Liquidity Trend Heatmap [BigBeluga]🔵 OVERVIEW
The Liquidity Trend Heatmap is a professional-grade volume analysis tool that maps market liquidity directly onto your price chart. By combining a trend-following baseline with a high-resolution volume-at-price heatmap, it helps traders instantly visualize where the market's "heavy" trading zones are located relative to the current trend.
🔵 FEATURES
The indicator utilizes a sophisticated volume-distribution engine to provide actionable market intelligence:
1 — Dynamic Liquidity Heatmap
Multi-Node Distribution: The indicator divides the recent price range into a 26-level grid, calculating the cumulative volume traded at each level over your defined Lookback Period .
Visual Heatmap Nodes: Liquidity is displayed as shapes (Squares, Circles, etc.) that shift color and intensity based on the volume processed at that price.
Normalized Intensity: Nodes appear more vivid based on their volume relative to the Point of Control (POC), ensuring you only focus on the most significant liquidity zones.
2 — Institutional Point of Control (POC) Tracker
Automated POC Detection: The system identifies the specific price level with the highest volume accumulation, marking it as the market’s primary liquidity magnet.
Real-Time Metrics: A dedicated POC label on the far right of your chart provides the exact price and volume traded at the POC, keeping your focus on the most critical level.
3 — Trend-Following Dashboard
Trend Baseline: Includes a customizable moving average ( Trend Length ) that acts as a structural midline. This midline automatically updates color to indicate whether the current environment is Bullish or Bearish.
Information Dashboard: A clean, configurable table at the top-right provides instant updates on the current trend status, POC price, and total POC volume without cluttering your workspace.
🔵 HOW TO USE
This tool is designed to identify "smart money" zones and potential mean-reversion levels:
Identify Liquidity Magnets: Use the POC level as a primary target or support/resistance level. High-volume nodes often act as magnets for price action.
Confirm Trend: Use the Trend Line and dashboard status to ensure your liquidity-based trades are aligned with the prevailing market trend.
Filter Weak Levels: Adjust the Heatmap Threshold % to hide low-volume levels. This cleans up your chart and leaves only the most relevant, high-conviction liquidity zones visible.
🔵 NOTES
Why this implementation is unique:
It combines complex volume-profile math with a lightweight, user-friendly visual interface, making it suitable for both scalpers and swing traders.
The "future-extending" heatmap nodes visualize expected liquidity distribution into the immediate future, helping you anticipate price behavior before it happens.
The system is highly customizable, allowing you to toggle the trend line, adjust shape types, and change heatmap thresholds to suit your specific trading style.
Indicator
Liquidity Levels, Sweeps & Grabs | Falcon AIPrice is constantly hunting liquidity — the pools of stop orders that sit just beyond obvious highs and lows. This free tool draws the four levels where that liquidity rests, then flags the exact bar each one gets taken, so you see stop-runs as they happen instead of after the move.
THE LEVELS IT DRAWS
• Previous Day High / Low (PDH / PDL)
• Previous Week High / Low (PWH / PWL)
Calculated from the last COMPLETED day and week and fixed for the whole period — non-repainting.
TWO WAYS LIQUIDITY GETS TAKEN — FLAGGED SEPARATELY
• Sweep (triangle) — a multi-candle event. Price runs beyond a level, can hover or consolidate there, then closes back through it. The classic stop-run that often front-runs a reversal.
• Grab (diamond) — a single-candle event. One candle wicks sharply beyond the level and closes back inside with a small body (a doji-like rejection). A fast, one-bar liquidity raid.
The two are mutually exclusive per level: a slow multi-candle reversal reads as a sweep; a one-bar wick rejection reads as a grab.
ALERTS
Four ready-to-use alerts — high sweep, low sweep, high grab, low grab — so you're pinged the moment buy-side or sell-side liquidity is taken.
INPUTS
• Toggle each level set (day / week) and each signal type (sweeps / grabs)
• Grab sensitivity via a wick-to-body ratio (higher = stricter / more doji-like)
• Line style, colors, price labels
HOW TRADERS USE IT
Sweeping and grabbing liquidity is a core Smart-Money / ICT idea: price is pushed beyond a well-watched level to fill orders and trigger stops before reversing. Watching for a sweep or grab of PDH/PDL or PWH/PWL — especially into a higher-timeframe level or a session open — can help spot exhaustion and potential turning points. This tool marks those moments objectively; how you act on them is your call.
Educational tool — not financial advice. Past behavior does not guarantee future results. Indicator
Liquidity Sweep & Stop-Hunt Signals [ForexCracked]🔵 OVERVIEW
Liquidity Sweep & Stop-Hunt Signals marks the price levels where stop orders pile up, detects the moment price runs those stops and reverses, and prints a BUY or SELL with a ready-made entry, stop and target. It is a focused reversal tool built around one of the most reliable behaviours in the market: the failed breakout.
Every signal confirms on candle close, so nothing repaints after the bar is done. A live dashboard shows the higher-timeframe bias, the last signal, and the current trade plan.
🔵 WHAT A LIQUIDITY SWEEP ACTUALLY IS
Stops cluster in obvious places: just above a recent swing high (buy-side liquidity) and just below a recent swing low (sell-side liquidity). Price is often drawn to those pools because that is where resting orders sit.
A sweep, or stop hunt, happens when price spikes through one of those swings, triggers the stops, and then closes back inside the range on the same candle. Breakout traders get trapped, and the reversal that follows is the trade this tool is built to catch.
🔵 HOW IT FINDS SIGNALS
• It tracks recent swing highs and lows as liquidity lines and keeps them on the chart until they are taken
• A SELL fires when a candle's high runs above a tracked swing high but its close falls back below it (buy-side liquidity swept, then rejected)
• A BUY fires when a candle's low runs below a tracked swing low but its close climbs back above it (sell-side liquidity swept, then rejected)
• An optional rejection-body filter ignores weak wicks and only accepts sweeps that close with a real body back inside the level
• An optional higher-timeframe EMA bias lets you take only trend-aligned sweeps, only counter-trend sweeps, or all of them
🔵 THE TRADE PLAN IT DRAWS
On every signal the tool draws three lines and labels them:
• Entry at the close of the sweep candle
• Stop just beyond the swept wick, with an ATR buffer so normal noise does not clip it
• Target at your chosen reward-to-risk multiple of that stop distance
You get a complete plan on the chart the moment a signal prints, with the exact prices in the label.
🔵 SETTINGS
• Swing Strength: how major a swing must be to count as liquidity (higher = fewer, cleaner levels)
• Levels Tracked: how many liquidity lines to keep per side
• Trend Filter: All sweeps, HTF trend only, or Counter-HTF only
• HTF Bias Timeframe and EMA Length: the higher-timeframe trend reference
• Require Rejection Body and Min Rejection Body (x ATR): quality filter for the sweep candle
• Stop Buffer (x ATR) and Reward : Risk: the trade-plan geometry
🔵 HOW TO USE
• Start on H1 or H4 for forex, gold and indices, with the HTF bias set one or two steps higher
• Treat a swept level plus a strong rejection close as the signal, not the wick alone
• Use Counter-HTF only when you want pure reversal setups at range extremes, and HTF trend only when you want continuation entries after a stop-run against the trend
• Size every trade off the drawn stop distance at a fixed account risk
• Raise Swing Strength on noisy pairs so only the meaningful liquidity gets tracked
🔵 BEST AND WEAKEST CONDITIONS
✅ Strongest at range extremes, session highs and lows, and around prior day or week highs and lows, where liquidity genuinely rests
⚠️ Weakest in fast one-way trends with no pullbacks, and on very low timeframes where every wick looks like a sweep
⚠️ DISCLAIMER
This tool identifies liquidity sweeps and marks reversal setups. It does not predict price. A swept level is a probability, not a certainty, and sweeps can extend further before reversing. Results depend on market conditions, settings, and your own execution and risk management. Shared for educational and research purposes; not financial advice. Indicator
Liquidity Sweep Hunter [BigBeluga]🔵 OVERVIEW
The Liquidity Sweep Hunter is a smart, volume-aware charting tool that automatically detects major support and resistance levels.
Unlike basic horizontal line indicators that just draw lines on every swing high or low, this script filters levels based on volume strength . It identifies the "heavy" levels where big money has clearly participated, projects them forward as active boundaries, and alerts you the exact moment price "sweeps" through them.
🔵 FEATURES
The system works by tracking the relationship between price pivots and real-time volume:
1 — Volume-Weighted Level Detection
Smart Pivot Filtering: The engine identifies price pivots ( Length ) but only confirms a level if the volume at that pivot exceeds your defined Filter threshold. This ignores "weak" pivots and keeps your focus only on high-conviction zones.
Dynamic Intensity Engine: The indicator automatically changes the look of the lines based on volume. Levels created with higher volume activity get thicker lines ( Max Line Width ) and higher opacity, making them visually stand out more on your chart.
2 — Automated Liquidity Sweep & Break Logic
Sweep Alerts (✔): When the price briefly dips below a support level (or spikes above a resistance level) and then closes back inside, the indicator plots a checkmark (✔) to identify the "liquidity sweep."
Smart Self-Cleaning: If the price candles break directly through a support or resistance line, the indicator detects the structural breach, changes the line to a dotted style, and removes it from your active list. This keeps your chart free of outdated, broken levels.
🔵 HOW TO USE
This tool is designed to help you trade based on where market participants have placed their stops and orders:
Identify High-Volume Anchors: Use the thick, bold lines to spot the most important support and resistance levels on your timeframe. These are the zones where the script detected significant institutional interest.
Look for Sweep Confirmations: Watch for the (✔) checkmarks after a line is tagged. A liquidity sweep often signals that the market is grabbing "stop-loss" liquidity before reversing in the opposite direction.
Manage Trade Exit Points: Use the lines as your target zones. Since the script automatically turns lines into "dotted" style when they are broken, you have a visual trigger to cut a position if a key structural level fails.
🔵 NOTES
Why this implementation is unique:
It combines two powerful concepts—volume analysis and pivot structure—into a single, lightweight tool that doesn't overwhelm your chart.
The "Dynamic Intensity" settings allow you to see at a glance which levels are mathematically the most significant based on the volume data behind them.
