Smart Money Liquidation Exploits [AlgoAlpha]🟠 OVERVIEW
Smart Money Liquidation Exploits maps recent swing highs and lows as liquidity levels, then watches how price reacts when these levels are reached. It focuses on liquidity sweeps where price moves beyond a prior swing with the wick but the candle body remains on the other side of the level.
The indicator combines pivot-based liquidity mapping, wick rejection signals, and structure-based take-profit levels. This helps traders separate a liquidity sweep from a simple break through a previous high or low.
It can use the current chart timeframe or a selected higher timeframe. This lets traders view liquidity and sweep signals from broader market structure while staying on a lower-timeframe chart.
🟠 CONCEPTS
Liquidity Level — A price level formed from a confirmed pivot high or pivot low. Pivot highs represent potential buy-side liquidity, while pivot lows represent potential sell-side liquidity.
Liquidity Sweep — A move where the wick crosses a liquidity level but the candle body stays beyond neither side of that level. A sweep below a pivot low is treated as bullish, while a sweep above a pivot high is treated as bearish.
Pivot Structure — Confirmed swing highs and lows defined by the Pivot Length setting. Consecutive pivots in the same direction are updated when a more extreme high or low forms.
Take-Profit Level — A target created after a valid sweep. For bullish sweeps, the target is the midpoint between the swept low and the latest swing high. For bearish sweeps, it is the midpoint between the swept high and the latest swing low.
Level Expiry — The period during which a liquidity or take-profit level remains active. Levels stop extending after they are reached or after the selected number of bars expires.
🟠 FEATURES
Liquidity Levels — Displays active pivot-based liquidity levels above and below price.
Sweep Signals — Marks bullish sweeps with ▲ and bearish sweeps with ▼ when price wicks through a liquidity level without the candle body crossing it.
Take-Profit Levels — Displays a dotted target after a valid liquidity sweep when an opposing swing is available.
Target Confirmation — Marks completed take-profit targets with a ✅ and connects the original sweep to the target hit.
Higher-Timeframe Mode — Allows liquidity levels, sweeps, targets, and expiry periods to use structure from a selected higher timeframe.
🟠 HOW TO USE
Watch the active liquidity levels around price to identify recent swing highs and lows that price may test.
Look for a ▲ below price when sell-side liquidity is swept. This shows that price moved below a pivot low but the candle body remained above the level.
Look for a ▼ above price when buy-side liquidity is swept. This shows that price moved above a pivot high but the candle body remained below the level.
After a valid sweep, use the dotted take-profit level as the indicator's structure-based target.
Watch for a ✅ when price reaches an active target. The connecting dotted line shows which sweep produced the completed target.
Increase Pivot Length to focus on broader swings, or reduce it to detect smaller local swings.
Enable Higher Timeframe mode when you want the liquidity structure and signals to come from a broader timeframe than the current chart.
Adjust Level Expiry Bars to control how long untouched liquidity and take-profit levels remain active.
🟠 CONCLUSION
Smart Money Liquidation Exploits combines pivot-based liquidity levels, wick-defined liquidity sweeps, and structure-based take-profit targets. It gives traders a visual way to identify rejected liquidity runs and track the price objective associated with each valid sweep. Indicator
VWAP Reversal Probability Signals🟠 OVERVIEW
VWAP Reversal Probability Signals tracks price movements around an anchored VWAP and two volume-weighted standard deviation bands. It looks for price excursions outside these bands and waits for price to move back through the same band before marking a potential reversal.
Each reversal signal is paired with a fixed VWAP target. The script records whether price reaches that target within a user-defined number of bars and displays the historical success rate for each band independently. This allows traders to compare how different reversal distances have performed over time instead of treating every signal the same.
🟠 CONCEPTS
Anchored VWAP — A volume-weighted average price that resets at the selected session, week, month, quarter, or year and acts as the central reference level.
VWAP Deviation Bands — Upper and lower bands created from volume-weighted standard deviation multiples around the anchored VWAP to define progressively larger price extensions.
Reversal Signal — Generated when price first extends beyond a deviation band and then closes back through that same band, indicating that the extreme move has started to reverse.
VWAP Target — Every signal uses the current anchored VWAP as its fixed target, allowing completed signals to be measured using the same destination.
Reversal Probability — The historical percentage of completed signals from each individual band that reached the VWAP target before the expiry period.
🟠 FEATURES
Anchored VWAP and Reversal Bands — Displays the anchored VWAP together with two configurable upper and lower deviation bands.
Reversal Signal Markers — Shows bullish and bearish reversal signals after price returns back
through the selected deviation band.
Historical Probability Labels — Displays the historical VWAP target hit rate beside each new reversal signal for the corresponding band.
VWAP Target Lines — Draws a projected target from every signal to the current VWAP until the trade either succeeds or expires.
Target Confirmation Marks — Places a confirmation mark when a tracked signal reaches its VWAP target within the selected expiry window.
🟠 HOW TO USE
Choose the VWAP anchor period that matches your trading style, such as session, week, or month.
Watch for price to extend beyond a VWAP deviation band and then move back through that same band before considering a reversal signal.
Compare the probability label shown with the signal to understand how that band has performed historically.
Use the dashed VWAP target line as the expected mean reversion objective for the active signal.
Treat the displayed probability as historical context rather than a prediction of future performance.
🟠 CONCLUSION
VWAP Reversal Probability Signals combines an anchored VWAP, volume-weighted deviation bands, reversal signals, and historical outcome tracking. By measuring how often each type of reversal has returned to the VWAP, it provides both reversal locations and statistical context for those signals. Indicator
High Volume Breakout Targets [AlgoAlpha]🟠 OVERVIEW
High Volume Breakout Targets identifies price zones formed by related pivot highs or pivot lows. These zones represent areas where price previously reacted around overlapping wick and candle-body levels.
The indicator then checks whether price closes through a zone with enough of the breakout candle extending beyond its boundary. Qualified breakouts can display directional labels, an entry level, and three targets based on the height of the broken zone.
Normalized volume candles are also shown inside recent active zones. This helps traders compare current volume with its recent average while watching price interact with a potential support or resistance area.
🟠 CONCEPTS
Pivot High Zone — A resistance area formed when a confirmed pivot-high wick falls within the body of a previous pivot-high candle. The zone spans the associated wick highs and body-top levels.
Pivot Low Zone — A support area formed when a confirmed pivot-low wick falls within the body of a previous pivot-low candle. The zone spans the associated wick lows and body-bottom levels.
Pivot Confirmation — A pivot requires the selected number of bars on both sides of the turning point. A higher Pivot Length identifies broader structures but confirms them later and less often.
Zone Maximum Age — The maximum number of bars during which two pivots can be associated and an active zone can continue extending. An expired zone remains visible but no longer produces a breakout.
Qualified Breakout — A breakout requires a confirmed close above a bearish zone or below a bullish zone. It must also place the selected percentage of the candle’s full range beyond the broken boundary.
Normalized Volume — Current volume is divided by its 20-bar average. The resulting ratio controls the size and transparency of the volume candle displayed inside an active zone.
Breakout Targets — The breakout close becomes the entry level. The broken zone’s height is divided into three equal steps to calculate TP1, TP2, and TP3 in the breakout direction.
Target Expiry — Each target setup remains active for a selected number of bars. When TP1 or TP2 is reached, the remaining unhit targets receive a new expiry period from the hit candle.
