear Regression).
- **Oscillators & Ranges:** `wRsi`, `wAtr` (Average True Range),
`wTr` (True Range), and `wR` (High-Low Range).
3. **Volatility Decomposition:** Provides functions to decompose
total variance into distinct components for market analysis.
- **Two-Way Decomposition (`wTotVar`):** Separates variance into
**between-bar** (directional) and **within-bar** (noise)
components.
- **Three-Way Decomposition (`wLRTotVar`):** Decomposes variance
relative to a linear regression into **Trend** (explained by
the LR slope), **Residual** (mean-reversion around the
LR line), and **Within-Bar** (noise) components.
- **Local Volatility (`wLRLocTotStdDev`):** Measures the total
"noise" (within-bar + residual) around the trend line.
4. **Weighted Statistics and Regression:** Provides a robust
function for Weighted Linear Regression (`wLinReg`) and a
full suite of related statistical measures:
- **Between-Bar Stats:** `wBtwVar`, `wBtwStdDev`, `wBtwStdErr`.
- **Residual Stats:** `wResVar`, `wResStdDev`, `wResStdErr`.
5. **Fallback Mechanism:** All functions are designed for reliability.
If the total weight over the lookback period is zero (e.g., in
a no-volume period), the algorithms automatically fall back to
their unweighted, uniform-weight equivalents (e.g., `wSma`
becomes a standard `ta.sma`), preventing errors and ensuring
continuous calculation.
---
**DISCLAIMER**
This library is provided "AS IS" and for informational and
educational purposes only. It does not constitute financial,
investment, or trading advice.
The author assumes no liability for any errors, inaccuracies,
or omissions in the code. Using this library to build
trading indicators or strategies is entirely at your own risk.
As a developer using this library, you are solely responsible
for the rigorous testing, validation, and performance of any
scripts you create based on these functions. The author shall
not be held liable for any financial losses incurred directly
or indirectly from the use of this library or any scripts
derived from it.
wSma(source, weight, length)
Weighted Simple Moving Average (linear kernel).
Parameters:
source (float) : series float Data to average.
weight (float) : series float Weight series.
length (int) : series int Look-back length ≥ 1.
Returns: series float Linear-kernel weighted mean; falls back to
the arithmetic mean if Σweight = 0.
wEma(source, weight, length)
Weighted EMA (exponential kernel).
Parameters:
source (float) : series float Data to average.
weight (float) : series float Weight series.
length (simple int) : simple int Look-back length ≥ 1.
Returns: series float Exponential-kernel weighted mean; falls
back to classic EMA if Σweight = 0.
wWma(source, weight, length)
Weighted WMA (linear kernel).
Parameters:
source (float) : series float Data to average.
weight (float) : series float Weight series.
length (int) : series int Look-back length ≥ 1.
Returns: series float Linear-kernel weighted mean; falls back to
classic WMA if Σweight = 0.
wRma(source, weight, length)
Weighted RMA (Wilder kernel, α = 1/len).
Parameters:
source (float) : series float Data to average.
weight (float) : series float Weight series.
length (simple int) : simple int Look-back length ≥ 1.
Returns: series float Wilder-kernel weighted mean; falls back to
classic RMA if Σweight = 0.
wHma(source, weight, length)
Weighted HMA (linear kernel).
Parameters:
source (float) : series float Data to average.
weight (float) : series float Weight series.
length (int) : series int Look-back length ≥ 1.
Returns: series float Linear-kernel weighted mean; falls back to
classic HMA if Σweight = 0.
wRsi(source, weight, length)
Weighted Relative Strength Index.
Parameters:
source (float) : series float Price series.
weight (float) : series float Weight series.
length (simple int) : simple int Look-back length ≥ 1.
Returns: series float Weighted RSI; uniform if Σw = 0.
wAtr(tr, weight, length)
Weighted ATR (Average True Range).
Implemented as WRMA on *true range*.
Parameters:
tr (float) : series float True Range series.
weight (float) : series float Weight series.
length (simple int) : simple int Look-back length ≥ 1.
Returns: series float Weighted ATR; uniform weights if Σw = 0.
wTr(tr, weight, length)
Weighted True Range over a window.
Parameters:
tr (float) : series float True Range series.
weight (float) : series float Weight series.
length (int) : series int Look-back length ≥ 1.
Returns: series float Weighted mean of TR; uniform if Σw = 0.
wR(r, weight, length)
Weighted High-Low Range over a window.
Parameters:
r (float) : series float High-Low per bar.
weight (float) : series float Weight series.
length (int) : series int Look-back length ≥ 1.
Returns: series float Weighted mean of range; uniform if Σw = 0.
wBtwVar(source, weight, length, biased)
Weighted Between Variance (biased/unbiased).
Parameters:
source (float) : series float Data series.
weight (float) : series float Weight series.
length (int) : series int Look-back length ≥ 2.
biased (bool) : series bool true → population (biased); false → sample.
Returns:
variance series float The calculated between-bar variance (σ²btw), either biased or unbiased.
sumW series float The sum of weights over the lookback period (Σw).
sumW2 series float The sum of squared weights over the lookback period (Σw²).
wBtwStdDev(source, weight, length, biased)
Weighted Between Standard Deviation.
Parameters:
source (float) : series float Data series.
weight (float) : series float Weight series.
length (int) : series int Look-back length ≥ 2.
biased (bool) : series bool true → population (biased); false → sample.
Returns: series float σbtw uniform if Σw = 0.
wBtwStdErr(source, weight, length, biased)
Weighted Between Standard Error.
Parameters:
source (float) : series float Data series.
weight (float) : series float Weight series.
length (int) : series int Look-back length ≥ 2.
biased (bool) : series bool true → population (biased); false → sample.
Returns: series float √(σ²btw / N_eff) uniform if Σw = 0.
wTotVar(mu, sigma, weight, length, biased)
Weighted Total Variance (= between-group + within-group).
Useful when each bar represents an aggregate with its own
mean* and pre-estimated σ (e.g., second-level ranges inside a
1-minute bar). Assumes the *weight* series applies to both the
group means and their σ estimates.
Parameters:
mu (float) : series float Group means (e.g., HL2 of 1-second bars).
sigma (float) : series float Pre-estimated σ of each group (same basis).
weight (float) : series float Weight series (volume, ticks, …).
length (int) : series int Look-back length ≥ 2.
biased (bool) : series bool true → population (biased); false → sample.
Returns:
varBtw series float The between-bar variance component (σ²btw).
varWtn series float The within-bar variance component (σ²wtn).
sumW series float The sum of weights over the lookback period (Σw).
sumW2 series float The sum of squared weights over the lookback period (Σw²).
wTotStdDev(mu, sigma, weight, length, biased)
Weighted Total Standard Deviation.
Parameters:
mu (float) : series float Group means (e.g., HL2 of 1-second bars).
sigma (float) : series float Pre-estimated σ of each group (same basis).
weight (float) : series float Weight series (volume, ticks, …).
length (int) : series int Look-back length ≥ 2.
biased (bool) : series bool true → population (biased); false → sample.
Returns: series float σtot.
wTotStdErr(mu, sigma, weight, length, biased)
Weighted Total Standard Error.
SE = √( total variance / N_eff ) with the same effective sample
size logic as `wster()`.
Parameters:
mu (float) : series float Group means (e.g., HL2 of 1-second bars).
sigma (float) : series float Pre-estimated σ of each group (same basis).
weight (float) : series float Weight series (volume, ticks, …).
length (int) : series int Look-back length ≥ 2.
biased (bool) : series bool true → population (biased); false → sample.
Returns: series float √(σ²tot / N_eff).
wLinReg(source, weight, length)
Weighted Linear Regression.
Parameters:
source (float) : series float Data series.
weight (float) : series float Weight series.
length (int) : series int Look-back length ≥ 2.
Returns:
mid series float The estimated value of the regression line at the most recent bar.
slope series float The slope of the regression line.
intercept series float The intercept of the regression line.
wResVar(source, weight, midLine, slope, length, biased)
Weighted Residual Variance.
linear regression – optionally biased (population) or
unbiased (sample).
Parameters:
source (float) : series float Data series.
weight (float) : series float Weighting series (volume, etc.).
midLine (float) : series float Regression value at the last bar.
slope (float) : series float Slope per bar.
length (int) : series int Look-back length ≥ 2.
biased (bool) : series bool true → population variance (σ²_P), denominator ≈ N_eff.
false → sample variance (σ²_S), denominator ≈ N_eff - 2.
(Adjusts for 2 degrees of freedom lost to the regression).
Returns:
variance series float The calculated residual variance (σ²res), either biased or unbiased.
sumW series float The sum of weights over the lookback period (Σw).
sumW2 series float The sum of squared weights over the lookback period (Σw²).
wResStdDev(source, weight, midLine, slope, length, biased)
Weighted Residual Standard Deviation.
Parameters:
source (float) : series float Data series.
weight (float) : series float Weight series.
midLine (float) : series float Regression value at the last bar.
slope (float) : series float Slope per bar.
length (int) : series int Look-back length ≥ 2.
biased (bool) : series bool true → population (biased); false → sample.
Returns: series float σres; uniform if Σw = 0.
wResStdErr(source, weight, midLine, slope, length, biased)
Weighted Residual Standard Error.
