ATR Table (Top Right) - Multi Rangejust your friendly atr table to multiple ranges and for the sense of what is brewing
Volatilidade
SMA Cross + Adaptive Q MA + AMA Channel
📘 OPERATIONAL MANUAL: Adaptive Trend & SR Breakout SystemThis system combines non-parametric regression, volatility channels, and automated price action structures to identify high-probability entries.
1. Core IndicatorsAdaptive Q (KAMA): The primary trend line.
Green = Bullish;
Red = Bearish.
AMA Channel: An ATR-based envelope ($1.5 \times ATR$) that defines the "Value Area".
SMA 50 Filter: Global trend filter. Trade Long only above; Short only below.
SR Zones: Automatic boxes marking historical Support
(Blue/Green) and Resistance (Red).Shutterstock
2. Entry Rules
🟢 LONG SETUP:Price is above SMA 50.Large Lime Triangle appears (Channel Cross).Adaptive Q line is Green.Best entry: Price bounces off a Support Box.
🔴 SHORT SETUP:Price is below SMA 50.Large Red Triangle appears (Channel Cross).Adaptive Q line is Red.Best entry: Price rejects a Resistance Box.
3. Risk Management
Stop Loss: Set at $1.5 \times ATR$ or behind the nearest SR Box.
Take Profit: Target the next opposite SR Zone or exit if the Adaptive Q changes color.
4. LegendLarge Triangles: High-conviction volatility signals.
Small Triangles: Standard SMA Cross (early warning).
Red/Green Boxes: Supply and Demand zones for structural confirmation.
EDUVEST UTBOT ADJ - Adaptive ATR Trailing StopEDUVEST UTBOT ADJ - Adaptive ATR Trailing Stop with Session-Based Sensitivity
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█ ORIGINALITY
This indicator is an enhanced version of the classic UT Bot concept, featuring automatic session-based ATR sensitivity adjustment. Unlike the original UT Bot which uses a fixed sensitivity value, this version dynamically adapts to different trading sessions (Tokyo, London, New York) and automatically detects asset characteristics to optimize signal generation.
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█ WHAT IT DOES
- Generates BUY and SELL signals based on ATR trailing stop crossovers with a moving average
- Automatically adjusts sensitivity based on current trading session (Tokyo/London/NY)
- Auto-detects asset type and applies optimized parameters for each instrument
- Displays real-time session information and volatility status
- Provides alert functionality with customizable cooldown periods
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█ HOW IT WORKS
【Core Logic: ATR Trailing Stop】
The indicator calculates an ATR-based trailing stop using the formula:
Trailing Stop = Price ± (Sensitivity × ATR)
When price is above the trailing stop and rising, the stop trails below price.
When price is below the trailing stop and falling, the stop trails above price.
【Signal Generation】
- BUY Signal: Price crosses above the trailing stop AND Moving Average crosses above the trailing stop
- SELL Signal: Price crosses below the trailing stop AND Moving Average crosses below the trailing stop
【Session-Based Sensitivity Adjustment】
The indicator adjusts ATR sensitivity based on trading session (JST timezone):
- Tokyo (08:00-15:00): Lower sensitivity (reduced by adjustment value) - typically quieter markets
- London (15:00-23:00): Base sensitivity - moderate volatility
- New York (23:00-08:00): Higher sensitivity (increased by adjustment value) - higher volatility
【Dynamic ATR Adjustment】
When enabled, the indicator compares current ATR to its smoothed average:
- ATR Ratio = Current ATR / SMA(ATR, smoothing period)
- Volatility Multiplier = 1.0 + (Sensitivity × (2.0 - ATR Ratio))
This reduces sensitivity during high volatility (fewer false signals) and increases sensitivity during low volatility (faster response).
【Auto Asset Detection】
The indicator automatically detects the traded instrument and applies optimized parameters:
- Stable pairs (USDJPY, EURUSD, USDCHF): Base sensitivity 1.5-1.8
- Moderate pairs (AUDUSD, USDCAD, EURJPY): Base sensitivity 2.0-2.3
- Volatile pairs (GBPUSD): Base sensitivity 2.8
- Commodities (GOLD/XAUUSD): Base sensitivity 3.5
- Indices (NASDAQ/NAS100): Base sensitivity 4.0
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█ HOW TO USE
【Recommended Settings】
- Timeframe: 15 minutes or higher (15M, 1H, 4H recommended)
- Best performance on: Forex majors, Gold, NASDAQ
- Enable "Auto Asset Detection" for optimized parameters
【Entry Rules】
- BUY: Enter long when green BUY label appears
- SELL: Enter short when pink SELL label appears
【Session Panel】
The top-right panel displays:
- Current trading session (Tokyo/London/NY)
- Volatility status (High Chance/Medium Chance/Caution)
- Mode (AUTO/MANUAL)
【Alert Setup】
1. Enable "Viewer Alert Display" in settings
2. Set cooldown period (default: 15 minutes) to avoid signal spam
3. Create alert with "Any alert() function call" condition
【Important Notes】
- This indicator does not repaint - signals are confirmed at bar close
- Lower timeframes (1M, 5M) may generate excessive signals
- Always use proper risk management and confirm with other analysis
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█ SETTINGS OVERVIEW
🎯 Alert Settings
- Viewer Alert Display: Enable/disable alert labels
- Cooldown Function: Prevent rapid consecutive signals
- Cooldown Time: Minutes between alerts (5-60)
🔧 Dynamic ATR Settings
- Enable Dynamic ATR: Auto-adjust based on volatility
- ATR Period: Calculation period (default: 14)
- ATR Smoothing: Smoothing period for ratio calculation
- Volatility Sensitivity: How much to adjust (0.1-1.0)
🕐 Session ATR Adjustment
- Enable Time Adjustment: Session-based sensitivity
- Show Session Info: Display session panel
📊 Asset Settings
- Auto Asset Detection: Automatically optimize for instrument
- Manual settings available when auto-detection is disabled
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█ CREDITS
Based on the original UT Bot concept by QuantNomad.
Enhanced with session-based adaptation and auto-asset detection by EduVest.
License: Mozilla Public License 2.0
Aggro-15min Pro V4.2 [SMA200 + Vortex] (v6 Ready)🚀 Aggro-15min Pro
Aggro-15min Pro is a professional-grade algorithmic strategy optimized for the 15-minute timeframe. It combines structural trend analysis with aggressive momentum tracking to capture high-probability swings while filtering out market noise.
🛠️ How the Strategy Works
1. Structural Trend (The "Guardrail")
200 SMA: The strategy identifies the primary market direction. It only buys above the 200 SMA and only sells below it, ensuring you stay on the side of institutional flow.
2. Execution Trigger (The "Signal")
EMA Cross (9/50): A crossover of the 9-period Fast EMA and 50-period Slow EMA triggers the entry, identifying a confirmed shift in medium-term momentum.
3. Momentum Engine (The "Vortex")
Vortex Indicator (VI): Validates the "thrust" behind the move.
Dynamic Exit: Includes a "Vortex Reverse" logic that closes trades early if the directional energy fades, preserving capital before a full reversal occurs.
4. Risk & Volatility
ADX Filter: Prevents entries during low-volatility "sideways" periods.
ATR Risk Management: Uses the Average True Range to set dynamic Stop Loss and Take Profit levels that adapt to current market volatility.
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# 📂 STRATEGY PACKAGE: AGGRO-15MIN PRO
**Version:** 4.2 (Pine Script v6 Ready)
**Asset Class:** Crypto, Forex, Indices
**Timeframe:** 15 Minutes
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## 📘 1. OPERATIONS MANUAL (English)
### 🟢 Strategy Overview
Aggro-15min Pro is a momentum-based trend-following system. It uses a "Triple-Filter" logic to ensure that trades are only taken when long-term trend, medium-term momentum, and short-term volatility are perfectly aligned.
### 🟢 Technical Indicators Setup
* **Structural Filter:** 200-period Simple Moving Average (SMA).
