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.
Volatilidad
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.
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! 🚀
Simple RSI Strategy - Rule Based Higher Timeframe Trading
HOW IT WORKS
With the default settings, the strategy buys when RSI reaches 30 and closes when RSI reaches 40 .
That’s it.
A simple, rule-based mean reversion strategy designed for higher timeframes , where market noise is lower and trading becomes easier to manage.
Core logic:
Long when RSI moves into oversold territory
Exit when RSI mean-reverts upward
Optional short trades from overbought levels
One position at a time (no pyramiding)
No filters.
No discretion.
Just clear, testable rules.
MARKETS & TIMEFRAMES
This strategy is intended for:
Indices (Nasdaq, S&P 500, DAX, etc.)
Liquid futures and CFDs
Higher timeframes: 2H, 4H and Daily
The published example is Nasdaq (NDX) on the 2-hour timeframe .
Higher timeframes are strongly recommended.
HOW TO USE IT
Apply the strategy on a higher timeframe
Adjust RSI levels per market if needed
Use TradingView alerts to avoid constant screen-watching
Focus on execution, risk control, and consistency
This strategy is meant to be a building block , not a complete trading business on its own.
For long-term consistency, it works best when combined with other uncorrelated, rule-based systems.
IMPORTANT
This is not financial advice
All results are historical and not indicative of future performance
Always forward-test and apply proper risk management
For additional notes, setups and related systems, visit my TradingView profile page .
JPX Stop High/Low Limits by Koji- Japanese Description :
日本株における値幅制限のスクリプト by Koji
X : Koji26650263 Youtube : www.youtube.com
【背景】
①日本株におけるストップ安・ストップ高の値幅制限について
価格によって値幅が変動するために、フル板で見れる場合はよいですが
トレード時に覚えたり計算する必要があります
②またチャートを分析する際に、過去のストップ安の日や連続ストップしているのか
など、チャートを拡大しないとわかりづらい
【本スクリプトのメリット】
①チャート上に視覚的に表示することで瞬間的に認知できることとし
ストップを狙っているか、などを板を見ないでチャートで判断できます
②過去のストップの位置をわかりやすく表示でき、過去の値動きを瞬間的に認知できます
【おすすめ】
チャートはローソク足や出来高など、極力シンプルにすべきなために
当スクリプトを導入はした上で、普段は表示オフ（目のマークをオフ）にしておくと
必要な時にすぐに見れるがチャートは普段見やすい、という使い方がおすすめです
- English Description :
Japanese Stock Price Limits (Stop High/Low) Indicator by Koji
X: Koji26650263 YouTube: www.youtube.com
【Background】
1. About Daily Price Limits (Stop High/Stop Low) in Japanese Stocks The daily price limit range for Japanese stocks varies depending on the stock price itself. Unless you have access to "Full Board" (Level 2) data, you often need to memorize these ranges or calculate them manually during trading, which can be cumbersome.
2. Analyzing Historical Volatility When analyzing charts, it can be difficult to identify past "Stop Low" or "Stop High" days—or to see if a stock hit consecutive stops—without zooming in significantly on the chart.
【Benefits of this Script】
1. Instant Visual Recognition By displaying price limits directly on the chart, you can instantly recognize the day's upper and lower limits. This allows you to judge whether the price is aiming for a "Stop High" or "Stop Low" without needing to check the order book (board).
2. Historical Context Past stop levels are clearly marked, allowing you to instantly grasp historical price movements and volatility at a glance.
【Recommended Usage】
To keep your chart analysis effective, it is best to keep the screen simple (displaying primarily candlesticks and volume).
My recommendation: Add this script to your chart, but keep the visibility toggled OFF (click the "eye" icon to hide it) during normal use. Toggle it ON only when you specifically need to check price limits. This ensures your chart remains clean and easy to read for daily analysis.
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
Apex Adaptive Trend Navigator [Pineify]Apex Adaptive Trend Navigator
The Apex Adaptive Trend Navigator is a comprehensive trend-following indicator that combines adaptive moving average technology, dynamic volatility bands, and market structure analysis into a single, cohesive trading tool. Designed for traders who want to identify trend direction with precision while filtering out market noise, this indicator adapts its sensitivity based on real-time market efficiency calculations.