Parameters:
source (float) : series float Data series.
weight (float) : series float Weight series.
midLine (float) : series float Regression value at the last bar.
slope (float) : series float Slope per bar.
length (int) : series int Look-back length ≥ 2.
biased (bool) : series bool true → population (biased); false → sample.
Returns: series float √(σ²res / N_eff); uniform if Σw = 0.
wLRTotVar(mu, sigma, weight, midLine, slope, length, biased)
Weighted Linear-Regression Total Variance **around the
window’s weighted mean μ**.
σ²_tot = E_w ⟶ *within-group variance*
+ Var_w ⟶ *residual variance*
+ Var_w ⟶ *trend variance*
where each bar i in the look-back window contributes
m_i = *mean* (e.g. 1-sec HL2)
σ_i = *sigma* (pre-estimated intrabar σ)
w_i = *weight* (volume, ticks, …)
ŷ_i = b₀ + b₁·x (value of the weighted LR line)
r_i = m_i − ŷ_i (orthogonal residual)
Parameters:
mu (float) : series float Per-bar mean m_i.
sigma (float) : series float Pre-estimated σ_i of each bar.
weight (float) : series float Weight series w_i (≥ 0).
midLine (float) : series float Regression value at the latest bar (ŷₙ₋₁).
slope (float) : series float Slope b₁ of the regression line.
length (int) : series int Look-back length ≥ 2.
biased (bool) : series bool true → population; false → sample.
Returns:
varRes series float The residual variance component (σ²res).
varWtn series float The within-bar variance component (σ²wtn).
varTrd series float The trend variance component (σ²trd), explained by the linear regression.
sumW series float The sum of weights over the lookback period (Σw).
sumW2 series float The sum of squared weights over the lookback period (Σw²).
wLRTotStdDev(mu, sigma, weight, midLine, slope, length, biased)
Weighted Linear-Regression Total Standard Deviation.
Parameters:
mu (float) : series float Per-bar mean m_i.
sigma (float) : series float Pre-estimated σ_i of each bar.
weight (float) : series float Weight series w_i (≥ 0).
midLine (float) : series float Regression value at the latest bar (ŷₙ₋₁).
slope (float) : series float Slope b₁ of the regression line.
length (int) : series int Look-back length ≥ 2.
biased (bool) : series bool true → population; false → sample.
Returns: series float √(σ²tot).
wLRTotStdErr(mu, sigma, weight, midLine, slope, length, biased)
Weighted Linear-Regression Total Standard Error.
SE = √( σ²_tot / N_eff ) with N_eff = Σw² / Σw² (like in wster()).
Parameters:
mu (float) : series float Per-bar mean m_i.
sigma (float) : series float Pre-estimated σ_i of each bar.
weight (float) : series float Weight series w_i (≥ 0).
midLine (float) : series float Regression value at the latest bar (ŷₙ₋₁).
slope (float) : series float Slope b₁ of the regression line.
length (int) : series int Look-back length ≥ 2.
biased (bool) : series bool true → population; false → sample.
Returns: series float √((σ²res, σ²wtn, σ²trd) / N_eff).
wLRLocTotStdDev(mu, sigma, weight, midLine, slope, length, biased)
Weighted Linear-Regression Local Total Standard Deviation.
Measures the total "noise" (within-bar + residual) around the trend.
Parameters:
mu (float) : series float Per-bar mean m_i.
sigma (float) : series float Pre-estimated σ_i of each bar.
weight (float) : series float Weight series w_i (≥ 0).
midLine (float) : series float Regression value at the latest bar (ŷₙ₋₁).
slope (float) : series float Slope b₁ of the regression line.
length (int) : series int Look-back length ≥ 2.
biased (bool) : series bool true → population; false → sample.
Returns: series float √(σ²wtn + σ²res).
wLRLocTotStdErr(mu, sigma, weight, midLine, slope, length, biased)
Weighted Linear-Regression Local Total Standard Error.
Parameters:
mu (float) : series float Per-bar mean m_i.
sigma (float) : series float Pre-estimated σ_i of each bar.
weight (float) : series float Weight series w_i (≥ 0).
midLine (float) : series float Regression value at the latest bar (ŷₙ₋₁).
slope (float) : series float Slope b₁ of the regression line.
length (int) : series int Look-back length ≥ 2.
biased (bool) : series bool true → population; false → sample.
Returns: series float √((σ²wtn + σ²res) / N_eff).
wLSma(source, weight, length)
Weighted Least Square Moving Average.
Parameters:
source (float) : series float Data series.
weight (float) : series float Weight series.
length (int) : series int Look-back length ≥ 2.
Returns: series float Least square weighted mean. Falls back
to unweighted regression if Σw = 0.
Enhanced MA Crossover Pro📝 Strategy Summary: Enhanced MA Crossover Pro
This strategy is an advanced, highly configurable moving average (MA) crossover system designed for algorithmic trading. It uses the crossover of two customizable MAs (a "Fast" MA 1 and a "Slow" MA 2) as its core entry signal, but aggressively integrates multiple technical filters, time controls, and dynamic position management to create a robust and comprehensive trading system.
💡 Core Logic
Entry Signal: A bullish crossover (MA1 > MA2) generates a Long signal, and a bearish crossover (MA1 < MA2) generates a Short signal. Users can opt to use MA crossovers from a Higher Timeframe (HTF) for the entry signal.
Confirmation/Filters: The basic MA cross signal is filtered by several optional indicators (see Filters section below) to ensure trades align with a broader trend or momentum context.
Position Management: Trades are managed with a sophisticated system of Stop Loss, Take Profit, Trailing Stops, and Breakeven stops that can be fixed, ATR-based, or dynamically adjusted.
Risk Management: Daily limits are enforced for maximum profit/loss and maximum trades per day.
⚙️ Key Features and Customization
1. Moving Averages
Primary MAs (MA1 & MA2): Highly configurable lengths (default 8 & 20) and types: EMA, WMA, SMA, or SMMA/RMA.
Higher Timeframe (HTF) MAs: Optional MAs calculated on a user-defined resolution (e.g., "60" for 1-hour) for use as an entry signal or as a trend confirmation filter.
2. Multi-Filter System
The entry signal can be filtered by the following optional conditions:
SMA Filter: Price must be above a 200-period SMA for long trades, and below it for short trades.
VWAP Filter: Price must be above VWAP for long trades, and below it for short trades.
RSI Filter: Long trades are blocked if RSI is overbought (default 70); short trades are blocked if RSI is oversold (default 30).
MACD Filter: Requires the MACD Line to be above the Signal Line for long trades (and vice versa for short trades).
HTF Confirmation: Requires the HTF MA1 to be above HTF MA2 for long entries (and vice versa).
3. Dynamic Stop and Target Management (S/L & T/P)
The strategy provides extensive control over exits:
Stop Loss Methods:
Fixed: Fixed tick amount.
ATR: Based on a multiple of the Average True Range (ATR).
Capped ATR: ATR stop limited by a maximum fixed tick amount.
Exit on Close Cross MA: Position is closed if the price crosses back over the chosen MA (MA1 or MA2).
Breakeven Stop: A stop can be moved to the entry price once a trigger distance (fixed ticks or Adaptive Breakeven based on ATR%) is reached.
Trailing Stop: Can be fixed or ATR-based, with an optional feature to auto-tighten the trailing multiplier after the breakeven condition is met.
Profit Target: Can be a fixed tick amount or a dynamic target based on an ATR multiplier.
4. Time and Session Control
Trading Session: Trades are only taken between defined Start/End Hours and Minutes (e.g., 9:30 to 16:00).
Forced Close: All open positions are closed near the end of the session (e.g., 15:45).
Trading Days: Allows specific days of the week to be enabled or disabled for trading.
5. Risk and Position Limits
Daily Profit/Loss Limits: The strategy tracks daily realized and unrealized PnL in ticks and will close all positions and block new entries if the user-defined maximum profit or maximum loss is hit.
Max Trades Per Day: Limits the number of executed trades in a single day.
🎨 Outputs and Alerts
Plots: Plots the MA1, MA2, SMA, VWAP, and HTF MAs (if enabled) on the chart.
Shapes: Plots visual markers (BUY/SELL labels) on the bar where the MA crossover occurs.
Trailing Stop: Plots the dynamic trailing stop level when a position is open.
Alerts: Generates JSON-formatted alerts for entry ({"action":"buy", "price":...}) and exit ({"action":"exit", "position":"long", "price":...}).
Halt-Risk Guard (5-min / 10%) — TTP Safe🛑 Halt-Risk Guard (5-min / 10%) — TTP Safe
Stay clear of halts, invalidations, and over-extended moves.
🔍 Overview
The Halt-Risk Guard helps traders avoid sudden invalidations by monitoring price velocity over the past X minutes (default: 5 min) and flagging when moves exceed a configurable threshold (default: 10%).
Originally built to meet Trade The Pool (TTP) risk-management rules — where even non-halted 10% moves can void trades — this tool provides a clear, visual warning system and optional entry blocker.
⚙️ Key Features
✅ Halt-Risk Detection – Calculates both reference-based and swing-based (high↔low) percentage change over the chosen lookback period.
✅ TTP Safe Mode – “Swing mode” captures extreme volatility spikes that may invalidate trades even when the market stays open.