* **Trigger Engine:** 9-period & 50-period Exponential Moving Averages (EMA).
* **Momentum Engine:** 14-period Vortex Indicator (VI).
* **Strength Filter:** 14-period Average Directional Index (ADX).
* **Volatility/Exits:** 14-period Average True Range (ATR).
### 🟢 Entry Checklist
#### LONG Position:
1. **Trend:** Price is **ABOVE** the 200 SMA.
2. **Trigger:** 9 EMA crosses **ABOVE** the 50 EMA.
3. **Vortex:** VIP (Positive) is **ABOVE** VIM (Negative).
4. **Strength:** ADX is **ABOVE** 20.
#### SHORT Position:
1. **Trend:** Price is **BELOW** the 200 SMA.
2. **Trigger:** 9 EMA crosses **BELOW** the 50 EMA.
3. **Vortex:** VIM (Negative) is **ABOVE** VIP (Positive).
4. **Strength:** ADX is **ABOVE** 20.
### 🟢 Exit Management
* **Take Profit (TP):** $3.0 \times ATR$ (Risk/Reward 1:2).
* **Stop Loss (SL):** $1.5 \times ATR$.
* **Dynamic Exit:** If the Vortex lines cross in the opposite direction (e.g., VIM > VIP during a Long), the strategy closes the position immediately to lock in profits or minimize loss.
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Asset Volatility Heatmap [SeerQuant]Asset Volatility Heatmap (AVH)
AVH is a cross-sectional volatility dashboard that ranks up to 30 assets and visualizes regime shifts as a time-series heatmap.
It computes annualized historical volatility (%) on a fixed 1D basis, then maps each asset’s volatility into a configurable color spectrum for fast, intuitive scanning of risk conditions across cryptocurrencies.
⚙️ How It Works
1. Daily, Annualized Historical Volatility
Each asset is measured on a fixed 1D timeframe (independent of your chart timeframe). Volatility is annualized and expressed in percentage terms. The user can choose between 1 of 4 volatility estimators: Close-Close (log returns stdev), Parkinson (H/L), Garman-Klass or Rogers-Satchell.
2. Heatmap
A heatmap is plotted on the lower window (sorting is turned on by default). Each row represents a rank position. (Rank #1 highest vol ... Rank #30 lowest vol). This means that tokens will move between rows over time as their volatility changes. The asset labels show the current token sitting in each rank bucket. This setting can be turned off for more of a "random" look.
3. Color Scaling
The user can select how the color range is normalized for visualization.
n = (v - scaleMin) / (scaleMax - scaleMin)
Cross-Section: Scales colors using the current bar’s cross-sectional min/max across the asset list.
Rolling: Scales colors using a lookback window of cross-sectional ranges, so today’s values are judged relative to recent volatility history.
Fixed: Uses your chosen Fixed Scale Min / Max for consistent benchmarking across time.
4. Contrast Control
The Color Contrast control option changes how aggressively the palette emphasizes extremes (useful for making “risk spikes” pop vs keeping gradients smooth).
5. Summary Table + Composite Read
The table highlights the highest vol / lowest vol token, along with average / median volatility, and a simple regime read (low / medium / high cross-sectional volatility).
✨ How to Use (Practical Reads)
Spot risk-on / risk-off transitions: When the heatmap “heats up” broadly (more hot colors across ranks), cross-sectional volatility is expanding (higher dispersion / risk).
Identify which names are driving the narrative: With sorting ON, the top ranks show which assets are currently the volatility leaders — often where attention, liquidity, and positioning stress is concentrated.
Use it as a regime overlay: Low/steady colors across most ranks tends to align with calmer conditions; sharp bright bursts signal volatility events.
✨ Customizable Settings
1. Assets
30 symbol inputs (defaults to crypto, but works across markets)
2. Calculation Settings
Length (lookback)
Volatility Estimator (Close-Close / Parkinson / GK / RS)
3. Style Settings
Color Scheme (SeerQuant / Viridis / Plasma / Magma / Turbo / Red-Blue)
Color Scaling (Cross-Section / Rolling / Fixed)
Scaling Lookback (for Rolling)
Fixed Scale Min / Max (for Fixed)
Color Contrast (emphasize extremes vs smooth gradients)
Sort Heatmap (High → Low)
Gradient Legend toggle
Focus Mode (highlights the chart symbol if included)
Ticker Label Right Padding
🚀 Features & Benefits
Cross-sectional volatility at a glance (dispersion/risk conditions)
Sortable rank heatmap for tracking “who’s hot” in volatility
Multiple estimators for different volatility philosophies
Flexible normalization (current cross-section, rolling context, or fixed benchmarks)
Clean legend + summary stats for quick context
📌 Notes
Sorting changes which token appears in each row over time (rows are rank buckets).
Volatility is computed on 1D even if your chart is lower/higher timeframe.
📜 Disclaimer
This indicator is for educational purposes only and does not constitute financial advice. Past performance does not guarantee future results. Always consult a licensed financial advisor before making trading decisions. Use at your own risk.
Pro Minimalist ATR (Black)The script I provided is a tool that automatically calculates and displays volatility "zones" around the average price. Here is the plain English explanation of what it is doing and why:
1. The Anchor: 20 DMA (The "Fair Value")
The script starts by calculating the 20-Day Moving Average (20 DMA).
What it represents: Think of this as the "fair price" or the "center of gravity" for the market over the last month.
In the script: It looks at the closing price of the last 20 candles, adds them up, and divides by 20. This is your baseline.
2. The Ruler: ATR (The "Volatility")
Next, it measures the Average True Range (ATR) over the last 14 days.
What it represents: This measures the "energy" or "noise" of the market. If candles are huge, the ATR is high. If candles are tiny, the ATR is low.
Why we use it: Using a fixed number (like $50) doesn't work because stocks move differently. ATR adapts to the current market mood.
3. The Zones: +1, +2, -1, -2
The script then takes that "center" (20 DMA) and adds/subtracts the "ruler" (ATR) to create four distinct levels:
+1 ATR: This is the "Upper Normal" limit. Price hanging here is bullish but normal.
+2 ATR: This is the "Extreme" limit. Statistically, price rarely stays above this line for long without snapping back. This is often an overbought signal.
-1 ATR: This is the "Lower Normal" limit.
-2 ATR: This is the "Extreme" discount. If price hits this, it is statistically stretched far below its average.
4. The Visuals: "Clean" Labeling
Finally, the script focuses on presentation:
No Lines: It specifically avoids drawing lines all over your history to keep your chart clean.
Dynamic Labels: It creates text labels only on the very last bar (the current moment). It constantly deletes the old label and draws a new one as the price moves, so it looks like the text is "floating" next to the current price.
Axis Marking: It forces marks onto the right-hand price scale (display=display.price_scale) so you can see the exact price levels (e.g., 154.20) without having to guess.
S&P 500 Momentum Coiling Tracker [20/200 MA]This indicator measures the absolute point distance between the 20-period SMA and the 200-period SMA, specifically optimized for the S&P 500 (ES/MES) index.
In the style of institutional trend following, it identifies the "Narrow State"—a period of low volatility where a major breakout is imminent.
How to read the Histogram:
🟢 GREEN (< 8 pts): Ultra-Narrow/Coiled State. Stored energy is high. Watch for an explosive breakout.
🟡 YELLOW (8-15 pts): Narrow/Transition. The averages are converging or just starting to fan out.
⚪ GRAY (15-30 pts): Neutral trending zone.
🔴 RED (> 30 pts): Extended State. Price is stretched far from the long-term mean; avoid chasing the move.
HOHO Oscillator Squeeze With Goldilocks Pivot FractalsDESCRIPTION:
HOHO Oscillator Squeeze With Goldilocks Pivot Fractals combines three powerful technical analysis methodologies into one comprehensive momentum indicator designed for identifying high-probability trading opportunities.
