Stop Loss Optimizer Engine [AGPro Series]Stop Loss Optimizer Engine
🔹 OVERVIEW
Stop Loss Optimizer Engine compares four independent stop-loss methodologies side by side on a single chart, so traders can see at a glance where each approach would place protection and which one has historically held up best on the current symbol and timeframe. Every method is calculated for both LONG and SHORT, giving eight reference levels plus a compact panel with distance-to-price and a historical hold-rate statistic per method. A Risk Zone highlights the area between current price and the method with the strongest historical hold-rate, providing a clean S/R-style visual anchor for position sizing and R-multiple planning.
🔹 UNIQUE EDGE
Most stop-loss indicators on the platform commit to a single philosophy — pure ATR, pure Chandelier, or pure structure. Traders who want to compare approaches end up loading multiple scripts and eyeballing the differences. Stop Loss Optimizer Engine is built around a different premise: volatility, structure, trailing and recent-extreme stops each have environments in which they work well, and the trader should decide based on evidence rather than habit. The indicator renders all four on one chart, adds a per-method hold-rate measured on the active instrument, and flags the highest-hold-rate method with a star marker so the comparison is always a single glance away. The Risk Zone is drawn using the current-best method, which means the visual anchor adapts to whichever approach is statistically holding up best on that symbol and timeframe right now.
🔹 METHODOLOGY
The four engines are independent and each produces a LONG and a SHORT level:
ATR-SL — close minus or plus ATR × multiplier. Volatility-adaptive, widens in turbulent markets, tightens in calm ones.
Pivot-SL — the most recent confirmed pivot low or pivot high. Respects market structure, places the stop beyond the last reversal point rather than at an arithmetic distance.
Chandelier-SL — highest high minus ATR × multiplier for LONG, lowest low plus ATR × multiplier for SHORT. The classic Le Beau / Elder trailing stop, designed to follow strong trends without premature exits.
Swing-SL — the lowest low or highest high over a short lookback. A simple, robust baseline that works well for shorter trades and scalping.
Hold Rate — for every historical bar in the lookback window, the indicator records the SL level that each method would have produced at that bar, then checks whether price breached that level within a fixed forward window. Hold Rate is the percentage of evaluated bars in which the SL was not breached. This is a pure historical observation, not a forward performance projection.
🔹 SIGNALS & ALERTS
Visual — dotted lines for LONG stops (plotted below price), dashed lines for SHORT stops (plotted above price). Each method uses a distinct color. Labels sit at the right edge of each line with the method name and exact price. A dedicated anti-overlap resolver repositions labels vertically whenever two or more methods produce near-identical levels, so the rightmost chart panel stays readable in tight clusters.
Risk Zone — a shaded rectangle between current close and the highest-hold-rate SL on the trend-dominant side, extending forward from the current bar. Color matches the selected best method.
Panel — four-column layout showing method, LONG price (and distance %), SHORT price (and distance %), and Hold Rate, with a star marker beside the method currently holding the highest rate. A trend footer reports Bullish or Bearish based on the EMA50 filter.
Alerts — four pre-configured conditions for price breaching the ATR and Chandelier SL levels on either side.
🔹 KEY INPUTS
Method toggles for each of the four engines. Length and multiplier inputs per method, with balanced defaults (ATR 1.5× / 14, Pivot length 5, Chandelier 2.5× / 22, Swing lookback 7). Hold-rate statistics lookback and forward window, defaulting to 1000 and 10 bars. Visual controls for long-side lines, short-side lines, labels, the Risk Zone and a trend-based dimming of the counter-trend side. Panel location (six positions), panel theme (Dark or Light), and adjustable font sizes for panel and labels, all defaulting to Normal.
🔹 HOW TO USE
Open the indicator on any symbol and any timeframe. Read the panel first — the starred method is the one with the best historical hold-rate on the current chart. Pick a method that matches the trade plan: ATR for volatility-aware scalps, Pivot for structural setups, Chandelier for trend-following swings, Swing for simple quick trades. Use the Hold Rate column as secondary evidence, not as a standalone forecast. Read the SL price and the distance percentage next to it to size position accordingly — a 2% stop and a 6% stop are not the same trade, even on the same entry. The Risk Zone is a convenience visual for the trend-dominant side and should be interpreted together with the other levels, not in isolation.
🔹 LIMITATIONS & TRANSPARENCY
Hold Rate is a backward-looking statistic computed on historical bars of the active chart. It describes what would have happened under a fixed forward-window assumption on past data and does not guarantee any future behavior. The forward-window length, lookback size and method parameters all influence the resulting numbers; changing inputs changes the statistic. The Pivot-SL method depends on the availability of confirmed pivots in the lookback window and will fall back to a conservative ATR-based placeholder when a pivot is not yet confirmed. Risk Zone selection is based on hold-rate ranking, which can switch between methods as markets evolve. This script is a decision-support tool for discretionary risk management, not a trade-entry signal generator. Always combine with independent analysis and sound position sizing. Past performance of any stop-loss method does not guarantee future results.
🔒 RISK DISCLOSURE
This script is provided for educational and informational purposes only. It is not financial, investment or trading advice. Trading involves substantial risk of loss; use at your own discretion and risk. Indicator
Risk Reward Visualizer [AGPro Series]Risk Reward Visualizer
🔹 Overview
Risk Reward Visualizer is a professional trade-planning indicator that transforms every setup into a clean visual framework: entry, stop-loss, and up to three take-profit targets displayed as long rectangular R-multiple zones. Beyond basic visualization, it adds three features rarely found together in one tool — a breakeven probability calculator, live MFE/MAE excursion tracking, and an automatic trail-to-breakeven workflow.
The indicator is built for traders who think in R-multiples: swing traders, prop-firm candidates, day traders, and anyone who wants to answer the question "does this setup actually make mathematical sense?" before committing capital.
🔹 What Makes It Different
Most risk/reward scripts stop at drawing levels and a position-size table. This one goes further:
• Breakeven Probability Math — For every R target, the panel displays the minimum win rate required to break even, adjusted for round-trip fees. A 3R target needs only 25% wins; a 1R target needs 50%. Seeing this side-by-side reframes how you evaluate setups.
• Live MFE / MAE Tracking — Maximum Favorable Excursion and Maximum Adverse Excursion are tracked in real time from the moment the setup becomes valid. Labels mark the exact bar of each peak in R-multiples, with leader lines connecting the label to the wick, so you can grade trade quality after the fact.
• Trail-to-Breakeven Visualization — When TP1 is hit, the original stop fades and a new breakeven line is drawn at entry, making the risk management discipline visible on the chart.
• Hybrid Auto-Detect — Leave Entry and Stop at zero and the script fills them using the current close and the most recent swing pivot plus an ATR buffer. Provide one manually and the other auto-completes. Everything can be overridden.
🔹 Methodology
Levels are calculated from the standard R-multiple framework:
• Risk per unit = |Entry − Stop|
• Take-profit N = Entry ± (N × Risk per unit), signed by trade direction
• Breakeven win rate = (1 + fees_R) / (1 + R target)
Direction is auto-inferred from the relationship between Entry and Stop (Long when Stop is below Entry, Short otherwise), and can be forced. Auto-detect uses a pivot lookback to locate the most recent swing high or low, then offsets the stop by a user-defined ATR multiple to reduce wick-out risk.
MFE and MAE reset whenever Entry or Stop changes, so editing inputs restarts tracking cleanly. Hit detection uses bar high or low against each level and fires alerts only on the rising edge of each event.
🔹 Visuals & Signals
• Risk zone rendered as a pink rectangle between Entry and Stop
• TP1, TP2 and TP3 zones rendered as stacked teal rectangles with graded opacity
• Entry line in indigo, stop in pink, take-profits in teal
• Labels anchor to the right edge of the zone so they never hide candles
• MFE label on the favorable excursion peak, MAE on the adverse peak, each offset 1.5 ATR with a dotted leader line
• Alerts: TP1 hit, TP2 hit, TP3 hit, Stop Loss hit, Breakeven reached
🔹 Key Inputs
• Setup Mode — Manual, Auto-Detect, or Hybrid
• Trade Side — Auto, Long, or Short
• Entry and Stop — leave at zero to auto-detect
• Swing Lookback and ATR Buffer — for auto-detected stops
• TP1, TP2, TP3 multipliers with individual show/hide toggles
• Trail Stop to Breakeven After TP1 — toggle
• Round-Trip Fees (%) — folded into breakeven math
• Enable Position Size Calculator — optional; account size and risk percentage
• Panel location, panel font size, label font size, zone length, zone transparency
🔹 How To Use
Step 1 — Add the script to any symbol and timeframe. By default, Hybrid mode uses the current close as entry and the most recent swing plus an ATR buffer as stop.
Step 2 — Override Entry or Stop with your planned levels if you have a specific setup in mind.
Step 3 — Check the Breakeven Analysis section of the panel. Confirm the minimum win rate required for your chosen R target is realistic for your strategy.
Step 4 — Set alerts for the targets you want to be notified on. If Trail-to-Breakeven is enabled, you will also receive a notification when TP1 hits so you can move your stop in your broker.
Step 5 — After the trade, review MFE and MAE to grade execution. Did price reach favorable excursion that you missed? Did it dip deep into risk before resolving?
🔹 Limitations & Transparency
• This is a planning and visualization tool. It does not place orders and does not produce buy or sell signals.
• The breakeven calculation treats fees as a percentage of entry price converted into R-units. It is a useful approximation, not a tax or slippage model.
• Auto-detected stops depend on recent swing structure. On very low-liquidity symbols or during strong trends without pullbacks, recent swings may be stale. Verify visually before using.
• MFE and MAE tracking uses bar high or low and resets when inputs change.
• Position sizing assumes a linear contract value and does not account for margin, leverage, or instrument-specific tick rules. Always cross-check with your broker.
🔹 Risk Disclosure
Trading carries risk of loss. This indicator is provided for educational and analytical purposes only and is not financial advice. Past behavior of any tool does not guarantee future performance. Use proper position sizing and never risk more than you can afford to lose. Indicator
Indicator
AG Pro Stop Hunt Map Engine [AGPro Series]AG Pro Stop Hunt Map Engine
Overview / What it does
AG Pro Stop Hunt Map Engine is a price-action overlay designed to map potential trap zones after liquidity sweeps. The script focuses on moments where price briefly moves beyond an important reference level, rejects that move, and then closes back through the swept area. In practical terms, this helps traders visualize where a failed breakout or failed breakdown may have left trapped positioning behind.
The engine can work with pivot-based liquidity references, previous day high / previous day low references, or both at the same time. This makes it useful for traders who want a structured way to monitor classic stop-hunt behavior without relying on a single interpretation of liquidity. Instead of treating every wick beyond a level as meaningful, the script applies reclaim logic and filtering rules so that only sweeps with stronger reversal characteristics are highlighted.
The core goal is not to predict every reversal. The goal is to organize sweep events into a readable map: where the sweep happened, which side may be trapped, which zones remain active, and which levels are still relevant as price moves forward. That is why the script is built as a map engine rather than a simple marker tool.
This publication is especially suited to traders who study rejection structure, failed continuation, stop runs, and liquidity-driven reversals. It can be used as a visual context layer inside a broader workflow that may already include structure, trend, momentum, or higher-timeframe bias analysis.
Unique Edge
Many liquidity-sweep tools only mark a wick beyond a prior level and stop there. This script takes a more selective approach. It requires a reclaim condition, supports wick-to-body quality filtering, allows optional fake-sweep filtering, and maintains the resulting event as an actionable mapped zone rather than a one-bar marker.
Its main differentiation is the emphasis on post-sweep structure. Once a sweep qualifies, the script builds and extends a zone so the trader can continue monitoring that area after the original event. This provides a cleaner framework for seeing whether the market is respecting that trap region, moving away from it, or invalidating it.