It is a "self-managing" system; by automatically deleting broken levels, it ensures your screen stays clear for your actual trade execution.
Indicator
Advanced Liquidity Sweep [HexaTrades]Advanced Liquidity Sweep is a Smart Money Concepts (SMC) indicator designed to automatically identify liquidity pools, equal highs and lows, liquidity sweeps, and potential reversal areas. Rather than simply detecting wick breaks, it evaluates each sweep using multiple confirmation factors and assigns a strength score, helping traders distinguish between minor stop hunts and higher-quality liquidity events.
The indicator is designed for cryptocurrencies, stocks, forex, futures, commodities, and indices across all timeframes.
What is Liquidity?
Financial markets constantly search for liquidity before making significant moves.
Retail traders often place:
• Stop losses below swing lows
• Stop losses above swing highs
• Breakout orders above resistance
• Breakdown orders below support
These orders accumulate into liquidity pools. Large market participants frequently move prices into these areas to fill large positions before reversing or continuing the trend.
This indicator automatically identifies those liquidity pools and highlights when they are swept.
How it works :
- Map the liquidity.: Confirmed pivot highs become BSL lines, pivot lows become SSL lines. You choose Major and/or Minor swing sizes.
- Cluster equal highs/lows. Several highs (or lows) at nearly the same price form an EQH / EQL cluster, a bigger, juicier liquidity pool that scores higher.
- Detect the sweep (on closed candles only).
• Bearish: price trades above a BSL level but closes back below it.
• Bullish: price trades below an SSL level but closes back above it.
- Score it 0–100. Six factors rate how convincing the rejection was (see below). At/above your Strong threshold, it’s tagged STRONG.
- Draw a sweep zone. Optionally turn each sweep into a supply/demand zone you can watch for re-entry, with optional auto-expiry.
- Filter the noise. Optional Trend, Higher-Timeframe and Filter presets keep only the cleaner grabs.
Features
🔶 Major & Minor Swing Detection
The indicator detects both major and minor swing highs and lows.
Major swings represent stronger institutional liquidity and usually produce higher-quality reactions.
Minor swings identify shorter-term liquidity that is commonly targeted during intraday trading.
Users can monitor:
• Major swings only
• Minor swings only
• Both simultaneously
🔶Buy-Side Liquidity (BSL)
Buy-side liquidity forms above previous swing highs.
These areas usually contain:
• Short stop losses
• Breakout buy orders
• Momentum entries
When price trades above these highs before quickly closing back below, the indicator identifies a bearish liquidity sweep.
🔶 Sell-Side Liquidity (SSL)
Sell-side liquidity forms below previous swing lows.
These areas usually contain:
• Long stop losses
• Panic selling
• Breakdown entries
When price trades below these lows before closing back above, the indicator identifies a bullish liquidity sweep.
🔶 Equal Highs & Equal Lows
Equal highs and equal lows are some of the strongest liquidity pools because many traders place stops at nearly identical price levels.
The indicator automatically detects these structures using:
• ATR-based tolerance
• Percentage-based tolerance
Equal liquidity levels are highlighted separately and tracked independently from normal swing liquidity.
🔶 Zone Colors
Here are the zone and line colors used in this indicator and what each one means:
🔴 Red: Buy-Side Liquidity (BSL)
- Represents swing highs where buy-side liquidity is concentrated.
- Commonly contains short stop-loss orders and breakout buy orders.
- These are active, unswept liquidity levels and potential targets for a bearish liquidity sweep.
🟢 Green: Sell-Side Liquidity (SSL)
- Represents swing lows where sell-side liquidity is concentrated.
- Commonly contains long stop-loss orders and breakdown sell orders.
- These are active, unswept liquidity levels and potential targets for a bullish liquidity sweep.
🟠 Orange: Equal Highs / Equal Lows (EQH / EQL)
- Marks two or more highs or lows formed at nearly the same price.
- These levels are displayed using dashed lines and often contain larger clusters of resting liquidity.
- Sweeps of Equal Highs and Equal Lows typically produce stronger, higher-probability trading opportunities.
⚪ Gray: Swept (Inactive) Liquidity
- Indicates liquidity that has already been swept by price.
- Once a level has been taken, it changes to gray and becomes inactive.
- This helps distinguish spent liquidity from active levels that may still attract future price movement.
Sweep Signal Colors
🟩 Bullish Liquidity Sweep
-Appears when Sell-Side Liquidity (SSL) or an Equal Low (EQL) is swept.
-Price trades below the liquidity level but closes back above it, confirming a bullish liquidity sweep.
🟪 Bearish Liquidity Sweep
- Appears when Buy-Side Liquidity (BSL) or an Equal High (EQH ) is swept.
- Price trades above the liquidity level but closes back below it, confirming a bearish liquidity sweep.
🔶 Liquidity Sweep Detection
A liquidity sweep occurs when price temporarily breaks a liquidity level but fails to hold beyond it.
For a valid sweep:
Bearish Sweep
• Price trades above Buy-Side Liquidity
• The candle closes back below the level
Bullish Sweep
• Price trades below Sell-Side Liquidity
• The candle closes back above the level
Because the signal is generated only after the candle closes, the indicator does not repaint.
🔶Sweep Strength Score
Every sweep receives a strength score from 0 to 100.
The score combines multiple factors including:
• Wick rejection
• Candle body strength
• Penetration distance beyond liquidity
• Volume confirmation
• Distance from the EMA
• Equal High / Equal Low cluster strength
Higher scores generally indicate stronger liquidity events.
Strength tiers are classified as: Weak, Medium, Strong, and Elite
Users can also define a minimum score to filter out lower-quality sweeps.
🔶 Score Presets
Three scoring profiles are available:
Conservative: Places greater emphasis on clean rejection candles and body structure.
Balanced: Provides an even weighting across all scoring components and is suitable for most trading styles.
Aggressive: Places greater importance on volume and equal liquidity clusters, making it more responsive to institutional activity.
🔶 Trend & Higher Timeframe Filters
The indicator includes optional trend confirmation filters to help improve signal quality.
The Trend Filter uses the EMA 50 and EMA 200 to evaluate the current market direction and offers two modes:
Continuation : Displays only sweeps that align with the prevailing trend.
Reversal : Displays only sweeps that occur against the prevailing trend, helping identify potential market reversals.
For additional confirmation, the Higher Timeframe (HTF) Bias Filter compares price with a higher timeframe EMA. When enabled, sweeps are generated only if they align with the broader market trend, helping reduce false signals and improving overall trade selection.
🔶 Liquidity & Sweep Zones
The indicator provides two complementary ways to visualize liquidity on the chart.
Liquidity Zones highlight swing highs and lows as either horizontal lines, price zones, or both, making it easier to identify areas where liquidity is likely to accumulate. Users can choose between Lines Only, Zones Only, or Both to match their preferred chart style.
When a liquidity sweep occurs, the indicator automatically creates a Sweep Zone around the rejection candle. These zones can be extended into the future, automatically removed after a user-defined period, or kept indefinitely. Sweep zones often serve as potential support or resistance areas, making them useful for identifying future reaction zones, retests, and trade opportunities.
⭐️ Bullish Liquidity Sweep
Price sweeps below the Sell-Side Liquidity (SSL), triggering stop-loss orders before quickly reversing and closing back above the liquidity level. The Sweep Zone acts as a potential support area, while the strength score helps evaluate the quality of the setup. Traders may look for long opportunities on the confirmation or retest, targeting the next Buy-Side Liquidity (BSL).
Example:
⭐️Bearish Liquidity Sweep
Price sweeps above Buy-Side Liquidity (BSL), triggering breakout orders and stop-losses before reversing and closing back below the liquidity level. The Sweep Zone acts as a potential resistance area, while the strength score helps evaluate the quality of the setup. Traders may look for short opportunities on the rejection or retest, targeting the next Sell-Side Liquidity (SSL
example chart:
Alerts
Built-in alert conditions include:
• Bullish Liquidity Sweep
• Bearish Liquidity Sweep
• Equal High Sweep
• Equal Low Sweep
• Strong Bullish Sweep
• Strong Bearish Sweep
• Next-Candle Confirmed Sweep
• Any Liquidity Sweep
These alerts allow traders to automate notifications without monitoring charts continuously.
How to Use
The Advanced Liquidity Sweep indicator helps identify where liquidity exists, when it has been swept, and how strong the resulting market reaction is. For the best results, combine it with market structure, support and resistance, and proper risk management.
Bullish Setup:
- Wait for price to sweep a Sell-Side Liquidity (SSL) level.
- The candle should close back above the liquidity level, confirming a bullish sweep.
- Prefer Medium, Strong, or Elite sweep scores for higher-quality setups.
- Use the Trend Filter or Higher Timeframe Bias Filter for additional confirmation.
- Watch for a retest of the Sweep Zone before considering a long entry.
-Place the stop-loss below the sweep low and target nearby resistance or Buy-Side Liquidity.
Bearish Setup:
- Wait for price to sweep a Buy-Side Liquidity (BSL) level.
- The candle should close back below the liquidity level, confirming a bearish sweep.
- Focus on higher-strength sweep scores for better probability.
- Confirm the setup using the Trend or Higher Timeframe filters.
- Look for rejection from the Sweep Zone before entering a short position.
- Place the stop-loss above the sweep high and target nearby support or Sell-Side Liquidity.
Advanced Liquidity Sweep is designed to help traders understand where liquidity exists, identify when it has been taken, and evaluate the quality of each sweep using multiple confirmation factors. Rather than relying on simple wick breaks, it combines liquidity analysis, market structure, trend confirmation, and strength scoring to provide greater context for trading decisions. As with any technical tool, it should be used alongside sound risk management and additional market analysis for the best results.
We would love to hear your suggestions. If you have ideas for new features, indicators, analytics, or improvements, please share your feedback. Your input helps guide future updates and improve the indicator for all traders.
This indicator is for educational and analytical purposes only. It should not be considered financial advice. Always use proper risk management and make trading decisions based on your own analysis
Indicator
Liquidity PoolsThis script is an automated liquidity mapping tool based on ICT concepts. It actively hunts your chart for zones where retail stop losses and pending breakout orders are clustered.