Core Components:
1. HOHO (Hump Oscillator)
Multi-timeframe momentum analysis using dual oscillators (fast and slow) to identify market momentum shifts. The histogram colors change based on momentum direction and strength, providing clear visual cues for trend changes.
2. Squeeze Detection
Bollinger Bands and Keltner Channel compression analysis identifies periods of low volatility (squeeze conditions) that often precede significant price moves. Yellow dots on the zero line indicate active squeeze conditions.
3. Goldilocks Pivot Fractals
Williams Fractals-based reversal detection identifies significant swing highs and lows. BUY and SELL signals are dynamically positioned to "hug" the histogram, providing clear entry and exit signals at major turning points.
Key Features:
- Dynamic Signal Positioning: Arrows and text automatically adjust to histogram height for optimal visibility
- Customizable Visual Elements: Full control over colors for arrows, text, squeeze dots, and histogram
- Multiple Alert Options: Configurable alerts for fractals, squeeze events, and momentum shifts
- Adjustable Sensitivity: Fractal periods can be tuned for different trading styles (lower = more signals, higher = fewer signals)
- Paint Bars Option: Optional bar coloring based on fast or slow oscillator momentum
- Non-Repainting: All signals are based on confirmed price action
- Independent Spacing Controls: Separate BUY and SELL text spacing for perfect visual balance
How to Use:
Entry Signals:
- BUY arrows appear below histogram at swing lows (bullish fractals)
- SELL arrows appear above histogram at swing highs (bearish fractals)
- Best entries occur when squeeze releases coincide with fractal signals
Momentum Confirmation:
- Green histogram = bullish momentum
- Red histogram = bearish momentum
- Lighter shades indicate weakening momentum
- Darker shades indicate strengthening momentum
Squeeze Conditions:
-Yellow dots = Volatility compression (squeeze active)
- Gray dots = Normal volatility (no squeeze)
- Watch for squeeze release followed by directional move
HOHO Settings:
- Adjustable MA lengths and types (EMA/SMA)
- Customizable smoothing parameters
Goldilocks Fractals:
- Fractal Periods: Sensitivity control (default: 2)
- Arrow Spacing: Distance from histogram (default: 2.0)
- BUY Text Spacing: Distance from BUY arrow (default: 1.7)
- SELL Text Spacing: Distance from SELL arrow (default: 0.8)
- Toggle arrows and text independently
Visual Customization:
- Arrow colors (bullish/bearish)
- Text colors (BUY/SELL)
- Squeeze dot colors (ON/OFF)
- Dot size adjustment
Alerts:
- Bullish/Bearish fractal detection
- Squeeze start/release
- Momentum shift crossovers
Best Practices:
- Trend Alignment: Use on higher timeframes (15m+) for more reliable signals
- Confluence: Combine fractal signals with momentum direction for higher probability trades
- Risk Management: Place stops beyond the fractal high/low that triggered the signal
- Squeeze Strategy: Wait for squeeze release before taking directional positions
- Filter Signals: Increase fractal periods (10-20) to focus only on major turning points
Recommended Timeframes:
- Scalping: 5m-15m (fractal periods 2-5)
- Day Trading: 15m-1H (fractal periods 5-10)
- Swing Trading: 4H-Daily (fractal periods 10-20)
Important Notes:
This indicator is provided for educational and informational purposes only. It is not financial advice. Past performance does not guarantee future results. Always perform your own analysis and use proper risk management. Trading involves substantial risk of loss.
BD SessionsSession boxes indicator for intraday charts.
Highlights up to four customizable market sessions using transparent boxes with clearly defined high/low ranges and labels.
Each session can be individually configured by name, time, timezone, and color.
EMA Trend Reversal (Regime Change)EMA Trend Reversal (Regime Change)
This indicator highlights EMA slope reversals that often coincide with trend or regime shifts, using a simple two-stage visual system.
It is especially effective on higher timeframes (Daily / Weekly) for swing trading and trend-bias awareness.
Detailed User Guide
What the signals mean
Confirmed signals (dots)
Green dot below price
- EMA slope has confirmed upward (bullish regime shift)
Red dot above price
- EMA slope has confirmed downward (bearish regime shift)
Confirmed dots only appear after the candle closes.
Unconfirmed signals (triangles)
Yellow triangle below price
- EMA is turning up intrabar (not yet confirmed)
Yellow triangle above price
- EMA is turning down intrabar (not yet confirmed)
Unconfirmed signals may repeat at a set interval until confirmation.
Alerts
This script provides two alerts:
EMA Reversal UP
EMA Reversal DOWN
Each alert can fire on:
Initial unconfirmed reversal
Reminder interval while unconfirmed
Final confirmed reversal
Alerts will NOT fire unless this indicator is active on at least one chart.
It may be kept on a chart you do not actively trade.
Settings
EMA Length (default: 21)
Reminder interval (minutes)
Show / hide unconfirmed triangles
Show / hide confirmed dots
Dot transparency
Colors (locked to preserve signal meaning)
Best use cases
Identifying trend or regime changes
Weekly swing trade entries and exits
Holding-period guidance during trends
Alert-based monitoring without watching charts
This is not a scalp or oscillator signal.
It works best when combined with structure, support/resistance, or higher-timeframe context.
Disclaimer
This indicator is provided for educational and informational purposes only.
It does not constitute financial, investment, or trading advice.
All trading involves risk. Use at your own discretion.
Dynamic ATR-based Renko Overlay - Non repaintingDaily ATR-Based Renko Overlay
Overview
This Pine Script v5 indicator creates a dynamic Renko overlay on your time-based charts (optimized for 1-minute timeframes), using the previous period's ATR from a user-specified higher timeframe (default: 1-hour) to determine brick sizes. Unlike traditional Renko charts, this is an overlay that draws Renko bricks directly on top of your existing candles, allowing you to combine the noise-filtering power of Renko with the full features of time-based charts.
It's designed for traders who want Renko's trend-clarity benefits without switching chart types, especially useful for intraday trading in volatile markets like forex, stocks, or crypto.
Key Features
- Adaptive Brick Sizing: Brick size is calculated as a percentage (default 40%) of the previous period's ATR (Average True Range, default length 14) from the selected higher timeframe (default: 1-hour). This makes bricks volatility-adjusted—larger in high-vol periods to reduce noise, smaller in low-vol for more detail.
- Periodic Recalculation: Resets brick size at the start of each new period based on the user-specified reset timeframe (default: daily), using the prior period's ATR from the chosen timeframe. This ensures relevance without unwanted disruptions.
- Traditional Renko Logic: Uses 1-box reversal (a full brick against the trend to reverse). Bricks form based on closing prices, ignoring time and minor fluctuations.
- Visual Style: Stepped lines with green (up) and red (down) fills for a box-like appearance. Semi-transparent for easy overlay on candles.
- Customizable Inputs:
- ATR Length: Adjust the ATR period (default: 14).
- Percentage of ATR: Fine-tune brick sensitivity (default: 0.4 or 40%; range 0-1).
- ATR Timeframe: Specify the timeframe for ATR calculation (default: "60" for 1-hour; enter as a string like "240" for 4-hour, "D" for daily, etc.).
- Reset Timeframe: Specify the period for recalculating the brick size (default: "D" for daily; enter as a string like "W" for weekly, "M" for monthly, etc.).
How It Works
1. Fetches ATR from the user-specified timeframe via `request.security` for higher-timeframe volatility data.
2. On new periods based on the reset timeframe (or first load), sets brick size to `percent * ATR_HTF`.
3. Tracks Renko "close" and "previous close" to calculate bricks:
- Upward moves add green bricks in multiples of the size.
- Downward moves add red bricks.
- Reversals require a full brick against the direction.
4. Plots and fills create the overlay, updating on each 1-min bar close.
Add it to a 1-minute chart for best results—bricks will adapt periodically while you retain full candle visibility.
Why This Indicator is Helpful
TradingView's native Renko charts are powerful but come with limitations that can frustrate serious traders:
- No Bar Replay: Native Renko doesn't support TradingView's bar replay feature, making it hard to simulate historical trading sessions.
