Smart Money Flow Index (SMFI) - Advanced SMC [PhenLabs]📊Smart Money Flow Index (SMFI)
Version: PineScript™v6
📌Description
The Smart Money Flow Index (SMFI) is an advanced Smart Money Concepts implementation that tracks institutional trading behavior through multi-dimensional analysis. This comprehensive indicator combines volume-validated Order Block detection, Fair Value Gap identification with auto-mitigation tracking, dynamic Liquidity Zone mapping, and Break of Structure/Change of Character detection into a unified system.
Unlike basic SMC indicators, SMFI employs a proprietary scoring algorithm that weighs five critical factors: Order Block strength (validated by volume), Fair Value Gap size and recency, proximity to Liquidity Zones, market structure alignment (BOS/CHoCH), and multi-timeframe confluence. This produces a Smart Money Score (0-100) where readings above 70 represent optimal institutional setup conditions.
🚀Points of Innovation
Volume-Validated Order Block Detection – Only displays Order Blocks when formation candle exceeds customizable volume multiplier (default 1.5x average), filtering weak zones and highlighting true institutional accumulation/distribution
Auto-Mitigation Tracking System – Fair Value Gaps and Order Blocks automatically update status when price mitigates them, with visual distinction between active and filled zones preventing trades on dead levels
Proprietary Smart Money Score Algorithm – Combines weighted factors (OB strength 25%, FVG proximity 20%, Liquidity 20%, Structure 20%, MTF 15%) into single 0-100 confidence rating updating in real-time
ATR-Based Adaptive Calculations – All distance measurements use 14-period Average True Range ensuring consistent function across any instrument, timeframe, or volatility regime without manual recalibration
Dynamic Age Filtering – Automatically removes liquidity levels and FVGs older than configurable thresholds preventing chart clutter while maintaining relevant levels
Multi-Timeframe Confluence Integration – Analyzes higher timeframe bias with customizable multipliers (2-10x) and incorporates HTF trend direction into Smart Money Score for institutional alignment
🔧Core Components
Order Block Engine – Detects institutional supply/demand zones using characteristic patterns (down-move-then-strong-up for bullish, up-move-then-strong-down for bearish) with minimum volume threshold validation, tracks mitigation when price closes through zones
Fair Value Gap Scanner – Identifies price imbalances where current candle's low/high leaves gap with two-candle-prior high/low, filters by minimum size percentage, monitors 50% fill for mitigation status
Liquidity Zone Mapper – Uses pivot high/low detection with configurable lookback to mark swing points where stop losses cluster, extends horizontal lines to visualize sweep targets, manages lifecycle through age-based removal
Market Structure Analyzer – Tracks pivot progression to identify trend through higher-highs/higher-lows (bullish) or lower-highs/lower-lows (bearish), detects Break of Structure and Change of Character for trend/reversal confirmation
Scoring Calculation Engine – Evaluates proximity to nearest Order Blocks using ATR-normalized distance, assesses FVG recency and distance, calculates liquidity proximity with age weighting, combines structure bias and MTF trend into smoothed final score
🔥Key Features
Customizable Display Limits – Control maximum Order Blocks (1-10), Liquidity Zones (1-10), and FVG age (10-200 bars) to maintain clean charts focused on most relevant institutional levels
Gradient Strength Visualization – All zones render with transparency-adjustable coloring where stronger/newer zones appear more solid and weaker/older zones fade progressively providing instant visual hierarchy
Educational Label System – Optional labels identify each zone type (Bullish OB, Bearish OB, Bullish FVG, Bearish FVG, BOS) with color-coded text helping traders learn SMC concepts through practical application
Real-Time Smart Money Score Dashboard – Top-right table displays current score (0-100) with color coding (green >70, yellow 30-70, red <30) plus trend arrow for at-a-glance confidence assessment
Comprehensive Alert Suite – Configurable notifications for Order Block formation, Fair Value Gap detection, Break of Structure events, Change of Character signals, and high Smart Money Score readings (>70)
Buy/Sell Signal Integration – Automatically plots triangle markers when Smart Money Score exceeds 70 with aligned market structure and fresh Order Block detection providing clear entry signals
🎨Visualization
Order Block Boxes – Shaded rectangles extend from formation bar spanning high-to-low of institutional candle, bullish zones in green, bearish in red, with customizable transparency (80-98%)
Fair Value Gap Zones – Rectangular areas marking imbalances, active FVGs display in bright colors with adjustable transparency, mitigated FVGs switch to gray preventing trades on filled zones
Liquidity Level Lines – Dashed horizontal lines extend from pivot creation points, swing highs in bearish color (short targets above), swing lows in bullish color (long targets below), opacity decreases with age
Structure Labels – "BOS" labels appear above/below price when Break of Structure confirmed, colored by direction (green bullish, red bearish), positioned at 1% beyond highs/lows for visibility
Educational Info Panel – Bottom-right table explains key terminology (OB, FVG, BOS, CHoCH) and score interpretation (>70 high probability) with semi-transparent background for readability
📖Usage Guidelines
General Settings
Show Order Blocks – Default: On, toggles visibility of institutional supply/demand zones, disable when focusing solely on FVGs or Liquidity
Show Fair Value Gaps – Default: On, controls FVG zone display including active and mitigated imbalances
Show Liquidity Zones – Default: On, manages liquidity line visibility, disable on lower timeframes to reduce clutter
Show Market Structure – Default: On, toggles BOS/CHoCH label display
Show Smart Money Score – Default: On, controls score dashboard visibility
Order Block Settings
OB Lookback Period – Default: 20, Range: 5-100, controls bars scanned for Order Block patterns, lower values detect recent activity, higher values find older blocks
Min Volume Multiplier – Default: 1.5, Range: 1.0-5.0, sets minimum volume threshold as multiple of 20-period average, higher values (2.0+) filter for strongest institutional candles
Max Order Blocks to Display – Default: 3, Range: 1-10, limits simultaneous Order Blocks shown, lower settings (1-3) maintain focus on most recent zones
Fair Value Gap Settings
Min FVG Size (%) – Default: 0.3, Range: 0.1-2.0, defines minimum gap size as percentage of close price, lower values detect micro-imbalances, higher values focus on significant gaps
Max FVG Age (bars) – Default: 50, Range: 10-200, removes FVGs older than specified bars, lower settings (10-30) for scalping, higher (100-200) for swing trading
Show FVG Mitigation – Default: On, displays filled FVGs in gray providing visual history, disable to show only active untouched imbalances
Liquidity Zone Settings
Liquidity Lookback – Default: 50, Range: 20-200, sets pivot detection period for swing highs/lows, lower values (20-50) mark shorter-term liquidity, higher (100-200) identify major swings
Max Liquidity Age (bars) – Default: 100, Range: 20-500, removes liquidity lines older than specified bars, adjust based on timeframe
Liquidity Sensitivity – Default: 0.5, Range: 0.1-1.0, controls pivot detection sensitivity, lower values mark only major swings, higher values identify minor swings
Max Liquidity Zones to Display – Default: 3, Range: 1-10, limits total liquidity levels shown maintaining chart clarity
Market Structure Settings
Pivot Length – Default: 5, Range: 3-15, defines bars to left/right for pivot validation, lower values (3-5) create sensitive structure breaks, higher (10-15) filter for major shifts
Min Structure Move (%) – Default: 1.0, Range: 0.1-5.0, sets minimum percentage move required between pivots to confirm structure change
Multi-Timeframe Settings
Enable MTF Analysis – Default: On, activates higher timeframe trend analysis incorporation into Smart Money Score
Higher Timeframe Multiplier – Default: 4, Range: 2-10, multiplies current timeframe to determine analysis timeframe (4x on 15min = 1hour)
Visual Settings
Bullish Color – Default: Green (#089981), sets color for bullish Order Blocks, FVGs, and structure elements
Bearish Color – Default: Red (#f23645), defines color for bearish elements
Neutral Color – Default: Gray (#787b86), controls color of mitigated zones and neutral elements
Show Educational Labels – Default: On, displays text labels on zones identifying type (OB, FVG, BOS), disable once familiar with patterns
Order Block Transparency – Default: 92, Range: 80-98, controls Order Block box transparency
FVG Transparency – Default: 92, Range: 80-98, sets Fair Value Gap zone transparency independently from Order Blocks
Alert Settings
Alert on Order Block Formation – Default: On, triggers notification when new volume-validated Order Block detected
Alert on FVG Formation – Default: On, sends alert when Fair Value Gap appears enabling quick response to imbalances
Alert on Break of Structure – Default: On, notifies when BOS or CHoCH confirmed
Alert on High Smart Money Score – Default: On, alerts when Smart Money Score crosses above 70 threshold indicating high-probability setup
✅Best Use Cases
Order Block Retest Entries – After Break of Structure, wait for price retrace into fresh bullish Order Block with Smart Money Score >70, enter long on zone reaction targeting next liquidity level
Fair Value Gap Retracement Trading – When price creates FVG during strong move then retraces, enter as price approaches unfilled gap expecting institutional orders to continue trend
Liquidity Sweep Reversals – Monitor price approaching swing high/low liquidity zones against prevailing Smart Money Score trend, after stop hunt sweep watch for rejection into premium Order Block/FVG
Multi-Timeframe Confluence Setups – Identify alignment when current timeframe Order Block coincides with higher timeframe FVG plus MTF analysis showing matching trend bias
Break of Structure Continuations – After BOS confirms trend direction, trade pullbacks to nearest Order Block or FVG in direction of structure break using Smart Money Score >70 as entry filter
Change of Character Reversal Plays – When CHoCH detected indicating potential reversal, look for Smart Money Score pivot with opposing Order Block formation then enter on structure confirmation
⚠️Limitations
Lagging Pivot Calculations – Pivot-based features (Liquidity Zones, Market Structure) require bars to right of pivot for confirmation, meaning these elements identify levels retrospectively with delay equal to lookback period
Whipsaw in Ranging Markets – During choppy conditions, Order Blocks fail frequently and structure breaks produce false signals as Smart Money Score fluctuates without clear institutional bias, best used in trending markets
Volume Data Dependency – Order Block volume validation requires accurate volume data which may be incomplete on Forex pairs or limited in crypto exchange feeds
Subjectivity in Scoring Weights – Proprietary 25-20-20-20-15 weighting reflects general institutional behavior but may not optimize for specific instruments or market regimes, user cannot adjust factor weights