🟠 FEATURES
Pivot Zones — Displays bullish support zones and bearish resistance zones created from associated pivot structures.
Breakout Labels — Marks bullish and bearish closes that satisfy the selected outside-range requirement.
Three-Level Targets — Displays the breakout entry, a target area, and TP1, TP2, and TP3 levels derived from the broken zone’s height.
Zone Volume Display — Shows normalized volume candles inside the four most recently active zones.
Target Completion Marker — Prints a checkmark on the first candle whose wick reaches TP3.
🟠 HOW TO USE
Adjust Pivot Length to match the structure you trade. Use lower values for smaller and more frequent zones, or higher values for broader and less frequent zones.
Treat bullish zones as potential support and bearish zones as potential resistance while they continue extending.
Watch how price behaves inside a zone. Use the normalized volume candles to compare participation with the recent volume average.
Wait for a breakout label rather than treating every wick through a zone as a breakout. A label appears only after the candle closes beyond the boundary and meets the Minimum Breakout Range setting.
Use a higher Minimum Breakout Range to require more of the breakout candle to trade beyond the zone. Use a lower value to accept less decisive moves.
After a qualified breakout, use the entry line as the breakout reference and TP1, TP2, and TP3 as zone-based projection levels.
Check whether targets are reached before their expiry. TP1 and TP2 extend the active period for the remaining targets when reached.
Combine the zones and breakout signals with market structure, trend direction, liquidity, and risk controls. The indicator does not define a stop-loss or position size.
🟠 CONCLUSION
High Volume Breakout Targets combines pivot-based support and resistance zones, normalized volume context, qualified breakout signals, and zone-height target projections. It gives traders a structured way to assess price interaction with established zones and track the progression of confirmed breakouts. Indicator
Liquidity Sweep Hunter Algo [AlgoAlpha]🟠 OVERVIEW
Liquidity Sweep Hunter Algo identifies liquidity highs and lows across three different lookback periods and keeps them active until they are mitigated. This creates a persistent view of where resting liquidity has formed instead of only showing the latest swing points.
The indicator also displays a heatmap that highlights the relative strength of active liquidity levels and generates reversal signals after price sweeps multiple visible liquidity bands before reclaiming them. Optional trade drawings project a stop loss, reward target, and intermediate target levels directly on the chart.
🟠 CONCEPTS
Liquidity Level — A price extreme detected from fast, medium, and slow lookback windows. Matching levels are merged so nearby highs or lows are treated as the same liquidity area.
Liquidity Heatmap — A visual strength map where colour represents the relative strength of each active liquidity level compared to the other visible levels.
Multi-Level Liquidity Sweep — A reversal condition where price sweeps at least two visible liquidity bands and then closes back beyond the reclaim level within a limited number of bars. An optional strength filter can require the swept levels to exceed a minimum average strength.
🟠 FEATURES
Liquidity Heatmap — Displays active liquidity levels using a colour gradient that reflects their relative strength.
Multi-Level Sweep Signals — Plots bullish and bearish reversal labels after confirmed liquidity sweep and reclaim events.
Trade Projection Boxes — Draws entry, stop loss, reward zone, and target milestone levels after each signal.
Trade Progress Display — Fills the target area as price reaches successive target levels and marks completed trades with a check mark.
🟠 HOW TO USE
Watch the heatmap to identify where stronger liquidity has accumulated around current price.
Wait for a bullish or bearish sweep signal after price clears multiple liquidity bands and reclaims the area.
Use the optional trade projection as a visual reference for the calculated stop loss, reward target, and target milestones.
Increase the lookback values to focus on broader liquidity zones or decrease them to detect more local levels.
Adjust the sweep strength filter if you want signals only when stronger liquidity zones are involved.
🟠 CONCLUSION
Liquidity Sweep Hunter Algo combines persistent liquidity mapping, a relative strength heatmap, and multi-level liquidity sweep detection in a single indicator. It also provides optional trade projections that remain on the chart after each signal. Together these features help traders monitor where liquidity has formed, when it has been swept, and where price has reclaimed the area. Indicator
Indicator
Indicator
Adaptive Smart Money Liquidity Sweep Levels [AlgoAlpha]🟠 OVERVIEW
Adaptive Smart Money Liquidity Levels tracks liquidity resting above and below price by detecting swing highs and lows across multiple lookback periods. Instead of displaying every historical level equally, it stores active liquidity zones, updates them over time, and removes them once price mitigates them.
The indicator also estimates the amount of liquidity accumulated around nearby levels using traded volume. This information is displayed through level opacity, a near-range liquidity balance chart, and an orderbook-style liquidity depth profile to provide context around where liquidity is concentrated.
🟠 CONCEPTS
Liquidity Level — Swing highs and swing lows detected from fast, medium, and slow lookback windows. Nearby levels are merged together to reduce duplicate levels. These levels are used to estimate the location of stop-loss orders, and volume + candle direction are used to estimate the buying/selling (and thus concentration of stop-loss orders) to determine the magnitude of orders at these levels.
Liquidity Depth — Volume is assigned to the nearest active liquidity levels based on candle direction and configurable distance weighting. The accumulated volume forms a depth profile around current price.
Mass Liquidation — Triggered when a candle body moves through two or more active liquidity levels on the same side, indicating multiple liquidity pools were cleared within a single move.
Stop-runs and Liquidity Dynamics — This script takes advantage of the concept of resting limit orders, and resting stop-loss orders. When a bar wicks a liquidity level instead of strongly trading through it, it implies a stronger amount of opposing pressure from both limit and market-orders than the pressure coming from clustered stop-losses, preventing a stop run and signalling a higher chance of that level holding and potentially a rebound. In simple terms, this indicator can be used as part of ICT and Smart Monet Concepts to help better understand a real liquidity sweep (marked by ▲▼) vs liquidation events (marked by highlighted candles) as both events usually require vastly different actions to capitalize on correctly.
🟠 FEATURES
Adaptive Liquidity Levels . Displays the nearest active liquidity above and below price.
• Level opacity increases as more volume accumulates.
• Levels automatically disappear after mitigation or when they exceed the selected maximum age.
• Levels represent accumulating stop loss orders as more trades occur (using volume and candle direction to estimate market orders)
Near Range Liquidity Balance . Shows the relative liquidity accumulated of the 3 nearest levels above and below current price using a two-column comparison chart.
Liquidity Depth Curve . Draws an orderbook-style cumulative depth profile beside price to visualize how liquidity builds further away from the current market.
Liquidation And Sweep Signals . Highlights candles that clear multiple liquidity levels and marks wick-only liquidity sweeps with directional markers.
🟠 HOW TO USE
Monitor liquidation labels and wick sweep markers to distinguish between full liquidity removals and liquidity that was only briefly tested. Liquidity removals imply weak levels while those that were wicked imply strong concentration of limit orders, useful for planning where to place stop losses or to time trade entries.
Watch the nearest liquidity levels to identify where resting liquidity is currently concentrated around price.
Compare the Near Range Liquidity Balance to see whether more liquidity is currently stacked above or below the market.
Use the Liquidity Depth Curve to estimate how liquidity changes as price moves further away from its current location.
