Order Block Finder [MHA Finverse]Order Block Finder is a sophisticated Smart Money Concepts (SMC) tool designed to identify and visualize institutional order blocks on your charts. This indicator helps traders spot key areas where smart money has placed their orders, providing valuable insights for potential support and resistance zones.
What are Order Blocks?
Order blocks are price zones where institutional traders have placed significant orders. This indicator identifies these zones by detecting pivot points in price action and tracking structural breaks in both internal (short-term) and swing (long-term) timeframes.
Key Features:
• Dual Structure Analysis
- Internal Order Blocks: Fast-moving blocks based on 5-bar pivots for short-term trading
- Swing Order Blocks: Slower blocks based on 50-bar pivots for position trading
- Display up to 20 order blocks per type
• Volume Metrics
Each order block displays two important metrics:
- Volume value: The total volume of the candle that formed the order block
- Percentage: Relative volume compared to all visible order blocks (always totals 100%)
Higher percentages indicate stronger institutional activity and more significant zones
• Smart Filtering System
- ATR Filter: Filters out high-volatility candles (>2x ATR) to focus on genuine order blocks
- CMR Filter: Uses Cumulative Mean Range for adaptive filtering across different market conditions
• Flexible Mitigation Options
Choose how order blocks are considered broken:
- High/Low: Order block breaks when price touches its boundary
- Close: Order block breaks only when candle closes through it
• Visual Customization
- Colored or Monochrome themes
- Adjustable text size for volume metrics
- Customizable colors for bullish and bearish blocks
- Historical or Present mode for clean chart analysis
• Built-in Alert System
- Real-time alerts when order blocks are mitigated
- Individual toggles for each alert type
- Clear emoji indicators (🔵 Bullish, 🔴 Bearish)
- Compatible with TradingView's alert system
How It Works:
The indicator identifies order blocks by:
1. Detecting pivot highs and lows in price structure
2. Monitoring when price crosses these pivots (structure breaks)
3. Finding the highest/lowest volatility-filtered candle in the pivot zone
4. Marking this candle as an order block with its volume data
5. Removing blocks when the price mitigates them
Order blocks with higher volume percentages represent stronger institutional interest and are typically more reliable for trading decisions.
Best Practices:
- Use Internal OBs for day trading and scalping
- Use Swing OBs for swing trading and position entries
- Pay attention to blocks with higher volume percentages
- Combine with other SMC concepts for confirmation
Perfect for traders who follow Smart Money Concepts, ICT methodology, and institutional trading analysis.
Disclaimer:
This indicator is provided for educational and informational purposes only. It should not be considered as financial advice or a recommendation to buy or sell any financial instrument. Trading involves substantial risk of loss and is not suitable for all investors. Past performance does not guarantee future results. Always conduct your own research and consult with a qualified financial advisor before making any trading decisions. The creator of this indicator assumes no responsibility for any losses incurred from its use.
Smartmoneyconcepts
Market Structure High/Low [MaB]📊 Market Structure High/Low
A precision indicator for identifying and tracking market structure through validated swing highs and lows.
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
🎯 KEY FEATURES
• Automatic Swing Detection
Identifies structural High/Low points using a dual-confirmation system (minimum candles + pullback percentage)
• Smart Trend Tracking
Automatically switches between Uptrend (Higher Highs & Higher Lows) and Downtrend (Lower Highs & Lower Lows)
• Breakout Alerts
Visual markers for confirmed breakouts (Br↑ / Br↓) with configurable threshold
• Sequential Labeling
Clear numbered labels (L1, H2, L3, H4...) showing the exact market structure progression
• Color-Coded Structure Lines
- Green: Uptrend continuation legs
- Red: Downtrend continuation legs
- Gray: Trend inversion points
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
⚙️ CONFIGURABLE PARAMETERS
• Analysis Start Date: Define when to begin structure analysis
• Min Confirmation Candles: Required candles for validation (default: 3)
• Pullback Percentage: Minimum retracement for confirmation (default: 10%)
• Breakout Threshold: Percentage beyond structure for breakout (default: 1%)
• Table Display: Toggle Market Structure
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
💡 HOW IT WORKS
1. Finds initial swing low using lookback period
2. Tracks price movement for potential High candidates
3. Validates candidates with dual criteria (candles + pullback)
4. Monitors for breakout above High (continuation) or below Low (inversion)
5. Repeats the cycle, building complete market structure
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
🔧 BEST USED FOR
• Identifying key support/resistance levels
• Trend direction confirmation
• Breakout trading setups
• Multi-timeframe structure analysis
• Understanding market rhythm and flow
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
⚠️ NOTES
- Works best on higher timeframes (1H+) for cleaner structure
- Statistics become more reliable with larger sample sizes
- Extension ratios use σ-filtered averages to exclude outliers
- Pullback filter automatically bypasses during extended impulsive moves
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
Smart Money Concepts [Kodexius]Smart Money Concepts is a price action framework designed to integrate market structure, liquidity behavior, and inefficiencies into a single, readable view. Rather than acting as a signal generator, it serves as a live market map highlighting where price has displaced, where liquidity may be resting, which zones remain valid, and how that context updates as new candles print.
What separates this script from typical “SMC bundles” is not the presence of familiar concepts like swings, order blocks, FVGs or liquidity sweeps. The value is in the engine design and how the components are maintained together as a consistent state, with automatic pruning and prioritization so the chart stays usable over time. Many tools can draw boxes, but fewer tools manage the lifecycle of those zones, reduce overlap, rank relevance, and keep the display focused on what still matters near current price.
At the core is a structure model that tracks directional state and labels structural transitions as they happen. CHoCH and BoS are not just printed whenever price crosses a line. Each event is anchored to a swing reference and handled in a way that reduces repeated triggers from the same context, helping you see genuine transitions versus minor noise. This gives structure a “narrative” across time instead of a cluttered sequence of identical labels.
Order blocks are built from the most relevant candle within the post break window and displayed as true zones that extend forward while they remain valid. Beyond the zone itself, the script adds context that is usually missing in basic OB implementations: a volumetric pressure visualization and a displacement strength score that is normalized and ranked over a rolling window. In practice, this creates an information hierarchy. You can quickly see which zones carried more participation, whether the internal push was dominated by buying or selling pressure, and whether the move that created the zone had meaningful displacement relative to recent history. This is designed to help prioritization, not to claim prediction.
Imbalances are handled as a dedicated module with multiple detection modes (FVG, VI, OG, IFVG) and optional MTF logic so you can map inefficiencies from a higher timeframe while executing on a lower timeframe. Each imbalance is displayed as a zone with a midline reference, and mitigation behavior can be tuned (wick or close). IFVG adds lifecycle depth by tracking inversion behavior rather than simply deleting the zone, which can be useful for monitoring how price rebalances and flips inefficiencies over time. An optional sentiment style internal fill is available for visual context, but it is intentionally framed as informational rather than a “buy/sell meter.”
Liquidity is treated as an event driven layer. Pivot highs and lows are tracked as potential liquidity pools, then monitored for sweeps and rejection behavior. If you enable EQH/EQL logic, the script can label equal highs and lows during the sweep process to highlight common resting liquidity formations. A volume filter is available to reduce low quality levels, aiming to keep the liquidity map focused on swings that occurred with meaningful participation rather than every small fluctuation.
Swing Failure Patterns (SFP) are included as a separate confirmation style tool that focuses on rejection after liquidity is taken. The module supports optional volume validation using lower timeframe volume distribution outside the swing level, which helps filter some low quality SFPs on noisy instruments. The output is a cleaner set of events intended to complement structure, liquidity and zones, not replace discretionary decision making.
For higher timeframe context, the HTF candle projection panel can display a compact set of higher timeframe candles to the right of current price, with classic or Heikin Ashi style and configurable sizing, spacing and labels. This allows you to maintain HTF awareness without switching charts, which is especially helpful when structure and zones are being interpreted across multiple timeframes.
Finally, the alert framework is designed around well defined structural and zone states. Alerts cover structural shifts (CHoCH, BoS), liquidity sweeps, new and broken order blocks, breaker behavior (if enabled), new and approached imbalances, premium and discount entries, trendline events, and SFP detection. These alerts are intended as monitoring prompts so you can review context, not as automated trade execution signals.
Every major component is modular and configurable. You can run a minimal structure only layout or enable a full framework with zones, imbalances, liquidity, SFP and HTF projection. The guiding principle is chart clarity and relevance: keep the most important information visible, reduce overlap and stale objects, and maintain a consistent view of how price is interacting with liquidity and value over time.
🔹 Features
🔸 Market Structure Engine (CHoCH and BoS)
This script automatically tracks zigzag based market structure and differentiates between:
CHoCH (Change of Character) : the first meaningful structural shift that suggests the prior directional leg is weakening.
BoS (Break of Structure) : continuation breaks that confirm structure extension in the active direction.
Instead of relying on plain pivot dots, our market structure swings are built with a lightweight zigzag style engine that tracks direction and “locks in” the true leg extreme only when the leg flips. This produces cleaner, more consistent swing highs/lows for BOS/CHoCH than simple left/right pivot checks.
Bullish CHoCH:
Bearish CHoCH:
Bullish BoS:
Bearish BoS:
🔸 Order Blocks with Volumetric and Displacement Insight
The script identifies recent bullish and bearish order block zones around meaningful structural reactions and keeps the display focused on the most relevant areas. Instead of drawing a static rectangle and leaving it there forever, each zone is maintained as an active region on the chart and can be limited by a user defined visibility depth to avoid clutter. When enabled, the overlay also adds compact volume based context inside the block so you can quickly compare relative participation between recent zones and see whether the origin move showed strong follow through versus a softer transition. The intention is to provide structured context and cleaner prioritization on the chart, not to present a trade call or a guaranteed reaction level.
Bullish Order Block:
Bearish Order Block:
Order blocks are derived from the structure shifts, marking the institutional “origin zone” behind a decisive move and projecting it forward as a live area of interest. In practice, it highlights the candle cluster where price last rebalanced before expanding away, so you can track potential retests with context instead of guessing.
Inside each order block, the internal bars act as a compact strength meter green vs red summarizes the relative bullish vs bearish participation, while the blue segment reflects the “departure force” (displacement/momentum) away from the zone. It’s meant to help you scan which blocks left clean and strong versus those that moved out more slowly or with mixed pressure.
🔸 Breaker Blocks & Mitigation Tracking
Tracks when previously identified order blocks fail and converts them into breaker blocks, visually marking a change in how price is interacting with that zone.
Bullish Breaker Block :
Bearish Breaker Block :
Separate handling of bullish and bearish breakers with clear color differentiation.
Includes optional “mitigation” logic using either wick or close to determine when a block is considered broken or mitigated.
Breaker blocks are updated and removed dynamically as price trades through them, keeping the chart focused on current, active zones.
🔸 Imbalances
The imbalance module maps common price inefficiencies as zones, with support for multiple detection styles such as Fair Value Gaps, volume style imbalances, opening gaps, and an inverted gap mode. Each imbalance is drawn as a practical area on the chart with a midpoint reference, so you can quickly see where price may be revisiting unbalanced movement. You can also choose how mitigation is evaluated (wick or close) and optionally run imbalance detection on a separate timeframe for cleaner higher timeframe context while staying on your execution chart.
Fair Value Gaps:
Inverse Fair Value Gaps:
Opening Gaps:
🔸 Liquidity Sweeps, EQH/EQL, and Optional Volume Filter
Liquidity levels are derived from swing highs and lows and then monitored for sweep behavior, where price trades beyond a prior level and rejects back. If you enable EQH/EQL marking, the script can highlight equal highs and equal lows behavior around those liquidity areas to make common pool formations easier to spot. An optional volume filter can be used to reduce tracking of low participation swings, helping keep the liquidity layer focused and less noisy on instruments that produce frequent small pivots.
Sellside Liquidity Sweep Definition:
Buyside Liquidity Sweep Definition:
Highlights equal highs (EQH) and equal lows (EQL) when sweeps occur, marking where price probed above/below prior liquidity and then rejected.
Optional volume filter to ignore low volume swings and focus on more meaningful liquidity zones.
🔸 Premium, Discount, and Equilibrium
The premium and discount view provides a simple contextual map of where price is trading within a measured range, alongside an optional equilibrium line as a midpoint reference. This is intended as a higher level framing tool to help you avoid treating every price location the same, especially when combining structure with reaction zones. Price labels can be enabled for quick orientation, and the display updates as the underlying range evolves.
Projects premium and discount bands based on a dynamically measured range, offering a simple view of where price is trading relative to that range.
Draws separate Premium and Discount boxes with optional price labels for quick orientation.
Optional mid line (equilibrium) to visualize the “50%” of the current range, often used as a reference for balanced versus extended price.
Zones auto update as the underlying range evolves, with logic to prevent stale levels from cluttering the chart.
🔸 Trend Channels
When enabled, the trend module draws swing based diagonal structure using trendlines and a channel style visualization. You can tune sensitivity and choose whether the source should be depending on how you prefer to read trend behavior. The channel is maintained dynamically so you can keep directional context without manually drawing and constantly adjusting diagonal lines, and the script can highlight basic break behavior when price pushes beyond the active diagonal reference.
🔸 Swing Failure Pattern (SFP) Detector
The SFP module highlights common swing failure behavior, where price briefly trades beyond a swing level and then reclaims it, often reflecting a liquidity grab followed by rejection. Bullish and bearish SFPs can be enabled independently, and the display is designed to keep the key level and the rejection visible without excessive clutter. Optional volume validation can be used as a filter, so you can choose whether you want the detector to be more permissive or more selective based on participation characteristics.
🔸 HTF Candle Projection Panel
The HTF panel projects a compact set of higher timeframe candles to the right of price, giving you higher timeframe context without switching charts. You can select classic candles or Heikin Ashi style, adjust the scale and spacing, and optionally display reference lines and labels for OHLC values. This is a visual context tool intended to support multi timeframe reading, not a replacement for your own higher timeframe analysis.
In addition to projecting higher timeframe candles, the HTF panel can also detect and visualize higher timeframe liquidity sweeps directly within the projected candle set. The script monitors each completed HTF candle’s high and low and evaluates subsequent HTF candles for sweep behavior i.e., when price briefly trades beyond a prior HTF extreme but fails to hold acceptance beyond it (filtered using the later candle’s body positioning). When a sweep is detected, the panel draws a dotted sweep line and marks the event, allowing you to spot HTF stop runs and failed breaks without switching timeframes. Sweeps are dynamically invalidated if a later HTF candle shows genuine acceptance beyond that level, ensuring the display stays context relevant and avoids stale markings. This turns the HTF projection from a passive visualization into an actionable context layer for identifying HTF liquidity events while executing on lower timeframes.
🔸 Alerts
Alerts are included for the most practical events produced by the overlay, such as structure shifts (CHoCH and BoS), liquidity sweeps, new and invalidated zones, price approaching recent zones, imbalance creation and mitigation, premium or discount entries, trendline events, and SFP detections. The alerts are designed to function as a monitoring layer so you can be notified when something changes in your mapped context, rather than acting as standalone trade instructions.
🔸 Originality & Usefulness
This script is not a collection of separate SMC drawings layered on top of price. It is built as a unified price action engine where market structure, order blocks, inefficiencies, and liquidity are produced from the same evolving state. That matters because most SMC indicators treat these concepts as independent overlays, which often leads to contradictory markings and excessive clutter. Here, the design priority is consistency and readability: modules update in sync, older elements are managed, and the chart stays usable during live conditions.