Another important distinction is the visual hierarchy. The script is designed to separate nearest relevant zones from older or weaker context. This helps keep the chart readable while still preserving useful background information. Instead of cluttering the screen with every historical event at equal importance, the engine highlights what is currently closest and most relevant.
Methodology
The script first defines the liquidity source. Users can choose pivot highs and lows, previous day high and previous day low, or a combined mode that monitors both.
For a bullish trap scenario, price must sweep below a valid downside reference and then reclaim it according to the selected conditions. For a bearish trap scenario, price must sweep above a valid upside reference and then reclaim it. This creates two independent directional engines: one for bullish recovery after downside liquidity is taken, and one for bearish rejection after upside liquidity is taken.
The detection logic is built around several layers:
1. Sweep source selection
The engine checks whether price has moved beyond a chosen pivot or previous-day level.
2. Wick / body filter
The script can require a minimum wick-to-body relationship so that weak or low-conviction candles are filtered out.
3. Reclaim close requirement
The user can require price to close back through the swept level before the event is accepted.
4. Fake sweep filter
An optional penetration filter limits how deep price can move beyond the level before the event is treated as lower quality.
5. Zone persistence
Qualified sweep-and-reclaim events are not left as isolated markers. They are stored and extended forward as zones so the trader can monitor their ongoing relevance.
6. Nearest-zone emphasis
The display engine highlights the nearest bull and bear trap zones so current context is easier to read.
The result is a framework that treats sweep events as evolving market context rather than isolated historical dots.
Signals & Alerts
The script identifies two primary event types:
Bull Trap Reclaim
This appears when price sweeps below a valid reference level and then closes back above it, suggesting that downside liquidity may have been taken and rejected.
Bear Trap Reclaim
This appears when price sweeps above a valid reference level and then closes back below it, suggesting that upside liquidity may have been taken and rejected.
Visual elements can include:
- Sweep zones
- Trap labels
- Right-edge state tags
- Nearest-zone emphasis
- Origin markers on qualifying sweep bars
- A summary panel showing current state and nearest bull / bear trap information
Alert conditions are included for:
- Bullish trap reclaim events
- Bearish trap reclaim events
These alerts are event-based. They identify when a qualifying reclaim occurs according to the active settings.
Key Inputs
Sweep Source
Choose whether the engine uses pivots, previous day levels, or both.
Pivot Strength
Controls how strict the pivot reference detection should be.
Require Reclaim Close
Requires price to close back through the swept level before a zone is created.
Min Wick / Body Ratio
Filters low-quality sweeps by requiring stronger rejection candles.
Use Fake Sweep Filter
Enables an additional penetration-depth filter to reduce weaker events.
Max Penetration (ATR Multiple)
Sets the maximum allowed overshoot beyond the swept level when fake-sweep filtering is enabled.
Chart Mode
Allows a cleaner publish-style view or a more detailed analysis-style view.
Label Mode
Controls how aggressively labels are shown on the chart.
Highlight Nearest Bull / Bear Zones
Emphasizes the closest active zones for faster visual interpretation.
Summary Panel
Shows the current trap state, active bull and bear zone counts, nearest trap levels, and the last detected events.
Limitations & Transparency
This script is not a prediction engine and does not guarantee reversals. A sweep-and-reclaim event can still fail, especially in strong directional environments where price continues expanding after a temporary rejection.
Reference choice matters. Pivot-based detection and previous-day level detection describe different types of liquidity behavior. Depending on the instrument, timeframe, and volatility regime, one source may be more relevant than the other.
Filtering also changes behavior significantly. Tight wick/body requirements or stricter fake-sweep settings will reduce signal frequency. Looser settings will create more events but may also admit weaker structures.
Zones are contextual tools, not standalone trade instructions. Many traders may still want to combine the script with higher-timeframe structure, trend bias, volatility context, or execution rules before making decisions.
As with any chart overlay, visual cleanliness depends on timeframe, market conditions, and user configuration. Different settings may be appropriate for intraday charts versus higher-timeframe swing charts.
Risk Disclosure
This script is for chart analysis and market structure visualization only. It does not provide financial advice, trade recommendations, or guaranteed outcomes. Markets can remain irrational longer than a trap setup appears logical, and any liquidity sweep signal can fail.
Always apply independent judgment, position sizing discipline, and risk management. No single indicator should be used in isolation for live trading decisions.
Indicator
AG Pro Liquidity Sweep Quality [AGPro Series]AG Pro Liquidity Sweep Quality
OVERVIEW / WHAT IT DOES
AG Pro Liquidity Sweep Quality is a pivot-based overlay designed to map bullish and bearish liquidity sweep events around confirmed swing highs and swing lows. Instead of only flagging whether price traded beyond a prior level, the script evaluates whether that move behaved like a meaningful rejection or a weak sweep. The result is a structured liquidity sweep indicator that focuses on sweep quality, not only sweep detection.
In practical terms, the script looks for price moving above a prior swing high or below a prior swing low and then closing back through that level on the same bar or, if enabled, on the next bar. This behavior is commonly associated with stop hunts, failed breakout attempts, failed breakdown attempts, and short-term rejection events around visible liquidity. The script then ranks the event using a multi-factor quality model so the chart does not treat every sweep as equally important.
This makes the tool relevant for traders studying liquidity sweep behavior, smart money concepts, ICT-style chart reading, rejection anatomy, wick-driven reversals, sweep confirmation, and swing-based context. It is not built to predict direction on its own. It is built to organize sweep events so users can distinguish weaker noise from stronger rejection structures.
UNIQUE EDGE
The main objective of this script is not to publish another generic liquidity grab marker. Its edge comes from the fact that it scores each confirmed sweep using a quality framework. That framework combines how deeply price traded through the level, how decisively it closed back beyond the level, the wick-to-body relationship of the sweep bar, relative volume behavior, swing freshness, nearby swing crowding, and optional higher-timeframe bias alignment.
This matters because many sweep-style tools stop at a binary answer:
sweep happened / sweep did not happen.
This script asks a more useful follow-up question:
how good was that sweep?
That distinction is important on real charts. Some liquidity sweeps show strong rejection, clean close-back behavior, fresh structure, and supportive context. Others are simply noisy level violations inside a crowded area. By assigning a quality score, the script is designed to help users compare sweep events with more nuance.
Another distinguishing feature is that the script separates watch conditions from qualified conditions. A level can first be challenged, then either reclaim cleanly or fail to reclaim. This helps reduce the tendency to treat every level breach as a reversal event.
METHODOLOGY
1) SWING DETECTION
The script uses confirmed pivot highs and confirmed pivot lows as its structural reference points. These pivots are not assumed in advance. They become available only after the user-defined Pivot Strength confirmation process is complete.
2) SWEEP TRIGGER
A bearish sweep scenario begins when price trades above a stored swing high.
A bullish sweep scenario begins when price trades below a stored swing low.
3) QUALIFICATION
A sweep is considered qualified when price closes back through the swept level. By default, the script can evaluate same-bar reclaim behavior and, optionally, next-bar reclaim behavior.
4) QUALITY MODEL
Each qualified sweep is scored using multiple factors, including:
- penetration relative to ATR
- rejection distance back through the level
- wick-to-body ratio
- relative volume versus a recent baseline
- freshness of the swing level
- nearby level crowding penalty
- optional higher-timeframe trend alignment bonus
The final output is normalized into a simple 1 to 10 quality score so chart reading remains fast and visually clean.
5) VISUAL MAPPING
Qualified sweeps can display:
- direction label
- quality score label
- sweep zone box
- dashed memory line at the swept level
- optional chart background tint
- compact minor markers for lower-priority qualified sweeps
This allows the chart to remain informative without forcing every event to carry the same visual weight.
SIGNALS & ALERTS
The script includes deterministic alert conditions for:
- Bull Sweep Trigger
- Bear Sweep Trigger
- Bull Sweep Qualified
- Bear Sweep Qualified
- High Quality Bull Sweep
- High Quality Bear Sweep
A trigger means price challenged the stored liquidity level.
A qualified sweep means price also reclaimed the level according to the script rules.
A high-quality sweep means the final score exceeded the selected threshold.
These states are intended to help users organize workflow and review price behavior. They are not instructions to buy or sell.
KEY INPUTS
Pivot Strength
Controls how swings are confirmed. Higher values generally reduce noise but also make structural detection slower and more selective.
Max Swing Age
Limits how long old swing levels remain eligible. This helps keep the liquidity map focused on fresher structure.
Allow Next-Bar Reclaim
Allows the script to qualify a sweep when the reclaim happens on the next bar instead of only the sweep bar itself.
ATR Length
Used in the quality engine to normalize sweep depth and rejection distance.
Relative Volume Length
Defines the baseline used for volume comparison.
Crowding Width (ATR)
Helps penalize sweeps occurring in dense structural clusters, where nearby levels can reduce interpretive clarity.
Higher Timeframe and HTF EMA Length
Used to build an optional bias filter so aligned sweeps can receive a context bonus.
Min Score For Full Labels
Lets users keep high-information labels on stronger sweeps while weaker qualified sweeps can remain as compact markers.
Same-Side Full Label Cooldown
Reduces repeated full labels in the same direction over a short span, improving chart readability.
LIMITATIONS & TRANSPARENCY
This script is a chart-organization tool, not a stand-alone decision engine.
Because the logic is pivot-based, swing levels are only confirmed after the chosen Pivot Strength delay. That means the structural reference points are confirmed swings, not instantly-known highs or lows.
A liquidity sweep on one market, timeframe, or volatility regime may not behave the same way on another. The scoring framework is designed to rank events relative to the script's own rules, not to certify that a sweep will lead to reversal or continuation.
Higher relative volume may improve context, but volume confirmation does not guarantee outcome quality.
The higher-timeframe alignment feature is a contextual filter. It should not be interpreted as a macro trend forecast.
Like any visual overlay, this tool can produce signals in choppy or highly reactive conditions that later prove less useful than they first appeared. Parameter selection matters.
WHAT THIS SCRIPT IS NOT
This script is not a promise of reversal.
It is not a complete smart money framework.
It is not a substitute for execution planning, risk management, or broader market context.
It does not claim to detect institutional intent.
It does not classify every level break as tradable.
Instead, it focuses on one specific chart behavior:
sweep-and-reclaim quality around confirmed swing liquidity.
RISK DISCLOSURE
This indicator is for analytical and educational use only. It does not provide financial advice, investment advice, or guaranteed trade outcomes. Markets can remain irrational, trend aggressively, or ignore local sweep signals for extended periods. Users should validate any chart workflow with their own process, risk controls, and market understanding before acting on any signal or alert.
If you use this tool, it is generally best treated as a structural filter inside a broader workflow rather than as a stand-alone trigger.
AGPro Series note:
This publication is designed to emphasize structured chart reading, deterministic event definitions, and transparent methodology over promotional claims or outcome promises.
Indicator
Automate on Hyperliquid - Strategy Webhook Template [HYPR-run]DESCRIPTION
You define the entry signal. The system manages everything after the fill. This is a production-grade trade system for automating strategies on Hyperliquid using PulseWire webhooks. Five-level priority chain trade system. Four ATR trailing architectures including volume-weighted ATR with Efficiency Ratio scaling and ratchet floor. Smart stops that exit when a trade is invalidated. Pyramid scaling into winners and a redundant failsafe stop.
Three signal systems are included ready to backtest and deploy (EMA crossover, Turtle breakout, SFP - Swing Failure Pattern) that you can toggle on/off independently; replace or extend them with your own logic in three places: the input toggle, the signal condition, and the priority chain entry call. There are clear landmarks in the code to make it as straightforward as possible.
This strategy is built for you to hit the ground running backtesting or automating with a systematic framework to execute around your entry logic or the example signals provided. All signals fire on confirmed bar closes only. Entries, exits, pyramids, and stops are evaluated at close, not during the bar, so intrabar wick spikes do not trigger the system. This is by design. No lookahead bias: all highest/lowest references use prior-bar offsets, LinReg is calculated with offset=1, and no security() calls are used. The script does not repaint or compound returns.