Visual Complexity on Lower Timeframes – Sub-hour timeframes generate excessive zones creating cluttered charts, requires aggressive display limit reduction and higher minimum thresholds
No Fundamental Integration – Indicator analyzes purely technical price action and volume without incorporating economic events, news catalysts, or fundamental shifts that override technical levels
💡What Makes This Unique
Unified SMC Ecosystem – Unlike indicators displaying Order Blocks OR FVGs OR Liquidity separately, SMFI combines all three institutional concepts plus market structure into single cohesive system
Proprietary Confidence Scoring – Rather than manual setup assessment, automated Smart Money Score quantifies probability by weighting five institutional dimensions into actionable 0-100 rating
Volume-Filtered Quality – Eliminates weak Order Blocks forming without institutional volume confirmation, ensuring displayed zones represent genuine accumulation/distribution
Adaptive Lifecycle Management – Automatically updates mitigation status and removes aged zones preventing trades on dead levels through continuous validity and age monitoring
Educational Integration – Built-in tooltips, labeled zones, and reference panel make indicator functional for both learning Smart Money Concepts and executing strategies
🔬How It Works
Order Block Detection – Scans for patterns where strong directional move follows counter-move creating last down-candle before rally (bullish OB) or last up-candle before sell-off (bearish OB), validates formations only when candle exhibits volume exceeding configurable multiple (default 1.5x) of 20-bar average volume
Fair Value Gap Identification – Compares current candle’s high/low against two-candles-prior low/high to detect price imbalances, calculates gap size as percentage of close and filters micro-gaps below minimum threshold (default 0.3%), monitors whether subsequent price fills 50% triggering mitigation status
Liquidity Zone Mapping – Employs pivot detection using configurable lookback (default 50 bars) to identify swing highs/lows where retail stops cluster, extends horizontal reference lines from pivot creation and applies age-based filtering to remove stale zones
Market Structure Analysis – Tracks pivot progression using structure-specific lookback (default 5 bars) to determine trend, confirms uptrend when new pivot high exceeds previous by minimum move percentage, detects Break of Structure when price breaks recent pivot level, flags Change of Character for potential reversals
Multi-Timeframe Confluence – When enabled, requests security data from higher timeframe (current TF × HTF multiplier, default 4x), compares HTF close against HTF 20-period MA to determine bias, contributes ±50 points to score ensuring alignment with institutional positioning on superior timeframe
Smart Money Score Calculation – Evaluates Order Block component via ATR-normalized distance producing max 100-point contribution weighted at 25%, assesses FVG factor through age penalty and distance at 20% weight, calculates Liquidity proximity at 20%, incorporates structure bias (±50-100 points) at 20%, adds MTF component at 15%, applies 3-period smoothing to reduce volatility
Visual Rendering and Lifecycle – Draws Order Block boxes, Fair Value Gap rectangles with color coding (green/red active, gray mitigated), extends liquidity dashed lines with fade-by-age opacity, plots BOS labels, displays Smart Money Score dashboard, continuously updates checking mitigation conditions and removing elements exceeding age/display limits
💡Note:
The Smart Money Flow Index combines multiple Smart Money Concepts into unified institutional order flow analysis. For optimal results, use the Smart Money Score as confluence filter rather than standalone entry signal – scores above 70 indicate high-probability setups but should be combined with risk management, higher timeframe bias, and market regime understanding.
ATR
Twisted Analytics ATR Model ProThe Trend Spotter Indicator is a sophisticated technical analysis tool engineered to identify high-probability trend formations across all timeframes and asset classes. Built with proprietary algorithms, this indicator combines multiple technical methodologies to deliver clear, actionable signals for traders at all experience levels.
What Makes It Unique
Unlike basic moving average systems, the Trend Spotter employs a multi-layered approach that validates trends through:
Multi-Timeframe Analysis: Confirms signals across higher timeframes to filter false positives
Adaptive Volatility Filtering: Adjusts thresholds based on ATR to optimize for both ranging and trending markets
Momentum Confirmation: Validates trend strength using proprietary oscillators before generating signals
Dynamic Trend Strength Measurement: Real-time assessment of trend intensity and potential exhaustion
Key Features
✅ Universal Compatibility: Works seamlessly on crypto, stocks, forex, commodities, and indices
✅ No Repainting: Signals remain fixed once generated - reliable for backtesting and live trading
✅ Customizable Alerts: Set up notifications for trend reversals, breakouts, and momentum shifts
✅ Visual Clarity: Color-coded signals with adjustable display settings
✅ Smart Noise Filtering: Advanced algorithms eliminate market noise and focus on genuine trends
✅ Support/Resistance Detection: Automatically identifies key levels based on trend structure
How It Works
The indicator analyzes price action through four independent validation layers:
Trend Identification: Detects higher highs/lows (uptrend) or lower highs/lows (downtrend)
Momentum Confirmation: Ensures signals align with prevailing momentum
Volatility Analysis: Adapts to changing market conditions using ATR-based thresholds
Signal Validation: Cross-references multiple factors before generating final signals
This multi-factor approach significantly reduces false signals by requiring confirmation from multiple independent analysis methods.
Best Use Cases
Trend Following: Ride major trends from early entry to exhaustion
Breakout Trading: Catch strong momentum moves out of consolidation
Reversal Trading: Identify trend exhaustion and potential reversals
Multi-Timeframe Strategies: Confirm lower timeframe entries with higher timeframe trends
Who Should Use This
Day traders seeking reliable trend signals on intraday charts
Swing traders looking for multi-day trend opportunities
Position traders wanting to identify major trend changes
Both beginner and professional traders who value data-driven decision making
Configuration Flexibility
The indicator offers extensive customization options:
Trend Period: Adjust sensitivity from 5 to 200 bars
Signal Sensitivity: Choose Low/Medium/High based on trading style
Trend Strength Threshold: Filter weak trends (0-100 scale)
Multi-Timeframe Mode: Enable/disable higher timeframe confirmation
Visual Settings: Customize colors, signal size, and labels
Trading Strategy Examples
Trend Following: Enter on initial signal, add on pullbacks, exit on reversal
Breakout Strategy: Wait for consolidation, enter on trend signal breakout
Reversal Strategy: Identify exhaustion, enter on first opposite signal
Scalping: Use high sensitivity on 1-15 min charts for quick trades
Risk Management Note
While the Trend Spotter provides high-probability signals, no indicator guarantees profits. Always use proper risk management:
Risk only 1-2% of capital per trade
Set stop-losses based on technical levels
Combine with volume analysis and support/resistance
Backtest settings on historical data before live trading
What You Get
Professional-grade trend detection algorithm
Real-time signal generation with no lag
Comprehensive parameter customization
Visual clarity with intuitive color coding
Compatible with all TradingView account types
Ongoing updates and improvements
Technical Specifications
Calculation Method: Proprietary multi-factor analysis
Signal Type: Non-repainting trend direction and strength
Overlay: Yes - displays directly on price chart
Alerts: Fully customizable alert conditions
Timeframes: All timeframes from 1-minute to monthly
Asset Classes: Universal - works on all tradable instruments
Support
Published by Twisted Analytics - Professional trading tools built by traders, for traders.
Volume Weighted Average True RangeThis indicator calculates a customizable version of the Average True Range (ATR), a tool for measuring market volatility. It enhances the standard ATR with volume weighting, a dual-smoothing process, normalization, and volatility pivot detection.
Key Features:
Volume Weighting: An option (Volume weighted) allows for volume to be incorporated into the volatility calculation. This provides a measure of "volume-adjusted" volatility that is more responsive to significant market activity.
Dual Smoothing Process: For noise reduction, the indicator employs a two-stage smoothing process. It first calculates a smoothed True Range (TR) over a user-defined period (TR Length) before applying the final ATR moving average (ATR Length & ATR Smooth).
Normalization (Percentage Volatility): An optional 'Normalize' mode calculates the ATR as a percentage of the price. This allows for consistent volatility comparison across different assets and over long time periods.
Volatility Pivot Detection: The indicator includes a built-in pivot detector that identifies significant turning points (highs and lows) in the ATR line itself, signaling potential shifts in volatility.
Note on Confirmation (Lag): Pivot signals are confirmed using a lookback method. A pivot is only plotted after the Pivot Right Bars input has passed. This is essential for ensuring the signal is non-repainting but introduces an inherent lag.
Multi-Timeframe (MTF) Capability:
MTF ATR Line: The ATR line itself can be calculated on a different timeframe, with standard options to handle gaps (Fill Gaps) and prevent repainting (Wait for...).
Limitation: The Pivot detection (Calculate Pivots) is disabled if a Higher Timeframe (HTF) is selected.
Integrated Alerts: Includes alerts that trigger when a new volatility pivot (high or low) is detected in the ATR line.
DISCLAIMER
For Informational/Educational Use Only: This indicator is provided for informational and educational purposes only. It does not constitute financial, investment, or trading advice, nor is it a recommendation to buy or sell any asset.
Use at Your Own Risk: All trading decisions you make based on the information or signals generated by this indicator are made solely at your own risk.
No Guarantee of Performance: Past performance is not an indicator of future results. The author makes no guarantee regarding the accuracy of the signals or future profitability.
No Liability: The author shall not be held liable for any financial losses or damages incurred directly or indirectly from the use of this indicator.
Signals Are Not Recommendations: The alerts and visual signals (e.g., crossovers) generated by this tool are not direct recommendations to buy or sell. They are technical observations for your own analysis and consideration.
Volatility Resonance CandlesVolatility Resonance Candles visualize the dynamic interaction between price acceleration, volatility, and volume energy.
They’re designed to reveal moments when volatility expansion and directional momentum resonate — often preceding strong directional moves or reversals.
🔬 Concept
Traditional candles display direction and range, but they miss the energetic structure of volatility itself.