- Inaccurate/Repainting Strategy Testing: Strategies on native Renko can repaint or lack precision due to the non-time-based nature, leading to unreliable backtests.
- Limited Data History: Fast Renko timeframes (e.g., small bricks) often load very little historical data, restricting long-term analysis.
This overlay solves these by building Renko on a time-based chart:
- Full Bar Replay Support: Replay sessions as usual on your 1-min chart—the Renko follows along.
- Accurate, Non-Repainting Testing: Test strategies on the underlying time chart without repainting issues, as Renko is derived from closes.
- Unlimited Data Depth: Access TradingView's full historical data for 1-min charts (up to years of bars), not limited by Renko's data constraints.
- Hybrid Analysis: Overlay Renko on candles to spot trends while using volume, indicators (e.g., RSI, MAs), or drawing tools that don't work well on native Renko.
It's a game-changer for trend-following, breakout strategies, or filtering noise in short-term trades. No more switching charts—get the best of both worlds!
Usage Tips
- Best on 1-min charts for intraday precision, but experiment with others.
- Tune the percentage lower (e.g., 0.3) for more bricks/sensitivity, higher (e.g., 0.5) for fewer/false-signal reduction.
- Adjust the ATR timeframe to match your strategy—e.g., "240" for longer-term volatility or "15" for shorter.
- Customize the reset timeframe for different recalculation frequencies—e.g., "W" for weekly resets to capture broader market shifts, or "240" for every 4 hours.
- Combine with alerts: right now I am experimenting with 90 period EMA and the Renko brick pullbacks to find some EDGE
If you find this useful, give it a thumbs up or share your tweaks in the comments. Feedback welcome—happy trading! 🚀
Daily ATR (Shown on All Timeframes)Daily ATR (Shown on All Timeframes) displays the Daily timeframe ATR on any chart you’re viewing, so you always know the current day’s average range without switching timeframes.
True Daily ATR (not chart ATR): The script pulls ATR from the Daily chart using request.security() and shows that value on every timeframe.
On-chart table (top-right): A clean 2-row table shows:
The label: Daily ATR (Length)
The ATR value, with an optional ATR-as-% of price readout.
Custom display controls:
ATR Length input (default 14)
Toggle to show ATR % of current price
Toggle to show/hide the table
Choose table text color
Choose table text size (Tiny → Huge)
Data Window output: The Daily ATR value is also plotted invisibly so it appears in TradingView’s Data Window for quick reference.
This is useful for gauging daily volatility, setting risk/position sizing, and comparing intraday movement to the stock’s typical daily range.
Daily ATR (Shown on All Timeframes)Daily ATR (Shown on All Timeframes) displays the Daily timeframe ATR on any chart you’re viewing, so you always know the current day’s average range without switching timeframes.
True Daily ATR (not chart ATR): The script pulls ATR from the Daily chart using request.security() and shows that value on every timeframe.
On-chart table (top-right): A clean 2-row table shows:
The label: Daily ATR (Length)
The ATR value, with an optional ATR-as-% of price readout.
Custom display controls:
ATR Length input (default 14)
Toggle to show ATR % of current price
Toggle to show/hide the table
Choose table text color
Choose table text size (Tiny → Huge)
Data Window output: The Daily ATR value is also plotted invisibly so it appears in TradingView’s Data Window for quick reference.
This is useful for gauging daily volatility, setting risk/position sizing, and comparing intraday movement to the stock’s typical daily range.
Intermarket Divergence (Futures vs Equity)Intermarket Divergence (Futures vs Equity)
This indicator detects intermarket divergence between a traded instrument (futures, CFD, or spot) and a related equity or ETF.
It highlights moments where price and its underlying market drivers disagree, often appearing before reversals or expansions.
🎯 What It Shows
Bullish divergence:
Price makes a lower low while the equity makes a higher low
Bearish divergence:
Price makes a higher high while the equity makes a lower high
Based on swing pivots, not candle noise
Designed for intraday context, not mechanical entries
✅ Recommended Use
XAUUSD (Gold) → GDX (default)
XAGUSD (Silver) → SIL
USOIL / WTI → XLE
(These guidelines are included directly in the indicator settings.)
🧭 How to Use
Apply on 15m–30m
Look for signals near key levels (PDH/PDL, Asia high/low, HTF structure)
Use price action for entries
Divergence is context, not a signal.
⚠️ Notes
Non-repainting
Signals are selective by design
Best during London & New York sessions
LiquidityPulse MTF Intrabar Micro-Structure Absorption DetectorLiquidityPulse MTF Intrabar Micro-Structure Absorption Detector
Non-repainting: Markers appear on bar close and do not change.
Important (if you can’t see any markers)
This indicator measures intrabar micro-structure and it can use seconds-based micro data on lower timeframes.
If you load it and don’t see anything:
Go to 15m or higher, or
In settings, change Micro feed (inside HTF bar) from Auto to 1m / 5m / 15m.
Auto will often choose a “micro” feed that’s very small when your HTF is small, which can affect what you see.
What this indicator does
This script is designed to highlight absorption-like conditions by analysing what happens inside each higher-timeframe (HTF) candle — not just the candle’s OHLC.
It looks for candles where:
price moves a lot internally (high intrabar activity),
the candle structure shows churn / rejection (wick dominates body),
and participation is elevated (relative high volume).
When those conditions align, the indicator prints a marker line at the wick extreme:
LW (Lower-wick marker) = printed at the candle’s low
UW (Upper-wick marker) = printed at the candle’s high
Each marker is then extended to the right (so it can be treated like a potential level).
Image shows a wick-dominant candle with an absorption marker: Markers appear when price shows strong intrabar movement, a wick-dominant candle structure, and elevated participation — a combination often associated with absorption-like behaviour.
How it works
A marker is created only when all three filters pass on a confirmed candle close:
1) Intrabar micro-speed (internal activity)
The script pulls intrabar closes from a lower timeframe (“micro feed”) and sums the absolute internal price changes inside the HTF candle.
It then converts this to a Z-score and checks it against the Speed-z threshold.
Higher threshold = fewer, stronger events.
2) Wick vs body (churn / rejection structure)
This measures how the HTF candle’s internal range compares to its net close-to-open movement using:
Churn ratio = (HTF range) / (HTF body)
If the candle has a large range but a relatively small body, it indicates that price moved extensively during the candle but made limited net progress by the close — a structure often associated with active two-sided participation and absorption-like behaviour.
3) Relative HTF volume (participation filter)
The script also Z-scores HTF volume and requires it to exceed the Volume z-score threshold.
This helps filter out candles that show apparent activity but occur on relatively low participation.
Multi-timeframe + micro-structure analysis: Image shows a 15 minute chart marker on the 1 minute timeframe. The indicator can analyse higher-timeframe candles (15 minute) while using lower-timeframe micro data inside each bar (1 minute). This allows absorption-style markers to be plotted with higher-timeframe context and intrabar detail.
Composite Intensity
When a marker triggers, the script calculates a Composite Intensity number (CI):
It’s a combined score based on how strongly each of the three conditions exceeded its threshold.
Higher CI = stronger absorption-style event
Higher CI = brighter chart marker
The table shows:
HTF and Micro timeframes being used
the last marker type (LW or UW)
the last CI value
Micro feed & multi-timeframe behaviour
This indicator always works as a two-layer system:
HTF candle (context) → the candle you’re analysing
Micro feed (inside HTF bar) → the intrabar data used to measure micro-speed
Higher-TF source
Chart timeframe = uses your chart timeframe as HTF
Manual = choose any HTF (example: chart = 1m, HTF = 15m → prints 15m absorption markers onto a 1m chart)
Micro feed options
Auto (recommended) picks a sensible micro feed based on HTF
Or choose 1s / 1m / 5m / 15m manually for performance/clarity
HTF direction filter (optional)
When enabled:
LW markers only print when the HTF candle closes bullish
UW markers only print when the HTF candle closes bearish
This is optional and is designed to reduce noise by aligning markers with the directional bias of the higher-timeframe candle.