WHAT THE STRATEGY SYSTEMIZES
1. Five-Level Priority Action Chain
Entries fire first. Pyramids fire second and block exits on the same bar. Trailing exits ride winners. Smart stops catch failing trades early. Failsafe stop is the absolute floor. The if/else order is intentional and prevents conflicts so that every action occurs only when it should.
2. Four ATR Trailing Stop Modes
Select from a dropdown. All use separate long/short look backs and multipliers because drops are faster than rallies; the defaults reflect this asymmetry.
• A3.1: LinReg + plain ATR, no ratchet. Baseline for comparison.
• A4.0 (default): LinReg + volume-weighted ATR + Efficiency Ratio + ratchet. VWATR discounts low-volume bars. ER tightens in chop (0.8x), widens in trend (1.2x). Ratchet means the stop only moves in your favor.
• A4.1: Chandelier + VWATR + ratchet + first-bar multiplier for tighter initial protection.
• A4.2: LinReg + VWATR, no ratchet or ER. Stop moves freely with projection.
***The multipliers determine how much room the stop gives price before triggering. They have the greatest influence on overall system performance and must be tuned to the asset and timeframe being traded. Default values are a starting point, not final settings.
• L Multi: 4.0 (long stop distance). Wider because uptrends are slower and require more room.
• S Multi: 2.0 (short stop distance). Tighter because drops are faster and corrections are sharper.
• Long LB: 14 bars. ATR lookback for long stops.
• Short LB: 26 bars. ATR lookback for short stops; longer lookback smooths volatile short-side moves.
• LinReg LB: 10 bars. LinReg projection window (A3.1, A4.0, A4.2).
• First Bar Mult: 1.5x (A4.1 only). Tighter stop on the entry bar; expands to standard multiplier after.
3. Smart Stops
Two trigger paths, both requiring open P&L below threshold (default -3.5%): (1) price crosses under the trailing stop while losing, or (2) price breaks the entry bar’s structure while losing. Either path exits the trade before the failsafe would trigger. The P&L condition on both paths prevents exits on noise when the trade is still within normal range.
4. Pyramid Entries
Scales into winning trades on 5-bar extremes. Requires full bar confirmation and must be within 13 bars of the initial entry.
5. Basic Entry Quality Filters
Applied automatically to every entry:
• Wick nullification: bars with wicks > 38.2% of range block entries in that direction
• SFP nullification: active reversal patterns block opposing entries
• Full bar filter: candle body must be >= 66.6% of total range
• Bar confirmation: entries only fire on confirmed bars
THREE SIGNALS INCLUDED (replace or extend)
• XO/XU: EMA crossover with four configurable pairs (5/13, 9/26, 12/25, 26/128). Requires price above swing high (longs) or below swing low (shorts) plus volume spike (Dropdown Selection).
• Turtle: 13/26 bar breakout with Lost Trade System logic. First breakout after an opposing signal gets priority.
• SFP: Swing Failure Pattern. Longs fire on either 5/5 with full-body confirmation or 5/2 with bullish candle confirmation and strong volume spike (1.618x average). Shorts fire on 5/5 with full-body or 13/3 with bearish candle confirmation. Dual-path per direction allows the signal to catch both high-conviction structure failures and high-volume reversals. The function accepts any left/right look back combination, making it straightforward to adapt. (#/# refers to pivot look back left and right)
Each has its own toggle. Enable one, combine them, or swap in your own signals.
WEBHOOK AUTOMATION
Every fill event fires through PulseWire’s built-in webhook system when enabled: entries, exits, pyramids, smart stops, and failsafe closes. To execute those webhooks on Hyperliquid, an intermediary service (execution layer) that accepts PulseWire webhooks and routes orders to Hyperliquid's API is required.
Setup:
1. Create an alert on this strategy
2. Set trigger to "Order fills only"
3. Check Webhook URL, paste your endpoint
4. Message box: {"ticker":"{{ticker}}","position":"{{strategy.market_position}}"}
5. Set expiration to Open-ended
The snippet will most likely require customization depending on your execution layer. The {{ticker}} and {{strategy.market_position}} fields are PulseWire placeholders that auto-populate when a strategy signal fires.
We recommend referencing PulseWire’s Strategy Alerts documentation to fully understand placeholder use and function when setting up your snippet for your execution layer: www.pulsewire.com
BUILDING WITH YOUR OWN SIGNALS
The most straightforward path is adding your own entry logic. The ATR module, smart stops, and pyramids can also be edited to preferred logic while still leveraging the systemized structure for clean execution when automating on an exchange.
Option 1: Replace an existing signal. Find its section under the SIGNALS header (look for "EXAMPLE 1", "EXAMPLE 2", or "EXAMPLE 3"). Delete the example code and write your condition in its place. Find the matching entry in the STRATEGY CALLS priority chain and swap the condition variable. The toggle still works; rename its label in the input line. Everything downstream works automatically.
Option 2: Add a new signal. Three places to touch:
1. Copy a strategy toggle line from the STRATEGIES input group, change the variable name and label
2. Add your signal logic in the SIGNALS section as a boolean
3. Add an else-if block in the STRATEGY CALLS priority chain using your toggle as the gate
Two test switches (Tsw1, Tsw2) are reserved in Settings for custom signals.
READING THE CHART
Candles are colored by direction: black bodies up, gray bodies down (Quant Filter toggle).
The trailing stop draws as a colored line following your position: green below price when long, red/orange above price when short. A gradient fill shades the zone between price and the stop; it intensifies as price approaches the exit level.
Green dots on the long stop line and red dots on the short stop line are ratchet markers (A4.0 and A4.1 only). Each dot means the stop locked in a new level and will not pull back.
Entry labels appear at each fill: "xoL" (EMA long), "xuS" (EMA short), "tL" (Turtle long), "tS" (Turtle short), "sfpL"/"sfpS" (SFP entries), "pyrL"/"pyrS" (pyramid adds). Exit labels: "Cl"/"Cs" (trailing close long/short), "smrtstp" (smart stop), "fstp" (failsafe).
SFP candle wicks are color-coded by lookback: 5/5 bull wick = bright green, 5/2 bull wick = dark green, 5/5 bear wick = bright red, 13/3 bear wick = dark red. The shade tells you which configuration triggered — brighter means the more common 5/5 detection, darker means the secondary lookback fired.
Horizontal lines extending from entry price are the Late Entry Window: white solid line is entry price, green dashed line is entry + ATR window, red dashed line is entry - ATR window. Visual reference only; does not affect trade logic. Useful when away from the screen to quickly see if a missed entry is still within a safe ATR range.
Market structure labels (HH, LH, HL, LL) appear at swing pivots when the Structure toggle is enabled.
RISK MATH
Order size is fixed at $5,000 (50% of starting capital). That means it's always a flat $5k order, no compounding. With the failsafe at -5.25%, maximum loss per trade is $262.50, or 2.625% of the $10,000 starting balance.
*Because order size is fixed in dollars while equity grows, risk as a percentage of equity decreases over time: 2.625% at start, 2.1% at $12,500, 1.75% at $15,000. The smart stop triggers before the failsafe in most cases, reducing average realized loss further.
STRATEGY PROPERTIES (What's used in the chart published here)
Strategies (all off by default - toggle on to activate):
• XO/XU: on
• Turtle: on
• SFP: on
Settings:
• Mode: Historical (switch to Bot Mode for live automation - limits calculation depth for speed)
• EMA Pair: 9/26
Risk Management:
• Smart Stop: on | -3.5%
• Failsafe Stop: on | -5.25%
• Mech TP/Cls: on
ATR Trailing Exits:
• Mode: A4.0
• L Multi: 4.0 | S Multi: 2.0
• Lng LB: 14 | Shrt LB: 26
• LinReg: 10 | First Bar: 1.5 (A4.1 only)
Backtest Properties:
• Initial capital: $10,000
• Commission: 0.05%
• Slippage: 2 ticks
• Order size: $5,000 (cash, fixed)
• Fill limit assumption: 5 ticks
• Max risk per trade: $262.50 (2.625% of starting equity)
CREDITS
ATR: J. Welles Wilder (1978).
Efficiency Ratio: Perry Kaufman.
Turtle breakout concept: Richard Donchian. Strategy
ATR Trailing Stops for Hyperliquid Spot + Perps [HYPR-run]DESCRIPTION:
A drop-in ATR trailing exits module. Four architectures that maximize
profit on winning trades using volume weighted volatility instead of fixed levels or
plain ATR. Built modular; the trailing logic is self-contained so you
can drop it into any existing indicator or strategy as a plug-and-play
exits block. Two independent stops (long/short), spot and perps.
DISCOVERING EDGE
ATR trailing exits are popular, everyone uses them, but this indicator doesn't just trail on volatility, it trails on meaningful volatility that very few people measure. In order to gain a persistent, mechanical edge in how winners run and protect capital on the trades that don't work, we explored a more meaningful expression of ATR trailing exits.
VOLUME-WEIGHTED ATR vs PLAIN ATR
Plain ATR treats every candle equally. Volume-weighted ATR will only expand stops when volume validates the volatility, preventing premature exits on noise and letting winners run further on real moves. Over hundreds of trades this single difference can compound in the spirit of letting winners run further, losers stay controlled versus fixed levels or vanilla ATR.
- Four modes (A3.1, A4.0, A4.1, A4.2) cover different trailing
behaviors: ratcheting, chandelier anchor, free-floating, and raw
baseline. All size stop distance from volatility, not fixed levels.
- Modular engine. The trailing logic is self-contained; drop it into
any existing indicator or strategy as a plug-and-play exits block.
- Alerts fire built-in JSON webhook payloads. Paste your webhook URL,
create the alert, execute on the exchange of your choice.
ATR MODES
A3.1: LinReg + plain ATR, no ratchet. The baseline. Linear regression
projects where price is heading, plain ATR sets the distance. Stop moves
freely in both directions. Use as a reference or when you want a raw
trailing stop.
A4.0: LinReg + VWATR + Efficiency Ratio + ratchet (default). The
all-rounder. Volume-weighted ATR discounts low-liquidity candles. The
Efficiency Ratio (Kaufman) measures trend quality: in a clean trend it
widens the stop to let price run; in chop it tightens. Ratchet floor
means the stop only moves in your favor.
A4.1: Chandelier + VWATR + ratchet + first-bar multiplier. Anchored to
the highest high (longs) or lowest low (shorts). First-bar multiplier
sets a tighter initial stop, then the standard multiplier takes over as
the ratchet locks in gains. Use when entering off key levels.
A4.2: LinReg + VWATR, no ratchet. Same as A4.0 but without ratchet
floor or Efficiency Ratio. Stop moves freely with the projection, giving
the trade room through consolidation at the cost of less locked profit.
FEATURES
- Four ATR architectures selectable via dropdown
- Volume-weighted ATR: low-liquidity candles contribute less
- Efficiency Ratio: tightens in chop, widens in trend (A4.0)
- Ratchet floor: stop only moves in your favor (A4.0, A4.1)
- First-bar multiplier for tighter initial protection (A4.1)
- Separate ATR lookbacks for longs and shorts
- Separate multipliers for longs and shorts
- Two-bar confirmation prevents single-wick fakeouts
- Gradient fill between price and stop (intensifies near danger)
- Stop line color shifts with ATR regime (green stable, amber expanding)
- Ratchet circles mark each new locked-in level on the stop line
- Dashboard: mode, stop price, gap %, ER, VWATR %, regime state
- Dark/light theme toggle for any chart background
- Independent long/short alert toggles
- No JSON snippet needed; close payload is built into the script
HOW IT WORKS
Volume-weighted ATR scales each bar's true range by its volume relative
to the lookback average. High-volume bars contribute more; thin candles
contribute less. This prevents low-liquidity spikes from inflating stop
distance. Separate lookbacks for longs (default 14) and shorts (default
26) reflect that crypto drops faster than it climbs.