A key differentiator is the internal swing logic, which functions like a compact zigzag style structure engine. Instead of reacting to every minor fluctuation, it aims to focus on meaningful swing decisions and treat structure as a sequence. This reduces repetitive labeling and makes structural transitions easier to follow. Structure events are anchored to the swing that defined them and are designed to trigger in a clean, non spammy way, which is critical for anyone who uses structure as a workflow backbone.
The structure layer is intentionally narrative oriented. It separates a transition event from continuation events, so CHoCH is used to highlight the first meaningful shift after an established leg, while BoS is used to mark follow through in the same direction. This is not a prediction claim. It is a clarity feature that helps users read “phase changes” versus “continuation” without constantly second guessing whether the script is just printing noise.
Order blocks are where this script becomes especially distinctive compared to typical SMC tools. Instead of drawing identical rectangles, each block is rendered with an internal gauge that communicates participation and directional dominance at a glance. The zone is visually segmented to reflect bullish and bearish pressure components, and it also carries a volume readout plus a relative weight compared to other recent blocks. This creates a ranked view of blocks rather than an unfiltered pile. In practice, you can prioritize zones faster because the script surfaces which blocks had more meaningful participation and whether the internal push looked one sided or mixed. The result is less subjective filtering and a cleaner chart.
Imbalances are handled as structured inefficiency zones with clear references and optional context. Beyond drawing the zone and midpoint, the script can overlay a sentiment style gauge that divides the imbalance into bullish and bearish portions and updates as new data comes in. The practical value is that you can see whether an inefficiency remains strongly one sided or is gradually being balanced. This turns imbalances from static boxes into a living context layer, which is particularly useful when you monitor reactions over time instead of treating every touch the same.
Liquidity is treated as an event driven tracking system rather than simple pivot plotting. Liquidity pools are identified from swing behavior and can be gated through a participation filter so the script focuses on levels that formed with meaningful activity rather than low quality noise. Once tracked, levels are monitored for outcomes like sweeps and equal high/low behavior, and then updated or retired when they are decisively resolved. This prevents the display from accumulating stale levels and keeps the liquidity layer focused on what is still relevant now.
Swing failure patterns are integrated as selective events rather than continuous spam. The intent is to produce fewer but more structurally meaningful SFPs, aligned with the liquidity narrative, instead of printing clusters around the same price area. This keeps the pattern readable and reinforces the “event based” design philosophy across the script.
Higher timeframe context is supported through a compact HTF projection panel that provides quick orientation without forcing constant timeframe switching. It lets you see where current price action sits inside a larger timeframe candle and range, which helps maintain consistency when you are executing on a lower timeframe but respecting higher timeframe structure.
Disclaimer: This indicator is for educational and analytical purposes only. It does not provide financial advice, and it does not guarantee results.
🔹 How to Use
This tool is designed to support multiple trading styles, but it is most effective when you treat it as a top down mapping and decision support tool. A practical workflow looks like this.
1) Establish higher timeframe bias and context
Start on your reference timeframe such as H4 or Daily and read the market’s dominant story first. Use the Market Structure Engine to identify whether the market is in continuation mode or transition mode. The goal is to avoid executing lower timeframe ideas that conflict with the larger structure narrative.
Use the HTF Candle Projection Panel as a fast orientation aid. It helps you judge whether current price is building acceptance near the highs of the larger candle, rotating back toward its open, or rejecting from its extremes. This is especially useful when you execute on lower timeframes but want to stay aligned with higher timeframe positioning.
Add Premium and Discount framing to understand location. When price is trading in premium, continuation longs are often more selective and require stronger confirmation, while shorts may have better location if structure supports it. When price is in discount, the opposite applies. Treat this as location context, not a rule.
2) Map your key reaction zones with prioritization
Next, build your map of where reactions are most likely to occur. Enable Order Blocks with Volumetric Insight to highlight the most relevant origin zones that form after important structure events. Keep your focus on the most recent blocks and adjust the visible depth so the chart stays clean.
Use the internal gauge and participation readouts to prioritize. Instead of treating every zone as equal, treat higher participation blocks as primary candidates and lower participation blocks as secondary. The bullish and bearish split inside the gauge helps you quickly judge whether the zone formed from a clearly one sided push or a more mixed move, which can inform how strict you want to be with confirmation on a retest.
If you use Breaker Blocks, treat them as role shift zones. They are especially useful when the market has clearly transitioned and you want to track where a previously defended origin area may become a meaningful retest level later.
3) Layer in inefficiencies only where they add clarity
If your workflow includes imbalances, add them selectively to avoid visual overload. Use Fair Value Gaps, Volume Imbalances, or Opening Gaps as secondary reaction areas that often sit inside, near, or between larger zones.
If you enable the internal sentiment gauge, read it as context rather than a signal. It is meant to help you see whether the imbalance remains one sided or has started to balance out as price develops. A strongly one sided presentation can support the idea of continuation through the zone, while a more balanced presentation can support the idea of deeper mitigation or chop. Use it to refine expectations, not to force entries.
4) Track liquidity as events, not as static levels
Enable Liquidity Sweeps and EQH/EQL tagging to highlight where resting liquidity is likely concentrated and when it gets taken. The main value here is narrative: you can see when price runs obvious highs or lows and whether it immediately rejects back into structure or accepts beyond the level.
If you use the volume filter, treat it as a quality gate. The point is to ignore small, low participation swings and keep the liquidity layer focused on levels that formed with meaningful activity. This tends to reduce noise and makes sweeps and equal level behavior more relevant.
Combine the liquidity layer with the Swing Failure Pattern detector to isolate moments where liquidity is taken and then rejected. The cleanest use is when SFPs occur at or near your pre mapped reaction zones, after a sweep, and in alignment with your higher timeframe bias.
5) Refine execution timing on your entry timeframe
Drop to your execution timeframe and use local structure shifts as timing tools. CHoCH and BoS on the lower timeframe can help you see when micro structure is flipping in your intended direction after price interacts with your mapped zone.
If you use the Trend Channel framework, treat it as diagonal context rather than strict support and resistance. A channel helps you see where price is riding the trend and where it is deviating. This can help you time entries by waiting for price to re enter the corridor, show rejection near a boundary, or confirm a shift by building structure outside the channel.
A common practical sequence is: price reaches a mapped OB or imbalance area, liquidity gets taken, price rejects, micro structure begins to flip, and then you execute with your own confirmation and risk rules. The tool helps you see each step clearly, but your plan determines what is sufficient confirmation.
6) Use alerts as monitoring, not as standalone signals
Set alerts only for events that are meaningful to your workflow, such as:
-fresh CHoCH or BoS in your preferred direction
-new or invalidated order blocks and breaker blocks
-price approaching the most recent priority zones
-liquidity sweeps and EQH/EQL interactions
-new SFP events
-entry into premium or discount and interaction with HTF projection levels
-imbalance creation, mitigation, or approach
Treat alerts as prompts to check the chart, not as automatic entries or exits. This script is designed as a mapping and decision support tool. Trade execution, confirmation, and risk management remain entirely dependent on your own strategy and discretion.
🔴 Price Action Practical Notes
💠 Market structure
Market structure is the framework used to describe how price organizes itself into swings. It is built from successive swing highs and swing lows, and it is used to decide whether the market is expanding upward, expanding downward, or transitioning. A practical structure model focuses on “meaningful” turning points rather than every minor fluctuation, because the goal is to capture intent and flow, not noise.
💠 Swing highs and swing lows
A swing high is a local peak where price stops advancing and begins to rotate lower, while a swing low is a local trough where selling pressure pauses and price rotates higher. Swings matter because many traders anchor risk, liquidity, and entries around them. The stronger the reaction away from a swing, the more likely it is to be referenced again as a decision point.
💠 Break of structure
A break of structure is the event where price decisively exceeds a prior swing in the direction of the prevailing move. In practice, it is used as confirmation that a directional leg is still active and that liquidity resting beyond the swing has been taken. This concept is less about predicting and more about validating continuation.
💠 Change of character
A change of character is a structural break that signals transition rather than continuation. Instead of breaking a swing in the same direction as the recent trend, price breaks a key swing in the opposite direction, suggesting that control may be shifting. It is often treated as an early warning that the market may be moving from continuation into reversal or deeper pullback conditions.
💠 Order blocks
An order block is commonly described as the last opposing candle or consolidation zone that precedes a strong directional expansion. The idea is that this area represents a footprint of aggressive execution and unfilled interest. When price revisits it later, it can act as a reaction zone because participants who missed the move may defend it, or because remaining orders may still exist there.
💠 Mitigation and invalidation of a zone
Mitigation describes the process of price returning to a zone and “consuming” the remaining interest there. A zone is typically considered invalidated when price trades through it in a way that implies the resting orders were absorbed and the area no longer has protective value. Some approaches treat a wick through the boundary as enough to invalidate, while others require a candle close beyond the boundary to confirm that the level has truly failed.
💠 Breaker blocks
A breaker block is an order block concept that changes role after being invalidated. When a previously respected zone fails, it can later become a reaction area in the opposite direction because trapped participants may use the retest to exit, or because the market may recognize it as a new supply or demand reference. Breakers are often treated as “failed zones that become liquidity magnets” and are closely watched on retests.
💠 Liquidity and liquidity pools
Liquidity is the availability of resting orders that allow large transactions to execute with minimal slippage. In chart terms, liquidity pools often form around obvious swing highs and lows, equal highs and lows, and clear ranges. These areas attract price because they contain clustered stops and entries that can be used to fuel continuation or trigger reversals through rapid order flow shifts.
💠 Liquidity sweeps
A liquidity sweep is a move where price briefly trades beyond a known liquidity pool and then returns back inside, often closing back within the prior range. The concept implies that stops were triggered and liquidity was captured, but that continuation beyond the swept level did not sustain. Sweeps are frequently used as context for reversals or for confirming that a “cleanout” occurred before a directional move.
💠 Equal highs and equal lows
Equal highs and equal lows describe repeated swing levels that form a flat or nearly flat top or bottom. They matter because they concentrate liquidity. Many traders place stops just beyond these repeated levels, and many breakout traders place entries around them. The result is a dense cluster of orders that can be targeted efficiently by price.
💠Imbalances and inefficiencies
Imbalances represent zones where price moved so quickly that it left behind inefficient trading, meaning fewer transactions occurred in that region compared to surrounding areas. The underlying idea is that markets often revisit these areas to rebalance, fill gaps, or complete unfinished business. Imbalances are treated as areas of interest for pullback entries, targets, or reaction zones.
💠 Fair value gap
A fair value gap is a specific form of imbalance commonly framed as a three candle displacement that leaves a gap between candles, indicating rapid repricing. Traders use it as a proxy for inefficiency: if price returns, it may partially or fully fill the gap before continuing. The midpoint of the gap is often treated as a particularly relevant reference, but whether price respects it depends on context.
💠 Inverted fair value gap
An inverted fair value gap is the idea that once an imbalance is “broken” in a meaningful way, the zone can flip its behavior. Instead of acting like a supportive zone, it may become resistive (or vice versa) on a later retest. Conceptually, this is similar to role reversal: what once behaved as a continuation aid can become a rejection zone after failure.
💠 Premium, discount, and equilibrium
Premium and discount describe where price sits relative to a defined recent range. Premium is the upper portion of that range and discount is the lower portion. Equilibrium is the midpoint. The concept is mainly used to align trade direction with location: buying is generally more attractive in discount and selling is generally more attractive in premium, assuming you are trading mean reversion within a range or seeking favorable risk placement within a broader trend.
💠 Swing failure pattern
A swing failure pattern is a reversal archetype where price breaks a known swing level, fails to hold beyond it, and returns back through the level. The logic is that the breakout attempt attracted orders and triggered stops, but the market rejected the extension. SFPs are often considered higher quality when the failure is followed by a decisive move away and when it aligns with a broader liquidity narrative.
💠 Higher timeframe context
Higher timeframe context means framing intraday or lower timeframe signals within the structure of a larger timeframe. This can include aligning trades with higher timeframe swings, using higher timeframe candles as reference for open/high/low behavior, and avoiding taking counter trend signals when the larger timeframe is strongly directional. The purpose is to improve signal quality by ensuring the smaller timeframe idea is not fighting a dominant larger flow.
💠 Trend channels
A trend channel is a structured way to visualize a market’s directional “lane” by framing price between two roughly parallel boundaries. The central idea is that trending price action often oscillates in a repeatable corridor: pullbacks tend to stall around one side of the lane, while impulses tend to extend toward the opposite side. Instead of treating trend as a single line, a channel treats trend as an area, which better reflects real market behavior where reactions occur in zones rather than at perfect prices.
A channel typically has three functional references: a guiding line that represents the prevailing slope, an upper boundary that approximates where bullish expansions tend to stretch before mean reversion, and a lower boundary that approximates where bearish pullbacks tend to terminate before continuation. The space between boundaries represents the market’s accepted path. When price stays inside this corridor, the trend is considered healthy. When price repeatedly fails to progress within it, the trend is weakening.
Channels are commonly used for timing and location. In an uptrend channel, pullbacks into the lower portion of the corridor are often treated as higher quality “location” for continuation attempts, while pushes into the upper portion are treated as extension territory where risk of a pause or retracement increases. In a downtrend channel, the logic is mirrored: rallies into the upper portion are often treated as sell side location, and moves into the lower portion are treated as extension territory. The channel does not predict direction by itself; it provides a disciplined map for where continuation is more likely versus where momentum is more likely to cool.
A key concept is acceptance versus deviation. If price briefly pierces a boundary and snaps back inside, that is often interpreted as a deviation, meaning the market tested outside the lane but did not accept it. If price holds outside the corridor and begins to build new swings there, that suggests acceptance and a potential regime change: either a new channel with a different slope, a shift into range, or a broader reversal context. This is why channels are most useful when you treat them as a framework for evaluating behavior, not as rigid support and resistance.
FVG vertical Created by Alphaomega18
🎯 What is an FVG (Fair Value Gap)?
A Fair Value Gap is a price imbalance created by a mismatch between buyers and sellers, formed by 3 consecutive candles where:
Bullish FVG: The low of the current candle is above the high of the candle 2 periods ago
Bearish FVG: The high of the current candle is below the low of the candle 2 periods ago
⚙️ Indicator Settings
Display Group:
Show Bullish vertical FVG: Display bullish vertical FVGs (green) ✅
Show Bearish vertical FVG: Display bearish vertical FVGs (red) ✅
Box Extension (bars): Zone extension duration (1-50 bars, default: 10)
Show Labels: Display labels with gap size 🏷️
Remove When Filled: Automatically remove filled zones ✅
📊 Visual Elements
FVG Zones:
🟢 Green = Bullish vertical FVG (potential support zone)
🔴 Red = Bearish vertical FVG (potential resistance zone)
Labels:
Show gap size in points
Positioned at the beginning of each zone
Dashboard (top right corner):
Real-time count of active FVGs
🟢 = Number of bullish vertical FVGs
🔴 = Number of bearish vertical FVGs
Candle Coloring:
Light green background = Candle forming a bullish vertical FVG
Light red background = Candle forming a bearish vertical FVG
🎯 How to Use the Indicator
1. Installation:
Open TradingView
Click "Indicators" at the top of the chart
Search for "FVG Clean" or paste the code in the Pine Editor
2. Trading Strategies:
Support/Resistance:
Bullish vertical FVGs act as support zones
Bearish vertical FVGs act as resistance zones
Price tends to return to "fill" these gaps
Position Entries:
Long: Wait for a return to a bullish vertical FVG + confirmation
Short: Wait for a return to a bearish vertical FVG + confirmation
Position Management:
Place stops below/above FVGs
Use FVGs as price targets
A filled FVG loses its validity
🔔 Alerts
The indicator includes 2 configurable alert types:
Bullish vertical FVG: Triggers when a new bullish vertical FVG forms
Bearish vertical FVG: Triggers when a new bearish vertical FVG forms
To configure: Right-click on chart → "Add Alert" → Select desired alert
💡 Usage Tips
✅ Do:
Combine with other indicators (volume, momentum)
Wait for confirmation before entering
Use across multiple timeframes
Respect your risk management
❌ Don't:
Trade solely on FVGs without confirmation
Ignore the overall market trend
Overload your chart with too many zones
🔧 Parameter Optimization
Scalping (1-5min):
Box Extension: 5-10 bars
Remove When Filled: Enabled
Day Trading (15min-1H):
Box Extension: 10-20 bars
Remove When Filled: Enabled
Swing Trading (4H-Daily):
Box Extension: 20-50 bars
Remove When Filled: As preferred
📈 Performance
Maximum 100 FVGs of each type in memory
Automatic removal of oldest ones
Optimized to not slow down your chart
Compatible with all markets and timeframes
FVG with Fibonacci Levels [MHA Finverse]FVG with Fibonacci Levels - Professional Fair Value Gap Indicator
This advanced Fair Value Gap (FVG) indicator automatically identifies and tracks market imbalances with integrated Fibonacci retracement levels, providing traders with precise entry and exit opportunities.