Key Features
Adaptive Moving Average with efficiency-based smoothing factor
Dynamic ATR-based volatility bands that expand and contract with market conditions
Market Structure detection including BOS (Break of Structure) and CHoCH (Change of Character)
Real-time performance dashboard displaying trend status and efficiency metrics
Color-coded cloud visualization for intuitive trend identification
How It Works
The core of this indicator is built on an Adaptive Moving Average that uses a unique efficiency-based calculation method inspired by the Kaufman Adaptive Moving Average (KAMA) and TRAMA concepts. The efficiency ratio measures the directional movement of price relative to total price movement over the lookback period:
Efficiency = |Price Change over N periods| / Sum of |Individual Bar Changes|
This ratio ranges from 0 to 1, where values closer to 1 indicate a strong trending market with minimal noise, and values closer to 0 indicate choppy, sideways conditions. The smoothing factor is then squared to penalize noisy markets more aggressively, causing the adaptive line to flatten during consolidation and respond quickly during strong trends.
The Dynamic Volatility Bands are calculated using the Average True Range (ATR) multiplied by a user-defined factor. These bands create a channel around the adaptive moving average, helping traders visualize the current volatility regime and potential support/resistance zones.
Trading Ideas and Insights
When price stays above the adaptive line with the bullish cloud forming, consider this a confirmation of uptrend strength
The efficiency percentage in the dashboard indicates trend quality - higher values suggest more reliable trends
Watch for price interactions with the upper and lower bands as potential reversal or continuation zones
A flat adaptive line indicates consolidation - wait for a clear directional break before entering trades
How Multiple Indicators Work Together
This indicator integrates three complementary analytical approaches:
The Adaptive Moving Average serves as the trend backbone, providing a dynamic centerline that automatically adjusts to market conditions. Unlike fixed-period moving averages, it reduces lag during trends while minimizing whipsaws during ranging markets.
The ATR Volatility Bands work in conjunction with the adaptive MA to create a volatility envelope. When the adaptive line is trending and price remains within the cloud (between the MA and outer band), this confirms trend strength. Price breaking through the opposite band may signal exhaustion or reversal.
The Market Structure Analysis using swing point detection adds a Smart Money Concepts (SMC) layer. BOS signals indicate trend continuation when price breaks previous swing highs in uptrends or swing lows in downtrends. CHoCH signals warn of potential reversals when the structure shifts against the prevailing trend.
Unique Aspects
The squared efficiency factor creates a non-linear response that dramatically reduces noise sensitivity
Cloud fills only appear on the trend side, providing clear visual distinction between bullish and bearish regimes
The integrated dashboard eliminates the need to switch between multiple indicators for trend assessment
Pivot-based swing detection ensures accurate market structure identification
How to Use
Add the indicator to your chart and adjust the Lookback Period based on your trading timeframe (shorter for scalping, longer for swing trading)
Monitor the cloud color - green clouds indicate bullish conditions, red clouds indicate bearish conditions
Use the efficiency reading in the dashboard to gauge trend reliability before entering positions
Consider entries when price pulls back to the adaptive line during strong trends (high efficiency)
Use the volatility bands as dynamic take-profit or stop-loss reference levels
Customization
Lookback Period : Controls the sensitivity of trend detection and swing point identification (default: 20)
Volatility Multiplier : Adjusts the width of the ATR bands (default: 2.0)
Show Market Structure : Toggle visibility of BOS and CHoCH labels
Show Performance Dashboard : Toggle the trend status table
Color Settings : Customize bullish, bearish, and neutral colors to match your chart theme
Conclusion
The Apex Adaptive Trend Navigator offers traders a sophisticated yet intuitive approach to trend analysis. By combining adaptive smoothing technology with volatility measurement and market structure concepts, it provides multiple layers of confirmation for trading decisions. Whether you are a day trader seeking quick trend identification or a swing trader looking for reliable trend-following signals, this indicator adapts to your market conditions and trading style. The efficiency-based calculations ensure you always know not just the trend direction, but also the quality and reliability of that trend.
[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.
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.
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.