The Efficiency Ratio measures directional movement versus noise on a 0-1
scale. It scales the ATR multiplier between 0.8x (choppy) and 1.2x
(trending), adapting stop width to market regime. Only active in A4.0.
Two-bar confirmation requires a confirmed close beyond the stop level.
A single wick does not trigger the exit. The cross must hold for at
least one additional bar close.
ALERTS
Close Long fires as SPOT (sell spot position). Close Short fires as
PERPS (close short; spot is long-only). Toggle each independently.
Alert payload is built into the script as JSON; works with any webhook
receiver that accepts market/ticker/position fields.
CREDITS
ATR: J. Welles Wilder (1978)
Efficiency Ratio: Perry Kaufman Indicator
AG Pro ATR Compression Map [AGPro Series]AG Pro ATR Compression Map
Overview / What it does
AG Pro ATR Compression Map is a chart-first compression analysis tool designed to evaluate how organized a low-volatility phase is and how structurally developed that contraction has become.
Instead of treating every quiet market phase as equally meaningful, the script separates loose and unstable contraction from cleaner, more contained compression conditions. The goal is not to label every narrow range as important, but to provide a structured visual framework for monitoring whether a tightening phase is becoming more coherent and potentially worth closer attention.
The script is built for users who want to read compression quality directly on the chart without relying on overly complex dashboard-style presentation. It highlights active compression zones, assigns a normalized compression score, classifies the current state of contraction, and summarizes the condition through a compact on-chart panel.
This is intended as a context and monitoring tool. It does not attempt to forecast direction, guarantee expansion, or replace execution planning and risk management.
Unique Edge
The main idea behind this script is that low volatility alone is not enough.
Many consolidations look similar at first glance, but their internal structure can be very different. Some are noisy, unstable, and disorderly. Others become progressively tighter, cleaner, and more contained. AG Pro ATR Compression Map is designed to make that distinction clearer.
Its edge is not based on directional prediction. Instead, it evaluates compression quality through a blended framework that combines volatility contraction, local range tightening, internal noise behavior, and containment structure. This allows the script to differentiate between random quiet price action and more organized compression phases.
This also keeps the script distinct from tools that focus on breakout confirmation, retest quality, trend classification, or level-based pressure analysis. Here, the focus is narrower and more specific: measuring the quality of compression itself.
Methodology
The script combines four internal components into a unified compression score:
1) ATR contraction
Measures whether current ATR is compressed relative to its own baseline.
2) Range tightness
Measures whether the recent price range has narrowed compared with a broader reference window.
3) Noise evaluation
Evaluates whether the contraction phase is relatively clean or increasingly disordered. This includes internal bar behavior such as wick activity, directional flipping, and local overlap behavior.
4) Structural containment
Measures whether price is remaining contained within a tighter local area instead of drifting loosely inside a broad consolidation.
These components are normalized and combined into a 0-100 compression score.
The script then classifies the result into four stages:
• Loose
• Building
• Tight
• Mature
This stage logic is designed to help distinguish early contraction from more developed compression conditions. Higher states reflect more structured tightening, but not certainty of resolution.
What the script highlights
• Compression zone
A shaded chart area is displayed when compression conditions are active.
• Compression score
A compact label shows the current normalized compression score.
• State label
The current compression stage is shown directly on the chart.
• Mini panel
A small panel summarizes ATR state, range state, noise condition, containment quality, overall compression score, active state, and current compression window length.
Signals & Alerts
This script includes deterministic alert conditions for:
• Compression Active
Triggered when compression conditions become active according to the script's scoring logic.
• Compression Mature
Triggered when the current state reaches Mature.
• Compression State Change
Triggered when the internal compression state changes.
These alerts are designed to reflect state transitions inside the script's existing framework. They should be interpreted as analytical status changes, not as trade instructions.
Key Inputs
Main controls include:
• ATR Length
• Baseline Length
• Range Window
• Noise Window
• Containment Window
• Compression Threshold
• Mature Threshold
The script also includes display controls for zone visibility, labels, panel position, theme mode, text sizing, and label offset. Advanced options allow stricter filtering and additional sensitivity controls for wick behavior and close-overlap behavior.
How to read it
In practice, the script is most useful when users want to answer questions such as:
• Is this contraction still loose, or is it becoming more organized?
• Is the range tightening in a meaningful way, or is price simply drifting?
• Is the structure relatively clean, or is internal noise increasing?
• Has the compression developed enough to justify closer monitoring?
A higher compression score means the script is detecting tighter and more structured contraction conditions. A lower score suggests that the current quiet phase is still broad, unstable, or underdeveloped.
Best use cases
This script can be useful when monitoring:
• developing consolidations
• low-volatility phases inside broader trends
• pre-expansion observation zones
• structured pauses after directional movement
• markets where users want to distinguish clean compression from random inactivity
It is especially suited for traders who prefer chart-first context tools rather than signal-heavy overlays.
Limitations & Transparency
Compression can remain inactive for long periods, fail to resolve cleanly, or resolve without meaningful follow-through.
A high compression reading does not imply directional certainty, timing certainty, or inevitable expansion. Likewise, a low reading does not mean price cannot move sharply. The script measures structure quality inside contraction conditions. It does not measure certainty.
The output should be used as contextual information alongside price action, market structure, execution rules, and risk management.
What it does not do
This script does not:
• predict breakout direction
• guarantee expansion
• project targets
• replace trade planning
• function as a standalone entry engine
Risk Disclosure
For educational and analytical use only. Indicator
AG Pro Position Planner [AGPro Series]AG Pro Position Planner
OVERVIEW
AG Pro Position Planner is a structured trade-planning and risk-organization tool designed for traders who want to map a position before execution. It focuses on four core elements of trade preparation: entry location, stop placement, target mapping, and position sizing. Instead of trying to predict direction or generate automated entries, the script helps organize a plan around levels that the user defines manually.
The purpose of this tool is not to tell the user what to buy or sell. Its purpose is to turn a discretionary plan into a visible, measurable framework on the chart. By combining entry, stop, risk budget, capital usage, and target structure in one view, the script helps reduce planning ambiguity and makes the trade idea easier to review before any order is placed.
The script supports both long and short planning. It can also operate in two different target modes. In R-Based mode, targets are derived from the distance between entry and stop. In Manual mode, the user can input exact target prices directly and the script will convert those targets into their implied R-multiples. This allows the same tool to support both systematic planning and discretionary scenario mapping without changing the underlying workflow.
The visual design is intentionally restrained. The chart shows entry, stop, and target levels, along with optional reward and risk zones. A compact panel summarizes the key planning information, including direction, mode, risk per unit, risk budget, sizing, exposure, and target statistics. The result is a planning layout that remains readable on both light and dark themes while keeping the focus on structure rather than decoration.
WHAT THIS SCRIPT DOES
This script helps the user:
• define a planned entry price
• define a planned stop price
• convert account risk into a position size estimate
• map one to three targets on the chart
• compare manual targets to the initial risk distance
• review exposure before execution
• validate whether a manual target structure is logically ordered
• visualize the reward zone above entry and the risk zone below entry for long scenarios, or the inverse logic for short scenarios
The script is designed as a planning layer. It does not attempt to replace the user’s analysis process. It assumes the user already has a trade idea and needs a cleaner way to structure and review that idea.
UNIQUE EDGE
The distinguishing feature of this script is not signal generation. Its edge is organizational clarity.
Many tools focus on entries, signals, or directional interpretation. This one focuses on plan construction. The user chooses the key prices, and the script translates them into a coherent risk model. That distinction matters. The script does not present itself as a forecasting engine, a market-timing system, or an automated decision model. It is a position-planning framework.
A second differentiator is the dual target workflow. Some users think in fixed R-multiples. Others think in exact price objectives. AG Pro Position Planner supports both approaches in the same interface. In Manual mode, the script still reports the effective R-value of each target, which helps the user compare discretionary targets against the initial stop distance without losing consistency.
A third differentiator is the built-in validation behavior. The script checks whether the trade structure is logically valid for the chosen direction. In Manual mode, it also checks whether the targets are placed in the correct direction and in the correct order. This helps the user detect plan errors before execution rather than after the fact.
METHODOLOGY
The planning model is straightforward by design.
1) Entry and stop define the base risk distance.
The script measures the absolute distance between entry and stop. That distance becomes the reference risk per unit.
2) Account risk defines the risk budget.
The user enters an account size and a percentage risk per trade. The script converts this into a monetary risk budget.
3) Position size is estimated from the risk budget.
The script divides the risk budget by effective risk per unit and rounds the resulting quantity down to the selected quantity step.
4) Optional fee adjustment can be included.
An estimated fee percentage can be added to the per-unit risk as a conservative sizing buffer.
5) Targets are then mapped in one of two ways.
In R-Based mode, each target is calculated from the entry-to-stop distance using the selected R-multipliers.
In Manual mode, the user provides exact target prices and the script calculates the implied R-value of each target relative to the original stop distance.
6) Exposure statistics are summarized in the panel.
The panel shows stop distance, capital usage, risk budget, and sizing information so the trade can be evaluated as a complete plan rather than as isolated levels.
This methodology is intentionally transparent. The script is not using hidden directional filters, prediction logic, or undisclosed entry models. The calculations are derived from the user’s own inputs.
TARGET MODES
R-Based Mode
R-Based mode is intended for users who want a consistent structure around initial risk. The user defines entry and stop, then sets target multipliers such as 1R, 2R, or 3R. The script projects those levels automatically from the base risk distance. This is useful when the user wants standardized scenario planning and fast comparison between multiple setups.
Manual Mode
Manual mode is intended for users who work with exact price objectives. In this mode, the user enters target prices directly. The script then converts those levels into implied R-values. This allows discretionary targets to be measured against the same initial risk model.
To reduce planning mistakes, the script validates whether manual targets are placed in the correct direction and in the correct order for the chosen trade direction. Invalid target structures are flagged in the panel instead of being silently accepted.
PANEL AND VISUAL STRUCTURE
The chart can display:
• entry line
• stop line
• target lines
• reward zone
• risk zone
• right-side labels for entry, stop, and targets
• a compact summary panel
The panel is designed to keep the most useful information visible without taking over the chart. Its goal is to support review, not to dominate the screen.
The compact panel includes:
• plan summary
• validation badge
• entry and stop
• risk per unit
• risk budget
• sizing
• exposure
• target statistics
This structure is meant to help the user answer practical questions quickly:
How much is being risked?
How large is the position?
How much capital is being used?
How far is the stop?
What does each target represent in both price and R terms?
KEY INPUTS
Trade Setup
• Trade Direction
• Target Mode
• Entry Price
• Stop Price
• R-based targets
• Manual targets
Risk Model
• Account Size
• Risk Per Trade (%)
• Estimated Fees (%)
• Quantity Step
Visual Settings
• Panel visibility
• Panel position
• Panel theme
• Panel text size
• Level label size
• Label offset
• Risk/reward zone visibility
• Zone transparency
• Individual target visibility
These inputs are separated by function so the planning workflow stays readable and predictable.
VALIDATION AND SAFETY LOGIC
The script validates several conditions before presenting a plan as valid.
For direction:
• Long plans require stop below entry
• Short plans require stop above entry
For base structure:
• Entry must be positive
• Stop must be positive
• Account size must be positive
• Risk percentage must be positive
• Quantity step must be positive
• Entry and stop must not be identical
For manual targets:
• Targets must be in the correct direction relative to entry
• Targets must be logically ordered for the selected direction
If the structure is invalid, the panel reflects that status instead of presenting the setup as a clean plan. This behavior is intentional. The script is designed to help organize decisions, but also to prevent simple construction errors from being overlooked.
WHO THIS SCRIPT IS FOR
This script is intended for users who already make their own directional decisions and want a cleaner way to structure position plans on the chart.
It may be useful for:
• discretionary traders
• swing traders
• intraday traders
• users who plan entries and stops manually
• users who prefer fixed-R target mapping
• users who want manual targets translated into risk terms
• users who want better visual discipline before execution
It is less relevant for users who are looking for:
• automated entries
• hidden directional logic
• predictive signals
• scanner behavior
• portfolio automation
• strategy backtests
SIGNALS AND ALERTS
This script does not generate buy signals or sell signals.
