EMA Spread Exhaustion DetectorEMA Spread Exhaustion – Reversal Scalper's Tool
Identifies trend exhaustion for high-probability counter-trend entries. Triggers when EMA(4/9/20) stack is fully aligned and spread stretches beyond ±ATR threshold. Ideal confluence for TDI hooks + strong rejection candles on 15s charts. Visual markers, fills, and alerts for quick scalps.
Meanreversion
D2E + Bands (Distance to EMA)D2E (Distance to Daily EMA)
Concept and Underlying Calculation This indicator is built on the theory of Mean Reversion. It operates on the premise that price acts like a rubber band; while it can stretch away from its average value, it rarely stays at extreme extensions for long periods without snapping back (retracement) or pausing to let the average catch up (consolidation).
Unlike standard deviations (Bollinger Bands) or ATR channels, this script uses Fixed Percentage Thresholds relative to a Multi-Timeframe Daily EMA.
How it Works (The Math)
Multi-Timeframe Data: The script specifically requests the Daily (1D) Exponential Moving Average (default length 20) regardless of the timeframe you are currently viewing. This allows day traders on a 5-minute or 15-minute chart to see their position relative to the macro Daily trend.
Distance Calculation: It calculates the variance between the current Close price and the Daily EMA using the formula: 100 * (Close - DailyEMA) / DailyEMA.
Projected Zones: It plots theoretical bands at user-defined percentage distances (e.g., 3% and 6%) above and below the Daily EMA.
How to Use
Trend Extension: When price interacts with the "Threshold %" (Yellow), it indicates the asset is becoming overextended relative to its daily mean. This often serves as a take-profit target for trend followers.
Reversal Signals: Interaction with the "Extreme Threshold %" (Red) suggests a statistically significant deviation, often signaling an exhaustion point where a mean-reversion trade (returning to the EMA) becomes probable.
The Dashboard: A dynamic table is included to provide real-time data on the exact dollar amount and percentage distance from the EMA, color-coded to match the severity of the extension.
Features and Settings
EMA Length: Customizable lookback period for the Daily EMA (Default: 20).
Thresholds: Adjustable percentage settings for standard and extreme deviations.
Visuals: Toggleable threshold lines and a customizable on-screen dashboard (position and size).
Alerts: Pre-configured alert conditions for crossing both standard and extreme thresholds.
Disclaimer This tool is for informational purposes only and does not constitute financial advice. Past performance of mean reversion strategies does not guarantee future results.
Volumetrix Mean Reversion [by Oberlunar] VolumeTRIX Mean Reversion is a volume-oriented mean-reversion and confirmation indicator built around one core principle: reversal opportunities become higher quality when “price stretch” is not just visible on one feed, but confirmed across venues and supported by internal market pressure.
Mean reversion is often explained with the “rubber band” metaphor, but in real trading, it’s more concrete than that. When price runs too far from a working equilibrium, the market tends to accumulate imbalances: liquidity gets thin in spots, inventories get skewed, and positioning becomes one-sided. Very often, the next meaningful move is not continuation, but a repair move—price coming back toward areas where business was actually done. That doesn’t mean the market must revert every time. It means that when displacement becomes extreme, reversion becomes *plausible*, and sometimes structurally incentivised.
This is why Volumetrix does not treat a single overbought/oversold trigger as a trade. It treats mean reversion as a multi-factor event that needs alignment.
The first pillar is multi-venue consensus. The script can track the same instrument across up to five brokers/exchanges and look for agreement. In crypto and CFDs, a large portion of “signals” are simply microstructure artefacts: isolated wicks, temporary dislocations, exchange-specific liquidity holes, short-lived imbalances.
I believe that a stretch that shows up on one venue may be noise; a stretch that shows up across venues at the same time is far more likely to be structural.
The second pillar is how the indicator defines “stretch.” Volumetrix intentionally blends different families of mean-reversion logic because each one captures a different way markets deviate from equilibrium. Statistical displacement (think Z-score) asks how far the price has moved away from its recent average in volatility units. Anchored equilibrium (VWAP) asks whether the price is trading away from a fair value built on *where volume actually traded*.
Volatility envelopes (Keltner-style bands) translate stretch into something regime-aware: what is “far” in a quiet market is not “far” in a fast one. None of these views is perfect alone, but together they describe displacement in a much more robust way than a single oscillator.
Then comes the part most traders miss: mean reversion is not just a distance problem, it’s a *regime* problem. That is where the Ornstein–Uhlenbeck idea matters. OU is the textbook mean-reverting process: deviations don’t just wander, they tend to be pulled back toward an equilibrium, and the strength of that pull defines how “elastic” the market feels. In trading terms, some environments punish deviations quickly; other environments reward drift and make reversals late and painful.
VolumeTRIX Mean Reversion uses an OU-style bias to estimate that temperament, so the script is not only asking “are we stretched?”, but also “does this market currently behave like it wants to revert, or like it’s comfortable drifting?”
From there, Volumetrix combines four perspectives (the “lanes”) into a single directional decision. The mean-reversion trust lane quantifies stretch and converts it into a normalised confidence. The OU lane adds the regime lens—how mean-reverting the market appears right now. TRIX adds momentum context because fading a move while momentum is still expanding is one of the fastest ways to get chopped up. Finally, the volumetric pressure gate looks at internal buy/sell pressure and asks a practical question: is the move still being *defended*, or is dominance starting to fade?
The real edge is not in any one component. The edge is in how they are forced to agree. Volumetrix allows you to determine the level of strictness in the agreement (All / Majority / Any). That’s an ensemble approach: each lane can be wrong, but they tend to be mistaken in different conditions. When multiple independent views of the market line up, you’re filtering for moments where the signal is less likely to be random and more likely to reflect an actual imbalance that can unwind.
So the question I'm trying to answer with this indicator is simple, and trader-practical: “Are we stretched across venues, is the current regime compatible with reversion (OU-style), is momentum no longer dominating (TRIX), and is volume pressure no longer supporting continuation?” When those answers align, the odds of a usable reversal improve.
Operationally, signals print only on confirmed bars and are hard-constrained to the most liquid global sessions (London and US), because mean-reversion quality tends to degrade in thin windows and produce low-quality signals.
The indicator also includes an internal forward-stat tracker that estimates how often signals reach a reasonable target move within a maximum number of bars. It is not a strategy backtest, and it doesn’t simulate compounding; it’s a calibration tool to compare settings and understand expectancy behaviour without guessing.
As always, this is an indicator, not financial advice. Mean reversion can fail hard in expansion regimes, so risk management and context always come first.
Enjoy!
Oberlunar 👁★
Dip Buy/Sell Signals (Vix Fix + MA Deviation + TRMAD) [DotGain]Dip Buy/Sell Signals (Vix Fix + MA Deviation + TRMAD)
This indicator combines three proven market stress and mean-reversion components to identify potential buy and sell opportunities during extended market conditions.
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📌 Included Components
1️⃣ Volatility-Based Stress Filter (Vix Fix)
Detects short-term market panic using relative price movement.
Signals are generated only during periods of elevated volatility or market stress.
2️⃣ Moving Average Deviation (MA Deviation)
Identifies overbought and oversold conditions based on the percentage deviation from a selected moving average.
Supported MA types:
• EMA
• SMA
• RMA
• VWMA
• WMA
• TEMA
3️⃣ TRMAD (True Range Mean Absolute Deviation)
Measures the distance of price from its mean relative to current volatility.
Useful for filtering extreme price moves and reducing false signals.
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📈 Trading Signals
Buy Signal:
• Elevated market volatility
• Price significantly below the moving average
• TRMAD below the defined threshold
Sell Signal:
• Elevated market volatility
• Price significantly above the moving average
• TRMAD above the defined threshold
Signals are visualized directly on the chart:
• Buy: green label below the candle
• Sell: red label above the candle
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⚙️ Settings & Customization
All components are fully adjustable:
• Lookback periods
• Moving average types and lengths
• Volatility and threshold levels
This makes the indicator suitable for:
• Intraday trading
• Swing trading
• Crypto, Forex, indices, and equities
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Disclaimer
This "Dip Buy/Sell Signals (Vix Fix + MA Deviation + TRMAD)" (DipSig) indicator is provided for informational and educational purposes only. It does not, and should not be construed as, financial, investment, or trading advice.
