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Liquiditygrab

Volume Liquidity Sweep - XWiseTradeCatch liquidity sweeps the moment volume confirms them. Price loves to spike past a prior high or low, grab the stops sitting there, then snap back. This indicator catches those sweeps — but only when volume confirms real participation, filtering out the quiet fakeouts. What it shows: •Auto-detected swing highs / lows (where liquidity rests) •Bull sweep — price wicks below a prior low, then closes back above, on rising volume •Bear sweep — price wicks above a prior high, then closes back below, on rising volume •Swept levels marked on the chart Features: •Volume confirmation built into every sweep — no low-volume noise •Adjustable pivot lookback and volume threshold •Signal cooldown to keep the chart clean •Built-in alerts Great for traders who track liquidity grabs, stop hunts, and reversals after a sweep.
Chỉ báo Pine Script®
của xwisetrade
Liquidity Sweeps [Quantum Algo]Liquidity Sweeps is an open-source liquidity sweep indicator that maps resting liquidity at swing highs and swing lows, then flags the exact moment that liquidity is swept and rejected — the classic stop-hunt behaviour traders watch for in Smart Money Concepts (SMC). WHAT IS A LIQUIDITY SWEEP? A liquidity sweep (also called a liquidity grab or stop hunt) happens when price briefly spikes beyond an obvious swing high or swing low — where stop-loss and breakout orders rest — and then closes back inside the prior range. The wick takes the liquidity; the close shows the breakout failed. Liquidity sitting above swing highs is buy-side liquidity (BSL); liquidity sitting below swing lows is sell-side liquidity (SSL). A bearish liquidity sweep occurs when buy-side liquidity above a swing high is swept and price closes back below it. A bullish liquidity sweep occurs when sell-side liquidity below a swing low is swept and price closes back above it. HOW THE INDICATOR WORKS - It detects confirmed swing highs and swing lows using a configurable pivot strength, and draws a liquidity level at each one. Buy-side levels sit above price; sell-side levels sit below. - Each level extends to the right until it is interacted with. - When a candle wicks through a level but closes back inside, the indicator marks a liquidity sweep with a label and an optional highlight on the sweeping wick. - An optional volume filter confirms only sweeps where the sweeping candle trades above its average volume, filtering out low-conviction wicks. - If price instead closes fully through a level, that is treated as a clean break (a plain liquidity grab / breakout), not a sweep, and the level is retired without a signal. WHAT IT SHOWS - Mapped buy-side (BSL) and sell-side (SSL) liquidity levels. - Bullish and bearish liquidity sweep markers, the moment a level is swept and rejected. - Optional wick highlighting on the sweep candle. - A dashboard showing bullish/bearish sweep counts, the last sweep direction, and the nearest un-swept buy-side and sell-side levels with their percentage distance from price. HOW TO USE IT Liquidity sweeps are most useful as a timing and context tool, not a standalone buy/sell system. A common workflow: - Mark the obvious highs and lows where liquidity is likely resting. - Wait for a sweep into one of those pools (a wick through, close back inside), ideally with the volume filter confirming participation. - Look for confirmation in your own process — a market-structure shift, an order block, a fair-value-gap fill, or higher-timeframe trend alignment — before acting. - A bearish sweep above resistance can precede a move down; a bullish sweep below support can precede a move up. Always define risk beyond the swept extreme. SETTINGS - Pivot Strength: how many bars define a swing; higher values keep only major liquidity pools. - Max Levels per Side: how many recent levels to keep mapped. - Volume Confirmation: toggle, average length, and multiplier to qualify a sweep. - Treat Clean Breaks as Grabs: retire levels that are broken through rather than swept. - Line width, style, and transparency for clear level visibility. - Full colour controls and a movable dashboard. ALERTS Three named alert conditions are included: Bullish Liquidity Sweep, Bearish Liquidity Sweep, and Any Liquidity Sweep. DISCLAIMER For educational purposes only. This is a technical analysis tool, not financial advice, and it does not predict price. Trading involves risk and you can lose your capital. No indicator is profitable on its own — always do your own research and use proper risk management.
Chỉ báo Pine Script®
của Quantum-Algo
The Blueprint by RossenHouseThe Blueprint by RossenHouse is a precision‑built market structure tool designed to track 4‑Hour sweep setups and project their key levels onto any lower timeframe, from 1H all the way down to 1‑minute charts. This script automatically detects both forming and confirmed 4H sweeps using wick‑based logic and body‑validation rules. Once a sweep is identified, the indicator anchors: A 4H sweep line at the exact wick of the swept candle 25% / 50% / 75% fib levels derived from the 4H range All levels projected forward with perfect time alignment using bar‑time anchoring The result is a clean, non‑repainting multi‑TF view of higher‑timeframe liquidity events, allowing traders to zoom into lower timeframes while maintaining full awareness of the dominant 4H structure. Ideal for traders who rely on liquidity sweeps, premium/discount zones, and HTF‑to‑LTF execution
Chỉ báo Pine Script®
của JamminToast
1
Elaris Session Liquidity Grabs Pro# Elaris Session Liquidity Grabs Pro Elaris Session Liquidity Grabs Pro is a professional session-based liquidity sweep and reversal detection tool designed for traders who focus on smart money concepts, stop hunts, failed breakouts, and institutional liquidity behavior. The indicator automatically builds key liquidity ranges from major global trading sessions including London, New York, and Asia, then detects high-probability liquidity grabs when price sweeps session highs or lows and rejects back into range. Unlike basic sweep indicators, this tool includes advanced filtering systems designed to reduce noise and focus on stronger reversal conditions using ATR displacement, candle strength analysis, EMA trend filtering, and optional volume confirmation. Built for active intraday traders, scalpers, and smart money traders, the indicator provides a clean visual framework for identifying areas where liquidity may have been engineered before a market reversal or continuation move. ━━━━━━━━━━━━━━━━━━ FEATURES ━━━━━━━━━━━━━━━━━━ • Automatic London, New York, and Asia session ranges • Session high/low liquidity tracking • Bullish and bearish liquidity grab detection • Wick sweep and close-break detection modes • ATR-based sweep validation filters • Strong displacement candle confirmation • EMA trend filter for directional bias • Volume confirmation filter • Optional cooldown system to reduce signal clustering • Session equilibrium (midline) plotting • Clean session range visualization • Professional dashboard panel • Dark mode and light mode support • Alert conditions for automation and notifications • Non-repainting confirmed signals ━━━━━━━━━━━━━━━━━━ HOW IT WORKS ━━━━━━━━━━━━━━━━━━ The indicator builds liquidity ranges from selected market sessions and monitors price action after those sessions complete. When price aggressively sweeps a session high or low and then rejects back into the range, the indicator identifies it as a potential liquidity grab event. Examples: • Price sweeps above London High and closes back below → potential bearish liquidity grab • Price sweeps below New York Low and closes back above → potential bullish liquidity grab Additional confirmation filters help reduce weak or low-quality signals by requiring stronger candle displacement, trend alignment, and optional volume expansion. ━━━━━━━━━━━━━━━━━━ BEST USE CASES ━━━━━━━━━━━━━━━━━━ • Smart money trading concepts • Session liquidity trading • Stop hunt reversals • Scalping and intraday trading • ICT-style trading approaches • Breakout failure detection • Market manipulation detection ━━━━━━━━━━━━━━━━━━ RECOMMENDED MARKETS ━━━━━━━━━━━━━━━━━━ • Crypto Futures • Forex • Indices • Gold and Commodities ━━━━━━━━━━━━━━━━━━ RECOMMENDED TIMEFRAMES ━━━━━━━━━━━━━━━━━━ • 1 Minute • 3 Minute • 5 Minute • 15 Minute ━━━━━━━━━━━━━━━━━━ NON-REPAINTING ━━━━━━━━━━━━━━━━━━ This indicator is designed to be non-repainting. Signals are confirmed only after candle close and session levels are finalized after the session completes. No future data is used. ━━━━━━━━━━━━━━━━━━ NOTES ━━━━━━━━━━━━━━━━━━ This tool is designed to assist with identifying liquidity behavior and market structure reactions. It should be used alongside proper risk management, higher timeframe analysis, and additional trade confirmation techniques. No indicator guarantees profitability or win rate consistency across all market conditions.
Chỉ báo Pine Script®
của ElarisGroup
Liquidity Swings [ Zero Lag ] - FloAlgoThis indicator identifies and tracks liquidity pools at swing highs and lows — a key Smart Money Concepts tool for visualizing institutional order flow and potential reversal zones. How It Works The script operates in three stages: Pivot Detection — Confirmed swing highs and lows are identified using a lookback period, establishing the outer boundaries of resting liquidity pools. Zone Tracking — For each pivot, the script counts how many subsequent bars trade through the liquidity zone (wick tip to body edge) and accumulates the total volume of those touches, revealing market interest at each level. Cross Event — When price closes beyond a pivot's extreme, the level is marked as "consumed" — liquidity has been taken and the level becomes a dashed historical reference rather than an active trading zone. Visual Elements Solid horizontal lines extending from pivot levels to current price Semi-transparent zone boxes spanning from wick tip to body edge Dashed lines marking levels where liquidity has been consumed Volume/count labels pinned at pivot bars showing accumulated activity Color-coded zones: red for supply (highs), green for demand (lows) Key Settings Pivot Lookback — Sensitivity of pivot high/low detection Swing Area — Zone definition: Wick Tip to body edge, or Full Range (wick to opposite wick) Filter Areas By — Display threshold metric: Count (number of touches) or Volume (total volume) Filter Value — Minimum threshold — zones only appear when activity exceeds this value Swing High/Low — Toggle visibility of supply or demand zones Label Size — Size of volume/count labels displayed on chart
Chỉ báo Pine Script®
của FloAlgo
3
SMC Setup: Sweep + CHoCH + FVG v21.1SMC Setup: Sweep + CHoCH + FVG v21.1 (Multi-Timeframe Execution Engine) Introducing a complete, institutional-grade Smart Money Concepts (SMC) execution algorithm. This is not just a standard sweep indicator; it is a "3D" Top-Down Analysis Engine designed to flawlessly mimic how professional human traders track order flow across multiple timeframes, natively executing on your lower-timeframe charts. Built to solve the common pitfalls of algorithmic SMC (such as repainting, MTF blindness, and zero-width visual crashes), this indicator tracks Major (External) and Minor (Internal) liquidity simultaneously and automates your entire entry and trade management visualization. 🔥 Core Features Multi-Timeframe (MTF) "Time-Warp" Engine: Track 15-minute and 5-minute structural liquidity sweeps natively on the 1-minute execution chart. The script uses internal mathematical multipliers and a massive 5000-bar deep memory buffer to track HTF structure without relying on laggy or repainting request.security() calls. Dual-Fractal Liquidity Tracking: * Solid Blue Lines: Tracks Major/External Higher Timeframe liquidity peaks. Dotted Blue Lines: Tracks Minor/Internal Lower Timeframe pullbacks for aggressive continuation order flow. Two Selectable Entry Models: BOS Breakout: For aggressive momentum traders. Executes the exact millisecond the micro-structure BOS (Break of Structure/CHoCH) line is cracked. FVG Pullback: For conservative traders. Waits for a Break of Structure, verifies a Fair Value Gap has formed, and sets a limit entry exactly at the FVG boundary. Dynamic Visual Trade Management: The script automatically generates a physical Risk Zone Box (mimicking the native TradingView Short/Long Position tools) and projects dynamic, trailing lines for your Entry, Stop Loss, TP1, TP2, and Full Target based on customizable Risk:Reward settings. Webhook-Ready Alerts: Generates highly detailed, once-per-bar-close alerts containing dynamic strings for Entry Price, Stop Loss, and all Take Profit targets, making it perfect for automated execution via 3Commas, PineConnector, etc. ⚙️ How It Works (The Logic Flow) The Hunt: The algorithm maps higher timeframe peaks (e.g., 15m/5m) and local micro-peaks simultaneously. The Sweep: When price sweeps a mapped liquidity line, the algorithm "arms" the setup and locks the Stop Loss to the highest point of the sweep. The CHoCH/BOS: It tracks the immediate local pullback prior to the sweep. If price breaks this micro-structure support, the setup is confirmed. The Execution: Depending on your selected model, it either triggers instantly on the BOS breakout or waits for a bearish FVG pullback. The Management: Target lines trail alongside price action and automatically lock into place the moment the trade hits the Full Target or the Stop Loss. 💡 Best Practices Optimal Use: Load this indicator on the 1-minute chart. Set the Major HTF Multiplier to 15 and the Minor HTF Multiplier to 5. This allows the script to see 15m and 5m market structure while leveraging the 1-minute candles for surgical entries. Asset Classes: Highly effective on high-volume assets like Indices (NAS100, US30, SPX) and Forex (EURUSD, XAUUSD) during the London or New York sessions.
