Opening Hour Lines + Touch StatsDescription:
Plots horizontal price levels at the open of up to 8 configurable intraday hours (default: 18:00, 00:00, 03:00, 06:00, 07:00, 08:00 NY time) and tracks how often RTH price returns to touch each level — split across two windows.
Each level label shows:
| |
Example: 0600 | 68% 86/126 | 81% 102/126
Features:
Up to 8 hour levels, each fully configurable (time, color, style, thickness, label)
Touch stats tracked independently for the AM session (09:30–12:00) and the full RTH session (09:30–16:00)
Configurable stat lookback (default 126 days) and display lookback (default 5 lines)
Lines extend from the hour open through the RTH close (16:00), then freeze
Stats commit and reset at the 18:00 Globex open each day
Hours 7 and 8 (09:00, 09:30) available as display-only lines with no stat tracking
Designed for ES / NQ CME Globex on 1m–3m charts
Use case: Quickly assess how likely price is to revisit overnight and pre-market reference levels during the morning session versus the full trading day — useful for fade setups, target placement, and level confluence analysis. Indicator
Indicator
CUSUM Structural Break DetectorDescription
This indicator implements the symmetric CUSUM (Cumulative Sum) filter from Marcos López de Prado's Advances in Financial Machine Learning (Chapter 2) as an overlay on any chart. It detects structural breaks in the price process by accumulating log-return deviations against a dynamic, volatility-adaptive threshold.
What it does
Most chart indicators sample market data at fixed time intervals. The CUSUM filter takes a different approach: it only flags an event when the price process has accumulated enough cumulative deviation from its baseline to indicate that something structurally meaningful has changed. This is the event-based sampling method used in quantitative finance before applying machine learning models to market data.
The filter maintains two accumulators:
S⁺ = max(0, S⁺_prev + log_return)
S⁻ = min(0, S⁻_prev + log_return)
An upward structural break is flagged when S⁺ ≥ h. A downward break is flagged when S⁻ ≤ −h. Both accumulators reset to zero on trigger — this prevents consecutive events clustering in the same trend. The threshold h is adaptive:
h = multiplier × realized_volatility
where realized volatility is estimated as a rolling standard deviation of log returns. This makes the filter regime-aware: in high-volatility periods the threshold widens automatically, requiring larger price moves before flagging an event.
Visual output
▲ (teal, below bar) — upward structural break. The positive accumulator has crossed h.
▼ (amber, above bar) — downward structural break. The negative accumulator has crossed −h.
Volatility bands — ±h expressed in price units around close. Shows the live threshold.
Background shading (faint red) — appears when realized σ exceeds 1.5× its rolling median, indicating a high-volatility regime.
Info table (bottom right) — shows current σ, current h, regime state, and cumulative event count.
How to use it
These markers are not buy or sell signals. They are sampling points — moments where the price process has undergone a statistically meaningful shift. In the AFML pipeline they serve as the input to triple-barrier labeling: for each flagged event, you define a forward price window with a profit-take barrier, a stop-loss barrier, and a timeout horizon, and record which barrier is hit first. That outcome becomes the training label for a supervised ML model.
Use the markers to identify which historical moments would have been worth labeling and studying. Use the alerts (JSON format, compatible with any webhook receiver) to log events in real time as they occur.
Parameters
Volatility lookback (default 20): Rolling window for realized volatility estimation. Shorter values react faster to volatility changes; longer values produce a smoother threshold.
Threshold multiplier k (default 1.0): Controls sensitivity. Higher values produce fewer, higher-confidence events. For daily equity bars, 1.5–2.0 is recommended. For intraday data, 0.7–0.8. For crypto, 1.5 or higher given baseline volatility.
Min bar gap (default 5): Minimum number of bars required between consecutive events. Prevents clustering on noisy instruments.
Show volatility bands (default on): Toggles the ±h overlay.
Alert format
Each event triggers a PulseWire alert with a structured message containing the ticker, direction, close price, realized volatility, threshold value, and bar timestamp. Configure alert conditions in the PulseWire alert manager after adding the indicator to your chart.
Reference
López de Prado, M. (2018). Advances in Financial Machine Learning. Wiley. Chapter 2: Financial Data Structures.