The signals generated by this tool (both "Buy" and "Sell") are the result of a specific set of algorithmic conditions. They are not a direct recommendation to buy or sell any asset. All trading and investing in financial markets involves substantial risk of loss. You can lose all of your invested capital.
Past performance is not indicative of future results. The signals generated may produce false or losing trades. The creator (© DotGain) assumes no liability for any financial losses or damages you may incur as a result of using this indicator.
You are solely responsible for your own trading and investment decisions. Always conduct your own research (DYOR) and consider your personal risk tolerance before making any trades.
Anchored VWAP PercentageINDICATOR: ANCHORED VWAP PERCENTAGE (AVWAP)
1. Overview
The Anchored VWAP Percentage (AVWAP) is a quantitative momentum and mean-reversion tool. It measures the percentage distance between the current price and a Volume Weighted Average Price (VWAP) that resets automatically based on specific time cycles. It allows traders to identify overextended market conditions relative to institutional value.
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2. Core Logic & Calculation
The script tracks the relationship between price and volume starting from a specific Anchor Point .
* Volume-Weighted Foundation: Unlike simple moving averages, this indicator uses the VWAP formula: sum(Volume * Price) / sum(Volume) .
* Automatic Anchoring: The starting point (Anchor) resets automatically depending on the chart timeframe (e.g., resets weekly on a 15m chart, or yearly on a Daily chart).
* Percentage Deviation: It calculates the precise gap between the price and the VWAP, plotted as an oscillator: ((Price - VWAP) / VWAP) * 100 .
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3. Adaptive Intelligence (Multi-Asset & Multi-TF)
The AVWAP is built with an internal database of 85th Percentile (P85) volatility thresholds. It recognizes that different assets have different "stretching" limits:
1. Asset-Specific Calibration: It includes optimized data for Bitcoin, Ethereum, Altcoins, Forex, and Indices .
2. Dynamic Timeframe Mapping: The anchor period and the exhaustion thresholds adjust automatically. For example:
* Intraday (1m-5m): Anchors to an 8-hour (480 min) cycle.
* Mid-Term (15m-60m): Anchors to a Weekly (W) cycle.
* Swing (Daily): Anchors to a Yearly (12M) cycle.
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4. Visual Anatomy
The indicator is designed for high-speed decision-making:
* The Histogram:
* Green: Price is trading above the VWAP (Bullish premium).
* Red: Price is trading below the VWAP (Bearish discount).
* P85 Threshold Lines:
* These lines represent the 85th percentile of historical deviations . Historically, the price stays within these boundaries 85% of the time.
* Background Highlighting: When the histogram crosses the P85 line, the background glows, signaling a Statistical Exhaustion Zone where a retracement to the mean is highly probable.
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5. How to Trade with AVWAP
* Mean Reversion: When the histogram reaches the P85 Zone , the price is "statistically overextended." This is a prime area to look for reversals or to take profits on existing trends.
* Trend Strength: If the histogram stays near the Zero Line while the price moves, the trend is supported by healthy volume.
* Value Area: The Zero Line represents the Fair Value . Buying near the Zero Line during a bullish histogram (Green) offers a high-probability entry with low risk.
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6. Technical Parameters
* Asset Selection: A dropdown to switch between Crypto, Forex, and Indices.
* Color Customization: User-defined colors for bullish and bearish sentiment.
* Precision Control: 4-decimal precision for accurate tracking of thin-margin assets like Forex.
Swing Failure Signals [AlgoAlpha]🟠 OVERVIEW
This script detects swing failure patterns by tracking how price interacts with recent swing highs and lows, then confirming those sweeps with a change in candle behavior. The goal is to highlight areas where price briefly breaks a key level, fails to continue, and then shifts direction. These events often occur around liquidity runs, where stops are triggered before price reverses. The script draws levels, colors bars, and prints clear markers to help visualize where these failures occur and when they are confirmed.
🟠 CONCEPTS
The logic starts with pivot-based swing detection. Recent swing highs and lows are stored and monitored. When price trades beyond one of these levels within a defined historical window, it is treated as a sweep. A sweep alone is not enough. The script then waits for a Change in State of Delivery (CISD), which is defined by a shift in candle structure that shows follow-through in the opposite direction. A tolerance filter measures how far price traveled beyond the level relative to the reaction that followed. If the reaction is strong enough and happens within a limited number of bars, the sweep is validated as a swing failure. In short: the swing defines the reference, the sweep shows intent, and the CISD confirms acceptance or rejection.
🟠 FEATURES
Sweep detection with a maximum lookback to avoid outdated levels
CISD confirmation using candle structure and price expansion
Alert conditions for bullish and bearish swing failures
🟠 USAGE
Setup : Add the script to your chart. It works on any market and timeframe. Lower timeframes highlight intraday liquidity runs, while higher timeframes show structural failures. Start with the default inputs before adjusting.
Read the chart : A bullish swing failure occurs when price sweeps a prior low, then reverses and confirms with a bullish CISD. A bearish swing failure is the opposite, sweeping a prior high and confirming with a bearish CISD. Dashed lines mark the swept swing. Solid lines mark the CISD level. Bars are colored while the SFP state is active.
Settings that matter : Increasing Pivot Detection Length finds more significant swings but fewer signals. Reducing Max Pivot Point Edge limits how far back sweeps are allowed, keeping signals more current. The Patience setting controls how many bars are allowed for confirmation after a sweep. The Trend Noise Filter raises or lowers how strong the reaction must be to qualify as a valid failure.
Volume-Weighted Price Z-Score [QuantAlgo]🟢 Overview
The Volume-Weighted Price Z-Score indicator quantifies price deviations from volume-weighted equilibrium using statistical standardization. It combines volume-weighted moving average analysis with logarithmic deviation measurement and volatility normalization to identify when prices have moved to statistically extreme levels relative to their volume-weighted baseline, helping traders and investors spot potential mean reversion opportunities across multiple timeframes and asset classes.
🟢 How It Works
The indicator's core methodology lies in its volume-weighted statistical approach, where price displacement is measured through normalized deviations from volume-weighted price levels:
volumeWeightedAverage = ta.vwma(priceSource, lookbackPeriod)
logDeviation = math.log(priceSource / volumeWeightedAverage)
volatilityMeasure = ta.stdev(logDeviation, lookbackPeriod)
The script uses logarithmic transformation to capture proportional price changes rather than absolute differences, ensuring equal treatment of percentage moves regardless of price level:
rawZScore = logDeviation / volatilityMeasure
zScore = ta.ema(rawZScore, smoothingPeriod)
First, it establishes the volume-weighted baseline which gives greater weight to price levels where significant trading occurred, creating a more representative equilibrium point than simple moving averages.
Then, the logarithmic deviation measurement converts the price-to-average ratio into a normalized scale:
logDeviation = math.log(priceSource / volumeWeightedAverage)
Next, statistical normalization is achieved by dividing the deviation by its own historical volatility, creating a standardized z-score that measures how many standard deviations the current price sits from the volume-weighted mean.
Finally, EMA smoothing filters noise while preserving the signal's responsiveness to genuine market extremes:
rawZScore = logDeviation / volatilityMeasure
zScore = ta.ema(rawZScore, smoothingPeriod)
This creates a volume-anchored statistical oscillator that combines price-volume relationship analysis with volatility-adjusted normalization, providing traders with probabilistic insights into market extremes and mean reversion potential based on standard deviation thresholds.
🟢 Signal Interpretation
▶ Positive Values (Above Zero): Price trading above volume-weighted average indicating potential overvaluation relative to volume-weighted equilibrium = Caution on longs, potential mean reversion downward = Short/sell opportunities
▶ Negative Values (Below Zero): Price trading below volume-weighted average indicating potential undervaluation relative to volume-weighted equilibrium = Caution on shorts, potential mean reversion upward = Long/buy opportunities
▶ Zero Line Crosses: Mean reversion transitions where price crosses back through volume-weighted equilibrium, indicating shift from overvalued to undervalued (or vice versa) territory
▶ Extreme Positive Zone (Above +2.5σ default): Statistically rare overvaluation representing 98.8%+ confidence level deviation, indicating extremely stretched bullish conditions with high mean reversion probability = Strong correction warning/short signal
▶ Extreme Negative Zone (Below -2.5σ default): Statistically rare undervaluation representing 98.8%+ confidence level deviation, indicating extremely stretched bearish conditions with high mean reversion probability = Strong buying opportunity signal
▶ ±1σ Reference Levels: Moderate deviation zones (±1 standard deviation) marking common price fluctuation boundaries where approximately 68% of price action occurs under normal distribution
▶ ±2σ Reference Levels: Significant deviation zones (±2 standard deviations) marking unusual price extremes where approximately 95% of price action should be contained under normal conditions
🟢 Features
▶ Preconfigured Presets: Three optimized parameter sets accommodate different analytical approaches, instruments and timeframes. "Default" provides balanced statistical measurement suitable for swing trading and daily/4-hour analysis, offering deviation detection with moderate responsiveness to price dislocations. "Fast Response" delivers heightened sensitivity optimized for intraday trading and scalping on 15-minute to 1-hour charts, using shorter statistical windows and minimal smoothing to capture rapid mean reversion opportunities as they develop. "Smooth Trend" offers conservative extreme identification ideal for position trading on daily to weekly charts, employing extended statistical periods and heavy noise filtering to isolate only the most significant market extremes.