Chỉ báo Pine Script®
của shinattey
Heatmap Liquidity Zones [BigBeluga]🔵 OVERVIEW Heatmap Liquidity Zones is a higher-timeframe volume heatmap tool designed to reveal where liquidity is concentrated inside institutional ranges. Instead of plotting a traditional volume profile, this indicator builds a dynamic heatmap across each selected higher-timeframe candle. It highlights high-volume price clusters, filters significant liquidity zones, and extends them forward as actionable support/resistance levels. The result is a clean liquidity map that visualizes where participation is strongest — and where reactions are most likely to occur. 🔵 CORE CONCEPT HTF Range Segmentation — Each higher-timeframe candle (D/W/M or custom) defines a new accumulation range. ATR-Based Adaptive Binning — Vertical bin size is derived from ATR to maintain consistent resolution across volatility regimes. Volume Density Mapping — Volume is distributed into price bins and normalized relative to the highest-volume bin. Liquidity Filtering — Only bins exceeding a configurable percentage threshold are promoted to active liquidity levels. Self-Cleaning Zones — Liquidity levels automatically disappear once breached by price. 🔵 HOW IT WORKS 1️⃣ Higher-Timeframe Reset Logic When a new selected HTF candle begins, the previous range is finalized. A new accumulation range starts from that bar. High and Low are tracked dynamically throughout the segment. 2️⃣ ATR-Based Bin Construction ATR defines the vertical bin size (ATR × Multiplier). The total range is divided into up to Max Bins. This ensures bin resolution adapts automatically to volatility. 3️⃣ Volume Distribution For each completed segment, volume is distributed into bins based on proximity to bin midpoint. Volume per bin is normalized relative to the maximum bin. Each bin is assigned a heat color based on relative density: Low Density → Purple Mid Density → Cyan High Density → Yellow 4️⃣ Liquidity Zone Creation If a bin exceeds the Liquidity Filter %, it becomes a tracked liquidity level. Liquidity levels extend forward as horizontal lines. The thickness is controlled by Liquidity Level Width. Stronger zones display larger markers and percentage labels. 🔵 HEATMAP VISUAL STRUCTURE Completed segments display full heatmap boxes across the range. Active segment updates in real time. Color intensity reflects liquidity concentration. High-density zones stand out clearly for institutional reference. 🔵 OPTIONAL MOVING AVERAGE Optional smoothing MA overlay (SMA, EMA, RMA, WMA, VWMA). Hidden by default. Can be used for confluence with liquidity zones. 🔵 KEY FEATURES Higher-timeframe segmented liquidity mapping. ATR-based adaptive resolution. Three-stage heatmap gradient. Configurable liquidity filtering. Auto-expiring support/resistance levels. Dynamic zone thickness based on volume strength. Real-time developing heatmap. Optional MA overlay. 🔵 HOW TO USE Focus on yellow (high-density) zones for strongest liquidity pools. Watch reactions at filtered liquidity levels. Use HTF segmentation (Weekly/Monthly) to identify institutional positioning. Combine with breakout tools for liquidity sweep setups. Lower ATR multiplier → more granular liquidity clusters. Higher Liquidity Filter % → only strongest zones remain. 🔵 INTERPRETING LIQUIDITY High density near highs → potential distribution. High density near lows → potential accumulation. Clustered zones → compression areas before expansion. Thin zones → low participation, faster price movement potential. 🔵 CONCLUSION Heatmap Liquidity Zones transforms higher-timeframe volume into a structured liquidity map. By combining ATR-adaptive binning, density-based heat gradients, and intelligent liquidity filtering, it highlights where institutional participation is concentrated — and where meaningful reactions are most likely. This makes it especially powerful for identifying liquidity pools, sweep zones, and structural turning points.
Chỉ báo Pine Script®
của BigBeluga
6
Liquidity Sweep Detector [SSFX]Liquidity Sweep Detector is a price action indicator designed to highlight potential liquidity grabs around confirmed swing highs and swing lows. The script identifies pivot-based levels, tracks them forward on the chart, and detects when price briefly trades beyond those levels with the wick while failing to close through them with the candle body. This behavior is often associated with stop hunts, liquidity sweeps, and rejection-based reversals. The indicator is built to help traders quickly spot these events in a clear and structured way. The script first builds its framework using pivot highs and pivot lows. Each confirmed pivot becomes a horizontal reference level that remains active until it is either swept or mitigated. A bearish sweep is detected when price pushes above a pivot high with the wick, but the candle body remains below that level. A bullish sweep is detected when price trades below a pivot low with the wick, while the candle body remains above it. This allows the indicator to separate true wick rejections from full body breaks, which is useful for traders who want to focus specifically on liquidity-based price reactions rather than standard support and resistance breaks. To improve selectivity, the indicator also includes an optional volume filter. When enabled, sweeps are only marked if volume is greater than a configurable moving average threshold multiplied by a user-defined factor. This can help filter out weaker sweeps and emphasize events that occur with stronger market participation. Traders who prefer a cleaner chart can leave the volume filter disabled, while those who want more confirmation can use it to reduce noise. The script provides clear visual feedback directly on the chart. Active pivot levels are plotted as horizontal dashed lines. When a valid sweep occurs, the indicator draws a colored highlight between the level and the wick extreme, making the rejection area easy to identify. It also places a sweep marker exactly at the wick high or wick low of the sweep candle, rather than simply above or below the bar, which gives more precise visual alignment with the actual liquidity event. Bullish sweeps and bearish sweeps use separate colors so both directions can be distinguished instantly. In addition to sweep detection, the indicator tracks mitigation events. A mitigation occurs when price breaks a stored pivot level with the candle body rather than merely sweeping it with the wick. When enabled, mitigated levels are recolored and marked with a small cross placed in the middle of the line, helping users differentiate between levels that produced a rejection and levels that were cleanly broken. There is also an option to hide mitigation markings entirely for traders who want the chart to focus only on sweep signals. Historical levels can be preserved or removed after resolution depending on user preference. This indicator is intended as a visual price action tool, not a complete trading system. It does not generate entries, stop losses, take profits, or strategy performance statistics. Instead, it is designed to support discretionary analysis by helping traders locate areas where liquidity may have been taken and where rejection behavior may be developing. It can be used on its own or combined with higher timeframe structure, supply and demand zones, session context, or confirmation from other price action concepts. Main features Detects bullish and bearish liquidity sweeps from confirmed pivot levels Uses wick-only sweep logic to distinguish sweeps from body breaks Optional volume filter for stronger signal selection Draws active historical liquidity levels on the chart Highlights sweep zones visually with directional coloring Places sweep dots exactly at the wick high or wick low Marks mitigated levels with a centered cross when enabled Includes options to keep or remove historical levels after resolution Provides alert conditions for bullish and bearish sweeps How to use Watch for price to wick above a prior high or below a prior low without closing through it Use the sweep marker and highlighted zone to quickly confirm the rejection area Combine signals with market structure, session timing, or additional confirmation before making trade decisions Use the volume filter if you want fewer but more selective sweep signals Notes Pivot-based logic requires right-side confirmation, so signals appear only after the pivot is confirmed The script is meant for chart analysis and signal visualization only Best used as a supporting tool within a broader trading plan
Chỉ báo Pine Script®
của SimplySafeFx
Stop Loss Cascades (Breakouts) [Kioseff Trading]Hello friends and traders! 🔹Introduction This indicator " Stop-Loss Clustering (Breakouts) " attempts to model trader stop-loss placement logic and identify price areas where a large amount of stop losses might cluster. The idea is, if stop losses are indeed highly concentrated in a specific area, price extending through that area may produce high-velocity breakout conditions via forced order flow . I'll cover this topic more thoroughly throughout the description. For now, just know that stop loss location & size data is not publicly available . Any model of their concentration locations is highly assumptive. However, there's some reasonable academic research we can reference to make worthwhile estimates. Academic references supporting the concepts discussed are listed at the end of this description. To maintain readability, I won't cite individual statements inline. 🔹The Premise 🔸Liquidity, Behavior, and Stop Cascades Markets operate through a continuous limit order book , where two fundamental order types interact: Limit orders , which provide liquidity by resting in the book Market orders , which consume liquidity by exhausting those resting orders This mechanical interaction drives price movement - incoming order flow consuming available liquidity . This begs the question.. Does liquidity distribute evenly across the LOB? If it did : If liquidity were evenly distributed, price impact could be modeled as a relatively smooth function of incoming order flow. But it doesn’t : Liquidity is unevenly distributed. Academic research supports this claim and, regardless, this is an intuitive conclusion most traders arrive at. Liquidity forms localized concentrations and gaps. Liquidity concentrations are commonly referenced as: liquidity shelves , liquidity clusters , liquidity zones . Liquidity gaps are commonly referenced as: liquidity vacuums , thin book zones . As a result, identical order flow can produce very different price movements depending on the state of the order book. Let’s consider an example.. Assume price is trading at $99. The price levels $100, $101, $102 have resting sell limit order concentrations of 100. This is where you come in. You execute a market order buy for 300 size. Your order first exhausts all sell-side resting order concentrations at the $100 level. You still have 200 size that needs to be filled, and the ask price has moved from $100 to $101. Your order will now sequentially exhaust available liquidity at the $101 level, the ask price will increase to $102, and your final 100 size will exhaust the $102 level. To keep the example simple, we’ll say that your order moved price from $99 to $102, and now the ask price is $103. But, you still want to accumulate. The nearest sell-side levels in the LOB are $103, $104, $105. The $103 level has a sell limit order concentration of 500. $104 and $105 both have concentrations of 50. You execute your same market order buy for 300 size. This time, price doesn’t move.. At all.. Instead, you consumed 300 of the 500 size at $103 with your order, and the level remains a barrier. Your order was absorbed by available liquidity. This example demonstrates how price movement depends on available liquidity , not simply the size of incoming orders. In the first scenario, liquidity was thin and the order walked through multiple price levels, causing price to move quickly. In the second scenario, a large concentration of resting liquidity absorbed the same order, preventing price from advancing. 🔸Liquidity Does Not Distribute Evenly Alright, we understand that liquidity doesn’t distribute evenly. And we understand that high concentrations of liquidity can act as price barriers (liquidity shelves) while sparse liquidity can permit rapid price movement - we saw this in our example above. There’s an important question we should ask next before we move on.. If liquidity distributes unevenly, then where does it tend to cluster? And where does it tend to thin? Of course, knowing these tendencies provides multi-purpose advantages. If price approaches a liquidity vacuum - a local block of the order book with thin resting liquidity - rapid price movement can occur without requiring unusually strong aggressive order flow. If price approaches a liquidity shelf - a local block of the order book with thick resting liquidity - price can stall or contract even if the same level of aggressive order flow that previously moved price continues. With this in mind, order flow intensity alone does not determine price movement . The distribution of liquidity across surrounding price levels plays a similarly important role. So, is there any evidence of where liquidity tends to concentrate ? 🔸Empirical Observations Empirical research on limit order books shows that liquidity does not distribute smoothly across the LOB . Instead, depth tends to concentrate at specific price levels, producing irregular profiles with localized peaks in resting liquidity. These concentrations arise because order placement is not random . Traders frequently anchor decisions to widely observed reference prices such as: • prior highs • prior lows • round numbers • widely referenced price extremes Because many traders monitor the same price history, order placement decisions often reference similar price levels. This concept is simpler than it sounds. Let’s use market structure traders for example. Market structure traders frequently reference prior swing highs and swing lows when making decisions about entries, exits, and risk. A trader entering a long position may place their stop-loss below a recent swing low , reasoning that if price breaks that level, the trade idea is invalidated. A trader entering a short position may place their stop-loss above a recent swing high for the same reason. Timeframe price aggregation may differ; however, we’re all looking at roughly the same recent highs and lows when evaluating a chart (structure). When many traders collectively reference the same prices, orders may accumulate near those levels. This produces localized depth concentrations, which traders refer to as liquidity shelves . Liquidity shelves act as temporary barriers where the book contains disproportionately large resting liquidity compared to surrounding prices. 