✅ Entry Blocker (optional) – Automatically greys candles and dims the background during risky conditions to prevent impulsive entries.
✅ Customisable Positioning – Move the on-chart info box to any corner of your chart (Top Left / Top Right / Bottom Left / Bottom Right).
✅ Clean Alerts –
⚠️ At/Above Threshold
✅ Back to Safe
⛔ Entry Blocker Active
✅ Visual Table Display – Compact dashboard shows current % move, lookback window, and threshold with intuitive green/red status.
✅ Strategy-Ready Output – A hidden 0/1 plot lets you block or filter trades in automated systems.
⚡ How It Works
Monitors the selected symbol using your chosen computation timeframe (recommended 1-minute).
Evaluates either:
REF mode: Close-to-close change over the lookback window.
SWING mode: High-to-low range within the same window.
If the move ≥ Threshold %, the script highlights a halt-risk condition and optionally activates the entry blocker.
🎨 Recommended Settings
Lookback: 5 minutes
Threshold: 10 %
Swing mode: ON (TTP-safe)
Computation timeframe: 1 minute
Entry blocker: ON
Dim background: ON
🧠 Use Cases
TTP and other prop-firm evaluations enforcing price-movement limits.
Volatility-based scalping systems to avoid chasing extended candles.
Strategy filters for algorithmic entries (e.g. pause trading during halt-risk windows).
⚠️ Disclaimer
This tool provides visual and alert-based guidance only. It does not guarantee compliance with any specific firm’s rules or eliminate trading risk. Always verify thresholds and rules with your broker or evaluation provider.
Uptrick: Volume Weighted BandsIntroduction
This indicator, Uptrick: Volume Weighted Bands, overlays dynamic, volume-informed trend channels directly on the chart. By fusing price and volume data through volume-weighted and exponential moving averages, the script forms a core trend line with adaptive bandwidth controlled by volatility. It is designed to help traders identify trend direction, breakout entries, and extended conditions that may warrant take-profits or pullback re-entries.
Overview
The Volume Weighted Bands system is built around a trend line calculated by averaging a Volume Weighted Moving Average (VWMA) and an Exponential Moving Average (EMA), both over a configurable lookback period. This hybrid trend baseline is then smoothed further and expanded into dynamic upper and lower bands using an Average True Range (ATR) multiplier. These bands adapt with market volatility and shift color based on prevailing price action, helping traders quickly identify bullish, bearish, or neutral conditions.
Originality and Unique Features
This script introduces originality by blending both price and volume in the core trend calculation, a technique that is more responsive than traditional moving average bands. Its multi-mode visualization (cloud, single-band, or line-only), combined with selective buy/sell signals, makes it flexible for discretionary and algorithmic strategies alike. Optional modules for take-profit signals based on z-score deviation and RSI slope, as well as buy-back detection logic with cooldown filters, offer practical tools for managing trades beyond simple entries.
Explanation of Inputs
Every user input in this script is included to give the trader control over behavior and visual presentation:
Trend Length (len): Defines the lookback window for both the VWMA and EMA, controlling the sensitivity of the core trend baseline. A lower value makes the bands more reactive, while a higher value smooths out short-term noise.
Extra Smoothing (smoothLen): Applies an additional EMA to the blended VWMA/EMA average. This second-level smoothing ensures the central trend line reacts gradually to shifts in price.
Band Width (ATR Multiplier) (bandMult): Multiplies the ATR to create the width of the upper and lower bands around the trend line. Larger values widen the bands, capturing more volatility, while smaller values narrow them.
ATR Length (atrLen): Sets the length of the ATR used in calculating band width and signal offsets. Longer values produce smoother band boundaries.
Show Buy/Sell Signals (showSignals): Toggles the primary crossover/crossunder entry signals, which are labeled when the close crosses the upper or lower band.
Visual Mode (visualMode): Allows selection between three display modes:
--> Cloud: Shows both bands and the central trend line with a shaded background.
--> Single Band: Displays only the active (upper or lower) band depending on trend state, with gradient fill to price.
--> Line Only: Shows only the trend line for a minimal visual profile.
Take Profit Signals (enableTP): Enables a z-score-based profit-taking signal system. Signals occur when price deviates significantly from the trend line and RSI confirms exhaustion.
TP Z-Score Threshold (tpThreshold): Sets the z-score deviation required to trigger a take-profit signal. Higher values reduce the frequency of signals, focusing on more extreme moves.
Re-Entries (enableBuyBack): Enables logic to signal when price reverts into the band after an initial breakout, suggesting a possible re-entry or pullback setup.
Buy Back Cooldown (bars) (buyBackCooldown): Defines a minimum bar count before a new buy-back signal is allowed, preventing rapid retriggering in choppy conditions.
Buy Offset and Sell Offset: Hidden inputs used to vertically adjust the placement of the Buy ("𝓤𝓹") and Sell ("𝓓𝓸𝔀𝓷") labels relative to the bands. These use ATR units to maintain proportionality across different instruments and timeframes.
Take-Profit Signal Module
The take-profit module uses a z-score of the distance between price and the trend line to detect extended conditions. In bullish trends, a signal appears when price is well above the band and RSI indicates exhaustion; the opposite applies for bearish conditions. A boolean flag is used to prevent retriggering until RSI resets. These signals are plotted with minimalist “X” markers near recent highs or lows, based on whether the market is extended upward or downward.
Re-Entry Logic
The re-entry system identifies instances where price momentarily dips or spikes into the opposite band but closes back inside, implying a continuation of the prevailing trend. This module can be particularly useful for traders managing entries after brief pullbacks. A built-in cooldown period helps filter out noise and prevents signal overloading during fast markets. Visual markers are shown as upward or downward arrows near the relevant candle wicks.
How to Use This Indicator
The basic usage of this indicator follows a directional, signal-driven approach. When a buy signal appears, it suggests entering a long position. The recommended stop loss placement is below the lower band, allowing for some breathing space to accommodate natural volatility. As the position progresses, take partial profits—typically 10% to 15% of the position—each time a take-profit signal (marked with an "X") is shown on the chart.
An optional feature is the buy-back signal, which can be used to re-enter after partial exits or missed entries. Utilizing this can help reduce losses during false breakouts or trend reversals by scaling in more gradually. However, it also means that in strong, clean trends, the full position may not be captured from the start, potentially reducing the total return. It is up to the trader to decide whether to enter fully on the initial signal or incrementally using buy-backs.
When a sell signal appears, the strategy advises fully exiting any long positions and immediately switching to a short position. The short trade follows the same logic: place your stop loss above the upper band with some margin, and again, take partial profits at each take-profit signal.
Visual Presentation and Signal Labels
All signals are plotted with clean, minimal labels that avoid clutter, and are color-coded using a custom palette designed to remain clear across light and dark chart themes. Bullish trends are marked in teal and bearish trends in magenta. Candles and wicks are also colored accordingly to align price action with the detected trend state. Buy and sell entries are marked with "𝓤𝓹" and "𝓓𝓸𝔀𝓷" labels.
Summary
In summary, the Uptrick: Volume Weighted Bands indicator provides a versatile, visually adaptive trend and volatility tool that can serve multiple styles of trading. Through its integration of price, volume, and volatility, along with modular take-profit and buy-back signaling, it aims to provide actionable structure across a range of market conditions.
Disclaimer
This indicator is for educational purposes only. Trading involves risk, and past performance does not guarantee future results. Always test strategies before applying them in live markets.
21 SMA over 200 SMA Bullish Cross Highlighter21 SMA Over 200 SMA — Momentum Cross for BTC Scalpers
A precise and lightweight indicator designed to highlight when short-term momentum aligns with the broader Bitcoin trend.
It visualizes when the 21-period Simple Moving Average (SMA) crosses above the 200-period SMA, often signaling the beginning of a sustained directional move — especially effective on the 1-minute BTC chart during trending market conditions.
Core Concept
When the 21 SMA crosses above the 200 SMA on Bitcoin during an active uptrend, the probability increases that price will continue rising as short-term traders and algorithms join the move.
This indicator helps you identify that momentum shift in real time and react before the breakout gains full traction.
Features
Clear visual label for every bullish cross (21↑200)
Optional bearish cross labels (21↓200)
Optimized for 1m, 5m, and 15m BTC charts
Lightweight and efficient — ideal for multi-chart scalping layouts
Built-in alert conditions for manual alert setup
Excellent synergy with VRVP (Visible Range Volume Profile) for confirming volume-based breakout zones
Suggested Use
Focus on the 1-minute Bitcoin chart for early signals.
When a bullish cross appears, use VRVP to locate high-volume nodes or breakout levels for precise entries.
Confirm alignment on 5m or 15m charts before executing.
Combine with RSI, Stoch RSI, or volume analysis to refine timing and manage risk.
Trading Insight
The 21/200 SMA relationship has long been a trusted tool for trend identification.
When both averages slope upward and the cross occurs above a strong VRVP volume zone, it often marks the start of a new impulsive leg in BTC ideal for short-term scalps or the first confirmation of a broader trend continuation.
Created for disciplined BTC scalpers who value structured setups, clarity, and confirmation through data rather than noise.
Balanced Delta Volume Profile (Zeiierman)█ Overview
Balanced Delta Volume Profile (Zeiierman) builds a vertical, price-by-price profile that blends total participation with balance quality. Instead of plotting raw volume alone, it weights each price bin by:
how balanced buyers vs. sellers were,
how compressed price was inside that bin,
how often price revisited it.