▶ Built-in Alerts: Seven alert conditions enable comprehensive automated monitoring of statistical extremes and mean reversion events. Extreme Overbought triggers when z-score crosses above the extreme threshold (default +2.5σ) signaling rare overvaluation, Extreme Oversold activates when z-score crosses below the negative extreme threshold (default -2.5σ) signaling rare undervaluation. Exit Extreme Overbought and Exit Extreme Oversold alert when prices begin reverting from these statistical extremes back toward the mean. Bullish Mean Reversion notifies when z-score crosses above zero indicating shift to overvalued territory, while Bearish Mean Reversion triggers on crosses below zero indicating shift to undervalued territory. Any Extreme Level provides a combined alert for any extreme threshold breach regardless of direction. These notifications allow you to capitalize on statistically significant price dislocations without continuous chart monitoring.
▶ Color Customization: Six visual themes (Classic, Aqua, Cosmic, Ember, Neon, plus Custom) accommodate different chart backgrounds and visual preferences, ensuring optimal contrast for identifying positive versus negative deviations across trading environments. The adjustable fill transparency control (0-100%) allows fine-tuning of the gradient area prominence between the z-score line and zero baseline, with higher opacity values creating subtle background context while lower values produce bold deviation emphasis. Optional bar coloring extends the z-score gradient directly to the indicator pane bars, providing immediate visual reinforcement of current deviation magnitude and direction without requiring reference to the plotted line itself.
*Note: This indicator requires volume data to function correctly, as it calculates deviations from a volume-weighted price average. Tickers with no volume data or extremely limited volume will not produce meaningful results, i.e., the indicator may display flat lines, erratic values, or fail to calculate properly. Using this indicator on assets without volume data (certain forex pairs, synthetic indices, or instruments with unreported/unavailable volume) will produce unreliable or no results at all. Additionally, ensure your chart has sufficient historical data to cover the selected lookback period, e.g., using a 100-bar lookback on a chart with only 50 bars of history will yield incomplete or inaccurate calculations. Always verify your chosen ticker has consistent, accurate volume information and adequate price history before applying this indicator.
SNIPER Mean Reversion V1MR SNIPER (Mean Reversion)
### When to Use
- Market is **IN BALANCE** (ranging, consolidating)
- Price **breaks out but FAILS** to hold
- **London session** or compressed summer conditions
- Failed breakouts returning to value
### The Setup Sequence
```
1. BALANCE DETECTED
└── Price rotating around POC
2. BREAKOUT ATTEMPT
└── Price pushes beyond Value Area
3. FAILURE + RECLAIM ← KEY MOMENT
└── Price comes BACK inside balance
└── DO NOT trade first move back!
4. PULLBACK INTO LVN
└── Wait for pullback after reclaim
5. AGGRESSION CONFIRMATION
└── Entry candle shows buy/sell pressure
└── Volume elevated (1.2×+ average)
└── Fat body (60%+ of range)
6. ENTRY → TARGET: POC
```
### Signal Labels
- **MR↑** = Mean Reversion Long (failed breakdown)
- **MR↓** = Mean Reversion Short (failed breakout)
- **S/A/B** = Signal quality tier
### Risk Management
- **Stop**: Below recent low (long) / Above recent high (short)
- **Target**: POC (center of value)
- **Risk**: 0.25-0.5% per trade
Gamma Adaptive Regime Engine - CoreGamma Adaptive Regime Engine – Core
The Gamma Adaptive Regime Engine (GARO) is a visualization tool designed to help identify how market conditions are currently behaving — whether price is moving directionally or fluctuating within a range. Many indicators apply the same logic in all environments; GARO instead focuses on displaying the surrounding context so users can better understand what type of environment they are looking at.
Why the Source Is Protected
This script uses Protected Source to prevent accidental edits and keep calculations consistent across all users. The study combines several technical concepts — adaptive moving averages, volatility filters, and context-based visuals — inside one framework. Protection is used strictly for stability and maintenance, not as a claim of performance.
How to Use: Visual Overview
GARO highlights the chart with colors and overlays to help illustrate the current environment. These visuals are intended as context only and should always be combined with independent analysis.
1) Market Regimes
Expansion (Green background / bands)
Represents conditions where price movement appears more directional and trends can develop.
Contraction (Blue background / bands)
Represents conditions where price behavior is more range-like, often moving back and forth within boundaries.
Spike (Red background)
Represents periods of elevated volatility where price behavior can become fast and irregular.
These categories describe conditions — they are not trade instructions.
2) Visual Elements
Orange Dots (Range Anchor)
Displayed primarily during Contraction.
They represent a smoothed “fair-value” anchor that price frequently fluctuates around in sideways environments.
Green / Fuchsia Line (Expansion Core)
A smoothed directional line showing the current bias during Expansion phases.
Green indicates upward bias; Fuchsia indicates downward bias.
Cloud Bands (Shaded Areas)
Adaptive volatility boundaries.
In range-type conditions, touches near the edges may indicate stretched behavior.
During directional movement, they may function visually like trailing boundaries.
Yellow Dashed Line (Zero Gamma Proxy)
A calculated reference level that sometimes aligns with areas where price pauses, consolidates, or rotates.
It is intended purely as a contextual reference.
Table (Top-Right)
The table summarizes what the engine is currently reading:
Regime Status — Expansion, Contraction, or Spike
Context Label — Examples include:
Trend Context
Mean-Reversion Context
Range — Trend Bias Intact
These labels describe the environment only and do not generate signals.
Educational Disclaimer
This script is for visualization and educational purposes only.
It does not provide trading signals, guarantees, or advice. All decisions should be based on independent analysis, personal judgment, and appropriate risk management.
MA Distance Percentile - HighQ ToolsHighQTools — MA Distance Percentile (MADP)
As always, if anyone has any tips or additional features they'd like to see, feel free to reach out!
MA Distance Percentile (MADP) measures how far price is from its moving average relative to its own recent history.
Instead of showing raw distance (which varies by symbol, volatility, and timeframe), MADP normalizes price-to-MA distance into a 0–100 percentile rank over a rolling lookback window. This allows traders to quickly identify when price is relatively extended or compressed compared to recent conditions.
🔍 How It Works
A moving average is calculated (EMA by default, configurable).
The ratio of price / MA is computed.
That ratio is percentile-ranked over a user-defined lookback window.
The result is optionally smoothed for clarity.
High values (e.g., 80–100): Price is more extended above its MA than it has been recently.
Low values (e.g., 0–20): Price is relatively compressed or discounted vs its MA.
🧭 How to Use It
MADP is best used as a context tool, not a standalone signal:
Identify mean-reversion potential at relative extremes
Distinguish trend continuation vs exhaustion
Filter entries taken near highs/lows vs those taken in compression
Combine with structure, volume, delta, or VWAP-based tools
Optional visual levels (20 / 50 / 80) are provided for quick reference. Simple signals are included but disabled by default to encourage discretionary use.
⚙️ Defaults & Notes
Default MA: 20-period EMA
Default lookback: 200 bars
Designed for intraday and swing analysis
Does not repaint
Percentile-based normalization makes it robust across symbols and timeframes
This indicator is part of the HighQTools framework: clean, transparent tools designed to provide context first, not overfitted signals.
ATR-Normalized VWMA DeviationThis indicator measures how far price deviates from the Volume-Weighted Moving Average ( VWMA ), normalized by market volatility ( ATR ). It identifies significant price reversal points by combining price structure and volatility-adjusted deviation behavior.