🟠 CONCLUSION
Adaptive Smart Money Liquidity Levels combines multi-scale liquidity detection, volume-weighted liquidity accumulation, and mitigation tracking into a single view. By displaying active liquidity, nearby liquidity balance, and cumulative liquidity depth together, it provides additional context for where price is interacting with resting stop orders and how that structure changes over time. A key detail to note is that this script estimates the position and concentration of orders with proxies like swing levels and volume, and that the levels represent stop-loss orders, not limit orders. Indicator
Strong Risk Management | ProjectSyndicateStrong Risk Management turns trade planning into an institutional-grade pre-trade cockpit. Click your Entry, Stop, and three Take-Profit levels straight onto the chart and the tool instantly sizes the position, derives your leverage and margin, estimates the liquidation price, scores the setup, and stress-tests it against your prop-firm rules — all on two clean Bloomberg-amber panels. Every figure is computed live from your own inputs and the symbol's real tick size, not hard-coded, so the numbers describe the exact trade you are about to take, right now.
🎯 Click-to-Place Interactive Levels — drop Entry, Stop Loss, and TP1 / TP2 / TP3 directly on the chart and drag them whenever you want, just like native drawing tools. An anchor-time input lets you pin the setup to a specific bar, direction (Long / Short) is auto-detected from where your stop sits, and every level you place is always respected — the auto R-multiples only fill in the targets you leave blank.
🧮 Fee-Aware Position Sizing — the engine uses the classic fixed-fractional model and sizes the position so a full stop-out equals exactly the risk you defined, with entry and exit fees folded into the math. Choose your risk as a percentage of balance, a percentage of allocated trade capital, or a fixed cash amount, and read the precise contracts/size and notional position value it produces.
⚡ Three Leverage Modes + Liquidation Engine — run Isolated Capital (leverage derived from the margin you commit), Fixed Leverage (you set the multiplier), or Auto-Safe Leverage, which automatically picks the highest leverage that still keeps your liquidation price safely beyond your stop by a configurable buffer. The panel shows effective trade leverage, account leverage, maintenance margin rate and amount, the estimated liquidation price, and how many times further it sits than your stop — with a loud warning if liquidation would ever come before your stop is hit.
📊 Dual Bloomberg-Amber Panels — Panel 1 (Risk Console) lays out balance, trade capital, risk model, max loss, the full setup (entry, stop, stop distance, break-even, size, position value), the leverage and liquidation block, and the setup-quality verdict. Panel 2 (Prop Guardrails + Take-Profit Plan) handles the funded-account rule checks and the full target ladder. Position each panel independently anywhere on the chart.
🛡️ Prop-Firm Guardrails — purpose-built for funded and challenge traders. Set your account size, phase (Challenge / Verification / Funded), daily loss limit, maximum drawdown (with a trailing option), profit target, per-trade risk cap, and consistency rule, then see this trade scored against every one of them with SAFE / CAUTION / VIOLATION lights and an overall status. It also tells you how many trades like this you can take before breaching your daily and max-drawdown budgets, how much budget is left, and how many wins remain to the profit target.
🎚️ Take-Profit Ladder with FULL / SLICE — each target shows its price, R multiple, and allocation %, plus the dollars it books two ways: FULL (if you closed the whole position there) next to SLICE (what your partial allocation actually books). The plan rolls up into a Plan Profit row with blended R and ROI on margin, so partial exits never look inconsistent against a full-size stop again.
↔️ Reward : Risk Verdict — a single, color-coded 1 : x line grades the whole plan EXCELLENT / GOOD / MARGINAL / POOR, so a setup whose targets sit inside the stop distance screams at you instead of hiding inside an average. A companion "1R Value (full, net)" read exposes the fee drag by showing what one clean R is actually worth in cash after costs.
★ 0–10 Setup Quality Score — a composite grade blending reward-to-risk quality, risk-per-trade discipline, liquidation safety, and prop-rule headroom into one number and an ELITE / STRONG / FAIR / WEAK tier, for a fast go/no-go read before you commit.
🟢 Risk-Free-After-TP1 Read — shows exactly what closing your first partial locks in, and confirms that trailing your stop to break-even afterwards takes the remaining downside to near zero — the de-risking move spelled out in dollars.
🖥️ On-Chart Trade Map — the full trade is drawn as banded zones (profit, loss, a liquidation-danger band, and a runner zone beyond TP3), precise level lines for entry, stop, every target, break-even, and liquidation, and right-edge labels carrying each level's price, R multiple, and cash value at a glance.
🔴 Honest Live Trade Tracker — once price reaches your entry, the tool tracks floating P&L and then prints a clear ✓ TARGET HIT or ✘ STOPPED OUT outcome. Losers are never hidden, and same-bar ambiguity is always resolved pessimistically to the stop, so the read stays truthful.
🔔 Native Alerts — fire on entry triggered, target hit, stopped out, and any prop-firm guardrail violation, so you can wire the cockpit straight into your workflow.
🧩 Fully Customizable — choose each panel's position (Top / Middle / Bottom paired with Left / Right) and text size, pick your quote-currency symbol, set entry and exit fees, the maintenance-margin rate and liquidation safety factor, your R multiples and allocation split, auto-vs-manual targets, and toggle the chart zones, liquidation line, break-even line, and live tracker — all from the settings menu, no code editing required.
🎯 Why this is different — most position-size calculators hand you a lot size and stop there. This is a complete pre-trade cockpit: it sizes the trade, derives leverage and margin, estimates liquidation, scores the setup, grades the reward-to-risk honestly with fees included, and checks the whole thing against your funded-account rules — two panels that answer "how big, how safe, and is this even worth taking?" before you click buy or sell.
🚀 Where to use it — works on any symbol and timeframe. Built with crypto perpetuals, futures, and margin/leverage trading in mind, but equally useful for forex and stocks: plan the trade, validate the sizing and prop-rule headroom, then execute with the levels already mapped on your chart.
⚠️ Important — this is a research and decision-support tool, not a buy/sell system, and it makes no performance guarantees. Liquidation price, fees, maintenance margin, and leverage figures are simplified estimates and can differ from your specific broker or exchange — always verify against their exact contract specifications before sizing a live position. Nothing here is financial advice. Pair it with your own analysis and risk management. Indicator
Machine Learning Adaptive DMI Signals [AlgoAlpha]🟠 OVERVIEW
The Directional Movement Index (DMI) is commonly calculated using a fixed lookback length. But market conditions change over time, and a length that works well during one period may become less effective during another.
This script builds multiple DMI models across a user-defined range of lengths and continuously evaluates their past performance. Each DMI length acts as an independent expert. As new directional flips occur, the script measures how well each expert performed and updates its internal scoring system.
The result is an adaptive DMI that automatically shifts toward lengths that have recently produced better directional signals while reducing the influence of weaker performers.
🟠 CONCEPTS
Expert DMI — A DMI calculation running at a specific lookback length within the tested range.
Directional Flip — A change in trend state when +DI crosses above -DI or when -DI crosses above +DI.
Reward Score — A performance score assigned to each completed flip based on return, move quality, pullback behavior, or win rate.
Maximum Favorable Excursion (MFE) — The largest move in the trade's favor before the next directional flip.
Maximum Adverse Excursion (MAE) — The largest move against the trade before the next directional flip.
Recency Decay — A weighting system that gradually reduces the influence of older observations so recent market behavior has greater impact.