Traders can use the absorption markers to:
Identify potential areas of interest where price showed unusually high intrabar activity but limited net progress by the close.
Mark reference levels where price may react again later, reflecting prior elevated participation and extensive intrabar movement areas.
Add structural context to existing analysis such as trend structure, support/resistance, session highs/lows, or other volume-based tools.
Compare behaviour across timeframes, by observing how absorption-style events on a higher timeframe align with lower-timeframe price action.
Image shows price reacting to a previous absorption markers level (Lines/ levels can be extended in the settings): Extended LW / UW markers can be observed as areas of prior absorption-like activity. Traders may watch how price behaves around these levels (reaction, acceptance, or rejection) alongside their own structure, liquidity, or risk management tools.
Key settings (what they change)
Higher-TF source / Higher-TF bar (manual): which candle timeframe is analysed
Micro feed (inside HTF bar): what intrabar resolution is used to calculate micro-speed
Speed-z threshold: how unusual intrabar activity must be
Wick/Body threshold: how large the candle’s total range must be compared to its body
Volume z-score threshold: how elevated HTF volume must be
Z-score look-back: how far back the indicator normalises speed/volume
Line extension (bars): raise if you want markers to behave more like extended levels
Max markers: how many markers remain on the chart at once
Alerts
Alerts trigger on candle close when an absorption marker is detected.
Disclaimer
This indicator does not measure true order flow or the full limit order book. It uses intrabar price activity, candle structure, and relative participation as interpretive tools to highlight absorption-like behaviour. It is not a buy/sell system, and all signals should be used with traders own confirmation and risk management.
STOP_TRADING_MODE📘 Release Notes
STOP_TRADING_MODE — Stable Release
Version: 1.0.0
Status: Stable / Production-ready
⸻
🎯 Purpose
This indicator is designed to identify market regimes, not to generate constant trade signals.
Its primary goal is to protect the trader from low-quality environments and highlight rare, high-quality interaction points with equilibrium.
⸻
🧠 Core Concepts
• STOP Mode — identifies impulsive, dangerous, or one-sided market conditions
• Equilibrium (MID / EQ) — represents the auction balance, not a trend level
• MAGNET vs SPRING — distinguishes range behavior from trend behavior
• EQ_HOLD — highlights valid reactions at equilibrium only in a range-friendly environment
⸻
✅ What’s Included
🔴 STOP Mode (Background Only)
• Red background marks:
• volatility spikes (ATR expansion)
• impulsive candles
• one-directional movement
• No entry signals
• Used strictly as a risk-environment filter
🟨 MID (Equilibrium Line)
• Calculated as SMA of HL2
• Acts as:
• Magnet in ranging markets
• Spring in trending markets
• Not a trade trigger by itself
🔁 MAGNET / SPRING Regime Detection
• Based on:
• frequency of MID crossings
• time spent near equilibrium
• market “trendiness” ratio
• Regime labels appear only when the regime changes
• Prevents constant label repainting or noise
🟢 EQ_HOLD Signal (Rare by Design)
• Triggered only when:
• STOP mode is OFF
• MID behaves as MAGNET
• price reacts cleanly at equilibrium
• Designed for micro-scaling / position management, not aggressive entries
• Low frequency = high informational value
⸻
🚫 What Was Removed (By Design)
• No STOP / STOP_OFF labels on chart (alerts only)
• No constant signal spam
• No reliance on trend prediction
• No “buy/sell” prompts
⸻
🎛 UI & Usability Improvements
• Clean, minimal visual layout
• Color logic aligned with meaning:
• 🔴 Risk / danger
• 🟨 Balance / structure
• 🟢 Action-permitted condition
• Optional toggles for regime and EQ_HOLD labels
⸻
🧪 Known Behavior (Not Bugs)
• MID crossing does not immediately change regime
• STOP may activate after entry — this signals risk management mode, not exit
• EQ_HOLD appears infrequently by intention
⸻
🧩 Intended Usage
• Best suited for:
• range-aware traders
• scale-in / scale-out strategies
• discretionary decision support
• Not intended for:
• high-frequency trading
• signal-following automation
• prediction-based entries
⸻
🧠 Design Philosophy
“Silence is a feature.”
If the indicator does nothing —
the market likely offers nothing worth doing.
H1 Liquidity Sweep Tracker🇬🇧 English: H1 Liquidity Sweep Tracker
Overview
The H1 Liquidity Sweep Tracker is a technical analysis tool designed for TradingView (Pine Script v5). It identifies "Liquidity Sweeps"—market movements where the price briefly breaches a significant level to trigger stop-loss orders before reversing.
Core Functions
H1 Level Detection: Regardless of your current timeframe (e.g., 1m, 5m, or 15m), the script automatically fetches the High and Low of the previous 1-hour candle.
Real-Time Monitoring: It tracks price action relative to these levels to identify failed breakouts.
Visual Indicators:
Horizontal Lines: Displays the H1 High (Red) and H1 Low (Green) from the previous hour.
Sweep Shapes: A triangle appears above/below the candle when a sweep is detected.
How it Works (The Logic)
A "Sweep" is triggered when the current price moves beyond the H1 boundary but fails to maintain that position:
Bullish Sweep: The price drops below the previous H1 Low (collecting sell-side liquidity) but closes back above it. This suggests a potential upward reversal.
Bearish Sweep: The price rises above the previous H1 High (collecting buy-side liquidity) but closes back below it. This suggests a potential downward reversal.
[GYTS] Volatility Toolkit Volatility Toolkit
🌸 Part of GoemonYae Trading System (GYTS) 🌸
🌸 --------- INTRODUCTION --------- 🌸
💮 What is Volatility Toolkit?
Volatility Toolkit is a comprehensive volatility analysis indicator featuring academically-grounded range-based estimators. Unlike simplistic measures like ATR, these estimators extract maximum information from OHLC data — resulting in estimates that are 5-14× more statistically efficient than traditional close-to-close methods.
The indicator provides two configurable estimator slots, weighted aggregation, adaptive threshold detection, and regime identification — all with flexible smoothing options via
GYTS FiltersToolkit integration.
💮 Why Use This Indicator?
Standard volatility measures (like simple standard deviation) are highly inefficient, requiring large amounts of data to produce stable estimates. Academic research has shown that range-based estimators extract far more information from the same price data:
• Statistical Efficiency — Yang-Zhang achieves up to 14× the efficiency of close-to-close variance, meaning you can achieve the same estimation accuracy with far fewer bars
• Drift Independence — Rogers-Satchell and Yang-Zhang correctly isolate variance even in strongly trending markets where simpler estimators become biased
• Gap Handling — Yang-Zhang properly accounts for overnight gaps, critical for equity markets
• Regime Detection — Built-in threshold modes identify when volatility enters elevated or suppressed states
↑ Overview showing Yang-Zhang volatility with dynamic threshold bands and regime background colouring
🌸 --------- HOW IT WORKS --------- 🌸
💮 Core Concept
The toolkit groups volatility estimators by their output scale to ensure valid comparisons and aggregations:
• Log-Return Scale (σ) — Close-to-Close, Parkinson, Garman-Klass, Rogers-Satchell, Yang-Zhang. These are comparable and can be aggregated. Annualisable via √(periods_per_year) scaling.
• Price Unit Scale ($) — ATR. Measures volatility in absolute price terms, directly usable for stop-loss placement.
• Percentage Scale (%) — Chaikin Volatility. Measures the rate of change of the trading range — whether volatility is expanding or contracting.
Only estimators with the same scale can be meaningfully compared or aggregated. The indicator enforces this and warns when mixing incompatible scales.
💮 Range-Based Estimator Overview
Range-based estimators utilise High, Low, Open, and Close prices to extract significantly more information about the underlying diffusion process than close-only methods:
• Parkinson (1980) — Uses High-Low range. ~5× more efficient than close-to-close. Assumes zero drift.