The core idea is to use VWMA as a dynamic trend anchor, then measure how far price travels away from it relative to recent volatility . This helps highlight when price has stretched too far and may be due for a reversal or pullback.
How it works:
VWMA deviation is calculated as the difference between price and the VWMA.
That deviation is divided by ATR (Average True Range) to normalize for current volatility.
The script tracks the highest and lowest normalized deviations over the chosen lookback period.
It also tracks price structure (highest/lowest highs/lows) over the same period.
A reversal signal is generated when a historical extreme in deviation aligns with a price structure extreme, and a confirmed reversal candle forms.
You get visual signals and color highlights where these conditions occur.
Settings explained:
Lookback period defines how many bars the script uses to find recent extremes.
ATR length controls how volatility is measured.
VWMA length controls how the volume-weighted moving average is calculated.
Signal filters help refine entries based on price vs deviation behavior.
Display options let you customize how signals and levels appear on the chart.
This indicator is especially useful for spotting potential turning points where price has moved far from VWMA relative to volatility, suggesting possible exhaustion or overextension.
Tips for use:
Combine with broader trend context (higher timeframe support/resistance).
Use with risk management rules (position sizing, stops) — signals are guides, not guaranteed entries.
Adjust lookback and ATR settings based on your trading timeframe and asset volatility.
Hurst-Optimized Adaptive Channel [Kodexius]Hurst-Optimized Adaptive Channel (HOAC) is a regime-aware channel indicator that continuously adapts its centerline and volatility bands based on the market’s current behavior. Instead of using a single fixed channel model, HOAC evaluates whether price action is behaving more like a trend-following environment or a mean-reverting environment, then automatically selects the most suitable channel structure.
At the core of the engine is a robust Hurst Exponent estimation using R/S (Rescaled Range) analysis. The Hurst value is smoothed and compared against user-defined thresholds to classify the market regime. In trending regimes, the script emphasizes stability by favoring a slower, smoother channel when it proves more accurate over time. In mean-reversion regimes, it deliberately prioritizes a faster model to react sooner to reversion opportunities, similar in spirit to how traders use Bollinger-style behavior.
The result is a clean, professional adaptive channel with inner and outer bands, dynamic gradient fills, and an optional mean-reversion signal layer. A minimalist dashboard summarizes the detected regime, the current Hurst reading, and which internal model is currently preferred.
🔹 Features
🔸 Robust Regime Detection via Hurst Exponent (R/S Analysis)
HOAC uses a robust Hurst Exponent estimate derived from log returns and Rescaled Range analysis. The Hurst value acts as a behavioral filter:
- H > Trend Start threshold suggests trend persistence and directional continuation.
- H < Mean Reversion threshold suggests anti-persistence and a higher likelihood of reverting toward a central value.
Values between thresholds are treated as Neutral, allowing the channel to remain adaptive without forcing a hard bias.
This regime framework is designed to make the channel selection context-aware rather than purely reactive to recent volatility.
🔸 Dual Channel Engine (Fast vs Slow Models)
Instead of relying on one fixed channel, HOAC computes two independent channel candidates:
Fast model: shorter WMA basis and standard deviation window, intended to respond quickly and fit more reactive environments.
Slow model: longer WMA basis and standard deviation window, intended to reduce noise and better represent sustained directional flow.
Each model produces:
- A midline (basis)
- Outer bands (wider deviation)
- Inner bands (tighter deviation)
This structure gives you a clear core zone and an outer envelope that better represents volatility expansion.
🔸 Rolling Optimization Memory (Model Selection by Error)
HOAC includes an internal optimization layer that continuously measures how well each model fits current price action. On every bar, each model’s absolute deviation from the basis is recorded into a rolling memory window. The script then compares total accumulated error between fast and slow models and prefers the one with lower recent error.
This approach does not attempt curve fitting on multiple parameters. It focuses on a simple, interpretable metric: “Which model has tracked price more accurately over the last X bars?”
Additionally:
If the regime is Mean Reversion, the script explicitly prioritizes the fast model, ensuring responsiveness when reversals matter most.
🔸 Optional Output Smoothing (User-Selectable)
The final selected channel can be smoothed using your choice of:
- SMA
- EMA
- HMA
- RMA
This affects the plotted midline and all band outputs, allowing you to tune visual stability and responsiveness without changing the underlying decision engine.
🔸 Premium Visualization Layer (Inner Core + Outer Fade)
HOAC uses a layered band design:
- Inner bands define the core equilibrium zone around the midline.
- Outer bands define an extended volatility envelope for extremes.
Gradient fills and line styling help separate the core from the extremes while staying visually clean. The midline includes a subtle glow effect for clarity.
🔸 Adaptive Bar Tinting Strength (Regime Intensity)
Bar coloring dynamically adjusts transparency based on how far the Hurst value is from 0.5. When market behavior is more decisively trending or mean-reverting, the tint becomes more pronounced. When behavior is closer to random, the tint becomes more subtle.
🔸 Mean-Reversion Signal Layer
Mean-reversion signals are enabled when the environment is not classified as Trending:
- Buy when price crosses back above the lower outer band
- Sell when price crosses back below the upper outer band
This is intentionally a “return to channel” logic rather than a breakout logic, aligning signals with mean-reversion behavior and avoiding signals in strongly trending regimes by default.
🔸 Minimalist Dashboard (HUD)
A compact table displays:
- Current regime classification
- Smoothed Hurst value
- Which model is currently preferred (Fast or Slow)
- Trend flow direction (based on midline slope)
🔹 Calculations
1) Robust Hurst Exponent (R/S Analysis)
The script estimates Hurst using a Rescaled Range approach on log returns. It builds a returns array, computes mean, cumulative deviation range (R), standard deviation (S), then converts RS into a Hurst exponent.
calc_robust_hurst(int length) =>
float r = math.log(close / close )
float returns = array.new_float(length)
for i = 0 to length - 1
array.set(returns, i, r )
float mean = array.avg(returns)
float cumDev = 0.0
float maxCD = -1.0e10
float minCD = 1.0e10
float sumSqDiff = 0.0
for i = 0 to length - 1
float val = array.get(returns, i)
sumSqDiff += math.pow(val - mean, 2)
cumDev += (val - mean)
if cumDev > maxCD
maxCD := cumDev
if cumDev < minCD
minCD := cumDev
float R = maxCD - minCD
float S = math.sqrt(sumSqDiff / length)
float RS = (S == 0) ? 0.0 : (R / S)
float hurst = (RS > 0) ? (math.log10(RS) / math.log10(length)) : 0.5
hurst
This design avoids simplistic proxies and attempts to reflect persistence (trend tendency) vs anti-persistence (mean reversion tendency) from the underlying return structure.
2) Hurst Smoothing
Raw Hurst values can be noisy, so the script applies EMA smoothing before regime decisions.
float rawHurst = calc_robust_hurst(i_hurstLen)
float hVal = ta.ema(rawHurst, i_smoothHurst)
This stabilized hVal is the value used across regime classification, dynamic visuals, and the HUD display.
3) Regime Classification
The smoothed Hurst reading is compared to user thresholds to label the environment.
string regime = "NEUTRAL"
if hVal > i_trendZone
regime := "TRENDING"
else if hVal < i_chopZone
regime := "MEAN REV"
Higher Hurst implies more persistence, so the indicator treats it as a trend environment.
Lower Hurst implies more mean-reverting behavior, so the indicator enables MR logic and emphasizes faster adaptation.
4) Dual Channel Models (Fast and Slow)
HOAC computes two candidate channel structures in parallel. Each model is a WMA basis with volatility envelopes derived from standard deviation. Inner and outer bands are created using different multipliers.
Fast model (more reactive):
float fastBasis = ta.wma(close, 20)
float fastDev = ta.stdev(close, 20)
ChannelObj fastM = ChannelObj.new(fastBasis, fastBasis + fastDev * 2.0, fastBasis - fastDev * 2.0, fastBasis + fastDev * 1.0, fastBasis - fastDev * 1.0, math.abs(close - fastBasis))
Slow model (more stable):
float slowBasis = ta.wma(close, 50)
float slowDev = ta.stdev(close, 50)
ChannelObj slowM = ChannelObj.new(slowBasis, slowBasis + slowDev * 2.5, slowBasis - slowDev * 2.5, slowBasis + slowDev * 1.25, slowBasis - slowDev * 1.25, math.abs(close - slowBasis))
Both models store their structure in a ChannelObj type, including the instantaneous tracking error (abs(close - basis)).