🔸Research documenting liquidity clustering includes : Bourghelle & Cellier (2007) , who find that limit orders cluster at prominent price levels (especially round numbers), creating localized depth concentrations that can act as price barriers. Kavajecz & Odders-White (2004) , who demonstrate that prices identified as support or resistance coincide with higher resting limit order depth These findings suggest that many commonly observed price levels may correspond to real concentrations of liquidity rather than being purely visual artifacts on a chart. Kavajecz & Odders-White (2004) is an important observation for support/resistance traders! Kavajecz & Odders-White (2004) show that levels traders commonly call support and resistance often align with areas where more limit orders are resting in the order book. This suggests a plausible mechanical pathway through which support and resistance levels can emerge! 🔸Liquidity Shelves and Price Interaction When liquidity clusters around a price level, the resulting liquidity shelf can influence how price behaves when it approaches that area. Price interaction with these shelves is state-dependent : If incoming order flow is absorbed, price may stall or reverse If resting liquidity is consumed, price may transition rapidly to the next liquidity zone Once a shelf is depleted, follow-through can accelerate due to thinner liquidity beyond the level Research on order book dynamics supports this mechanical view of price movement. For example: Jean-Philippe Bouchaud, J. Doyne Farmer, and Fabrizio Lillo (2009) demonstrate that price impact emerges from the interaction between order flow and finite liquidity From this perspective, price does not move simply because a level is crossed. Price moves because available liquidity at that level has been consumed. 🔸Latent Liquidity and Stop Clustering In addition to visible liquidity from limit orders, markets also contain latent liquidity . This is where ”Stop-Loss Clustering (Breakouts)” becomes important - we’re almost done! Latent liquidity consists of conditional orders such as stop-losses that are not visible in the order book until triggered . Although these orders aren’t public information, empirical studies show that stop orders tend to cluster near widely referenced price levels . Research by Carol Osler (2001, 2002) using institutional FX order data finds that stop-loss orders frequently accumulate just beyond salient price levels such as prior highs and lows. When these stops trigger, they convert into aggressive market orders and can generate bursts of directional order flow that may accelerate price movement. 🔸Stop-Loss Cascades Stop losses add another layer of latent order flow that isn’t visible in the order book until it triggers. If enough of them sit around the same price area.. Think “hidden pressure” waiting to activate. Nothing happens while price trades nearby, but once that level is traded at, those stops convert into market orders and immediately begin consuming available liquidity. This matters because stop placement is unlikely to be random in most instances. Traders frequently anchor stops to widely observed prices such as prior highs, prior lows, or other prominent structure points, or use volatility methods such as ATR, etc. So when price approaches one of these areas, two things can happen. If the resting liquidity there is large enough, the incoming orders can be absorbed and price may stall or reject. But if that liquidity gets consumed, the stops sitting just beyond the level begin triggering. Those triggered stops add additional market orders, which consume more liquidity and can push price further into the next layer of stops. This creates a cascading effect: price reaches a stop cluster stops trigger and convert into market orders liquidity gets consumed faster price moves further, triggering more stops When this chain reaction starts, price can transition very quickly from a slow battle near the level to rapid expansion through it. This is one of the mechanical reasons why some reference-point breaks barely move, while others accelerate rapidly. 🔹How It Works Now that we understand the why - let’s discuss how the indicator works. 🔸Absorbtion Extremes The image above shows the absorption extremes model. In this model, the indicator treats recent & relevant swing points as plausible stop clustering candidates. You can find similar swing point identification mechanics in other indicators. However, this model assigns subsequent volume to the swing level after its formation. There are limitations and assumptions - let’s go over them. The images above explain how the indicator determines the intensity of a possible stop-cluster around a swing level. There are limitations and assumptions 1: The indicator assigns all “directional volume” to a swing level after it’s formed and while it remains the closest active swing point to the current price. “Buy volume” is assigned to the closest active swing low. “Sell volume” is assigned to the closest active swing high. I say “buy volume” and “sell volume” because there’s assumptions on what constitutes the relevant classification. The indicators follow the traditional two-region tick model for classifying buy volume and sell volume. Higher close = “buy volume” proxy Lower close = “sell volume” proxy Depending on the granularity you select (the indicator is capable of using tick data), this model can be more/less accurate. However, even with tick-level data and bid/ask quotes, trade direction must still be inferred using classification rules. Because some trades occur inside the spread or involve hidden liquidity, perfect classification is not possible without exchange aggressor flags. For assumptions.. The model assigns ALL classified volume to the swing level. In reality, traders use a wide range of risk management methods, and not every position will place a stop loss directly at the most recent swing point. ATR-based stops, percentage-based stops, and other volatility-based methods are also common. Because the true distribution of stop placement is unobservable, the model assumes that positions entered are structurally invalidated at the closest swing level based on their classified direction. As a result, the values displayed by the indicator should be interpreted as relative proxies for potential stop concentration, rather than precise estimates of actual stop-loss size. The displayed magnitudes are intentionally exaggerated and comparative, designed to highlight where stop pressure may accumulate relative to other levels. The images above show how to interpret the indicator when using this model. The image above shows the triggered stop-cluster graph. Each point corresponds to a triggered stop-cluster - assuming it exists. The greater the size attached to that cluster, the further distant the data point is placed. Far away from zero line = large size. Close to zero line = low size. Radiating/glowing points indicate a potentially large cluster trigger. 🔸 Volatility-At-Entry Model (Time Scaled) The Volatility-At-Entry model uses ATR scaled by various timeframes to predict plausible stop loss placements. For this model, the indicator uses the same tick classification model to assign volume directionally. Volume is then dispersed across six common timeframes (1m, 5m, 15m, 30m, 1h, 4h) and 3 common ATR multiples for risk management (1ATR, 1.5ATR, 2ATR). This model assumes traders are entering positions across various timeframes and are scaling risk congruent with those timeframes. For instance, A trader using the 1-minute chart for opportunity is more likely to use a stop loss closer to entry than a trader using the 4-hour chart for opportunity. If this assumption is reasonable to you - great, we can move forward! The image above visualizes the model. Purple-shaded regions indicate a price area with less opportunity for stop loss clustering. Either transaction intensity around eligible price areas was low, or position accumulation wasn’t given sufficient time. Pink-shaded regions indicate a price area with greater opportunity for stop loss clustering. Volume was significant around these regions or price has traded within proximity for extended periods. This model naturally shows more future opportunity than historical outcomes. You can select to show historical outcomes in the settings, this image shows examples of such outcomes. The image above shows the triggered stop loss graph in effect for this model. Stop clustered are distributed across more price areas with this model - from low intensity to high intensity. Therefore, a cluster is almost always “triggering” to some degree. A classification model for what’s typical and what’s unusual is used for the graph in this case. Radiating points always indicate large stop clusters triggered. Anything within the green/pink line indicates usual size. Typical Move The image above explains the nearest cluster information table. The size and location of the nearest buy-stop cluster and sell-stop cluster are recorded. Additionally, the indicator identifies whether clusters of similar size were triggered in the past, and how price behaved following those events. Since all models here are highly assumptive, and similar sized clusters might only have one or two relative neighbors, treat these measurements as a description of history rather than a prediction. The model takes the logarithm of the current stop-volume (buy or sell) to normalize its scale and compare it with a historical dataset of previously observed stop-volume sizes that have also been log-scaled. It then identifies historical observations whose sizes are most similar to the current value, either by selecting all observations within a tolerance range around that value (where the range is based on the typical spacing between historical observations), or by selecting the single closest match. Finally, the model retrieves the historical price moves associated with those matched observations, producing a sample of “typical moves” that occurred when stop-volume magnitude was similar to the current situation. Ratio Meter The stop-cluster ratio meter shows the current sum of active and triggered all buy-side clusters and sell-side clusters. This meter is useful for quick scanning across assets to see if active or recently triggered stop clusters are lopsided. Additional Features The single most important setting outside model selection is the lower timeframe used to retrieve volume from. This setting is set to 1-minute data by default because it works with paid and free plans. If you want better granularity, I strongly suggest changing this setting to either 1-second or 1-tick. This will sacrifice the number of identifiable cluster locations, because better granularity data has less programmatically retrievable values. 🔹Closing Remarks Stop-loss clustering is an appealing concept because it offers a plausible explanation for why some breakouts accelerate so quickly while others stall. When a large number of conditional orders sit near the same price, a breakout through that area can trigger a cascade of market orders that rapidly consume liquidity and push price toward the next available zone. However, it’s important to remember that the models used in this indicator are approximations, not direct measurements. True stop-loss locations and sizes are not publicly observable, and many traders use different risk management techniques that cannot be perfectly inferred from chart data alone. The goal of this indicator is therefore not to identify exact stop locations, but to highlight price areas where stop pressure may plausibly accumulate relative to surrounding levels. Like any model based on behavioral assumptions and historical observations, results should be interpreted probabilistically. Large clusters do not guarantee breakouts, and small clusters do not guarantee quiet price behavior. Instead, the indicator is best used as a tool for context and situational awareness. References General Microstructure and Price Formation Madhavan, A. (2000). Market microstructure: A survey. Journal of Financial Markets, 3(3), 205–258. O'Hara, M. (1995). Market Microstructure Theory. Blackwell. Biais, B., Glosten, L., & Spatt, C. (2005). Market microstructure: A survey of microfoundations, empirical results, and policy implications. Journal of Financial Markets, 8(2), 217–264. Limit Order Books and Liquidity as Resting Orders Gould, M. D., Porter, M. A., Williams, S., McDonald, M., Fenn, D. J., & Howison, S. D. (2013). Limit order books. Quantitative Finance, 13(11), 1709–1742. Rosu, I. (2009). A dynamic model of the limit order book. Review of Financial Studies, 22(11), 4601–4641. Biais, B., Hillion, P., & Spatt, C. (1995). An empirical analysis of the limit order book and the order flow in the Paris Bourse. Journal of Finance, 50(5), 1655–1689. Liquidity Clustering and Depth Concentration Kavajecz, K. A., & Odders-White, E. R. (2004). Technical analysis and liquidity provision. Review of Financial Studies, 17(4), 1043–1071. Bourghelle, D., & Cellier, A. (2007). Limit order clustering and price barriers on financial markets. Working paper / SSRN. Order Flow and Price Impact Bouchaud, J.-P., Farmer, J. D., & Lillo, F. (2009). How markets slowly digest changes in supply and demand. In Handbook of Financial Markets: Dynamics and Evolution. Stop Orders and Price Cascades Osler, C. L. (2003). Currency orders and exchange-rate dynamics: Explaining the success of technical analysis. Journal of Finance, 58(5), 1791–1819. Osler, C. L. (2005). Stop-loss orders and price cascades in currency markets. Journal of International Money and Finance, 24(2), 219–241. Liquidity Provision and Execution Ho, T., & Stoll, H. (1981). Optimal dealer pricing under transactions and return uncertainty. Journal of Financial Economics, 9(1), 47–73. Almgren, R., & Chriss, N. (2000). Optimal execution of portfolio transactions. Journal of Risk, 3(2), 5–39. Menkveld, A. J. (2013). High frequency trading and the new market makers. Journal of Financial Markets, 16(4), 712–740. Behavioral Anchoring and Attention Kahneman, D., & Tversky, A. (1974). Judgment under uncertainty: Heuristics and biases. Science, 185(4157), 1124–1131. Barber, B. M., & Odean, T. (2008). All that glitters: The effect of attention and news on the buying behavior of individual and institutional investors. Review of Financial Studies, 21(2), 785–818. George, T. J., & Hwang, C. Y. (2004). The 52-week high and momentum investing. Journal of Finance, 59(5), 2145–2176. Mizrach, B., & Weerts, S. (2007). Highs and lows: A behavioral and technical analysis. SSRN working paper.