Key Features:
Smart Gap Detection
• Automatically identifies bullish and bearish fair value gaps in real-time
• Customizable minimum gap percentage filter to avoid noise
• Visual color-coded boxes for easy identification
Fibonacci Integration
• Built-in 0.5 and 0.618 Fibonacci retracement levels
• Fully customizable fib levels, colors, and line styles
• Helps identify optimal entry zones within each gap
Intelligent Gap Management
• Tracks multiple gaps simultaneously (up to 20)
• Automatic gap mitigation detection (Close or Wicks)
• Option to remove or highlight filled gaps
• Auto-hide boxes after specified bar count
Advanced Alert System
• Alerts when gaps are filled
• Fibonacci level touch alerts for both 0.5 and 0.618 levels
• Separate alerts for bullish and bearish setups
• Customizable alert preferences
Clean Visual Display
• Transparent boxes that don't clutter your chart
• Extending lines that update in real-time
• Customizable colors for both bullish and bearish gaps
• Option to change border style when gaps are filled
Perfect For:
Smart Money Concepts (SMC) traders, Price Action traders, and anyone looking to trade market structure and liquidity gaps with precision.
How to Use:
The indicator draws boxes around identified fair value gaps and extends them forward until they are filled. Fibonacci levels within each gap provide optimal entry zones. Set up alerts to get notified when price interacts with these key levels.
Credits
Special thanks to Quant Vue for their code examples and inspiration that contributed to the development of this indicator.
Disclaimer:
This indicator is for educational and informational purposes only. It does not constitute financial advice. Trading involves substantial risk of loss. Always conduct your own research and consider your risk tolerance before making any trading decisions. Past performance does not guarantee future results.
Smart Money Concepts [MHA Finverse]A comprehensive Smart Money Concepts (SMC) indicator designed to identify institutional trading behavior and market structure shifts. This tool helps traders align with "smart money" by detecting key supply and demand zones, structural breaks, and liquidity patterns.
Core Features
Market Structure Analysis
- Real-time Internal Structure: Detects short-term BOS (Break of Structure) and CHoCH (Change of Character) with customizable filters
- Swing Structure: Identifies major trend shifts and structural breaks on higher timeframes
- Adjustable pivot detection with customizable swing point visualization
- Strong/Weak High/Low identification for bias confirmation
Order Blocks (OB)
- Internal and Swing Order Blocks with independent control
- Volume-based metrics showing OB strength and percentage contribution
- Two filtering methods: ATR-based and Cumulative Mean Range
- Flexible mitigation options (Close or High/Low)
- Display up to 20 order blocks per type with auto-cleanup on mitigation
- Color-coded zones with transparency control
Liquidity Detection
- Equal Highs (EQH) and Equal Lows (EQL) identification
- Threshold-based detection using ATR calculation
- Visual confirmation lines connecting equal levels
- Adjustable sensitivity and bar confirmation settings
Fair Value Gaps (FVG)
- Multi-timeframe FVG detection
- Auto-threshold calculation based on price momentum
- Bullish and Bearish gap visualization
- Extendable gap boxes for tracking unfilled imbalances
Premium & Discount Zones
- Automated premium, equilibrium, and discount zone plotting
- Based on current swing range extremes
- Visual representation of optimal entry zones
- Helps identify potential reversal and continuation areas
Multi-Timeframe Levels
- Previous Daily, Weekly, and Monthly High/Low levels
- Customizable line styles (solid, dashed, dotted)
- Independent color controls for each timeframe
- Auto-adjusted labels (PDH, PDL, PWH, PWL, PMH, PML)
Display Modes
- Historical Mode: Shows all past structures and maintains drawing history
- Present Mode: Displays only current active structures for cleaner charts
Visual Themes
- Colored: Full color customization for all elements
- Monochrome: Clean grey-scale design for minimal distraction
Smart Features
- Confluence filter for internal structure to reduce noise
- Automatic candle coloring based on market bias
- 16 pre-configured alert conditions for all major signals
- Efficient rendering with automatic cleanup of broken structures
- Independent control over each feature for modular usage
Use Cases
- Identify institutional entry and exit points through order blocks
- Spot potential reversals at premium/discount zones
- Confirm trend direction with BOS and CHoCH signals
- Find liquidity grabs at equal highs and lows
- Trade imbalances at fair value gaps
- Align entries with multi-timeframe key levels
Settings Organization
All features are neatly organized into logical groups:
- Smart Money Concepts (general settings)
- Real Time Internal Structure
- Real Time Swing Structure
- Order Blocks
- EQH/EQL
- Fair Value Gaps
- Highs & Lows MTF
- Premium & Discount Zones
Note: This indicator works on all timeframes and instruments. For optimal results, combine multiple SMC concepts together to find high-probability setups with confluence.
Credits
Special thanks to Dau_tu_hieu_goc and BigBeluga for their code examples and inspiration that contributed to the development of this indicator.
Disclaimer
This indicator is for educational purposes only and does not constitute financial advice. Trading involves substantial risk of loss. Past performance does not guarantee future results. Always use proper risk management and conduct your own analysis before making trading decisions. The developer is not responsible for any trading losses incurred.
Happy Trading
SMC N-Gram Probability Matrix [PhenLabs]📊 SMC N-Gram Probability Matrix
Version: PineScript™ v6
📌 Description
The SMC N-Gram Probability Matrix applies computational linguistics methodology to Smart Money Concepts trading. By treating SMC patterns as a discrete “alphabet” and analyzing their sequential relationships through N-gram modeling, this indicator calculates the statistical probability of which pattern will appear next based on historical transitions.
Traditional SMC analysis is reactive—traders identify patterns after they form and then anticipate the next move. This indicator inverts that approach by building a transition probability matrix from up to 5,000 bars of pattern history, enabling traders to see which SMC formations most frequently follow their current market sequence.
The indicator detects and classifies 11 distinct SMC patterns including Fair Value Gaps, Order Blocks, Liquidity Sweeps, Break of Structure, and Change of Character in both bullish and bearish variants, then tracks how these patterns transition from one to another over time.
🚀 Points of Innovation
First indicator to apply N-gram sequence modeling from computational linguistics to SMC pattern analysis
Dynamic transition matrix rebuilds every 50 bars for adaptive probability calculations
Supports bigram (2), trigram (3), and quadgram (4) sequence lengths for varying analysis depth
Priority-based pattern classification ensures higher-significance patterns (CHoCH, BOS) take precedence
Configurable minimum occurrence threshold filters out statistically insignificant predictions
Real-time probability visualization with graphical confidence bars
🔧 Core Components
Pattern Alphabet System: 11 discrete SMC patterns encoded as integers for efficient matrix indexing and transition tracking
Swing Point Detection: Uses ta.pivothigh/pivotlow with configurable sensitivity for non-repainting structure identification
Transition Count Matrix: Flattened array storing occurrence counts for all possible pattern sequence transitions
Context Encoder: Converts N-gram pattern sequences into unique integer IDs for matrix lookup
Probability Calculator: Transforms raw transition counts into percentage probabilities for each possible next pattern
🔥 Key Features
Multi-Pattern SMC Detection: Simultaneously identifies FVGs, Order Blocks, Liquidity Sweeps, BOS, and CHoCH formations
Adjustable N-Gram Length: Choose between 2-4 pattern sequences to balance specificity against sample size
Flexible Lookback Range: Analyze anywhere from 100 to 5,000 historical bars for matrix construction
Pattern Toggle Controls: Enable or disable individual SMC pattern types to customize analysis focus
Probability Threshold Filtering: Set minimum occurrence requirements to ensure prediction reliability
Alert Integration: Built-in alert conditions trigger when high-probability predictions emerge
🎨 Visualization
Probability Table: Displays current pattern, recent sequence, sample count, and top N predicted patterns with percentage probabilities
Graphical Probability Bars: Visual bar representation (█░) showing relative probability strength at a glance
Chart Pattern Markers: Color-coded labels placed directly on price bars identifying detected SMC formations
Pattern Short Codes: Compact notation (F+, F-, O+, O-, L↑, L↓, B+, B-, C+, C-) for quick pattern identification
Customizable Table Position: Place probability display in any corner of your chart
📖 Usage Guidelines
N-Gram Configuration
N-Gram Length: Default 2, Range 2-4. Lower values provide more samples but less specificity. Higher values capture complex sequences but require more historical data.
Matrix Lookback Bars: Default 500, Range 100-5000. More bars increase statistical significance but may include outdated market behavior.
Min Occurrences for Prediction: Default 2, Range 1-10. Higher values filter noise but may reduce prediction availability.
SMC Detection Settings
Swing Detection Length: Default 5, Range 2-20. Controls pivot sensitivity for structure analysis.
FVG Minimum Size: Default 0.1%, Range 0.01-2.0%. Filters insignificant gaps.
Order Block Lookback: Default 10, Range 3-30. Bars to search for OB formations.
Liquidity Sweep Threshold: Default 0.3%, Range 0.05-1.0%. Minimum wick extension beyond swing points.
Display Settings
Show Probability Table: Toggle the probability matrix display on/off.
Show Top N Probabilities: Default 5, Range 3-10. Number of predicted patterns to display.
Show SMC Markers: Toggle on-chart pattern labels.
✅ Best Use Cases
Anticipating continuation or reversal patterns after liquidity sweeps
Identifying high-probability BOS/CHoCH sequences for trend trading
Filtering FVG and Order Block signals based on historical follow-through rates
Building confluence by comparing predicted patterns with other technical analysis
Studying how SMC patterns typically sequence on specific instruments or timeframes
⚠️ Limitations
Predictions are based solely on historical pattern frequency and do not account for fundamental factors
Low sample counts produce unreliable probabilities—always check the Samples display
Market regime changes can invalidate historical transition patterns
The indicator requires sufficient historical data to build meaningful probability matrices
Pattern detection uses standardized parameters that may not capture all institutional activity
💡 What Makes This Unique
Linguistic Modeling Applied to Markets: Treats SMC patterns like words in a language, analyzing how they “flow” together
Quantified Pattern Relationships: Transforms subjective SMC analysis into objective probability percentages
Adaptive Learning: Matrix rebuilds periodically to incorporate recent pattern behavior
Comprehensive SMC Coverage: Tracks all major Smart Money Concepts in a unified probability framework
🔬 How It Works
1. Pattern Detection Phase
Each bar is analyzed for SMC formations using configurable detection parameters
A priority hierarchy assigns the most significant pattern when multiple detections occur
2. Sequence Encoding Phase
Detected patterns are stored in a rolling history buffer of recent classifications
The current N-gram context is encoded into a unique integer identifier
3. Matrix Construction Phase
Historical pattern sequences are iterated to count transition occurrences
Each context-to-next-pattern transition increments the appropriate matrix cell
4. Probability Calculation Phase
Current context ID retrieves corresponding transition counts from the matrix
Raw counts are converted to percentages based on total context occurrences
5. Visualization Phase
Probabilities are sorted and the top N predictions are displayed in the table
Chart markers identify the current detected pattern for visual reference
💡 Note:
This indicator performs best when used as a confluence tool alongside traditional SMC analysis. The probability predictions highlight statistically common pattern sequences but should not be used as standalone trading signals. Always verify predictions against price action context, higher timeframe structure, and your overall trading plan. Monitor the sample count to ensure predictions are based on adequate historical data.
Volumetric Inverse Fair Value Gap (IFVG) [Kodexius]The Volumetric Inverse Fair Value Gap (IFVG) indicator detects and visualizes inverse fair value gaps (IFVGs) zones where previous inefficiencies in price (fair value gaps) are later invalidated or “inverted.”
Unlike traditional FVG indicators, this tool integrates volume-based analysis to quantify the bullish, bearish, and overall strength of each inversion. It visually represents these metrics within a dynamically updating box on the chart, giving traders deeper insight into market reactions when liquidity imbalances are filled and reversed.
Features
Inverse fair value gap detection
The script identifies bullish and bearish fair value gaps, stores them as pending zones, and turns them into inverse fair value gaps when price trades back through the gap in the opposite direction. Each valid inversion becomes an active IFVG zone on the chart.
Sensitivity control with ATR filter and strict mode
A minimum gap size based on ATR is used to filter out small and noisy gaps. Strict mode can be enabled so that any wick contact between the relevant candles prevents the gap from being accepted as a fair value gap. This lets you decide how clean and selective the zones should be.
Show Last N Boxes control
The indicator can keep only the most recent N IFVG zones visible. Older zones are removed from the chart once the number of active objects exceeds the user setting. This prevents clutter on higher timeframes or long histories and keeps attention on the most relevant recent zones.
Ghost box for the original gap
When the ghost option is enabled, the script draws a faint box that marks the original fair value gap from which the inverse zone came. This makes it easy to see where the initial imbalance appeared and how price later inverted that area.
Volumetric bull, bear and strength metrics
For each IFVG, the script estimates how much of the bar volume is associated with buying and how much with selling, then computes bull percentage, bear percentage and a strength score that uses a percentile rank of volume. These values are stored with the IFVG object and drive the visualization inside the zone.
Three band visual layout inside each IFVG
Each active IFVG is drawn as a container with three horizontal sections. The top band represents the bull percentage, the middle band the bear percentage and the bottom band the strength metric. The width of each bar reflects its respective value so you can read the structure of the zone at a glance.
Customizable colors and label text
Colors for bull, bear, strength, the empty background area, the ghost box and label text can be adjusted in the inputs. This allows you to match the indicator to different chart themes or highlight specific aspects such as strength or direction.
Automatic invalidation and cleanup
When price clearly closes beyond the IFVG in a way that breaks the logic of that zone, the script marks it as inactive and deletes all boxes and labels linked to it. Only valid and active IFVGs remain on the chart, which keeps the display clean and focused.
Calculations
1. Detecting Fair Value Gaps (FVGs)
A fair value gap is identified when price action leaves an imbalance between candle wicks. Depending on the mode:
Bullish FVG: When low > high
Bearish FVG: When high < low
Optionally, the strict mode ensures wicks do not touch.
The gap’s significance is filtered using the ATR multiplier input to exclude minor noise.
Once detected, FVGs are stored as pending zones until inverted by opposite movement (price crossing through).
bool bull_cond = strict_mode ? (low > high ) : (close > high )
bool bear_cond = strict_mode ? (high < low ) : (close < low )
float gap_size = 0.0
if bull_cond and close > open
gap_size := low - high
if bear_cond and close < open
gap_size := low - high
2. Creating IFVGs (Inversions)
When price later moves through a previous FVG in the opposite direction, an Inverse FVG (IFVG) is created.