5) Rolling Error Memory and Model Preference
To decide which model fits current conditions better, the script stores recent errors into rolling arrays and compares cumulative error totals.
var float errFast = array.new_float()
var float errSlow = array.new_float()
update_error(float errArr, float error, int maxLen) =>
errArr.unshift(error)
if errArr.size() > maxLen
errArr.pop()
Each bar updates both error histories and computes which model has lower recent accumulated error.
update_error(errFast, fastM.error, i_optLookback)
update_error(errSlow, slowM.error, i_optLookback)
bool preferFast = errFast.sum() < errSlow.sum()
This is an interpretable optimization approach: it does not attempt to brute-force parameters, it simply prefers the model that has tracked price more closely over the last i_optLookback bars.
6) Winner Selection Logic (Regime-Aware Hybrid)
The final model selection uses both regime and rolling error performance.
ChannelObj winner = regime == "MEAN REV" ? fastM : (preferFast ? fastM : slowM)
rawMid := winner.mid
rawUp := winner.upper
rawDn := winner.lower
rawUpInner := winner.upper_inner
rawDnInner := winner.lower_inner
In Mean Reversion, the script forces the fast model to ensure responsiveness.
Otherwise, it selects the lowest-error model between fast and slow.
7) Optional Output Smoothing
After the winner is selected, the script optionally smooths the final channel outputs using the chosen moving average type.
smooth(float src, string type, int len) =>
switch type
"SMA" => ta.sma(src, len)
"EMA" => ta.ema(src, len)
"HMA" => ta.hma(src, len)
"RMA" => ta.rma(src, len)
=> src
float finalMid = i_enableSmooth ? smooth(rawMid, i_smoothType, i_smoothLen) : rawMid
float finalUp = i_enableSmooth ? smooth(rawUp, i_smoothType, i_smoothLen) : rawUp
float finalDn = i_enableSmooth ? smooth(rawDn, i_smoothType, i_smoothLen) : rawDn
float finalUpInner = i_enableSmooth ? smooth(rawUpInner, i_smoothType, i_smoothLen) : rawUpInner
float finalDnInner = i_enableSmooth ? smooth(rawDnInner, i_smoothType, i_smoothLen) : rawDnInner
This preserves decision integrity since smoothing happens after model selection, not before.
8) Dynamic Visual Intensity From Hurst
Transparency is derived from the distance of hVal to 0.5, so stronger behavioral regimes appear with clearer tints.
int dynTrans = int(math.max(20, math.min(80, 100 - (math.abs(hVal - 0.5) * 200))))
Sen Regression ChannelSen Regression Channel
OVERVIEW
The Sen Regression Channel is a trend-structure visualization tool built on the Theil–Sen estimator, a median-based regression method designed to reduce sensitivity to price outliers. Unlike traditional least-squares regression channels, this approach anchors trend using the most representative slope across the lookback period, resulting in a more stable and noise-resistant structure.
TECHNICAL LOGIC & ORIGINALITY
To protect the proprietary implementation of the median-slope engine and adaptive band construction, this script is published as Protected.
Median Slope Engine
Calculates the Theil–Sen slope by evaluating the median rate of change across the lookback window, producing a trendline less distorted by extreme candles or transient volatility.
Adaptive Volatility Bands
Channel width can be derived from either Standard Deviation or ATR, allowing the envelope to adjust dynamically to changing volatility regimes.
Multi-Reference Context (Optional)
VWAP and EMA/SMA overlays can be enabled to compare the median regression structure against commonly used price and volume-weighted references.
HOW TO USE (EDUCATIONAL)
This tool is designed to help analyze trend quality and market structure, not to generate trade signals.
Trend Direction & Stability
A sustained upward or downward slope of the median regression line indicates directional structure with reduced noise sensitivity.
Volatility Expansion Zones
Price closing outside the channel bands highlights volatility expansion relative to the median trend and may signal regime change.
Mean-Reversion Context
Price oscillation between the median line and bands reflects balanced conditions; movement toward the outer bands indicates relative extension.
VWAP Confluence
Alignment between the regression midline and VWAP may highlight areas of consensus value.
USER INPUTS
Lookback Period – Sets the window for the median slope calculation
Band Multiplier – Scales the channel width
Band Method – Standard Deviation or ATR-based envelope
Visual Overlays – Toggle VWAP, midline, and cloud transparency
NOTES
This script is a historical charting and visualization tool for educational purposes only.
It does not provide trade signals, alerts, or financial advice.
All values are calculated in real time using available chart data.
Microstructure Participation & Acceptance Indicator📊 Microstructure Participation & Acceptance Indicator
An advanced participation-based filter combining VWAP distance analysis, volume delta detection, and real-time acceptance/rejection state identification—designed for smaller timeframe trading.
📊 FEATURES
VWAP Distance Normalization
Context-aware fair value measurement:
Automatically resets based on selected anchor (Session/Week/Month)
ATR-normalized distance calculation for universal application
Identifies when price is extended or compressed relative to equilibrium
Configurable extreme distance threshold (default: 1.5 ATR)
Adjustable source input (default: HLC3)
Volume Delta Proxy
Bull vs Bear participation tracking:
Calculates volume imbalance between bullish and bearish candles
EMA smoothing for cleaner signal generation (default: 9 periods)
Delta ratio measurement to identify dominant side
Expansion/compression detection to gauge momentum commitment
Configurable expansion threshold (default: 1.3x)
Acceptance/Rejection State Machine
Real-time market regime identification with six distinct states:
🟢 Accepted Long
Price moving away from VWAP with expanding bullish delta
Distance from VWAP increasing
Volume confirming the move
Indicates real buying pressure—trade WITH the move
🟢 Accepted Short
Price moving away from VWAP with expanding bearish delta
Distance from VWAP increasing
Volume confirming the move
Indicates real selling pressure—trade WITH the move
🟠 Fade Long
Price extended beyond threshold (>1.5 ATR above VWAP)
Delta not supporting the extension
Volume participation absent or diminishing
Potential mean-reversion short setup
🟠 Fade Short
Price extended beyond threshold (>1.5 ATR below VWAP)
Delta not supporting the extension
Volume participation absent or diminishing
Potential mean-reversion long setup
⚪ Chop
Price compressed near VWAP
Bollinger Bands tight (width compressed)
Delta neutral—no clear commitment
NO TRADE ZONE—wait for expansion
⚪ Neutral
Transitional state between regimes
Momentum shifting but not yet confirmed
Monitor for next acceptance signal
Bollinger Bands
Standard volatility measurement with TradingView default styling:
Adjustable period length (default: 20)
Configurable standard deviation multiplier (default: 2.0)
Visual fill between bands for volatility context
Used internally for chop/compression detection
Live Dashboard
Real-time metrics display (top-right corner):
Current market state with color coding
VWAP distance in ATR units
Delta ratio (bull/bear volume balance)
Delta state (Expanding/Compressing)
High-contrast design for instant readability
🎯 HOW TO USE
For Trend Trading:
Accepted Long/Short backgrounds indicate confirmed participation—stay with the trend
Strong moves typically travel 1-1.5 ATR from VWAP with delta support
Use VWAP as dynamic support/resistance
Combine with momentum indicators (MACD, RSI) for confluence
Price above VWAP + Accepted Long state = bullish bias
Price below VWAP + Accepted Short state = bearish bias
For Mean Reversion:
Fade Long/Short states signal overextension without participation
Price beyond 1.5 ATR from VWAP with weak delta = potential reversal
Look for price return to VWAP when extended
Bollinger Band extremes + Fade state = high-probability mean reversion setup
VWAP acts as mean reversion anchor during range-bound sessions
For Risk Management:
Chop state = avoid new entries
Bollinger Band compression + Chop = pre-expansion zone (wait for breakout)
Delta compression after strong move = early exhaustion warning
State transitions (Accepted → Neutral → Fade) = tighten stops
Signal Confirmation:
Strongest setups occur when multiple factors align:
BB breakout + Accepted state + price above/below VWAP
Price rejection at BB bands + Fade state
VWAP support/resistance hold + state transition
Delta expansion + distance increasing + trend direction
⚙️ SETTINGS
All components are fully customizable through organized input groups:
VWAP Distance Group:
VWAP source (default: HLC3)
Anchor period (Session/Week/Month)
ATR length for normalization (default: 14)
Extreme distance threshold in ATR multiples (default: 1.5)
Volume Delta Group:
Delta EMA length (default: 9)
Delta expansion threshold (default: 1.3)
Acceptance Logic Group:
Acceptance lookback period (default: 5)
Chop threshold in VWAP/ATR units (default: 0.3)
Bollinger Bands Group:
BB length (default: 20)
Standard deviation multiplier (default: 2.0)
Display Group:
Toggle state backgrounds
Toggle state change labels
Toggle VWAP line
Toggle Bollinger Bands
💡 EDUCATIONAL VALUE
This indicator teaches important concepts:
How institutional money identifies fair value (VWAP)
The difference between price movement and market acceptance
Why volume participation matters more than price action alone
How to distinguish between noise and committed directional moves
The relationship between volatility compression and expansion cycles
Why distance from equilibrium predicts mean reversion probability
⚠️ IMPORTANT NOTES
This indicator is for educational and informational purposes only
This is a filter, not a standalone trading system
No indicator is perfect—always use proper risk management
Past performance does not guarantee future results
Combine with your own analysis and risk tolerance
Test thoroughly on historical data before live trading
This is not financial advice—use at your own risk
🔧 TECHNICAL DETAILS
Pine Script Version 6
Overlay indicator (displays on price chart)
All calculations use standard, well-documented formulas
No repainting—all signals are confirmed on bar close
Compatible with all timeframes and instruments
Optimized for smaller timeframes (1-5 minute charts)
Minimal computational overhead
📝 CHANGELOG
Version 1.0
Initial release
VWAP distance normalization with ATR scaling
Volume delta proxy system (bull/bear EMA)
6-state acceptance/rejection state machine
Bollinger Bands integration
Real-time dashboard with live metrics
State change labels and background coloring
Full customization options
Developed for traders who need objective participation filters to distinguish high-probability setups from low-quality noise—without cluttering their charts with multiple indicator panels.