This indicator introduces a resonance model, where ATR ratio, price acceleration, and volume intensity combine to form a composite signal.
* ATR Resonance: compares short-term vs. long-term volatility
* Acceleration: captures the rate of price change
* Volume Energy: reinforces the move’s significance
When these components align, the candle color “resonates” — brighter, more intense candles signal stronger volatility–momentum coupling.
⚙️ Features
* Adaptive Scaling
Normalizes energy intensity dynamically across a user-defined lookback period, ensuring consistency in changing market conditions.
* Power-Law Transformation
Optional non-linear scaling (gamma) emphasizes higher-energy events while keeping low-intensity noise visually subdued.
* Divergence Mode
When enabled, colors can invert to highlight energy divergence from candle direction (e.g., bearish pressure during bullish closes).
* Customizable Styling
Full control over bullish/bearish base colors, transparency scaling, and threshold sensitivity.
🧠 Interpretation
* Bright / High-Intensity Candles → Strong alignment of volatility and directional energy.
Often signals the resonant phase of a move — acceleration backed by volatility expansion and volume participation.
* Dim / Low-Intensity Candles → Energy dispersion or consolidation.
These typically mark quiet zones, pauses, or inefficient volatility.
* Opposite-Colored Candles (if divergence mode on) → Potential inflection zones or hidden stress in the trend structure.
⚠️ Disclaimer
This script is for educational purposes only.
It does not constitute financial advice, and past performance is not indicative of future results. Always do your own research and test strategies before making trading decisions.
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.
Volatility Dashboard (ATR-Based)Here's a brief description of what this indicator does:
- This measures volatility of currents based on ATR (Average True Range) and plots them against the smoothed ATR baseline (SMA of ATR for the same periods).
- It categorizes the market as one of the three regimes depending on the above-mentioned ratio:
- High Volatility (ratio > 1.2)
- Normal Volatility (between 0.8 and 1.2),
|- Low Volatility (ratio < 0.8, green)
- For each type of trading regime, Value Area (VA) coverage to use: for example: 60-65% in high vol trade regimes, 70% in normal trade regimes, 80-85% in low trade regimes
* What you’ll see on the chart:
- Compact dashboard in the top-right corner featuring:
- ATR (present, default length 20)
- ATR Avg (ATR baseline)
- The volatility regime identified based on the color-coded background and the coverage recommended for the VA.
Important inputs that can be adjusted:
- ATR Length (default 20) - “High/Low volatility thresholds” (default values: 1.2 – The VA coverage recommendations for each scheme (text) Purpose: - Quickly determine whether volatility is above/below average and adjust the coverage of the Value Area.
If you're using this for the GC1! Use 14 ATR Length, For ES or NQ Use Default Setting(20)
MTF K-Means Price Regimes [matteovesperi] ⚠️ The preview uses a custom example to identify support/resistance zones. due to the fact that this identifier clusterizes, this is possible. this example was set up "in a hurry", therefore it has a possible inaccuracy. When setting up the indicator, it is extremely important to select the correct parameters and double-check them on the selected history.
📊 OVERVIEW
Purpose
MTF K-Means Price Regimes is a TradingView indicator that automatically identifies and classifies the current market regime based on the K-Means machine learning algorithm. The indicator uses data from a higher timeframe (Multi-TimeFrame, MTF) to build stable classification and applies it to the working timeframe in real-time.
Key Features
✅ Automatic market regime detection — the algorithm finds clusters of similar market conditions
✅ Multi-timeframe (MTF) — clustering on higher TF, application on lower TF
✅ Adaptive — model recalculates when a new HTF bar appears with a rolling window
✅ Non-Repainting — classification is performed only on closed bars
✅ Visualization — bar coloring + information panel with cluster characteristics
✅ Flexible settings — from 2 to 10 clusters, customizable feature periods, HTF selection
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🔬 TECHNICAL DETAILS
K-Means Clustering Algorithm
What is K-Means?
K-Means is one of the most popular clustering algorithms (unsupervised machine learning). It divides a dataset into K groups (clusters) so that similar elements are within each cluster, and different elements are between clusters.
Algorithm objective:
Minimize within-cluster variance (sum of squared distances from points to their cluster center).
How Does K-Means Work in Our Indicator?
Step 1: Data Collection
The indicator accumulates history from the higher timeframe (HTF):
RSI (Relative Strength Index) — overbought/oversold indicator
ATR% (Average True Range as % of price) — volatility indicator
ΔP% (Price Change in %) — trend strength and direction indicator
By default, 200 HTF bars are accumulated (clusterLookback parameter).
Step 2: Creating Feature Vectors
Each HTF bar is described by a three-dimensional vector:
Vector =
Step 3: Normalization (Z-Score)
All features are normalized to bring them to a common scale:
Normalized_Value = (Value - Mean) / StdDev
This is critically important, as RSI is in the range 0-100, while ATR% and ΔP% have different scales. Without normalization, one feature would dominate over others.
Step 4: K-Means++ Centroid Initialization
Instead of random selection of K initial centers, an improved K-Means++ method is used:
First centroid is randomly selected from the data
Each subsequent centroid is selected with probability proportional to the square of the distance to the nearest already selected centroid
This ensures better initial centroid distribution and faster convergence
Step 5: Iterative Optimization (Lloyd's Algorithm)
Repeat until convergence (or maxIterations):
1. Assignment step:
For each point find the nearest centroid and assign it to this cluster
2. Update step:
Recalculate centroids as the average of all points in each cluster
3. Convergence check:
If centroids shifted less than 0.001 → STOP
Euclidean distance in 3D space is used:
Distance = sqrt((RSI1 - RSI2)² + (ATR1 - ATR2)² + (ΔP1 - ΔP2)²)
Step 6: Adaptive Update
With each new HTF bar:
The oldest bar is removed from history (rolling window method)
New bar is added to history
K-Means algorithm is executed again on updated data
Model remains relevant for current market conditions
Real-Time Classification
After building the model (clusters + centroids), the indicator works in classification mode:
On each closed bar of the current timeframe, RSI, ATR%, ΔP% are calculated
Feature vector is normalized using HTF statistics (Mean/StdDev)
Distance to all K centroids is calculated
Bar is assigned to the cluster with minimum distance
Bar is colored with the corresponding cluster color
Important: Classification occurs only on a closed bar (barstate.isconfirmed), which guarantees no repainting .
Data Architecture
Persistent variables (var):
├── featureVectors - Normalized HTF feature vectors
├── centroids - Cluster center coordinates (K * 3 values)
├── assignments - Assignment of each HTF bar to a cluster
├── htfRsiHistory - History of RSI values from HTF
├── htfAtrHistory - History of ATR values from HTF
├── htfPcHistory - History of price changes from HTF
├── htfCloseHistory - History of close prices from HTF
├── htfRsiMean, htfRsiStd - Statistics for RSI normalization
├── htfAtrMean, htfAtrStd - Statistics for ATR normalization
├── htfPcMean, htfPcStd - Statistics for Price Change normalization
├── isCalculated - Model readiness flag
└── currentCluster - Current active cluster
All arrays are synchronized and updated atomically when a new HTF bar appears.
Computational Complexity
Data collection: O(1) per bar
K-Means (one pass):
- Assignment: O(N * K) where N = number of points, K = number of clusters
- Update: O(N * K)
- Total: O(N * K * I) where I = number of iterations (usually 5-20)
Example: With N=200 HTF bars, K=5 clusters, I=20 iterations:
200 * 5 * 20 = 20,000 operations (executes quickly)
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📖 USER GUIDE
Quick Start
1. Adding the Indicator
TradingView → Indicators → Favorites → MTF K-Means Price Regimes
Or copy the code from mtf_kmeans_price_regimes.pine into Pine Editor.
2. First Launch
When adding the indicator to the chart, you'll see a table in the upper right corner:
┌─────────────────────────┐
│ Status │ Collecting HTF │
├─────────────────────────┤
│ Collected│ 15 / 50 │
└─────────────────────────┘
This means the indicator is accumulating history from the higher timeframe. Wait until the counter reaches the minimum (default 50 bars for K=5).
3. Active Operation
After data collection is complete, the main table with cluster information will appear:
┌────┬──────┬──────┬──────┬──────────────┬────────┐
│ ID │ RSI │ ATR% │ ΔP% │ Description │Current │
├────┼──────┼──────┼──────┼──────────────┼────────┤
│ 1 │ 68.5 │ 2.15 │ 1.2 │ High Vol,Bull│ │
│ 2 │ 52.3 │ 0.85 │ 0.1 │ Low Vol,Flat │ ► │
│ 3 │ 35.2 │ 1.95 │ -1.5 │ High Vol,Bear│ │
└────┴──────┴──────┴──────┴──────────────┴────────┘
The arrow ► indicates the current active regime. Chart bars are colored with the corresponding cluster color.
Customizing for Your Strategy
Choosing Higher Timeframe (HTF)
Rule: HTF should be at least 4 times higher than the working timeframe.
| Working TF | Recommended HTF |
|------------|-----------------|
| 1 min | 15 min - 1H |
| 5 min | 1H - 4H |
| 15 min | 4H - D |
| 1H | D - W |
| 4H | D - W |
| D | W - M |
HTF Selection Effect:
Lower HTF (closer to working TF): More sensitive, frequently changing classification
Higher HTF (much larger than working TF): More stable, long-term regime assessment
Number of Clusters (K)
K = 2-3: Rough division (e.g., "uptrend", "downtrend", "flat")
K = 4-5: Optimal for most cases (DEFAULT: 5)
K = 6-8: Detailed segmentation (requires more data)
K = 9-10: Very fine division (only for long-term analysis with large windows)
Important constraint:
clusterLookback ≥ numClusters * 10
I.e., for K=5 you need at least 50 HTF bars, for K=10 — at least 100 bars.
Clustering Depth (clusterLookback)
This is the rolling window size for building the model.