The result spotlights fair value and acceptance zones while still revealing momentum/imbalance areas—ideal for reading rotation vs. trend, continuation vs. exhaustion, and the prices that truly matter.
Highlights
Balanced score that fuses delta symmetry, price compression, and hit frequency.
Optional heat spectrum for instant read of participation density and balance strength.
POC-like auto highlight of the dominant price level within the lookback window.
Works across timeframes for session profiling, swing context, or regime shifts.
█ How It Works
⚪ Profile Construction
The script scans a fixed History Length and divides the full high–low span into Bin Count price bins. For every bar in the window, its volume is proportionally distributed across the bins it overlaps, so wide-range bars contribute across multiple bins, while narrow bars concentrate where they traded most. This yields per-bin totals for:
Total Volume (participation)
Positive / Negative Volume (up vs. down bar contribution)
Hit Count (how often price touched the bin)
Average Price Range (mean bar range inside the bin; a proxy for compression)
⚪ Delta & Direction
For each bin, delta symmetry is measured via the ratio of |pos − neg| to total volume. Bins with balanced two-sided flow score higher than one-sided, runaway bins. This curbs the tendency of raw volume profiles to over-reward impulsive bursts.
⚪ Balance Score
Each price bin gets a balance score that multiplies three normalized components:
Delta Balance: rewards bins where buy/sell pressure is symmetrical (configurable via Volume Momentum Weight).
Price Compression: rewards bins where average bar range is relatively small (configurable via Price Momentum Weight).
Durability: rewards bins revisited often (configurable via Hits Weight).
A Min Hits Filter removes flimsy, single-touch bins from dominating the score. The profile can display pure totals or Average Mode (Vol/Hit) to compare bins fairly when hit counts differ.
⚪ Display & Heat Spectrum
The final plotted bar length per bin is the display volume (total or average) weighted by the balance score and normalized to 100.
POC-like Highlight: The 100% bin is outlined (and labeled) when Highlight Max Volume Bin is ON.
Heat Spectrum (optional): A background gradient scales with normalized bar length and balance hue.
Balance Hue: Interpolates between Balance Low/High Colors so high-balance bins visually pop as “accepted value.”
█ How to Use
The profile is effectively a map of price acceptance:
High, bright bars = strong participation at balanced prices → fair value/rotation zones.
Thin, muted bars = poor acceptance → imbalance or transition areas.
POC-style level = most influential price in the lookback window.
⚪ Find Fair Value & Acceptance
Thick, high-balance bins mark value. Expect rotation: price often revisits or oscillates around these areas. They’re prime zones for mean-reversion fades, scale-ins, and risk-defined trades against the edges.
⚪ Identify Imbalance & Funnels
Low-balance, low-hit bins often act like air pockets—price can move through them quickly. These zones are helpful for continuation trades into thin areas or for timing breakout pulls back into acceptance.
⚪ POC Dynamics
When price leaves the POC and returns, watch for re-acceptance (price comes back into the POC or high-balance zone and stays there.) vs. rejection (trend continuation away from value). The auto-highlight makes this quick to judge.
█ Settings
History Length – Bars scanned for the profile. Longer = broader context, slower to adapt.
Bin Count – Vertical resolution of bins between the window’s min and max price.
Display Shift – Offsets the rendering rightward for clarity.
Average Mode (Vol/Hit) – ON uses average volume per visit; OFF uses total volume.
Volume Momentum Weight – Emphasizes two-way flow; higher values favor balanced bins over one-sided deltas.
Price Momentum Weight – Emphasizes compression; higher values favor narrow-range, coiling price action.
Hits Weight – Rewards bins revisited often; higher values favor durable acceptance.
Min Hits Filter – Minimum visits a bin needs to qualify for the balance score.
Show Heat Spectrum – Background gradient for quick read of density and balance.
Highlight Max Volume Bin – Outline + raw volume label for the dominant bin.
Max Volume Color – Color used for that highlight.
Balance Low/High Colors – Gradient endpoints for balance hue across the profile.
-----------------
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.
Vandan V2Vandan V2 is an automated trend-following strategy for NASDAQ E-mini Futures (NQ1!).
It uses multi-timeframe momentum and volatility filters to identify high-probability entries.
Includes dynamic risk management and trailing logic optimized for intraday trading.
Scissors&Knifes V3.1✂️ The Scissors (PAG Chop V4 Engine)
🧠 Core idea
Scissors measure market compression and breakout readiness.
They use a modified Choppiness Index that looks at the relationship between:
True Range volatility (ATR × period length)
The total high–low range over the same window.
The smaller the ratio (sum of TR vs range), the more directional and impulsive the market is.
The higher the ratio, the more “sideways” the market trades.
This version smooths the result over PAG_SMOOTHLEN bars and applies several color bands that correspond to volatility states.
🎨 Color code meaning
Range State Color Interpretation
≤ 30 Strong Red #8B0000 Momentum exhaustion on downside, sellers dominating — about to reverse or already strong down-trend.
30 – 38 Brick Red #A52A2A Fading downside pressure; often the “bleeding edge” of a bearish climax.
38 – 55 Transparent black (α≈100) Neutral chop zone — indecision, range-building.
55 – 61.8 Yellow (optional) #DAA520 Early compression pocket where volatility starts contracting; the calm before a trend.
61.8 – 70 Bright Green #556B2F Energy release phase: volatility breaking out upward.
≥ 70 Strong Green #355E3B Sustained bullish drive, often continuation leg of a trend.
🪶 Secret nuance:
The transition bands (38–45 and 45–55) are treated as fully transparent to mark “dead zones.”
When PAG Chop sits here, all label activity pauses — the system resets its cluster memory so the next colored print begins a new “cluster”, letting you clearly see where fresh directional momentum starts.
🧩 Cluster logic
Every time a colored (non-transparent) reading appears, it belongs to a “color cluster.”
Grey labels (= count 1) mark the genesis of a new cluster, and following counts 2, 3, 4 … represent the internal continuity of that trend state.
You can optionally hide the first N grey or count 2 labels to reduce clutter on the initial stabilization bars.
✂️ Label meaning
Each label shows:
Emoji ✂️
Current count (e.g. ✂️ = 3 means 3 timeframes are simultaneously firing)
Optional list of the timeframes that contribute.
So a high count (e.g. 8–10) means many lower TFs are synchronizing volatility breakout — a multiframe alignment, often just before an acceleration burst.
🔪 The Knife (Mr Blonde V4 Engine)
🧠 Core idea
Mr Blonde converts the slope of a long EMA into an angle-of-attack metric — literally the “tilt” of market momentum.
It computes the EMA gradient relative to price span and rescales it into degrees (-5 ° to +5 °).
The steeper the angle, the stronger the directional push.
🎨 Color code meaning
Angle range Color Interpretation
≥ +5 ° Transparent (Black 1) Fully over-extended up move — wait for reset.
+3.57 – +5 ° Dark Red Strong upward slope, momentum apex.
+2.14 – +3.57 ° Orange Medium upward slope, trend acceleration zone.
+0.71 – +2.14 ° Light Orange Mild upward bias, pre-momentum phase.
0 to -0.71 ° Yellow Neutral transition.
-0.71 – -2.14 ° Olive Green Soft bearish slope.
-2.14 – -3.57 ° Olive Drab Building bearish momentum.
-3.57 – -5 ° Hunter Green Strong downward angle, aggressive push.
≤ -5 ° Transparent (Black 2) Oversold/over-tilted — likely exhaustion.
🪶 Secret nuance:
Mr Blonde uses a “span normalization” factor that divides EMA slope by the dynamic range of highs and lows.
This lets it compare angles fairly across assets with different volatility profiles (e.g. BTC vs ES) — it’s one of the rare EMA-angle implementations that self-scales properly.
🗡 Label meaning
Emoji 🔪
Count = how many TFs share the same momentum angle bias.
When many TFs show the same slope polarity (e.g. knife = 8), you’re in a deep momentum cascade — a “knife trend.”
💫 Yellow knife
The yellow state marks neutrality or slope flattening.
If you enable yellow visibility (mb_show_yellow), you can see where momentum cools off — often the earliest reversal hint.
⚙️ Shared mechanics between ✂️ and 🔪
Multi-timeframe sweep
The script cycles through 1 m → 10 m by default, running both engines once per TF.
Each returning true adds +1 to the count.
So:
sc_hits = count of timeframes where PAG fires + 1
knife_hits = count of timeframes where MB fires + 1
That “+1 shift” means there’s always at least 1, letting count = 1 represent the local TF itself.
Cluster limiter
If Limit max labels per cluster is on, you cap how many total symbols (both ✂️ & 🔪, including trails) can appear within one color phase — avoiding chart spam during extended trends.
Trails
Each printed label seeds a short-lived “trail” sequence — faded copies extending N bars forward.
Trails visualize the linger effect of the last signal, useful for visually connecting bursts in momentum.
Grey or count = 1 labels can have shorter or longer trails depending on your overrides (*_trail_bars_grey).
They’re purely visual and do not affect alerting.
Alerts
Alerts fire independently of whether you hide labels — unless you enable “respect filters”.
This guarantees you never miss a structural signal even if you suppress visuals for clarity.