This script does not publish automated trade calls.
This script does not attempt to identify market direction.
This script does not include alert logic for execution decisions.
Its purpose is planning, visualization, and risk organization.
LIMITATIONS AND TRANSPARENCY
This script is a planning tool, not an execution engine.
It does not know whether the selected entry will be filled.
It does not know whether slippage will occur.
It does not know whether the market will reach the defined targets.
It does not account for instrument-specific margin rules, liquidation mechanics, funding costs, or exchange-specific order behavior unless the user adjusts inputs manually.
The sizing output is an estimate based on the values entered into the script. Real-world execution may differ due to slippage, fees, order type, spread, partial fills, and instrument-specific trading conditions.
In Manual mode, the script evaluates the price structure entered by the user, but it does not claim that those targets are likely to be reached. It only expresses them relative to the initial risk distance.
The chart zones are visual planning aids. They are not probability forecasts and should not be interpreted as predictive boundaries.
WHAT THIS SCRIPT IS NOT
This script is not:
• a strategy tester
• a signal service
• an automated trade system
• a forecasting model
• a promise of profitability
• a replacement for independent analysis
• a substitute for execution judgment
• a guarantee of risk control in live market conditions
It is a structured chart tool for planning and reviewing position scenarios.
RISK DISCLOSURE
Trading and investing involve risk. Any planned setup can fail, and losses can exceed expectations due to slippage, volatility, or execution conditions. This script is provided as an organizational and visualization tool only. Users remain fully responsible for their own analysis, trade selection, order placement, and risk management decisions.
No indicator can remove market risk. A visually clean plan is still only a plan. Position sizing, stop placement, and target mapping should always be reviewed in the context of the instrument, timeframe, liquidity conditions, and the user’s own trading process.
FINAL NOTE
AG Pro Position Planner is built around a simple idea: a trade plan should be measurable before it is actionable. By turning entry, stop, risk budget, sizing, and targets into a single visible structure, the script aims to make discretionary planning more disciplined, more transparent, and easier to review.
The script does not attempt to decide for the user. It helps the user define the plan clearly enough to evaluate it. Indicator
Indicator
Indicator
Stop Loss Cascades (Breakouts) [Kioseff Trading]Hello friends and traders!
🔹Introduction
This indicator " Stop-Loss Clustering (Breakouts) " attempts to model trader stop-loss placement logic and identify price areas where a large amount of stop losses might cluster.
The idea is, if stop losses are indeed highly concentrated in a specific area, price extending through that area may produce high-velocity breakout conditions via forced order flow .
I'll cover this topic more thoroughly throughout the description. For now, just know that stop loss location & size data is not publicly available . Any model of their concentration locations is highly assumptive.
However, there's some reasonable academic research we can reference to make worthwhile estimates.
Academic references supporting the concepts discussed are listed at the end of this description. To maintain readability, I won't cite individual statements inline.
🔹The Premise
🔸Liquidity, Behavior, and Stop Cascades
Markets operate through a continuous limit order book , where two fundamental order types interact:
Limit orders , which provide liquidity by resting in the book
Market orders , which consume liquidity by exhausting those resting orders
This mechanical interaction drives price movement - incoming order flow consuming available liquidity .
This begs the question.. Does liquidity distribute evenly across the LOB?
If it did : If liquidity were evenly distributed, price impact could be modeled as a relatively smooth function of incoming order flow.
But it doesn’t : Liquidity is unevenly distributed. Academic research supports this claim and, regardless, this is an intuitive conclusion most traders arrive at.
Liquidity forms localized concentrations and gaps.
Liquidity concentrations are commonly referenced as: liquidity shelves , liquidity clusters , liquidity zones .
Liquidity gaps are commonly referenced as: liquidity vacuums , thin book zones .
As a result, identical order flow can produce very different price movements depending on the state of the order book.
Let’s consider an example..
Assume price is trading at $99.
The price levels $100, $101, $102 have resting sell limit order concentrations of 100.
This is where you come in.
You execute a market order buy for 300 size.
Your order first exhausts all sell-side resting order concentrations at the $100 level.
You still have 200 size that needs to be filled, and the ask price has moved from $100 to $101.
Your order will now sequentially exhaust available liquidity at the $101 level, the ask price will increase to $102, and your final 100 size will exhaust the $102 level.
To keep the example simple, we’ll say that your order moved price from $99 to $102, and now the ask price is $103.
But, you still want to accumulate.
The nearest sell-side levels in the LOB are $103, $104, $105.
The $103 level has a sell limit order concentration of 500.
$104 and $105 both have concentrations of 50.
You execute your same market order buy for 300 size.
This time, price doesn’t move.. At all..
Instead, you consumed 300 of the 500 size at $103 with your order, and the level remains a barrier.
Your order was absorbed by available liquidity.
This example demonstrates how price movement depends on available liquidity , not simply the size of incoming orders.
In the first scenario, liquidity was thin and the order walked through multiple price levels, causing price to move quickly.
In the second scenario, a large concentration of resting liquidity absorbed the same order, preventing price from advancing.
🔸Liquidity Does Not Distribute Evenly
Alright, we understand that liquidity doesn’t distribute evenly. And we understand that high concentrations of liquidity can act as price barriers (liquidity shelves) while sparse liquidity can permit rapid price movement - we saw this in our example above.
There’s an important question we should ask next before we move on..
If liquidity distributes unevenly, then where does it tend to cluster? And where does it tend to thin?
Of course, knowing these tendencies provides multi-purpose advantages.
If price approaches a liquidity vacuum - a local block of the order book with thin resting liquidity - rapid price movement can occur without requiring unusually strong aggressive order flow.
If price approaches a liquidity shelf - a local block of the order book with thick resting liquidity - price can stall or contract even if the same level of aggressive order flow that previously moved price continues.
With this in mind, order flow intensity alone does not determine price movement . The distribution of liquidity across surrounding price levels plays a similarly important role.
So, is there any evidence of where liquidity tends to concentrate ?
🔸Empirical Observations
Empirical research on limit order books shows that liquidity does not distribute smoothly across the LOB . Instead, depth tends to concentrate at specific price levels, producing irregular profiles with localized peaks in resting liquidity.
These concentrations arise because order placement is not random . Traders frequently anchor decisions to widely observed reference prices such as:
• prior highs
• prior lows
• round numbers
• widely referenced price extremes
Because many traders monitor the same price history, order placement decisions often reference similar price levels.
This concept is simpler than it sounds.
Let’s use market structure traders for example.
Market structure traders frequently reference prior swing highs and swing lows when making decisions about entries, exits, and risk.
A trader entering a long position may place their stop-loss below a recent swing low , reasoning that if price breaks that level, the trade idea is invalidated.
A trader entering a short position may place their stop-loss above a recent swing high for the same reason.
Timeframe price aggregation may differ; however, we’re all looking at roughly the same recent highs and lows when evaluating a chart (structure).
When many traders collectively reference the same prices, orders may accumulate near those levels. This produces localized depth concentrations, which traders refer to as liquidity shelves .
Liquidity shelves act as temporary barriers where the book contains disproportionately large resting liquidity compared to surrounding prices.
🔸Research documenting liquidity clustering includes :
Bourghelle & Cellier (2007) , who find that limit orders cluster at prominent price levels (especially round numbers), creating localized depth concentrations that can act as price barriers.
Kavajecz & Odders-White (2004) , who demonstrate that prices identified as support or resistance coincide with higher resting limit order depth
These findings suggest that many commonly observed price levels may correspond to real concentrations of liquidity rather than being purely visual artifacts on a chart.
Kavajecz & Odders-White (2004) is an important observation for support/resistance traders!
Kavajecz & Odders-White (2004) show that levels traders commonly call support and resistance often align with areas where more limit orders are resting in the order book.
This suggests a plausible mechanical pathway through which support and resistance levels can emerge!
🔸Liquidity Shelves and Price Interaction
When liquidity clusters around a price level, the resulting liquidity shelf can influence how price behaves when it approaches that area.
Price interaction with these shelves is state-dependent :
If incoming order flow is absorbed, price may stall or reverse
If resting liquidity is consumed, price may transition rapidly to the next liquidity zone
Once a shelf is depleted, follow-through can accelerate due to thinner liquidity beyond the level
Research on order book dynamics supports this mechanical view of price movement.
For example:
Jean-Philippe Bouchaud, J. Doyne Farmer, and Fabrizio Lillo (2009) demonstrate that price impact emerges from the interaction between order flow and finite liquidity
From this perspective, price does not move simply because a level is crossed.
Price moves because available liquidity at that level has been consumed.
🔸Latent Liquidity and Stop Clustering
In addition to visible liquidity from limit orders, markets also contain latent liquidity .
This is where ”Stop-Loss Clustering (Breakouts)” becomes important - we’re almost done!
Latent liquidity consists of conditional orders such as stop-losses that are not visible in the order book until triggered .
Although these orders aren’t public information, empirical studies show that stop orders tend to cluster near widely referenced price levels .
Research by Carol Osler (2001, 2002) using institutional FX order data finds that stop-loss orders frequently accumulate just beyond salient price levels such as prior highs and lows.
When these stops trigger, they convert into aggressive market orders and can generate bursts of directional order flow that may accelerate price movement.
🔸Stop-Loss Cascades
Stop losses add another layer of latent order flow that isn’t visible in the order book until it triggers.
If enough of them sit around the same price area.. Think “hidden pressure” waiting to activate. Nothing happens while price trades nearby, but once that level is traded at, those stops convert into market orders and immediately begin consuming available liquidity.
This matters because stop placement is unlikely to be random in most instances. Traders frequently anchor stops to widely observed prices such as prior highs, prior lows, or other prominent structure points, or use volatility methods such as ATR, etc.
So when price approaches one of these areas, two things can happen.
If the resting liquidity there is large enough, the incoming orders can be absorbed and price may stall or reject.
But if that liquidity gets consumed, the stops sitting just beyond the level begin triggering. Those triggered stops add additional market orders, which consume more liquidity and can push price further into the next layer of stops.
This creates a cascading effect:
price reaches a stop cluster
stops trigger and convert into market orders
liquidity gets consumed faster
price moves further, triggering more stops
When this chain reaction starts, price can transition very quickly from a slow battle near the level to rapid expansion through it.
This is one of the mechanical reasons why some reference-point breaks barely move, while others accelerate rapidly.
🔹How It Works
Now that we understand the why - let’s discuss how the indicator works.
🔸Absorbtion Extremes
The image above shows the absorption extremes model.
In this model, the indicator treats recent & relevant swing points as plausible stop clustering candidates.
You can find similar swing point identification mechanics in other indicators.
However, this model assigns subsequent volume to the swing level after its formation.
There are limitations and assumptions - let’s go over them.
The images above explain how the indicator determines the intensity of a possible stop-cluster around a swing level.
There are limitations and assumptions
1: The indicator assigns all “directional volume” to a swing level after it’s formed and while it remains the closest active swing point to the current price.
“Buy volume” is assigned to the closest active swing low.
“Sell volume” is assigned to the closest active swing high.
I say “buy volume” and “sell volume” because there’s assumptions on what constitutes the relevant classification.
The indicators follow the traditional two-region tick model for classifying buy volume and sell volume.
Higher close = “buy volume” proxy
Lower close = “sell volume” proxy
Depending on the granularity you select (the indicator is capable of using tick data), this model can be more/less accurate.
However, even with tick-level data and bid/ask quotes, trade direction must still be inferred using classification rules. Because some trades occur inside the spread or involve hidden liquidity, perfect classification is not possible without exchange aggressor flags.
For assumptions..
The model assigns ALL classified volume to the swing level.
In reality, traders use a wide range of risk management methods, and not every position will place a stop loss directly at the most recent swing point. ATR-based stops, percentage-based stops, and other volatility-based methods are also common.