50-100 HTF bars: Fast adaptation to market changes
200 HTF bars: Optimal balance (DEFAULT)
500-1000 HTF bars: Long-term, stable model
If you get an "Insufficient data" error:
Decrease clusterLookback
Or select a lower HTF (e.g., "4H" instead of "D")
Or decrease numClusters
Color Scheme
Default 10 colors:
Red → Often: strong bearish, high volatility
Orange → Transition, medium volatility
Yellow → Neutral, decreasing activity
Green → Often: strong bullish, high volatility
Blue → Medium bullish, medium volatility
Purple → Oversold, possible reversal
Fuchsia → Overbought, possible reversal
Lime → Strong upward momentum
Aqua → Consolidation, low volatility
White → Undefined regime (rare)
Important: Cluster colors are assigned randomly at each model recalculation! Don't rely on "red = bearish". Instead, look at the description in the table (RSI, ATR%, ΔP%).
You can customize colors in the "Colors" settings section.
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⚙️ INDICATOR PARAMETERS
Main Parameters
Higher Timeframe (htf)
Type: Timeframe selection
Default: "D" (daily)
Description: Timeframe on which the clustering model is built
Recommendation: At least 4 times larger than your working TF
Clustering Depth (clusterLookback)
Type: Integer
Range: 50 - 2000
Default: 200
Description: Number of HTF bars for building the model (rolling window size)
Recommendation:
- Increase for more stable long-term model
- Decrease for fast adaptation or if there's insufficient historical data
Number of Clusters (K) (numClusters)
Type: Integer
Range: 2 - 10
Default: 5
Description: Number of market regimes the algorithm will identify
Recommendation:
- K=3-4 for simple strategies (trending/ranging)
- K=5-6 for universal strategies
- K=7-10 only when clusterLookback ≥ 100*K
Max K-Means Iterations (maxIterations)
Type: Integer
Range: 5 - 50
Default: 20
Description: Maximum number of algorithm iterations
Recommendation:
- 10-20 is sufficient for most cases
- Increase to 30-50 if using K > 7
Feature Parameters
RSI Period (rsiLength)
Type: Integer
Default: 14
Description: Period for RSI calculation (overbought/oversold feature)
Recommendation:
- 14 — standard
- 7-10 — more sensitive
- 20-25 — more smoothed
ATR Period (atrLength)
Type: Integer
Default: 14
Description: Period for ATR calculation (volatility feature)
Recommendation: Usually kept equal to rsiLength
Price Change Period (pcLength)
Type: Integer
Default: 5
Description: Period for percentage price change calculation (trend feature)
Recommendation:
- 3-5 — short-term trend
- 10-20 — medium-term trend
Visualization
Show Info Panel (showDashboard)
Type: Checkbox
Default: true
Description: Enables/disables the information table on the chart
Cluster Color 1-10
Type: Color selection
Description: Customize colors for visual cluster distinction
Recommendation: Use contrasting colors for better readability
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📊 INTERPRETING RESULTS
Reading the Information Table
┌────┬──────┬──────┬──────┬──────────────┬────────┐
│ ID │ RSI │ ATR% │ ΔP% │ Description │Current │
├────┼──────┼──────┼──────┼──────────────┼────────┤
│ 1 │ 68.5 │ 2.15 │ 1.2 │ High Vol,Bull│ │
│ 2 │ 52.3 │ 0.85 │ 0.1 │ Low Vol,Flat │ ► │
│ 3 │ 35.2 │ 1.95 │ -1.5 │ High Vol,Bear│ │
│ 4 │ 45.0 │ 1.20 │ -0.3 │ Low Vol,Bear │ │
│ 5 │ 72.1 │ 3.05 │ 2.8 │ High Vol,Bull│ │
└────┴──────┴──────┴──────┴──────────────┴────────┘
"ID" Column
Cluster number (1-K). Order doesn't matter.
"RSI" Column
Average RSI value in the cluster (0-100):
< 30: Oversold zone
30-45: Bearish sentiment
45-55: Neutral zone
55-70: Bullish sentiment
> 70: Overbought zone
"ATR%" Column
Average volatility in the cluster (as % of price):
< 1%: Low volatility (consolidation, narrow range)
1-2%: Normal volatility
2-3%: Elevated volatility
> 3%: High volatility (strong movements, impulses)
Compared to the average volatility across all clusters to determine "High Vol" or "Low Vol".
"ΔP%" Column
Average price change in the cluster (in % over pcLength period):
> +0.05%: Bullish regime
-0.05% ... +0.05%: Flat (sideways movement)
< -0.05%: Bearish regime
"Description" Column
Automatic interpretation:
"High Vol, Bull" → Strong upward momentum, high activity
"Low Vol, Flat" → Consolidation, narrow range, uncertainty
"High Vol, Bear" → Strong decline, panic, high activity
"Low Vol, Bull" → Slow growth, low activity
"Low Vol, Bear" → Slow decline, low activity
"Current" Column
Arrow ► shows which cluster the last closed bar of your working timeframe is in.
Typical Cluster Patterns
Example 1: Trend/Flat Division (K=3)
Cluster 1: RSI=65, ATR%=2.5, ΔP%=+1.5 → Bullish trend
Cluster 2: RSI=50, ATR%=0.8, ΔP%=0.0 → Flat/Consolidation
Cluster 3: RSI=35, ATR%=2.3, ΔP%=-1.4 → Bearish trend
Strategy: Open positions when regime changes Flat → Trend, avoid flat.
Example 2: Volatility Breakdown (K=5)
Cluster 1: RSI=72, ATR%=3.5, ΔP%=+2.5 → Strong bullish impulse (high risk)
Cluster 2: RSI=60, ATR%=1.5, ΔP%=+0.8 → Moderate bullish (optimal entry point)
Cluster 3: RSI=50, ATR%=0.7, ΔP%=0.0 → Flat
Cluster 4: RSI=40, ATR%=1.4, ΔP%=-0.7 → Moderate bearish
Cluster 5: RSI=28, ATR%=3.2, ΔP%=-2.3 → Strong bearish impulse (panic)
Strategy: Enter in Cluster 2 or 4, avoid extremes (1, 5).
Example 3: Mixed Regimes (K=7+)
With large K, clusters can represent condition combinations:
High RSI + Low volatility → "Quiet overbought"
Neutral RSI + High volatility → "Uncertainty with high activity"
Etc.
Requires individual analysis of each cluster.
Regime Changes
Important signal: Transition from one cluster to another!
Trading situation examples:
Flat → Bullish trend → Buy signal
Bullish trend → Flat → Take profit, close longs
Flat → Bearish trend → Sell signal
Bearish trend → Flat → Close shorts, wait
You can build a trading system based on the current active cluster and transitions between them.
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💡 USAGE EXAMPLES
Example 1: Scalping with HTF Filter
Task: Scalping on 5-minute charts, but only enter in the direction of the daily regime.
Settings:
Working TF: 5 min
HTF: D (daily)
K: 3 (simple division)
clusterLookback: 100
Logic:
IF current cluster = "Bullish" (ΔP% > 0.5)
→ Look for long entry points on 5M
IF current cluster = "Bearish" (ΔP% < -0.5)
→ Look for short entry points on 5M
IF current cluster = "Flat"
→ Don't trade / reduce risk
Example 2: Swing Trading with Volatility Filtering
Task: Swing trading on 4H, enter only in regimes with medium volatility.
Settings:
Working TF: 4H
HTF: D (daily)
K: 5
clusterLookback: 200
Logic:
Allowed clusters for entry:
- ATR% from 1.5% to 2.5% (not too quiet, not too chaotic)
- ΔP% with clear direction (|ΔP%| > 0.5)
Prohibited clusters:
- ATR% > 3% → Too risky (possible gaps, sharp reversals)
- ATR% < 1% → Too quiet (small movements, commissions eat profit)
Example 3: Portfolio Rotation
Task: Managing a portfolio of multiple assets, allocate capital depending on regimes.
Settings:
Working TF: D (daily)
HTF: W (weekly)
K: 4
clusterLookback: 100
Logic:
For each asset in portfolio:
IF regime = "Strong trend + Low volatility"
→ Increase asset weight in portfolio (40-50%)
IF regime = "Medium trend + Medium volatility"
→ Standard weight (20-30%)
IF regime = "Flat" or "High volatility without trend"
→ Minimum weight or exclude (0-10%)
Example 4: Combining with Other Indicators
MTF K-Means as a filter:
Main strategy: MA Crossover
Filter: MTF K-Means on higher TF
Rule:
IF MA_fast > MA_slow AND Cluster = "Bullish regime"
→ LONG
IF MA_fast < MA_slow AND Cluster = "Bearish regime"
→ SHORT
ELSE
→ Don't trade (regime doesn't confirm signal)
This dramatically reduces false signals in unsuitable market conditions.
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📈 OPTIMIZATION RECOMMENDATIONS
Optimal Settings for Different Styles
Day Trading
Working TF: 5M - 15M
HTF: 1H - 4H
numClusters: 4-5
clusterLookback: 100-150
Swing Trading
Working TF: 1H - 4H
HTF: D
numClusters: 5-6
clusterLookback: 150-250
Position Trading
Working TF: D
HTF: W - M
numClusters: 4-5
clusterLookback: 100-200
Scalping
Working TF: 1M - 5M
HTF: 15M - 1H
numClusters: 3-4
clusterLookback: 50-100
Backtesting
To evaluate effectiveness:
Load historical data (minimum 2x clusterLookback HTF bars)
Apply the indicator with your settings
Study cluster change history:
- Do changes coincide with actual trend transitions?
- How often do false signals occur?
Optimize parameters:
- If too much noise → increase HTF or clusterLookback
- If reaction too slow → decrease HTF or increase numClusters
Combining with Other Techniques
Regime-Based Approach:
MTF K-Means (regime identification)
↓
+---+---+---+
| | | |
v v v v
Trend Flat High_Vol Low_Vol
↓ ↓ ↓ ↓
Strategy_A Strategy_B Don't_trade
Examples:
Trend: Use trend-following strategies (MA crossover, Breakout)
Flat: Use mean-reversion strategies (RSI, Bollinger Bands)
High volatility: Reduce position sizes, widen stops
Low volatility: Expect breakout, don't open positions inside range
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📞 SUPPORT
Report an Issue
If you found a bug or have a suggestion for improvement:
Describe the problem in as much detail as possible
Specify your indicator settings
Attach a screenshot (if possible)
Specify the asset and timeframe where the problem is observed
Volume Order Block Scanner [BOSWaves]Volume Order Block Scanner - Dynamic Detection of High-Volume Supply and Demand Zones
Overview
The Volume Order Block Scanner introduces a refined approach to institutional zone mapping, combining volume-weighted order flow, structural displacement, and ATR-based proportionality to identify regions of aggressive participation from large entities.