Softmax Weighting — A probability-style weighting process that gives greater influence to higher-scoring DMI lengths when estimating the adaptive length.
🟠 FEATURES
Adaptive +DI and -DI Lines — Displays directional movement using a dynamically selected DMI length that adjusts over time.
Directional Clouds — Color-filled regions between the DI lines help visualize which side currently has directional control.
Bullish and Bearish Flip Signals — ▲ and ▼ markers appear when the Adaptive +DI and -DI lines cross.
ADX Strength Display — Strength squares at the bottom of the pane become more visible as trend strength increases and fade as strength decreases.
Information Table — Displays the active adaptive length, selected scoring mode, memory count, and current bullish or bearish trend state in a customizable table.
🟠 HOW TO USE
Watch for bullish flips when Adaptive +DI crosses above Adaptive -DI to identify potential shifts toward upward directional control.
Watch for bearish flips when Adaptive -DI crosses above Adaptive +DI to identify potential shifts toward downward directional control.
Use the ADX strength squares to gauge whether directional movement is strengthening or weakening.
Increase the tested length range when evaluating a wider variety of market conditions.
Increase Memory and Forget Old Trades values for more stable adaptation and slower length changes.
Decrease Memory or lower the decay factor when faster adaptation to recent behavior is preferred.
Experiment with the available scoring methods to determine whether return, trend quality, or consistency is more important for your analysis.
🟠 CONCLUSION
Machine Learning Adaptive DMI combines traditional DMI calculations with a performance-driven adaptive length selection process. Instead of relying on a fixed lookback period, it continuously evaluates how different DMI lengths have behaved and adjusts accordingly. This provides a dynamic view of directional strength, trend bias, and signal quality that reflects recent market behavior. Indicator
Support and Resistance Retest Breakout Signals [AlgoAlpha]🟠 OVERVIEW
This script identifies support and resistance zones using pairs of swing highs and swing lows that occur within a volatility-adjusted price tolerance. Instead of drawing levels from a single pivot, it waits for two matching swings to confirm a zone, helping filter out isolated highs and lows that may have little significance.
Each zone contains a buy/sell volume balance estimate calculated from lower timeframe data. This provides additional context about the activity that formed the zone and helps visualize whether buying or selling pressure was more dominant during its creation.
The script also tracks how price interacts with existing zones after they form. When price fully breaks through a zone and later retests it, bullish or bearish retest signals are generated based on the direction of the breakout.
🟠 CONCEPTS
Swing Matching — Two swing highs or two swing lows must occur within a volatility-adjusted tolerance before a resistance or support zone is created.
Volatility-Adjusted Tolerance — The script uses the standard deviation of price over a lookback period to determine how close swing points must be to qualify as the same zone.
Support and Resistance Zones — Zones are built from the full price structure around matched swing points rather than from a single horizontal price level.
Volume Balance — Lower timeframe buying and selling volume is aggregated between the two swings that formed the zone to estimate directional participation.
Breakout Retest Logic — Price must first move completely beyond a zone, then close through it, and finally revisit the zone before a retest signal is confirmed.
🟠 FEATURES
Support and Resistance Zones — Highlights confirmed support and resistance areas formed from recurring swing lows and swing highs.
Volume Balance Display — Shows buy and sell volume balance bars inside each zone for visual participation analysis.
Retest Signals — Displays signals when price breaks above a zone and successfully retests it.
🟠 HOW TO USE
Watch for newly formed support and resistance zones to identify areas where price has repeatedly reacted.
Compare the buy/sell balance bars inside each zone to understand the volume profile that formed the level.
Look for bullish retest signals after price breaks above a resistance zone and returns to test it from above.
Look for bearish retest signals after price breaks below a support zone and returns to test it from below.
Use larger Time Horizon values to focus on major market structure and smaller values to detect more frequent zones.
Enable overlap prevention when you want fewer but more distinct zones on the chart.
Use alerts to monitor new zones and confirmed retest events without continuously watching the chart.
🟠 CONCLUSION
Support and Resistance Retest Breakout Signals combines volatility-adjusted zone detection, lower timeframe volume balance analysis, and breakout retest confirmation into a single workflow. It identifies areas where price has repeatedly reacted, measures the participation behind those areas, and tracks whether breakouts successfully hold during retests. This gives traders a structured view of support, resistance, and post-breakout behavior. Indicator
Regression Trend Reversal Signals & Forecasts [AlgoAlpha]🟠 OVERVIEW
Regression Trend Reversal Signals & Forecasts combines multiple regression methods into a single trend and reversal framework. It allows traders to choose between Linear Regression, Theil-Sen Regression, LOESS smoothing, Nadaraya-Watson smoothing, Polynomial Regression, and a Kalman Filter to estimate the underlying price path.
The selected regression line acts as the center of a dynamic channel. The channel width is based on the standard deviation of the distance between price and the regression line, allowing it to adapt to changing market conditions.
The script also identifies potential reversal conditions when price extends beyond the channel and then shows signs of rejection. In addition, it can project the current regression slope forward to provide a simple forecast of the current trend path.
🟠 CONCEPTS
Regression Line — A statistical estimate of the underlying price trend. Different methods can be selected, ranging from straight-line regressions to adaptive smoothing techniques.
Theil-Sen Regression — A robust regression method that uses median slopes from all point pairs, reducing the influence of outlier price spikes.
LOESS Regression — A locally weighted regression that fits nearby observations more heavily than distant observations to create a smooth trend curve.
Nadaraya-Watson Smoothing — A kernel-weighted averaging method that estimates trend by assigning larger weights to recent observations.
Kalman Filter — A recursive estimation method that continuously updates the trend estimate as new prices arrive.
Polynomial Regression — A curved regression model that can capture non-linear trend structures using higher-order polynomial functions.
Regression Deviation Bands — Channel boundaries calculated from the standard deviation of price relative to the regression line.
Regression Slope — The rate of change of the regression estimate used to determine trend direction and forecast projections.
🟠 FEATURES
Regression Channel — Dynamic bands expand and contract based on how far price deviates from the regression line.
Trend Flip Signals — Generates directional markers when the regression trend changes from rising to falling or from falling to rising.
Reversal Signals — Marks potential bullish and bearish reversals when price extends beyond the channel and begins rejecting those extremes.
Forecast Projection — Extends the current regression slope into future bars and optionally displays projected channel boundaries.
🟠 HOW TO USE
Select a regression method that matches the market behavior you want to analyze. Linear and Theil-Sen are suited to directional trends, while LOESS, Nadaraya-Watson, and Kalman provide smoother adaptive estimates.
Use the regression line as the primary trend reference. Rising regression values indicate strengthening conditions, while falling values indicate weakening conditions.
Monitor the channel boundaries for extended price movement away from the regression estimate.
Watch for bullish reversal markers below the lower band after downside extensions and bearish reversal markers above the upper band after upside extensions.
Use trend flip signals as confirmation that the regression slope has changed direction.
Compare price location within the channel to gauge whether price is trading near trend equilibrium or at an extreme deviation.
Use the forecast projection as a continuation estimate of the current regression slope rather than a prediction of future market behavior.