🌈 Interpreting Both Together
Scenario Interpretation
✂️ = low (1–2) + 🔪 rising (red/orange) Market just leaving chop, early thrust stage.
✂️ = high (≥ 5) + 🔪 green Fully aligned breakout continuation — trend in progress.
✂️ = yellow cluster + 🔪 yellow Volatility squeeze, energy buildup — next expansion near.
✂️ = green cluster → 🔪 turns red Cross-state conflict; likely transition or correction.
✂️ = grey + 🔪 grey Reset condition — both engines cooling; stand aside.
💡 Hidden edge:
Scissors signal potential, Knife measures kinetic force.
The perfect storm is when ✂️ goes from yellow→green one bar before 🔪 shifts from orange→green — it catches the birth of directional flow while volatility is still tight.
🧭 Reading the labels intuitively
Grey ✂️/🔪 = 1 → embryonic state, may fizzle or bloom.
✂️/🔪 = 2 or 3 → expansion taking hold.
✂️/🔪 ≥ 4 (mid black) → strong synchronized drive across TFs.
Transparent gap → cluster reset; prepare for new phase.
Trail lines → echo of previous cluster strength.
Final secret tip 🗝
Because both engines are mathematically uncorrelated (volatility vs EMA angle), when they agree in color polarity on multiple TFs, you have one of the cleanest probabilistic trend windows possible.
If you ever see ✂️ = 6 + 🔪 = 6 both pointing the same way — that’s a “knife-through-the-scissors” moment: volatility expansion and directional slope synchronized — those are the bars where institutional algorithms tend to add size.
Auto Fibonacci LevelsAuto Fibonacci Momentum Zones with Visible Range Table
Overview and Originality
The Auto Fibonacci Momentum Zones indicator offers a streamlined, static overlay of Fibonacci retracement levels inspired by extreme RSI momentum thresholds, enhanced with a dynamic table displaying the high and low of the currently visible chart range. This isn't a repackaged RSI oscillator or basic Fib drawer—common in TradingView's library—but a purposeful fusion of geometric harmony (Fibonacci ratios) with momentum psychology (RSI extremes at 35/85), projected as fixed horizontal reference lines on the price chart. The addition of the visible range table, powered by PineCoders' VisibleChart library, provides real-time context for the chart's current view, enabling traders to quickly assess range compression or expansion relative to these zones.
This script's originality stems from its "static momentum mapping": by hardcoding Fib levels on a dynamic chart, it creates universal psychological support/resistance lines that transcend specific assets or timeframes.
Unlike dynamic Fib tools that auto-adjust to price swings (risking noise in ranging markets) or standalone RSI plots (confined to panes), this delivers clean, bias-adjustable overlays for confluence analysis. The visible range table justifies the library integration—it's not a gratuitous add-on but a complementary tool that quantifies the "screen real estate" of price action, helping users correlate Fib touches with actual volatility. Drawn from original code (no auto-generation or public templates), it builds TradingView's body of knowledge by simplifying multi-tool workflows into one indicator, ideal for discretionary traders who value visual efficiency over algorithmic complexity.
How It Works: Underlying Concepts
Fibonacci retracements, derived from the Fibonacci sequence and the golden ratio (≈0.618), identify potential reversal points based on the idea that markets retrace prior moves in predictable proportions: shallow (23.6%, 38.2%), mid (50%), and deep (61.8%, 78.6%).
Adjustable Outputs
1. The "Invert Fibs" toggle (default: true) for bearish/topping bias, can be flipped aligning with trend context.
2. Fibonacci Levels: Seven semi-transparent horizontal lines are drawn using `hline()`:
- 0.0 at high (gray).
- 0.236: high - (range × 0.236) (light cyan, shallow pullback).
- 0.382: high - (range × 0.382) (teal, common retracement).
- 0.5: midpoint average (green, equilibrium).
- 0.618: high - (range × 0.618) (amber, golden pocket for reversals).
- 0.786: high - (range × 0.786) (orange, deep support).
- 1.0 at low (gray).
Colors progress from cool (shallow) to warm (deep) for intuitive scanning.
3. Optional Fib Labels: Right-edge text labels (e.g., "0.618") appear only if enabled, positioned at the last bar + offset for non-cluttering visibility.
4. Visible Range Table: Leveraging the VisibleChart library's `visible.high()` and `visible.low()` functions, a compact 2x2 table (top-right corner) updates on the last bar to show the extrema of bars currently in view. This mashup enhances utility: Fib zones provide fixed anchors, while the table's dynamic values reveal if price is "pinned" to a zone (e.g., visible high hugging 0.382 signals resistance). The library is invoked sparingly for performance, adding value by bridging static geometry with viewport-aware data—unavailable in built-ins without custom code.
How to Use It
1. Setup:
Add to any chart (e.g., 15M for scalps, Daily for swings). As an overlay, lines appear directly on price candles—adjust chart scaling if needed.
2. Input Tweaks:
Invert Fibs: Enable for downtrends (85 top), disable for uptrends (35 bottom).
Show Fibs: Toggle labels for ratio callouts (off for clean charts).
Show Table: Display/hide the visible high/low summary (red for high, green for low, formatted to 2 decimals).
3. Trading Application:
Zone Confluence: Seek price reactions at each fibonacci level—e.g., a doji at 0.618 + rising volume suggests entry; use 0.0/1.0 as invalidation.
Range Context: Check the table: If visible high/low spans <20% of the Fib arc (e.g., both near 0.5), anticipate breakout; wider spans signal consolidation.
Multi-Timeframe: Overlay on higher TF for bias, lower for precision—e.g., Daily Fibs guide 1H entries.
Enhancements: Pair with volume or candlesticks; set alerts on line crosses via TradingView's built-in tools. Backtest on your symbols to validate (e.g., equities favor 0.382, forex the 0.786).
This indicator automates advanced Fibonacci synthesis dynamically, eliminating manual measurement and calculations.
published by ozzy_livin
Flux AI PullBack System (Hybrid Pro)Flux AI PullBack System (Hybrid Pro)
//Session-Aware | Adaptive Confluence | Grace Confirm Logic//
Overview:
The Flux AI PullBack System (Hybrid Pro v5) is an adaptive, session-aware pullback indicator designed to identify high-probability continuation setups within trending markets. It automatically adjusts between “Classic” and “Enhanced” logic modes based on volatility, volume, and ATR slope, allowing it to perform seamlessly across different market sessions (Asian, London, and New York).
Core Features:
Hybrid Auto Mode — Dynamically switches between Classic (fast-moving) and Enhanced (strict) modes.
Session-Aware Context — Optimized for intraday trading in ES, NQ, and SPY.
Grace Confirmation Logic — Validates pullbacks with a follow-through condition to reduce noise.
Adaptive EMA Zone (38/62) — Highlights pullback areas with dynamic aqua fill and transparency linked to trend strength.
Noise Suppression Filter — Prevents false pullbacks during EMA crossovers or unstable transitions.
Weighted Confluence Model — Combines trend, ATR, volume, and swing structure for confirmation strength.
Pine v6 Compliant Alerts — Constant-string safe, ready for webhooks and automation.
Visual Elements:
Aqua EMA Zone: Displays the “breathing” pullback band (tightens during volatility spikes).
PB↑ / PB↓ Markers: Confirmed pullbacks with subtle transparency and fixed label size.
Bar Highlights: Yellow for pullbacks; ice-blue for confirmed continuation.
Use Cases
Perfect for:
Intraday trend traders
0DTE SPX / ES scalpers
Futures traders (NQ, MNQ, MES)
Algorithmic strategy builders using webhooks
Recommended Timeframes:
1–15 minute charts (scalping / intraday)
Higher timeframes for swing confirmations.
Attribution:
This open-source script was inspired by Chris Moody’s “CM Slingshot System” and JustUncleL’s Pullback Tools, but it was built from scratch using AI-assisted code refinement (ChatGPT).
All logic and enhancements are original, not derived from proprietary software.
License: MIT (Open Source)
© 2025 Ken Anderson — You may modify, use, or redistribute with credit.
Keywords:
Pullback, Reversal, AI Trading, EMA Zone, Session Aware, Futures Trading, SPX, ES, NQ, ATR Filter, Volume Confirmation, Flux System, Pine Script v6, Non-Repainting, Adaptive Trading Indicator.
Ehlers Phasor Analysis (PHASOR)# PHASOR: Phasor Analysis (Ehlers)
## Overview and Purpose
The Phasor Analysis indicator, developed by John Ehlers, represents an advanced cycle analysis tool that identifies the phase of the dominant cycle component in a time series through complex signal processing techniques. This sophisticated indicator uses correlation-based methods to determine the real and imaginary components of the signal, converting them to a continuous phase angle that reveals market cycle progression. Unlike traditional oscillators, the Phasor provides unwrapped phase measurements that accumulate continuously, offering unique insights into market timing and cycle behavior.