Unlike static zone mapping or simplistic body-size filters, this framework dynamically evaluates each candle through a multi-layer model of relative volume, candle structure, and volatility context to isolate genuine order block formations while filtering out market noise.
Each identified zone represents a potential institutional footprint, defined by significant volume surges and efficient body-to-ATR relationships that indicate purposeful positioning. Once mapped, each order block is dynamically adjusted for volatility and tracked throughout its lifecycle - from creation to mitigation to potential invalidation - producing an evolving liquidity map that adapts with price.
This adaptive behavior allows traders to visualize where liquidity was absorbed and where it remains unfilled, revealing the structural foundation of institutional intent across timeframes.
Theoretical Foundation
At its core, the Volume Order Block Scanner is built on the interaction between volume displacement and structural imbalance. Traditional order block systems often rely on fixed candle formations or simple engulfing logic, neglecting the fundamental driver of institutional activity: volume concentration relative to volatility.
This framework redefines that approach. Each candle is filtered through two comparative ratios:
Relative Volume Ratio (RVR) - the candle’s volume compared to its rolling average, confirming genuine transactional surges.
Body-ATR Ratio (BAR) - a measure of displacement efficiency relative to recent volatility, ensuring structural strength.
Only when both conditions align is an order block validated, marking a displacement event significant enough to create a lasting imbalance.
By embedding this logic within a volatility-adjusted environment, the system maintains scalability across asset classes and volatility regimes - equally effective in crypto, forex, or index markets.
How It Works
The Volume Order Block Scanner operates through a structured multi-stage process:
Displacement Detection - Identifies candles whose body and volume exceed dynamic thresholds derived from ATR and rolling volume averages. These represent the origin points of institutional aggression.
Zone Construction - Each qualified candle generates an order block with ATR-proportional dimensions to ensure consistency across instruments and timeframes. The zone includes two regions: Body Zone (the precise initiation point of displacement) and Wick Imbalance (the residual inefficiency representing unfilled liquidity).
Lifecycle Tracking - Each zone is continuously monitored for market interaction. Reactions within a defined window are classified as respected, mitigated, or invalidated, giving traders a data-driven sense of ongoing institutional relevance.
Volume Confirmation Layer - Reinforces signal integrity by ensuring that all detected blocks correspond with meaningful increases in transactional activity.
Temporal Decay Control - Zones that remain untested beyond a set period gradually lose visual and analytical weight, maintaining chart clarity and contextual precision.
Interpretation
The Volume Order Block Scanner visualizes how institutional participants interact with the market through zones of accumulation and distribution.
Bullish order blocks denote demand imbalances where price displaced upward under high volume; bearish order blocks signify supply regions formed by concentrated selling pressure.
Price revisiting these areas often reflects institutional re-entry or liquidity rebalancing, offering actionable insights for both continuation and reversal scenarios.
By continuously monitoring interaction and expiry, the framework enables traders to distinguish between active institutional footprints and historical liquidity artifacts.
Strategy Integration
The Volume Order Block Scanner integrates naturally into advanced structural and order-flow methodologies:
Liquidity Mapping : Identify high-volume regions that are likely to influence future price reactions.
Break-of-Structure Confirmation : Validate BOS and CHOCH signals through aligned order block behavior.
Volume Confluence : Combine with BOSWaves volume or momentum indicators to confirm real institutional intent.
Smart-Money Frameworks : Utilize order block retests as precision entry zones within SMC-based setups.
Trend Continuation : Filter zones in line with higher-timeframe bias to maintain directional integrity.
Technical Implementation Details
Core Engine : Dual-filter mechanism using Relative Volume Ratio (RVR) and Body-ATR Ratio (BAR).
Volatility Framework : ATR-based scaling for cross-asset proportionality.
Zone Composition : Body and wick regions plotted independently for visual clarity of imbalance.
Lifecycle Logic : Real-time monitoring of reaction, mitigation, and invalidation states.
Directional Coloring : Distinct bullish and bearish shading with adjustable transparency.
Computation Efficiency : Lightweight structure suitable for multi-timeframe or multi-asset environments.
Optimal Application Parameters
Timeframe Guidance:
5m - 15m : Reactive intraday zones for short-term liquidity engagement.
1H - 4H : Medium-term structures for swing or intraday trend mapping.
Daily - Weekly : Macro accumulation and distribution footprints.
Suggested Configuration:
Relative Volume Threshold : 1.5× - 2.0× average volume.
Body-ATR Threshold : 0.8× - 1.2× for valid displacement.
Zone Expiry : 5 - 10 bars for intraday use, 15 - 30 for swing/macro contexts.
Parameter optimization should be asset-specific, tuned to volatility conditions and liquidity depth.
Performance Characteristics
High Effectiveness:
Markets exhibiting clear displacement and directional flow.
Environments with consistent volume expansion and liquidity inefficiencies.
Reduced Effectiveness:
Range-bound markets with frequent false impulses.
Low-volume sessions lacking institutional participation.
Integration Guidelines
Confluence Framework : Pair with structure-based BOS or liquidity tools for validation.
Risk Management : Treat active order blocks as contextual areas of interest, not guaranteed reversal points.
Multi-Timeframe Logic : Derive bias from higher-timeframe blocks and execute from refined lower-timeframe structures.
Volume Verification : Confirm each reaction with concurrent volume acceleration to avoid false liquidity cues.
Disclaimer
The Volume Order Block Scanner is a quantitative mapping framework designed for professional traders and analysts. It is not a predictive or guaranteed system of profit.
Performance depends on correct configuration, market conditions, and disciplined risk management. BOSWaves recommends using this indicator as part of a comprehensive analytical process - integrating structural, volume, and liquidity context for accurate interpretation.
THAIT Moving Averages Tight within # ATR EMA SMA convergence
THAIT(tight) indicator is a powerful tool for identifying moving average convergence in price action. This indicator plots four user-defined moving averages (EMA or SMA). It highlights moments when the MAs converge within a user specified number of ATRs, adjusted by the 14-period ATR, signaling potential trend shifts or consolidation.
A convergence is flagged when MA1 is the maximum, the spread between MAs is tight, and the price is above MA1, excluding cases where the longest MA (MA4) is the highest. The indicator alerts and visually marks convergence zones with a shaded green background, making it ideal for traders seeking precise entry or exit points.
EdgeBox: MA DistanceEdgeBox: MA Distance adds a clean HUD showing the percentage distance from the current close to your selected moving averages (default: SMA 100/150/200/250). Values are positive when MAs are above price and negative when below. Also includes ATR% (volatility) and RSI(14). Fully customizable: corner position, font sizes, and text/background colors. A fast context panel for trend and volatility at a glance.
ATR Trailing Stop with Entry Date & First-Day MultiplierATR based trailing stop based on a X post of Aksel Kibar.
Smart ATR - Position Sizing for YM Dow JonesSmart ATR includes all basic functionality of ATR + an EMA of ATR. The EMA can give you a baseline or long-term perspective of what ATR normally is. The built-in, automatic sizing tool will display a recommended number of contracts each bar, based upon a multiple of the current ATR. Supports fractional tick values for MYM by clicking the down arrow. Supports fractional ATR values, such as 1.5x. Updates contract sizing on each new bar. This indicator will maintain your RR as volatility increases and decreases. Currently only optimized for YM, will publish other versions if there is an interest.
Market Profile based Support/ResistanceBrought to you by Stock Kaka - Your trading sidekick 🦜📈 - pay your visit at stockkaka.my.canva.site or find us on X #StockKaka
📊 What This Indicator Does
Ever wish the market would just tell you where the important levels are? Well, buckle up, because this indicator is like having a market whisperer on your chart!
Based on cutting-edge hierarchical market structure analysis (fancy words for "smart support and resistance"), this bad boy uses ATR-based Directional Change to identify turning points that actually matter. No more guessing where price might bounce or break—let the algorithm do the heavy lifting while you sip your coffee ☕
🎯 The Five Levels Explained (From Noisy to Mighty)
Think of these levels like a pyramid of importance. Level 0 is your chatty friend who notices everything, while Level 4 is the wise oracle who only speaks when it really matters.
Level 0: The Hyperactive Scout 🐿️
What it does: Catches every little zigzag in price using ATR confirmation
Significance: Very short-term, intraday noise
Best for: Scalpers who love action every few minutes
Trader Type: "I refresh my chart 100 times an hour"
Reliability: ⭐⭐ (It's enthusiastic but easily excitable)
Level 1: The Day Trader's Buddy 🎯
What it does: Filters Level 0 to show minor swing highs/lows
Significance: Intraday support/resistance, hourly structure
Best for: Day traders, scalpers looking for better entries
Trader Type: "I close all positions before dinner"
Reliability: ⭐⭐⭐ (Solid for quick moves)
Level 2: The Swing Trader's Sweet Spot 🎪
What it does: Identifies multi-day to weekly structure points
Significance: Intermediate support/resistance where battles happen
Best for: Swing traders, position traders
Trader Type: "I hold for days, not minutes"
Reliability: ⭐⭐⭐⭐ (Now we're talking real structure!)
Level 3: The Big Money Magnet 💰
What it does: Shows major market structure—where the whales play
Significance: Weekly to monthly levels, institutional zones
Best for: Position traders, trend followers
Trader Type: "I think in weeks and months, not hours"
Reliability: ⭐⭐⭐⭐⭐ (These levels have gravitational pull!)