For example:
A previous bearish FVG becomes bullish IFVG if price moves upward through it.
A previous bullish FVG becomes bearish IFVG if price moves downward through it.
The IFVG is initialized with structural boundaries (top, bottom) and timestamp metadata to anchor visualization.
if not p.is_bull_gap and close > p.top
inverted := true
to_bull := true
if p.is_bull_gap and close < p.btm
inverted := true
to_bull := false
3. Volume Metrics (Bull, Bear, Strength)
Each IFVG calculates buy and sell volumes from the current bar’s price spread and total volume.
Bull % = proportion of upward (buy) volume
Bear % = proportion of downward (sell) volume
Strength % = normalized percentile rank of total volume
These are obtained through a custom function that estimates directional volume contribution:
calc_metrics(float o, float h, float l, float c, float v) =>
float rng = h - l
float buy_v = 0.0
if rng == 0
buy_v := v * 0.5
else
if c >= o
buy_v := v * ((math.abs(c - o) + (math.min(o, c) - l)) / rng)
else
buy_v := v * ((h - math.max(o, c)) / rng)
float sell_v = v - buy_v
float total = buy_v + sell_v
float p_bull = total > 0 ? buy_v / total : 0
float p_bear = total > 0 ? sell_v / total : 0
float p_str = ta.percentrank(v, 100) / 100.0
SMC Statistical Liquidity Walls [PhenLabs]📊 SMC Statistical Liquidity Walls
Version: PineScript™ v6
📌 Description
The SMC Statistical Liquidity Walls indicator is designed to visualize market volatility and potential reversal zones using advanced statistical modeling. Unlike traditional Bollinger Bands that use simple lines, this script utilizes an “Inverted Sigmoid” opacity function to create a “fog of war” effect. This visualizes the density of liquidity: the further price moves from the equilibrium (mean), the “harder” the liquidity wall becomes.
This tool solves the problem of over-trading in low-probability areas. By automatically mapping “Premium” (Resistance) and “Discount” (Support) zones based on Standard Deviation (SD), traders can instantly see when price is overextended. The result is a clean, intuitive overlay that helps you identify high-probability mean reversion setups without cluttering your chart with manual drawings.
🚀 Points of Innovation
Inverted Sigmoid Logic: A custom mathematical function maps Standard Deviation to opacity, creating a realistic “wall” density effect rather than linear gradients.
Dynamic “Solidity”: The indicator is transparent at the center (Equilibrium) and becomes visually solid at the edges, mimicking physical resistance.
Separated Directional Bias: distinct Red (Premium) and Green (Discount) coding helps SMC traders instantly recognize expensive vs. cheap pricing.
Smart “Safe” Deviation: Includes fallback logic to handle calculation errors if deviation hits zero, ensuring the indicator never crashes during data gaps.
🔧 Core Components
Basis Calculation: Uses a Simple Moving Average (SMA) to determine the market’s equilibrium point.
Standard Deviation Zones: Calculates 1SD, 2SD, and 3SD levels to define the statistical extremes of price action.
Sigmoid Alpha Calculation: Converts the SD distance into a transparency value (0-100) to drive the visual gradient.
🔥 Key Features
Automated Premium/Discount Zones: Red zones indicate overbought (Premium) areas; Green zones indicate oversold (Discount) areas.
Customizable Density: Users can adjust the “Steepness” and “Midpoint” of the sigmoid curve to control how fast the walls become solid.
Integrated Alerts: Built-in alert conditions trigger when price hits the “Solid” wall (2SD or higher), perfect for automated trading or notifications.
Visual Clarity: The center of the chart remains clear (high transparency) to keep focus on price action where it matters most.
🎨 Visualization
Equilibrium Line: A gray line representing the mean price.
Gradient Fills: The space between bands fills with color that increases in opacity as it moves outward.
Premium Wall: Upper zones fade from transparent red to solid red.
Discount Wall: Lower zones fade from transparent green to solid green.
📖 Usage Guidelines
Range Period: Default 20. Controls the lookback period for the SMA and Standard Deviation calculation.
Source: Default Close. The price data used for calculations.
Center Transparency: Default 100 (Clear). Controls how transparent the middle of the chart is.
Edge Transparency: Default 45 (Solid). Controls the opacity of the outermost liquidity wall.
Wall Steepness: Default 2.5. Adjusts how aggressively the gradient transitions from clear to solid.
Wall Start Point: Default 1.5 SD. The deviation level where the gradient shift begins to accelerate.
✅ Best Use Cases
Mean Reversion Trading: Enter trades when price hits the solid 2SD or 3SD wall and shows rejection wicks.
Take Profit Targets: Use the Equilibrium (Gray Line) as a logical first target for reversal trades.
Trend Filtering: Do not initiate new long positions when price is deep inside the Red (Premium) wall.
⚠️ Limitations
Lagging Nature: As a statistical tool based on Moving Averages, the walls react to past price data and may lag during sudden volatility spikes.
Trending Markets: In strong parabolic trends, price can “ride” the bands for extended periods; mean reversion should be used with caution in these conditions.
💡 What Makes This Unique
Physics-Based Visualization: We treat liquidity as a physical barrier that gets denser the deeper you push, rather than just a static line on a chart.
🔬 How It Works
Step 1: The script calculates the mean (SMA) and the Standard Deviation (SD) of the source price.
Step 2: It defines three zones above and below the mean (1SD, 2SD, 3SD).
Step 3: The custom `get_inverted_sigmoid` function calculates an Alpha (transparency) value based on the SD distance.
Step 4: Plot fills are colored dynamically, creating a seamless gradient that hardens at the extremes to visualize the “Liquidity Wall.”
💡 Note
For best results, combine this indicator with Price Action confirmation (such as pin bars or engulfing candles) when price touches the solid walls.
Smart Money Setup 08 [TradingFinder] Binary Options Gold Scalper🔵 Introduction
In the Smart Money methodology, the market is understood as a structure driven by liquidity flow. This structure forms through the movement of large orders, the accumulation of liquidity, and the reactions that occur around key price zones. The logic of Smart Money is based on the idea that price movement is not random and usually evolves with the intention of collecting liquidity and creating price inefficiencies known as imbalances.
Within this framework, several important stages including the liquidity sweep, the formation of a point of interest, the appearance of an imbalance and the transition of market structure play major roles and collectively define the broader direction of price.
In many bullish scenarios, the market begins by sweeping sell side liquidity and targeting important lows in order to collect the liquidity resting below them. This liquidity collection often becomes the starting point for creating a point of interest which usually marks the area where Smart Money begins to enter the market.
After price moves away from this point, it breaks a structural high and forms a change of character. This shift marks a transition in the balance of power between buyers and sellers and is considered the first clear signal that the market structure is changing.
After the change of character, new institutional order flow often creates a strong and rapid movement that leaves behind an imbalance. This imbalance is one of the most important elements in Smart Money analysis because price tends to return to this area in order to complete structure and restore balance.
The return into the imbalance becomes meaningful when it occurs together with the liquidity sweep, the presence of a validated point of interest and a confirmed structural transition. These conditions frequently mark the beginning of powerful movements within the Smart Money cycle.
Understanding the sequence of liquidity, point of interest, imbalance, change of character and market structure builds the foundation of Smart Money analysis and provides a clear view of the true direction of institutional strength.
Bullish Setup :
Bearish Setup :
🔵 How to Use
To use this framework effectively, the trader must analyze the market through the principles of Smart Money and observe how liquidity drives price. A trade becomes valid only when several essential components appear together in a clear and consistent order.
These components include the liquidity sweep, the formation of a point of interest, the confirmation of a change of character, the transition of market structure and the return of price into an imbalance. The method is built on the understanding that the market first collects liquidity, then shifts order flow and finally provides an entry opportunity inside an inefficient area or inside a point of interest.
For this reason, the trader must follow the path of liquidity from the moment the sweep occurs, through the point of interest and the change of character and finally into the return of price toward the imbalance. When applied correctly, this approach creates entries that are more precise, more structural and more aligned with the real behavior of the market rather than with superficial signals.
🟣 Long Position
A bullish setup in Smart Money structure begins with a liquidity sweep on the sell side. The market first targets the areas where sell side liquidity is located and collects the stops and resting liquidity under previous lows. This collection is the condition that Smart Money requires to begin creating a new order flow. After this liquidity has been taken, a point of interest forms which is usually the last bearish candle or the effective demand zone that initiated the upward movement.
Price then moves away from the point of interest and breaks a structural high which creates a change of character. This event confirms that the market structure has moved from a bearish state to a bullish one and that buying pressure has taken control of the order flow. Following this shift, a strong upward movement often occurs and creates an imbalance between candles. This imbalance reflects the entrance of strong Smart Money orders and is seen as an important confirmation of bullish strength.
When price returns to this imbalance after the displacement, the market enters a phase where Smart Money aims to complete the corrective movement and continue the upward direction. The reaction inside the imbalance when combined with the liquidity sweep, the confirmed point of interest and the change of character completes the bullish setup and forms a structure that often leads to a continuation of the bullish trend.
🟣 Short Position
A bearish setup follows the same Smart Money logic but in the opposite direction. The market begins by collecting buy side liquidity and targets the highs where buy side liquidity and resting stops are located. This liquidity sweep on the buy side becomes the starting phase for Smart Money to initiate a downward order flow. After the liquidity is collected, a bearish point of interest forms which is usually the last bullish candle or the supply zone that created the initial drop.
Price then moves away from this point and breaks the first structural low. This creates a change of character to the downside which confirms that the market structure has transitioned from bullish to bearish and that selling pressure has gained control. After this shift, a strong downward displacement appears and leaves behind a bearish imbalance that clearly shows the dominance of sellers.
As price returns to this imbalance and corrects the inefficient movement, the bearish setup becomes complete as long as the market structure remains bearish. The combination of the buy side liquidity sweep, the bearish point of interest, the change of character, the imbalance and the corrective return creates the ideal structure that Smart Money uses to continue the downward movement and develop a reliable selling opportunity.
🔵 Settings
🟣 Logic Settings
Pivot Period : Defines how many bars are analyzed to identify swing highs and lows. Higher values detect larger, slower structures, while lower values respond to faster patterns. The default value of 5 offers a balanced sensitivity.
🟣 Alert Settings
Alert : Enables alerts for SMS08.
Message Frequency : Determines the frequency of alerts. Options include 'All' (every function call), 'Once Per Bar' (first call within the bar), and 'Once Per Bar Close' (final script execution of the real-time bar). Default is 'Once per Bar'.
Show Alert Time by Time Zone : Configures the time zone for alert messages. Default is 'UTC'.
🔵 Conclusion
The Smart Money approach demonstrates that price movement is not random or based on surface level patterns. Instead, it develops through a clear cycle of liquidity collection, structural transition and corrective movement toward key price zones. By recognizing events such as the liquidity sweep, the formation of the point of interest, the change of character and the return into the imbalance, the trader gains the ability to understand order flow more accurately and identify the true direction of market structure.
Both bullish and bearish setups show that the alignment of these elements creates a transparent view of institutional behavior and reveals the source of strong movements in the market. When the trader correctly identifies this sequence, entry points become more reliable and more aligned with liquidity flow. The combination of liquidity, structure and imbalance provides a consistent framework that removes guesswork and guides decisions through the real logic of the market.
Reversal SMC Suite Pro by TradeswithBThe Reversal SMC Suite is an intraday Smart Money Concepts toolkit designed to help traders visually analyze structure, imbalances, and displacement during trending or volatile sessions. This script combines multiple SMC elements—reversals, order blocks, FVGs, HTF bias, and pivot-based support/resistance—into one organized framework to support decision-making.
This indicator does not generate buy or sell signals and does not guarantee results. It is strictly a charting and visualization tool intended to help traders study market behavior.
🔍 Key Features
1. Reversal Detection
Swing Failure Pattern (SFP)
Bullish/Bearish Engulfing
Momentum candle detection (ATR-based)
Optional unified “reversal” signal
Visual arrows and reversal blocks
These are designed to highlight potential turning points based on price behavior—not to predict or guarantee outcomes.
2. HTF Trend Filter
Optional higher timeframe EMA/SMA filter
Customizable HTF resolution
Bias modes: Long only / Short only / Both
This helps you align lower-timeframe reversals with broader market context.
3. Dynamic Order Blocks
Automated OB detection (Body, Wick, or Hybrid)
Smart mitigation logic (body-based or wick-based)
Configurable lookback and OB count
Optional ATR body-size filter for OB quality
Real-time mitigation removal
These tools help visualize areas of interest where price previously showed displacement.
4. Fair Value Gaps (FVG)
Automatic gap detection
Optional FVG extension until filled
Per-side max FVG limit
Useful for identifying imbalance zones and measuring how price revisits inefficiencies.
5. Support / Resistance
Pivot-based S/R with left/right bar settings
Auto-drawing with customizable line counts
Optional S/R visibility toggle
🎛 Presets Included
Several visual configurations are included for convenience:
Custom / Manual (default)
Intraday ORB 5–15m (optimized for fast futures charts)
Clean SMC (Trend + OB)
FVG + OB Combo
Presets adjust inputs automatically to give new users cleaner starting points.
🧠 How To Use
This script is meant to be paired with any strategy or workflow that benefits from:
visual structure analysis,
HTF/LTF alignment,
OB + FVG context, or
intraday trend identification.
It does not replace risk management, strategy rules, or trade planning.
⚠️ Important Notes / Disclaimer
This indicator does not generate trading signals.
No part of this script guarantees profitable outcomes.
It is for educational and informational purposes only.
Always perform your own analysis and use proper risk management.
Past market behavior does not guarantee future results.
The 'Qualified' POI Scorer [PhenLabs]📊 The “Qualified” POI Scorer (Q-POI)
Version: PineScript™ v6
📌 Description
The “Qualified” POI Scorer helps intermediate traders overcome "analysis paralysis" by filtering Smart Money Concepts (SMC) structures based on their probability. Instead of flooding your chart with every possible Order Block, this script assigns a proprietary “Quality Score” (0-100) to each zone. It analyzes the strength of the displacement, the presence of imbalances (FVG), and liquidity mechanics to determine which zones are worth your attention. It is designed to clean up your charts and enforce discipline by visually fading out low-quality setups.
🚀 Points of Innovation
Dynamic “Glass UI” Transparency that automatically fades weak zones based on their score.
Proprietary Scoring Algorithm (0-100) based on three distinct institutional factors.
Visual Icon System that prints analytical context (💧— 🚀/🐌—🧱) directly on the chart.
Automated Mitigation Tracking that changes the visual state of zones after they are tested.
Displacement Velocity calculation using ATR to verify institutional intent.
🔧 Core Components
Liquidity Sweep Engine: Detects if a pivot point grabbed liquidity from the previous X bars before reversing.
FVG Validator: Checks if the move away from the zone created a valid Fair Value Gap.
Momentum Scorer: Calculates the size of the displacement candle relative to the Average True Range (ATR).
🔥 Key Features
Quality Filtering: Automatically hides or dims zones that score below 50 (user configurable).
State Management: Zones turn grey when mitigated and delete themselves when invalidated.
Visual Scorecard: Displays the exact numeric score on the zone for quick decision-making.
Time-Decay Logic: Keeps the chart clean by managing the lifespan of old zones.
🎨 Visualization
High Score Zones (80-100): Display as bright, semi-solid boxes indicating high probability.
Medium Score Zones (50-79): Display as translucent “glass” boxes.
Low Score Zones (<50): Display as faint “ghost” boxes or are completely hidden.