## Core Concepts
* **Complex Signal Analysis** — Uses real and imaginary components to determine cycle phase
* **Correlation-Based Detection** — Employs Ehlers' correlation method for robust phase estimation
* **Unwrapped Phase Tracking** — Provides continuous phase accumulation without discontinuities
* **Anti-Regression Logic** — Prevents phase angle from moving backward under specific conditions
Market Applications:
* **Cycle Timing** — Precise identification of cycle peaks and troughs
* **Market Regime Analysis** — Distinguishes between trending and cycling market conditions
* **Turning Point Detection** — Advanced warning system for potential market reversals
## Common Settings and Parameters
| Parameter | Default | Function | When to Adjust |
|-----------|---------|----------|----------------|
| Period | 28 | Fixed cycle period for correlation analysis | Match to expected dominant cycle length |
| Source | Close | Price series for phase calculation | Use typical price or other smoothed series |
| Show Derived Period | false | Display calculated period from phase rate | Enable for adaptive period analysis |
| Show Trend State | false | Display trend/cycle state variable | Enable for regime identification |
## Calculation and Mathematical Foundation
**Technical Formula:**
**Stage 1: Correlation Analysis**
For period $n$ and source $x_t$:
Real component correlation with cosine wave:
$$R = \frac{n \sum x_t \cos\left(\frac{2\pi t}{n}\right) - \sum x_t \sum \cos\left(\frac{2\pi t}{n}\right)}{\sqrt{D_{cos}}}$$
Imaginary component correlation with negative sine wave:
$$I = \frac{n \sum x_t \left(-\sin\left(\frac{2\pi t}{n}\right)\right) - \sum x_t \sum \left(-\sin\left(\frac{2\pi t}{n}\right)\right)}{\sqrt{D_{sin}}}$$
where $D_{cos}$ and $D_{sin}$ are normalization denominators.
**Stage 2: Phase Angle Conversion**
$$\theta_{raw} = \begin{cases}
90° - \arctan\left(\frac{I}{R}\right) \cdot \frac{180°}{\pi} & \text{if } R \neq 0 \\
0° & \text{if } R = 0, I > 0 \\
180° & \text{if } R = 0, I \leq 0
\end{cases}$$
**Stage 3: Phase Unwrapping**
$$\theta_{unwrapped}(t) = \theta_{unwrapped}(t-1) + \Delta\theta$$
where $\Delta\theta$ is the normalized phase difference.
**Stage 4: Ehlers' Anti-Regression Condition**
$$\theta_{final}(t) = \begin{cases}
\theta_{final}(t-1) & \text{if regression conditions met} \\
\theta_{unwrapped}(t) & \text{otherwise}
\end{cases}$$
**Derived Calculations:**
Derived Period: $P_{derived} = \frac{360°}{\Delta\theta_{final}}$ (clamped to )
Trend State:
$$S_{trend} = \begin{cases}
1 & \text{if } \Delta\theta \leq 6° \text{ and } |\theta| \geq 90° \\
-1 & \text{if } \Delta\theta \leq 6° \text{ and } |\theta| < 90° \\
0 & \text{if } \Delta\theta > 6°
\end{cases}$$
> 🔍 **Technical Note:** The correlation-based approach provides robust phase estimation even in noisy market conditions, while the unwrapping mechanism ensures continuous phase tracking across cycle boundaries.
## Interpretation Details
* **Phasor Angle (Primary Output):**
- **+90°**: Potential cycle peak region
- **0°**: Mid-cycle ascending phase
- **-90°**: Potential cycle trough region
- **±180°**: Mid-cycle descending phase
* **Phase Progression:**
- Continuous upward movement → Normal cycle progression
- Phase stalling → Potential cycle extension or trend development
- Rapid phase changes → Cycle compression or volatility spike
* **Derived Period Analysis:**
- Period < 10 → High-frequency cycle dominance
- Period 15-40 → Typical swing trading cycles
- Period > 50 → Trending market conditions
* **Trend State Variable:**
- **+1**: Long trend conditions (slow phase change in extreme zones)
- **-1**: Short trend or consolidation (slow phase change in neutral zones)
- **0**: Active cycling (normal phase change rate)
## Applications
* **Cycle-Based Trading:**
- Enter long positions near -90° crossings (cycle troughs)
- Enter short positions near +90° crossings (cycle peaks)
- Exit positions during mid-cycle phases (0°, ±180°)
* **Market Timing:**
- Use phase acceleration for early trend detection
- Monitor derived period for cycle length changes
- Combine with trend state for regime-appropriate strategies
* **Risk Management:**
- Adjust position sizes based on cycle clarity (derived period stability)
- Implement different risk parameters for trending vs. cycling regimes
- Use phase velocity for stop-loss placement timing
## Limitations and Considerations
* **Parameter Sensitivity:**
- Fixed period assumption may not match actual market cycles
- Requires cycle period optimization for different markets and timeframes
- Performance degrades when multiple cycles interfere
* **Computational Complexity:**
- Correlation calculations over full period windows
- Multiple mathematical transformations increase processing requirements
- Real-time implementation requires efficient algorithms
* **Market Conditions:**
- Most effective in markets with clear cyclical behavior
- May provide false signals during strong trending periods
- Requires sufficient historical data for correlation analysis
Complementary Indicators:
* MESA Adaptive Moving Average (cycle-based smoothing)
* Dominant Cycle Period indicators
* Detrended Price Oscillator (cycle identification)
## References
1. Ehlers, J.F. "Cycle Analytics for Traders." Wiley, 2013.
2. Ehlers, J.F. "Cybernetic Analysis for Stocks and Futures." Wiley, 2004.
DayFlow VWAP Relay Forex Majors StrategySummary in one paragraph
DayFlow VWAP Relay is a day-trading strategy for major FX pairs on intraday timeframes, demonstrated on EURUSD 15 minutes. It waits for alignment between a daily anchored VWAP regime check, residual percentiles, and lower-timeframe micro flow before suggesting trades. The originality is the fusion of daily VWAP residual percentiles with a live micro-flow score from 1 minute data to switch between fade and breakout behavior inside the same session. Add it to a clean chart and use the markers and alerts.
Scope and intent
• Markets: Major FX pairs such as EURUSD, GBPUSD, USDJPY, AUDUSD, USDCHF, USDCAD
• Timeframes: One minute to one hour
• Default demo in this publication: EURUSD on 15 minutes
• Purpose: Reduce false starts by acting only when context, location and micro flow agree
• Limits: This is a strategy. Orders are simulated on standard candles only
Originality and usefulness
• Core novelty: Residual percentiles to daily anchored VWAP decide “balanced versus expanding day”. A separate 1 minute micro-flow score confirms direction, so the same model fades extremes in balance and rides range breaks in expansion
• Failure modes addressed: Chop fakeouts and unconfirmed breakouts are filtered by the expansion gate and micro-flow threshold
• Testability: Every input is exposed. Bands, background regime color, and markers show why a suggestion appears
• Portable yardstick: Stops and targets are ATR multiples converted to ticks, which transfer across symbols
• Open source status: No reused third-party code that requires attribution
Method overview in plain language
The day is anchored with a VWAP that updates from the daily session start. Price minus VWAP is the residual. Percentiles of that residual measured over a rolling window define location extremes for the current day. A regime score compares residual volatility to price volatility. When expansion is low, the day is treated as balanced and the model fades residual extremes if 1 minute micro flow points back to VWAP. When expansion is high, the model trades breakouts outside the VWAP bands if slope and micro flow agree with the move.
Base measures
• Range basis: True Range smoothed by ATR for stops and targets, length 14
• Return basis: Not required for signals; residuals are absolute price distance to VWAP
Components
• Daily Anchor VWAP Bands. VWAP with standard-deviation bands. Slope sign is used for trend confirmation on breakouts
• Residual Percentiles. Rolling percentiles of close minus VWAP over Signal length. Identify location extremes inside the day
• Expansion Ratio. Standard deviation of residuals divided by standard deviation of price over Signal length. Classifies balanced versus expanding day
• Micro Flow. Net up minus down closes from 1 minute data across a short span, normalized to −1..+1. Confirms direction and avoids fades against pressure
• Session Window optional. Restricts trading to your configured hours to avoid thin periods
• Cooldown optional. Bars to wait after a position closes to prevent immediate re-entry
Fusion rule
Gating rather than weighting. First choose regime by Expansion Ratio versus the Expansion gate. Inside each regime all listed conditions must be true: location test plus micro-flow threshold plus session window plus cooldown. Breakouts also require VWAP slope alignment.
Signal rule
• Long suggestion on balanced day: residual at or below the lower percentile and micro flow positive above the gate while inside session and cooldown is satisfied
• Short suggestion on balanced day: residual at or above the upper percentile and micro flow negative below the gate while inside session and cooldown is satisfied
• Long suggestion on expanding day: close above the upper VWAP band, VWAP slope positive, micro flow positive, session and cooldown satisfied
• Short suggestion on expanding day: close below the lower VWAP band, VWAP slope negative, micro flow negative, session and cooldown satisfied
• Positions flip on opposite suggestions or exit by brackets
What you will see on the chart
• Markers on suggestion bars: L for long, S for short
• Exit occurs on reverse signal or when a bracket order is filled
• Reference lines: daily anchored VWAP with upper and lower bands
• Optional background: teal for balanced day, orange for expanding day
Inputs with guidance
Setup
• Signal length. Residual and regime window. Typical 40 to 100. Higher smooths, lower reacts faster
Micro Flow
• Micro TF. Lower timeframe used for micro flow, default 1 minute
• Micro span bars. Count of lower-TF bars. Typical 5 to 20
• Micro flow gate 0..1. Minimum absolute flow. Raising it demands stronger confirmation and reduces trade count
VWAP Bands
• VWAP stdev multiplier. Band width. Typical 0.8 to 1.6. Wider bands reduce breakout frequency and increase fade distance
• Expansion gate 0..3. Threshold to switch from fades to breakouts. Raising it favors fades, lowering it favors breakouts
Sessions
• Use session filter. Enable to trade only inside your window
• Trade window UTC. Default 07:00 to 17:00
Risk
• ATR length. Stop and target basis. Typical 10 to 21
• Stop ATR x. Initial stop distance in ATR multiples
• Target ATR x. Profit target distance in ATR multiples
• Cooldown bars after close. Wait bars before a new entry
• Side. Both, long only, or short only
View
• Show VWAP and bands
• Color bars by residual regime
Properties visible in this publication
• Initial capital 10000
• Base currency Default
• request.security uses lookahead off everywhere
• Strategy: Percent of equity with value 3. Pyramiding 0. Commission cash per order 0.0001 USD. Slippage 3 ticks. Process orders on close ON. Bar magnifier ON. Recalculate after order is filled OFF. Calc on every tick OFF. Using standard OHLC fills ON.