Here is a breakdown of how the script functions and visualizes liquidity on your chart:
1. Automatic Pivot Detection (Old Highs & Old Lows)
The script continuously monitors price action to find major structural turning points (swing highs and swing lows).
When a confirmed swing high forms, it registers it as Buy-Side Liquidity (BSL) and draws a blue line projecting to the right. This marks a zone where retail traders have placed their buy-stop loss orders above the high.
When a confirmed swing low forms, it registers it as Sell-Side Liquidity (SSL) and draws a red line projecting to the right. This marks a zone where sell-stop loss orders are resting.
2. Equal Highs (EQH) and Equal Lows (EQL) Detection
In ICT methodology, the most powerful magnets for price are "Relative Equal Highs" or "Relative Equal Lows".
The script actively measures the distance between a newly formed pivot and an old active pivot.
If a new pivot forms within a few ticks of an old one (customizable in settings), the script recognizes it as highly engineered liquidity!
It automatically thickens the line, changes its color to bright orange, and updates the text label to EQH or EQL, signaling an extremely high-probability draw on liquidity.
3. Smart Text Labeling
To ensure you never have to guess what a line means, the script pins a text label (BSL, SSL, EQH, or EQL) directly at the starting point of every liquidity pool.
4. Sweep Detection & "Stop-Hunting" Tracking
Liquidity pools are only valid until they are traded through.
The script tracks every live tick. The exact moment price sweeps through a liquidity line, it stops extending the line.
It drops a small "X" right where the line was broken. This gives you a permanent historical footprint on your chart of exactly where and when "Smart Money" swept stops.
5. Memory Management
Because liquidity lines could theoretically build up infinitely and crash your chart, the script has built-in garbage collection. It only keeps track of the 15 most recent unswept pools (you can change this number in the settings) so your chart always stays clean and fast. Indicator
Indicator
Liquidity Sweeps [Quantum Algo]Liquidity Sweeps is an open-source liquidity sweep indicator that maps resting
liquidity at swing highs and swing lows, then flags the exact moment that liquidity is swept and
rejected — the classic stop-hunt behaviour traders watch for in Smart Money Concepts (SMC).
WHAT IS A LIQUIDITY SWEEP?
A liquidity sweep (also called a liquidity grab or stop hunt) happens when price briefly spikes
beyond an obvious swing high or swing low — where stop-loss and breakout orders rest — and then
closes back inside the prior range. The wick takes the liquidity; the close shows the breakout
failed. Liquidity sitting above swing highs is buy-side liquidity (BSL); liquidity sitting below
swing lows is sell-side liquidity (SSL).
A bearish liquidity sweep occurs when buy-side liquidity above a swing high is swept and price
closes back below it. A bullish liquidity sweep occurs when sell-side liquidity below a swing low
is swept and price closes back above it.
HOW THE INDICATOR WORKS
- It detects confirmed swing highs and swing lows using a configurable pivot strength, and draws a
liquidity level at each one. Buy-side levels sit above price; sell-side levels sit below.
- Each level extends to the right until it is interacted with.
- When a candle wicks through a level but closes back inside, the indicator marks a liquidity
sweep with a label and an optional highlight on the sweeping wick.
- An optional volume filter confirms only sweeps where the sweeping candle trades above its
average volume, filtering out low-conviction wicks.
- If price instead closes fully through a level, that is treated as a clean break (a plain
liquidity grab / breakout), not a sweep, and the level is retired without a signal.
WHAT IT SHOWS
- Mapped buy-side (BSL) and sell-side (SSL) liquidity levels.
- Bullish and bearish liquidity sweep markers, the moment a level is swept and rejected.
- Optional wick highlighting on the sweep candle.
- A dashboard showing bullish/bearish sweep counts, the last sweep direction, and the nearest
un-swept buy-side and sell-side levels with their percentage distance from price.
HOW TO USE IT
Liquidity sweeps are most useful as a timing and context tool, not a standalone buy/sell system.
A common workflow:
- Mark the obvious highs and lows where liquidity is likely resting.
- Wait for a sweep into one of those pools (a wick through, close back inside), ideally with the
volume filter confirming participation.
- Look for confirmation in your own process — a market-structure shift, an order block, a
fair-value-gap fill, or higher-timeframe trend alignment — before acting.
- A bearish sweep above resistance can precede a move down; a bullish sweep below support can
precede a move up. Always define risk beyond the swept extreme.
SETTINGS
- Pivot Strength: how many bars define a swing; higher values keep only major liquidity pools.
- Max Levels per Side: how many recent levels to keep mapped.
- Volume Confirmation: toggle, average length, and multiplier to qualify a sweep.
- Treat Clean Breaks as Grabs: retire levels that are broken through rather than swept.
- Line width, style, and transparency for clear level visibility.
- Full colour controls and a movable dashboard.
ALERTS
Three named alert conditions are included: Bullish Liquidity Sweep, Bearish Liquidity Sweep, and
Any Liquidity Sweep.
DISCLAIMER
For educational purposes only. This is a technical analysis tool, not financial advice, and it does
not predict price. Trading involves risk and you can lose your capital. No indicator is profitable
on its own — always do your own research and use proper risk management. Indicator
Indicator
Elaris Session Liquidity Grabs Pro# Elaris Session Liquidity Grabs Pro
Elaris Session Liquidity Grabs Pro is a professional session-based liquidity sweep and reversal detection tool designed for traders who focus on smart money concepts, stop hunts, failed breakouts, and institutional liquidity behavior.
The indicator automatically builds key liquidity ranges from major global trading sessions including London, New York, and Asia, then detects high-probability liquidity grabs when price sweeps session highs or lows and rejects back into range.
Unlike basic sweep indicators, this tool includes advanced filtering systems designed to reduce noise and focus on stronger reversal conditions using ATR displacement, candle strength analysis, EMA trend filtering, and optional volume confirmation.
Built for active intraday traders, scalpers, and smart money traders, the indicator provides a clean visual framework for identifying areas where liquidity may have been engineered before a market reversal or continuation move.
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FEATURES
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• Automatic London, New York, and Asia session ranges
• Session high/low liquidity tracking
• Bullish and bearish liquidity grab detection
• Wick sweep and close-break detection modes
• ATR-based sweep validation filters
• Strong displacement candle confirmation
• EMA trend filter for directional bias
• Volume confirmation filter
• Optional cooldown system to reduce signal clustering
• Session equilibrium (midline) plotting
• Clean session range visualization
• Professional dashboard panel
• Dark mode and light mode support
• Alert conditions for automation and notifications
• Non-repainting confirmed signals
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HOW IT WORKS
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The indicator builds liquidity ranges from selected market sessions and monitors price action after those sessions complete.
When price aggressively sweeps a session high or low and then rejects back into the range, the indicator identifies it as a potential liquidity grab event.
Examples:
• Price sweeps above London High and closes back below → potential bearish liquidity grab
• Price sweeps below New York Low and closes back above → potential bullish liquidity grab
Additional confirmation filters help reduce weak or low-quality signals by requiring stronger candle displacement, trend alignment, and optional volume expansion.
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BEST USE CASES
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• Smart money trading concepts
• Session liquidity trading
• Stop hunt reversals
• Scalping and intraday trading
• ICT-style trading approaches
• Breakout failure detection
• Market manipulation detection
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RECOMMENDED MARKETS
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• Crypto Futures
• Forex
• Indices
• Gold and Commodities
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RECOMMENDED TIMEFRAMES
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• 1 Minute
• 3 Minute
• 5 Minute
• 15 Minute
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NON-REPAINTING
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This indicator is designed to be non-repainting.
Signals are confirmed only after candle close and session levels are finalized after the session completes. No future data is used.
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NOTES
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This tool is designed to assist with identifying liquidity behavior and market structure reactions. It should be used alongside proper risk management, higher timeframe analysis, and additional trade confirmation techniques.
No indicator guarantees profitability or win rate consistency across all market conditions.
Indicator
Indicator
SMC Setup: Sweep + CHoCH + FVG v21.1SMC Setup: Sweep + CHoCH + FVG v21.1 (Multi-Timeframe Execution Engine)
Introducing a complete, institutional-grade Smart Money Concepts (SMC) execution algorithm. This is not just a standard sweep indicator; it is a "3D" Top-Down Analysis Engine designed to flawlessly mimic how professional human traders track order flow across multiple timeframes, natively executing on your lower-timeframe charts.
Built to solve the common pitfalls of algorithmic SMC (such as repainting, MTF blindness, and zero-width visual crashes), this indicator tracks Major (External) and Minor (Internal) liquidity simultaneously and automates your entire entry and trade management visualization.
🔥 Core Features
Multi-Timeframe (MTF) "Time-Warp" Engine: Track 15-minute and 5-minute structural liquidity sweeps natively on the 1-minute execution chart. The script uses internal mathematical multipliers and a massive 5000-bar deep memory buffer to track HTF structure without relying on laggy or repainting request.security() calls.
Dual-Fractal Liquidity Tracking: * Solid Blue Lines: Tracks Major/External Higher Timeframe liquidity peaks.
Dotted Blue Lines: Tracks Minor/Internal Lower Timeframe pullbacks for aggressive continuation order flow.
Two Selectable Entry Models:
BOS Breakout: For aggressive momentum traders. Executes the exact millisecond the micro-structure BOS (Break of Structure/CHoCH) line is cracked.
FVG Pullback: For conservative traders. Waits for a Break of Structure, verifies a Fair Value Gap has formed, and sets a limit entry exactly at the FVG boundary.
Dynamic Visual Trade Management: The script automatically generates a physical Risk Zone Box (mimicking the native PulseWire Short/Long Position tools) and projects dynamic, trailing lines for your Entry, Stop Loss, TP1, TP2, and Full Target based on customizable Risk:Reward settings.
Webhook-Ready Alerts: Generates highly detailed, once-per-bar-close alerts containing dynamic strings for Entry Price, Stop Loss, and all Take Profit targets, making it perfect for automated execution via 3Commas, PineConnector, etc.
⚙️ How It Works (The Logic Flow)
The Hunt: The algorithm maps higher timeframe peaks (e.g., 15m/5m) and local micro-peaks simultaneously.
The Sweep: When price sweeps a mapped liquidity line, the algorithm "arms" the setup and locks the Stop Loss to the highest point of the sweep.