IV Rank & Percentile Suite V1.0What This Indicator Does
The IV Rank & Percentile Suite provides the volatility context options traders need to time entries. It calculates two complementary metrics—IV Rank and IV Percentile—using historical volatility as a proxy, then displays clear visual zones to identify favorable conditions for premium selling strategies.
Stop guessing if volatility is "high" or "low." This indicator tells you exactly where current volatility sits relative to recent history.
The Two Metrics Explained
IV Rank (0-100) Measures where current volatility sits within its 52-week high-low range.
IV Rank = (Current HV - 52w Low) / (52w High - 52w Low) × 100
70 means current volatility is 70% of the way between the yearly low and high
Sensitive to extreme spikes (a single high reading affects the range)
IV Percentile (0-100) Measures what percentage of days in the lookback period had lower volatility than today.
IV Percentile = (Days with lower HV / Total days) × 100
70 means volatility was lower than today on 70% of days in the past year
More stable, less affected by outlier spikes
Why Both?
IV Rank reacts faster to volatility changes. IV Percentile is more stable and statistically robust. When both agree (e.g., both above 50), you have stronger confirmation. Divergence between them can signal transitional periods.
Zone System
The indicator divides readings into three zones:
Zone ------- Default Range ---- Meaning ------------------ Premium Selling
🟢 High ≥ 50 Elevated volatility Favorable
🟡 Neutral 25-50 Normal volatility Selective
🔴 Low ≤ 25 Compressed volatility Avoid
An additional Extreme threshold (default 75) highlights prime conditions when volatility is significantly elevated.
Zone thresholds are fully customizable in settings.
How to Use It
For Premium Sellers (Iron Condors, Credit Spreads, Strangles)
Wait for IV Rank to enter the green zone (≥50)
Confirm IV Percentile agrees (also elevated)
Enter premium selling positions when both metrics align
Avoid initiating new positions when in the red zone
For Premium Buyers (Long Options, Debit Spreads)
Low IV Rank/Percentile means cheaper options
Red zone can favor directional debit strategies
Avoid buying premium when both metrics are in the green zone
General Principle:
Sell premium when volatility is high (it tends to revert to mean). Buy premium when volatility is low (if you have a directional thesis).
Inputs
Volatility Calculation
HV Period — Lookback for historical volatility calculation (default: 20)
Trading Days/Year — 252 for stocks, 365 for crypto
Lookback Periods
IV Rank Lookback — Period for high/low range (default: 252 = 1 year)
IV Percentile Lookback — Period for percentile calculation (default: 252)
Zone Thresholds
High IV Zone — Readings above this are highlighted green (default: 50)
Low IV Zone — Readings below this are highlighted red (default: 25)
Extreme High — Threshold for "prime" conditions alert (default: 75)
Display Options
Toggle IV Rank, IV Percentile, and raw HV display
Show/hide zone backgrounds
Show/hide info panel
Panel position selection
Info Panel
The panel displays:
Field ------- Description
IV Rank ------- Current reading with color coding
IV Pctl ------- Current percentile with color coding
HV 20d ------- Raw historical volatility percentage
52w Range ------- Lowest to highest HV in lookback period
Zone ------- Current zone status
Premium ------- Signal quality for premium selling
Lookback ------- Days used for calculations
R/P Spread ------- Difference between Rank and Percentile
Alerts
Six alerts are available:
Zone Transitions
IV Entered High Zone — Favorable for premium selling
IV Reached Extreme Levels — Prime conditions
IV Dropped to Low Zone — Caution for premium sellers
Threshold Crosses
IV Rank Crossed Above High Threshold
IV Rank Crossed Below Low Threshold
IV Percentile Above 75
IV Percentile Below 25
Set up alerts to get notified when conditions change without watching charts.
Technical Notes
Volatility Calculation Method
This indicator uses close-to-close historical volatility as an IV proxy:
Calculate log returns: ln(Close / Previous Close)
Take standard deviation over HV Period
Annualize: multiply by √(Trading Days)
This method correlates well with implied volatility for most liquid instruments. On highly liquid options underlyings (SPY, QQQ, major stocks), HV and IV tend to move together, making this a reliable proxy for IV Rank analysis.
Non-Repainting
All calculations use confirmed bar data. Values are fixed once a bar closes.