Realism and responsible publication
No performance claims. Past results never guarantee future outcomes. Fills and slippage vary by venue. Shapes can move while a bar forms and settle on close. Strategies must run on standard candles for signals and orders.
Honest limitations and failure modes
High impact news, session opens, and thin liquidity can invalidate assumptions. Very quiet days can reduce contrast between residuals and price volatility. Session windows use the chart exchange time. If both stop and target are touched within a single bar, TradingView’s standard OHLC price-movement model decides the outcome.
Expect different behavior on illiquid pairs or during holidays. The model is sensitive to session definitions and feed time. Past results never guarantee future outcomes.
Legal
Education and research only. Not investment advice. You are responsible for your decisions. Test on historical data and in simulation before any live use. Use realistic costs.
Unicorn Trade Indicator - Enhanced V1This code also contains pinescripts from iFVG (BPR) by Algorize and Visualizing displacement by tradeforopp who have kindly provided them as open source.
An ICT Unicorn is where a breaker block is traded through which incorporates a fair value gap. I decided to code this indicator as I couldn't find an existing free indicator on Trading View that performed adequately.
This indicator will highlight breaker blocks and when broken will post an Unicorn emoji and send an alert if requested. The last 3 breaker blocks are displayed, the prior boxes are labled PBB and are shown as red for bearish and green for bullish. After the main Unicorn is posted, the code continues to mark market structure shifts.
As all trading strategies work better with confluence I have added several other features which is very useful for people who are restricted on the number of indicators that can place on a single chart.
I have added iFVG (BPR) by Algoryze and Visualizing displacement by tradeforopp which have kindly been made open source by the authors. My thanks to them for their hard work.
Unicorn alerts will only be sent when a yellow displacement candle ( from the Visualizing displacement code) is present along with the Unicorn as this is the best type of Unicorn to trade.
The number of fvg's and bpr's from the code by Algoryze can be adjusted in the settings.
Also to add confluence I have used my own code to display liquidity depth boxes made popular by toodegrees.
I hope you find this indicator useful.
Range Oscillator (Zeiierman)█ Overview
Range Oscillator (Zeiierman) is a dynamic market oscillator designed to visualize how far the price is trading relative to its equilibrium range. Instead of relying on traditional overbought/oversold thresholds, it uses adaptive range detection and heatmap coloring to reveal where price is trading within a volatility-adjusted band.
The oscillator maps market movement as a heat zone, highlighting when the price approaches the upper or lower range boundaries and signaling potential breakout or mean-reversion conditions.
Highlights
Adaptive range detection based on ATR and weighted price movement.
Heatmap-driven coloring that visualizes volatility pressure and directional bias.
Clear transition zones for detecting trend shifts and equilibrium points.
█ How It Works
⚪ Range Detection
The indicator identifies a dynamic price range using two main parameters:
Minimum Range Length: The number of bars required to confirm that a valid range exists.
Range Width Multiplier: Expands or contracts the detected range proportionally to the ATR (Average True Range).
This approach ensures that the oscillator automatically adapts to both trending and ranging markets without manual recalibration.
⚪ Weighted Mean Calculation
Instead of a simple moving average, the script calculates a weighted equilibrium mean based on the size of consecutive candle movements:
Larger price changes are given greater weight, emphasizing recent volatility.
⚪ Oscillator Formula
Once the range and equilibrium mean are defined, the oscillator computes:
Osc = 100 * (Close - Mean) / RangeATR
This normalizes price distance relative to the dynamic range size — producing consistent readings across volatile and quiet periods.
█ Heatmap Logic
The Range Oscillator includes a built-in heatmap engine that color-codes each oscillator value based on recent price interaction intensity:
Strong Bullish Zones: Bright green — price faces little resistance upward.
Weak Bullish Zones: Muted green — uptrend continuation but with minor hesitation.
Transition Zones: Blue — areas of uncertainty or trend shift.
Weak Bearish Zones: Maroon — downtrend pressure but soft momentum.
Strong Bearish Zones: Bright red — strong downside continuation with low resistance.
Each color band adapts dynamically using:
Number of Heat Levels: Controls granularity of the heatmap.
Minimum Touches per Level: Defines how reactive or “sensitive” each color zone is.
█ How to Use
⚪ Trend & Momentum Confirmation
When the oscillator stays above +0 with green coloring, it suggests sustained bullish pressure.
Similarly, readings below –0 with red coloring, it suggests sustained bearish pressure.
⚪ Range Breakouts
When the oscillator line breaks above +100 or below –100, the price is exceeding its normal volatility range, often signaling breakout potential or exhaustion extremes.
⚪ Mean Reversion Trades
Look for the oscillator to cross back toward zero after reaching an extreme. These transitions (often marked by blue tones) can identify early reversals or range resets.
⚪ Divergence
Use oscillator peaks and troughs relative to price action to spot hidden strength or weakness before the next move.
█ Settings
Minimum Range Length: Number of bars needed to confirm a valid range.
Range Width Multiplier: Expands or contracts range width based on ATR.
Number of Heat Levels: Number of gradient bands used in the oscillator.
Minimum Touches per Level: Sensitivity threshold for when a zone becomes “hot.”
-----------------
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.
saodisengxiaoyu-lianghua-2.1- This indicator is a modular, signal-building framework designed to generate long and short signals by combining a chosen leading indicator with selectable confirmation filters. It runs on Pine Script version 5, overlays directly on price, and is built to be highly configurable so traders can tailor the signal logic to their market, timeframe, and trading style. It includes a dashboard to visualize which conditions are active and whether they validate a signal, and it outputs clear buy/sell labels and alert conditions so you can automate or monitor trades with confidence.
Core Design
- Leading Indicator: You choose one primary signal generator from a broad list (for example, Range Filter, Supertrend, MACD, RSI, Ichimoku, and many others). This serves as the anchor of the system and determines when a preliminary long or short setup exists.
- Confirmation Filters: You can enable additional filters that validate the leading signal before it becomes actionable. Each “respect…” input toggles a filter on or off. These filters include popular tools like EMA, 2/3 EMA crosses, RQK (Nadaraya Watson), ADX/DMI, Bollinger-based oscillators, MACD variations, QQE, Hull, VWAP, Choppiness Index, Damiani Volatility, and more.
- Signal Expiry: To avoid waiting indefinitely for confirmations, the indicator counts how many consecutive bars the leading condition holds. If confirmations do not align within a defined number of bars, the setup expires. This controls latency and helps reduce late or stale entries.
- Alternating Signals: An optional mode enforces alternation (long must follow short and vice versa), helping avoid repeated entries in the same direction without a meaningful reset.
- Aggregation Logic: The final long/short conditions are formed by combining the leading condition with all selected confirmation filters through logical conjunction. Only if all enabled filters validate the signal (within expiry constraints) does the indicator consider it a confirmed long or short.
- Visualization and Alerts: The script plots buy/sell labels at signal points, provides alert conditions for automation, and displays a compact dashboard summarizing the leading indicator’s status and each confirmation’s pass/fail result using checkmarks.
Leading Indicator Options
- The indicator includes a very large menu of leading tools, each with its own logic to determine uptrend or downtrend impulses. Highlights include:
- Range Filter: Uses a dynamic centerline and bands computed via conditional EMA/SMA and range sizing to define directional movement. It can operate in a default mode or an alternative “DW” mode.
- Rational Quadratic Kernel (RQK): Applies a kernel smoothing model (Nadaraya Watson) to detect uptrends and downtrends with a focus on noise reduction.
- Supertrend, Half Trend, SSL Channel: Classic trend-following tools that derive direction from ATR-based bands or moving average channels.
- Ichimoku Cloud and SuperIchi: Multi-component systems validating trend via cloud position, conversion/base line relationships, projected cloud, and lagging span.
- TSI (True Strength Index), DPO (Detrended Price Oscillator), AO (Awesome Oscillator), MACD, STC (Schaff Trend Cycle), QQE Mod: Momentum and cycle tools that parse direction from crossovers, zero-line behavior, and momentum shifts.
- Donchian Trend Ribbon, Chandelier Exit: Trend and exit tools that can validate breakouts or sustained trend strength.