Page, E.S. (1954). Continuous inspection schemes. Biometrika, 41(1/2), 100–115. Indicator
Indicator
Indicator
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
Custom trade checklist + pos calcThis script is an all-in-one trade management dashboard designed to sit directly on your PulseWire chart. It replaces the need for external calculators, sticky notes, or mental math by combining a visual position tool with a customizable pre-trade checklist.
Here is a breakdown of exactly what this script does, section by section:
1. The Interactive Position & Risk Tool
When you add the script to your chart, it turns your mouse into a drawing tool. You click three times to set your Entry, Target (Take Profit), and Stop Loss.
Once placed, the script automatically:
Draws the Levels: It plots your Entry (Gray), Target (Green), and Stop Loss (Red) as clean lines on the chart.
Finds the 50% Mark: It instantly calculates and draws a yellow dashed line exactly halfway between your Entry and your Target.
Calculates Position Size: Based on the Account Size and Risk Percentage you enter in the settings (default is $10,000 and 1% risk), it calculates exactly how many units/shares you need to buy to keep your risk perfectly managed.
Calculates Risk/Reward (R/R): It divides your potential profit distance by your stop loss distance to give you your exact R/R ratio.
2. The Pre-Trade Checklist
In the indicator settings, you have a built-in checklist with up to three customizable rules (e.g., "HTF Bias Confirmed", "No Major News").
You can toggle which rules are active for a specific trade.
You can change their status using a dropdown menu (from a neutral ⚪ to a completed ✅ or failed ❌).
3. The Live Dashboard (The Table)
The script takes all of the information above and neatly packages it into a professional-looking table in the corner of your chart. This table displays:
The Current Time: So if you screenshot your chart, you have a timestamped record of the setup.
Your Checklist Status: A visual rundown of your rules and whether they are met.
A "Readiness" Progress Bar: As you mark items with a ✅, the script calculates your completion percentage. The row changes color from Red to Orange, and finally to Green when you are 100% ready.
Trade Stats: It displays your calculated Risk/Reward (turning green if it's over 1.5R, red if it's under) and your exact Position Size.
4. The Execution Alert
Once you go into your settings and mark every single active checklist item as ✅, the script triggers a background condition. If you have PulseWire alerts set up for this indicator, it will immediately fire off a notification saying: "All trade criteria met. Ready to execute!"
In short: It is designed to force you to slow down, verify your rules, and mathematically size your position before you ever click the buy or sell button. Indicator
Rolling KPSS Statistic [LuxAlgo]The Rolling KPSS Statistic indicator evaluates the stationarity of price action within a rolling window using the Kwiatkowski-Phillips-Schmidt-Shin (KPSS) test. This tool helps traders identify whether the current market environment is ranging, trending, or undergoing a structural regime shift by providing a continuous statistical measure of mean reversion.
🔶 USAGE
The indicator is designed to distinguish between stationary price action (where price fluctuates around a mean or trend) and non-stationary price action (where price exhibits random walk or breakout behavior). By applying a rolling window calculation, it provides a real-time assessment of market stability.
The script offers two primary modes of operation tailored to different market conditions:
🔹 Level Mode
This mode tests for stationarity around a constant mean. It is the optimal setting for detecting ranging or mean-reverting environments. When the KPSS statistic is low in this mode, it suggests the market is staying within a defined horizontal corridor.
🔹 Trend Mode
This mode tests for stationarity around a linear trend. It is used to identify if the market is moving consistently within a trending channel. A low KPSS value here indicates that while the price is moving up or down, it is doing so in a mathematically stable "stationary" trend rather than an erratic or parabolic one.
🔶 DETAILS
The KPSS test operates on the null hypothesis that the series is stationary. Unlike other unit root tests (like the Augmented Dickey-Fuller test), a low value in KPSS indicates stationarity, while a high value suggests the presence of a unit root (non-stationarity).
🔹 Critical Levels
The indicator plots three significance thresholds: 10%, 5%, and 1%.
KPSS < 5% Level: The market is considered stationary. In "Level" mode, this implies a Range. In "Trend" mode, this implies a stable Trend.