Lookback Requirement
The indicator needs sufficient history to calculate accurately. For a 252-day lookback, ensure your chart has at least 300+ bars of data.
Best Used On
ETFs: SPY, QQQ, IWM, DIA
Indices: SPX, NDX
High-volume stocks: AAPL, TSLA, NVDA, AMD, META
Timeframe: Daily (recommended), Weekly for longer-term view
The indicator works on any instrument but is most meaningful on underlyings with active options markets.
Important Notes
⚠️ This indicator uses historical volatility as a proxy for implied volatility. While HV and IV are correlated, they are not identical. For precise IV data, consult your options broker's platform.
⚠️ High IV Rank does not guarantee profitable premium selling. It indicates favorable conditions, not guaranteed outcomes. Position sizing and risk management remain essential.
⚠️ Past volatility patterns do not guarantee future behavior. Volatility regimes can shift, and historical ranges may not predict future ranges.
Suggested Workflow
Add to daily chart of your preferred underlying
Set up alert for "IV Entered High Zone"
When alerted, check both IV Rank and IV Percentile
If both elevated, evaluate premium selling opportunities
Use your broker's actual IV data for final entry decisions
Questions? Leave a comment below.
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.
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.
Bollinger Aurora Velocity [Pineify]Pineify - Bollinger Aurora Velocity
The Bollinger Aurora Velocity is an enhanced volatility and trend analysis indicator that transforms the classic Bollinger Bands into a visually stunning, multi-dimensional trading tool. By combining standard deviation bands with historical extreme tracking and dynamic momentum coloring, this indicator provides traders with deeper insights into volatility cycles, squeeze conditions, and trend strength all in one overlay.
Key Features
Classic Bollinger Bands with customizable period and standard deviation multiplier
Nebula Memory Cloud tracking historical band extremes for volatility context
Volatility Squeeze Detection with visual dot indicators on the basis line
Gradient-based candle coloring reflecting normalized price position
Multi-layer aurora gradient fills for intuitive visual analysis
How It Works
The indicator begins with a standard Bollinger Bands calculation using a simple moving average as the basis line, with upper and lower bands placed at a user-defined multiple of standard deviation. This core structure measures price volatility and identifies overbought/oversold conditions.
The Nebula Memory Cloud extends beyond traditional bands by tracking the highest point of the upper band and lowest point of the lower band over a configurable lookback period. This creates an outer envelope showing the maximum volatility expansion in recent history.
Trading Ideas and Insights
The Volatility Squeeze is a powerful concept where contracting Bollinger Bands often precede significant price breakouts. This indicator detects squeezes by comparing the current band width to its 100-period simple moving average. When the current range falls below this average, yellow dots appear on the basis line, alerting traders to potential explosive moves ahead.
When squeeze dots appear and the outer nebula cloud shows significant distance from the current bands, it suggests volatility is at a historical low relative to recent extremes—a setup often followed by strong directional moves.
How Multiple Indicators Work Together
Bollinger Bands establish the primary volatility envelope and mean-reversion zones
The Nebula Cloud provides historical context, showing how current volatility compares to recent extremes
Squeeze Detection identifies compression phases using relative bandwidth analysis
Normalized Scoring translates price position into a 0-100 scale for gradient coloring
Unique Aspects
Unlike standard Bollinger Bands indicators, the Aurora Velocity creates a heat-map effect on price bars. The normalized score calculates where price sits within the bands as a percentage, then applies a smooth gradient from bearish to bullish colors. This allows traders to instantly perceive momentum strength—saturated bullish colors near the upper band indicate strong upward pressure, while saturated bearish colors near the lower band signal selling dominance.
The aurora-style gradient fills between band layers create visual depth, making it easy to distinguish the core volatility zone from the historical extreme boundaries.