• Garman-Klass (1980) — Incorporates Open and Close. ~7.4× more efficient. Assumes zero drift, no gaps.
• Rogers-Satchell (1991) — Drift-independent. Superior in trending markets where Parkinson/GK become biased.
• Yang-Zhang (2000) — Composite estimator handling both drift and overnight gaps. Up to 14× more efficient.
💮 Theoretical Background
• Parkinson, M. (1980). The Extreme Value Method for Estimating the Variance of the Rate of Return. Journal of Business, 53 (1), 61–65. DOI
• Garman, M.B. & Klass, M.J. (1980). On the Estimation of Security Price Volatilities from Historical Data. Journal of Business, 53 (1), 67–78. DOI
• Rogers, L.C.G. & Satchell, S.E. (1991). Estimating Variance from High, Low and Closing Prices. Annals of Applied Probability, 1 (4), 504–512. DOI
• Yang, D. & Zhang, Q. (2000). Drift-Independent Volatility Estimation Based on High, Low, Open, and Close Prices. Journal of Business, 73 (3), 477–491. DOI
🌸 --------- KEY FEATURES --------- 🌸
💮 Feature Reference
Estimators (8 options across 3 scale groups):
• Close-to-Close — Classical benchmark using closing prices only. Least efficient but useful as baseline. Log-return scale.
• Parkinson — Range-based (High-Low), ~5× more efficient than close-to-close. Assumes zero drift. Log-return scale.
• Garman-Klass — OHLC-optimised, ~7.4× more efficient. Assumes zero drift, no gaps. Log-return scale.
• Rogers-Satchell — Drift-independent, handles trending markets where Parkinson/GK become biased. Log-return scale.
• Yang-Zhang — Gap-aware composite, most comprehensive (up to 14× efficient). Uses internal rolling variance (unsmoothed). Log-return scale.
• Std Dev — Standard deviation of log returns. Log-return scale.
• ATR — Average True Range in absolute price units. Useful for stop-loss placement. Price unit scale.
• Chaikin — Rate of change of range. Measures volatility expansion/contraction, not level. Percentage scale.
Smoothing Filters (10 options via FiltersToolkit):
• SMA / EMA — Classical moving averages
• Super Smoother (2-Pole / 3-Pole) — Ehlers IIR filter with excellent noise reduction
• Ultimate Smoother (2-Pole / 3-Pole) — Near-zero lag in passband
• BiQuad — Second-order IIR with configurable Q factor
• ADXvma — Adaptive smoothing, flat during ranging periods
• MAMA — MESA Adaptive Moving Average (cycle-adaptive)
• A2RMA — Adaptive Autonomous Recursive MA
Threshold Modes:
• Static — Fixed threshold values you define (e.g., 0.025 annualised)
• Dynamic — Adaptive bands: baseline ± (standard deviation × multiplier)
• Percentile — Threshold at Nth percentile of recent history (e.g., 80th percentile for high)
Visual Features:
• Level-based colour gradient — Line colour shifts with percentile rank (warm = high vol, cool = low vol)
• Fill to zero — Gradient fill intensity proportional to volatility level
• Threshold fills — Intensity-scaled fills when thresholds are breached
• Regime background — Chart background indicates HIGH/NORMAL/LOW volatility state
• Legend table — Displays estimator names, parameters, current values with percentile ranks (P##)
💮 Dual Estimator Slots
Compare two volatility estimators side-by-side. Each slot independently configures:
• Estimator type (8 options across three scale groups)
• Lookback period and smoothing filter
• Colour palette and visual style
This enables direct comparison between estimators (e.g., Yang-Zhang vs Rogers-Satchell) or between different parameterisations of the same estimator.
↑ Yang-Zhang (reddish) and Rogers-Satchell (greenish)
💮 Flexible Smoothing via FiltersToolkit
All estimators (except Yang-Zhang, which uses internal rolling variance) support configurable smoothing through 10 filter types. Using Infinite Impulse Response (IIR) filters instead of SMA avoids the "drop-off artefact" where volatility readings crash when old spikes exit the window.
Example: Same estimator (Parkinson) with different smoothing filters
Add two instances of Volatility Toolkit to your chart:
• Instance 1: Parkinson with SMA smoothing (lookback 14)
• Instance 2: Parkinson with Super Smoother 2-Pole (lookback 14)
Notice how SMA creates sharp drops when volatile bars exit the window, while Super Smoother maintains a gradual transition.
↑ Two Parkinson estimators — SMA (red mono-colour, showing drop-off artefacts) vs Super Smoother (turquoise mono colour, with smooth transitions)
↑ Garman-Klass with BiQuad (orangy) and 2-pole SuperSmoother filters (greenish)
💮 Weighted Aggregation
Combine multiple estimators into a single weighted average. The indicator automatically:
• Validates scale compatibility (only same-scale estimators can be aggregated)
• Normalises weights (so 2:1 means 67%:33%)
• Displays clear warnings when scales differ
Example: Robust volatility estimate
Combine Yang-Zhang (handles gaps) with Rogers-Satchell (handles drift) using equal weights:
• E1: Yang-Zhang (14)
• E2: Rogers-Satchell (14)
• Aggregation: Enabled, weights 1:1
The aggregated line (with "fill to zero" enabled) provides a more robust estimate by averaging two complementary methodologies.
↑ Yang-Zhang + Rogers-Satchell with aggregation line (thicker) showing combined estimate (notice how opening gaps are handled differently)
Example: Trend-weighted aggregation
In strongly trending markets, weight Rogers-Satchell more heavily since it's drift-independent:
• Estimator 1: Garman-Klass (faster, higher weight in ranging)
• Estimator 2: Rogers-Satchell (drift-independent, higher weight in trends)
• Aggregation: weights 1:2 (favours RS during trends)
💮 Adaptive Threshold Detection
Three threshold modes for identifying volatility regime shifts. Threshold breaches are visualised with intensity-scaled fills that grow stronger the further volatility exceeds the threshold.
Example: Dynamic thresholds for regime detection
Configure dynamic thresholds to automatically adapt to market conditions:
• High Threshold Mode: Dynamic (baseline + 2× std dev)
• Low Threshold Mode: Dynamic (baseline - 2× std dev)
• Show threshold fills: Enabled
This creates adaptive bands that widen during volatile periods and narrow during calm periods.
Example: Percentile-based thresholds
Use percentile mode for context-aware regime detection:
• High Threshold Mode: Percentile (96th)
• Low Threshold Mode: Percentile (4th)
• Percentile Lookback: 500
This identifies when volatility enters the top/bottom 4% of its recent distribution.
↑ Different threshold settings, where the dynamic and percentile methods show adaptive bands that widen during volatile periods, with fill intensity varying by breach magnitude. Regime detection (see next) is enabled too.
💮 Regime Background Colouring
Optional background colouring indicates the current volatility regime:
• High Volatility — Warm/alert background colour
• Normal — No background (neutral)
• Low Volatility — Cool/calm background colour
Select which source (Estimator 1, Estimator 2, or Aggregation) drives the regime display.
Example: Regime filtering for trade decisions
Use regime background to filter trading signals from other indicators:
• Regime Source: Aggregation
• Background Transparency: 90 (subtle)
When the background shows HIGH volatility (warm), consider tighter stops. When LOW (cool), watch for breakout setups.
↑ Regime background emphasis for breakout strategies. Note the interesting A2RMA smoothing for this case.
🌸 --------- USAGE GUIDE --------- 🌸
💮 Getting Started
1. Add the indicator to your chart
2. Estimator 1 defaults to Yang-Zhang (14) — the most comprehensive estimator for gapped markets
3. Keep "Annualise Volatility" enabled to express values in standard annualised form
4. Observe the legend table for current values and percentile ranks (P##). Hover over the table cells to see a little more info in the tooltip.
💮 Choosing an Estimator
• Trending equities with gaps — Yang-Zhang. Handles both drift and overnight gaps optimally.