🟠 CONCLUSION
Regression Reversal Signals combines multiple regression techniques, adaptive deviation channels, reversal detection, and forward projections into a single framework. By allowing traders to switch between several trend estimation methods, it provides different perspectives on trend structure and price deviation. The indicator helps identify trend direction, potential reversals, and areas where price has moved unusually far from its estimated path. Indicator
Nadaraya-Watson Regression Liquidity Sweeps [AlgoAlpha]🟠 OVERVIEW
This script combines Nadaraya-Watson regression, momentum analysis, and liquidity level tracking into a single workflow. It measures the slope of a smoothed price regression curve, converts that slope into a normalized oscillator, and uses momentum shifts to identify areas where liquidity may be resting.
The oscillator is built from the rate of change of the Nadaraya-Watson estimate rather than price itself. This allows momentum transitions to be measured relative to the underlying regression trend. When momentum weakens after an extended move, the script records swing-based liquidity levels that can later be swept by price.
A volatility-adjusted Nadaraya-Watson band is also displayed on the chart. This provides context for trend direction, momentum strength, and potential rebound conditions around the regression value.
🟠 CONCEPTS
Nadaraya-Watson Regression — A kernel-based smoothing method that estimates an underlying price curve by weighting nearby historical data more heavily than distant data.
Normalized Regression Slope — The change in the Nadaraya-Watson estimate divided by its recent standard deviation, allowing momentum strength to be compared across different market conditions.
Liquidity Sweep Level — A horizontal level created from a swing high or swing low when momentum begins to weaken, representing an area that may later attract price.
Oscillator Signal Line — An EMA of the normalized oscillator used to identify momentum crossovers and momentum phase changes.
Rebound Condition — A signal generated when price moves back through the Nadaraya-Watson value while oscillator direction remains aligned with the prevailing momentum bias.
🟠 FEATURES
Normalized Nadaraya-Watson Oscillator — Measures momentum using the slope of a smoothed regression curve.
Liquidity Sweep Detection — Creates liquidity levels when bullish or bearish momentum begins to weaken.
Volatility-Adjusted Regression Band — Displays a dynamic overlay around the Nadaraya-Watson estimate using smoothed ATR values.
Momentum Weakening Signals — Marks locations where oscillator momentum begins to lose strength against the current directional bias.
Rebound Signals — Highlights situations where price reclaims or loses the regression value while momentum remains aligned with trend direction.
🟠 HOW TO USE
Monitor the oscillator relative to its signal line to identify momentum shifts and changes in directional bias.
Watch for newly created liquidity levels after momentum weakening events, as these levels may become future sweep targets.
Use sweeps of upper or lower liquidity levels to identify areas where price has taken resting liquidity.
Look for bullish rebound signals when price reclaims the regression value while bullish momentum remains active.
Look for bearish rebound signals when price loses the regression value while bearish momentum remains active.
Combine oscillator direction, liquidity levels, and regression band structure to build context around trend continuation or reversal scenarios.
🟠 CONCLUSION
The Nadaraya-Watson Regression Liquidity Sweeps indicator combines regression-based momentum analysis, volatility-adjusted trend structure, and liquidity level tracking. By linking momentum transitions to swing-derived liquidity zones, it helps identify where liquidity may be forming and when it has been swept. This provides traders with additional context for trend analysis, pullbacks, and potential reversal areas. Indicator
Whale Liquidity and Absorption Profile [AlgoAlpha]🟠 OVERVIEW
The Whale Liquidity and Absorption Profile maps intrabar buying, selling, delta, and absorption activity into stacked horizontal profiles. It samples lower timeframe volume data inside each chart candle, then groups that activity into price bins to show where aggressive participation and absorption occurred across a configurable lookback range.
The script separates strong and weak activity using a percentile-based strength filter. It also builds a delta heatmap, absorption profile, historical absorption heatmap, and local absorption zones. Together, these components help traders identify where liquidity entered the market, where imbalance formed, and where price may react again.
🟠 CONCEPTS
Intrabar Sampling — Lower timeframe volume and directional data are requested using request.security_lower_tf() to reconstruct buying and selling activity inside each chart candle.
Strength Filter — Intrabar volume samples are ranked by percentile. Volumes above the selected percentile threshold are classified as strong activity while lower values are treated as weak activity.
Delta Profile — Buy volume minus sell volume calculated per price bin. Positive delta shows aggressive buying while negative delta shows aggressive selling.
Absorption Volume — Bullish volume occurring in upper wicks and bearish volume occurring in lower wicks. This is used to estimate where opposing liquidity absorbed incoming pressure.
Price Bins — The full price range inside the lookback is divided into vertical bins. All volume, delta, and absorption calculations are aggregated into these bins.
Absorption Peaks — Local highs in the absorption profile compared against neighboring bins. These areas are drawn as support and resistance zones.
🟠 FEATURES
Multi-Layer Volume Profile — Displays stacked buying and selling activity across price levels.
• Separates strong bullish, weak bullish, weak bearish, and strong bearish volume.
• Optional strong-only mode hides weak participation and normalizes the profile using only strong activity.
Delta Heatmap — Displays signed delta values directly inside each profile cell.
• Positive delta highlights dominant buying pressure.
• Negative delta highlights dominant selling pressure.
Absorption Profile — Aggregates wick-based absorption activity into a separate horizontal profile. (Buys at high wicks, Sells at low wicks)
Historical Absorption Heatmap — Creates rolling 5-bar heatmap snapshots to show where historical absorption accumulated over time.
Absorption Zones — Detects local absorption peaks and projects them across the chart as potential reaction areas.
Strong Activity Bubbles — Marks the strongest intrabar buying and selling events directly on price using percentile-ranked bubble tiers.
🟠 HOW TO USE
Load 2 instances of the indicator to bypass box drawing limits and use both the Absorption heatmap and the profiles.
Watch for stacked strong bullish volume combined with positive delta — this can show aggressive participation entering a price region.
Watch for stacked strong bearish volume combined with negative delta — this can show heavy selling pressure dominating a level.
Use absorption zones as areas where price previously encountered opposing liquidity — these zones may act as future reaction points.
Compare delta against absorption — strong positive delta with heavy upper-wick absorption can indicate trapped buyers or resistance.
Use the historical absorption heatmap to locate repeated liquidity interaction zones that price continues to respect over time.
Increase profile resolution for tighter price detail and reduce it for broader structural zones.
Enable strong-only mode to isolate high-participation liquidity events and remove weaker intrabar activity from the profile.
🟠 CONCLUSION
Whale Liquidity and Absorption Profile combines intrabar volume profiling, delta analysis, and wick-based absorption detection into a single structured framework. The indicator separates strong and weak participation while mapping where liquidity was absorbed across price levels. This gives traders a clearer view of imbalance, participation strength, and potential reaction zones inside the current market structure. Indicator
Indicator
SuperTrend Take-Profit Dimensions [AlgoAlpha]🟠 OVERVIEW
A multi-dimensional take-profit aid that scores how typical the current bar looks compared to past SuperTrend pivots, so you can tell when a trend has reached favorable exit conditions.
The indicator runs a standard SuperTrend and records every confirmed zigzag pivot that occurs during a matching-direction run. Tops go into a bull pool , bottoms into a bear pool . Each pivot is stored as a set of readings across several independent axes, such as relative volume , time of day , and price position inside the recent range .
On every bar, the current reading on each axis is compared to that historical pool. A blended score from 0 to 100 tells you how closely the current conditions resemble where past pivots in the same direction have clustered. The idea is to give trend followers a data-backed sense of when to start tightening up, rather than guessing an exit or using a fixed R-multiple.