Chỉ báo Pine Script®
của KioseffTrading
19
Liquidity Raids [UAlgo]Liquidity Raids is a market structure overlay designed to highlight classic liquidity sweep events around recent swing levels. The script continuously maps swing highs and swing lows using pivot detection, projects those levels forward as active lines, and then monitors price behavior around each level to detect a raid. A raid is defined here as a sweep through a prior level followed by rejection back across it within the same bar. This behavior often represents stop runs, liquidity grabs, or failed break attempts. The script separates these events into: BSL sweeps, where buy side liquidity above prior highs is taken and price closes back below the level SSL sweeps, where sell side liquidity below prior lows is taken and price closes back above the level To improve signal quality, an optional relative volume confirmation filter can be enabled. When active, a sweep is only valid if the sweep bar’s volume exceeds a multiple of the recent average, and the script prints the relative volume percentage on the chart for additional context. The indicator also includes practical object management to keep charts clean by limiting the number of active levels and removing invalidated lines automatically. 🔹 Features 1) Automatic Swing Level Mapping via Pivot Highs and Lows The script uses pivot detection to identify meaningful swing highs and swing lows. Each confirmed pivot becomes a projected liquidity level that extends forward in time. These levels represent areas where stops and breakout orders tend to cluster. Pivot Length controls how sensitive the swing detection is. Higher values produce fewer but more significant levels. Lower values react faster and produce more frequent levels. 2) Active Level Projection and Management Each pivot level is drawn as a horizontal line and stored in an internal array. On every new bar, the script updates each active line so it extends to the current bar. A Maximum Active Levels setting prevents chart clutter and controls the number of stored objects. When the limit is exceeded, the oldest level is removed. 3) Clear Sweep Definitions for BSL and SSL Each level is monitored for two outcomes: Sweep and reject Broken and accepted For resistance levels, a BSL sweep requires the bar high to trade above the level while the close finishes at or below the level. A break requires the close to finish above the level. For support levels, an SSL sweep requires the bar low to trade below the level while the close finishes at or above the level. A break requires the close to finish below the level. When a sweep is detected, the level is removed after the event is confirmed. When a level is broken, it is removed to prevent outdated levels from remaining on the chart. 4) Optional Volume Confirmation Using Relative Volume When enabled, sweeps are filtered using Relative Volume (RVOL). The script compares the current bar’s volume to the 20 bar average volume and requires it to exceed a user defined multiplier. This is useful for separating meaningful stop runs from thin market spikes. The script also prints the RVOL percentage near the swept level for quick evaluation. 5) Sweep Highlighting and Labels On a valid sweep, the script highlights the swept level with a bright confirmation line and optionally prints labels: ▼ BSL for buy side liquidity sweeps ▲ SSL for sell side liquidity sweeps Volume information is also displayed as a percentage at the midpoint of the swept segment, positioned above for BSL and below for SSL to reduce overlap. 6) Configurable Visual Styling You can control resistance and support colors independently, choose line style (solid, dotted, dashed), and toggle labels. This makes the overlay adaptable to both clean minimalist charts and more information dense layouts. 7) Alerts for Automation and Monitoring Alert conditions are included for both sweep types. In addition, the script triggers immediate alerts with the close price when a sweep is detected on bar close. This supports both discretionary monitoring and automated notification workflows. 🔹 Calculations 1) Pivot Based Level Detection Swing highs and lows are detected using symmetric pivot logic: float ph = ta.pivothigh(high, pivotPeriodInput, pivotPeriodInput) float pl = ta.pivotlow(low, pivotPeriodInput, pivotPeriodInput) Interpretation: A pivot high is confirmed only after pivotPeriodInput bars to the right A pivot low is confirmed only after pivotPeriodInput bars to the right Confirmed pivot values become new resistance or support liquidity levels 2) Level Storage and Line Creation When a pivot is confirmed, the script creates a line starting at the pivot bar and stores it as a LiquidityLevel object: line newL = line.new(bar_index , ph, bar_index, ph, color = resistanceColorInput, style = getLineStyle(lineStyleInput)) resistanceLevels.push(LiquidityLevel.new(ph, bar_index , newL)) The same logic applies to pivot lows for support levels. To prevent excessive object growth, levels are capped: if resistanceLevels.size() > maxLinesInput (resistanceLevels.shift()).delete() 3) Relative Volume and Volume Filter The script computes average volume over the last 20 bars and converts current volume into a percentage: float volAvg = ta.sma(volume, 20) float volRelative = (volume / volAvg) * 100 The volume filter is satisfied when either the filter is disabled or the current volume exceeds the average multiplied by the chosen multiplier: bool isVolStrong = not useVolFilterInput or (volume > volAvg * volMultiplierInput) 4) Sweep and Break Conditions Each active resistance level is checked for a sweep or a break: bool priceSwept = high > lvl.price and close <= lvl.price bool broken = close > lvl.price Each active support level is checked similarly: bool priceSwept = low < lvl.price and close >= lvl.price bool broken = close < lvl.price Interpretation: A sweep requires a wick through the level and a close back across it A break requires acceptance beyond the level on close 5) Sweep Confirmation Handling and Cleanup When a sweep occurs with strong volume, the script sets a flag for alerts, draws highlight objects, prints labels, and removes the level from active tracking: Resistance sweep flow: if priceSwept and isVolStrong buySweepOccurred := true line.new(lvl.startBar, lvl.price, bar_index, lvl.price, color = C_SWEEP_BUY) resistanceLevels.remove(i).delete() Support sweep flow: if priceSwept and isVolStrong sellSweepOccurred := true line.new(lvl.startBar, lvl.price, bar_index, lvl.price, color = C_SWEEP_SELL) supportLevels.remove(i).delete() If a level is broken, it is removed as invalid: else if broken resistanceLevels.remove(i).delete() 6) Volume Annotation Placement On a sweep, the script computes the midpoint of the level segment in bar index space and prints RVOL percent: int midX = math.round((lvl.startBar + bar_index) / 2) label.new(midX, lvl.price, str.tostring(volRelative, "#") + "% VOL") Placement is above for BSL sweeps and below for SSL sweeps to align with the direction of the liquidity being taken. 7) Alerts Alert conditions and direct alerts are provided: alertcondition(buySweepOccurred, "Buy Liquidity Sweep", "BSL Swept!") alertcondition(sellSweepOccurred, "Sell Liquidity Sweep", "SSL Swept!") The script also triggers runtime alerts including the close price once per bar close when a sweep occurs.
Chỉ báo Pine Script®
của UAlgo
Sweep Volume Index [LuxAlgo]The Sweep Volume Index indicator is a specialized volume analysis tool designed to measure the volume traded specifically during "sweeps" of liquidity levels like swing highs and swing lows. By utilizing intrabar data, the script provides a granular view of market participant activity at key technical levels where liquidity is often concentrated. Note: This indicator requires access to lower timeframe data. Ensure your chart has sufficient historical data for the intrabar timeframe selected. 🔶 USAGE The indicator helps traders identify if a breakout beyond a previous structural high or low is a genuine trend continuation or a liquidity grab (stop-run). 🔹 Identifying Reversals High sweep volume at a key level followed by a price rejection often signals a strong potential for a trend reversal. When the oscillator shows a large spike as price pierces a pivot level but fails to close beyond it, it suggests that "smart money" has absorbed the liquidity. 🔹 Trend Exhaustion Multiple sweeps appearing in succession with increasing volume but decreasing price extension can indicate trend exhaustion. The decaying envelopes in the oscillator pane help put these volume spikes into context relative to recent historical activity. 🔹 Liquidity Gaps Low sweep volume might suggest that price has cleared a level with very little resistance or participation, which can potentially lead to a fast continuation as there is no "absorption" taking place. 🔶 DETAILS A "sweep" occurs when the market price extends beyond a previous structural high or low but fails to sustain that breakout, often resulting in a wick or a "fakeout." The script operates through several stages: Pivot Identification: The indicator identifies structural pivot highs and lows based on the Pivot Length input. Threshold Zone: A dynamic ATR-based threshold is applied to these levels. This zone defines the area where price can "pierce" without the candle body closing outside, qualifying the move as a sweep rather than a breakout. Intrabar Analysis: Using request.security_lower_tf , the script analyzes the volume on a lower timeframe. It only counts volume traded beyond the pivot level during the sweep. Sweep Volume Calculation: Bullish Sweep Volume measures volume traded above a Pivot High while the candle body remains below the threshold. Bearish Sweep Volume measures volume traded below a Pivot Low while the candle body remains above the threshold. 🔶 SETTINGS 🔹 Detection Pivot Length: Determines the lookback/lookahead period for identifying structural swing highs and lows. 🔹 Calculation Intrabar Timeframe: The lower timeframe used to calculate granular volume data. Lower timeframes provide higher precision. 🔹 Threshold Use ATR Threshold: Enables a buffer zone around pivots. If the candle body closes within this zone (but beyond the pivot), it is still considered a sweep. ATR Length: The period used for the Average True Range calculation. ATR Multiplier: Multiplier applied to the ATR to define the width of the sweep zone. 🔹 Envelopes Envelope Alpha %: Controls the rate at which the oscillator envelopes decay. Higher values make the envelopes stay elevated for longer. Upper/Lower Envelope Color: Sets the colors for the bullish and bearish oscillator envelopes. 🔹 Visuals Show Swing Levels: Toggles the visibility of the horizontal pivot lines and ATR zones on the main chart. Show Oscillator Fills: Toggles the gradient fills within the oscillator pane. Bullish/Bearish Sweep Color: Sets the colors for the volume columns in the oscillator. Pivot High/Low Colors & Zones: Customizes the colors for the price levels and the shaded threshold areas on the chart.