• Crypto (24/7 trading) — Rogers-Satchell. Drift-independent without Yang-Zhang's multi-period lag.
• Ranging markets — Garman-Klass or Parkinson. Simpler, no drift adjustment needed.
• Price-based stops — ATR. Output in price units, directly usable for stop distances.
• Regime detection — Combine any estimator with threshold modes enabled.
💮 Interpreting Output
• Value (P##) — The volatility reading with percentile rank. "0.1523 (P75)" means 0.1523 annualised volatility at the 75th percentile of recent history.
• Colour gradient — Warmer colours = higher percentile (elevated volatility), cooler colours = lower percentile.
• Threshold fills — Intensity indicates how far beyond the threshold the current reading is.
• ⚠️ HIGH / 🔻 LOW — Table indicators when thresholds are breached.
🌸 --------- ALERTS --------- 🌸
💮 Direction Change Alerts
• Estimator 1/2 direction change — Triggers when volatility inflects (rising to falling or vice versa)
💮 Cross Alerts
• E1 crossed E2 — Triggers when the two estimator lines cross
💮 Threshold Alerts
• E1/E2/Aggr High Volatility — Triggers when volatility breaches the high threshold
• E1/E2/Aggr Low Volatility — Triggers when volatility falls below the low threshold
💮 Regime Change Alerts
• E1/E2/Aggr Regime Change — Triggers when the volatility regime transitions (High ↔ Normal ↔ Low)
🌸 --------- LIMITATIONS --------- 🌸
• Drift bias in Parkinson/GK — These estimators overestimate variance in trending conditions. Switch to Rogers-Satchell or Yang-Zhang for trending markets.
• Yang-Zhang minimum lookback — Requires at least 2 bars (enforced internally). Cannot produce instantaneous readings like other estimators.
• Flat candles — Single-tick bars produce near-zero variance readings. Use higher timeframes for illiquid assets.
• Discretisation bias — Estimates degrade when ticks-per-bar is very small. Consider higher timeframes for thinly traded instruments.
• Scale mixing — Different scale groups (log-return, price unit, percentage) cannot be meaningfully compared or aggregated. The indicator warns but does not prevent display.
🌸 --------- CREDITS --------- 🌸
💮 Academic Sources
• Parkinson, M. (1980). The Extreme Value Method for Estimating the Variance of the Rate of Return. Journal of Business, 53 (1), 61–65. DOI
• Garman, M.B. & Klass, M.J. (1980). On the Estimation of Security Price Volatilities from Historical Data. Journal of Business, 53 (1), 67–78. DOI
• Rogers, L.C.G. & Satchell, S.E. (1991). Estimating Variance from High, Low and Closing Prices. Annals of Applied Probability, 1 (4), 504–512. DOI
• Yang, D. & Zhang, Q. (2000). Drift-Independent Volatility Estimation Based on High, Low, Open, and Close Prices. Journal of Business, 73 (3), 477–491. DOI
• Wilder, J.W. (1978). New Concepts in Technical Trading Systems . Trend Research.
💮 Libraries Used
• VolatilityToolkit Library — Range-based estimators, smoothing, and aggregation functions
• FiltersToolkit Library — Advanced smoothing filters (Super Smoother, Ultimate Smoother, BiQuad, etc.)
• ColourUtilities Library — Colour palette management and gradient calculations
VIXO - VIX OscillatorVIXO (VIX Oscillator) is a volatility oscillator built from the CBOE Volatility Index (symbol: TVC:VIX). It helps visualize volatility regime shifts by combining a smoothed VIX RSI with a normalized VIX momentum component, plus a VIX histogram that becomes more/less prominent depending on how far VIX is from its moving average. It helps you assess whether market conditions may be approaching rare but powerful squeeze phases.
WHAT THIS INDICATOR PLOTS
1) VIX RSI (cyan line)
- RSI is calculated on the VIX close and then smoothed (SMA) to reduce noise.
- Use it to observe short-term momentum in volatility rather than price.
2) VIX Normalized Momentum (gray line)
- Momentum is measured as ROC (rate of change) of the VIX close.
- That ROC is normalized to a 0–100 scale using a rolling lookback window:
- 50 is the midpoint of the recent momentum range (neutral within the selected window).
- Values near 0/100 indicate momentum near the low/high of that lookback window.
3) VIX Value Bars (histogram)
- Histogram shows the raw VIX value.
- Bar visibility is dynamically adjusted (transparency changes) based on the ratio of VIX to its 21-period SMA:
- When VIX is close to its MA, bars are more transparent.
- When VIX deviates more from its MA (within a capped range), bars become more visible.
- If VIX High is below 30, the script intentionally keeps bars fully transparent to reduce visual clutter.
LEVELS (REFERENCE ONLY)
The horizontal levels are visual guides to help segment oscillator zones. They are not guarantees and should not be treated as standalone trade signals:
- 80: “Panic of Market”
- 60: “VIX says BUY” (label only; not financial advice)
- 50: “Neutral / Momentum Mid”
- 40: “Get Ready”
HOW TO USE
- Apply VIXO to any chart. The indicator always pulls TVC:VIX data, regardless of the chart symbol.
- Typical interpretation:
- Rising VIX RSI and/or rising normalized momentum can indicate increasing volatility pressure.
- Falling readings can indicate volatility easing.
- Compare changes in VIXO with your chart’s price structure, trend filters, or risk management framework.
INPUTS
- RSI Length: RSI period on VIX close (smoothed afterward).
- Momentum Length: ROC period on VIX close.
- Momentum Normalization Lookback: window used to scale ROC into 0–100.
DATA & BEHAVIOR NOTES
- Data source: request.security("TVC:VIX", timeframe.period, OHLC).
- The script does not use lookahead to access future data.
- On realtime bars, values can update while the current bar is forming; historical bars remain fixed once closed.
- Availability of TVC:VIX data depends on your TradingView data access.
IMPORTANT DISCLAIMER
This indicator is provided for educational and informational purposes only and does not constitute financial, investment, or trading advice. It does not predict the future, does not guarantee results, and should not be used as the sole basis for any trading decision. Always validate signals with additional analysis and use appropriate risk management.
Compression-to-Expansion Early Warning (CEEWS)The Compression → Expansion Early Warning System (CEEWS) is a volatility-structure and market-timing indicator designed to identify periods of statistical price compression and to signal when that compression transitions into directional expansion. Rather than predicting direction in advance, CEEWS focuses on detecting when price action becomes tightly constrained and then confirms when stored energy begins to release.
CEEWS quantifies compression using a composite of volatility contraction, range tightening, candle overlap, and reference-level convergence, producing a normalized Build score (0–100) that reflects the degree of latent price pressure. Elevated Build values indicate that the market is coiled and increasingly susceptible to movement, while expansion signals occur only when volatility begins to expand and price breaks from its recent range.
The indicator is intended as a timing and transition tool, not a standalone trend or directional system. CEEWS is most effective when paired with broader regime or trend-health indicators and is particularly well suited for index funds and highly liquid markets, where prolonged consolidation phases often precede sharp directional moves. Its primary purpose is to help traders identify when the market is likely to move, not to forecast where it will go.
[CT] Daily & Weekly Percentage Price Oscillator Daily & Weekly Percentage Price Oscillator, or D&W PPO, is a dual-speed momentum oscillator that blends a slower “weekly-style” percentage oscillator with a faster “daily-style” percentage oscillator, then turns the relationship between them into a clean histogram that is easy to trade. The script builds four EMAs from the chart’s close. The first pair, L1 and L2, is used to create the W component, which behaves like a slow, higher-timeframe trend pressure line. W is calculated as the percentage distance between EMA(L1) and EMA(L2), normalized by EMA(L2). When W is rising and positive, it tells you the broader momentum is expanding upward, and when W is falling and negative, the broader momentum is expanding downward. The second pair, L3 and L4, creates the D component, which behaves like a faster, lower-timeframe momentum pulse, also expressed as a percentage but normalized by the same EMA(L2), so both components share a consistent “scale.” The script then combines them into R = W + D, which represents the total blended momentum, where W supplies the slow structure and D supplies the fast impulse.