Level 4: The Market Prophet 🔮
What it does: Reveals ultra-major turning points (think: quarterly/yearly pivots)
Significance: Long-term macro structure, investment-grade levels
Best for: Investors, long-term position traders
Trader Type: "Warren Buffett is my spirit animal"
Reliability: ⭐⭐⭐⭐⭐⭐ (When these break, market's rewrite the story)
⚙️ Parameter Setup Guide (The Secret Sauce)
The magic ingredient is the ATR Lookback Period—think of it as teaching the indicator your timeframe's "dialect." Here's your cheat sheet:
2-Minute Chart ⚡
ATR Lookback: 720 (24 hours of 2-min bars)
Who uses this: Crypto degens, futures scalpers, adrenaline junkies
Show Levels: L0, L1, L2 (L3+ won't budge much)
Pro Tip: Enable only L1 and L2 or your chart will look like spaghetti
5-Minute Chart 🏃
ATR Lookback: 288 (24 hours of 5-min bars)
Who uses this: Active day traders, news traders
Show Levels: L1, L2, L3
Pro Tip: L2 is your best friend here—perfect for intraday swings
15-Minute Chart 📈
ATR Lookback: 96 (24 hours of 15-min bars)
Who uses this: Swing traders, patient day traders
Show Levels: L1, L2, L3
Pro Tip: This is the "Goldilocks zone"—not too fast, not too slow
1-Hour Chart ⏰
ATR Lookback: 168 (1 week of hourly bars)
Who uses this: Swing traders, position traders
Show Levels: L2, L3, L4
Pro Tip: L3 levels here are like magnets for price action
Daily Chart 📅
ATR Lookback: 30 to 50 (1-2 months)
Who uses this: Investors, long-term traders, people with patience
Show Levels: L2, L3, L4
Pro Tip: L4 on dailies = "Don't fight this level, respect it"
🎨 How to Use This Thing
Add to Chart - Duh! 😄
Set Your ATR Lookback - Use the guide above (don't wing it!)
Enable Relevant Levels - Less is more! Turn off levels that just clutter
Watch the Magic - See horizontal lines appear at key S/R zones
Check the Table - Top-right corner shows current levels (fancy!)
Set Alerts - Get notified when price approaches or breaks levels
Trading Strategies 🎲
The Bounce Play:
Price approaches Level 2 or 3 support → Look for bullish reversal signals
Take profit at the next level resistance
Stop loss just below the support level
The Breakout Play:
Price breaks through Level 2/3 resistance with volume → Go long
Next level becomes your target
Failed breakout? Level becomes resistance again (classic fake-out)
The Confluence Play:
When Level 3 aligns with your favorite indicator (RSI oversold, moving average, Fibonacci) → Chef's kiss! 👨🍳💋
These multi-confirmation setups are where the money lives
🚨 Important Notes (Read This or Blame Yourself Later)
⚠️ This indicator REPAINTS on the current bar until an extreme is confirmed. That's not a bug, it's how directional change works. The past levels are solid as a rock, but the pending one is still... pending.
⚠️ More levels ≠ Better results. Showing all 5 levels is like having 5 GPS apps shouting directions at once. Pick 2-3 levels max.
⚠️ ATR Lookback matters! Wrong setting = garbage results. Use the guide above or experiment carefully.
⚠️ Volatile markets (crypto, meme stocks) work GREAT with this. Choppy, range-bound markets? Meh.
⚠️ Combine with other tools! This shows you WHERE, not WHEN. Use momentum indicators, volume, or your favorite chicken entrails for timing 🐔
🦜 Final Word from Stock Kaka
Remember: Indicators don't make money, traders do. This tool shows you where the market has historically respected structure. What you do with that info? That's on you, champ!
Use proper risk management, don't YOLO your rent money, and may your stops never get hunted 🎯
Trade smart, trade safe, and let Stock Kaka be your guide!
📝 Credits
Algorithm: neurotrader888 (Python implementation)
Pine Script Conversion: Your friendly neighborhood Stock Kaka team!!
Inspiration: Ginger chai, market inefficiencies, and a dash of chaos
📌 Tags
support-and-resistance market-structure atr directional-change multi-timeframe swing-trading day-trading levels hierarchical-analysis algo-trading
DTR & ATR with live zonesThis indicator is designed to help traders gauge the day's volatility in real-time. It compares the current Daily True Range (DTR)—the distance between the session's high and low—to the historical Average True Range (ATR).
The main purpose is to project potential price levels where the market might reach based on its average volatility. These levels (100% ATR, 150%, 200%, etc.) can be used as price targets. For instance, if you're in a long trade, you might consider taking partial or full profits as the price approaches these upper ATR extension levels. The indicator is highly customisable, allowing you to control the appearance of the ATR lines, zones, and labels to fit your charting preferences.
Core Concepts: ATR and DTR
To use this indicator effectively, it's important to understand its two main components:
Average True Range (ATR): This is a classic technical analysis indicator that measures market volatility. It calculates the average range of price movement over a specific period (e.g., 14 days). A higher ATR means the price is, on average, moving more, while a low ATR indicates less volatility. This script uses a higher timeframe ATR (e.g., Daily) to establish a stable volatility baseline for the current trading day.
Daily True Range (DTR): This is simply the difference between the current trading session's highest high and lowest low (session high - session low). It tells you how much the price has actually moved so far today.
The indicator's logic revolves around comparing the live, unfolding DTR to the historical, baseline ATR. An on-screen table conveniently shows this comparison as a percentage, to show how volatile the day has been.
How It Works: The Dynamic & Locked Mechanism
The most clever part of this indicator is how it draws the ATR levels. It operates in two distinct phases during the trading session:
Phase 1: Dynamic Expansion (Before DTR meets ATR)
At the start of the session, the DTR is small. The indicator calculates the remaining range needed to "complete" the 100% ATR level (difference = avg_atr - dtr). It then adds this remaining amount to the session high and subtracts it from the session low. This creates a "floating" 100% ATR range that expands dynamically as the session high or low is extended.
Phase 2: The Lock-in (After DTR meets or exceeds ATR)
Once the day's range (DTR) becomes equal to or greater than the avg_atr, the day has met its "expected" volatility. At this point, the levels lock in place. The indicator intelligently determines the anchor point for the locked range.
Once this primary 100% ATR range is established (either dynamically or locked), the script projects the other levels (150%, 200%, 250%, and 300%) by adding or subtracting multiples of the avg_atr from this base.
How to Use It for Trading
The primary use of this indicator is to set logical, volatility-based price targets.
Setting Profit Targets: If you enter a long position, the upper ATR levels (100%, 150%, 200%) serve as excellent areas to consider taking profits. A move to the 200% or 250% level often signifies an overextended or "exhaustion" move, making it a high-probability exit zone. For short positions, the lower ATR levels serve the same purpose.
Assessing Intraday Momentum: The on-screen table tells you how much of the expected daily range has been used. If it's early in the session and the DTR is only at 30% of the ATR, you can anticipate more significant price movement is likely to come. Conversely, if the DTR is already at 150% of ATR, the bulk of the day's move may already be complete.
Mean Reversion Signals: If the price pushes to an extreme level (e.g., 250% ATR) and shows signs of stalling (e.g., bearish divergence on an oscillator), it could signal a potential reversal or pullback, offering an opportunity for a counter-trend trade.
Key Settings
ATR Length & Smoothing Type: These settings control how the baseline ATR is calculated. The default 14 period and RMA smoothing are standard, but you can adjust them to your preference.
Session Settings: This is crucial. You must set the Market Session and Time Zone to match the primary trading hours of the asset you are analysing (e.g., "0930-1600" for the NYSE session).
Show Lines / Show Labels / Show Zones: The script gives you full control over the visual display. You can toggle each ATR level's lines, labels, and background zones individually to avoid a cluttered chart and focus only on the levels that matter to your strategy.
Renko BandsThis is renko without the candles, just the endpoint plotted as a line with bands around it that represent the brick size. The idea came from thinking about what renko actually gives you once you strip away the visual brick format. At its core, renko is a filtered price series that only updates when price moves a fixed amount, which means it's inherently a trend-following mechanism with built-in noise reduction. By plotting just the renko price level and surrounding it with bands at the brick threshold distances, you get something that works like regular volatility bands while still behaving as a trend indicator.
The center line is the current renko price, which trails actual price based on whichever brick sizing method you've selected. When price moves enough to complete a brick in the renko calculation, the center line jumps to the new brick level. The bands sit at plus and minus one brick size from that center line, showing you exactly how far price needs to move before the next brick would form. This makes the bands function as dynamic breakout levels. When price touches or crosses a band, you know a new renko brick is forming and the trend calculation is updating.
What makes this cool is the dual-purpose nature. You can use it like traditional volatility bands where the outer edges represent boundaries of normal price movement, and breaks beyond those boundaries signal potential trend continuation or exhaustion. But because the underlying calculation is renko rather than standard deviation or ATR around a moving average, the bands also give you direct insight into trend state. When the center line is rising consistently and price stays near the upper band, you're in a clean uptrend. When it's falling and price hugs the lower band, downtrend. When the center line is flat and price is bouncing between both bands, you're ranging.
The three brick sizing methods work the same way as standard renko implementations. Traditional sizing uses a fixed price range, so your bands are always the same absolute distance from the center line. ATR-based sizing calculates brick range from historical volatility, which makes the bands expand and contract based on the ATR measurement you chose at startup. Percentage-based sizing scales the brick size with price level, so the bands naturally widen as price increases and narrow as it decreases. This automatic scaling is particularly useful for instruments that move proportionally rather than in fixed increments.
The visual simplicity compared to full renko bricks makes this more practical for overlay use on your main chart. Instead of trying to read brick patterns in a separate pane or cluttering your price chart with boxes and lines, you get a single smoothed line with two bands that convey the same information about trend state and momentum. The center line shows you the filtered trend direction, the bands show you the threshold levels, and the relationship between price and the bands tells you whether the current move has legs or is stalling out.