Because the true distribution of stop placement is unobservable, the model assumes that positions entered are structurally invalidated at the closest swing level based on their classified direction.
As a result, the values displayed by the indicator should be interpreted as relative proxies for potential stop concentration, rather than precise estimates of actual stop-loss size.
The displayed magnitudes are intentionally exaggerated and comparative, designed to highlight where stop pressure may accumulate relative to other levels.
The images above show how to interpret the indicator when using this model.
The image above shows the triggered stop-cluster graph.
Each point corresponds to a triggered stop-cluster - assuming it exists.
The greater the size attached to that cluster, the further distant the data point is placed.
Far away from zero line = large size.
Close to zero line = low size.
Radiating/glowing points indicate a potentially large cluster trigger.
🔸 Volatility-At-Entry Model (Time Scaled)
The Volatility-At-Entry model uses ATR scaled by various timeframes to predict plausible stop loss placements.
For this model, the indicator uses the same tick classification model to assign volume directionally.
Volume is then dispersed across six common timeframes (1m, 5m, 15m, 30m, 1h, 4h) and 3 common ATR multiples for risk management (1ATR, 1.5ATR, 2ATR).
This model assumes traders are entering positions across various timeframes and are scaling risk congruent with those timeframes.
For instance,
A trader using the 1-minute chart for opportunity is more likely to use a stop loss closer to entry than a trader using the 4-hour chart for opportunity.
If this assumption is reasonable to you - great, we can move forward!
The image above visualizes the model.
Purple-shaded regions indicate a price area with less opportunity for stop loss clustering. Either transaction intensity around eligible price areas was low, or position accumulation wasn’t given sufficient time.
Pink-shaded regions indicate a price area with greater opportunity for stop loss clustering. Volume was significant around these regions or price has traded within proximity for extended periods.
This model naturally shows more future opportunity than historical outcomes. You can select to show historical outcomes in the settings, this image shows examples of such outcomes.
The image above shows the triggered stop loss graph in effect for this model. Stop clustered are distributed across more price areas with this model - from low intensity to high intensity. Therefore, a cluster is almost always “triggering” to some degree.
A classification model for what’s typical and what’s unusual is used for the graph in this case. Radiating points always indicate large stop clusters triggered. Anything within the green/pink line indicates usual size.
Typical Move
The image above explains the nearest cluster information table.
The size and location of the nearest buy-stop cluster and sell-stop cluster are recorded.
Additionally, the indicator identifies whether clusters of similar size were triggered in the past, and how price behaved following those events.
Since all models here are highly assumptive, and similar sized clusters might only have one or two relative neighbors, treat these measurements as a description of history rather than a prediction.
The model takes the logarithm of the current stop-volume (buy or sell) to normalize its scale and compare it with a historical dataset of previously observed stop-volume sizes that have also been log-scaled.
It then identifies historical observations whose sizes are most similar to the current value, either by selecting all observations within a tolerance range around that value (where the range is based on the typical spacing between historical observations), or by selecting the single closest match.
Finally, the model retrieves the historical price moves associated with those matched observations, producing a sample of “typical moves” that occurred when stop-volume magnitude was similar to the current situation.
Ratio Meter
The stop-cluster ratio meter shows the current sum of active and triggered all buy-side clusters and sell-side clusters.
This meter is useful for quick scanning across assets to see if active or recently triggered stop clusters are lopsided.
Additional Features
The single most important setting outside model selection is the lower timeframe used to retrieve volume from.
This setting is set to 1-minute data by default because it works with paid and free plans. If you want better granularity, I strongly suggest changing this setting to either 1-second or 1-tick. This will sacrifice the number of identifiable cluster locations, because better granularity data has less programmatically retrievable values.
🔹Closing Remarks
Stop-loss clustering is an appealing concept because it offers a plausible explanation for why some breakouts accelerate so quickly while others stall. When a large number of conditional orders sit near the same price, a breakout through that area can trigger a cascade of market orders that rapidly consume liquidity and push price toward the next available zone.
However, it’s important to remember that the models used in this indicator are approximations, not direct measurements. True stop-loss locations and sizes are not publicly observable, and many traders use different risk management techniques that cannot be perfectly inferred from chart data alone. The goal of this indicator is therefore not to identify exact stop locations, but to highlight price areas where stop pressure may plausibly accumulate relative to surrounding levels.
Like any model based on behavioral assumptions and historical observations, results should be interpreted probabilistically. Large clusters do not guarantee breakouts, and small clusters do not guarantee quiet price behavior. Instead, the indicator is best used as a tool for context and situational awareness.
References
General Microstructure and Price Formation
Madhavan, A. (2000). Market microstructure: A survey. Journal of Financial Markets, 3(3), 205–258.
O'Hara, M. (1995). Market Microstructure Theory. Blackwell.
Biais, B., Glosten, L., & Spatt, C. (2005). Market microstructure: A survey of microfoundations, empirical results, and policy implications. Journal of Financial Markets, 8(2), 217–264.
Limit Order Books and Liquidity as Resting Orders
Gould, M. D., Porter, M. A., Williams, S., McDonald, M., Fenn, D. J., & Howison, S. D. (2013). Limit order books. Quantitative Finance, 13(11), 1709–1742.
Rosu, I. (2009). A dynamic model of the limit order book. Review of Financial Studies, 22(11), 4601–4641.
Biais, B., Hillion, P., & Spatt, C. (1995). An empirical analysis of the limit order book and the order flow in the Paris Bourse. Journal of Finance, 50(5), 1655–1689.
Liquidity Clustering and Depth Concentration
Kavajecz, K. A., & Odders-White, E. R. (2004). Technical analysis and liquidity provision. Review of Financial Studies, 17(4), 1043–1071.
Bourghelle, D., & Cellier, A. (2007). Limit order clustering and price barriers on financial markets. Working paper / SSRN.
Order Flow and Price Impact
Bouchaud, J.-P., Farmer, J. D., & Lillo, F. (2009). How markets slowly digest changes in supply and demand. In Handbook of Financial Markets: Dynamics and Evolution.
Stop Orders and Price Cascades
Osler, C. L. (2003). Currency orders and exchange-rate dynamics: Explaining the success of technical analysis. Journal of Finance, 58(5), 1791–1819.
Osler, C. L. (2005). Stop-loss orders and price cascades in currency markets. Journal of International Money and Finance, 24(2), 219–241.
Liquidity Provision and Execution
Ho, T., & Stoll, H. (1981). Optimal dealer pricing under transactions and return uncertainty. Journal of Financial Economics, 9(1), 47–73.
Almgren, R., & Chriss, N. (2000). Optimal execution of portfolio transactions. Journal of Risk, 3(2), 5–39.
Menkveld, A. J. (2013). High frequency trading and the new market makers. Journal of Financial Markets, 16(4), 712–740.
Behavioral Anchoring and Attention
Kahneman, D., & Tversky, A. (1974). Judgment under uncertainty: Heuristics and biases. Science, 185(4157), 1124–1131.
Barber, B. M., & Odean, T. (2008). All that glitters: The effect of attention and news on the buying behavior of individual and institutional investors. Review of Financial Studies, 21(2), 785–818.
George, T. J., & Hwang, C. Y. (2004). The 52-week high and momentum investing. Journal of Finance, 59(5), 2145–2176.
Mizrach, B., & Weerts, S. (2007). Highs and lows: A behavioral and technical analysis. SSRN working paper.
Indicator
Liquidity Sweep Rider Institutional HFT Grabber Liquidity Sweep Rider Strategy (Swing Pivot + Volume Filter)
Publication Description:
This is an open-source Pine Script v6 strategy that identifies potential liquidity sweep patterns around confirmed swing highs and lows.
It uses:
Pivot points (ta.pivothigh / ta.pivotlow) to mark historical swing levels where orders (such as stops or pending entries) often cluster.
A volume filter requiring above-average volume (SMA-based with multiplier) on the sweep candle to highlight stronger moves.
Classic sweep logic: price wicks beyond the level but closes back inside, suggesting a possible reversal after liquidity is taken.
Entry rules:
Long: after a downside sweep below a recent swing low (with volume condition).
Short: after an upside sweep above a recent swing high (with volume condition).
Features include:
Optional toggles to enable/disable long/short directions.
ATR-based stop-loss and take-profit (configurable multipliers and risk-reward ratio).
Visual plots for liquidity levels, entry signals, background highlights, and an info table.
Alert conditions for long/short triggers.
Important notes:
This is an educational/example script for backtesting and learning.
Past performance does not indicate future results. Trading involves significant risk of loss — use proper risk management and never risk more than you can afford to lose.
No guarantees of profitability are made. Always test thoroughly on demo accounts before live use.
Customize parameters (pivot lengths, volume multiplier, ATR settings) based on the instrument and timeframe you trade. Works on various markets/timeframes but performs differently depending on liquidity and volatility.
Feel free to fork/modify the code. Feedback and improvements are welcome!
(≈ 3–4 paragraphs, clear, educational, includes risk disclaimer, explains logic + usage without hype.) Strategy
Neighboring Trailing Stop [LuxAlgo]The Neighboring Trailing Stop indicator provides a dynamic, data-driven trailing stop-loss mechanism by analyzing the local distribution of prices relative to the current market position. It uses a "k-nearest neighbors" approach to identify support and resistance levels based on historical price clusters, offering a unique alternative to standard volatility-based stops like ATR.
🔶 USAGE
The indicator helps traders identify trend reversals and manage open positions by providing a protective stop that adjusts based on where price has historically "congested" near the current level.
🔹 Trend Interpretation
Bullish Trend: When the stop-loss line is below the price (colored green), the market is in a bullish state. The trailing stop will only move upward, securing profits as the price creates new local distribution highs.
Bearish Trend: When the stop-loss line is above the price (colored red), the market is in a bearish state. The trailing stop will only move downward, following the price as it explores lower distribution zones.
🔹 Signals
The script plots "B" (Buy) and "S" (Sell) labels at the point of trend reversals. These occurs when the price breaks through the current "neighboring" distribution boundary, suggesting a shift in the local market structure.
🔶 DETAILS
The methodology behind this indicator is rooted in non-parametric statistics and price distribution analysis rather than simple moving averages or volatility.
🔹 Price Distribution & K-Neighbors
The script maintains a "Historical Buffer" of recent prices in a sorted array. For every new bar, it identifies the position of the current price within this sorted distribution. It then looks at k neighbors above the price and k neighbors below the price.
🔹 Percentile Bands
Within these local "neighborhoods" of price data, the script calculates a specific percentile. This allows the indicator to ignore outliers and focus on where the bulk of historical price action occurred near the current level. If the price moves into a "discovery" phase where it exceeds the range of its historical neighbors, a trend reversal is triggered.
🔹 Trailing Logic
The resulting levels are smoothed via an SMA to prevent erratic jumps. The trailing stop is "ratcheted"—meaning it can only move in the direction of the trend (up for long, down for short)—ensuring that realized gains are protected even if the distribution neighborhood expands.
🔶 SETTINGS
Historical Buffer (Bars): Determines how many historical price points are kept in the distribution memory. A larger buffer considers more history, leading to more stable but slower-reacting levels.
Neighboring Range (K): The number of price points to analyze immediately above and below the current price. Smaller values make the stop more sensitive to local price changes.
Percentile: Controls the depth within the neighborhood used for the stop level. A higher percentile (e.g., 90) places the stop further away from the current price.
Smoothing: Applies a Simple Moving Average (SMA) to the raw distribution levels to create a smoother trailing line.
Indicator
Indicator
EDUVEST UTBOT ADJ - Adaptive ATR Trailing StopEDUVEST UTBOT ADJ - Adaptive ATR Trailing Stop with Session-Based Sensitivity
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█ ORIGINALITY
This indicator is an enhanced version of the classic UT Bot concept, featuring automatic session-based ATR sensitivity adjustment. Unlike the original UT Bot which uses a fixed sensitivity value, this version dynamically adapts to different trading sessions (Tokyo, London, New York) and automatically detects asset characteristics to optimize signal generation.