The three built-in axes were chosen deliberately to be as uncorrelated as possible , each describing a different dimension of market context: volume (relative volume percentile), time (time of day), and price (position in recent range). Correlated inputs would double-count the same information and distort the blended score; picking axes that describe genuinely different aspects of the market means each one contributes independent evidence, and the score reflects how many distinct dimensions are currently in agreement.
🟠 CONCEPTS
SuperTrend — An ATR-based trailing stop that flips between bullish and bearish states. Controls which pool of historical pivots the script reads from.
Pivot pool — A rolling store of confirmed zigzag pivots, split by direction. Bull pool holds pivot highs that printed during bullish SuperTrend runs; bear pool holds pivot lows from bearish runs. Capped at 2000 entries per side .
Context axis — A 0–100 value measured at the pivot bar. The script ships with three built-ins ( relative volume percentile , time of day , position in recent range ) and one optional user-plugged signal.
Axis independence — The three built-in axes cover volume , time , and price respectively, chosen so each describes a structurally different part of the market. Low correlation between axes keeps the blended score from being dominated by any single factor.
Conditional histogram — For each active axis, the script walks its pool and keeps only pivots whose bins on every other active axis match the current bar. The survivors are binned to form a histogram.
Axis score — For one axis, the count of pivots in the current bar's bin divided by the count in the histogram's tallest bin, scaled to 0–100 . 100 means the current context sits in the densest part of past pivots.
Blended favourability score — Arithmetic mean of the active per-axis scores. This is what the gauge and table display.
Density-match scoring — The score measures how common the current context is among past pivots. It is not a forward probability and makes no claim about what happens next.
🟠 FEATURES
Right-side context profiles — Stacked mini histograms render to the right of price, one per active axis.
• Bar heights show how pivots in each axis's conditional pool distribute across bins.
• A dashed vertical line marks the current bar's bin on that axis, so you can see at a glance where today sits against history.
• Bar hue tracks the active SuperTrend direction.
Favourability gauge — A vertical gradient table in the bottom-right showing the blended score, with a chevron marking the current level. Green at the top, red at the bottom.
Favourability breakdown table — A two-column readout of each active axis's individual score out of 100, plus a final row that classifies the blended score as Good , Neutral , or Bad . Position and text size are configurable.
Bar coloring — Bars fade from neutral grey toward the opposing trend colour as the blended score rises toward 100, so the chart itself signals when the context is stretched.
Take-profit markers — Small orange markers print above or below the bar when the blended score hits 100 for the active SuperTrend direction.
Timeframe guard — The time-of-day axis disables automatically on daily and higher timeframes, where the reading has no meaning, and a banner explains this so the blended score stays honest.
Multi-dimensional scoring engine — Four independent axes feed into a single score, each conditioned on all the others.
• Three built-in axes can be toggled on or off individually.
• A fourth axis accepts any plot via source input , provided the series stays within 0–100 on all loaded bars.
• An on-chart warning prints if the custom signal leaves that range, and the axis is ignored until it is corrected.
Deliberately uncorrelated built-in axes — Volume ( relative volume percentile ), time ( time of day ), and price ( position in recent range ) cover three structurally different facets of market context. Keeping the axes independent means each one adds new information to the blend rather than reinforcing the others.
Alert conditions — Six alerts are included: SuperTrend bullish flip, SuperTrend bearish flip, score peak match, and crossovers into the Good , Neutral , and Bad bands.
🟠 HOW TO USE
Add the script to an intraday chart on a liquid instrument and let it run long enough to populate the pools. More history means more stable conditional histograms.
Let SuperTrend define the active regime. The script only scores in the direction of the current trend; bar coloring and take-profit markers respect that regime.
Read the gauge and breakdown table together. The gauge shows the blended level; the table shows which individual axes are pulling it up or down.
Use the right-side profiles as a sanity check. If the dashed current-bin marker is sitting on or near the tallest bar across most axes, the current context closely resembles past pivot contexts in that direction.
Treat high scores as a cue to tighten management, not as reversal signals. A reading of 100 means conditions match where pivots have historically clustered, not that the trend is guaranteed to end.
Adjust the zigzag pivot length to control how strict the pool is. Lower values admit more pivots ( bigger, noisier sample ); higher values keep only firmer pivots ( smaller, cleaner sample ).
Plug your own signal into the custom axis to test whether an existing 0–100 oscillator adds useful conditioning, such as an RSI or a normalised momentum reading. For best results, pick a signal that is not strongly correlated with the three built-ins, so the custom axis adds a new dimension rather than re-stating an existing one.
Enable only the alerts that fit your workflow. The band-crossover alerts fire once per transition , not on every bar inside a band.
🟠 LIMITATIONS
The pool holds every confirmed pivot during a matching-direction run, not only pivots that ended the trend. Intermediate pullbacks sit alongside genuine terminal pivots. Raising the zigzag pivot length filters the pool further if you want a cleaner sample.
On strongly trending symbols the pool is dominated by pullback pivots rather than true terminal exits, because strong trends have many small pullbacks and only one final top or bottom. On choppy symbols the ratio is more balanced. Read the score with this in mind.
The blended score is a density-match measure, not a forward probability . A high reading means today's context is common among past pivots of this direction. It does not predict that the trend is about to end.
The time-of-day axis has no meaning on daily and higher timeframes and is disabled automatically on those timeframes. A warning banner confirms when this is active.
The custom axis requires a source already scaled to 0–100 on every loaded bar. Values outside that range disable the axis and surface a warning. Toggling the custom axis on a live chart starts the range check from the current bar; reload the chart to validate against full loaded history .
Pools are capped at 2000 entries per direction , with the oldest entries dropped first. On very long intraday histories the effective lookback is symbol- and timeframe-dependent.
All scoring uses data up to and including the confirmation bar of each pivot; pivots themselves are detected with the standard zigzag confirmation lag, meaning the scoring population on any given bar reflects pivots confirmed at least zzLen bars earlier.
🟠 CONCLUSION
SuperTrend Take-Profit Dimensions combines a standard SuperTrend with a rolling pool of historical pivot contexts and scores the current bar against that pool across up to four independent axes spanning volume, time, and price. The output is a blended 0–100 favourability reading , a per-axis breakdown, and a set of context profiles that show where past pivots have clustered. It gives trend followers a structured, data-backed way to judge when the current context matches where trends have historically given back profit, without pretending to predict the next bar. Indicator
Flag Breakout Forecasts [AlgoAlpha]🟠 OVERVIEW
This indicator detects converging price channels — commonly called flags or wedges — directly on the chart using a zigzag-based pivot detection algorithm. It identifies three collinear pivot points on both the highs and the lows to confirm a valid channel, then monitors the channel in real time for a breakout.
Beyond just drawing the channel, the script assigns probabilistic forecasts to each active pattern. It uses the historical distribution of past breakout durations and directions to estimate the likelihood of an imminent breakout, whether that breakout will be bullish or bearish, and adjusts those estimates using live volume data accumulated inside the pattern.
A supplemental volume table and a net-volume gauge render alongside each detected pattern, giving traders a second lens into the supply-and-demand balance before a move resolves.
🟠 CONCEPTS
Zigzag — A filtered sequence of alternating swing highs and swing lows. Pivots are confirmed only after a user defined bars on each side, so shorter user defined values capture minor swings and larger values require more significant price moves.