Chỉ báo Pine Script®
của LuxAlgo
1
Liquidity Pools + Sweep Signals [Metrify]If breakouts feel like a scam, it’s because they often function like one. Most charts are taught like they’re a clean story of supply and demand. But real price action is messier: it’s a sequence of tests, traps, and collections. The market doesn’t need to “respect” your line, it needs to find liquidity. And liquidity usually sits in predictable places: swing highs, swing lows, prior reaction points, the levels everyone can see. This Liquidity Sweep Canvas is a market-structure overlay that tracks liquidity pools built from swing highs/lows, then monitors how price interacts with those pools over time (touches → sweeps → breaks/expiry). The goal is not to “predict” — it’s to map where liquidity is parked, highlight when it’s raided with rejection, and keep a clean, visual “canvas” of relevant pools near current market. It builds two sides: SELL liquidity pools (from pivot highs, shown in red) BUY liquidity pools (from pivot lows, shown in teal) Each pool is zoned around the pooled level, merges nearby levels (optional aggressiveness), tracks hits, and can transition through states: Active (building / being respected) Swept (liquidity taken + rejection confirmed) Ended (broken through or expired) Sweep logic in plain terms A sweep is detected when price pierces beyond a pool boundary and then closes back through the pool’s midline in the opposite direction (rejection). Bear sweep (SELL liquidity): price wicks above a SELL pool, then closes back below the pool mid. Bull sweep (BUY liquidity): price wicks below a BUY pool, then closes back above the pool mid. Optionally, you can require a second-step confirmation: Displacement confirm waits for follow-through (within a small window) where price breaks beyond the sweep candle’s reference (with a minimum body size in ATR). This filters some noise, at the cost of being delayed. 🔥 Scoring system (how “quality” is decided) Sweeps are common. Clean sweeps are not. We uses a weighted scoring model (0–100) so you can filter out weak sweeps and keep the ones that show stronger intent. A sweep starts when price penetrates beyond the pool boundary (takes liquidity) and reclaims back inside the zone (closes through the pool mid). From there, a score is built from two layers: ✅ Layer 1 —> Sweep candle “core bundle” (base part) This is computed immediately on the sweep candle (or stored if you require displacement). The base bundle blends: Penetration: how deep the wick pushed beyond the pool in ATR terms (not “deeper is always better”, it’s shaped to reward a realistic sweet spot). Reclaim strength: how much of the candle reclaimed back (close relative to the range). Wick ratio: rejection wick size vs body (controlled by 'Wick Ratio Scale'). Body bias: bullish body for bull sweeps / bearish body for bear sweeps gets rewarded. EMA context: measures whether the sweep is happening with a favorable distance relative to EMA 200. Line age/maturity: longer pools can score differently via a length score, then get penalized by a separate age penalty. 🧠 Layer 2 —> Context add-ons After the base bundle, the final score can include: MSS context: a simple structural reference (recent swing extreme lookback) to rate whether the sweep is happening with useful positioning. Effort score: combines range expansion (ATR) with volume vs volume MA to reward sweeps that show actual participation. Displacement score (optional): if enabled, the sweep is only confirmed after follow-through within a small window. How to use it 1. Build a two-stage decision: location bias, then trigger selection Use pools to decide directional bias before you even consider entries. If price is pressing into SELL pools repeatedly and the dashboard shows dense sell-side activity, your bias shifts toward expecting a sell-side raid (sweep up then rejection) rather than a clean breakout. If price is pressing into BUY pools, same logic for downside raid and bounce. Then decide your trigger style manually: If you trade fast mean reversion, you can use immediate sweeps as the “first alarm” and enter on the reclaim + tight invalidation. If you trade safer confirmation, require displacement confirm, and only act once price has proven it can leave the pool with force. Either way, the script helps you separate where it matters (pools) from where it doesn’t (middle of nowhere). 2. Use hit count to judge liquidity density and trap probability The LP xN hit count is a manual edge if you treat it correctly: more hits generally implies more eyes, more orders, more liquidity, and therefore more potential for a meaningful raid. When you see a pool with high hits near current price, don’t assume it’s “strong support/resistance.” Instead, assume it’s a liquidity magnet. If price repeatedly taps a high-hit pool without breaking cleanly, it often sets up a sweep (stop run + reverse). If price breaks and stays outside with follow-through, that’s not a sweep environment, it’s a continuation environment. So you use hit count to anticipate which levels are likely to be hunted, then use candle behavior + displacement to judge whether the hunt was successful and rejected. 3. Turn sweeps into ‘event markers’ for post-move structure mapping Instead of treating a sweep as “enter now,” treat it as: a structural event happened here. After a sweep prints, manually re-map microstructure: identify the last minor swing before the sweep, then track whether price breaks it (MSS/BOS style) and whether the first pullback respects that break. 4. Use the channel read as a regime filter (premium/discount logic) The nearest pool edges effectively form a liquidity channel. Use it like a regime filter: Inside SELL zone / premium: prioritize short-side narratives Inside BUY zone / discount: prioritize long-side narratives Middle channel: treat as uncertainty, tighten your standards (or step aside). 5. Use scoring as a ‘quality gate’, then you do the narrative check” If you enable scoring, stop thinking of it as “higher score = higher win.” Think of it as a gate that filters out low-effort pokes. Once a high-score sweep prints, manually audit it. 6. Use it as a ‘sweep journal’ to study your market’s behavior A very “pro” use is not trading it at all for a week. Turn on historical traces and sweep markers, and just observe: Which sessions produce the cleanest sweeps? Do high-score sweeps outperform low-score? Do confirmed sweeps reduce chop at the cost of late entries? Does your instrument sweep more on highs or lows? The dashboard counts help you quantify frequency. After you collect observations, you tune inputs (Swing Length, Merge Distance, Minimum Score, Volume thresholds) to match the instrument’s microstructure. This is how you turn a generic sweep concept into a market-specific playbook—and the script becomes your data-driven visual log, not a guessing machine. ⚙️ Tuning tips (fast) Too many pools / too noisy → increase Swing Length / Merge Distance. Sweeps trigger too often → enable Activate Scoring and raise Min Score. Wick quality not valued enough → reduce Wick Ratio Scale. Effort scoring feels too easy/hard → adjust Min Volume / MA and Volume MA Length. A higher score is not a guarantee of a better trade, it simply means the sweep event matched more of the model’s criteria (penetration, reclaim, rejection wick, effort, context components, and optional displacement). Markets are adaptive: what high quality looks like changes by instrument, timeframe, and session. Use scoring to reduce noise, then manually validate.
Chỉ báo Pine Script®
của Metrify
10
Protected Swings [LuxAlgo]The Protected Swings indicator identifies and confirms high-probability structural levels based on the interaction between liquidity sweeps, Fair Value Gaps (FVG), and Change in State of Delivery (CISD) logic. This tool aims to highlight "protected" highs and lows that are expected to remain intact during trend continuations or market reversals. 🔶 USAGE The Protected Swings tool is designed to provide clear invalidation levels for stop placement and to help traders avoid false reversals by waiting for candle-body confirmation through specific price series. 🔹 Trend Reversals A reversal setup occurs when the market sweeps a major liquidity level (such as a previous swing high or low) or taps into a high-timeframe FVG. A Protected Swing High (PSH) forms after a sweep of a high followed by a close below the opening price of the up-close candle series that created that high. This suggests a shift to a bearish regime. A Protected Swing Low (PSL) forms after a sweep of a low followed by a close above the opening price of the down-close candle series that created that low. This suggests a shift to a bullish regime. 🔹 Trend Continuation Once Protected Swings are established, subsequent "stepping stones" often form. In a bearish trend, new PSHs will form as price wicks into internal FVGs and then closes back below the candle series that created the retracement high. These levels serve as trailing stop-loss points or areas to look for refined lower-timeframe entries. 🔹 Entry Refinement Traders can use Protected Swings to refine Risk:Reward. When a higher-timeframe protected level is confirmed, users can drop to a lower timeframe and wait for a secondary protected swing to form. The "Confirmation Level" shown by the indicator represents the exact price point that must be breached to validate the "protected" status of that swing. 🔶 DETAILS The script follows a multi-step logic to confirm Protected Swings: 🔹 Liquidity Sweeps The indicator tracks structural pivots (Fractals) based on the "Sweep Sensitivity" setting. A sweep is detected only when the price wick exceeds a previous pivot high or low, but the candle body remains within the previous extreme. This "wick-only" break suggests liquidity is being grabbed (Stop Run) rather than a displacement break of structure occurring. 🔹 FVG Mitigations The script detects Fair Value Gaps (3-candle imbalances). If enabled, a swing point is considered a candidate for a Protected Swing if it trades into an active FVG, even if a liquidity sweep of a major pivot did not occur. 🔹 Change in State of Delivery (CISD) The core confirmation logic (CISD) requires the price to close through the "series." For a Bullish Protected Swing , the script identifies the series of consecutive down-close candles leading into the low. The opening price of the first candle in that down-series becomes the Confirmation Level. For a Bearish Protected Swing , it identifies the consecutive up-close candles. The opening price of the first candle in that up-series becomes the level. The labels (PSL/PSH) only appear once a candle body closes past this level, ensuring the "State of Delivery" has shifted. 🔶 SETTINGS 🔹 Logic Settings Sweep Sensitivity: Defines the number of bars required on both sides to confirm a structural pivot level to be used for detecting sweeps. Include FVG Mitigations: When enabled, swings that tap into imbalances can trigger protected swing labels. FVG Search Lookback: Determines how many bars back the script searches for active imbalances to use as context. 🔹 Visualization Show Labels: Toggles the PSL (Protected Swing Low) and PSH (Protected Swing High) labels. Show Confirmation Levels: Displays the horizontal lines representing the candle series opening price that triggered the confirmation. Show Fair Value Gaps: Visualizes active imbalances on the chart. Highlight Liquidity Sweeps: Highlights the specific portion of the wick that exceeded the previous structural pivot. Colors: Customization for bullish and bearish elements and transparency for zones.