The CHoCH/BOS: It tracks the immediate local pullback prior to the sweep. If price breaks this micro-structure support, the setup is confirmed.
The Execution: Depending on your selected model, it either triggers instantly on the BOS breakout or waits for a bearish FVG pullback.
The Management: Target lines trail alongside price action and automatically lock into place the moment the trade hits the Full Target or the Stop Loss.
💡 Best Practices
Optimal Use: Load this indicator on the 1-minute chart. Set the Major HTF Multiplier to 15 and the Minor HTF Multiplier to 5. This allows the script to see 15m and 5m market structure while leveraging the 1-minute candles for surgical entries.
Asset Classes: Highly effective on high-volume assets like Indices (NAS100, US30, SPX) and Forex (EURUSD, XAUUSD) during the London or New York sessions. Indicator
Heatmap Liquidity Zones [BigBeluga]🔵 OVERVIEW
Heatmap Liquidity Zones is a higher-timeframe volume heatmap tool designed to reveal where liquidity is concentrated inside institutional ranges.
Instead of plotting a traditional volume profile, this indicator builds a dynamic heatmap across each selected higher-timeframe candle.
It highlights high-volume price clusters, filters significant liquidity zones, and extends them forward as actionable support/resistance levels.
The result is a clean liquidity map that visualizes where participation is strongest — and where reactions are most likely to occur.
🔵 CORE CONCEPT
HTF Range Segmentation — Each higher-timeframe candle (D/W/M or custom) defines a new accumulation range.
ATR-Based Adaptive Binning — Vertical bin size is derived from ATR to maintain consistent resolution across volatility regimes.
Volume Density Mapping — Volume is distributed into price bins and normalized relative to the highest-volume bin.
Liquidity Filtering — Only bins exceeding a configurable percentage threshold are promoted to active liquidity levels.
Self-Cleaning Zones — Liquidity levels automatically disappear once breached by price.
🔵 HOW IT WORKS
1️⃣ Higher-Timeframe Reset Logic
When a new selected HTF candle begins, the previous range is finalized.
A new accumulation range starts from that bar.
High and Low are tracked dynamically throughout the segment.
2️⃣ ATR-Based Bin Construction
ATR defines the vertical bin size (ATR × Multiplier).
The total range is divided into up to Max Bins.
This ensures bin resolution adapts automatically to volatility.
3️⃣ Volume Distribution
For each completed segment, volume is distributed into bins based on proximity to bin midpoint.
Volume per bin is normalized relative to the maximum bin.
Each bin is assigned a heat color based on relative density:
Low Density → Purple
Mid Density → Cyan
High Density → Yellow
4️⃣ Liquidity Zone Creation
If a bin exceeds the Liquidity Filter %, it becomes a tracked liquidity level.
Liquidity levels extend forward as horizontal lines.
The thickness is controlled by Liquidity Level Width.
Stronger zones display larger markers and percentage labels.
🔵 HEATMAP VISUAL STRUCTURE
Completed segments display full heatmap boxes across the range.
Active segment updates in real time.
Color intensity reflects liquidity concentration.
High-density zones stand out clearly for institutional reference.
🔵 OPTIONAL MOVING AVERAGE
Optional smoothing MA overlay (SMA, EMA, RMA, WMA, VWMA).
Hidden by default.
Can be used for confluence with liquidity zones.
🔵 KEY FEATURES
Higher-timeframe segmented liquidity mapping.
ATR-based adaptive resolution.
Three-stage heatmap gradient.
Configurable liquidity filtering.
Auto-expiring support/resistance levels.
Dynamic zone thickness based on volume strength.
Real-time developing heatmap.
Optional MA overlay.
🔵 HOW TO USE
Focus on yellow (high-density) zones for strongest liquidity pools.
Watch reactions at filtered liquidity levels.
Use HTF segmentation (Weekly/Monthly) to identify institutional positioning.
Combine with breakout tools for liquidity sweep setups.
Lower ATR multiplier → more granular liquidity clusters.
Higher Liquidity Filter % → only strongest zones remain.
🔵 INTERPRETING LIQUIDITY
High density near highs → potential distribution.
High density near lows → potential accumulation.
Clustered zones → compression areas before expansion.
Thin zones → low participation, faster price movement potential.
🔵 CONCLUSION
Heatmap Liquidity Zones transforms higher-timeframe volume into a structured liquidity map.
By combining ATR-adaptive binning, density-based heat gradients, and intelligent liquidity filtering, it highlights where institutional participation is concentrated — and where meaningful reactions are most likely.
This makes it especially powerful for identifying liquidity pools, sweep zones, and structural turning points. Indicator
Liquidity Sweep Detector [SSFX]Liquidity Sweep Detector is a price action indicator designed to highlight potential liquidity grabs around confirmed swing highs and swing lows. The script identifies pivot-based levels, tracks them forward on the chart, and detects when price briefly trades beyond those levels with the wick while failing to close through them with the candle body. This behavior is often associated with stop hunts, liquidity sweeps, and rejection-based reversals. The indicator is built to help traders quickly spot these events in a clear and structured way.
The script first builds its framework using pivot highs and pivot lows. Each confirmed pivot becomes a horizontal reference level that remains active until it is either swept or mitigated. A bearish sweep is detected when price pushes above a pivot high with the wick, but the candle body remains below that level. A bullish sweep is detected when price trades below a pivot low with the wick, while the candle body remains above it. This allows the indicator to separate true wick rejections from full body breaks, which is useful for traders who want to focus specifically on liquidity-based price reactions rather than standard support and resistance breaks.
To improve selectivity, the indicator also includes an optional volume filter. When enabled, sweeps are only marked if volume is greater than a configurable moving average threshold multiplied by a user-defined factor. This can help filter out weaker sweeps and emphasize events that occur with stronger market participation. Traders who prefer a cleaner chart can leave the volume filter disabled, while those who want more confirmation can use it to reduce noise.
The script provides clear visual feedback directly on the chart. Active pivot levels are plotted as horizontal dashed lines. When a valid sweep occurs, the indicator draws a colored highlight between the level and the wick extreme, making the rejection area easy to identify. It also places a sweep marker exactly at the wick high or wick low of the sweep candle, rather than simply above or below the bar, which gives more precise visual alignment with the actual liquidity event. Bullish sweeps and bearish sweeps use separate colors so both directions can be distinguished instantly.
In addition to sweep detection, the indicator tracks mitigation events. A mitigation occurs when price breaks a stored pivot level with the candle body rather than merely sweeping it with the wick. When enabled, mitigated levels are recolored and marked with a small cross placed in the middle of the line, helping users differentiate between levels that produced a rejection and levels that were cleanly broken. There is also an option to hide mitigation markings entirely for traders who want the chart to focus only on sweep signals. Historical levels can be preserved or removed after resolution depending on user preference.
This indicator is intended as a visual price action tool, not a complete trading system. It does not generate entries, stop losses, take profits, or strategy performance statistics. Instead, it is designed to support discretionary analysis by helping traders locate areas where liquidity may have been taken and where rejection behavior may be developing. It can be used on its own or combined with higher timeframe structure, supply and demand zones, session context, or confirmation from other price action concepts.
Main features
Detects bullish and bearish liquidity sweeps from confirmed pivot levels
Uses wick-only sweep logic to distinguish sweeps from body breaks
Optional volume filter for stronger signal selection
Draws active historical liquidity levels on the chart
Highlights sweep zones visually with directional coloring
Places sweep dots exactly at the wick high or wick low
Marks mitigated levels with a centered cross when enabled
Includes options to keep or remove historical levels after resolution
Provides alert conditions for bullish and bearish sweeps
How to use
Watch for price to wick above a prior high or below a prior low without closing through it
Use the sweep marker and highlighted zone to quickly confirm the rejection area
Combine signals with market structure, session timing, or additional confirmation before making trade decisions
Use the volume filter if you want fewer but more selective sweep signals
Notes
Pivot-based logic requires right-side confirmation, so signals appear only after the pivot is confirmed
The script is meant for chart analysis and signal visualization only
Best used as a supporting tool within a broader trading plan
Indicator
Stop Loss Cascades (Breakouts) [Kioseff Trading]Hello friends and traders!
🔹Introduction
This indicator " Stop-Loss Clustering (Breakouts) " attempts to model trader stop-loss placement logic and identify price areas where a large amount of stop losses might cluster.
The idea is, if stop losses are indeed highly concentrated in a specific area, price extending through that area may produce high-velocity breakout conditions via forced order flow .
I'll cover this topic more thoroughly throughout the description. For now, just know that stop loss location & size data is not publicly available . Any model of their concentration locations is highly assumptive.
However, there's some reasonable academic research we can reference to make worthwhile estimates.
Academic references supporting the concepts discussed are listed at the end of this description. To maintain readability, I won't cite individual statements inline.
🔹The Premise
🔸Liquidity, Behavior, and Stop Cascades
Markets operate through a continuous limit order book , where two fundamental order types interact:
Limit orders , which provide liquidity by resting in the book
Market orders , which consume liquidity by exhausting those resting orders
This mechanical interaction drives price movement - incoming order flow consuming available liquidity .
This begs the question.. Does liquidity distribute evenly across the LOB?
If it did : If liquidity were evenly distributed, price impact could be modeled as a relatively smooth function of incoming order flow.
But it doesn’t : Liquidity is unevenly distributed. Academic research supports this claim and, regardless, this is an intuitive conclusion most traders arrive at.
Liquidity forms localized concentrations and gaps.
Liquidity concentrations are commonly referenced as: liquidity shelves , liquidity clusters , liquidity zones .
Liquidity gaps are commonly referenced as: liquidity vacuums , thin book zones .
As a result, identical order flow can produce very different price movements depending on the state of the order book.
Let’s consider an example..
Assume price is trading at $99.
The price levels $100, $101, $102 have resting sell limit order concentrations of 100.
This is where you come in.
You execute a market order buy for 300 size.
Your order first exhausts all sell-side resting order concentrations at the $100 level.
You still have 200 size that needs to be filled, and the ask price has moved from $100 to $101.
Your order will now sequentially exhaust available liquidity at the $101 level, the ask price will increase to $102, and your final 100 size will exhaust the $102 level.