Session ATR Progression Tracker📊 Session ATR Progression Tracker - SIYL Regression Trading Tool
Track how much of your instrument's 7-day Average True Range (ATR) has been covered during the current trading session. This indicator is specifically designed for regression traders who follow the "Stay In Your Lane" (SIYL) methodology, helping you identify when the probability of mean reversion significantly increases. If you are interested in more on that check out Rod Casselli and tradersdevgroup.com.
🎯 Key Features:
• Real-time ATR Coverage Percentage - See at a glance what percentage of the 7-day ATR has been covered in the current session
• SIYL-Optimized Thresholds - See at a glance when the instrument has achieved 80% and 100% ATR coverage, the proven thresholds where mean reversion probability increases (customizable)
• Flexible Session Modes:
- Daily: Resets at calendar day change
- Session: Uses exchange-defined trading sessions
- Custom Session: Set your exact session start/end times (perfect for futures traders and international markets)
• Visual Alerts - Color-coded display (gray → orange → red) and optional background highlighting
• Repositionable Display - Choose from 9 screen positions to avoid chart clutter
• Session Markers - Green triangles mark the start of each new session
• Detailed Stats - View current range, ATR value, session high/low, and session status
💡 Why Use This Indicator?
This tool is built around a proven concept: regression trading becomes significantly more effective once a session has achieved at least 80% of its 7-day ATR. At this threshold, the probability of price reverting to mean increases substantially, creating higher-probability trade setups for SIYL practitioners.
Benefits for regression traders:
- Identify optimal entry points when mean reversion probability is highest (≥80% ATR coverage)
- Avoid premature regression entries before adequate range has been established
- Recognize when daily moves have "earned their range" and are ripe for reversal
- Time fade-the-move and counter-trend strategies with statistical backing
- Improve win rates by trading only after proven probability thresholds are met
⚙️ Setup Instructions:
1. Add the indicator to your chart
2. Select your preferred "Reset Mode" (recommend "Custom Session" for futures/international markets)
3. If using Custom Session, enter your session times in 24-hour format (e.g., 0930-1600 for US stocks, 1700-1600 for CME futures)
4. Adjust alert thresholds if desired (default: 80% and 100% - proven SIYL thresholds)
5. Position the display where it's most visible on your chart
📈 Works Across All Markets:
Stocks • Futures • Forex • Indices • Crypto • Commodities
Perfect for regression traders, mean reversion specialists, and SIYL practitioners who want to trade with probability on their side by entering only after the session has "earned its range."
---
Tip: For futures contracts with overnight sessions that span calendar days (like MES, MNQ, MYM), use "Custom Session" mode with your exchange's official session times for accurate tracking.
_Mean_RAWAn indicator based on the “ mean reversion ” strategy.
Works best with the EURUSD 4h pair. Different time frames can be used for other pairs.
The pyramiding feature does not make significant changes; it is not an important parameter.
It definitely does not repaint, especially if you trade on candle closes using the per bar close type alarm.
Green label -> 🟢 buy
Red label -> 🔴 sell
Yellow label -> 🟡 close
Your suggestions regarding the indicator are important to me.
Market Analysis Pro [Trademy]OVERVIEW
Trademy Market Analysis Pro is a professional-grade trading system that combines advanced momentum analysis with institutional-level Supply/Demand zone mapping. This indicator is designed to provide crystal-clear market analysis with precise risk management tools, creating a complete trading framework within a single, streamlined interface.
Unlike complex indicators that overwhelm traders with information, Trademy focuses on what matters: high-probability setups with clear entry points, defined risk levels, and multiple profit targets. The system is built to eliminate guesswork and provide actionable signals that work across multiple timeframes and asset classes eg: ( INDEX:BTCUSD , NASDAQ:NVDA and more )
CORE CONCEPTS
Advanced Momentum Engine: The foundation of Trademy Market Analysis Pro is a proprietary momentum detection system that identifies true directional shifts in the market. The algorithm analyzes price behavior relative to volatility-adjusted dynamic levels, generating signals only when genuine momentum reversals occur. The "Signal Sensitivity" control allows you to adapt the system from conservative (fewer, higher-quality signals) to aggressive (more frequent opportunities) based on your trading style and market conditions.
Institutional Supply/Demand Zones: The system automatically identifies and plots key institutional levels where significant buying (Demand) or selling (Supply) pressure has occurred. These zones are calculated using advanced price structure analysis, filtered through intelligent overlap detection to ensure only the most relevant zones appear on your chart. When price approaches these levels, they often act as strong support or resistance, providing logical areas for entries and exits.
Intelligent Signal Classification: Not all signals are created equal. Trademy categorizes every signal as either "Normal" or "Strong" based on its alignment with the broader market structure and trend context. Strong signals represent higher-conviction setups where momentum and trend align perfectly, while normal signals indicate counter-trend or early reversal opportunities.
Non-Repainting Architecture: Every signal is locked in at bar close (when enabled), and all TP/SL levels are calculated using volatility measurements captured at the moment of signal generation.