Chỉ báo Pine Script®
của LuxAlgo
3
Liquidity OS [PyraTime]Trading the lower timeframes (1m-15m) often feels like navigating a minefield. Charts become cluttered with noise, making it nearly impossible to distinguish random price action from genuine institutional intent. Traders frequently suffer from "Analysis Paralysis," struggling to spot clean setups or reacting too slowly to calculate risk accurately in fast-moving markets. The Solution: A Clean Operating SystemPyraTime: Liquidity OS was engineered to solve this specific problem. It is not just a signal tool; it is a complete visual operating system designed to declutter your workspace and enforce discipline. By filtering price action through a strict confluence of Structure, Time, and Momentum, it highlights only high-probability liquidity sweeps while automating the complex mental math of risk management. How to Use This Indicator This tool is designed for Scalpers and Day Traders utilizing liquidity concepts (ICT/SMC). Wait for the Signal: The indicator automatically identifies valid "Unicorn" setups—a confluence of a Liquidity Sweep followed by a displacement (Breaker) and a Fair Value Gap. Verify the Context: Look for the "Elite Glass" Capsule. Cyan Glass: Bullish Setup (Long Opportunity). Pink Glass: Bearish Setup (Short Opportunity). Note: The capsule physically covers messy wicks, forcing your eye to focus solely on the clear path to profit or invalidation. Consult the Dashboard: Glance at the "Monitor" panel (bottom right). It instantly displays the Position Size required to trade the setup based on your pre-defined account risk (e.g., 1%). Execute & Focus: Use the visual TP (Take Profit) and SL (Stop Loss) lines provided by the capsule to set your orders. The system automatically dims old trades ("Smart Spotlight") so only the current opportunity competes for your attention. Key Features 🦁 "Elite Glass" Visual Engine: A proprietary rendering system that displays trade setups as high-transparency, polished capsules. This creates a "Focus-First" environment, reducing chart noise and visual fatigue. 🧠 Smart Spotlight: Automatically manages visual history. The two most recent active zones remain bright, while older setups automatically dim to reduce clutter. Mitigated zones can be set to turn into "Ghosts" or disappear entirely. 🛡️ Risk OS Dashboard: A real-time, persistent monitor that calculates: Dynamic Position Sizing: Tells you exactly how many units/contracts to trade. Session Metrics: Tracks Win Rate, Total R, and Expectancy live. Safety Warnings: Highlights "High Risk" inputs in red if you exceed safety thresholds. ⚡ Logic Filters: Killzones: Restrict signals to specific sessions (e.g., London/NY) with a custom timezone selector. Trend Flow: Filters signals to align with the 4H Trend (EMA 50). Deep Value: Ensures buys occur in Discount and sells in Premium zones. Specifications & Settings Risk OS: Customizable Target R:R, Stop Loss Padding (ATR Multiplier), and Risk Per Trade %. Liquidity Filters: "1m Scalp Mode" (increased sensitivity), Killzone Time/Timezone selector, and Force Reset button. Visual Interface: Fully customizable colors. Toggles for "Show Midlines" (50% of FVG) and "Show Structure Breaks" (BOS lines) to further reduce noise. Performance: Built on Pine Script v6 with null-safe execution and optimized garbage collection for zero-lag performance on all timeframes. Disclaimer: Risk metrics, position sizing, and performance data displayed by this indicator are for informational and educational purposes only. This tool does not execute trades, manage funds, or guarantee future results. Always trade with a regulated broker and verify calculations independently.
Chỉ báo Pine Script®
của PyraTime
13
eBacktesting - Learning: Liquidity GrabseBacktesting - Learning: Liquidity Grabs highlights moments when price pushes just beyond a recent swing high or swing low (where many stops tend to sit) and then quickly returns back inside the level. This behavior is often called a stop run, sweep, or liquidity grab. Traders study these events because they can reveal: - Where liquidity is “resting” (obvious highs/lows) - A quick sweep and rejection (often a wick) - When a breakout attempt is actually a trap - A full candle close through the level, followed by an immediate reversal back inside (classic breakout trap) - Potential areas where price may reverse or accelerate after stops are taken Use it as a training tool to build pattern recognition and improve your patience around key levels, especially during active sessions where sweeps happen frequently. These indicators are built to pair perfectly with the eBacktesting extension, where traders can practice these concepts step-by-step. Backtesting concepts visually like this is one of the fastest ways to learn, build confidence, and improve trading performance. Educational use only. Not financial advice.
Chỉ báo Pine Script®
của BacktestingMaestro
Liquidity Sweeps [Kodexius]Liquidity Sweeps is a price action indicator built to visualize and react to common “stop run” behavior around recent swing highs and swing lows. It continuously detects pivot-based liquidity levels (recent resistance and support), extends them forward in time, and then classifies the interaction when price probes beyond a level but fails to hold through it. The script focuses on two outcomes: Buy-Side Liquidity Sweep (BSL): price takes liquidity above a recent swing high (high breaks above the level) but closes back at or below the level. Sell-Side Liquidity Sweep (SSL): price takes liquidity below a recent swing low (low breaks below the level) but closes back at or above the level. To support real trading workflows, it keeps charts readable by limiting active levels, offers clean styling options, and optionally filters sweep signals using relative volume (RVOL) so you can require participation before a sweep is considered valid. 🔹 Features 🔸 Pivot-Based Liquidity Level Detection (Swing Highs and Swing Lows) The indicator uses a user-defined Pivot Length to identify confirmed swing points: Pivot Highs become resistance liquidity levels (buy-side liquidity above highs). Pivot Lows become support liquidity levels (sell-side liquidity below lows). Each detected level is drawn as a horizontal line and automatically extended to the current bar until it is swept or broken. 🔸 Automatic Level Management (De-Cluttering) To prevent chart overload, the script stores levels in internal arrays and enforces Maximum Active Levels: When new levels are added and the limit is exceeded, the oldest level is removed. This keeps only the most relevant, recent liquidity zones visible. 🔸 Clear Sweep Classification (BSL and SSL) The sweep logic is intentionally strict and practical: - BSL Sweep triggers when the bar’s high is above resistance but the close is back below or at resistance. - SSL Sweep triggers when the bar’s low is below support but the close is back above or at support. This models the “probe and reject” behavior typical of liquidity grabs. 🔸 Optional Volume Confirmation Using RVOL When Enable Volume Filter is turned on, sweeps are only valid if the current bar’s volume is strong relative to the last 20 bars: The script computes a 20-period volume average. You can require volume to exceed the average by a chosen Volume Multiplier (example: 1.5 means 150% of the average). If the filter is disabled, sweeps are evaluated purely on price conditions. 🔸 Sweep Labels and Level Highlighting On a valid sweep: A label is printed on the sweep bar: - ▼ BSL for buy-side liquidity sweeps (yellow) - ▲ SSL for sell-side liquidity sweeps (blue) The swept level is highlighted by drawing an additional colored line over the swept range. The script also prints the bar’s RVOL percentage near the midpoint of the swept line segment: - BSL volume text is placed above the line midpoint - SSL volume text is placed below the line midpoint This makes it easy to see whether a sweep was low-effort or supported by strong participation. 🔸 Styling Controls You can fully tailor the visual output: Resistance and support line colors Line style selection: Solid, Dotted, Dashed Toggle sweep labels on or off 🔸 Alerts The indicator exposes alert conditions for both sweep types and also fires explicit alert messages once per bar close when a sweep is confirmed: - Buy Liquidity Sweep (BSL) - Sell Liquidity Sweep (SSL) 🔹 Calculations 1) Pivot High / Pivot Low Detection float ph = ta.pivothigh(high, pivotPeriodInput, pivotPeriodInput) float pl = ta.pivotlow(low, pivotPeriodInput, pivotPeriodInput) Interpretation: A pivot is only confirmed after pivotPeriodInput bars have passed. Once confirmed, the level is anchored at the pivot bar and then extended forward. 2) Creating and Storing Liquidity Levels New Resistance (Pivot High): if not na(ph) line newL = line.new(bar_index , ph, bar_index, ph, color = resistanceColorInput, width = 1, style = getLineStyle(lineStyleInput)) resistanceLevels.push(LiquidityLevel.new(ph, bar_index , newL)) if resistanceLevels.size() > maxLinesInput (resistanceLevels.shift()).delete() New Support (Pivot Low): if not na(pl) line newL = line.new(bar_index , pl, bar_index, pl, color = supportColorInput, width = 1, style = getLineStyle(lineStyleInput)) supportLevels.push(LiquidityLevel.new(pl, bar_index , newL)) if supportLevels.size() > maxLinesInput (supportLevels.shift()).delete() This enforces the “Maximum Active Levels” limit by deleting the oldest stored level when the cap is exceeded. 3) Relative Volume (RVOL) and Volume Filter float volAvg = ta.sma(volume, 20) float volRelative = (volume / volAvg) * 100 bool isVolStrong = not useVolFilterInput or (volume > volAvg * volMultiplierInput) volRelative expresses the sweep bar’s volume as a percentage of the last 20-bar average. If the filter is enabled, a sweep is valid only when isVolStrong is true. 4) Sweep Conditions (Core Logic) Buy-Side Liquidity Sweep (Resistance Sweep) A resistance level is considered swept when price trades above it but closes back at or below it. bool priceSwept = high > lvl.price and close <= lvl.price bool broken = close > lvl.price priceSwept captures the “probe and reject” behavior. broken invalidates the level if price closes above it. The confirmation and cleanup flow: if priceSwept and isVolStrong buySweepOccurred := true if showLabelsInput label.new(bar_index, high, "▼ BSL", style = label.style_label_down, color = #00000000, textcolor = C_SWEEP_BUY, size = size.small) line.new(lvl.startBar, lvl.price, bar_index, lvl.price, color = C_SWEEP_BUY, width = 1) int midX = math.round((lvl.startBar + bar_index) / 2) label.new(midX, lvl.price, str.tostring(volRelative, "#") + "% VOL", color = #00000000, textcolor = color.new(C_SWEEP_BUY, 20), style = label.style_label_down, size = size.tiny) resistanceLevels.remove(i).delete() else if broken resistanceLevels.remove(i).delete() Sell-Side Liquidity Sweep (Support Sweep) A support level is considered swept when price trades below it but closes back at or above it. bool priceSwept = low < lvl.price and close >= lvl.price bool broken = close < lvl.price The confirmation and cleanup flow: if priceSwept and isVolStrong sellSweepOccurred := true if showLabelsInput label.new(bar_index, low, "▲ SSL", style = label.style_label_up, color = #00000000, textcolor = C_SWEEP_SELL, size = size.small) line.new(lvl.startBar, lvl.price, bar_index, lvl.price, color = C_SWEEP_SELL, width = 1) int midX = math.round((lvl.startBar + bar_index) / 2) label.new(midX, lvl.price, str.tostring(volRelative, "#") + "% VOL", color = #00000000, textcolor = color.new(C_SWEEP_SELL, 20), style = label.style_label_up, size = size.tiny) supportLevels.remove(i).delete() else if broken supportLevels.remove(i).delete() 5) Level Extension to Current Bar method update(LiquidityLevel this) => line.set_x2(this.lineObj, bar_index) This keeps each active liquidity level extended to the current candle until it is swept or decisively broken. 6) Alerts alertcondition(buySweepOccurred, "Buy Liquidity Sweep", "BSL Swept!") alertcondition(sellSweepOccurred, "Sell Liquidity Sweep", "SSL Swept!") if buySweepOccurred alert("Kodexius BSL Sweep: " + str.tostring(close), alert.freq_once_per_bar_close) if sellSweepOccurred alert("Kodexius SSL Sweep: " + str.tostring(close), alert.freq_once_per_bar_close)