Rocket Icon (🚀): Indicates high momentum displacement.
Snail Icon (🐌): Indicates low momentum displacement.
Drop Icon (💧): Indicates the zone swept liquidity.
Brick Icon (🧱): Indicates the zone is supported by an FVG.
📖 Usage Guidelines
Swing Structure Length (Default: 5): Controls the sensitivity of the pivot detection; lower numbers create more zones, higher numbers find major swing points.
ATR Length (Default: 14): Determines the lookback period for calculating relative momentum.
Minimum Quality Score (Default: 50): The threshold for which zones are considered “valid” enough to be fully visible.
Bullish/Bearish Colors: Fully customizable colors that adapt their own transparency based on the score.
Show Weak Zones (Default: False): Toggles the visibility of zones that failed the quality check.
✅ Best Use Cases
Filtering noise during high-volatility sessions by focusing only on Score 80+ zones.
Confirming trend continuation entries by looking for the Rocket (🚀) momentum icon.
Avoiding “stale” zones by ignoring any box that has turned grey (Mitigated).
⚠️ Limitations
The indicator is reactive to closed candles and cannot predict news-driven spikes.
Scoring is based on technical structure and does not account for fundamental drivers.
In extremely choppy markets, the ATR filter may produce lower scores due to lack of displacement.
💡 What Makes This Unique
It transforms subjective SMC analysis into an objective, quantifiable score.
The visual hierarchy allows traders to assess chart quality in milliseconds without reading data.
It integrates three separate SMC concepts (Liquidity, Imbalance, Structure) into a single tool.
🔬 How It Works
Step 1: The script identifies a Swing High or Low based on your length input.
Step 2: It looks backward to see if that swing swept liquidity, and looks forward to check for an FVG and displacement.
Step 3: It calculates a weighted score (30pts for Sweep, 30pts for FVG, 40pts for Momentum).
Step 4: It draws the zone with a transparency level designated by the score and appends the relevant icons.
💡 Note:
For the best results, use this indicator on the timeframe you execute trades on (e.g., 15m or 1h). Do not use it to find entries on the 1m chart if your analysis is based on the 4h chart.
Smart Money COTThis indicator implements the method of analysing COT data as defined by Michael Huddleston (I.E. The Inner Circle Trader). It removes all superfluous information contained in the standard COT reports and focusses only on Commercial speculators using the overall Long-Short positions.
Features
The unique feature of this indicator is its ability to look back over time and provide the following information:
Calculation of the range high and low of the specified lookback range.
Calculation of equilibrium of that range.
Automatic colour coding of net long and net short positions when the Long-Short COT calculation is above or below equilibrium of the lookback range.
Instructions
Use the Daily Timeframe only. You may get unexpected results on other timeframes.
Ensure the asset has COT data available. Script is mainly focused on commodity futures, such as ES, NQ, YM. It has not been tested against Forex.
You will need to define the "Lookback" setting in the script settings. Use the total number of trading days required for your analysis. E.g. if you want a 6 month COT analysis, use the measurement tool to count the quantity of daily candles between now and 6 months ago - use this as your Lookback setting. Adjust as needed for other lookback periods, e.g. 3 months, 12 months etc.
Other Info
The script provides the ability to customise colours in its settings.
Range High and Range Low plots can be disabled in settings.
ICT Complete Multi-Setup StrategyThe ICT (Inner Circle Trader) trading strategies include multiple setups such as Silver Bullet, Cameron's Model, Inversion Fair Value Gap, Turtle Soup, Candle Range Theory (CRT), Optimal Trade Entry (OTE), Change in the State of Delivery (CISD), and Power of Three (PO3). These strategies revolve around concepts like liquidity sweeps, fair value gaps (FVG), order blocks, market structure shifts, and smart money footprints.
For a comprehensive Pine Script indicator that incorporates all ICT trading strategies with buy/sell toggles and detailed setups, it involves detecting and marking key ICT concepts like liquidity zones, fair value gaps, order blocks, market structure breaks, and then combining these signals into actionable buy/sell alerts.
Based on the available resources, a Pine Script indicator for all ICT setups would feature:
Marking and trading liquidity sweeps and stops (Silver Bullet, Cameron's Model)
Identifying fair value gaps and their inversions (Inversion FVG, Turtle Soup)
Highlighting Candle Range Theory zones with entries and stops
Fibonacci retracement-based Optimal Trade Entry (OTE) zones for entry timing
Detecting momentum shifts and Change in State of Delivery (CISD)
Recognizing accumulation, manipulation, and distribution phases for Power of Three (PO3)
Toggles for each strategy to enable/disable buy and sell signals
An indicator script needs well-commented code for readability and must visually display buy/sell signals, FVG zones, and key price levels on the chart.
Binary Options 1 Minute Signals [TradingFinder] 1 Min Strategy🔵 Introduction
At first sight, price movement in binary options appears random, but behind every move lies a clear logic of liquidity and market imbalance. The market is always driven by the hunt for liquidity and the continuous rebalancing that takes place around Fair Value Gaps (FVGs) and Order Blocks (OBs). These zones are where institutional activity is concentrated and where Smart Money creates the most significant reactions.
When price approaches a key liquidity zone, it often performs a Liquidity Sweep to capture orders resting around previous highs or lows. This move usually presents itself as a False Breakout. Price briefly breaks a level to trigger stop losses and collect liquidity, then quickly reverses direction. Understanding this false breakout behavior is essential for identifying high probability reversals in binary options trading.
After the liquidity sweep, price typically retraces into a Fair Value Gap or Order Block, where the market seeks balance and new orders are introduced. This interaction between liquidity, imbalance, and institutional order flow forms the core logic of every Smart Money trading model.
By focusing on Liquidity Sweeps, False Breakouts, and the structure of FVGs and OBs, traders can read the true intention behind price movements. What seems like random volatility becomes a structured cycle of liquidity collection and reaction, offering clear opportunities for precision-based binary entries.
Bullish Setup :
Bearish Setup :
🔵 How to Use
This indicator works within the Smart Money framework and focuses on the connection between Liquidity Sweep, False Breakout, Fair Value Gap (FVG) and Order Block (OB).
It is created to help traders identify the moment when the market finishes collecting liquidity and begins to show signs of reversal.
The indicator studies how price behaves around zones where liquidity is concentrated, such as previous highs and lows or areas with visible inefficiency. When a clear reaction forms and a valid candle pattern confirms the shift in direction, the indicator generates a signal that represents the activity of Smart Money.
This tool does not respond to random volatility or noise. It waits for structure, liquidity and confirmation to align together before providing an entry. As a result, every signal has a logical base related to institutional order flow rather than ordinary price fluctuations. This approach allows traders to focus only on the movements that reflect true liquidity behavior.
🟣 Long Setup
A bullish setup takes place when the market moves downward and reaches a sell-side liquidity zone located below previous swing lows. In this area, price performs a Liquidity Sweep by moving under key levels to trigger stop losses and capture liquidity from trapped sellers.
This movement usually appears as a False Breakout because the market breaks below a level for a short moment and then quickly moves back inside the range.
Around this zone, a bullish Order Block or Fair Value Gap (FVG) often exists, showing where institutional demand is active.
When the indicator detects the presence of liquidity collection together with a valid bullish confirmation candle near an OB or FVG, it creates a Call signal.
This marks the moment when Smart Money is shifting from selling pressure to accumulation, and a strong bullish move often follows. For binary entries, the best opportunity usually comes immediately after the confirmation candle closes.
The reaction tends to happen quickly because the liquidity grab has completed and new institutional buying pressure is entering the market. This type of setup often provides a clean and precise entry with a high probability of success.
🟣 Short Setup
A bearish setup happens when the market rises and enters a buy-side liquidity area above previous highs. Here, the market performs a Liquidity Sweep to trigger stop losses placed above those highs and to absorb liquidity from trapped buyers.
This pattern forms what traders recognize as a False Breakout because the price only breaks the level temporarily before reversing in the opposite direction. A bearish Order Block or Fair Value Gap (FVG) often appears around this zone, showing where institutional selling interest exists.
Once the liquidity sweep completes and a bearish confirmation candle closes, the indicator produces a Put signal that reflects the shift from buying to selling pressure by Smart Money.
This moment often leads to a fast downward reaction as the market rebalances and fills the nearby inefficiency.
The most effective entry for binary trading is right after the confirmation candle closes, when the false breakout and liquidity collection are both completed. The price usually reacts sharply as the market transitions from liquidity hunting to a new directional move. This setup represents a structured view of how liquidity drives market cycles and how Smart Money creates precise reversals through controlled imbalance and reaction.
🔵 Settings
Time Frame : Defines the timeframe used for analysis. If left blank, the indicator automatically uses the chart’s current timeframe.
Swing Period : Determines how many candles are used to identify structural turning points such as swing highs and swing lows. Higher values increase accuracy but reduce the number of signals.
Signal Type : Specifies the type of signal generated by the indicator. The option All shows every signal, Main Signal displays only the primary one, and Alternative Signal produces a secondary signal that appears one candle after the main signal for additional confirmation.
Candle Pattern : Enables candle pattern logic for reversal confirmation. When active, the indicator issues a signal only when a valid candle formation confirms the market reaction.
Candle LookBack Check : Verifies that the last few candles move in the opposite direction of the signal to be generated. This condition acts as a confirmation filter, ensuring that the signal appears only after a clear counter-move in price.
Last Candle Direction : Considers the direction of the most recent candle in the analysis. It helps determine whether the final candle moves with or against the current trend.
Last Candle Shadow Ratio : Sets the ratio between the last candle’s wick and body to refine confirmation accuracy. Higher values require longer wicks, indicating stronger rejection and a more reliable reversal pattern.
🔵 Conclusion
Trading with Smart Money logic means understanding how liquidity moves through the market.
Each Liquidity Sweep, False Breakout, Fair Value Gap (FVG) and Order Block (OB) reflects the process of collecting and redistributing orders.
This indicator captures that sequence and turns it into precise, structured signals for binary entries. When liquidity is absorbed and a candle confirmation appears, the market reveals its true direction.
At that moment, traders can act with confidence, following institutional flow instead of reacting to random price moves.
Success with this system comes from patience, confirmation, and a clear reading of liquidity behavior, the core principles behind every Smart Money reversal.
Smart Money Flow Index (SMFI) - Advanced SMC [PhenLabs]📊Smart Money Flow Index (SMFI)
Version: PineScript™v6
📌Description
The Smart Money Flow Index (SMFI) is an advanced Smart Money Concepts implementation that tracks institutional trading behavior through multi-dimensional analysis. This comprehensive indicator combines volume-validated Order Block detection, Fair Value Gap identification with auto-mitigation tracking, dynamic Liquidity Zone mapping, and Break of Structure/Change of Character detection into a unified system.
Unlike basic SMC indicators, SMFI employs a proprietary scoring algorithm that weighs five critical factors: Order Block strength (validated by volume), Fair Value Gap size and recency, proximity to Liquidity Zones, market structure alignment (BOS/CHoCH), and multi-timeframe confluence. This produces a Smart Money Score (0-100) where readings above 70 represent optimal institutional setup conditions.