Collinearity check — Given three pivot points, the script projects a straight line from the first to the third and measures how far the middle pivot deviates from it, expressed as a percentage of price. If the deviation falls below the tolerance threshold, the three pivots are treated as lying on the same trendline.
Converging channel — A pair of trendlines (one through swing highs, one through swing lows) where the gap between them narrows from left to right. This geometry distinguishes flags and symmetric wedges from parallel channels.
Early detection — When one trendline is confirmed but the other lacks a third pivot, the script uses the current running extreme (an unconfirmed potential pivot) as a temporary third point. The resulting line is drawn dashed and upgrades to solid when the pivot is confirmed.
Breakout confirmation — A break is logged after the close exits the projected channel boundary for two consecutive bars, or immediately when the breakout candle body extends well beyond the boundary and its body size is at least 3 standard deviations above the 20-bar mean body length.
Normal CDF approximation — Breakout duration probabilities are derived using the Abramowitz and Stegun rational approximation to the standard normal cumulative distribution function, applied to z-scores computed from the historical distribution of past breakout durations.
Net volume ratio — Bullish volume (up-close bars) minus bearish volume (down-close bars), divided by total volume, mapped to a −100 to +100 scale. Used to tilt the directional probability estimate away from the purely historical base rate.
🟠 FEATURES
Automatic channel detection — Channels are drawn the moment three collinear pivots are confirmed on each side with matching alignment and convergence.
• Solid lines for fully confirmed channels.
• Dashed lines for the side that is still waiting on a third confirmed pivot.
Probabilistic overlay label — Displayed above each active channel.
• P(break): probability that a breakout will occur soon, based on how the current pattern duration compares to historical durations.
• P(bull) / P(bear): directional probabilities derived from historical breakout directions and blended with live net volume.
Net volume gauge — A color-gradient vertical bar drawn to the right of the last candle, with a pointer showing whether up-close or down-close volume dominates the current pattern.
Volume statistics table — Shows bullish volume, bearish volume, net volume, total volume, ATR, and pattern duration for the most recent active pattern. Cell background intensity scales with volume magnitude.
Breakout signals — Arrow labels mark the breakout bar with the direction, total volume absorbed, and the number of bars the pattern lasted.
Background highlight — A subtle background color appears on the bar when a new pattern is first detected. To help users know the exact time the pattern was detected
🟠 HOW TO USE
Adjust len to match the swings you trade — lower values (3–5) for intraday patterns, higher values (10–20) for swing or position setups.
Tighten collinearity tolerance to 0.1–0.2% if you want only very clean trendline alignments; loosen it toward 1% if you want the indicator to catch more approximate formations.
Watch the dashed channel side — it signals an early, unconfirmed pattern. Treat it as a warning rather than a confirmed setup, and wait for it to turn solid before acting.
Check P(break) in the label — a reading above 70% means the current pattern has already lasted longer than most historical patterns, suggesting a resolution is statistically overdue.
Use P(bull) and P(bear) alongside the volume gauge — when P(bull) is elevated and the gauge leans bullish, the two signals agree on direction. Disagreement between them calls for extra caution.
Reference the volume table's net row — persistently positive net volume during a bearish-looking wedge can indicate absorption of selling pressure and a possible upside resolution.
Set alerts for "Pattern formed," "Bullish breakout," "Bearish breakout," and the strong-break variants to monitor multiple instruments without watching the chart continuously.
🟠 CONCLUSION
Flag Breakout Forecasts detects converging price channels using zigzag pivot collinearity and geometric validation, then layers on probabilistic duration and direction estimates derived from each instrument's own historical breakout data. The result is a self-calibrating pattern tool that combines structural chart analysis, volume profiling, and statistical inference in a single overlay. Indicator
Dynamic Median Momentum Oscillator [AlgoAlpha]🟠 OVERVIEW
This script provides a momentum oscillator that uses a median-based approach rather than traditional averages to find the center of price action. By calculating the distance between the current price and a rolling median (HLC3), it identifies how far the market has stretched from its historical equilibrium. The indicator is designed to filter out the noise typical of standard momentum tools, using a standardized range calculation to provide fixed overbought and oversold zones. It helps traders identify trend strength, potential exhaustion, and mean reversion opportunities across different market conditions.
🟠 CONCEPTS
The core of this tool is the Dynamic Median basis, which uses a rolling median of the HLC3 price to establish a "fair value" line. Unlike a simple moving average, the median is less sensitive to extreme price spikes, making the resulting oscillator more robust against outliers. To ensure the oscillator remains readable across different assets, the raw difference between price and median is standardized by the average candle range (EMA of High-Low). This normalization allows for the use of fixed thresholds (e.g., +/- 200, 250, 300) regardless of the asset's price. The median sets the context for the baseline, while the smoothed MCD and its signal line provide the timing for entries and exits.
🟠 FEATURES
Standardization feature to enable fixed overbought/oversold levels across any asset
Multi-component display: Fast (histogram), Slow (lines), and Super Slow (filled zones)
Reversion markers (triangles) indicating price returning from extreme levels
🟠 USAGE
Setup : Add the script to your chart and choose your preferred Display Mode. Use "All" to see the full picture or "Slow" for a cleaner view of trend direction. Ensure "Standardize" is checked if you want to use the built-in overbought/oversold bands effectively.
Read the chart : Look for the Smooth MCD (white line) crossing the Signal (orange line) for momentum shifts. Values above 0 indicate bullish momentum, while values below 0 indicate bearish momentum. Triangles appear at the top or bottom of the oscillator when price reaches extreme levels (300/-300) and begins to revert to the mean.
Settings that matter : The Basis Length determines how much historical data defines the "center" of the market; longer lengths are better for higher timeframes. Smoothing Length controls the reactivity of the main white line—increase this if you find the oscillator is giving too many false signals in choppy markets.
Indicator
Money Flow Divergence Zones [AlgoAlpha]🟠 OVERVIEW
This script identifies key price levels where volume and momentum show significant disagreement, visualizing these areas as Money Flow Liquidity Zones. By tracking the Money Flow Index (MFI) and its relationship to price action, the tool detects regular divergences that often precede market reversals. When a divergence is confirmed, the script projects a horizontal zone onto the chart based on the recent price extreme. These zones act as "liquidity pockets" that remain active until price successfully mitigates them through a wick or body cross, providing a clear map of potential support and resistance derived from volume-weighted momentum.
🟠 CONCEPTS
The core logic relies on the interaction between a smoothed MFI and pivot-based price extremes. While price might make a lower low, the MFI—calculated from $hlc3$ and volume—might make a higher low, signaling that selling pressure is exhausting despite the price drop. This script uses these divergences to set the initial context for a zone. The zones are then refined using a "Body vs Wick" logic, where the zone's depth is defined by the distance between the absolute high/low and the candle body. The MFI smoothing via a Hull Moving Average (HMA) ensures that the momentum signals are responsive yet filtered for high-frequency noise.
🟠 FEATURES
Dynamic Liquidity Zones : Automatically draws and extends support/resistance zones based on MFI divergence.
Divergence Engine : Detects regular bullish and bearish divergences with adjustable pivot lookbacks.
Visual Momentum Oscillator : Features a color-coded, smoothed MFI with a gradient midline to show volume strength.