Chỉ báo Pine Script®
của UnknownUnicorn113699460
1
Filter Bar1. Indicator Name Filter Bar 2. One-line Introduction A trend-aware bar coloring system that visualizes market direction and strength through adaptive transparency based on regression scoring. 3. General Overview Filter Bar+ is a minimalist but powerful trend visualization tool that colors chart bars according to market direction and momentum strength. It analyzes the linear regression trend alignment over a specified lookback period and uses a pairwise comparison algorithm to determine whether the market is in a bullish, bearish, or neutral state. The result is a "trend score" that gets normalized to reflect trend intensity (0~1). Bar colors are then dynamically updated using the specified bullish or bearish base colors, where higher intensity results in more opaque (darker) bars, and weaker trends lead to lighter, faded tones. If no strong trend is detected, bars are shown in gray, signaling indecision or neutrality. The strength of this indicator lies in its simplicity—it doesn’t draw lines, waves, or shapes, but overlays insight directly onto the chart through smart color cues. It’s particularly effective as a background filter for price action traders, scalpers, and anyone who prefers clean charts but still wants embedded directional context. 4. Key Advantages 🎨 Adaptive Bar Coloring Bar color opacity increases with trend strength, offering instant visual confirmation without clutter. 📊 Quantified Trend Direction Uses a regression-based scoring system to reliably detect uptrends, downtrends, or sideways markets. ⚖️ Customizable Sensitivity Parameters like lookback period and tolerance percentage give users full control over signal responsiveness. 🧼 Clean Chart Presentation No lines, shapes, or overlays—just color-coded bars that blend into your existing chart setup. 🚀 Lightweight & Fast Minimal computational load ensures it works smoothly even on lower-end devices or multiple chart setups. 🔒 Secure Internal Logic Algorithm is neatly encapsulated and optimized, with no critical logic exposed. 📘 Indicator User Guide 📌 Basic Concept Filter Bar+ evaluates trend direction and strength using a pairwise comparison of linear regression values. The result determines whether the market is bullish, bearish, or neutral, and adjusts bar colors accordingly. It visually amplifies the current market state without drawing any indicators on the chart. ⚙️ Settings Explained Lookback Period: Number of bars used to compare regression values Range Tolerance (%): Minimum score required to label a trend as bullish or bearish Regression Source: Data input used for regression (default: close) Linear Regression Length: Period for generating the base regression line Bull/Bear Base Colors: Choose colors to represent bullish or bearish bars 📈 Buy Timing Example Bars are green (or user-set bullish color) and becoming more vivid Indicates a strengthening bullish trend; helpful when used alongside breakout confirmation or support zones 📉 Sell Timing Example Bars turn red (or your custom bearish color) with increasing opacity Signals growing bearish pressure; acts as confirmation during short setups or breakdowns 🧪 Recommended Use Cases Combine with volume, RSI, or price action setups for direction filtering Ideal for clean chart strategies where visual simplicity is preferred Use as a confirmation layer to reduce noise in sideways markets 🔒 Precautions This is a visual filter, not a signal generator—use alongside other strategies for entries/exits In choppy markets, bars may flicker between colors—adjust sensitivity as needed Works best when you already have a directional thesis and want to validate it visually Always test settings for your asset/timeframe before applying in live trades
Chỉ báo Pine Script®
của c9indicator
Cnagda Liquidit Trading SystemCnagda Liquidit Trading System helps spot where price is likely to trap traders and reverse, then gives simple, actionable Level to entry, place SL, and take profits with confidence. It blends imbalance zones, trend bias, order blocks, liquidity pools, high-probability fake Signal, and context-aware candle patterns into one clean workflow. 🟩🟥 Imbalance boxes: “Crowd rushed, gaps left” What it is: Green/red boxes mark fast, one-sided moves where price “skipped” orders—think FVG-like zones that often get revisited. Why it helps: Price frequently pulls back to “fill” these zones, creating clean retest entries with logical stops. ⏩How to use: Green box = potential demand retest; Red box = potential supply retest. Enter on pullback into box, not on first impulse. Put stop on far side of box and aim first targets at recent swing points. ↕️ Swing bias (HH/HL vs LH/LL): “Which way is the road?” What it is: Higher-highs/higher-lows = up-bias; Lower-highs/lower-lows = down-bias. system plots Buy/Sell OB levels aligned with that bias. Why it helps: Trading with the broader flow reduces “hero trades” against institutions. Bias gives clearer entries and cleaner drawdowns. ⏩How to use: Up-bias: look for long on Buy OB retests. Down-bias: look for short on Sell OB retests. Wait for a small rejection/engulfing to confirm before triggering. 🧱Order blocks: “Where big players remember” What it is: last opposite-colored candle before an impulsive move—these zones often hold memory and reaction. system plots these as Buy/Sell OB lines. Why it helps: Many breakouts pull back to the origin. Good entries often happen on retest, not on the breakout chase. ⏩ How to use: Let price return into the OB, show wick rejection, and decent volume. Enter with stop beyond OB; define risk-reward before entry. 📊Volume coloring: “How Volume is move?” What it is: Bar color reflects relative volume; inside bars are black. The dashboard also shows Volume and “Volume vs Prev.” Why it helps: Patterns without volume often fade; volume validates strength and intent of moves. ⏩ How to use: Favor entries where imbalance/OB/liquidity-grab coincide with higher volume. If volume is weak, reduce size or skip. 🧲 BSL/SSL liquidity pools: “Fishing for stops” What it is: Equal highs cluster stops above (BSL); equal lows cluster stops below (SSL). system plots these and highlights the nearest one (“magnet”). Why it helps: Price often sweeps these pools to trigger stops before reversing. This is a prime trap-reversal location. ⏩ How to use: Watch nearest BSL/SSL. If price wicks through and closes back inside, anticipate a reversal. Trade reaction, not first poke. When price closes beyond, consider that pool mitigated and move on. 🟢🔴 Advanced liquidity grab: “Catch fakeout” What it is: Bullish grab = makes a new low beyond a prior low but closes back above it, with a long lower wick, small body, and higher volume. Bearish is mirror. Labeled automatically. Why it helps: It exposes trap moves (stop hunts) and often precedes true direction. ⏩ How to use: Best when it aligns with a nearby imbalance/OB and supportive volume. Enter on reversal candle break or on retest. Stop goes beyond sweep wick. 🧠 Smart candlestick patterns (only in right place) What it is: Engulfing, Hammer, Shooting Star, Hanging Man, Doji (with high volume), Morning/Evening Star, Piercing—but marked “effective” only if context (swing/trend/location) agrees. Why it helps: same pattern in the wrong place is noise; in the right place, it’s signal. ⏩ How to use: Location first (BSL/SSL/OB/imbalance), then pattern. Treat pattern as trigger/confirmation—one fresh label shows to keep chart clean. 🧭 Dashboard: “Context in a glance” ⏩ Reversal Level: current swing anchor—expect turns or reactions nearby; great for alerts and planning. ⏩ Volume vs Prev + Volume: Strength meter for signal candle—higher adds conviction. ⏩ Nearest Pool: next “magnet” area—look for sweeps/rejections there. 🧩Step-by-step trading flow (with mindset) ⏩ Set bias: HH/HL = long bias, LH/LL = short bias. Counter-trend only on clean sweeps with strong confirmation. ⏩ Find magnet: Check Nearest Pool (BSL/SSL). Focus attention there; it saves screen time. ⏩ Wait for event: Look for a sweep/grab label, or sharp rejection at pool/OB/imbalance. Avoid FOMO. ⏩ Add confluence: Stack 2–3 of these—imbalance box, OB, contextual pattern, supportive volume. ⏩Plan entry: Bullish: trigger above reversal candle high or take retest of FVG/OB. Stop below sweep wick/zone. Target at least 1:1.5–1:2. Bearish: mirror above. ⏩Manage smartly: Take partials, move to breakeven or trail thoughtfully. Don’t drag stops inside zone out of emotion. 🎛️ Parameter tuning (to reduce human error) ⏩ swingLen: Smaller = faster but noisier; larger = cleaner but slower. Backtest first, then go live. ⏩ Tolerance (ATR or percent): ATR tolerance adapts to volatility (good for fast markets and lower TFs). Start around 0.15–0.30. In calm markets, try percent 0.05–0.15%. ⏩ minBarsGap: Start with 3–5 so equal highs/lows are truly equal—reduces false pools. ❌Common mistakes → ✅ Better habits ⏩Chasing every breakout → Wait for sweep/rejection, then confirm. ⏩Ignoring volume → Validate strength; cut size or skip on weak volume. ⏩Losing history of pools → If reviewing/backtesting, keep mitigated pools visible (dashed/faded). ⏩Over-tight tolerance/too small swingLen → Increases false signals; backtest to find balance. 📝 checklist (before entry) ⏩ Is there a nearby BSL/SSL and did a sweep/grab happen there? ⏩ Is there a close imbalance/OB that price can retest? ⏩ Do we have an effective pattern plus supportive volume? ⏩Is the stop beyond the wick/zone and RR ≥ 1:1.5? •?((¯°·._.• 🎀 𝐻𝒶𝓅𝓅𝓎 𝒯𝓇𝒶𝒹𝒾𝓃𝑔 🎀 •._.·°¯((?•
Chỉ báo Pine Script®
của cnagda3
Smarter Money Concepts - Wyckoff Springs & Upthrusts [PhenLabs]📊Smarter Money Concepts - Wyckoff Springs & Upthrusts Version: PineScript™v6 📌Description Discover institutional manipulation in real-time with this advanced Wyckoff indicator that detects Springs (accumulation phases) and Upthrusts (distribution phases). It identifies when price tests support or resistance on high volume, followed by a strong recovery, signaling potential reversals where smart money accumulates or distributes positions. This tool solves the common problem of missing these subtle phase transitions, helping traders anticipate trend changes and avoid traps in volatile markets. By combining volume spike detection, ATR-normalized recovery strength, and a sigmoid probability model, it filters out weak signals and highlights only high-confidence setups. Whether you’re swing trading or day trading, this indicator provides clear visual cues to align with institutional flows, improving entry timing and risk management. 