🚀Points of Innovation
Volume-Validated Order Block Detection – Only displays Order Blocks when formation candle exceeds customizable volume multiplier (default 1.5x average), filtering weak zones and highlighting true institutional accumulation/distribution
Auto-Mitigation Tracking System – Fair Value Gaps and Order Blocks automatically update status when price mitigates them, with visual distinction between active and filled zones preventing trades on dead levels
Proprietary Smart Money Score Algorithm – Combines weighted factors (OB strength 25%, FVG proximity 20%, Liquidity 20%, Structure 20%, MTF 15%) into single 0-100 confidence rating updating in real-time
ATR-Based Adaptive Calculations – All distance measurements use 14-period Average True Range ensuring consistent function across any instrument, timeframe, or volatility regime without manual recalibration
Dynamic Age Filtering – Automatically removes liquidity levels and FVGs older than configurable thresholds preventing chart clutter while maintaining relevant levels
Multi-Timeframe Confluence Integration – Analyzes higher timeframe bias with customizable multipliers (2-10x) and incorporates HTF trend direction into Smart Money Score for institutional alignment
🔧Core Components
Order Block Engine – Detects institutional supply/demand zones using characteristic patterns (down-move-then-strong-up for bullish, up-move-then-strong-down for bearish) with minimum volume threshold validation, tracks mitigation when price closes through zones
Fair Value Gap Scanner – Identifies price imbalances where current candle's low/high leaves gap with two-candle-prior high/low, filters by minimum size percentage, monitors 50% fill for mitigation status
Liquidity Zone Mapper – Uses pivot high/low detection with configurable lookback to mark swing points where stop losses cluster, extends horizontal lines to visualize sweep targets, manages lifecycle through age-based removal
Market Structure Analyzer – Tracks pivot progression to identify trend through higher-highs/higher-lows (bullish) or lower-highs/lower-lows (bearish), detects Break of Structure and Change of Character for trend/reversal confirmation
Scoring Calculation Engine – Evaluates proximity to nearest Order Blocks using ATR-normalized distance, assesses FVG recency and distance, calculates liquidity proximity with age weighting, combines structure bias and MTF trend into smoothed final score
🔥Key Features
Customizable Display Limits – Control maximum Order Blocks (1-10), Liquidity Zones (1-10), and FVG age (10-200 bars) to maintain clean charts focused on most relevant institutional levels
Gradient Strength Visualization – All zones render with transparency-adjustable coloring where stronger/newer zones appear more solid and weaker/older zones fade progressively providing instant visual hierarchy
Educational Label System – Optional labels identify each zone type (Bullish OB, Bearish OB, Bullish FVG, Bearish FVG, BOS) with color-coded text helping traders learn SMC concepts through practical application
Real-Time Smart Money Score Dashboard – Top-right table displays current score (0-100) with color coding (green >70, yellow 30-70, red <30) plus trend arrow for at-a-glance confidence assessment
Comprehensive Alert Suite – Configurable notifications for Order Block formation, Fair Value Gap detection, Break of Structure events, Change of Character signals, and high Smart Money Score readings (>70)
Buy/Sell Signal Integration – Automatically plots triangle markers when Smart Money Score exceeds 70 with aligned market structure and fresh Order Block detection providing clear entry signals
🎨Visualization
Order Block Boxes – Shaded rectangles extend from formation bar spanning high-to-low of institutional candle, bullish zones in green, bearish in red, with customizable transparency (80-98%)
Fair Value Gap Zones – Rectangular areas marking imbalances, active FVGs display in bright colors with adjustable transparency, mitigated FVGs switch to gray preventing trades on filled zones
Liquidity Level Lines – Dashed horizontal lines extend from pivot creation points, swing highs in bearish color (short targets above), swing lows in bullish color (long targets below), opacity decreases with age
Structure Labels – "BOS" labels appear above/below price when Break of Structure confirmed, colored by direction (green bullish, red bearish), positioned at 1% beyond highs/lows for visibility
Educational Info Panel – Bottom-right table explains key terminology (OB, FVG, BOS, CHoCH) and score interpretation (>70 high probability) with semi-transparent background for readability
📖Usage Guidelines
General Settings
Show Order Blocks – Default: On, toggles visibility of institutional supply/demand zones, disable when focusing solely on FVGs or Liquidity
Show Fair Value Gaps – Default: On, controls FVG zone display including active and mitigated imbalances
Show Liquidity Zones – Default: On, manages liquidity line visibility, disable on lower timeframes to reduce clutter
Show Market Structure – Default: On, toggles BOS/CHoCH label display
Show Smart Money Score – Default: On, controls score dashboard visibility
Order Block Settings
OB Lookback Period – Default: 20, Range: 5-100, controls bars scanned for Order Block patterns, lower values detect recent activity, higher values find older blocks
Min Volume Multiplier – Default: 1.5, Range: 1.0-5.0, sets minimum volume threshold as multiple of 20-period average, higher values (2.0+) filter for strongest institutional candles
Max Order Blocks to Display – Default: 3, Range: 1-10, limits simultaneous Order Blocks shown, lower settings (1-3) maintain focus on most recent zones
Fair Value Gap Settings
Min FVG Size (%) – Default: 0.3, Range: 0.1-2.0, defines minimum gap size as percentage of close price, lower values detect micro-imbalances, higher values focus on significant gaps
Max FVG Age (bars) – Default: 50, Range: 10-200, removes FVGs older than specified bars, lower settings (10-30) for scalping, higher (100-200) for swing trading
Show FVG Mitigation – Default: On, displays filled FVGs in gray providing visual history, disable to show only active untouched imbalances
Liquidity Zone Settings
Liquidity Lookback – Default: 50, Range: 20-200, sets pivot detection period for swing highs/lows, lower values (20-50) mark shorter-term liquidity, higher (100-200) identify major swings
Max Liquidity Age (bars) – Default: 100, Range: 20-500, removes liquidity lines older than specified bars, adjust based on timeframe
Liquidity Sensitivity – Default: 0.5, Range: 0.1-1.0, controls pivot detection sensitivity, lower values mark only major swings, higher values identify minor swings
Max Liquidity Zones to Display – Default: 3, Range: 1-10, limits total liquidity levels shown maintaining chart clarity
Market Structure Settings
Pivot Length – Default: 5, Range: 3-15, defines bars to left/right for pivot validation, lower values (3-5) create sensitive structure breaks, higher (10-15) filter for major shifts
Min Structure Move (%) – Default: 1.0, Range: 0.1-5.0, sets minimum percentage move required between pivots to confirm structure change
Multi-Timeframe Settings
Enable MTF Analysis – Default: On, activates higher timeframe trend analysis incorporation into Smart Money Score
Higher Timeframe Multiplier – Default: 4, Range: 2-10, multiplies current timeframe to determine analysis timeframe (4x on 15min = 1hour)
Visual Settings
Bullish Color – Default: Green (#089981), sets color for bullish Order Blocks, FVGs, and structure elements
Bearish Color – Default: Red (#f23645), defines color for bearish elements
Neutral Color – Default: Gray (#787b86), controls color of mitigated zones and neutral elements
Show Educational Labels – Default: On, displays text labels on zones identifying type (OB, FVG, BOS), disable once familiar with patterns
Order Block Transparency – Default: 92, Range: 80-98, controls Order Block box transparency
FVG Transparency – Default: 92, Range: 80-98, sets Fair Value Gap zone transparency independently from Order Blocks
Alert Settings
Alert on Order Block Formation – Default: On, triggers notification when new volume-validated Order Block detected
Alert on FVG Formation – Default: On, sends alert when Fair Value Gap appears enabling quick response to imbalances
Alert on Break of Structure – Default: On, notifies when BOS or CHoCH confirmed
Alert on High Smart Money Score – Default: On, alerts when Smart Money Score crosses above 70 threshold indicating high-probability setup
✅Best Use Cases
Order Block Retest Entries – After Break of Structure, wait for price retrace into fresh bullish Order Block with Smart Money Score >70, enter long on zone reaction targeting next liquidity level
Fair Value Gap Retracement Trading – When price creates FVG during strong move then retraces, enter as price approaches unfilled gap expecting institutional orders to continue trend
Liquidity Sweep Reversals – Monitor price approaching swing high/low liquidity zones against prevailing Smart Money Score trend, after stop hunt sweep watch for rejection into premium Order Block/FVG
Multi-Timeframe Confluence Setups – Identify alignment when current timeframe Order Block coincides with higher timeframe FVG plus MTF analysis showing matching trend bias
Break of Structure Continuations – After BOS confirms trend direction, trade pullbacks to nearest Order Block or FVG in direction of structure break using Smart Money Score >70 as entry filter
Change of Character Reversal Plays – When CHoCH detected indicating potential reversal, look for Smart Money Score pivot with opposing Order Block formation then enter on structure confirmation
⚠️Limitations
Lagging Pivot Calculations – Pivot-based features (Liquidity Zones, Market Structure) require bars to right of pivot for confirmation, meaning these elements identify levels retrospectively with delay equal to lookback period
Whipsaw in Ranging Markets – During choppy conditions, Order Blocks fail frequently and structure breaks produce false signals as Smart Money Score fluctuates without clear institutional bias, best used in trending markets
Volume Data Dependency – Order Block volume validation requires accurate volume data which may be incomplete on Forex pairs or limited in crypto exchange feeds
Subjectivity in Scoring Weights – Proprietary 25-20-20-20-15 weighting reflects general institutional behavior but may not optimize for specific instruments or market regimes, user cannot adjust factor weights
Visual Complexity on Lower Timeframes – Sub-hour timeframes generate excessive zones creating cluttered charts, requires aggressive display limit reduction and higher minimum thresholds
No Fundamental Integration – Indicator analyzes purely technical price action and volume without incorporating economic events, news catalysts, or fundamental shifts that override technical levels
💡What Makes This Unique
Unified SMC Ecosystem – Unlike indicators displaying Order Blocks OR FVGs OR Liquidity separately, SMFI combines all three institutional concepts plus market structure into single cohesive system
Proprietary Confidence Scoring – Rather than manual setup assessment, automated Smart Money Score quantifies probability by weighting five institutional dimensions into actionable 0-100 rating
Volume-Filtered Quality – Eliminates weak Order Blocks forming without institutional volume confirmation, ensuring displayed zones represent genuine accumulation/distribution
Adaptive Lifecycle Management – Automatically updates mitigation status and removes aged zones preventing trades on dead levels through continuous validity and age monitoring
Educational Integration – Built-in tooltips, labeled zones, and reference panel make indicator functional for both learning Smart Money Concepts and executing strategies
🔬How It Works
Order Block Detection – Scans for patterns where strong directional move follows counter-move creating last down-candle before rally (bullish OB) or last up-candle before sell-off (bearish OB), validates formations only when candle exhibits volume exceeding configurable multiple (default 1.5x) of 20-bar average volume
Fair Value Gap Identification – Compares current candle’s high/low against two-candles-prior low/high to detect price imbalances, calculates gap size as percentage of close and filters micro-gaps below minimum threshold (default 0.3%), monitors whether subsequent price fills 50% triggering mitigation status
Liquidity Zone Mapping – Employs pivot detection using configurable lookback (default 50 bars) to identify swing highs/lows where retail stops cluster, extends horizontal reference lines from pivot creation and applies age-based filtering to remove stale zones
Market Structure Analysis – Tracks pivot progression using structure-specific lookback (default 5 bars) to determine trend, confirms uptrend when new pivot high exceeds previous by minimum move percentage, detects Break of Structure when price breaks recent pivot level, flags Change of Character for potential reversals
Multi-Timeframe Confluence – When enabled, requests security data from higher timeframe (current TF × HTF multiplier, default 4x), compares HTF close against HTF 20-period MA to determine bias, contributes ±50 points to score ensuring alignment with institutional positioning on superior timeframe
Smart Money Score Calculation – Evaluates Order Block component via ATR-normalized distance producing max 100-point contribution weighted at 25%, assesses FVG factor through age penalty and distance at 20% weight, calculates Liquidity proximity at 20%, incorporates structure bias (±50-100 points) at 20%, adds MTF component at 15%, applies 3-period smoothing to reduce volatility
Visual Rendering and Lifecycle – Draws Order Block boxes, Fair Value Gap rectangles with color coding (green/red active, gray mitigated), extends liquidity dashed lines with fade-by-age opacity, plots BOS labels, displays Smart Money Score dashboard, continuously updates checking mitigation conditions and removing elements exceeding age/display limits
💡Note:
The Smart Money Flow Index combines multiple Smart Money Concepts into unified institutional order flow analysis. For optimal results, use the Smart Money Score as confluence filter rather than standalone entry signal – scores above 70 indicate high-probability setups but should be combined with risk management, higher timeframe bias, and market regime understanding.
Multi-Timeframe Fibonacci + Open Levels🟣 Multi-Timeframe Fibonacci Levels + Open Levels | Trade Symmetry
This indicator automatically plots Fibonacci levels derived from higher timeframe candle ranges — all at once, directly on your current chart.
It helps you quickly visualize confluence zones and reaction levels where institutional traders are likely to participate.
⚙️ Features
✅ Multi-timeframe Fibonacci Levels — Daily, Weekly, Monthly, Quarterly & Yearly
✅ Automatic Bullish/Bearish detection based on previous candle
✅ Dynamic overlap detection (combines overlapping Fib levels into a single clean label)
✅ Configurable Fibonacci levels, colors, and styles
✅ Optional Open-Price Levels (Daily, Weekly, Monthly)
✅ Clean memory management to keep your chart lightweight
🧠 How to Use
• Add it to any timeframe — it will automatically overlay higher timeframe Fibs.
• Use overlapping or aligned Fib zones as confluence areas.
• Combine with structure or liquidity indicators for high-probability setups.
💡 Inspired by
The concept of higher-timeframe Fibonacci confluences used in Smart Money Concepts (SMC) and ICT-style analysis.
Smart Risk - Three Institutional Models📘 Smart Risk – Three Institutional Entry Models
A precision-engineered institutional framework that blends liquidity, structure, and multi-time-frame confirmation.
🧠 Concept Overview
The Smart Risk indicator models how institutional traders and algorithms engineer entries around liquidity, imbalance, and structural shifts .
It unifies t hree distinct institutional entry models —each built around core Smart Money Concepts (SMC)—and enhances them with a Multi-Time-Frame Confluence (MTF) engine for directional alignment.
This tool doesn’t simply merge indicators.
It connects l iquidity sweeps, order-block reactions, breaker validation, and fair-value-gap mitigation into one cohesive trading logic—filtering every setup through trend, structure, and volume confirmation.
⚙️ How It Works
Setup #1 – Liquidity Sweep + Order Block Revisit + FVG Mitigation
Identifies engineered stop-hunts where price sweeps external liquidity and returns to a prior Order Block or Fair Value Gap (FVG).
Signals reversal-style entries with high probability of mean-reversion or mitigation.
Setup #2 – Supply/Demand + Mitigation / Breaker / FVG Continuation
Captures continuation trades inside trending structure.
When trend bias (via moving-average context) aligns with breaker or mitigation blocks, signals confirm institutional continuation sequences.
Setup #3 – Sweep + Classic FVG Reaction
Tracks clean displacement gaps following a liquidity sweep—ideal for scalpers and intraday reversals where imbalances act as magnets for price.
Each setup can be independently enabled or disabled from the panel.
A built-in signal-cooldown prevents repetitive triggers on the same leg.
🕒 Multi-Time-Frame Confluence
The new MTF module aligns lower-time-frame precision entries with higher-time-frame market structure.
When enabled, each setup only validates if the HTF trend confirms the same directional bias as the LTF pattern—e.g. a 5-minute bullish FVG signal requires a bullish 1-hour structure.
This ensures institutional logic respects global liquidity flow and avoids counter-trend traps.
MTF Controls:
• ✅ Enable MTF Confluence toggle
• ⏱️ Lower Time-Frame (LTF) selector (default 5 min)
• ⏱️ Higher Time-Frame (HTF) selector (default 1 hour)
• 🔄 Automatic SMA-based HTF trend detection
🎨 Visualization & Dashboard
• Order Block / Supply–Demand Zones — highlight institutional footprints
• Fair Value Gaps (FVGs) — reveal displacement inefficiencies
• Liquidity Sweeps (X / $) — mark engineered stops
• BOS & CHoCH — confirm structure continuation or reversal
• Compact Dashboard — live “Armed” state for each setup and MTF bias
Color-coded background cues emphasize active trade phases without clutter.
🧩 Core Algorithm Highlights
• Dynamic swing and pivot structure detection
• Breaker / Mitigation / Volume confirmation filters
• Fair-Value-Gap logic with directional alignment
• Cooldown control for signal throttling
• Multi-Time-Frame bias filter for contextual precision
⸻
📈 How to Use
1. Apply indicator to any asset or timeframe.
2. Select which institutional setups you want active.
3. Optionally enable MTF Confluence (5 min → 1 hr recommended).
4. Wait for BOS/CHoCH confirmation + zone alignment before entry.
5. Use OB and FVG zones for entry/exit planning with risk management.
⸻
💡 Originality Statement
This script introduces a multi-layered institutional logic engine that merges liquidity, mitigation, and imbalance behavior into a unified framework—augmented with time-frame synchronization and signal-cooldown management.
All logic, calculations, and visualization structure were built from scratch for this model.
It is not a mash-up of existing public indicators and offers measurable analytical value through MTF-aware trade validation.
⸻
⚠️ Disclaimer
This tool is intended for educational and analytical purposes only.
It does not provide financial advice or guaranteed trading outcomes.
Always back-test, validate setups, and apply proper risk management.
Supply and Demand Scanner Toolkit [TradingFinder]🔵 Introduction
The analytical system presented here is built upon a deep quantitative foundation designed to capture the dynamic behavior of supply and demand in live markets. At its core, it calculates continuously adaptive zones where institutional liquidity, volatility shifts, and momentum transitions converge. These zones are derived from a combination of a regression-based moving average, a long-period ATR, and Fibonacci expansion ratios, all working together to model real-time volatility, price momentum, and the underlying market imbalance.
In practice, this means that at any given moment, five primary bands and seven variable analytical zones are generated around price, representing different market states ranging from extreme overbought to extreme oversold.
Each band reacts dynamically to price volatility, recalibrating with every new candle, which allows the system to mirror the true, constantly changing structure of supply and demand. Every movement between these zones reflects a transition in the strength and dominance of buyers and sellers, a process referred to as volatility-driven price state transitions.
Traditional analytical models often rely on fixed or static indicators that cannot keep up with the rapid microstructural changes in modern markets. This system instead uses regression and smoothing logic to adapt on the fly. By combining a regression moving average with a smoothed moving average, the model calculates real-time trend direction, momentum flow, and trend strength.
When the regression average rises above the smoothed one, the system classifies the trend as bullish; when it falls below, bearish. This dual-layer structure not only helps confirm direction but also enables the automatic detection of critical structural shifts such as Break of Structure (BoS), Change of Character (CHoCH), and directional reversals.
Both the current trend (Live Trend) and projected future trend (Vision Trend) are calculated simultaneously across all available timeframes. This dual analysis allows traders to identify structural changes earlier and to recognize whether a trend is gaining or losing momentum.
In most conventional moving-average-based frameworks, trading signals are delayed because these models react to price rather than anticipate it. As a result, many buy or sell signals appear after the real move has already begun, leading to entries that contradict the current trend. This system eliminates that lag by employing a mean reversion trading model. Instead of waiting for crossovers, it observes how far price deviates from its statistical mean and reacts when that deviation begins to shrink, the moment when equilibrium forces reemerge.
This approach produces non-lagging, data-driven signals that appear at the exact moment price begins to revert toward balance. At the same time, traders can visually assess the market’s condition by observing the spacing, compression, or expansion of the dynamic bands, which represent volatility shifts and trend energy. Through this interaction, the trader can quickly gauge whether a trend is strengthening, losing power, or preparing for a reversal. In other words, the model provides both quantitative precision and intuitive visualization.
A unique visual element in this system is how candles are displayed during transitional states. When Live Trend and Vision Trend contradict each other, for instance, when the current trend is bullish but the projected trend turns bearish, candle bodies automatically appear as hollow.