From a trend-following perspective, the renko line naturally stays flat during consolidation and only moves when directional momentum is strong enough to complete bricks. This built-in filter removes a lot of the whipsaw that affects moving averages during choppy periods. Traditional moving averages continue updating with every bar regardless of whether meaningful directional movement is happening, which leads to false signals when price is just oscillating. The renko line only responds to sustained moves that meet the brick size threshold, so it tends to stay quiet when price is going nowhere and only signals when something is actually happening.
The bands also serve as natural stop-loss or profit-target references since they represent the distance price needs to move before the trend calculation changes. If you're long and the renko line is rising, you might place stops below the lower band on the theory that if price falls far enough to reverse the renko trend, your thesis is probably invalidated. Conversely, the upper band can mark levels where you'd expect the current brick to complete and potentially see some consolidation or pullback before the next brick forms.
What this really highlights is that renko's value isn't just in the brick visualization, it's in the underlying filtering mechanism. By extracting that mechanism and presenting it in a more traditional band format, you get access to renko's trend-following properties without needing to commit to the brick chart aesthetic or deal with the complications of overlaying brick drawings on a time-based chart. It's renko after all, so you get the trend filtering and directional clarity that makes renko useful, but packaged in a way that integrates more naturally with standard technical analysis workflows.
Average True Range Stop Loss Finder with KAMAATR SL finder with bands
Kaufmann adaptive moving average
ATR SL finder with bands
Kaufmann adaptive moving average
ATR %ATR % Oscillator
A simple and effective Average True Range (ATR) indicator displayed as a percentage of the current price in a separate panel.
FEATURES:
• ATR displayed as percentage of current price for easy cross-asset comparison
• EMA smoothing line using the same period as ATR
• Configurable ATR period (default: 20)
• Clean visualization with zero reference line
HOW IT WORKS:
The indicator calculates ATR and converts it to a percentage: (ATR / Close) × 100
This normalization allows you to:
- Compare volatility across different instruments regardless of price
- Identify high and low volatility periods
- Use the EMA line to spot volatility trends
PARAMETERS:
ATR Period - The lookback period for ATR calculation (default: 20)
Timeframe - Choose any timeframe for ATR calculation independently from the chart timeframe (default: chart timeframe)
Axel Smart TrendAxel Smart Trend is a dynamic system for identifying and tracking market trends.
It combines ATR-based volatility analysis, EMA smoothing, and Fibonacci-anchored zones to show current trend direction and potential reversal areas.
Axel Smart Trend is a dynamic system for identifying and tracking market trends.
It combines ATR-based volatility analysis, EMA smoothing, and Fibonacci-anchored zones to display current trend direction and key reaction areas.
The indicator adapts to changing market volatility, automatically switching between bullish and bearish phases.
Colored clouds visualize the active trend and act as dynamic support and resistance zones during trend continuation.
Cross markers on the chart highlight moments when the price approaches important cloud levels. These crosses are not buy or sell signals, but rather a visual indication that the market has entered a zone of increased interest.
Main parameters:
The ATR period and multiplier define the sensitivity to volatility.
The EMA length controls the depth of trend smoothing.
Signal strength and cooldown settings adjust the precision and frequency of the markers.
Practical use:
Green crosses tend to appear near potential support areas, while red crosses form near resistance or overbought zones.
The clouds help assess trend strength and possible pullback levels.
Best suited for daily and weekly charts.
Disclaimer:
This indicator is intended for analytical and educational purposes only.
It does not provide financial advice or trading recommendations, and past performance does not guarantee future results.
Axel ATR FlowAxel ATR Flow is a dynamic, volatility-adaptive channel designed to visualize the natural rhythm of market movement.
The indicator builds its structure around the Average True Range (ATR) and a smooth central line — called the Flow — which acts as a flexible base.
As volatility increases, the channel expands; when the market calms down, it contracts.
This creates an adaptive envelope that helps traders see where price is likely to find balance, support, or exhaustion.
Unlike traditional static channels, Axel ATR Flow features real-time interpolation between closed and live data within the same higher-timeframe candle.
This means that even intraday, the indicator smoothly follows actual market movement, offering a realistic view of active volatility.
How it works
The system builds five key elements:
Central Flow Line — the main trend reference.
Main Trail — the primary volatility boundary and near-support zone.
Lower Trail — a deeper overshoot zone, often forming major accumulation areas.
An Upper Trail — the first resistance boundary.
An Upper2 Trail — the extreme resistance level, marking potential exhaustion.
The indicator adapts these levels dynamically using ATR calculations and smoothing filters (SMA or ZLEMA).
It can be locked to specific higher timeframes (Daily, Weekly, Monthly, 2D, 3D) while still reacting smoothly to current intraday price movement.
How to use it
• Trend direction:
The slope of the Flow Line represents the active trend.
When it’s rising, market flow is bullish; when falling, bearish pressure dominates.
• Support and resistance:
The Main and Lower Trails act as dynamic supports where price often bounces in an uptrend.
The Upper and Upper2 Trails mark zones where rallies typically slow down or reverse.
• Entries and exits:
— Buy setups often appear when price approaches or slightly dips below the Main or Lower Trail during an uptrend.
— Take-profit zones align with touches of the Upper or Upper2 Trails.
— In sideways markets, repeated touches at both extremes often precede breakout volatility.
• Volatility signals:
A wide channel means strong volatility — wait for stabilization or use smaller position sizes.
A narrow channel shows contraction — conditions are favorable for continuation trades after breakout.
Practical tips
• Combine Axel ATR Flow with oscillators such as RSI or Stoch RSI to confirm overbought or oversold conditions near outer bands.
• On higher timeframes, the indicator reveals the breathing pattern of the market — periods of compression followed by expansion.
• For spot trading or DCA strategies, entries near the Lower Trail during strong trends often provide excellent accumulation opportunities.
• Works effectively across markets: crypto, forex, indices, and commodities.
Summary
Axel ATR Flow unites precise volatility analysis with smooth visual representation of market structure.
It can be used as both a trend filter and an execution framework, identifying where price flow tends to stabilize or exhaust.
Part of the Axel Alts system, this indicator was engineered for traders who value clarity, adaptability, and realism in market analysis.
Squeeze Breakout Strategy [KedArc Quant]Description:
Squeeze Breakout strategy looks for volatility compression (Bollinger Bands inside Keltner Channels = a “squeeze”), then trades the volatility expansion in the direction of a momentum filter.
🧠 How the “Squeeze → Expansion” works
- Markets alternate between quiet (compressed) and active (expanded) phases.
- We call it a squeeze when Bollinger Bands (BB)—which reflect standard deviation around price—shrink inside the Keltner Channels (KC)—which reflect ATR/range.
- This means dispersion (stdev) is small relative to typical range (ATR). Price is coiling; participants are agreeing on value.
- When BB pops back outside KC, the squeeze releases. That’s the first sign that volatility is expanding again.
- A release alone doesn’t tell you direction. That’s why this strategy pairs the release with a momentum filter:
- We estimate momentum using a smoothed linear-regression slope of price (a clean proxy for acceleration).
- If the slope is positive at release, we favor longs; if negative, we favor shorts.
- Optionally, you can require Band Break + Momentum (price closes beyond the BB) for a stricter entry.
- This combination aims to capture the first leg of the range-to-trend transition while avoiding random pokes that often occur during tight consolidations.
💡 Why this is unique
Two entry modes (toggle):
1. Release + Momentum (enter when the squeeze turns off)
2. Band Break + Momentum (enter on a close beyond BB with momentum)
- Momentum = smoothed linear-regression slope, a clean thrust detector that’s less laggy than many oscillators.
- Risk module included: ATR stop, optional 1R partial take-profit, and a Chandelier trailing stop for the runner.
- Practical filters: higher-timeframe EMA trend alignment, volume surge, minimum BB width, and session window—so it adapts across markets/timeframes.
- Backtest-ready: uses TradingView’s `strategy.` framework with commission/slippage controls.
📈 How it helps traders
✅Regime clarity: distinguishes compression vs. expansion so you’re not forcing trades during dead zones.
✅Objective entries: momentum + band logic reduces discretionary “feel” and late chases.
✅Built-in risk plan: stop/targets/trailing defined in inputs—consistent execution across tickers.
✅Adaptable: works across instruments/timeframes; filters let you tailor noise tolerance per market session.
✅Alerts: real-time signals for entry and squeeze release.
✅Not a Mash-Up / Original Work
✅Fully authored in Pine Script v6; no external libraries or copied logic blocks.
✅Uses well-known, documented formulas (BB, KC, ATR, LinReg slope) combined into a new rule set (two entry modes + momentum + structured exits).
✅Code and parameters are transparent and adjustable; the script stands alone.
🧩 Formulas (core)
Bollinger Bands
# Basis = `SMA(close, bbLen)`
# Upper/Lower = `Basis ± bbMult × stdev(close, bbLen)`
# Width% = `(Upper − Lower) / Basis × 100`
Keltner Channels
# Basis = `EMA(close, kcLen)`
# Upper/Lower = `Basis ± kcMult × ATR(kcATR)`
Squeeze state
# ON: `BB_Upper < KC_Upper` and `BB_Lower > KC_Lower`
# Release: `squeeze_on ` and `not squeeze_on`
Momentum (this script)
# `lin = linreg(close, momLen, 0)`
# `mom = SMA( lin − lin , momSmoothing )`
# Long bias when `mom > 0`; short bias when `mom < 0`.
⚙️ Inputs
Compression
`bbLen`, `bbMult` — BB length & std-dev multiplier
`kcLen`, `kcATR`, `kcMult` — KC lengths & ATR multiplier
`Entry Mode` — Release + Momentum, Band Break + Momentum, or Either
Momentum
`momLen`, `momSmoothing`
Filters (optional)
`Use HTF Trend Filter` + `HTF Timeframe` + `HTF EMA Length`
`Require Volume Surge` (`volLen`, `volMult`)
`Avoid Ultra-Low Vol` (`Min BB Width %`)
`Session` window
Risk / Exits
`ATR Length`, `ATR Stop Multiplier`
`Take Profit at 1R` (with Partial 50%)
`Chandelier` (`chLen`, `chMult`)
Optional `Time Stop (bars)`
🎯 Entry & Exit Rules
Entry (choose one mode):
1. Release + Momentum (default)
Long: on the bar the squeeze releases and `mom > 0`, passing all enabled filters.