To keep the example simple, we’ll say that your order moved price from $99 to $102, and now the ask price is $103.
But, you still want to accumulate.
The nearest sell-side levels in the LOB are $103, $104, $105.
The $103 level has a sell limit order concentration of 500.
$104 and $105 both have concentrations of 50.
You execute your same market order buy for 300 size.
This time, price doesn’t move.. At all..
Instead, you consumed 300 of the 500 size at $103 with your order, and the level remains a barrier.
Your order was absorbed by available liquidity.
This example demonstrates how price movement depends on available liquidity , not simply the size of incoming orders.
In the first scenario, liquidity was thin and the order walked through multiple price levels, causing price to move quickly.
In the second scenario, a large concentration of resting liquidity absorbed the same order, preventing price from advancing.
🔸Liquidity Does Not Distribute Evenly
Alright, we understand that liquidity doesn’t distribute evenly. And we understand that high concentrations of liquidity can act as price barriers (liquidity shelves) while sparse liquidity can permit rapid price movement - we saw this in our example above.
There’s an important question we should ask next before we move on..
If liquidity distributes unevenly, then where does it tend to cluster? And where does it tend to thin?
Of course, knowing these tendencies provides multi-purpose advantages.
If price approaches a liquidity vacuum - a local block of the order book with thin resting liquidity - rapid price movement can occur without requiring unusually strong aggressive order flow.
If price approaches a liquidity shelf - a local block of the order book with thick resting liquidity - price can stall or contract even if the same level of aggressive order flow that previously moved price continues.
With this in mind, order flow intensity alone does not determine price movement . The distribution of liquidity across surrounding price levels plays a similarly important role.
So, is there any evidence of where liquidity tends to concentrate ?
🔸Empirical Observations
Empirical research on limit order books shows that liquidity does not distribute smoothly across the LOB . Instead, depth tends to concentrate at specific price levels, producing irregular profiles with localized peaks in resting liquidity.
These concentrations arise because order placement is not random . Traders frequently anchor decisions to widely observed reference prices such as:
• prior highs
• prior lows
• round numbers
• widely referenced price extremes
Because many traders monitor the same price history, order placement decisions often reference similar price levels.
This concept is simpler than it sounds.
Let’s use market structure traders for example.
Market structure traders frequently reference prior swing highs and swing lows when making decisions about entries, exits, and risk.
A trader entering a long position may place their stop-loss below a recent swing low , reasoning that if price breaks that level, the trade idea is invalidated.
A trader entering a short position may place their stop-loss above a recent swing high for the same reason.
Timeframe price aggregation may differ; however, we’re all looking at roughly the same recent highs and lows when evaluating a chart (structure).
When many traders collectively reference the same prices, orders may accumulate near those levels. This produces localized depth concentrations, which traders refer to as liquidity shelves .
Liquidity shelves act as temporary barriers where the book contains disproportionately large resting liquidity compared to surrounding prices.
🔸Research documenting liquidity clustering includes :
Bourghelle & Cellier (2007) , who find that limit orders cluster at prominent price levels (especially round numbers), creating localized depth concentrations that can act as price barriers.
Kavajecz & Odders-White (2004) , who demonstrate that prices identified as support or resistance coincide with higher resting limit order depth
These findings suggest that many commonly observed price levels may correspond to real concentrations of liquidity rather than being purely visual artifacts on a chart.
Kavajecz & Odders-White (2004) is an important observation for support/resistance traders!
Kavajecz & Odders-White (2004) show that levels traders commonly call support and resistance often align with areas where more limit orders are resting in the order book.
This suggests a plausible mechanical pathway through which support and resistance levels can emerge!
🔸Liquidity Shelves and Price Interaction
When liquidity clusters around a price level, the resulting liquidity shelf can influence how price behaves when it approaches that area.
Price interaction with these shelves is state-dependent :
If incoming order flow is absorbed, price may stall or reverse
If resting liquidity is consumed, price may transition rapidly to the next liquidity zone
Once a shelf is depleted, follow-through can accelerate due to thinner liquidity beyond the level
Research on order book dynamics supports this mechanical view of price movement.
For example:
Jean-Philippe Bouchaud, J. Doyne Farmer, and Fabrizio Lillo (2009) demonstrate that price impact emerges from the interaction between order flow and finite liquidity
From this perspective, price does not move simply because a level is crossed.
Price moves because available liquidity at that level has been consumed.
🔸Latent Liquidity and Stop Clustering
In addition to visible liquidity from limit orders, markets also contain latent liquidity .
This is where ”Stop-Loss Clustering (Breakouts)” becomes important - we’re almost done!
Latent liquidity consists of conditional orders such as stop-losses that are not visible in the order book until triggered .
Although these orders aren’t public information, empirical studies show that stop orders tend to cluster near widely referenced price levels .
Research by Carol Osler (2001, 2002) using institutional FX order data finds that stop-loss orders frequently accumulate just beyond salient price levels such as prior highs and lows.
When these stops trigger, they convert into aggressive market orders and can generate bursts of directional order flow that may accelerate price movement.
🔸Stop-Loss Cascades
Stop losses add another layer of latent order flow that isn’t visible in the order book until it triggers.
If enough of them sit around the same price area.. Think “hidden pressure” waiting to activate. Nothing happens while price trades nearby, but once that level is traded at, those stops convert into market orders and immediately begin consuming available liquidity.
This matters because stop placement is unlikely to be random in most instances. Traders frequently anchor stops to widely observed prices such as prior highs, prior lows, or other prominent structure points, or use volatility methods such as ATR, etc.
So when price approaches one of these areas, two things can happen.
If the resting liquidity there is large enough, the incoming orders can be absorbed and price may stall or reject.
But if that liquidity gets consumed, the stops sitting just beyond the level begin triggering. Those triggered stops add additional market orders, which consume more liquidity and can push price further into the next layer of stops.
This creates a cascading effect:
price reaches a stop cluster
stops trigger and convert into market orders
liquidity gets consumed faster
price moves further, triggering more stops
When this chain reaction starts, price can transition very quickly from a slow battle near the level to rapid expansion through it.
This is one of the mechanical reasons why some reference-point breaks barely move, while others accelerate rapidly.
🔹How It Works
Now that we understand the why - let’s discuss how the indicator works.
🔸Absorbtion Extremes
The image above shows the absorption extremes model.
In this model, the indicator treats recent & relevant swing points as plausible stop clustering candidates.
You can find similar swing point identification mechanics in other indicators.
However, this model assigns subsequent volume to the swing level after its formation.
There are limitations and assumptions - let’s go over them.
The images above explain how the indicator determines the intensity of a possible stop-cluster around a swing level.
There are limitations and assumptions
1: The indicator assigns all “directional volume” to a swing level after it’s formed and while it remains the closest active swing point to the current price.
“Buy volume” is assigned to the closest active swing low.
“Sell volume” is assigned to the closest active swing high.
I say “buy volume” and “sell volume” because there’s assumptions on what constitutes the relevant classification.
The indicators follow the traditional two-region tick model for classifying buy volume and sell volume.
Higher close = “buy volume” proxy
Lower close = “sell volume” proxy
Depending on the granularity you select (the indicator is capable of using tick data), this model can be more/less accurate.
However, even with tick-level data and bid/ask quotes, trade direction must still be inferred using classification rules. Because some trades occur inside the spread or involve hidden liquidity, perfect classification is not possible without exchange aggressor flags.
For assumptions..
The model assigns ALL classified volume to the swing level.
In reality, traders use a wide range of risk management methods, and not every position will place a stop loss directly at the most recent swing point. ATR-based stops, percentage-based stops, and other volatility-based methods are also common.
Because the true distribution of stop placement is unobservable, the model assumes that positions entered are structurally invalidated at the closest swing level based on their classified direction.
As a result, the values displayed by the indicator should be interpreted as relative proxies for potential stop concentration, rather than precise estimates of actual stop-loss size.
The displayed magnitudes are intentionally exaggerated and comparative, designed to highlight where stop pressure may accumulate relative to other levels.
The images above show how to interpret the indicator when using this model.
The image above shows the triggered stop-cluster graph.
Each point corresponds to a triggered stop-cluster - assuming it exists.
The greater the size attached to that cluster, the further distant the data point is placed.
Far away from zero line = large size.
Close to zero line = low size.
Radiating/glowing points indicate a potentially large cluster trigger.
🔸 Volatility-At-Entry Model (Time Scaled)
The Volatility-At-Entry model uses ATR scaled by various timeframes to predict plausible stop loss placements.
For this model, the indicator uses the same tick classification model to assign volume directionally.
Volume is then dispersed across six common timeframes (1m, 5m, 15m, 30m, 1h, 4h) and 3 common ATR multiples for risk management (1ATR, 1.5ATR, 2ATR).
This model assumes traders are entering positions across various timeframes and are scaling risk congruent with those timeframes.
For instance,
A trader using the 1-minute chart for opportunity is more likely to use a stop loss closer to entry than a trader using the 4-hour chart for opportunity.
If this assumption is reasonable to you - great, we can move forward!
The image above visualizes the model.
Purple-shaded regions indicate a price area with less opportunity for stop loss clustering. Either transaction intensity around eligible price areas was low, or position accumulation wasn’t given sufficient time.
Pink-shaded regions indicate a price area with greater opportunity for stop loss clustering. Volume was significant around these regions or price has traded within proximity for extended periods.
This model naturally shows more future opportunity than historical outcomes. You can select to show historical outcomes in the settings, this image shows examples of such outcomes.
The image above shows the triggered stop loss graph in effect for this model. Stop clustered are distributed across more price areas with this model - from low intensity to high intensity. Therefore, a cluster is almost always “triggering” to some degree.
A classification model for what’s typical and what’s unusual is used for the graph in this case. Radiating points always indicate large stop clusters triggered. Anything within the green/pink line indicates usual size.
Typical Move
The image above explains the nearest cluster information table.
The size and location of the nearest buy-stop cluster and sell-stop cluster are recorded.
Additionally, the indicator identifies whether clusters of similar size were triggered in the past, and how price behaved following those events.
Since all models here are highly assumptive, and similar sized clusters might only have one or two relative neighbors, treat these measurements as a description of history rather than a prediction.