KPSS > 5% Level: The null hypothesis is rejected. The market is "Non-Stationary," suggesting a breakout, a trend reversal, or a transition into a random walk state.
KPSS > 1% Level: This indicates a highly significant deviation from stationarity, often seen during impulsive market expansions.
🔹 Visual Feedback
The indicator uses a Viridis gradient theme. Brighter colors (yellow/green) represent stationary, mean-reverting behavior, while darker colors (purple/blue) represent non-stationary or trending behavior. A real-time dashboard is also included to provide an immediate summary of the current market state.
🔶 SETTINGS
🔹 Main Settings
Window Length: The number of bars used for the rolling window. The default of 100 provides a balanced statistical lookback for most timeframes.
Source: The price data used for the calculation (default is Close).
Test Type: Select between "Level" (for ranges) or "Trend" (for trending stationarity).
Newey-West Bandwidth: A lag truncation parameter used to account for serial correlation in the residuals.
🔹 Visuals & Dashboard
Show Critical Levels: Toggles the visibility of the 10%, 5%, and 1% dashed lines.
Dashboard: Enables or disables the on-screen information table.
Position/Size: Controls the location and scale of the dashboard on the chart.
Indicator
Multi-Leverage VAR/VaG IndicatorHere's why I developed this indicator: I love leverage but most people don't use leverage correctly. This indicator helps you understanding whether leverage is advantageous and how much should be used.
Standard VAR calculations assume linear scaling (2x leverage = 2x risk), which is wrong for leveraged ETFs. Also, most VaR indicators show risk without comparing it to potential reward. This one tells you how do you quantify whether current market conditions are friendly or hostile to leveraged positions?
To do this, we calculate both the downside risk (VAR), upside potential (VaG), and their relationship across different leverage levels.
PROBLEMS THIS INDICATOR SOLVES
THE LEVERAGE SCALING FALLACY
Problem: Traders assume 3x leverage means 3x the risk.
Reality: Due to volatility decay and daily rebalancing, leveraged ETFs don't scale linearly. A 3x ETF can lose MORE than 3x in high downside volatility markets or LESS than 3x during up trending markets.
Solution: This indicator simulates actual leveraged ETF mechanics by applying leverage to each daily return and compounding over your holding period.
THE REGIME BLINDNESS PROBLEM
Problem: Traders use the same leverage in all market conditions.
Reality: Trending, low-volatility markets favor leverage. Choppy, high-volatility markets penalize leverage through volatility drag.
Solution: The VaG/|VAR| ratio quantifies leverage efficiency. When the leverage VaG/|VAR| is higher than the 1x VaG/|VAR|, then leverage is friendly .
THE RISK-WITHOUT-CONTEXT PROBLEM
Problem: Knowing your maximum loss doesn't tell you if that risk is worth taking.
Reality: A -10% VAR might be acceptable if VaG is +30%, but terrible if VaG is only +8%.
Solution: I calculate both downside and upside at the same confidence level for complete risk/reward context.
HOW THIS INDICATOR IS USEFUL TO INVESTORS
Determine optimal leverage level for current market conditions
Identify when to scale up or reduce leveraged positions based on regime changes
Calculate dollar risk on any account size for proper position sizing
Understand true risk of leveraged ETFs beyond the "3x" label
Detect transitions between leverage-friendly and leverage-hostile regimes
CORE METHODOLOGY: Historical simulation with daily rebalancing
Unlike parametric VAR (assumes normal distribution) or Monte Carlo (generates synthetic scenarios), this uses historical simulation - what actually happened in the past.
Calculate daily returns from closing prices
Simulate leveraged ETF behavior with daily rebalancing - apply leverage to each daily return, compound over the holding period, and cap losses at -100% (ETFs can't go negative)
Create a distribution by sliding the holding period window across the lookback period (252-day lookback with 21-day holding = 232 scenarios)
Sort all outcomes and extract percentiles: VAR = lower tail (e.g., 5th percentile at 95% confidence), VaG = upper tail (e.g., 95th percentile)
Calculate efficiency ratio: VaG / |VAR|
This tells you: for every dollar of downside risk, how many dollars of upside potential do you get?