KEY FEATURES
Precision Signal System
Dual Signal Modes: Choose between Normal signals (standard momentum reversals) or Strong signals (high-conviction trend-aligned setups), or view both simultaneously
Wait for Bar Close: Optional no-repaint mode ensures signals only appear after candle confirmation
Visual Signal Hierarchy: Normal signals shown with standard arrows (▲/▼), Strong signals marked with distinctive colors for instant recognition
Adjustable Arrow Sizes: Customize signal display from tiny to large based on your chart preferences
Professional Risk Management
Automated TP/SL Calculation: Three take-profit levels (TP1, TP2, TP3) and one stop-loss level automatically calculated using advanced volatility measurement
Fixed Risk Levels: TP/SL lines are locked at signal generation and never move—providing consistent, reliable risk parameters
Visual Risk Zones: Optional colored zones highlight your risk and reward areas for instant position assessment
Adjustable Risk Multiplier: Scale your targets up or down with a single parameter while maintaining proper risk-reward ratios
Clear On-Chart Labels: Every level displays exact price values in an easy-to-read format
Supply/Demand Zone Mapping
Automatic Zone Detection: System identifies high-probability supply and demand zones using advanced price structure analysis
Anti-Overlap Algorithm: Intelligent filtering prevents zone clutter by removing overlapping levels
Extended Zone Projection: Zones extend into the future, showing you key levels before price reaches them
Break-of-Structure Tracking: Monitors when zones are broken and removes invalidated levels
Fully Customizable: Adjust zone colors, swing length, history depth, and box width to match your analysis style
Visual Customization
Flexible Color Schemes: Customize colors for bull/bear signals, TP/SL levels, and supply/demand zones
Trend Background: Optional background coloring to instantly visualize the current market bias
Support/Resistance Lines: Toggle automatic S/R level plotting from key price pivots
Multiple Arrow Sizes: Choose from tiny, small, normal, or large signal arrows
WHAT MAKES TRADEMY MARKET ANALYSIS PRO DIFFERENT
✅ Simplicity Meets Power
✅ TP/SL Levels
✅ Institutional Zone Integration
✅ Universal Indicator for all markets
✅ Multi-Timeframe Flexibility
BEST PRACTICES
📌 Always Use Stop-Loss: Enable the TP/SL system and respect your stop-loss levels,risk management is key to long-term success
📌 Backtest First: Before live trading, replay historical charts to understand signal behavior on your specific asset and timeframe
📌 Combine Timeframes: Use higher timeframe signals as your bias, enter on lower timeframe signals in the same direction
📌 Watch the Zones: Highest probability setups occur when signals align with supply/demand zones (buy near demand, sell near supply)
📌 Don't Chase: If you miss a signal, wait for the next one,forcing trades leads to losses
📌 Partial Profits: Consider taking partial profits at TP1, moving stop to breakeven, and letting the rest run to TP2/TP3
📩 ACCESS & SUPPORT
This is an invite-only indicator. For access inquiries, please contact via TradingView private message.
Important Disclaimers:
This indicator is a tool for technical analysis and does not constitute financial advice
Past performance does not guarantee future results
Always practice proper risk management and never risk more than you can afford to lose
Trading carries substantial risk of loss and is not suitable for all investors
Trend Tracer [AlgoAlpha]🟠 OVERVIEW
This tool builds a two-stage trend model that reacts to structure shifts while also showing how strong or weak the move is. It uses a mid-price band (from the highest high and lowest low over a lookback) and applies two Supertrend passes on top of it. The first pass smoothens the basis. The second pass refines that direction and produces the final trail used for signals. A gradient fill between the two trails uses RSI of price-to-trail distance to show when price is stretched or cooling off. The aim is to give traders a simple way to read trend alignment, pressure, and early turns without guessing.
🟠 CONCEPTS
The script starts with a mid-range basis. This is the average of the rolling highest high and lowest low. It acts as a stable structure reference instead of raw close or typical price. From there, two Supertrend layers are applied:
• The first Supertrend uses a shorter ATR period and lower factor. It reacts faster and sets the main regime.
• The second Supertrend uses a slightly longer ATR and higher factor. It filters noise, waits for confirmed continuation, and generates the signal line.
The interaction between these trails matters. The outer Supertrend provides context by defining the broader regime. The inner Supertrend provides timing by flipping earlier and marking possible shifts. The gradient fill uses RSI of (close − supertrend value) to display when price stretches away from the trail. This shows strength, exhaustion, or compression within the trend.
🟠 FEATURES
Bullish and bearish flip markers placed at recent highs/lows
Rejection signals off the trend tracer line
Alerts for bullish and bearish trend changes
🟠 USAGE
Setup : Add the script to your chart. Timeframe is flexible; lower timeframes show more flips while higher ones give cleaner swings. Adjust Length to change how wide the basis range is. Use the two ATR settings and factors to match the volatility of the market you trade.
Read the chart : When the refined trail (stv_) sits above price the regime is bearish; when below, it is bullish. The wide trail (stv) confirms the larger move. Watch the gradient fill: darker colors appear when price is stretched from the trail and lighter colors appear when the move is weakening. Flip markers ▲ or ▼ highlight the first clean shift of the refined trail.
Settings that matter : Increasing the Main Factor slows main-trend flips and filters chop. Increasing the Signal Factor delays the timing trail but reduces noise. Shortening Length makes the basis more reactive. ATR periods change how sensitive each Supertrend pass is to volatility.
Trend Step Channel [BigBeluga]🔵 OVERVIEW
Trend Step Channel identifies directional bias by forming a dynamic volatility-based step channel. It detects trend shifts when candle lows close above the upper band (bullish) or when candle highs drop below the lower band (bearish). A step-style midline tracks the trend evolution, while an integrated dashboard shows price positioning percentages across multiple timeframes.
🔵 CONCEPTS
ATR-Based Channel — The indicator constructs upper and lower channel boundaries using ATR distance around a single adaptive trend line, providing automatic scaling with volatility.
Trend Direction Logic —
• Low above upper band → uptrend confirmation.
• High below lower band → downtrend confirmation.
Step Trend Line — A reactive midline that locks onto price swings, stepping upward or downward as new trend confirmations occur.
Channel Width — Defines the total volatility range around the midline; a wider channel smooths market noise, while a narrower one reacts faster.
Price Position Ratio — Calculates the relative position of the close within the channel, from 0% (bottom) to 100% (top).
🔵 FEATURES
Volatility-Adaptive Channel — Expands and contracts dynamically to match market volatility, maintaining consistent distance scaling.
Configurable MA Source — Choose from SMA, EMA, SMMA, WMA, or VWMA as the base smoothing method.
Color-Coded Step Line —
• Green indicates an uptrend.
• Orange indicates a downtrend.
Channel Fill Visualization — Semi-transparent fills highlight active volatility zones for clear trend identification.
Price Position Label — Displays a “<” marker and percentage at the channel edge showing how far the current close is from the lower or upper band.
Multi-Timeframe Dashboard —
• Displays alignment across 1H–5H charts.
• Each cell shows an arrow (↑ / ↓) with price % positioning.
• Cell background color reflects bullish or bearish bias.
Real-Time Updating — The channel, midline, and dashboard refresh dynamically every bar for continuous feedback.
🔵 HOW TO USE
Trend Confirmation —
• Bullish trend forms when candle low closes above the upper band.
• Bearish trend forms when candle high closes below the lower band.
Trend Continuation — Maintain bias while the step line color remains consistent.
Volatility Breakouts — Sudden candle breaks outside the band suggest new directional strength.
Dashboard Alignment — Confirm trend consistency across multiple timeframes before entering trades.
Entry Planning — In uptrends, consider entries near the lower band; in downtrends, focus on upper-band rejections.
Price Position Insight — Use the % label to judge whether price is extended (near 100%) or compressed (near 0%) within the channel.
🔵 CONCLUSION
Trend Step Channel delivers a precise, volatility-driven view of trend structure using ATR-based boundaries and a step-line framework. The integrated dashboard, color-coded channel, and live positioning metrics give traders a complete picture of market direction, trend strength, and price location within evolving conditions.
SMC Statistical Liquidity Walls [PhenLabs]📊 SMC Statistical Liquidity Walls
Version: PineScript™ v6
📌 Description
The SMC Statistical Liquidity Walls indicator is designed to visualize market volatility and potential reversal zones using advanced statistical modeling. Unlike traditional Bollinger Bands that use simple lines, this script utilizes an “Inverted Sigmoid” opacity function to create a “fog of war” effect. This visualizes the density of liquidity: the further price moves from the equilibrium (mean), the “harder” the liquidity wall becomes.
This tool solves the problem of over-trading in low-probability areas. By automatically mapping “Premium” (Resistance) and “Discount” (Support) zones based on Standard Deviation (SD), traders can instantly see when price is overextended. The result is a clean, intuitive overlay that helps you identify high-probability mean reversion setups without cluttering your chart with manual drawings.
🚀 Points of Innovation
Inverted Sigmoid Logic: A custom mathematical function maps Standard Deviation to opacity, creating a realistic “wall” density effect rather than linear gradients.
Dynamic “Solidity”: The indicator is transparent at the center (Equilibrium) and becomes visually solid at the edges, mimicking physical resistance.
Separated Directional Bias: distinct Red (Premium) and Green (Discount) coding helps SMC traders instantly recognize expensive vs. cheap pricing.
Smart “Safe” Deviation: Includes fallback logic to handle calculation errors if deviation hits zero, ensuring the indicator never crashes during data gaps.
🔧 Core Components
Basis Calculation: Uses a Simple Moving Average (SMA) to determine the market’s equilibrium point.