How to Use
Monitor candle colors for momentum direction—bright green indicates bullish positioning, bright red signals bearish pressure
Watch for yellow squeeze dots on the basis line as early warning for potential breakouts
Use the outer nebula cloud to assess if current volatility is testing historical extremes
Set alerts for price breakouts above the upper band or below the lower band
Combine squeeze conditions with the nebula cloud width to gauge breakout potential
Customization
Base Period - Controls Bollinger Bands calculation length (default: 20)
Standard Deviation Multiplier - Adjusts band width from the basis (default: 2.0)
Price Source - Select the price input for calculations (default: close)
Nebula Memory Length - Lookback period for tracking historical extremes (default: 50)
Color Settings - Customize bullish and bearish gradient colors
Conclusion
The Bollinger Aurora Velocity elevates traditional Bollinger Bands analysis by adding historical volatility context through the Nebula Cloud, precise squeeze detection for breakout anticipation, and intuitive momentum visualization through gradient candle coloring. This combination helps traders identify not just where price is relative to volatility bands, but how that volatility compares to recent history and when compression may lead to expansion.
Lakshmi - Low Volatility Range Breakout (LVRB)⚡️ Overview
The Low Volatility Range Breakout (LVRB) indicator is designed to identify consolidation phases characterized by suppressed volatility and generate actionable signals when price breaks out of these ranges. The underlying premise is rooted in the market principle that periods of low volatility often precede significant directional moves—volatility contraction leads to expansion.
Important Note on Optimization: The default parameter settings of this indicator have been specifically optimized for BTCUSDT on the 2-hour (2H) timeframe. While the indicator can be applied to other instruments and timeframes, users are encouraged to adjust the parameters accordingly to suit different trading conditions and asset characteristics.
This indicator automates the detection of "quiet" accumulation/distribution zones and provides clear visual cues and alerts when a breakout occurs.
⚡️ How to Use
1. Add the indicator to your chart. Default settings are optimized for BTCUSDT 2H.
2. Wait for a gray box to appear—this indicates a qualified low-volatility range is forming.
3. Monitor for breakout signals:
• LONG (green triangle below bar): Price broke above the range. Consider entering a long position.
• SHORT (red triangle above bar): Price broke below the range. Consider entering a short position.
4. Set alerts using "LVRB LONG" or "LVRB SHORT" to receive notifications on confirmed breakouts.
5. Adjust parameters as needed for different instruments or timeframes.
Tip: Combine with volume analysis or trend filters for higher-probability setups.
⚡️ How It Works
1. Low Volatility Bar Detection
A bar is classified as "low volatility" when it meets the following criteria:
• True Range (TR) is at or below the average TR (Simple Moving Average) multiplied by a user-defined threshold.
• (Optional) Candle Body is at or below the average body size multiplied by a separate threshold.
This dual-filter approach helps isolate bars that exhibit genuine compression in both range and directional commitment.
2. Range Box Formation
When consecutive low-volatility bars are detected, the indicator begins constructing a consolidation box:
• The box expands to encompass the high and low of qualifying bars.
• A minimum number of bars and a minimum fraction of low-volatility bars are required for the box to become "qualified" (active).
• A configurable tolerance allows for a limited number of consecutive non-low-vol bars within the sequence, accommodating minor noise without invalidating the range.
• If the box height exceeds a maximum threshold (defined as a multiple of the base ATR at sequence start), the range is invalidated.
3. Breakout Detection
Once a qualified range is established, the indicator monitors for breakouts:
• Wick Mode: Requires both a wick pierce beyond the range boundary AND a close outside the range.
• Close Mode: Requires only a close beyond the range boundary.
• (Optional) Breakout Body Filter: The breakout candle's body must exceed a multiple of the average body size at range formation.
• (Optional) Candle Direction Filter: Bullish breakouts require a green candle; bearish breakouts require a red candle.
Signals are displayed in real-time and confirmed upon bar close.
⚡️ Inputs & Parameters
• Volatility Window: Lookback period for calculating average TR and average body size.
• TR Multiplier: A bar's TR must be ≤ avgTR × this value to qualify as low-vol.
• Body Multiplier: A bar's body must be ≤ avgBody × this value (if body filter is enabled).
• Use Body Filter: Toggle the body size filter on/off.
• Min Bars in Box: Minimum number of bars required for a range to become qualified.
• Min Low-Vol Fraction: Minimum proportion of bars in the sequence that must be low-vol.
• Allowed Consecutive Non-Low-Vol Bars: Tolerance for consecutive bars that do not meet low-vol criteria.
• Max Box Height: Maximum allowed range height as a multiple of the base ATR.