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█ WHAT IT DOES
- Generates BUY and SELL signals based on ATR trailing stop crossovers with a moving average
- Automatically adjusts sensitivity based on current trading session (Tokyo/London/NY)
- Auto-detects asset type and applies optimized parameters for each instrument
- Displays real-time session information and volatility status
- Provides alert functionality with customizable cooldown periods
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█ HOW IT WORKS
【Core Logic: ATR Trailing Stop】
The indicator calculates an ATR-based trailing stop using the formula:
Trailing Stop = Price ± (Sensitivity × ATR)
When price is above the trailing stop and rising, the stop trails below price.
When price is below the trailing stop and falling, the stop trails above price.
【Signal Generation】
- BUY Signal: Price crosses above the trailing stop AND Moving Average crosses above the trailing stop
- SELL Signal: Price crosses below the trailing stop AND Moving Average crosses below the trailing stop
【Session-Based Sensitivity Adjustment】
The indicator adjusts ATR sensitivity based on trading session (JST timezone):
- Tokyo (08:00-15:00): Lower sensitivity (reduced by adjustment value) - typically quieter markets
- London (15:00-23:00): Base sensitivity - moderate volatility
- New York (23:00-08:00): Higher sensitivity (increased by adjustment value) - higher volatility
【Dynamic ATR Adjustment】
When enabled, the indicator compares current ATR to its smoothed average:
- ATR Ratio = Current ATR / SMA(ATR, smoothing period)
- Volatility Multiplier = 1.0 + (Sensitivity × (2.0 - ATR Ratio))
This reduces sensitivity during high volatility (fewer false signals) and increases sensitivity during low volatility (faster response).
【Auto Asset Detection】
The indicator automatically detects the traded instrument and applies optimized parameters:
- Stable pairs (USDJPY, EURUSD, USDCHF): Base sensitivity 1.5-1.8
- Moderate pairs (AUDUSD, USDCAD, EURJPY): Base sensitivity 2.0-2.3
- Volatile pairs (GBPUSD): Base sensitivity 2.8
- Commodities (GOLD/XAUUSD): Base sensitivity 3.5
- Indices (NASDAQ/NAS100): Base sensitivity 4.0
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█ HOW TO USE
【Recommended Settings】
- Timeframe: 15 minutes or higher (15M, 1H, 4H recommended)
- Best performance on: Forex majors, Gold, NASDAQ
- Enable "Auto Asset Detection" for optimized parameters
【Entry Rules】
- BUY: Enter long when green BUY label appears
- SELL: Enter short when pink SELL label appears
【Session Panel】
The top-right panel displays:
- Current trading session (Tokyo/London/NY)
- Volatility status (High Chance/Medium Chance/Caution)
- Mode (AUTO/MANUAL)
【Alert Setup】
1. Enable "Viewer Alert Display" in settings
2. Set cooldown period (default: 15 minutes) to avoid signal spam
3. Create alert with "Any alert() function call" condition
【Important Notes】
- This indicator does not repaint - signals are confirmed at bar close
- Lower timeframes (1M, 5M) may generate excessive signals
- Always use proper risk management and confirm with other analysis
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█ SETTINGS OVERVIEW
🎯 Alert Settings
- Viewer Alert Display: Enable/disable alert labels
- Cooldown Function: Prevent rapid consecutive signals
- Cooldown Time: Minutes between alerts (5-60)
🔧 Dynamic ATR Settings
- Enable Dynamic ATR: Auto-adjust based on volatility
- ATR Period: Calculation period (default: 14)
- ATR Smoothing: Smoothing period for ratio calculation
- Volatility Sensitivity: How much to adjust (0.1-1.0)
🕐 Session ATR Adjustment
- Enable Time Adjustment: Session-based sensitivity
- Show Session Info: Display session panel
📊 Asset Settings
- Auto Asset Detection: Automatically optimize for instrument
- Manual settings available when auto-detection is disabled
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█ CREDITS
Based on the original UT Bot concept by QuantNomad.
Enhanced with session-based adaptation and auto-asset detection by EduVest.
License: Mozilla Public License 2.0 Indicator
MDZ Strategy v4.2 - Multi-factor trend strategyWhat This Strategy Does
MDZ (Momentum Divergence Zones) v4.2 is a trend-following strategy that enters long positions when multiple momentum and trend indicators align. It's designed for swing trading on higher timeframes (2H-4H) and uses ATR-based position management.
The strategy waits for strong trend confirmation before entry, requiring agreement across five different filters. This reduces trade frequency but aims to improve signal quality.
Entry Logic
A long entry triggers when ALL of the following conditions are true:
1. EMA Stack (Trend Structure)
Price > EMA 20 > EMA 50 > EMA 200
This "stacked" alignment indicates a strong established uptrend
2. RSI Filter (Momentum Window)
RSI between 45-75 (default)
Confirms momentum without entering overbought territory
3. ADX Filter (Trend Strength)
ADX > 20 (default)
Ensures the trend has sufficient strength, not a ranging market
4. MACD Confirmation
MACD line above signal line
Histogram increasing (momentum accelerating)
5. Directional Movement
+DI > -DI
Confirms bullish directional pressure
Exit Logic
Positions are managed with ATR-based levels:
ParameterDefaultDescriptionStop Loss2.5 × ATRBelow entry priceTake Profit6.0 × ATRAbove entry priceTrailing Stop2.0 × ATROptional, activates after entry
The default configuration produces a 1:2.4 risk-reward ratio.
Presets
The strategy includes optimized presets based on historical testing:
PresetTimeframeNotes1H Standard1 HourMore frequent signals2H Low DD2 HourConservative settings3H Optimized3 HourBalanced approach4H Swing4 HourWider stops for swing tradesCustomAnyFull manual control
Select "Custom" to adjust all parameters manually.
Inputs Explained
EMAs
Fast EMA (20): Short-term trend
Slow EMA (50): Medium-term trend
Trend EMA (200): Long-term trend filter
RSI
Length: Lookback period (default 14)
Min/Max: Entry window to avoid extremes
ADX
Min ADX: Minimum trend strength threshold
Risk
Stop Loss ATR: Multiplier for stop distance
Take Profit ATR: Multiplier for target distance
Trail ATR: Trailing stop distance (if enabled)
Session (Optional)
Filter entries by time of day
Recommended OFF for 3H+ timeframes
What's Displayed
Info Panel (Top Right)
Current preset
Trend status (Strong/Wait)
ADX, RSI, MACD readings
Position status
Risk-reward ratio
Stats Panel (Top Left)
Net P&L %
Total trades
Win rate
Profit factor
Maximum drawdown
Chart
EMA lines (20 blue, 50 orange, 200 purple)
Green background during strong uptrend
Triangle markers on entry signals
Important Notes
⚠️ This is a long-only strategy. It does not take short positions.
⚠️ Historical results do not guarantee future performance. Backtests show what would have happened in the past under specific conditions. Markets change, and any strategy can experience drawdowns or extended losing periods.
⚠️ Risk management is your responsibility. The default settings risk 100% of equity per trade for backtesting purposes. In live trading, appropriate position sizing based on your risk tolerance is essential.
⚠️ Slippage and commissions matter. The backtest includes 0.02% commission and 1 tick slippage, but actual execution costs vary by broker and market conditions.
Best Practices
Test on your specific market — Results vary significantly across different instruments
Use appropriate position sizing — Never risk more than you can afford to lose
Combine with your own analysis — No indicator replaces understanding market context
Paper trade first — Validate the strategy matches your trading style before risking capital
Alerts
Two alerts are available:
MDZ Long Entry: Fires when all entry conditions are met
Uptrend Started: Fires when EMA stack first aligns bullish
Methodology
This strategy is based on the principle that trend continuation has better odds than reversal when multiple timeframe momentum indicators agree. By requiring five independent confirmations, it filters out weak setups at the cost of fewer total signals.
The ATR-based exits adapt to current volatility rather than using fixed pip/point targets, which helps the strategy adjust to different market conditions.
Questions? Leave a comment below. Strategy
Live Position Sizer (LPS)Description (EN)
(Magyar leíráshoz görgess lejjebb!)
Live Position Sizer (LPS) is a discretionary trading utility designed to visualize risk, reward, and position size directly on the chart in real time.
The indicator draws a PulseWire-style long or short position box and calculates the required position size based on your defined capital, maximum risk, stop-loss distance, and a user-defined lot conversion factor.
LPS is intended strictly as a decision-support and risk management tool. It does not place trades or generate automated signals.
Core features:
Automatic Long / Short position visualization
Dynamic Entry, Stop Loss, and Take Profit levels
Real-time position size calculation
Configurable Risk/Reward ratio
Fully customizable colors, transparency, and line styles
Clean, minimal on-chart labels showing direction, RR, and lot size
Only one active position box at a time for a clutter-free chart
Position sizing logic:
PulseWire internally calculates position size in units, not broker-specific lots.
To bridge this difference, LPS uses a user-defined “Units per 1 Lot” multiplier.
Examples:
Forex (standard lot): 100000
Gold (XAUUSD): 1 or 100 (broker dependent)
Indices (e.g. NAS100): 1
The indicator first calculates the position size in PulseWire units and then converts it to lots using this multiplier.
The displayed lot size is rounded to 0.01 lots.
Stop Loss logic:
The Stop Loss level is derived from the High or Low of a selectable previous candle.
Increasing the bar-back value places the Stop Loss further away, which:
increases stop distance
reduces position size for the same risk
Intended use:
Manual / discretionary trading
Risk management and position sizing
Trade planning and visualization
Educational purposes
Important notes:
This indicator does not execute trades
No alerts or automation by default
Lot size and contract specifications vary by broker
Always verify the exact lot or contract size with your broker before trading
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Description (HU)
A Live Position Sizer (LPS) egy diszkrecionális kereskedést támogató segédindikátor, amely valós időben jeleníti meg a kockázatot, a célárat és a pozícióméretet közvetlenül a charton.
Az indikátor PulseWire-stílusú long vagy short pozíció boxot rajzol, és kiszámolja a szükséges pozícióméretet a megadott tőke, maximális kockázat, stop-loss távolság és egy felhasználó által definiált LOT szorzó alapján.
Az LPS nem stratégia, kizárólag döntéstámogató és kockázatkezelési eszköz.
Fő funkciók:
Automatikus Long / Short pozíció megjelenítés
Entry, Stop Loss és Take Profit szintek vizuális ábrázolása
Valós idejű pozícióméret számítás
Állítható Risk/Reward arány
Teljesen testreszabható színek, átlátszóság és vonalstílus
Letisztult chart label (irány, RR, lot méret)
Egyszerre csak egy aktív pozíció box
Pozícióméretezési logika:
A PulseWire belsőleg egységekben (units) számol, nem bróker-specifikus LOT-okban.
Ennek kezelésére az LPS egy „Units per 1 Lot” beállítást használ.
Példák:
Forex standard lot: 100000
Arany (XAUUSD): 1 vagy 100 (brókertől függ)
Indexek (pl. NAS100): 1
Az indikátor először PulseWire egységekben számol, majd ezt átváltja LOT-ra a megadott szorzó segítségével.
A kijelzett LOT méret 0.01-re van kerekítve.
Stop Loss logika:
A Stop Loss szint a kiválasztott korábbi gyertya high vagy low értékéből kerül meghatározásra.
Nagyobb bar-back érték:
távolabb helyezi a stopot
azonos kockázat mellett kisebb pozícióméretet eredményez
Ajánlott felhasználás:
Manuális, diszkrecionális kereskedés
Kockázatkezelés és pozícióméretezés
Trade tervezés
Oktatási célok
Fontos megjegyzések:
Az indikátor nem köt automatikusan
Alapértelmezetten nincs alert vagy automatizmus
A LOT és contract méret brókerenként eltérhet
Kereskedés előtt mindig ellenőrizd a pontos LOT / contract specifikációt a brókerednél
Indicator
Indicator
EMA Cross + RSI + ADX - Autotrade Strategy V2Overview
A versatile trend-following strategy combining EMA 9/21 crossovers with RSI momentum filtering and optional ADX trend strength confirmation. Designed for both cryptocurrency and traditional futures/options markets with built-in stop loss management and automated position reversals.