Standard Deviation Zones: Calculates 1SD, 2SD, and 3SD levels to define the statistical extremes of price action.
Sigmoid Alpha Calculation: Converts the SD distance into a transparency value (0-100) to drive the visual gradient.
🔥 Key Features
Automated Premium/Discount Zones: Red zones indicate overbought (Premium) areas; Green zones indicate oversold (Discount) areas.
Customizable Density: Users can adjust the “Steepness” and “Midpoint” of the sigmoid curve to control how fast the walls become solid.
Integrated Alerts: Built-in alert conditions trigger when price hits the “Solid” wall (2SD or higher), perfect for automated trading or notifications.
Visual Clarity: The center of the chart remains clear (high transparency) to keep focus on price action where it matters most.
🎨 Visualization
Equilibrium Line: A gray line representing the mean price.
Gradient Fills: The space between bands fills with color that increases in opacity as it moves outward.
Premium Wall: Upper zones fade from transparent red to solid red.
Discount Wall: Lower zones fade from transparent green to solid green.
📖 Usage Guidelines
Range Period: Default 20. Controls the lookback period for the SMA and Standard Deviation calculation.
Source: Default Close. The price data used for calculations.
Center Transparency: Default 100 (Clear). Controls how transparent the middle of the chart is.
Edge Transparency: Default 45 (Solid). Controls the opacity of the outermost liquidity wall.
Wall Steepness: Default 2.5. Adjusts how aggressively the gradient transitions from clear to solid.
Wall Start Point: Default 1.5 SD. The deviation level where the gradient shift begins to accelerate.
✅ Best Use Cases
Mean Reversion Trading: Enter trades when price hits the solid 2SD or 3SD wall and shows rejection wicks.
Take Profit Targets: Use the Equilibrium (Gray Line) as a logical first target for reversal trades.
Trend Filtering: Do not initiate new long positions when price is deep inside the Red (Premium) wall.
⚠️ Limitations
Lagging Nature: As a statistical tool based on Moving Averages, the walls react to past price data and may lag during sudden volatility spikes.
Trending Markets: In strong parabolic trends, price can “ride” the bands for extended periods; mean reversion should be used with caution in these conditions.
💡 What Makes This Unique
Physics-Based Visualization: We treat liquidity as a physical barrier that gets denser the deeper you push, rather than just a static line on a chart.
🔬 How It Works
Step 1: The script calculates the mean (SMA) and the Standard Deviation (SD) of the source price.
Step 2: It defines three zones above and below the mean (1SD, 2SD, 3SD).
Step 3: The custom `get_inverted_sigmoid` function calculates an Alpha (transparency) value based on the SD distance.
Step 4: Plot fills are colored dynamically, creating a seamless gradient that hardens at the extremes to visualize the “Liquidity Wall.”
💡 Note
For best results, combine this indicator with Price Action confirmation (such as pin bars or engulfing candles) when price touches the solid walls.
Volatility Signal-to-Noise Ratio🙏🏻 this is VSNR: the most effective and simple volatility regime detector & automatic volatility threshold scaler that somehow no1 ever talks about.
This is simply an inverse of the coefficient of variation of absolute returns, but properly constructed taking into account temporal information, and made online via recursive math with algocomplexity O(1) both in expanding and moving windows modes.
How do the available alternatives differ (while some’re just worse)?
Mainstream quant stat tests like Durbin-Watson, Dickey-Fuller etc: default implementations are ALL not time aware. They measure different kinds of regime, which is less (if at all) relevant for actual trading context. Mix of different math, high algocomplexity.
The closest one is MMI by financialhacker, but his approach is also not time aware, and has a higher algocomplexity anyways. Best alternative to mine, but pls modify it to use a time-weighted median.
Fractal dimension & its derivatives by John Ehlers: again not time aware, very low info gain, relies on bar sizes (high and lows), which don’t always exist unlike changes between datapoints. But it’s a geometric tool in essence, so this is fundamental. Let it watch your back if you already use it.
Hurst exponent: much higher algocomplexity, mix of parametric and non-parametric math inside. An invention, not a math entity. Again, not time aware. Also measures different kinds of regime.
How to set it up:
Given my other tools, I choose length so that it will match the amount of data that your trading method or study uses multiplied by ~ 4-5. E.g if you use some kind of bands to trade volatility and you calculate them over moving window 64, put VSNR on 256.
However it depends mathematically on many things, so for your methods you may instead need multipliers of 1 or ~ 16.
Additionally if you wanna use all data to estimate SNR, put 0 into length input.
How to use for regime detection:
First we define:
MR bias: mean reversion bias meaning volatility shorts would work better, fading levels would work better
Momo bias: momentum bias meaning volatility longs would work better, trading breakouts of levels would work better.
The study plots 3 horizontal thresholds for VSNR, just check its location:
Above upper level: significant Momo bias
Above 1 : Momo bias
Below 1 : MR bias
Below lower level: significant MR bias
Take a look at the screenshots, 2 completely different volatility regimes are spotted by VSNR, while an ADF does not show different regime:
^^ CBOT:ZN1!
^^ INDEX:BTCUSD
How to use as automatic volatility threshold scaler
Copy the code from the script, and use VSNR as a multiplier for your volatility threshold.
E.g you use a regression channel and fade/push upper and lower thresholds which are RMSEs multiples. Inside the code, multiply RMSE by VSNR, now you’re adaptive.
^^ The same logic as when MM bots widen spreads with vola goes wild.
How it works:
Returns follow Laplace distro -> logically abs returns follow exponential distro , cuz laplace = double exponential.
Exponential distro has a natural coefficient of variation = 1 -> signal to noise ratio defined as mean/stdev = 1 as well. The same can be said for Student t distro with parameter v = 4. So 1 is our main threshold.
We can add additional thresholds by discovering SNRs of Student t with v = 3 and v = 5 (+- 1 from baseline v = 4). These have lighter & heavier tails each favoring mean reversion or momentum more. I computed the SNR values you see in the code with mpmath python module, with precision 256 decimals, so you can trust it I put it on my momma.
Then I use exponential smoothing with properly defined alphas (one matches cumulative WMA and another minimizes error with WMA in moving window mode) to estimate SNR of abs returns.
…
Lightweight huh?
∞
Change in State of Delivery CISD [AlgoAlpha]🟠 OVERVIEW
This script tracks how price “changes delivery” after failed attempts to push in one direction. It builds swing levels from pivots, watches for those levels to be wicked, and then checks if price delivers cleanly in the opposite direction. When the pattern meets the script’s tolerance rules, it marks a Change in State of Delivery (CISD). These CISD levels are drawn as origin lines and are used to spot shifts in intent, failed pushes, and continuation attempts. A CISD becomes stronger when it forms after opposing liquidity is swept within a defined lookback.
🟠 CONCEPTS
The script first defines structure using swing highs/lows. These levels act as potential liquidity points. When price wicks through a swing, the script registers a mitigation event. After this, it looks for a reversal-style candle sequence: a failed push, followed by a counter-move strong enough to pass a tolerance ratio. This ratio compares how far price expanded away from the failed attempt versus the counter-move that followed. If the ratio is high enough, this becomes a CISD. The idea is simple: liquidity interaction sets context , and the tolerance logic identifies actual intent . CISD levels and sweep markers combine these two ideas into a clean map of where delivery flipped.
🟠 FEATURES
Liquidity tracking: marks swing highs/lows and updates them until expiry
Liquidity sweep confirmation when CISD aligns with recent mitigations
Alert conditions for all key events: mitigations, CISDs, and strong CISDs
🟠 USAGE
Setup : Add the script to your chart. Use it on any timeframe where swing behavior matters. Set the Swing Period for how wide a pivot must be. Set Noise Filter to control how strict the CISD detection is. Liquidity Lookback defines how recent a wick must be to confirm a sweep.
Read the chart : Origin lines mark where the CISD began. A green line signals bullish intent; a red line signals bearish intent. ▲ and ▼ shapes show CISDs that form after liquidity is swept, these mark strong signals for potential entry. Swing dots show recent swing highs/lows. Candle colors follow the latest CISD trend.
Settings that matter : Increasing Swing Period produces fewer but stronger swings. Raising Noise Filter requires cleaner counter-moves and reduces false CISDs. Liquidity Lookback controls how strict the sweep confirmation is. Expiry Bars decides how long swing levels remain active.