- ADX/DMI: Measures trend strength and directional movement via +DI/-DI relationships and minimum ADX thresholds.
- RSI and Stochastic: Use crossovers, level exits, or threshold filters to gate entries based on overbought/oversold dynamics or relative strength trends.
- Vortex, Chaikin Money Flow, VWAP, Bull Bear Power, ROC, Wolfpack Id, Hull Suite: A diverse set of directional, momentum, and volume-based indicators to suit different markets and styles.
- Trendline Breakout and Range Detector: Price-behavior filters that confirm signals during breakouts or within defined ranges.
Confirmation Filters
- Each filter is optional. When enabled, it must validate the leading condition for a signal to pass. Examples:
- EMA Filter: Requires price to be above a specified EMA for longs and below for shorts, filtering signals that contradict broader trend or baseline levels.
- 2 EMA Cross and 3 EMA Cross: Enforce moving average cross conditions (fast above slow for long, the reverse for short) or a three-line stacking logic for more stringent trend alignment.
- RQK, Supertrend, Half Trend, Donchian, QQE, Hull, MACD (crossover vs. zero-line), AO (zero line or AC momentum variants), SSL: Each adds its characteristic validation pattern.
- RSI family (MA cross, exits OB/OS zones, threshold levels) plus RSI MA direction and RSI/RSI MA limits: Multiple ways to constrain signals via relative strength behavior and trajectories.
- Choppiness Index and Damiani Volatility: Prevent entries during ranging conditions or insufficient volatility; choppiness thresholds and volatility states gate the trade.
- VWAP, Volume modes (above MA, simple up/down, delta), Chaikin Money Flow: Volume and flow conditions that ensure signals happen in supportive liquidity or accumulation/distribution contexts.
- ADX/DMI thresholds: Demand a minimum trend strength and directional DI alignment to reduce whipsaw trades.
- Trendline Breakout and Range Detector: Confirm that the price is breaking structure or remains within active range consistent with the leading setup.
- By combining several filters you can create strict, conservative entries or looser setups depending on your goals.
Range Filter Engine
- A core building block, the Range Filter uses conditional EMA and SMA functions to compute adaptive bands around a dynamic centerline. It supports two types:
- Type 1: The centerline updates when price exceeds the band thresholds; bands define acceptable drift ranges.
- Type 2: Uses quantized steps (via floor operations) relative to the previous centerline to handle larger moves in discrete increments.
- The engine offers smoothing for range values using a secondary EMA and can switch between raw and averaged outputs. Its hi/lo bands and centerline compose a corridor that defines directional movement and potential breakout confirmation.
Signal Construction
- The script computes:
- leadinglongcond and leadingshortcond : The primary directional signals from the chosen leading indicator.
- longCond and shortCond : Final signals formed by combining the leading conditions with all enabled confirmations. Each confirmation contributes a boolean gate. If a filter is disabled, it contributes a neutral pass-through, keeping the logic intact without enforcing that condition.
- Expiry Logic: The code counts consecutive bars where the leading condition remains true. If confirmations do not line up within the user-defined “Signal Expiry Candle Count,” the setup is abandoned and the signal does not trigger.
- Alternation: An optional state ensures that long and short signals alternate. This can reduce repeated entries in the same direction without a clear reset.
- Finally, longCondition and shortCondition represent the actionable signals after expiry and alternation logic. These drive the label plotting and alert conditions.
Visualization
- Buy and Sell Labels: When longCondition or shortCondition confirm, the script plots annotated labels directly on the chart, making entries easy to see at a glance. The labels use color coding and clear text tags (“long” vs. “short”).
- Dashboard: A table summarizes the status of the leading indicator and all confirmations. Each row shows the indicator label and whether it passed (✔️) or failed (❌) on the current bar. This intensely practical UI helps you diagnose why a signal did or did not trigger, empowering faster strategy iteration and parameter tuning.
- Failed Confirmation Markers: If a setup expires (count exceeds the limit) and confirmations failed to align, the script can mark the chart with a small label and provide a tooltip listing which confirmations did not pass. It’s a helpful audit trail to understand missed trades or prevent “chasing” invalid signals.
- Data Window Values: The script outputs signal states to the data window, which can be useful for debugging or building composite conditions in multi-indicator templates.
Inputs and Parameters
- You control the indicator from a comprehensive input panel:
- Setup: Signal expiry count, whether to enforce alternating signals, and whether to display labels and the dashboard (including position and size).
- Leading Indicator: Choose the primary signal generator from the large list.
- Per-Filter Toggles: For each confirmation, a respect... toggle enables or disables it. Many include sub-options (like MACD type, Stochastic mode, RSI mode, ADX variants, thresholds for choppiness/volatility, etc.) to fine-tune behavior.
- Range Filter Settings: Choose type and behavior; select default vs. DW mode and smoothing. The underlying functions adjust band sizes using ATR, average change, standard deviation, or user-defined scales.
- Because everything is customizable, you can adapt the indicator to different assets, volatility regimes, and timeframes.
Alerts and Automation
- The script defines alert conditions tied to longCondition and shortCondition . You can set these alerts in your chart to trigger notifications or webhook calls for automated execution in external bots. The alert text is simple, and you can configure your own message template when creating alerts in the chart, including JSON payloads for algorithmic integration.
Typical Workflow
- Select a Leading Indicator aligned with your style. For trend following, Supertrend or SSL may be appropriate; for momentum, MACD or TSI; for range/trend-change detection, Range Filter, RQK, or Donchian.
- Add a few key Confirmation Filters that complement the leading signal. For example:
- Pair Supertrend with EMA Filter and RSI MA Direction to ensure trend alignment and positive momentum.
- Combine MACD Crossover with ADX/DMI and Volume Above MA to avoid signals in low-trend or low-liquidity conditions.
- Use RQK with Choppiness Index and Damiani Volatility to only act when the market is trending and volatile enough.
- Set a sensible Signal Expiry Candle Count. Shorter expiry keeps entries timely and reduces lag; longer expiry captures setups that mature slowly.
- Observe the Dashboard during live markets to see which filters pass or fail, then iterate. Tighten or loosen thresholds and filter combinations as needed.
- For automation, turn on alerts for the final conditions and use webhook payloads to notify your trading robot.
Strengths and Practical Notes
- Flexibility: The indicator is a toolkit rather than a single rigid model. It lets you test different combinations rapidly and visualize outcomes immediately.
- Clarity: Labels, dashboard, and failed-confirmation markers make it easy to audit behavior and refine settings without digging into code.
- Robustness: The expiry and alternation options add discipline, avoiding the temptation to enter late or repeatedly in one direction without a reset.
- Modular Design: The logical gates (“respect…”) make the behavior transparent: if a filter is on, it must pass; if it’s off, the signal ignores it. This keeps reasoning clean.
- Avoiding Overfitting: Because you can stack many filters, it’s tempting to over-constrain signals. Start simple (one leading indicator and one or two confirmations). Add complexity only if it demonstrably improves your edge across varied market regimes.
Limitations and Recommendations
- No single configuration is universally optimal. Markets change; tune filters for the instrument and timeframe you trade and revisit settings periodically.
- Trend filters can underperform in choppy markets; likewise, momentum filters can false-trigger in quiet periods. Consider using Choppiness Index or Damiani to gate signals by regime.
- Use expiry wisely. Too short may miss good setups that need a few bars to confirm; too long may cause late entries. Balance responsiveness and accuracy.
- Always consider risk management externally (position sizing, stops, profit targets). The indicator focuses on signal quality; combining it with robust trade management methods will improve results.
Example Configurations
- Trend-Following Setup:
- Leading: Supertrend uptrend for longs and downtrend for shorts.
- Confirmations: EMA Filter (price above 200 EMA for long, below for short), ADX/DMI (trend strength above threshold with +DI/-DI alignment), Volume Above MA.
- Expiry: 3–4 bars to keep entries timely.
- Result: Strong bias toward sustained moves while avoiding weak trends and thin liquidity.
- Mean-Reversion to Momentum Crossover:
- Leading: RSI exits from OB/OS zones (e.g., RSI leaves oversold for long and leaves overbought for short).
- Confirmations: 2 EMA Cross (fast crossing slow in the same direction), MACD zero-line behavior for added momentum validation.
- Expiry: 2–3 bars for responsive re-entry.
- Result: Captures momentum transitions after short-term extremes, with extra confirmation to reduce head-fakes.
- Range Breakout Focus:
- Leading: Range Filter Type 2 or Donchian Trend Ribbon to detect breakouts.
- Confirmations: Damiani Volatility (avoid low-volatility false breaks), Choppiness Index (prefer trend-ready states), ROC positive/negative threshold.
- Expiry: 1–3 bars to act on breakout windows.
- Result: Better alignment to breakout dynamics, gating trades by volatility and regime.
Conclusion
- This indicator is a comprehensive, configurable framework that merges a chosen leading signal with an array of corroborating filters, disciplined expiry handling, and intuitive visualization. It’s designed to help you build high-quality entry signals tailored to your approach, whether that’s trend-following, breakout trading, momentum capturing, or a hybrid. By surfacing pass/fail states in a dashboard and allowing alert-based automation, it bridges the gap between discretionary analysis and systematic execution. With sensible parameter tuning and thoughtful filter selection, it can serve as a robust backbone for signal generation across diverse instruments and timeframes.