The model takes the logarithm of the current stop-volume (buy or sell) to normalize its scale and compare it with a historical dataset of previously observed stop-volume sizes that have also been log-scaled.
It then identifies historical observations whose sizes are most similar to the current value, either by selecting all observations within a tolerance range around that value (where the range is based on the typical spacing between historical observations), or by selecting the single closest match.
Finally, the model retrieves the historical price moves associated with those matched observations, producing a sample of “typical moves” that occurred when stop-volume magnitude was similar to the current situation.
Ratio Meter
The stop-cluster ratio meter shows the current sum of active and triggered all buy-side clusters and sell-side clusters.
This meter is useful for quick scanning across assets to see if active or recently triggered stop clusters are lopsided.
Additional Features
The single most important setting outside model selection is the lower timeframe used to retrieve volume from.
This setting is set to 1-minute data by default because it works with paid and free plans. If you want better granularity, I strongly suggest changing this setting to either 1-second or 1-tick. This will sacrifice the number of identifiable cluster locations, because better granularity data has less programmatically retrievable values.
🔹Closing Remarks
Stop-loss clustering is an appealing concept because it offers a plausible explanation for why some breakouts accelerate so quickly while others stall. When a large number of conditional orders sit near the same price, a breakout through that area can trigger a cascade of market orders that rapidly consume liquidity and push price toward the next available zone.
However, it’s important to remember that the models used in this indicator are approximations, not direct measurements. True stop-loss locations and sizes are not publicly observable, and many traders use different risk management techniques that cannot be perfectly inferred from chart data alone. The goal of this indicator is therefore not to identify exact stop locations, but to highlight price areas where stop pressure may plausibly accumulate relative to surrounding levels.
Like any model based on behavioral assumptions and historical observations, results should be interpreted probabilistically. Large clusters do not guarantee breakouts, and small clusters do not guarantee quiet price behavior. Instead, the indicator is best used as a tool for context and situational awareness.
References
General Microstructure and Price Formation
Madhavan, A. (2000). Market microstructure: A survey. Journal of Financial Markets, 3(3), 205–258.
O'Hara, M. (1995). Market Microstructure Theory. Blackwell.
Biais, B., Glosten, L., & Spatt, C. (2005). Market microstructure: A survey of microfoundations, empirical results, and policy implications. Journal of Financial Markets, 8(2), 217–264.
Limit Order Books and Liquidity as Resting Orders
Gould, M. D., Porter, M. A., Williams, S., McDonald, M., Fenn, D. J., & Howison, S. D. (2013). Limit order books. Quantitative Finance, 13(11), 1709–1742.
Rosu, I. (2009). A dynamic model of the limit order book. Review of Financial Studies, 22(11), 4601–4641.
Biais, B., Hillion, P., & Spatt, C. (1995). An empirical analysis of the limit order book and the order flow in the Paris Bourse. Journal of Finance, 50(5), 1655–1689.
Liquidity Clustering and Depth Concentration
Kavajecz, K. A., & Odders-White, E. R. (2004). Technical analysis and liquidity provision. Review of Financial Studies, 17(4), 1043–1071.
Bourghelle, D., & Cellier, A. (2007). Limit order clustering and price barriers on financial markets. Working paper / SSRN.
Order Flow and Price Impact
Bouchaud, J.-P., Farmer, J. D., & Lillo, F. (2009). How markets slowly digest changes in supply and demand. In Handbook of Financial Markets: Dynamics and Evolution.
Stop Orders and Price Cascades
Osler, C. L. (2003). Currency orders and exchange-rate dynamics: Explaining the success of technical analysis. Journal of Finance, 58(5), 1791–1819.
Osler, C. L. (2005). Stop-loss orders and price cascades in currency markets. Journal of International Money and Finance, 24(2), 219–241.
Liquidity Provision and Execution
Ho, T., & Stoll, H. (1981). Optimal dealer pricing under transactions and return uncertainty. Journal of Financial Economics, 9(1), 47–73.
Almgren, R., & Chriss, N. (2000). Optimal execution of portfolio transactions. Journal of Risk, 3(2), 5–39.
Menkveld, A. J. (2013). High frequency trading and the new market makers. Journal of Financial Markets, 16(4), 712–740.
Behavioral Anchoring and Attention
Kahneman, D., & Tversky, A. (1974). Judgment under uncertainty: Heuristics and biases. Science, 185(4157), 1124–1131.
Barber, B. M., & Odean, T. (2008). All that glitters: The effect of attention and news on the buying behavior of individual and institutional investors. Review of Financial Studies, 21(2), 785–818.
George, T. J., & Hwang, C. Y. (2004). The 52-week high and momentum investing. Journal of Finance, 59(5), 2145–2176.
Mizrach, B., & Weerts, S. (2007). Highs and lows: A behavioral and technical analysis. SSRN working paper.
Indicator
Liquidity Raids [UAlgo]Liquidity Raids is a market structure overlay designed to highlight classic liquidity sweep events around recent swing levels. The script continuously maps swing highs and swing lows using pivot detection, projects those levels forward as active lines, and then monitors price behavior around each level to detect a raid.
A raid is defined here as a sweep through a prior level followed by rejection back across it within the same bar. This behavior often represents stop runs, liquidity grabs, or failed break attempts. The script separates these events into:
BSL sweeps, where buy side liquidity above prior highs is taken and price closes back below the level
SSL sweeps, where sell side liquidity below prior lows is taken and price closes back above the level
To improve signal quality, an optional relative volume confirmation filter can be enabled. When active, a sweep is only valid if the sweep bar’s volume exceeds a multiple of the recent average, and the script prints the relative volume percentage on the chart for additional context.
The indicator also includes practical object management to keep charts clean by limiting the number of active levels and removing invalidated lines automatically.
🔹 Features
1) Automatic Swing Level Mapping via Pivot Highs and Lows
The script uses pivot detection to identify meaningful swing highs and swing lows. Each confirmed pivot becomes a projected liquidity level that extends forward in time. These levels represent areas where stops and breakout orders tend to cluster.
Pivot Length controls how sensitive the swing detection is. Higher values produce fewer but more significant levels. Lower values react faster and produce more frequent levels.
2) Active Level Projection and Management
Each pivot level is drawn as a horizontal line and stored in an internal array. On every new bar, the script updates each active line so it extends to the current bar. A Maximum Active Levels setting prevents chart clutter and controls the number of stored objects. When the limit is exceeded, the oldest level is removed.
3) Clear Sweep Definitions for BSL and SSL
Each level is monitored for two outcomes:
Sweep and reject
Broken and accepted
For resistance levels, a BSL sweep requires the bar high to trade above the level while the close finishes at or below the level. A break requires the close to finish above the level.
For support levels, an SSL sweep requires the bar low to trade below the level while the close finishes at or above the level. A break requires the close to finish below the level.
When a sweep is detected, the level is removed after the event is confirmed. When a level is broken, it is removed to prevent outdated levels from remaining on the chart.
4) Optional Volume Confirmation Using Relative Volume
When enabled, sweeps are filtered using Relative Volume (RVOL). The script compares the current bar’s volume to the 20 bar average volume and requires it to exceed a user defined multiplier.
This is useful for separating meaningful stop runs from thin market spikes. The script also prints the RVOL percentage near the swept level for quick evaluation.
5) Sweep Highlighting and Labels
On a valid sweep, the script highlights the swept level with a bright confirmation line and optionally prints labels:
▼ BSL for buy side liquidity sweeps
▲ SSL for sell side liquidity sweeps
Volume information is also displayed as a percentage at the midpoint of the swept segment, positioned above for BSL and below for SSL to reduce overlap.
6) Configurable Visual Styling
You can control resistance and support colors independently, choose line style (solid, dotted, dashed), and toggle labels. This makes the overlay adaptable to both clean minimalist charts and more information dense layouts.
7) Alerts for Automation and Monitoring
Alert conditions are included for both sweep types. In addition, the script triggers immediate alerts with the close price when a sweep is detected on bar close. This supports both discretionary monitoring and automated notification workflows.
🔹 Calculations
1) Pivot Based Level Detection
Swing highs and lows are detected using symmetric pivot logic:
float ph = ta.pivothigh(high, pivotPeriodInput, pivotPeriodInput)
float pl = ta.pivotlow(low, pivotPeriodInput, pivotPeriodInput)
Interpretation:
A pivot high is confirmed only after pivotPeriodInput bars to the right
A pivot low is confirmed only after pivotPeriodInput bars to the right
Confirmed pivot values become new resistance or support liquidity levels
2) Level Storage and Line Creation
When a pivot is confirmed, the script creates a line starting at the pivot bar and stores it as a LiquidityLevel object:
line newL = line.new(bar_index , ph, bar_index, ph, color = resistanceColorInput, style = getLineStyle(lineStyleInput))
resistanceLevels.push(LiquidityLevel.new(ph, bar_index , newL))
The same logic applies to pivot lows for support levels.
To prevent excessive object growth, levels are capped:
if resistanceLevels.size() > maxLinesInput
(resistanceLevels.shift()).delete()
3) Relative Volume and Volume Filter
The script computes average volume over the last 20 bars and converts current volume into a percentage:
float volAvg = ta.sma(volume, 20)
float volRelative = (volume / volAvg) * 100
The volume filter is satisfied when either the filter is disabled or the current volume exceeds the average multiplied by the chosen multiplier:
bool isVolStrong = not useVolFilterInput or (volume > volAvg * volMultiplierInput)
4) Sweep and Break Conditions
Each active resistance level is checked for a sweep or a break:
bool priceSwept = high > lvl.price and close <= lvl.price
bool broken = close > lvl.price
Each active support level is checked similarly:
bool priceSwept = low < lvl.price and close >= lvl.price
bool broken = close < lvl.price
Interpretation:
A sweep requires a wick through the level and a close back across it
A break requires acceptance beyond the level on close
5) Sweep Confirmation Handling and Cleanup
When a sweep occurs with strong volume, the script sets a flag for alerts, draws highlight objects, prints labels, and removes the level from active tracking:
Resistance sweep flow:
if priceSwept and isVolStrong
buySweepOccurred := true
line.new(lvl.startBar, lvl.price, bar_index, lvl.price, color = C_SWEEP_BUY)
resistanceLevels.remove(i).delete()
Support sweep flow:
if priceSwept and isVolStrong
sellSweepOccurred := true
line.new(lvl.startBar, lvl.price, bar_index, lvl.price, color = C_SWEEP_SELL)
supportLevels.remove(i).delete()
If a level is broken, it is removed as invalid:
else if broken
resistanceLevels.remove(i).delete()
6) Volume Annotation Placement
On a sweep, the script computes the midpoint of the level segment in bar index space and prints RVOL percent:
int midX = math.round((lvl.startBar + bar_index) / 2)
label.new(midX, lvl.price, str.tostring(volRelative, "#") + "% VOL")
Placement is above for BSL sweeps and below for SSL sweeps to align with the direction of the liquidity being taken.