HOW TO USE THIS INDICATOR
Lookback Period (default: 252 days) - Longer = more data but slower to adapt; Shorter = more responsive but less reliable
Holding Period (default: 21 days) - Match to your timeframe: 5-10 days (day traders), 21-42 days (swing traders), 63-126 days (position traders)
Confidence Level (default: 95%) - 90% for typical outcomes, 95% for balanced view, 99% for extreme tail risk
Leverage Levels (default: 1x, 2x, 3x) - Customize to your trading, supports decimals like 1.5x
INTERPRETING THE TABLE:
Lev = Leverage multiplier
VAR (%) = Maximum expected loss over holding period
VaG (%) = Minimum expected gain over holding period
VaG/|VAR| = Leverage efficiency ratio
VAR on $10k = Dollar loss on $10,000 position
EXAMPLE INTERPRETATION
This QQQ chart demonstrates the indicator's power to identify leverage regimes.
Current metrics (table):
1x: VAR -3.21%, VaG +21.58%, Ratio 6.73
2x: VAR -6.79%, VaG +46.58%, Ratio 6.86
3x: VAR -10.71%, VaG +75.26%, Ratio 7.02
This means:
Ratios above 6.5 are outstanding - upside is nearly 7x the downside at all leverage levels
Backwardation pattern: the ratio IMPROVES with more leverage (6.73 → 7.02), indicating strong trending conditions favor higher leverage
VAR remains very manageable even at 3x (-10.71% on a 55-day hold)
At 3x leverage, you risk $1,071 to potentially gain $7,526 on $10k - exceptional risk/reward. And understanding risk/reward is one of the most important points here.
Trade smart. Manage risk. Know your regime.
And let me know if you have any questions or suggestions.
- Henrique Centieiro Indicator
Indicator
Market Entropy ScannerMarket Entropy Scanner (MES)
An Adaptive Trend and Reversal Analysis System
Where Volatility Dynamics Meet Signal Confluence.
🎓 THEORETICAL FOUNDATION
The Market Entropy Scanner (MES) is an integrated technical analysis system designed to identify high-probability trend continuations and mean-reversion opportunities. Its core philosophy is based on the principle of confluence—that the most reliable signals occur when multiple, uncorrelated analytical concepts align.
The MES architecture is built upon a hierarchy of specialized engines that work in concert to score market conditions, from the macro trend down to the microstructure of individual candles.
Pillar 1: Dynamic Volatility Scaling (DVS) Engine
The market is not static; it transitions between states of low and high volatility. The DVS engine is the adaptive brain of the MES. It continuously measures the market's current volatility against a longer-term baseline using one of four statistical methods (including the advanced Garman-Klass model). The resulting ratio dynamically tunes the indicator's core parameters, such as the Supertrend and RSI lengths.
In high-volatility (trending) environments, parameters become shorter for faster responsiveness.
In low-volatility (ranging) environments, parameters become longer to filter out noise and prevent false signals.
Pillar 2: Zero-Lag Supertrend Core
The system's foundation for trend direction is a Zero-Lag Supertrend. By using a Zero-Lag EMA (ZLEMA) as its baseline, it reduces the inherent lag of traditional Supertrend indicators, providing more timely trend-flip signals. Crucially, it also calculates "Extremity Zones"—dynamic thresholds measured in ATR multiples away from the Supertrend line. Price action that enters these zones is considered statistically over-extended, a primary condition for enabling reversal signals.
Pillar 3: Wick Pressure & Divergence Kernels
To identify reversals, MES quantifies exhaustion and momentum loss:
Wick Pressure Kernel: This engine analyzes candle microstructure, measuring the ratio of upper and lower wicks to the candle's total range. A high positive score indicates strong buying pressure (long lower wicks), while a high negative score indicates selling pressure (long upper wicks). This provides a quantifiable measure of price rejection.
Divergence Engine: The system scans for classical divergences between price pivots and RSI pivots. A valid divergence is only confirmed if it occurs while price is within an Extremity Zone, filtering for divergences that happen at points of maximum trend exhaustion.