These hollow candles act as visual alerts for zones of uncertainty or equilibrium between buyers and sellers, often preceding trend reversals, liquidity sweeps, or volatility compression phases. Traders quickly learn to interpret hollow candles as signals to pause, observe, or prepare for potential shifts rather than to act impulsively.
Signal generation in this model occurs when price reverts from extreme zones back toward neutrality. When price exits the strong overbought or strong oversold zones and reenters a milder area, the system produces a reversal signal that aligns with real-time market dynamics. To refine accuracy, these signals are confirmed through several filters, including momentum verification, volatility behavior, and smart money validation. This multi-layered signal logic significantly reduces false entries, helping traders avoid overreactions to temporary liquidity spikes and enhancing performance in volatility-driven markets.
On a broader level, the model supports full multi-timeframe analysis. It can analyze up to twenty symbols simultaneously, across multiple timeframes, to detect directional bias, correlation, and confluence. The result is a holistic map of market structure in real time, showing how each asset aligns or diverges from others and how lower timeframes fit into the macro trend. Variables such as Live Trend, Vision Trend, Directional Strength, and Zone Positioning combine to give a complete structural snapshot at any given moment.
Risk management is handled by an adaptive Trailing Stop Engine that continuously aligns with current volatility and price flow. It integrates pivot mapping with ATR-based calculations to dynamically adjust stop-loss levels as price evolves. The engine offers four adaptive modes, Grip, Flow, Drift, and Glide, each tailored to different levels of market volatility and trader risk tolerance. In visualization, the profit area between entry and stop-loss is shaded light green for long positions and light red for short positions. This design allows immediate recognition of active risk exposure and profit lock-in zones, all in real time.
Altogether, the combination of ATR Volatility Mapping, Fibonacci Band Calibration, Regression-Based Trend Engine, Dynamic Supply and Demand Equilibrium, Conflict Detection through Hollow Candles, Mean Reversion Signal Model, and Adaptive Trailing Stop forms a unified analytical system. It maps the market’s structure, identifies current and future trends, measures the real-time balance of buyers and sellers, and highlights optimal entry and exit points. The final result is higher analytical precision, improved risk control, and a clearer view of the true, data-defined market structure.
🔵 How to Use
Analyzing supply and demand in live financial markets is one of the most complex challenges traders face. Price rarely moves in a straight line; instead, it evolves through phases of expansion, compression, and redistribution. Many traders misinterpret these movements because the zones that appear strong or reactive at first glance often represent nothing more than temporary liquidity redistributions.
These areas, while visually convincing, may lose relevance quickly when volatility increases or when viewed from another timeframe. In high-volatility environments, traditional zone analysis becomes even more unreliable. Price may seem to respect a support or resistance level only to break through it a few candles later. This behavior creates false zones and misleading reversal points.
The key to filtering such movements lies in understanding the context, how volatility, momentum, and structural flow interact across different timeframes. A single timeframe can only tell part of the story. The market’s true structure emerges only when data is synchronized from macro to micro levels.
This is where multi-timeframe correlation becomes essential. Every timeframe offers a different lens through which supply and demand balance can be observed. For example, a trader might see a bullish setup on a 15-minute chart while the 4-hour chart is still showing a strong distribution phase. Without alignment between these layers, trades are easily positioned against the dominant liquidity flow. The model presented here solves this by processing all relevant timeframes simultaneously, allowing traders to see how short-term movements fit within higher-level structures.
Each market phase, whether accumulation, expansion, or reversion, carries a unique volatility fingerprint. The system tracks transitions in volatility regimes, momentum divergence, and structural breakouts to anticipate when a phase change is approaching. For instance, when volatility compresses and ATR readings narrow, it often signals an upcoming breakout or reversal. By monitoring these shifts in real time, the model helps the trader differentiate between liquidity grabs (temporary volatility spikes) and genuine structural changes.
Every supply-demand interaction within this system is adaptive rather than static. The zones continuously recalibrate based on live parameters such as price velocity, momentum distribution, and liquidity displacement. This adaptive structure ensures that the balance between buyers and sellers is represented accurately as market conditions evolve.
In practice, this allows the user to identify early signs of trend exhaustion, potential reversals, and continuation patterns long before traditional indicators would react.
In essence, successful supply and demand analysis requires moving beyond subjective interpretation toward data-driven decision-making.
Manual drawing of zones or relying solely on visual intuition can lead to inconsistent results, especially in fast-changing markets. By combining ATR-driven volatility mapping, mean reversion dynamics, and multi-timeframe alignment, this framework offers a clear, objective, and responsive model of how market forces actually operate. Each decision becomes grounded in measurable context, not assumptions.
The analytical interface is divided into two main sections : the visual chart framework and the scanner data table.
On the chart, five dynamic bands and seven analytical zones appear around price. These are calculated from ATR, regression moving average, and Fibonacci expansion ratios to define whether the market is overbought, oversold, or neutral. Each zone has distinct color coding, allowing traders to recognize the market state instantly without switching tools or indicators.
Price movement within these bands reveals more than just direction, it tells a story of volatility, liquidity flow, and market equilibrium. The upper zones typically indicate exhaustion of buying pressure, while lower zones highlight areas of overselling or potential recovery. The way price reacts near these boundaries can help determine whether a continuation or reversal is likely.
At the heart of the visualization are two layered trend components : Live Trend and Vision Trend.
The Live Trend shows the present market direction based on regression and smoothing logic, while the Vision Trend projects the probable future trajectory by analyzing slope deviation and momentum displacement. When these two align, the trader sees confirmation of market strength. When they diverge, candle bodies turn hollow, a simple yet powerful visual alert signaling hesitation, consolidation, or a possible turning point.
At the bottom of the interface, the Scanner Table organizes all analytical data into a structured display. Each row corresponds to a symbol and timeframe, showing the current Live Trend, Vision Trend, Directional Strength, Zone Position, and Signal Age. This table provides a real-time overview of all assets being tracked, showing which ones are trending, which are in reversal, and which are entering transition zones. By analyzing this table, traders can instantly identify correlation clusters, where multiple assets share the same trend direction, often a sign of broader market sentiment shifts.
The Scanner can simultaneously process multiple timeframes and up to twenty different assets, producing a panoramic market overview. This makes it easy to apply a top-down analytical workflow, starting with higher timeframe alignment, then drilling down into lower levels for execution. Instead of reacting to isolated signals, traders can see where confluence exists across structures and focus only on setups that align with overall market context.
The bands and their color coding make interpretation intuitive even for less experienced users. Darker shades correspond to extreme zones, typically where institutional orders are being absorbed or distributed, while lighter zones mark mild overbought or oversold conditions. When price transitions from an outer extreme zone into a milder region, a signal condition becomes active. At this point, traders can cross-check the event using momentum and volatility filters before acting.
The trailing stop section of the display adds another critical dimension to decision-making. It visualizes stop levels as continuously updating colored lines that follow price movement. These levels are calculated dynamically through pivot mapping and ATR-based sensitivity. The shaded area between the entry point and active stop loss (light green for buys, light red for sells) gives traders immediate insight into how much of the move is currently secured as profit and how much remains exposed. This simple visual cue transforms risk management from a static calculation into a living, responsive process.
All components of this analytical system are fully customizable. Users can adjust signal type, calculation periods, smoothing intensity, and band sensitivity to match their trading style. For example, a scalper might shorten ATR and MA periods to capture rapid fluctuations, while a swing trader might increase them for smoother and more stable readings. Because every element responds to live data, even small adjustments lead to meaningful changes in how the system behaves.
When combined with the scanner’s data table, these features enable a top-down analytical workflow, one where decisions are not made from isolated indicators but from a complete, multi-dimensional understanding of market structure. The result is a system that supports both reactive precision and proactive market awareness.
🟣 Long Signal
A long signal is generated when price begins to rebound from deeply oversold conditions. More precisely, when price enters the strong or extreme oversold zones and then returns into the mild oversold region, the system identifies the start of a mean reversion phase. This transition is not based on subjective interpretation but on mathematical deviation from equilibrium, meaning that selling pressure has been exhausted and liquidity begins to shift toward buyers.
Unlike delayed signals that depend on moving average crossovers or oscillators, this signal appears the moment price starts moving back toward balance. The model’s mean reversion logic detects when volatility contraction and momentum realignment coincide, producing a non-lagging entry condition.
In this situation, traders can visually confirm the setup by observing the spacing and curvature of the lower bands. When the lower volatility bands begin to flatten or curve upward while ATR readings stabilize, it indicates that the market is transitioning from distribution to accumulation.
The strength and quality of each long signal depend on the configuration of trend variables. When both Live Trend and Vision Trend are bullish, the probability of continuation is significantly higher. This alignment suggests that the market’s short-term momentum is supported by long-term structure. On the other hand, when the two trends contradict each other, which the chart highlights with hollow candles, it represents a temporary phase of indecision or conflicting forces.
In these moments, traders are encouraged to monitor volatility compression and observe whether the next few candles confirm a real breakout or revert back to range conditions.
Additional confirmation can be derived from observing the slope of the regression moving average and the magnitude of ATR fluctuations. A steeper upward slope combined with decreasing volatility indicates stronger bullish intent. In contrast, if ATR expands while price remains flat, it signals potential traps or fakeouts driven by short-term liquidity grabs.
Valid long signals often emerge near the end of volatility compression periods or immediately after liquidity sweeps around major lows. These are points where large players typically absorb remaining sell orders before initiating upward movement. Once the long condition triggers, the system automatically calculates the initial stop loss using a combination of recent pivots and ATR range. From that point, the Trailing Stop Engine dynamically adjusts as price rises, maintaining optimal distance from the entry point and locking in profits without restricting trade potential.
For educational context, consider a situation where the market has been trending downward for several sessions, and the ATR value begins to decline, showing that volatility is compressing. As price touches the lower extreme zone and reverses into the mild oversold region while Live Trend starts turning positive, this creates an ideal long condition. A new cycle of expansion often begins right after such compression, and the system captures that early shift automatically.
🟣 Short Signal
A short signal represents the opposite scenario, a point where buying momentum weakens after a strong rally, and price begins to revert downward toward equilibrium. When price exits the strong or extreme overbought zones and moves into the mild overbought region, the model detects the start of a bearish mean reversion phase.
Here too, the signal appears without delay, as it is based on the real-time relationship between price and its volatility boundaries rather than on indicator crossovers.
The system identifies these short conditions when upward momentum shows visible fatigue in the volatility bands. The upper bands start to flatten or turn downward while the regression slope begins to lose angle. This is often accompanied by rising ATR readings, showing an expansion in volatility that reflects distribution rather than continuation.
The quality of the short signal is strongly influenced by the interaction between the two trend layers. When both Live Trend and Vision Trend point downward, the likelihood of sustained bearish continuation increases dramatically. However, if they diverge, candle bodies turn hollow, clearly marking zones of conflict or hesitation. These phases often coincide with the end of a bullish impulse wave and the start of an early correction.
A practical example can illustrate this clearly. Imagine a market that has been trending upward for several days with expanding volatility. When price pushes into the extreme overbought zone and starts pulling back into the mild region, the system interprets it as the first sign of distribution. If at the same time the regression moving average flattens and ATR begins to rise, it strongly suggests that institutional participants are taking profit. The generated short signal allows the trader to position early in anticipation of the downward reversion that follows.
The initial stop loss for short trades is calculated above the most recent pivot high, ensuring logical protection based on the structural context. From there, the Trailing Stop Engine automatically tracks the price movement downward, tightening stops as volatility decreases or expanding them during sharp swings to avoid premature exits.
The engine’s dynamic nature makes it suitable for both aggressive scalpers and patient swing traders. Scalpers can set the trailing sensitivity to “Grip” mode for tighter control, while swing traders can use “Glide” mode to capture larger portions of the trend.
Most short signals form right after volatility expansion or liquidity grabs around major highs, classic exhaustion areas where momentum divergence becomes evident. The combination of visual cues (upper band curvature, hollow candles, ATR spikes) provides traders with multiple layers of confirmation before taking action.
In both long and short scenarios, this analytical system replaces emotional decision-making with structured interpretation. By translating volatility, momentum, and price positioning into clear contextual patterns, it empowers the trader to see where reversals are forming in real time rather than guessing after the move has started.
🔵 Setting
🟣 Logical Setting
Channel Period : The main channel period that defines the base moving average used to calculate the central line of the bands. Higher values create a smoother and longer-term structure, while lower values increase short-term sensitivity and faster reactions.
Channel Coefficient Period : The ATR period used to measure volatility for determining the channel width. Higher values provide greater channel stability and reduce reactions to short-term market noise.
Channel Coefficient : The ATR sensitivity factor that defines the distance of the bands from the central average. A higher coefficient widens the bands and increases the probability of detecting overbought or oversold conditions earlier.
Band Smooth Period : The smoothing period applied to the bands to filter minor price noise. Lower values produce quicker reactions to price changes, while higher values create smoother and more stable lines.
Trend Period : The period used in the regression moving average calculation to identify overall trend direction. Shorter values highlight faster trend shifts, while longer values emphasize broader market trends.
Trend Smooth Period : The smoothing period for the regression trend to reduce volatility and confirm the dominant market direction. This setting helps to better distinguish between corrective and continuation phases.
Signals Gap : The time interval between generated signals to prevent consecutive signal clustering. A higher value strengthens the temporal filter and produces more selective and refined signals.
Bars to Calculate : Defines the number of historical candles used in calculations. Limiting this value optimizes script performance and reduces processing load, especially when multiple symbols or timeframes are analyzed simultaneously. Higher values increase analytical depth by including more historical data, while lower values improve responsiveness and reduce potential lag during live chart updates.
Trailing Stop : Enables or disables the dynamic trailing stop engine. When active, the system automatically adjusts stop loss levels based on live volatility and price structure, maintaining alignment with market flow and trend direction.
Trailing Stop Level : Defines the operational mode of the trailing stop engine with four adaptive styles: Grip, Flow, Drift, and Glide. Grip offers tight stop management for scalping and high precision setups, while Glide allows wider flexibility for swing or long-term trades.
Trailing Stop Noise Filter : Applies an additional filtering layer that smooths minor fluctuations and prevents unnecessary stop adjustments caused by short-term market noise or micro volatility.
🟣 Display Settings
Show Trend on Candles : Displays the current trend direction directly on price candles by applying dynamic color coding. When Live Trend and Vision Trend align bullish, candles appear in green tones, while bearish alignment displays in red. If the two trends conflict, candle bodies turn hollow, marking a Trend Conflict Zone that signals potential indecision or upcoming reversal. This feature provides instant visual confirmation of market direction without the need for external indicators
Table on Chart : Allows users to choose whether the analytical table appears directly over the chart or positioned below it. This gives full control over screen layout based on personal workspace preference and chart design.
Number of Symbols : Controls how many symbols are displayed in the screener table, adjustable from 10 up to 20 in steps of 2. This flexibility helps balance between detailed screening and visual clarity on different screen sizes.
Table Mode : Defines how the screener table is visually arranged.
Basic Mode : Displays all symbols in a single column for vertical readability.
Extended Mode : Arranges symbols side by side in pairs to create a more compact and space-efficient layout.
Table Size : Adjusts the visual scaling of the table. Available options include auto, tiny, small, normal, large, and huge, allowing traders to optimize table visibility based on their screen resolution and preferred chart density.
Table Position : Determines the exact placement of the screener table within the chart interface. Users can select from nine available alignments combining top, middle, and bottom vertically with left, center, and right horizontally.
🟣 Symbol Settings
Each of the 10 available symbol slots includes a full range of adjustable parameters for personalized analysis.