Short: on the bar the squeeze releases and `mom < 0`, passing filters.
2. Band Break + Momentum
Long: `close > BB_Upper` and `mom > 0`, with filters.
Short: `close < BB_Lower` and `mom < 0`, with filters.
Initial Stop
ATR-based: `Stop Distance = atrMult × ATR(atrLen)` from entry.
Targets & Runner
TP1 at 1R (optional): take 50% at `entry + 1R` (long) / `entry − 1R` (short).
Runner: remaining position trails a Chandelier stop:
Long trail = `highest(high, chLen) − chMult × ATR`
Short trail = `lowest(low, chLen) + chMult × ATR`
Optional Time Stop: close the trade after N bars in position.
Labels on chart
“Long” / “Short” = entry signals.
“L-TP1 / S-TP1” = partial exits at 1R.
“L-Runner / S-Runner” = trailing-stop exits of the runner.
Alerts
Provided for Long Entry, Short Entry, and Squeeze Release.
💬 How to use
1. Choose your market/timeframe (e.g., NSE 5–15m intraday, 60m–Daily for swing).
2. If you prefer cleaner trends, enable the HTF EMA filter (e.g., 240m/1D).
3. For intraday, consider Band Break + Momentum with Volume Surge and a small Min BB Width.
4. Adjust ATR/Chandelier multipliers to fit your risk tolerance and instrument.
Abbreviations
BB – Bollinger Bands
KC – Keltner Channels
ATR – Average True Range
SMA / EMA – Simple/Exponential Moving Average
HTF – Higher Timeframe
R – Risk unit (equal to the initial stop distance)
⚠️ Disclaimer
This script is for educational purposes only. Past performance ≠ future returns. Always paper trade first. Options trading carries high risk — manage exposure responsibly.
Hyper SAR Reactor Trend StrategyHyperSAR Reactor Adaptive PSAR Strategy
Summary
Adaptive Parabolic SAR strategy for liquid stocks, ETFs, futures, and crypto across intraday to daily timeframes. It acts only when an adaptive trail flips and confirmation gates agree. Originality comes from a logistic boost of the SAR acceleration using drift versus ATR, plus ATR hysteresis, inertia on the trail, and a bear-only gate for shorts. Add to a clean chart and run on bar close for conservative alerts.
Scope and intent
• Markets: large cap equities and ETFs, index futures, major FX, liquid crypto
• Timeframes: one minute to daily
• Default demo: BTC on 60 minute
• Purpose: faster yet calmer PSAR that resists chop and improves short discipline
• Limits: this is a strategy that places simulated orders on standard candles
Originality and usefulness
• Novel fusion: PSAR AF is boosted by a logistic function of normalized drift, trail is monotone with inertia, entries use ATR buffers and optional cooldown, shorts are allowed only in a bear bias
• Addresses false flips in low volatility and weak downtrends
• All controls are exposed in Inputs for testability
• Yardstick: ATR normalizes drift so settings port across symbols
• Open source. No links. No solicitation
Method overview
Components
• Adaptive AF: base step plus boost factor times logistic strength
• Trail inertia: one sided blend that keeps the SAR monotone
• Flip hysteresis: price must clear SAR by a buffer times ATR
• Volatility gate: ATR over its mean must exceed a ratio
• Bear bias for shorts: price below EMA of length 91 with negative slope window 54
• Cooldown bars optional after any entry
• Visual SAR smoothing is cosmetic and does not drive orders
Fusion rule
Entry requires the internal flip plus all enabled gates. No weighted scores.
Signal rule
• Long when trend flips up and close is above SAR plus buffer times ATR and gates pass
• Short when trend flips down and close is below SAR minus buffer times ATR and gates pass
• Exit uses SAR as stop and optional ATR take profit per side
Inputs with guidance
Reactor Engine
• Start AF 0.02. Lower slows new trends. Higher reacts quicker
• Max AF 1. Typical 0.2 to 1. Caps acceleration
• Base step 0.04. Typical 0.01 to 0.08. Raises speed in trends
• Strength window 18. Typical 10 to 40. Drift estimation window
• ATR length 16. Typical 10 to 30. Volatility unit
• Strength gain 4.5. Typical 2 to 6. Steepness of logistic
• Strength center 0.45. Typical 0.3 to 0.8. Midpoint of logistic
• Boost factor 0.03. Typical 0.01 to 0.08. Adds to step when strength rises
• AF smoothing 0.50. Typical 0.2 to 0.7. Adds inertia to AF growth
• Trail smoothing 0.35. Typical 0.15 to 0.45. Adds inertia to the trail
• Allow Long, Allow Short toggles
Trade Filters
• Flip confirm buffer ATR 0.50. Typical 0.2 to 0.8. Raise to cut flips
• Cooldown bars after entry 0. Typical 0 to 8. Blocks re entry for N bars
• Vol gate length 30 and Vol gate ratio 1. Raise ratio to trade only in active regimes
• Gate shorts by bear regime ON. Bear bias window 54 and Bias MA length 91 tune strictness
Risk
• TP long ATR 1.0. Set to zero to disable
• TP short ATR 0.0. Set to 0.8 to 1.2 for quicker shorts
Usage recipes
Intraday trend focus
Confirm buffer 0.35 to 0.5. Cooldown 2 to 4. Vol gate ratio 1.1. Shorts gated by bear regime.
Intraday mean reversion focus
Confirm buffer 0.6 to 0.8. Cooldown 4 to 6. Lower boost factor. Leave shorts gated.
Swing continuation
Strength window 24 to 34. ATR length 20 to 30. Confirm buffer 0.4 to 0.6. Use daily or four hour charts.
Properties visible in this publication
Initial capital 10000. Base currency USD. Order size Percent of equity 3. Pyramiding 0. Commission 0.05 percent. Slippage 5 ticks. Process orders on close OFF. Bar magnifier OFF. Recalculate after order filled OFF. Calc on every tick OFF. No security calls.
Realism and responsible publication
No performance claims. Past results never guarantee future outcomes. Shapes can move while a bar forms and settle on close. Strategies execute only on standard candles.
Honest limitations and failure modes
High impact events and thin books can void assumptions. Gap heavy symbols may prefer longer ATR. Very quiet regimes can reduce contrast and invite false flips.
Open source reuse and credits
Public domain building blocks used: PSAR concept and ATR. Implementation and fusion are original. No borrowed code from other authors.
Strategy notice
Orders are simulated on standard candles. No lookahead.
Entries and exits
Long: flip up plus ATR buffer and all gates true
Short: flip down plus ATR buffer and gates true with bear bias when enabled
Exit: SAR stop per side, optional ATR take profit, optional cooldown after entry
Tie handling: stop first if both stop and target could fill in one bar
VWAP Entry Assistant (v1.0)Description:
Anchored VWAP with a lightweight assistant for VWAP reversion trades.
It shows the distance to VWAP, an estimated hit probability for the current bar, the expected number of bars to reach VWAP, and a recommended entry price.
If the chance of touching VWAP is low, the script suggests an adjusted limit using a fraction of ATR.
The VWAP line is white by default, and a compact summary table appears at the bottom-left.
Educational tool. Not financial advice. Not affiliated with TradingView or any exchange. Always backtest before use.
Buy The F*cking Dip [DotGain]How to Interpret the "Buy The F*cking Dip" (BTFD) Indicator
Main Purpose and Timeframe
The BTFD indicator is a confluence indicator designed to identify rare moments of extreme capitulation and panic in the market. As the name suggests, its primary focus is identifying significant buying opportunities ("Dips") on high timeframes.
Recommended Timeframes: Minimum Daily chart, ideally Weekly chart.
Primary Signal: The green "Buy" triangle is the default signal to watch for.
The Buy Signal (Green Triangle)
A green "Buy" triangle appears only when all three of the following conditions are met simultaneously. It signals not just a minor pullback, but a potentially macro-level oversold condition.
High Panic (CM Williams Vix Fix): The market is in a state of heightened volatility or "fear." This indicates that sellers are acting out of panic.
Structurally Oversold (Deviation from MA): The price has deviated extremely far (default: >10%) below its long-term moving average (default: 200-period EMA). This signals that the price is "cheap" in the big picture.
Short-Term Overextended (TRMAD): The price has fallen extremely hard and fast relative to its recent volatility (ATR) (default: < -3.0). This signals "maximum pain" on a short-term level.
In summary, a green triangle means: The market is panicky, structurally undervalued, and extremely oversold short-term. These are often the moments when long-term bottoms are formed.
The Sell Signal (Red Triangle)
The indicator can also identify the exact opposite: moments of extreme euphoria or "blow-off tops."
Disabled by Default: The red "Sell" triangle is disabled by default in the settings (display=display.none), as the indicator's focus is on buying.
Meaning (if enabled): It signals that the market (1) has high volatility, (2) is structurally overbought (far above its 200 MA), and (3) is extremely overextended (euphoric) on a short-term basis.
Visual Adjustments (In the "Style" Tab)
By default, only the green "Buy" triangle is active. You can, however, enable other visuals in the indicator's "Style" settings tab:
Buy (Green Triangle): On by default.
Sell (Red Triangle): Off by default.
Signal Bar Color: Colors the candle green/red. Off by default.
Signal Background: Shows a transparent green/red background. Off by default.
Have fun :)
Disclaimer
This "Buy The F*cking Dip" (BTFD) indicator is provided for informational and educational purposes only. It does not, and should not be construed as, financial, investment, or trading advice.
The signals generated by this tool (both "Buy" and "Sell") are the result of a specific set of algorithmic conditions. They are not a direct recommendation to buy or sell any asset. All trading and investing in financial markets involves substantial risk of loss. You can lose all of your invested capital.
Past performance is not indicative of future results. The signals generated may produce false or losing trades. The creator (© DotGain) assumes no liability for any financial losses or damages you may incur as a result of using this indicator.
You are solely responsible for your own trading and investment decisions. Always conduct your own research (DYOR) and consider your personal risk tolerance before making any trades.