Pillar 4: Footprint Intelligence Layer (Optional)
For maximum analytical depth, MES can integrate tick-level footprint data. When enabled, this layer provides two key enhancements:
Delta-Enhanced Pressure: The Wick Pressure score is blended with the bar's real delta (net difference between buying and selling volume), grounding the candle analysis with confirmed order flow data.
Structural Confluence: The Point of Control (POC) and Value Area (VA) for each bar are displayed, providing key intra-bar levels of support and resistance that can be used to validate signals.
Pillar 5: Integrated Trade & Performance Module
MES is a complete system that includes a full suite of trade management tools. It features an ATR-based exit strategy with defined profit targets and stop-losses, a sophisticated trailing stop mechanism, and the option for intra-bar exits for maximum precision. A built-in performance tracker logs all simulated trades, providing key metrics like Win Rate and Profit Factor directly on the dashboard.
🔧 COMPREHENSIVE INPUT SYSTEM
🧬 DVS Engine
Enable DVS: Master switch for the Dynamic Volatility Scaling engine. When enabled, it adapts key parameters based on market volatility. When disabled, the indicator uses the fixed "Base" values.
Volatility Method: Selects the formula for volatility estimation. Options include ATR Ratio (simple), Parkinson (efficient), Garman-Klass (statistically advanced), and Ensemble (most stable median of all three).
Volatility Memory: The lookback period for establishing the baseline average volatility.
DVS Smoothing: Applies an EMA to the final DVS ratio to ensure smooth transitions between regimes.
Sensitivity: A multiplier controlling the intensity of the adaptation. >1.0 exaggerates the effect; <1.0 dampens it.
⚡ ZeroLag Supertrend
Base Length: The base lookback period for the Supertrend, used as the 'slow' setting in low-volatility conditions.
Base Multiplier: The ATR multiplier that sets the width of the Supertrend channel. Higher values are less sensitive; lower values are more responsive.
Extremity Threshold (ATR): Defines how far price must move from the Supertrend line (in ATR multiples) to be flagged as 'extreme', enabling reversal signals.
Show Extremity Zones: Toggles the shaded boxes that visualize the overbought/oversold zones.
🕯️ Wick Pressure Kernel
Pressure Smoothing: The EMA smoothing period for the Wick Pressure calculation, creating a more stable reading.
Signal Threshold: The minimum normalized wick pressure value required to contribute to the signal score, acting as a quality filter.
📐 Divergence Engine
Pivot Lookback: The number of bars left and right to confirm a valid price/RSI pivot. Higher values find more significant swing points.
RSI Length: The base lookback period for the RSI. This value is adapted by the DVS engine.
🔬 Footprint
Enable Footprint: Master switch for all footprint features. Requires a data plan that supports it.
Ticks per Row: Sets the price resolution for the footprint profile.
Value Area %: The percentage of volume contained within the Value Area.
Delta Blend into Wick: Controls the influence of real footprint delta on the Wick Pressure calculation (0.0 = none, 0.8 = high).
Show POC/VA: Toggles visibility for the Point of Control and Value Area lines.
🎯 Exit & Targets
Show Target/Stop Levels: Toggles visibility of the TP/SL lines for an active trade.
Target/Stop ATR Multiple: Sets the profit target and initial stop-loss distance as a multiple of the 14-period ATR at entry.
Trailing Stop ATR: The ATR multiple for the trailing stop distance.
Trail Activation (% of target): The percentage of profit (from entry to target) that must be achieved before the trailing stop becomes active.
Intra-Bar Exits: If enabled, checks for exits on every tick. If disabled, exits are processed only on bar close.
🎨 ADVANCED VISUAL SYSTEM
Core Trend & Channel
Zero-Lag Supertrend: The main line on the chart, colored bullish or bearish to indicate the current trend direction.
Adaptive Channel: The upper and lower bands of the Supertrend are plotted with a transparent fill, creating a clear visual channel that expands and contracts with volatility.
Regime Background: The chart background is subtly shaded based on the trend direction and intensifies when price enters an Extremity Zone.
Reversal & Pressure Visuals
Extremity Zones: Shaded boxes appear in real-time when price becomes statistically
over-extended, visually highlighting potential reversal areas.