7) Alerts
Alert conditions and direct alerts are provided:
alertcondition(buySweepOccurred, "Buy Liquidity Sweep", "BSL Swept!")
alertcondition(sellSweepOccurred, "Sell Liquidity Sweep", "SSL Swept!")
The script also triggers runtime alerts including the close price once per bar close when a sweep occurs. Indicator
Indicator
Liquidity Pools + Sweep Signals [Metrify]If breakouts feel like a scam, it’s because they often function like one.
Most charts are taught like they’re a clean story of supply and demand. But real price action is messier: it’s a sequence of tests, traps, and collections. The market doesn’t need to “respect” your line, it needs to find liquidity.
And liquidity usually sits in predictable places: swing highs, swing lows, prior reaction points, the levels everyone can see.
This Liquidity Sweep Canvas is a market-structure overlay that tracks liquidity pools built from swing highs/lows, then monitors how price interacts with those pools over time (touches → sweeps → breaks/expiry). The goal is not to “predict” — it’s to map where liquidity is parked, highlight when it’s raided with rejection, and keep a clean, visual “canvas” of relevant pools near current market.
It builds two sides:
SELL liquidity pools (from pivot highs, shown in red)
BUY liquidity pools (from pivot lows, shown in teal)
Each pool is zoned around the pooled level, merges nearby levels (optional aggressiveness), tracks hits, and can transition through states:
Active (building / being respected)
Swept (liquidity taken + rejection confirmed)
Ended (broken through or expired)
Sweep logic in plain terms
A sweep is detected when price pierces beyond a pool boundary and then closes back through the pool’s midline in the opposite direction (rejection).
Bear sweep (SELL liquidity): price wicks above a SELL pool, then closes back below the pool mid.
Bull sweep (BUY liquidity): price wicks below a BUY pool, then closes back above the pool mid.
Optionally, you can require a second-step confirmation:
Displacement confirm waits for follow-through (within a small window) where price breaks beyond the sweep candle’s reference (with a minimum body size in ATR). This filters some noise, at the cost of being delayed.
🔥 Scoring system (how “quality” is decided)
Sweeps are common. Clean sweeps are not. We uses a weighted scoring model (0–100) so you can filter out weak sweeps and keep the ones that show stronger intent.
A sweep starts when price penetrates beyond the pool boundary (takes liquidity) and reclaims back inside the zone (closes through the pool mid). From there, a score is built from two layers:
✅ Layer 1 —> Sweep candle “core bundle” (base part)
This is computed immediately on the sweep candle (or stored if you require displacement). The base bundle blends:
Penetration: how deep the wick pushed beyond the pool in ATR terms (not “deeper is always better”, it’s shaped to reward a realistic sweet spot).
Reclaim strength: how much of the candle reclaimed back (close relative to the range).
Wick ratio: rejection wick size vs body (controlled by 'Wick Ratio Scale').
Body bias: bullish body for bull sweeps / bearish body for bear sweeps gets rewarded.
EMA context: measures whether the sweep is happening with a favorable distance relative to EMA 200.
Line age/maturity: longer pools can score differently via a length score, then get penalized by a separate age penalty.
🧠 Layer 2 —> Context add-ons
After the base bundle, the final score can include:
MSS context: a simple structural reference (recent swing extreme lookback) to rate whether the sweep is happening with useful positioning.
Effort score: combines range expansion (ATR) with volume vs volume MA to reward sweeps that show actual participation.
Displacement score (optional): if enabled, the sweep is only confirmed after follow-through within a small window.
How to use it
1. Build a two-stage decision: location bias, then trigger selection
Use pools to decide directional bias before you even consider entries. If price is pressing into SELL pools repeatedly and the dashboard shows dense sell-side activity, your bias shifts toward expecting a sell-side raid (sweep up then rejection) rather than a clean breakout. If price is pressing into BUY pools, same logic for downside raid and bounce. Then decide your trigger style manually:
If you trade fast mean reversion, you can use immediate sweeps as the “first alarm” and enter on the reclaim + tight invalidation.
If you trade safer confirmation, require displacement confirm, and only act once price has proven it can leave the pool with force.
Either way, the script helps you separate where it matters (pools) from where it doesn’t (middle of nowhere).
2. Use hit count to judge liquidity density and trap probability
The LP xN hit count is a manual edge if you treat it correctly: more hits generally implies more eyes, more orders, more liquidity, and therefore more potential for a meaningful raid. When you see a pool with high hits near current price, don’t assume it’s “strong support/resistance.” Instead, assume it’s a liquidity magnet.
If price repeatedly taps a high-hit pool without breaking cleanly, it often sets up a sweep (stop run + reverse).
If price breaks and stays outside with follow-through, that’s not a sweep environment, it’s a continuation environment.
So you use hit count to anticipate which levels are likely to be hunted, then use candle behavior + displacement to judge whether the hunt was successful and rejected.
3. Turn sweeps into ‘event markers’ for post-move structure mapping
Instead of treating a sweep as “enter now,” treat it as: a structural event happened here.
After a sweep prints, manually re-map microstructure: identify the last minor swing before the sweep, then track whether price breaks it (MSS/BOS style) and whether the first pullback respects that break.
4. Use the channel read as a regime filter (premium/discount logic)
The nearest pool edges effectively form a liquidity channel. Use it like a regime filter:
Inside SELL zone / premium: prioritize short-side narratives
Inside BUY zone / discount: prioritize long-side narratives
Middle channel: treat as uncertainty, tighten your standards (or step aside).
5. Use scoring as a ‘quality gate’, then you do the narrative check”
If you enable scoring, stop thinking of it as “higher score = higher win.” Think of it as a gate that filters out low-effort pokes. Once a high-score sweep prints, manually audit it.
6. Use it as a ‘sweep journal’ to study your market’s behavior
A very “pro” use is not trading it at all for a week. Turn on historical traces and sweep markers, and just observe: Which sessions produce the cleanest sweeps? Do high-score sweeps outperform low-score? Do confirmed sweeps reduce chop at the cost of late entries? Does your instrument sweep more on highs or lows? The dashboard counts help you quantify frequency. After you collect observations, you tune inputs (Swing Length, Merge Distance, Minimum Score, Volume thresholds) to match the instrument’s microstructure.
This is how you turn a generic sweep concept into a market-specific playbook—and the script becomes your data-driven visual log, not a guessing machine.
⚙️ Tuning tips (fast)
Too many pools / too noisy → increase Swing Length / Merge Distance.
Sweeps trigger too often → enable Activate Scoring and raise Min Score.
Wick quality not valued enough → reduce Wick Ratio Scale.
Effort scoring feels too easy/hard → adjust Min Volume / MA and Volume MA Length.
A higher score is not a guarantee of a better trade, it simply means the sweep event matched more of the model’s criteria (penetration, reclaim, rejection wick, effort, context components, and optional displacement). Markets are adaptive: what high quality looks like changes by instrument, timeframe, and session. Use scoring to reduce noise, then manually validate. Indicator
Protected Swings [LuxAlgo]The Protected Swings indicator identifies and confirms high-probability structural levels based on the interaction between liquidity sweeps, Fair Value Gaps (FVG), and Change in State of Delivery (CISD) logic. This tool aims to highlight "protected" highs and lows that are expected to remain intact during trend continuations or market reversals.
🔶 USAGE
The Protected Swings tool is designed to provide clear invalidation levels for stop placement and to help traders avoid false reversals by waiting for candle-body confirmation through specific price series.
🔹 Trend Reversals
A reversal setup occurs when the market sweeps a major liquidity level (such as a previous swing high or low) or taps into a high-timeframe FVG.
A Protected Swing High (PSH) forms after a sweep of a high followed by a close below the opening price of the up-close candle series that created that high. This suggests a shift to a bearish regime.
A Protected Swing Low (PSL) forms after a sweep of a low followed by a close above the opening price of the down-close candle series that created that low. This suggests a shift to a bullish regime.
🔹 Trend Continuation
Once Protected Swings are established, subsequent "stepping stones" often form. In a bearish trend, new PSHs will form as price wicks into internal FVGs and then closes back below the candle series that created the retracement high. These levels serve as trailing stop-loss points or areas to look for refined lower-timeframe entries.
🔹 Entry Refinement
Traders can use Protected Swings to refine Risk:Reward. When a higher-timeframe protected level is confirmed, users can drop to a lower timeframe and wait for a secondary protected swing to form. The "Confirmation Level" shown by the indicator represents the exact price point that must be breached to validate the "protected" status of that swing.
🔶 DETAILS
The script follows a multi-step logic to confirm Protected Swings:
🔹 Liquidity Sweeps
The indicator tracks structural pivots (Fractals) based on the "Sweep Sensitivity" setting. A sweep is detected only when the price wick exceeds a previous pivot high or low, but the candle body remains within the previous extreme. This "wick-only" break suggests liquidity is being grabbed (Stop Run) rather than a displacement break of structure occurring.
🔹 FVG Mitigations
The script detects Fair Value Gaps (3-candle imbalances). If enabled, a swing point is considered a candidate for a Protected Swing if it trades into an active FVG, even if a liquidity sweep of a major pivot did not occur.
🔹 Change in State of Delivery (CISD)
The core confirmation logic (CISD) requires the price to close through the "series."
For a Bullish Protected Swing , the script identifies the series of consecutive down-close candles leading into the low. The opening price of the first candle in that down-series becomes the Confirmation Level.
For a Bearish Protected Swing , it identifies the consecutive up-close candles. The opening price of the first candle in that up-series becomes the level.