Touch Signals : Small triangles appear when price interacts with an active zone while momentum aligns.
🟠 USAGE
Setup : Add the script to your chart. It is effective on most timeframes, but for intraday trading, the default 14-period MFI works well on 5m to 15m charts. Adjust the "Pivot Lookback" to fine-tune how sensitive the divergence detection is to local peaks.
Read the chart : Green zones represent bullish liquidity (potential support), while red zones represent bearish liquidity (potential resistance). Look for "▲" or "▼" symbols on the bars; these indicate price is currently touching a zone and might be ready for a reversal. The oscillator at the bottom confirms the trend: green for rising money flow and red for falling.
Settings that matter : The Sweep Type is critical—switching to "wick" will make zones disappear more easily (conservative), while "body" keeps zones active until a candle closes through them (aggressive). The Max Zone Age prevents old, irrelevant levels from cluttering your chart by removing them after a set number of bars.
Indicator
Indicator
HTF Volume Liquidity Profile [AlgoAlpha]🟠 OVERVIEW
This tool projects a volume profile from a higher timeframe directly onto your current chart. By breaking down historical price action into vertical intervals, it creates a heatmap of where volume was concentrated during that larger period. It maps out areas of high liquidity, showing exactly where buyers and sellers were most active, and displays a detailed breakdown of bullish versus bearish volume at specific price levels within that higher timeframe block.
🟠 CONCEPTS
This script takes that concept and applies it to a higher timeframe, meaning you can look at a 5-minute chart and see the volume distribution for the entire day overlaid as a single block. It calculates the highest and lowest prices of the chosen timeframe and divides that range into smaller segments based on your resolution setting. It then tallies the volume of every lower timeframe candle that falls into each segment. It also splits this volume into positive and negative flows based on whether the individual candles closed green or red. This gives you a clear picture of net directional pressure at each price level, acting like a lightweight footprint chart.
🟠 FEATURES
Higher timeframe volume heatmap overlaid directly on the current lower timeframe chart.
Inner mini-boxes showing the exact proportion of bullish (green) vs bearish (red) volume at each specific price level.
Summary label displaying total up volume, down volume, volume delta, and overall sentiment for the entire interval.
🟠 USAGE
Setup : Add the script to your chart. Choose a higher timeframe that makes sense for your trading style (for example, use 1D if you are trading on a 5-minute or 15-minute chart). Adjust the resolution depending on how granular you want the price levels to be.
Read the chart : Darker, more opaque background boxes mean a high amount of total volume was traded at that price level (High Volume Nodes). The inner mini-boxes show the tug-of-war at that level; a longer green inner box means buyers dominated that specific price, while a longer red one means sellers dominated. The label at the bottom of each block summarizes the total volume delta so you instantly know who won the overall period.
Settings that matter : The Higher TimeFrame input dictates the width and duration of each volume profile block. The Profile Resolution input controls how many vertical slices the price range is divided into; increasing this adds finer detail but can visually clutter the chart if set too high.
Indicator
Breakout Targets [AlgoAlpha]🟠 OVERVIEW
This script identifies consolidation zones and provides automated breakout targets with risk management levels. It focuses on finding periods where price action compresses and then tracks the subsequent breakout from these ranges. When a price breakout is confirmed, the script automatically projects three take-profit (TP) levels and a stop-loss (SL) based on current market volatility. This helps traders move from identifying a range to executing a trade with predefined exit points without manual calculation.
🟠 CONCEPTS
The script uses a relationship between Weighted Moving Averages (WMA) and Exponential Moving Averages (EMA) of price ranges to detect consolidation. When these moving averages cross, it triggers the detection of recent pivot highs and lows to draw a visual "box" or channel. This channel represents the current trading range. Once price closes outside this box, the script uses the Average True Range (ATR) to determine the volatility-adjusted distance for the stop loss. The take-profit levels are then calculated as multiples of this risk distance, ensuring a consistent reward-to-risk approach.
🟠 FEATURES
Dynamic box drawing that highlights potential supply and demand zones within the range.
Real-time breakout signals with bullish (green) and bearish (red) markers.
Automated trade projection including Entry, SL, and three TP levels.
Integrated alert system for breakouts and hits on any profit or loss target.
🟠 USAGE
Setup : Add the script to your chart and adjust the "Range Detection Period." A higher period will find larger, more significant ranges, while a lower period will find smaller, short-term consolidation zones.
Read the chart : Look for the grey boxes on your chart; these represent areas where the market is "coiling." A green arrow label indicates a bullish breakout from the top of the box, while a red arrow indicates a bearish breakout from the bottom. Once a breakout occurs, follow the projected horizontal levels for your trade management.
Settings that matter : The Stop Loss ATR Multiplier is the most critical setting for risk; increasing it will give the trade more room to breathe but will also push your TP levels further away. The Prevent Overlap toggle is useful for keeping the chart clean by ensuring the script doesn't draw new boxes until the current range has been resolved.
Indicator
Breaker Blocks Signals [AlgoAlpha]🟠 OVERVIEW
This script automates the detection of Breaker Blocks, a popular smart money concept used to identify high-probability reversal zones. It monitors price action for aggressive impulses—measured through a normalized Z-Score—to identify Orderblocks. When these blocks are "broken" or invalidated by price moving through them, they transform into Breaker Blocks. These zones act as "flipped" support or resistance, offering traders specific areas to look for retests and trend continuations. By handling the complex management of zone life-cycles and mitigation, this script provides a clean, real-time map of institutional supply and demand shifts.
🟠 CONCEPTS
The indicator relies on the relationship between price momentum and structural invalidation. It first identifies "impulsive" candles by calculating a Z-Score of price distance covered over a specific window. A Z-Score above 4 marks an "Algorithmically Significant" move. When such a move occurs, the script identifies the last opposite-colored candle (the Orderblock) and draws a gray zone. The transformation happens when price closes entirely through one of these gray zones. This "mitigation" is what triggers the creation of a Breaker Block: an old bearish supply zone becomes a bullish demand zone, and vice versa. This transition reflects a shift in market regime where previous trapped participants are forced to exit, often leading to price rejections at these newly formed levels.
🟠 FEATURES
Automated Breaker Transformation : Instantly flips mitigated Orderblocks into colored Breaker Blocks (Bullish/Bearish).
Rejection Markers : Small arrow icons appear when price enters a Breaker Block and shows signs of respect/reversal.
Comprehensive Alerts : Notifications for both the formation of new breakers and real-time price rejections.
🟠 USAGE
Setup : Add the script to your chart. It is effective on most timeframes, but many traders prefer the 15m or 1h for intraday structure. Use the "Z-Score Window" to adjust sensitivity; 100 is standard, but lower values (e.g., 50) will find more frequent, smaller impulses.
Read the chart : Gray boxes are "Pending" blocks. If price closes above a gray bearish box, it turns into a Bullish Breaker (Green). If price closes below a gray bullish box, it turns into a Bearish Breaker (Red). Look for price to return to these colored zones; the "▲" and "▼" symbols indicate the script has detected a rejection from that level.
Settings that matter : Prevent Overlap is useful for avoiding "cluttered" zones in ranging markets. Max Box Age is critical; it ensures that very old, irrelevant zones are removed from your chart after a set number of bars, keeping your technical analysis current and focused on recent price action.
Indicator
Indicator