Divergence Labels: A "DIV" label appears below bullish divergences and above bearish divergences, pinpointing the exact moment of momentum loss.
Wick Pressure Bar Coloring: Chart bars are colored based on the strength of the smoothed Wick Pressure, providing an immediate, intuitive sense of buying (bullish color) or selling (bearish color) pressure.
Footprint & Trade Management Visuals
POC & Value Area: When enabled, the POC, VAH, and VAL are plotted as steplines for each bar, offering key intra-bar structural levels.
Target & Stop Levels: For any active trade, the entry price, profit target, and stop-loss are clearly plotted as horizontal lines, providing an objective view of the trade's parameters. The stop-loss line changes color when the trailing stop is activated.
📊 INSTITUTIONAL-GRADE DASHBOARD
The dashboard provides a comprehensive, at-a-glance summary of every component of the system.
DVS Engine Section: Displays the real-time Volatility Ratio, the current Volatility Regime (High, Normal, Low), and the dynamically adapted lengths for the Supertrend and RSI.
Signals Section: Shows the current trend direction, the distance of price from the Supertrend (in ATRs), the current Wick Pressure and RSI values, and the calculated scores (0-100%) for potential Long and Short reversal signals.
Status Section: Confirms the current market zone (Overbought, Oversold), any active divergences, and the status of the signal cooldown timer.
Footprint Section: If active, displays the bar's real-time Delta and Point of Control price.
Position & Performance Section: If tracking is enabled, shows the current position (Flat, Long, Short), unrealized P&L, and key performance metrics like Total Trades, Win Rate (%), Profit Factor, and Expectancy (%).
Master Status Bar: A text field at the bottom provides a clear, human-readable summary of the most important current event (e.g., "▲ REV BUY SIGNAL", "⚠ OVERBOUGHT ZONE").
🎯 SIGNAL GENERATION LOGIC
MES utilizes a sophisticated scoring system for its primary reversal signals. A signal is not triggered by a single event but by the accumulation of a high score based on the confluence of multiple conditions.
Scoring System Breakdown:
Base Score: A significant score is awarded if price is in an Extremity Zone (Oversold for Longs, Overbought for Shorts). This is the foundational requirement.
Wick Pressure Score: The score increases if the Wick Pressure is strong and in the desired direction (e.g., high positive pressure for a Long signal).
Divergence Score: The score receives a substantial boost if a confirmed Divergence is present. The strength of the divergence also contributes.
Momentum Confirmation: A smaller score is added if the ZLEMA baseline has flattened or started to turn, indicating the primary trend is losing momentum.
Footprint Confirmation (Optional): If enabled, the score gets an additional boost if the real-time Delta supports the signal direction.
A final signal is generated only if the total score exceeds a predefined threshold (e.g., 45%) and the signal cooldown period has passed, ensuring only high-conviction setups are flagged.
⚖️ RESPONSIBLE USAGE AND LIMITATIONS
Not a Standalone System: MES is a powerful decision-support tool. It should be used in conjunction with sound risk management, position sizing, and an understanding of the broader market context.
Parameter Optimization: While the DVS engine provides robust adaptation, optimal performance may still require tuning of base parameters (like the Supertrend Multiplier or Extremity Threshold) to suit specific assets and timeframes.
Past Performance: The performance metrics displayed are based on a simulation of past data. This is not a guarantee of future results. Market conditions change, and the system's effectiveness can vary.
Data Requirements: The optional Footprint layer requires a premium data feed. The indicator will function fully without it but will lack the delta-enhancement features.
🔮 CONCLUSION
The Market Entropy Scanner (MES) is a comprehensive analysis tool designed for the discerning trader. It moves beyond static indicators by integrating a dynamic, self-adapting engine that adjusts to changing market conditions in real-time. By systematically scoring the confluence of trend exhaustion, momentum divergence, and candle pressure, it provides a clear, objective, and data-driven framework for identifying potential market turning points.
With its integrated exit logic and performance tracking, MES offers a complete, self-contained system for developing and testing structured trading approaches.
— Dskyz, Trade with insight. Trade with anticipation. (All day, Everyday) Indicator
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