• Breakout Mode: Choose between "Wick" (pierce + close) or "Close" (close only).
• Breakout Body Multiplier: Require breakout candle body ≥ avgBody × this value (1.0 = OFF).
• Require Candle Direction: Enforce green candle for LONG, red candle for SHORT.
⚡️ Visual Features
• Consolidation Boxes: Displayed in neutral (gray) color during formation. Upon a confirmed breakout, the box is colored green for bullish breakouts or red for bearish breakouts.
• Breakout Signals:
• LONG: Green upward triangle displayed below the price bar with "LONG" label.
• SHORT: Red downward triangle displayed above the price bar with "SHORT" label.
• Range Levels: Optional horizontal plots for the active range's high and low.
• Invalidated Boxes: Optionally retained in neutral (gray) color or deleted from the chart.
• Full Customization: Colors, transparency, and border width are all adjustable.
⚡️ Alerts
Two alert conditions are available:
• LVRB LONG: Triggered on a confirmed bullish breakout (bar close).
• LVRB SHORT: Triggered on a confirmed bearish breakout (bar close).
⚡️ Use Cases
• Breakout Trading: Enter positions when price escapes a well-defined low-volatility range.
• Volatility Expansion Plays: Anticipate increased volatility following periods of compression.
• Filtering Choppy Markets: Avoid trading during extended consolidation; wait for confirmed breakouts.
• Multi-Timeframe Analysis: Use on higher timeframes to identify major consolidation zones.
⚡️ Notes
• Best used in conjunction with volume analysis, trend context, or support/resistance levels for confirmation.
• Performance varies across instruments and timeframes; backtesting and parameter optimization are recommended.
⚡️ Credits
Developed by Lakshmi. Inspired by volatility contraction principles and range breakout methodologies.
⚡️ Disclaimer
This indicator is provided for educational and informational purposes only. It does not constitute financial advice, investment recommendations, or a guarantee of profits. Trading financial instruments involves substantial risk, and you may lose more than your initial investment. Past performance, whether indicated by backtesting or historical analysis, does not guarantee future results. The use of this indicator does not ensure or promise any profits or protection against losses. Users are solely responsible for their own trading decisions and should conduct their own research and/or consult with a qualified financial advisor before making any investment decisions. By using this indicator, you acknowledge and accept that you bear full responsibility for any trading outcomes.
Series #3: Commodity Momentum Analyzer Commodity Momentum Analyzer: Risk-First Logic
1. Thesis & Objective This script is the third release in a series dedicated to developing institutional-grade technical analysis tools. The primary objective of this indicator is to provide a visual framework for Momentum Identification in tokenized commodities (specifically optimized for PAXG/USD) while strictly adhering to a non-discretionary risk management model.
2. Logical Architecture
Momentum Module: Utilizes a dual-EMA crossover (9/21) to filter direction. This is a foundational trend-following approach used to demonstrate signal stability on assets backed by physical gold.
Volatility-Adjusted Levels: Unlike fixed-percentage tools, this analyzer calculates risk based on Average True Range (ATR). This ensures that stop-loss and profit-target projections are scaled to the current heartbeat of the market.
Fixed Reward-to-Risk (4:1): The script visually projects a target exactly four times the distance of the risk floor. This ensures a mathematical expectancy where a modest win rate maintains account growth.
3. Key Features
Pine Script® v6 Engine: Developed using the latest compiler standards for efficiency and reliability.
Dynamic Risk Table: Displays real-time dollar-risk values based on a standard $10,000 equity baseline.
Clean Visuals: Signal shapes (Triangles) and projected levels are designed to minimize chart clutter while providing maximum actionable data.
4. How to Use
Entries: Look for the triangle signals following an EMA cross.
Exits: Monitor the projected "Risk Floor" and "Reward Target" lines for trade management.
Asset Class: While functional on any asset, this series is optimized for the low-volatility, steady-trend characteristics of tokenized commodities.