The labels (PSL/PSH) only appear once a candle body closes past this level, ensuring the "State of Delivery" has shifted.
🔶 SETTINGS
🔹 Logic Settings
Sweep Sensitivity: Defines the number of bars required on both sides to confirm a structural pivot level to be used for detecting sweeps.
Include FVG Mitigations: When enabled, swings that tap into imbalances can trigger protected swing labels.
FVG Search Lookback: Determines how many bars back the script searches for active imbalances to use as context.
🔹 Visualization
Show Labels: Toggles the PSL (Protected Swing Low) and PSH (Protected Swing High) labels.
Show Confirmation Levels: Displays the horizontal lines representing the candle series opening price that triggered the confirmation.
Show Fair Value Gaps: Visualizes active imbalances on the chart.
Highlight Liquidity Sweeps: Highlights the specific portion of the wick that exceeded the previous structural pivot.
Colors: Customization for bullish and bearish elements and transparency for zones.
Indicator
Indicator
Filter Bar1. Indicator Name
Filter Bar
2. One-line Introduction
A trend-aware bar coloring system that visualizes market direction and strength through adaptive transparency based on regression scoring.
3. General Overview
Filter Bar+ is a minimalist but powerful trend visualization tool that colors chart bars according to market direction and momentum strength.
It analyzes the linear regression trend alignment over a specified lookback period and uses a pairwise comparison algorithm to determine whether the market is in a bullish, bearish, or neutral state.
The result is a "trend score" that gets normalized to reflect trend intensity (0~1).
Bar colors are then dynamically updated using the specified bullish or bearish base colors, where higher intensity results in more opaque (darker) bars, and weaker trends lead to lighter, faded tones.
If no strong trend is detected, bars are shown in gray, signaling indecision or neutrality.
The strength of this indicator lies in its simplicity—it doesn’t draw lines, waves, or shapes, but overlays insight directly onto the chart through smart color cues.
It’s particularly effective as a background filter for price action traders, scalpers, and anyone who prefers clean charts but still wants embedded directional context.
4. Key Advantages
🎨 Adaptive Bar Coloring
Bar color opacity increases with trend strength, offering instant visual confirmation without clutter.
📊 Quantified Trend Direction
Uses a regression-based scoring system to reliably detect uptrends, downtrends, or sideways markets.
⚖️ Customizable Sensitivity
Parameters like lookback period and tolerance percentage give users full control over signal responsiveness.
🧼 Clean Chart Presentation
No lines, shapes, or overlays—just color-coded bars that blend into your existing chart setup.
🚀 Lightweight & Fast
Minimal computational load ensures it works smoothly even on lower-end devices or multiple chart setups.
🔒 Secure Internal Logic
Algorithm is neatly encapsulated and optimized, with no critical logic exposed.
📘 Indicator User Guide
📌 Basic Concept
Filter Bar+ evaluates trend direction and strength using a pairwise comparison of linear regression values.
The result determines whether the market is bullish, bearish, or neutral, and adjusts bar colors accordingly.
It visually amplifies the current market state without drawing any indicators on the chart.
⚙️ Settings Explained
Lookback Period: Number of bars used to compare regression values
Range Tolerance (%): Minimum score required to label a trend as bullish or bearish
Regression Source: Data input used for regression (default: close)
Linear Regression Length: Period for generating the base regression line
Bull/Bear Base Colors: Choose colors to represent bullish or bearish bars
📈 Buy Timing Example
Bars are green (or user-set bullish color) and becoming more vivid
Indicates a strengthening bullish trend; helpful when used alongside breakout confirmation or support zones
📉 Sell Timing Example
Bars turn red (or your custom bearish color) with increasing opacity
Signals growing bearish pressure; acts as confirmation during short setups or breakdowns
🧪 Recommended Use Cases
Combine with volume, RSI, or price action setups for direction filtering
Ideal for clean chart strategies where visual simplicity is preferred
Use as a confirmation layer to reduce noise in sideways markets
🔒 Precautions
This is a visual filter, not a signal generator—use alongside other strategies for entries/exits
In choppy markets, bars may flicker between colors—adjust sensitivity as needed
Works best when you already have a directional thesis and want to validate it visually
Always test settings for your asset/timeframe before applying in live trades Indicator
Indicator
Cnagda Liquidit Trading SystemCnagda Liquidit Trading System helps spot where price is likely to trap traders and reverse, then gives simple, actionable Level to entry, place SL, and take profits with confidence. It blends imbalance zones, trend bias, order blocks, liquidity pools, high-probability fake Signal, and context-aware candle patterns into one clean workflow.
🟩🟥 Imbalance boxes: “Crowd rushed, gaps left”
What it is: Green/red boxes mark fast, one-sided moves where price “skipped” orders—think FVG-like zones that often get revisited.
Why it helps: Price frequently pulls back to “fill” these zones, creating clean retest entries with logical stops.
⏩How to use:
Green box = potential demand retest; Red box = potential supply retest. Enter on pullback into box, not on first impulse. Put stop on far side of box and aim first targets at recent swing points.
↕️ Swing bias (HH/HL vs LH/LL): “Which way is the road?”
What it is: Higher-highs/higher-lows = up-bias; Lower-highs/lower-lows = down-bias. system plots Buy/Sell OB levels aligned with that bias.
Why it helps: Trading with the broader flow reduces “hero trades” against institutions. Bias gives clearer entries and cleaner drawdowns.
⏩How to use:
Up-bias: look for long on Buy OB retests. Down-bias: look for short on Sell OB retests. Wait for a small rejection/engulfing to confirm before triggering.
🧱Order blocks: “Where big players remember”
What it is: last opposite-colored candle before an impulsive move—these zones often hold memory and reaction. system plots these as Buy/Sell OB lines.
Why it helps: Many breakouts pull back to the origin. Good entries often happen on retest, not on the breakout chase.
⏩ How to use:
Let price return into the OB, show wick rejection, and decent volume. Enter with stop beyond OB; define risk-reward before entry.
📊Volume coloring: “How Volume is move?”
What it is: Bar color reflects relative volume; inside bars are black. The dashboard also shows Volume and “Volume vs Prev.”
Why it helps: Patterns without volume often fade; volume validates strength and intent of moves.
⏩ How to use:
Favor entries where imbalance/OB/liquidity-grab coincide with higher volume. If volume is weak, reduce size or skip.
🧲 BSL/SSL liquidity pools: “Fishing for stops”
What it is: Equal highs cluster stops above (BSL); equal lows cluster stops below (SSL). system plots these and highlights the nearest one (“magnet”).
Why it helps: Price often sweeps these pools to trigger stops before reversing. This is a prime trap-reversal location.
⏩ How to use:
Watch nearest BSL/SSL. If price wicks through and closes back inside, anticipate a reversal. Trade reaction, not first poke. When price closes beyond, consider that pool mitigated and move on.
🟢🔴 Advanced liquidity grab: “Catch fakeout”
What it is: Bullish grab = makes a new low beyond a prior low but closes back above it, with a long lower wick, small body, and higher volume. Bearish is mirror. Labeled automatically.
Why it helps: It exposes trap moves (stop hunts) and often precedes true direction.
⏩ How to use:
Best when it aligns with a nearby imbalance/OB and supportive volume. Enter on reversal candle break or on retest. Stop goes beyond sweep wick.
🧠 Smart candlestick patterns (only in right place)
What it is: Engulfing, Hammer, Shooting Star, Hanging Man, Doji (with high volume), Morning/Evening Star, Piercing—but marked “effective” only if context (swing/trend/location) agrees.
Why it helps: same pattern in the wrong place is noise; in the right place, it’s signal.
⏩ How to use:
Location first (BSL/SSL/OB/imbalance), then pattern. Treat pattern as trigger/confirmation—one fresh label shows to keep chart clean.
🧭 Dashboard: “Context in a glance”
⏩ Reversal Level: current swing anchor—expect turns or reactions nearby; great for alerts and planning.
⏩ Volume vs Prev + Volume: Strength meter for signal candle—higher adds conviction.
⏩ Nearest Pool: next “magnet” area—look for sweeps/rejections there.
🧩Step-by-step trading flow (with mindset)
⏩ Set bias: HH/HL = long bias, LH/LL = short bias. Counter-trend only on clean sweeps with strong confirmation.
⏩ Find magnet: Check Nearest Pool (BSL/SSL). Focus attention there; it saves screen time.
⏩ Wait for event: Look for a sweep/grab label, or sharp rejection at pool/OB/imbalance. Avoid FOMO.
⏩ Add confluence: Stack 2–3 of these—imbalance box, OB, contextual pattern, supportive volume.
⏩Plan entry: Bullish: trigger above reversal candle high or take retest of FVG/OB. Stop below sweep wick/zone. Target at least 1:1.5–1:2.
Bearish: mirror above.
⏩Manage smartly: Take partials, move to breakeven or trail thoughtfully. Don’t drag stops inside zone out of emotion.
🎛️ Parameter tuning (to reduce human error)
⏩ swingLen: Smaller = faster but noisier; larger = cleaner but slower. Backtest first, then go live.
⏩ Tolerance (ATR or percent): ATR tolerance adapts to volatility (good for fast markets and lower TFs). Start around 0.15–0.30. In calm markets, try percent 0.05–0.15%.
⏩ minBarsGap: Start with 3–5 so equal highs/lows are truly equal—reduces false pools.
❌Common mistakes → ✅ Better habits
⏩Chasing every breakout → Wait for sweep/rejection, then confirm.
⏩Ignoring volume → Validate strength; cut size or skip on weak volume.
⏩Losing history of pools → If reviewing/backtesting, keep mitigated pools visible (dashed/faded).
⏩Over-tight tolerance/too small swingLen → Increases false signals; backtest to find balance.
📝 checklist (before entry)
⏩ Is there a nearby BSL/SSL and did a sweep/grab happen there?
⏩ Is there a close imbalance/OB that price can retest?
⏩ Do we have an effective pattern plus supportive volume?
⏩Is the stop beyond the wick/zone and RR ≥ 1:1.5?
•?((¯°·._.• 🎀 𝐻𝒶𝓅𝓅𝓎 𝒯𝓇𝒶𝒹𝒾𝓃𝑔 🎀 •._.·°¯((?• Indicator