Symbol : Defines or selects the asset to be tracked in the screener, such as XAUUSD, BTCUSD, or EURUSD. This enables multi-asset scanning across different markets including forex, commodities, indices, and crypto.
Timeframe : Sets the specific timeframe for analysis for each selected symbol. Examples include 15 minutes, 1 hour (60), 4 hours (240), or 1 day (1D). This flexibility ensures precise control over how each asset is monitored within the multi-timeframe structure.
🟣 Alert Settings
Alert : Enables alerts for AAS.
Message Frequency : Determines the frequency of alerts. Options include 'All' (every function call), 'Once Per Bar' (first call within the bar), and 'Once Per Bar Close' (final script execution of the real-time bar). Default is 'Once per Bar'.
Show Alert Time by Time Zone : Configures the time zone for alert messages. Default is 'UTC'.
🔵 Conclusion
Understanding financial markets requires more than indicators, it demands a framework that captures the interaction of price, volatility, and structure in real time. This analytical system achieves that by combining mean reversion logic, volatility mapping, and dynamic supply and demand modeling into an adaptive, data-driven environment. Its computational bands and trend layers visualize market intent, showing when momentum is strengthening, fading, or preparing to shift.
Each signal, derived from statistical equilibrium rather than delayed indicators, reflects the exact moment when the balance between buyers and sellers changes. Variables like Live Trend, Vision Trend, Directional Strength, and ATR-based Volatility Context help traders assess signal quality and alignment across multiple timeframes. The system blends automation with human interpretation, preserving macro-to-micro consistency and enabling confident entries, exits, and stop management through its adaptive Trailing Stop Engine.
Every component, from color-coded zones to hollow candles, forms part of a broader narrative that teaches traders to read the market’s language instead of reacting to it. Built on self-correcting analysis, the framework continuously recalibrates with live data. By transforming volatility, liquidity, and price behavior into structured insight, it empowers traders to move from reaction to prediction, a living ecosystem that evolves with both the market and the trader.
สคริปต์แบบชำระเงิน
SMC FVG/IFVG (Multi-TF x 4) [ZAUTEC]SMC FVG/IFVG (Multi-TF x 4): Multi-Timeframe Fair Value Gap with Inversed FVG Detection
This powerful Pine Script indicator is designed to help traders identify, track, and manage Fair Value Gaps (FVGs) and their respective Inversed Fair Value Gaps (IFVGs) across up to four different timeframes simultaneously.
Key Features
Multi-Timeframe Analysis (4x): Analyze and display FVGs from four distinct timeframes alongside your current chart, offering a comprehensive view of market imbalances across various scales.
Fair Value Gap (FVG) Detection: Automatically identifies classic three-candle FVGs (market inefficiencies).
Customizable FVG Length: Set how many bars the FVG boxes should initially extend for.
Minimum Gap Size: Filter out minor, insignificant gaps using a tick-based minimum size threshold.
Optional Box Extension: Dynamically extend FVG boxes to the current bar index or use a fixed extension for a cleaner chart.
Inversed FVG (IFVG) Logic: Detects a high-probability reversal pattern where a previously filled FVG zone is immediately followed by the formation of a new, opposite FVG within or adjacent to the same area. This confirms the old FVG has "flipped roles" (e.g., from support to resistance).
Lookback Period: Defines how long the indicator searches for a corresponding FVG breach to confirm the IFVG.
IFVG Minimum Size: Customizable minimum size threshold for the IFVG.
Dynamic Box Management:
Automatic Fill Deletion: FVGs are automatically removed from the chart when price action fully trades through the gap, signifying the imbalance has been "filled."
IFVG Tracking: IFVGs are tracked and removed from the chart after the configurable lookback period.
Full Customization: Control the visibility, colors, border styles (solid, dashed, dotted), and width for FVG, Bearish FVG, Bullish FVG, and IFVG boxes independently for each of the four timeframes.
How to Use
Select Timeframes: Choose up to four desired timeframes in the settings (e.g., "15" for 15-minute, "4H" for 4-hour, "D" for Daily). Leave the field empty to use the chart's current timeframe.
Toggle Visibility: Use the Show FVG and Show IFVG toggles to focus on the imbalances you wish to see.
Adjust Extension: Set Extend Boxes to bar index to true to keep all open FVG boxes drawn all the way to the current live price bar.
Interpret the Gaps:
FVG (Bullish/Bearish): Potential areas for price to return to and find support/resistance.
IFVG (Inverse FVG): Stronger signals that a previous zone of imbalance has been violated and is likely to act as a significant flip zone for future price movements.
This indicator is an essential tool for traders utilizing concepts like ICT (Inner Circle Trader) and SMC (Smart Money Concepts), providing a clear visual representation of market structure and liquidity voids.
FVG Buy/Sell [Multi-TF] by akshaykiriti1443The FVG Buy/Sell indicator is a precision trading tool designed for traders who operate with a clear directional bias. It excels at identifying high-probability entry points by detecting when price interacts with Fair Value Gaps (FVGs).
This indicator is built on a core principle: instead of predicting the market's direction, it provides the timing for an entry after you, the trader, have established your market bias. By automatically pinpointing bullish and bearish imbalances on both the current and a higher timeframe, it allows you to wait for the market to pull back to a key level and then provides a clear signal for execution.
The Core Strategy: Bias First, Entry Second
This indicator is most powerful when used as part of a two-step trading process. It is not a standalone signal generator; it is an entry confirmation tool.
Step 1: Determine Your Directional Bias
Before looking for any signals from this indicator, you must first have an opinion on the market's most likely direction. This bias should be derived from your primary analysis method, such as:
The Golden Rule:
If your bias is BULLISH, you will ONLY look for BUY signals generated by bullish (green/blue) FVGs. You will ignore all SELL signals.
If your bias is BEARISH, you will ONLY look for SELL signals generated by bearish (pink/orange) FVGs. You will ignore all BUY signals.
Step 2: Execute with the FVG Tap-In Signal
Once your bias is set, the indicator does the rest of the work. You simply wait for the price to pull back into an FVG zone that aligns with your bias and then wait for the confirmation arrow to appear.
A green up arrow confirms that price has tapped a bullish FVG and closed above it, signaling that support has held and it's a valid moment to enter a long position.
A red down arrow confirms that price has tapped a bearish FVG and closed below it, signaling that resistance has held and it's a valid moment to enter a short position.
How to Take a Trade (Step-by-Step Examples)
Example of a Bullish (Long) Trade Setup:
Establish Bias: Your primary analysis shows the market is in a clear uptrend. Your bias is Bullish. You are now only looking for buying opportunities.
Identify Zone: The indicator draws a bullish FVG (a green or blue box) during an impulsive up-move.
Wait for Pullback: Be patient and let the price retrace down into this FVG zone. Do not chase the price.
Confirmation Signal: A green UP arrow appears below a candle. This is your signal. It confirms that buyers have stepped in at the FVG level and defended it.
Entry: Enter a long (buy) position at the open of the candle immediately following the signal candle.
Stop Loss: Place your stop loss below the low of the signal candle or, for a safer stop, below the bottom of the FVG zone itself.
Take Profit: Target a previous high, a higher-timeframe resistance level, or use a risk-to-reward ratio like 1:2 or 1:3.
Example of a Bearish (Short) Trade Setup:
Establish Bias: Your primary analysis shows the market is breaking down into a downtrend. Your bias is Bearish. You are now only looking for selling opportunities.
Identify Zone: The indicator draws a bearish FVG (a pink or orange box) during an impulsive down-move.
Wait for Pullback: Patiently wait for the price to rally back up into this FVG zone.
Confirmation Signal: A red DOWN arrow appears above a candle. This is your confirmation that sellers have rejected the price at this level.
Entry: Enter a short (sell) position at the open of the next candle.
Stop Loss: Place your stop loss above the high of the signal candle or above the top of the FVG zone.
Take Profit: Target a previous low, a key support level, or the next major FVG below.
Features Explained in Detail
Multi-Timeframe (MTF) Analysis: HTF zones (dotted lines) carry more weight. A signal from a 4-hour FVG while you are on a 15-minute chart is significantly more powerful than a signal from a 15-minute FVG alone. Use HTF zones as major points of interest.
Confirmed Tap-In Logic: The arrow only appears after price has touched the zone and then closed outside of it in the expected direction. This built-in confirmation filters out wicks that simply pass through a zone without a real market reaction.
Dual Alert System:
Entry Alert ("Price has entered..."): This is a heads-up alert. It tells you to pay attention because price is now in your pre-defined zone of interest.
Tap-In Alert ("Confirmed tap-in..."): This is the execution alert. It signals that the conditions for a trade have been met according to the indicator's logic.
Fade on Tapped: When enabled, a zone will become transparent after a confirmed signal. This visually cleans up your chart, showing you which zones have already been tested and "mitigated."
Minimum FVG Size (Ticks): In volatile or ranging markets, many tiny, insignificant FVGs can form. Use this setting to filter out the noise. Increase the value to only display larger, more significant imbalances.
Disclaimer: Trading involves substantial risk. This indicator is a tool for analysis and should not be used as a sole reason to enter a trade. Always practice robust risk management and use this tool in conjunction with your own trading plan. Past performance is not indicative of future results.
Khosro XAUUSD Strategy [TradingFinder] Trading Room Hunter Setup🔵 Introduction
The Trading Room Hunter (TRH) strategy is an analytical model based on the Smart Money Concept, developed by Khosro, an Iranian international trader based in Dubai. This approach is built upon a deep understanding of liquidity engineering, market structure shifts, and institutional order flow. Its core objective is to identify the so-called TRH Zone, the area where market liquidity gets trapped and institutional investors begin accumulating positions. Unlike traditional indicator-based methods, the TRH Zone focuses purely on price behavior and supply & demand dynamics to pinpoint the most precise reversal zones in the market.
Within Smart Money logic, every impulsive move in price results from the displacement or absorption of liquidity in a specific range. In the TRH model, the last pivot preceding the impulsive move (Origin Pivot) is defined as the Distal Line, and the Break Candle, which disrupts the market structure, forms the Proximal Line. The area between these two points defines the Trading Room Hunter Zone, a reaction zone where price, after creating a displacement or Break of Structure (BoS), often returns to fill an imbalance and provide a precision entry opportunity.
In essence, the TRH Zone is the region where smart money seeks re-entry after a liquidity sweep and a confirmed CHoCH or BoS. It frequently lies between supply/demand boundaries and fair value gaps (FVGs), forming one of the strongest decision-making frameworks within modern price-action theory. Due to its structural accuracy, the TRH setup can also function as a Set & Forget Setup, where the trader defines the zone, places a limit order, and lets the market naturally react, eliminating emotional decision-making and allowing for automated execution aligned with institutional logic.
🔵 How to Use
In the TRH strategy, entries are taken based on price returning to the area between the last impulsive pivot and the break candle. This range (the TRH Zone) represents the region where liquidity from the previous move remains concentrated. Before continuing its main direction, price often revisits this zone to fill imbalances or mitigate unfilled orders. The logic is simple: every explosive move originates from a point where large orders were executed, and TRH precisely highlights that institutional footprint.
🟣 Bullish Setup
When the market breaks a structural high after a strong bearish leg, liquidity shifts from sellers to buyers. The last bearish candle before the breakout marks the origin of the bullish move, and the zone between that candle and the break candle becomes the smart-money entry area. As price revisits this zone and signs of exhaustion in selling pressure appear, that’s the optimal point for a long position. Stop-loss is placed slightly below the origin pivot, and targets are set at the next supply zone or upper liquidity pool.
🟣 Bearish Setup
Conversely, when the market breaks a structural low after a sharp bullish leg, liquidity transitions from buyers to sellers. The last bullish candle before the drop is identified as the origin pivot, while the bearish break candle defines the lower boundary of the zone. The range between these two points forms the TRH Supply Zone, where late buyers are trapped and fresh institutional selling begins. As price retraces into this zone, short entries can be placed near the upper boundary, with stops above the pivot and targets toward the next liquidity pool below.
Because of its structural precision and clearly defined reaction behavior, TRH is one of the most effective Set & Forget setups in Smart Money trading. Simply mark the zone, place your order, and let the market do the rest.
🔵Setting
🟣 Spike Filter | Movement
Minimum Spike Bars : Defines the minimum number of consecutive candles required for a valid spike.
Movement Power : Enables or disables the momentum-based spike filter.
Movement Power Level : Sets the strength threshold; higher values filter out weaker moves and only detect strong spikes.
Pivot Period : Defines the lookback range used to detect swing highs and swing lows in market structure. A higher value smooths out smaller fluctuations and focuses on major pivots, while a lower value increases sensitivity and identifies minor turning points more frequently.
🟣 Position Management
Stop-Loss Threshold : Enables or disables the stop-loss threshold feature.
Stop-Loss Threshold Value : Defines the value of the stop-loss threshold for risk management.
Risk-Reward Ratio : Sets the desired risk-to-reward ratio (e.g., 1:1 or 1:2).
Wide Zone Filter : Filters out zones that exceed a defined width threshold, preventing detection of overly broad TRH areas.
🟣 Display Settings
Display Mode : Chooses between Setup (showing setups) or Signal (showing trade signals).
Show Entry Levels : Displays entry levels on the chart (buy/sell zones) when enabled
Only Display the Last Position : Displays only the most recent position on the chart when enabled.
Setup Width Drawing : Adjusts the visual width of the setup drawings on the chart for better visibility.
🔵 Conclusion
The TRH strategy is a precise structural model of liquidity flow that identifies zones where smart money is most likely to enter and where price is most likely to react. By combining the Origin Pivot and Break Candle, TRH isolates the key areas that drive institutional order flow. Without relying on indicators, it focuses purely on price structure, making it highly effective for both reactive entries and Set & Forget setups.
Ultimately, TRH creates a balance between market structure and liquidity flow, enabling traders to identify institutional decision zones on the chart with minimal risk and maximum clarity
Orderblocks & BreakersThis indicator identifies potential orderblocks and breakers based on recent swing highs and lows. It is built to offer a structured, customizable, and noise-controlled view of how price interacts with supply and demand levels.
The script applies pivot-based swing detection to identify swing highs and lows.
Bullish Orderblocks: The script Identifies and stores the last down candle before a swing high is breached and confirms and plots the orderblock with a market structure break (close above the swing high).
Bearish Orderblocks: The script Identifies and stores the last up candle before a swing low is breached and confirms and plots the orderblock with a market structure break (close below the swing low).
When price later closes through an existing orderblock, it is reclassified as a Breaker and recolored accordingly. (all colors can be changed in the settings)
What Makes It Different
Unlike most orderblock tools that simply mark every swing-based block, this version introduces:
1. Chop Control – automatically hides breakers that price repeatedly closes through (2 closes after the orderblock becomes a breaker), keeping only relevant zones visible.
2. Recent Block Filtering – limits how many of the recent orderblocks or breakers are displayed, preventing chart clutter.
3. Dynamic Updating – orderblocks automatically convert to breakers when price closes beyond them, with clear color changes.
These features make it easier to study cleaner price structure without manually managing old or invalid zones. The optional Chop Control filter can reduce overlapping or repeatedly invalidated zones to keep the chart clearer.
Customizable Parameters
- Swing detection length (shorter means more aggressive pivot detection, longer means less aggressive so less highs/lows detected)
- Number of recent blocks to display
- Visibility toggles for orderblocks or breakers
- Color and transparency controls for each type
Alerts
Alerts can be set to trigger when price tests any defined zone.
Purpose
This indicator is designed as a price structure visualization and study tool.
It may assist in understanding how price interacts with previously active regions, but it does not produce signals or trade recommendations.






