🚀Points of Innovation Sigmoid-based probability threshold for signal filtering, ensuring only statistically significant Wyckoff patterns trigger alerts ATR-normalized recovery measurement that adapts to market volatility, unlike static recovery checks in traditional indicators Customizable volume spike multiplier to distinguish institutional volume from retail noise Integrated dashboard legend with position and size options for personalized chart visualization Hidden probability plots for advanced users to analyze underlying math without chart clutter 🔧Core Components Support/Resistance Calculator: Scans a user-defined lookback period to establish dynamic levels for Spring and Upthrust detection Volume Spike Detector: Compares current volume to a 10-period SMA, multiplied by a configurable factor to identify significant surges Recovery Strength Analyzer: Uses ATR to measure price recovery after breaks, normalizing for different market conditions Probability Model: Applies sigmoid function to combine volume and recovery data, generating a confidence score for each potential signal 🔥Key Features Spring Detection: Spots accumulation when price dips below support but recovers strongly, helping traders enter longs at potential bottoms Upthrust Detection: Identifies distribution when price spikes above resistance but falls back, alerting to possible short opportunities at tops Customizable Inputs: Adjust lookback, volume multiplier, ATR period, and probability threshold to match your trading style and market Visual Signals: Clear + (green) and - (red) labels on charts for instant recognition of accumulation and distribution phases Alert System: Triggers notifications for signals and probability thresholds, keeping you informed without constant monitoring 🎨Visualization Spring Signal: Green upward label (+) below the bar, indicating strong recovery after support break for accumulation Upthrust Signal: Red downward label (-) above the bar, showing failed breakout above resistance for distribution Dashboard Legend: Customizable table explaining signals, positioned anywhere on the chart for quick reference 📖Usage Guidelines Core Settings Support/Resistance Lookback Default: 20 Range: 5-50 Description: Sets bars back for S/R levels; lower for recent sensitivity, higher for stable long-term zones – ideal for spotting Wyckoff phases Volume Spike Multiplier Default: 1.5 Range: 1.0-3.0 Description: Multiplies 10-period volume SMA; higher values filter to significant spikes, confirming institutional involvement in patterns ATR for Recovery Measurement Default: 5 Range: 2-20 Description: ATR period for recovery strength; shorter for volatile markets, longer for smoother analysis of post-break recoveries Phase Transition Probability Threshold Default: 0.9 Range: 0.5-0.99 Description: Minimum sigmoid probability for signals; higher for strict filtering, ensuring only high-confidence Wyckoff setups Display Settings Dashboard Position Default: Top Right Range: Various positions Description: Places legend table on chart; choose based on layout to avoid overlapping price action Dashboard Text Size Default: Normal Range: Auto to Huge Description: Adjusts legend text; larger for visibility, smaller for minimal space use ✅Best Use Cases Swing Trading: Identify Springs for long entries in downtrends turning to accumulation Day Trading: Catch Upthrusts for short scalps during intraday distribution at resistance Trend Reversal Confirmation: Use in conjunction with other indicators to validate phase shifts in ranging markets Volatility Plays: Spot signals in high-volume environments like news events for quick reversals ⚠️Limitations May produce false signals in low-volume or sideways markets where volume spikes are unreliable Depends on historical data, so performance varies in unprecedented market conditions or gaps Probability model is statistical, not predictive, and cannot account for external factors like news 💡What Makes This Unique Probability-Driven Filtering: Sigmoid model combines multiple factors for superior signal quality over basic Wyckoff detectors Adaptive Recovery: ATR normalization ensures reliability across assets and timeframes, unlike fixed-threshold tools User-Centric Design: Tooltips, customizable dashboard, and alerts make it accessible yet powerful for all trader levels 🔬How It Works Calculate S/R Levels: Uses the highest high and the lowest low over the lookback period to set dynamic zones Establishes baseline for detecting breaks in Wyckoff patterns Detect Breaks and Recovery: Checks for price breaking support/resistance, then recovering on volume Measures recovery strength via ATR for volatility adjustment Apply Probability Model: Combines volume spike and recovery into a sigmoid function for confidence score Triggers signal only if above threshold, plotting visuals and alerts 💡Note: For optimal results, combine with price action analysis and test settings on historical charts. Remember, Wyckoff patterns are most effective in trending markets – use lower probability thresholds for practice, then increase for live trading to focus on high-quality setups.
Chỉ báo Pine Script®
của PhenLabs
2
Math by Thomas Liquidity PoolDescription Math by Thomas Liquidity Pool is a TradingView indicator designed to visually identify potential liquidity pools on the chart by detecting areas where price forms clusters of equal highs or equal lows. Bullish Liquidity Pools (Green Boxes): Marked below price where two adjacent candles have similar lows within a specified difference, indicating potential demand zones or stop loss clusters below support. Bearish Liquidity Pools (Red Boxes): Marked above price where two adjacent candles have similar highs within the difference threshold, indicating potential supply zones or stop loss clusters above resistance. This tool helps traders spot areas where smart money might hunt stop losses or where price is likely to react, providing valuable insight for trade entries, exits, and risk management. Features: Adjustable box height (vertical range) in points. Adjustable maximum difference threshold between candle highs/lows to consider them equal. Boxes automatically extend forward for visibility and delete when price sweeps through or after a defined lifetime. Separate visual zones for bullish and bearish liquidity with customizable colors. How to Use Add the Indicator to your chart (preferably on instruments like Nifty where point-based thresholds are meaningful). Adjust Inputs: Box Height: Set the vertical size of the liquidity zones (default 15 points). Max Difference Between Highs/Lows: Set the max price difference to consider two candle highs or lows as “equal” (default 10 points). Box Lifetime: How many bars the box stays visible if not swept (default 120 bars). Interpret Boxes: Green Boxes (Bullish Liquidity Pools): Areas of potential demand and stop loss clusters below price. Watch for price bounces or accumulation near these zones. Red Boxes (Bearish Liquidity Pools): Areas of potential supply and stop loss clusters above price. Watch for price rejections or distribution near these zones. Trading Strategy Tips: Use these zones to anticipate where stop loss hunting or liquidity sweeps may occur. Combine with your Order Block, Fair Value Gap, and Market Structure tools for higher probability setups. Manage risk by avoiding entries into price regions just before large liquidity pools get swept. Automatic Cleanup: Boxes delete automatically once price breaks above (for bearish zones) or below (for bullish zones) the zone or after the set lifetime.
Chỉ báo Pine Script®
của MathThomas
1
Liquidity Sweep Filter [AlgoAlpha]Unlock a deeper understanding of market liquidity with the Liquidity Sweep Filter by AlgoAlpha. This indicator identifies liquidity sweeps, highlighting key price levels where large liquidations have occurred. By visualizing major and minor liquidation events, traders can better anticipate potential reversals and market structure shifts, making this an essential tool for those trading in volatile conditions. Key Features : 🔍 Liquidity Sweep Detection – Identifies and highlights areas where liquidity has been swept, distinguishing between major and minor liquidation events. 📊 Volume Profile Integration – Displays a volume profile overlay, helping traders spot high-activity price zones where the market is likely to react. 📈 Trend-Based Filtering – Utilizes an adaptive trend detection algorithm to refine liquidity sweeps based on market direction, reducing noise. 🎨 Customizable Visualization – Modify colors, thresholds, and display settings to tailor the indicator to your trading style. 🔔 Alerts for Liquidity Sweeps & Trend Changes – Stay ahead of the market by receiving alerts when significant liquidity events or trend shifts occur. How to Use: 🛠 Add the Indicator : Add the Liquidity Sweep Filter to your chart and configure the settings based on your preferred sensitivity. Adjust the major sweep threshold to filter out smaller moves. 📊 Analyze Liquidity Zones and trend direction : Look for liquidation levels where large buy or sell stops have been triggered. Major sweeps indicate strong reactions, while minor sweeps show gradual liquidity absorption. You can also see which levels are high in liquidity by the transparency of the levels. 🔔 Set-Up Alerts : Use the in-built alerts so you don't miss a trading opportunity How It Works : The Liquidity Sweep Filter detects liquidity events by tracking swing highs and lows (defined as a pivot where neighboring candles are lower/higher than it) where traders are likely to have placed stop-loss orders. It evaluates volume and price action, marking areas where liquidity has been absorbed by the market. Additionally, the integrated trend filter ensures that only relevant liquidity sweeps are highlighted based on market direction, lows in an uptrend and highs in a downtrend. The trend filter works by calculating a basis, and defining trend shifts when the closing price crosses over the upper or lower bands.The included volume profile further enhances analysis by displaying key trading zones where price may react.
Chỉ báo Pine Script®
của AlgoAlpha
35
Turtle Soup Model [PhenLabs]📊 Turtle Soup Model Version: PineScript™ v6 Description The Turtle Soup Model is an innovative technical analysis tool that combines market structure analysis with inter-market comparison and gap detection. Unlike traditional structure indicators, it validates market movements against a comparison symbol (default: ES1!) to identify high-probability trading opportunities. The indicator features a unique “soup pattern” detection system, comprehensive gap analysis, and real-time structure breaks visualization. Innovation Points: First indicator to combine structure analysis with gap detection and inter-market validation Advanced memory management system for efficient long-term analysis Sophisticated pattern recognition with multi-market confirmation Real-time structure break detection with comparative validation 🔧 Core Components Structure Analysis: Advanced pivot detection with inter-market validation Gap Detection: Sophisticated gap identification and classification system Inversion Patterns: “Soup pattern” recognition for reversal opportunities Visual System: Dynamic rendering of structure levels and gaps Alert Framework: Multi-condition notification system 🚨 Key Features 🚨 The indicator provides comprehensive analysis through: Structure Levels: Validated support and resistance zones Gap Patterns: Identification of significant market gaps Inversion Signals: Detection of potential reversal points Real-time Comparison: Continuous inter-market analysis Visual Alerts: Dynamic structure break notifications 📈 Visualization Structure Lines: Color-coded for highs and lows Gap Boxes: Visual representation of gap zones Inversion Patterns: Clear marking of potential reversal points Comparison Overlay: Inter-market divergence visualization Alert Indicators: Visual signals for structure breaks 💡Example 📌 Usage Guidelines The indicator offers multiple customization options: Structure Settings: Pivot Period: Adjustable for different market conditions Comparison Symbol: Customizable reference market Visual Style: Configurable colors and line widths Gap Analysis: Signal Mode: Choice between close and wick-based signals Box Rendering: Automatic gap zone visualization Middle Line: Reference point for gap measurements ✅ Best Practices: 🚨Use comparison symbol from related market🚨 Monitor both structure breaks and gap inversions Combine signals for higher probability trades Pay attention to inter-market divergences ⚠️ Limitations Requires comparison symbol data Performance depends on market correlation Best suited for liquid markets What Makes This Unique Inter-market Validation: Uses comparison symbol for signal confirmation Gap Integration: Combines structure and gap analysis Soup Pattern Detection: Identifies specific reversal patterns Dynamic Structure Management: Automatically updates and removes invalid levels Memory-Efficient Design: Optimized for long-term chart analysis 🔧 How It Works The indicator processes market data through three main components: 1. Structure Analysis: Detects pivot points with comparison validation Tracks structure levels with array management Identifies and processes structure breaks 2. Gap Analysis: Identifies significant market gaps Processes gap inversions Manages gap zones visualization 3. Pattern Recognition: Detects “soup” patterns Validates with comparison market Generates structure break signals 💡 Note: The indicator performs best when used with correlated comparison symbols and appropriate timeframe selection. Its unique inter-market validation system provides additional confirmation for traditional structure-based trading strategies.
Chỉ báo Pine Script®
của PhenLabs
1