Key Features
Multi-Market Compatibility: Works on both crypto futures (Bitcoin, Ethereum) and traditional markets (NIFTY, Bank NIFTY, S&P 500 futures, equity options)
Triple Confirmation System: EMA crossover + RSI filter + ADX strength (optional)
Automated Risk Management: 2% stop loss with wick-touch detection
Position Auto-Reversal: Opposite signals automatically close and reverse positions
Webhook Ready: Six distinct alert messages for automation (Entry Buy/Sell, Close Long/Short, SL Hit Long/Short)
Performance Metrics
NIFTY Futures (15min): 50%+ win rate with ADX filter OFF
Crypto Markets: Requires extensive backtesting before live deployment
Optimal Timeframes: 15-minute to 1-hour charts (patience required for higher timeframes)
Strategy Logic
Entry Signals:
LONG: EMA 9 crosses above EMA 21 + RSI > 55 + ADX > 20 (if enabled)
SHORT: EMA 9 crosses below EMA 21 + RSI < 45 + ADX > 20 (if enabled)
Exit Signals:
Opposite EMA crossover (auto-closes current position)
Stop loss hit at 2% from entry price (tracks candle wicks)
Technical Indicators:
Fast EMA: 9-period (short-term trend)
Slow EMA: 21-period (primary trend)
RSI: 14-period with 55/45 thresholds (momentum confirmation)
ADX: 14-period with 20 threshold (trend strength filter - optional)
Market-Specific Settings
Traditional Markets (NIFTY, Bank NIFTY, S&P Futures, Options)
Recommended Settings:
ADX Filter: Turn OFF (less choppy, cleaner trends)
Timeframe: 15-minute chart
Win Rate: 50%+ on NIFTY Futures
Why No ADX: Traditional markets have more institutional participation and smoother price action, making ADX unnecessary
Cryptocurrency Markets (BTC, ETH, Altcoins)
Recommended Settings:
ADX Filter: Turn ON (ADX > 20)
Timeframe: 15-minute to 1-hour
Extensive backtesting required before live trading
Why ADX: Crypto markets are highly volatile and prone to false breakouts; ADX filters low-quality chop
Best Practices
✅ Backtest thoroughly on your specific instrument and timeframe
✅ Use larger timeframes (1H, 4H) for higher quality signals and better risk/reward
✅ Adjust RSI thresholds based on market volatility (try 52/48 for more signals, 60/40 for fewer but stronger)
✅ Monitor ADX effectiveness - disable for traditional markets, enable for crypto
✅ Proper position sizing - adjust default_qty_value based on your capital and instrument price
✅ Paper trade first - test for 2-4 weeks before risking real capital
Risk Management
Fixed 2% stop loss per trade (adjustable)
Stop loss tracks candle wicks for accurate execution
Positions auto-reverse on opposite signals (no manual intervention needed)
0.075% commission built into backtest (adjust for your broker)
Customization Options
All parameters are adjustable via inputs:
EMA periods (default: 9/21)
RSI length and thresholds (default: 14-period, 55/45 levels)
ADX length and threshold (default: 14-period, 20 threshold)
Stop loss percentage (default: 2%)
Webhook Automation
This strategy includes six distinct alert messages for automated trading:
"Entry Buy" - Long position opened
"Entry Sell" - Short position opened
"Close Long" - Long position closed on opposite crossover
"Close Short" - Short position closed on opposite crossover
"SL Hit Long" - Long stop loss triggered
"SL Hit Short" - Short stop loss triggered
Compatible with Delta Exchange, Binance Futures, 3Commas, Alertatron, and other webhook platforms.
Important Notes
⚠️ Crypto markets require extensive backtesting - volatility patterns differ significantly from traditional markets
⚠️ Higher timeframes = better results - 15min works but 1H/4H provide cleaner signals
⚠️ ADX toggle is critical - OFF for traditional markets, ON for crypto
⚠️ Not financial advice - always conduct your own research and use proper risk management
⚠️ Past performance ≠ future results - backtest results may not reflect live trading conditions
Disclaimer
This strategy is for educational and informational purposes only. Trading futures and options involves substantial risk of loss. Always backtest thoroughly, start with paper trading, and never risk more than you can afford to lose. The author assumes no responsibility for any trading losses incurred using this strategy. Strategy
% / ATR Buy, Target, Stop + Overlay & P/L% / ATR Buy, Target, Stop + Overlay & P/L
This tool combines volatility‑based and fixed‑percentage trade planning into a single, on‑chart overlay—with built‑in profit‑and‑loss estimates. Toggle between ATR or percentage modes, plot your Buy, Target and Stop levels, and see the dollar gain or loss for a specified position size—all in one interactive table and chart display.
NOTE: To activate plotted lines, price labels, P/L rows and table values, enter a Buy Price greater than zero.
What It Does
Mode Toggle: Choose between “ATR” (volatility‑based) or “%” (fixed‑percentage) calculations.
Buy Price Input: Manually enter your entry price.
ATR Mode:
Target = Buy + (ATR × Target Multiplier)
Stop = Buy − (ATR × Stop Multiplier)
Percentage Mode:
Target = Buy × (1 + Target % / 100)
Stop = Buy × (1 – Stop % / 100)
P/L Estimates: Specify a dollar amount to “invest” at your Buy price, and the script calculates:
Gain ($): Profit if Target is hit
Loss ($): Cost if Stop is hit
Visual Overlay: Draws horizontal lines for Buy, Target and Stop, with optional price labels on the chart scale.
Interactive Table: Displays Buy, Target, Stop, ATR/timeframe info (in ATR mode), percentages (in % mode), and P/L rows.
Customization Options
Line Settings:
Choose color, style (solid/dashed/dotted), and width for Buy, Target, Stop lines.
Extend lines rightward only or in both directions.
Table Settings:
Position the table (top/bottom × left/right).
Toggle individual rows: Buy Price; Target (multiplier or %); Stop (multiplier or %); Target ATR %; Stop ATR %; ATR Time Frame; ATR Value; Gain ($); Loss ($).
Customize text colors for each row and background transparency.
General Inputs:
ATR length and optional ATR timeframe override (e.g. use daily ATR on an intraday chart).
Target/Stop multipliers or percentages.
Dollar Amount for P/L calculations.
How to Use It for Trading
Plan Your Entry: Enter your intended Buy Price and position size (dollar amount).
Select Mode: Toggle between ATR or % mode depending on whether you prefer volatility‑based or fixed offsets.
Assess R:R and P/L: Instantly see your Target, Stop levels, and potential profit or loss in dollars.
Visual Reference: Lines and price labels update in real time as you tweak inputs—ideal for live trading, backtesting or trade journaling.
Ideal For
Traders who want both volatility‑based and percentage‑based exit options in one tool
Those who need on‑chart P/L estimates based on position size
Swing and intraday traders focused on objective, rule‑based trade management
Anyone who uses ATR for adaptive stops/targets or fixed percentages for simpler exits Indicator
NQ Position Size CalculatorNQ Position Size Line Calculator is designed specifically for Nasdaq 100 futures (NQ) and micro futures (MNQ) traders who want to maintain disciplined risk management. This visual tool eliminates the guesswork from position sizing by displaying distance lines and contract calculations directly on your chart.
The indicator creates horizontal lines at 10-tick intervals from your stop loss level, showing you exactly how many contracts to trade at each distance to maintain your predetermined risk amount. Whether you're trading regular NQ contracts or micro MNQ contracts, this calculator ensures you never risk more than intended while providing instant visual feedback for optimal position sizing decisions.
How to Use the Indicator
Step 1: Configure Your Settings
Stop Loss Price: Enter your exact stop loss level (e.g., 20000.00)
Risk Amount ($): Set your maximum dollar risk per trade (e.g., $500)
Contract Type: Choose between:
NQ (Regular): $5 per tick - for larger accounts
MNQ (Micro): $0.50 per tick - for smaller accounts or conservative sizing
Display Options:
Max Lines: Number of distance lines to show (default: 30)
Show Labels: Toggle tick distance and contract count labels
Line Color: Customize the color of distance lines
Label Size: Choose tiny, small, or normal label sizes
Step 2: Read the Visual Display
Once configured, the indicator displays:
Stop Loss Line:
Thick yellow line marking your exact stop loss level
Yellow label showing the stop loss price
Distance Lines:
Dashed red lines at 10-tick intervals above and below your stop loss
Lines appear on both sides for long and short position planning
Labels (if enabled):
Green labels (right side): For long positions above your stop loss
Red labels (left side): For short positions below your stop loss
Format: "20T 5x" means 20 ticks distance, 5 contracts maximum
Step 3: Use the Information Tables
The indicator provides two helpful tables:
Position Size Table (top-right):
Shows common tick distances (10, 20, 40, 80, 160 ticks)
Displays risk per contract at each distance
Contract count for your specified risk amount
Total risk with rounded contract numbers
Settings Table (bottom-right):
Confirms your current risk amount
Shows selected contract type
Displays current settings for quick reference
Step 4: Apply to Your Trading
For Long Positions:
Look at the green labels on the right side of your chart
Find your desired entry level
Read the label to see: distance in ticks and maximum contracts
Example: "30T 8x" = 30 ticks from stop, buy 8 contracts maximum
For Short Positions:
Look at the red labels on the left side of your chart
Find your desired entry level
Read the label for tick distance and contract count
Example: "40T 6x" = 40 ticks from stop, sell 6 contracts maximum
Step 5: Trading Execution
Before Entering a Trade:
Identify your stop loss level and input it into the indicator
Choose your entry point by looking at the distance lines
Note the contract count from the corresponding label
Verify the risk amount matches your trading plan
Execute your trade with the calculated position size
Risk Management Features:
Contract rounding: All position sizes are rounded down (never up) to ensure you don't exceed your risk limit
Zero position filtering: Lines only show where position size is at least 1 contract
Dual-sided display: Plan both long and short opportunities simultaneously
Indicator
Statistical Trailing Stop [LuxAlgo]The Statistical Trailing Stop tool offers traders a way to lock in profits in trending markets with four statistical levels based on the log-normal distribution of volatility.
The indicator also features a dashboard with statistics of all detected signals.
🔶 USAGE
The tool works out of the box, traders can adjust the data used with two parameters: data & distribution length.
By default, the tool takes volatility measures of groups of 10 candles, and statistical measures of the last 100 of these groups then traders can adjust the base level to use as trailing, the larger the level, the more resistant the tool will be to moves against the trend.
🔹 Base Levels
Traders can choose up to 4 different levels of trailing, all based on the statistical distribution of volatility.
As we can see in the chart above, each higher level is more resistant to market movements, so level 0 is the most reactive and level 3 the least.
It is up to the trader to determine the best level for each underlying, time frame and market conditions.
🔹 Dashboard
The tool provides a dashboard with the statistics of all trades, making it very easy to assess the performance of the parameters used for any given market.
As we can see on the chart, all Daily BTC signals with default parameters but different base levels, level 2 is the best performing of all four, giving a positive expectation of $2435 per trade, taking into account all long and short trades.
Of note are the long trades with a win rate of 76.47% and a risk-to-reward of 3.34, giving a positive expectation of $4839 per trade, with winners having an average duration of 210 days and losers 32 days.
This, compared to short trades with negative expectation, speaks to the uptrend bias of this particular market.
🔶 SETTINGS
Data Length: Select how many bars to use per data point
Distribution Length: Select how many data points the distribution will have
Base Level: Choose between 4 different trailing levels
🔹 Dashboard
Show Statistics: Enable/disable dashboard
Position: Select dashboard position
Size: Select dashboard size
Indicator