The indicator is plotted as a histogram using “R − W,” and that choice is intentional. Because R = W + D, the histogram value “R − W” is mathematically identical to D. In other words, the columns you see are the fast momentum component, but anchored to a clear baseline that reflects whether the fast component is adding to, or subtracting from, the slower component’s trend context. The zero line is the equilibrium point where R equals W, meaning the fast component is neutral relative to the slow trend context. When the histogram is above zero, the fast component is contributing positive momentum and the script colors the columns with the Bull color, indicating that R is above W and the short-term push is aligned to the upside. When the histogram is below zero, the fast component is contributing negative momentum and the script colors the columns with the Bear color, indicating that R is below W and the short-term push is aligned to the downside. If you enable “Color price bars,” the chart candles are painted with the same logic so you can visually stay in sync with the fast momentum regime without staring at the panel.
How to trade it comes down to treating the histogram as your actionable trigger layer and using its behavior around the zero line as the decision boundary. A basic long framework is to prioritize long trades when the histogram is above zero and either expanding or printing consecutive positive columns, because that tells you the fast momentum pulse is supportive and not fighting the current regime. The cleanest long entries usually occur when the histogram flips from negative to positive and holds above zero for at least a bar or two, because that transition often marks the shift from pullback pressure into renewed upside impulse. You can add selectivity by watching for a “dip and re-strengthen” pattern above zero: after a positive run, the histogram contracts toward the baseline without breaking materially below it, then turns back up, which often corresponds to a controlled pullback followed by continuation. A basic short framework is the mirror image: prioritize shorts when the histogram is below zero and expanding downward, and treat flips from positive to negative that hold below zero as the higher-quality transition into downside impulse. In both directions, the histogram is especially useful for avoiding trades during momentum dead zones, because when columns chop tightly around the zero line with frequent flips, it is signaling indecision and a lack of clean directional impulse, which is where most “false starts” tend to happen.
Risk management with this tool is straightforward because the oscillator gives you a natural invalidation concept. For long trades, a common invalidation is the histogram losing the zero line and staying negative, since that indicates the fast component has turned from supportive to opposing. For short trades, invalidation is the histogram regaining the zero line and holding positive. Another practical way to manage trades is to use histogram contraction as an early warning that the impulse is weakening. If you are long and positive columns begin to shrink toward zero for several bars, you can tighten risk, take partials, or wait for a fresh expansion before adding. If you are short and negative columns begin to shrink toward zero, the same concept applies. The optional W line can be shown if you want a visual anchor of the slow component; while the histogram is already built to reflect the fast component relative to the slow context, viewing W can help you quickly recognize whether the larger momentum backdrop is generally rising or falling, which can be used as an additional bias filter for trade selection.
In practice, the D&W PPO is best used as a momentum alignment and timing tool: the slow component defines the “weather,” the fast component defines the “wind,” and the histogram tells you whether the wind is pushing with the weather or pushing against it. When the histogram is cleanly one-sided and expanding, it supports continuation-style trading and trend-following entries. When the histogram is choppy around zero, it warns you that conditions are rotational and patience usually pays.
Minervini Ultimate +VCPMinervini Ultimate Suite (SEPA Dashboard)
This indicator implements Mark Minervini's "Trend Template" criteria combined with a Volatility Contraction Pattern (VCP) detector and a custom Relative Strength rating. It is designed to help traders visualize the technical health of a stock based on stage analysis concepts.
This indicator serves as a complete Control System (Dashboard) for Mark Minervini's SEPA trading strategy. Instead of manually checking five different metrics on every chart, this indicator performs the mathematical calculations and presents the "bottom line" in a single, organized table.
1. What This Indicator Does
The goal is to ensure you never enter a trade blindly. It verifies the stock against Minervini's strict requirements:
Trend: Is the stock in a healthy Stage 2 Uptrend?
Relative Strength: Is it stronger than the general market?
Buy Risk: Is it the right time to buy, or is the price extended?
Pressure: Are institutions accumulating or distributing?
VCP: Is there a breakout opportunity (volatility contraction) right now?
2. Key Benefits
Time-Saving: Instead of drawing lines and calculating percentages manually, you get immediate visual feedback (Green/Red).
Discipline: The indicator will flag "Extended" (Red) if you attempt to buy a stock that has run up too much, saving you from late entries and unnecessary losses.
Precision Timing: The VCP feature (Blue Dots) helps you identify the "calm before the storm"—the exact moment volatility contracts, which often precedes a major breakout.
3. Indicator Parameters & Features
A. Minervini Pressure (Buying vs. Selling)
What it checks: Money flow over the last 20 days.
Calculation: Sums up volume on "Up Days" (Green) versus volume on "Down Days" (Red).
Meaning:
🟢 Buying: More money is entering than leaving. A sign of institutional accumulation.
🔴 Selling: Selling pressure dominates. The price may be rising, but without strong volume backing.
B. Buy Risk (Price Extension)
What it checks: The distance of the current price from the 50-Day Moving Average. Minervini strictly warns against "chasing" stocks.
Signals:
🟢 Low Risk: Price is within 0% – 15% of the 50MA. This is the ideal "Buy Zone".
🟡 Caution: Price is 15% – 25% away. Buy with increased caution.
🔴 Extended: Price is >25% from the MA. Do not buy. The probability of a pullback is high.
⚪ Broken: Price is below the 50MA. The short-term trend is damaged.
C. TPR - Trend Template (Trend Power Rating)
What it checks: Is the stock in a Stage 2 Uptrend?
Strict Rules (All must be true for a PASS):
Price > 50MA > 150MA > 200MA.
The 200MA is trending UP (positive slope).
Price is near the 52-Week High (within 25%).
Price is above the 52-Week Low (at least 25%).
Meaning:
🟢 PASSED: Technically healthy and ready to move.
🔴 FAILED: The trend structure is broken (e.g., MAs are entangled).
D. RPR Score (Relative Performance Rating)
What it checks: How strong the stock is compared to the general market (S&P 500 / SPY).
Calculation: Weighted performance over 3, 6, 9, and 12 months vs. the SPY. The score ranges from 1 to 99.
Meaning:
🟢 80-99: Market Leader. These are the stocks Minervini targets.
🟡 70-80: Good, but not elite.
⚪ Below 70: Laggard (weaker than the market).
E. VCP Action (Volatility Contraction Pattern)
What it checks: Monitors price tightness. It calculates the range between the highest close and lowest close over the last 5 days.
Meaning:
🔵 SQUEEZE (Blue Text + Blue Dot on Chart): The price range has contracted to less than 2.5%.
Why it matters: When a stock stops moving wildly and trades in a tight range ("Flat Line"), it indicates supply has dried up. A high-volume breakout often follows immediately.
Adaptive Quant RSI [ML + MTF]This is an advanced momentum indicator that integrates Machine Learning (K-Means Clustering) with Multi-Timeframe (MTF) analysis. Unlike traditional RSI which uses fixed 70/30 levels, this script dynamically calculates support and resistance zones based on real-time historical data distribution.
Key Features:
🤖 ML Dynamic Thresholds: Uses K-Means clustering to segment RSI data into clusters, automatically plotting dynamic long/short thresholds that adapt to market volatility.
⏳ MTF Trend Background: The background color changes based on a Higher Timeframe (e.g., 5-min) RSI trend, helping you align with the broader market direction.
📊 Extreme Statistics: Incorporates percentile analysis (95th/5th) and historical pivots to identify extreme overbought/oversold conditions with high reversal probability.
📈 Probability Analysis: Displays the statistical probability of the current RSI value being at the top or bottom of its historical range.
Usage: Look for confluence between the dynamic ML thresholds and the MTF background color to identify high-probability reversal setups.