Dot PlotDot plot is a simple way to look at all of the best indicators in the market at one time. The momentum of a trade is evaluated by people in several different ways, indicating they should buy in or get out of a stock. Some people look at MACD Histogram (the second row of dots on the screen), some look at the Slow Stochastic (the 3rd row on the dot plot) and some use RSI (the last dot plot). The system has an overall rating (the top and dot) needs the majority of the indicators in a positive position to create a green dot, there will be no dot if there is under 5% strength up or down, and there will be a red dot if turning in a bullish or down position.
Liquidation Bubbles [OmegaTools]🔴🟢 Liquidation Bubbles — Advanced Volume & Price Stress Detector
Liquidation Bubbles is a professional-grade analytical tool designed to identify forced positioning events, stop-runs, and liquidation clusters by combining price displacement and volume imbalance into a single, statistically normalized framework.
This indicator is not a repainting signal tool and not a simple volume spike detector. It is a contextual market stress mapper, built to highlight areas where one-sided positioning becomes unstable and the probability of forced order execution (liquidations, stops, margin calls) materially increases.
---
## 🔬 Core Concept
Market liquidations do not occur randomly.
They emerge when price deviates aggressively from its volume-weighted equilibrium while volume itself becomes abnormal.
Liquidation Bubbles detects exactly this condition by:
* Estimating a **dynamic equilibrium price** using an *inverted volume-weighted moving average*
* Measuring **directional price stress** relative to that equilibrium
* Measuring **volume stress** relative to its own adaptive baseline
* Normalizing both into **Z-score–like metrics**
* Highlighting only **statistically extreme, asymmetric events**
The result is a clear visual map of stress points where market participants are most vulnerable.
---
⚙️ Methodology (How It Works)
1️⃣ Advanced Inverted VWMA (Equilibrium Engine)
The script uses a custom Advanced VWMA, where:
* High volume bars receive less weight
* Low volume bars receive more weight
This produces a **robust equilibrium level**, resistant to manipulation and volume bursts.
This equilibrium is used for **both price and volume normalization**, creating a consistent statistical framework.
---
2️⃣ Price Stress (Directional)
Price stress is calculated as:
* The **maximum deviation** between high/low and equilibrium
* Directionally signed (upside vs downside)
* Normalized by its own historical volatility
This allows the script to distinguish:
* Aggressive upside exhaustion
* Aggressive downside capitulation
---
3️⃣ Volume Stress
Volume stress is measured as:
* Deviation from volume equilibrium
* Normalized by historical volume dispersion
This filters out:
* Normal high-volume sessions
* Illiquid noise
And isolates abnormal participation imbalance.
---
4️⃣ Liquidation Logic
A liquidation event is flagged when:
* Both price stress and volume stress exceed adaptive thresholds
* The imbalance is directional and statistically extreme
Optional Combined Score Mode allows aggregation of price & volume stress into a single composite metric for smoother signals.
---
🔵 Bubble System (Signal Hierarchy)
The indicator plots **two tiers of bubbles**:
🟢🔴 Small Bubbles
* Early warning stress points
* Localized stop-runs
* Micro-liquidations
* Often precede reactions or short-term reversals
🟢🔴 Big Bubbles
* Full liquidation clusters
* Forced unwinds
* High probability exhaustion zones
* Frequently align with:
* Intraday extremes
* Range boundaries
* Reversal pivots
* Volatility expansions
Bubble color:
* **Green** → Downside liquidation (sell-side exhaustion)
* **Red** → Upside liquidation (buy-side exhaustion)
Bubble placement is **ATR-adjusted**, ensuring visual clarity without overlapping price.
---
🔄 Cross-Market Volume Analysis
The script allows optional **external volume sourcing**, enabling:
* Futures volume applied to CFDs
* Index volume applied to ETFs
* Spot volume applied to derivatives
This is critical when:
* Your traded instrument has unreliable volume
* You want **institutional-grade confirmation**
---
🧠 How to Use Liquidation Bubbles
This indicator is **not meant to be traded alone**.
Best use cases:
* 🔹 Confluence with support & resistance
* 🔹 Contextual confirmation for reversals
* 🔹 Identifying fake breakouts
* 🔹 Liquidity sweep detection
* 🔹 Risk management (avoid entering into liquidation zones)
Ideal for:
* Futures
* Indices
* Crypto
* High-liquidity FX pairs
* Intraday & swing trading
---
🎯 Who This Tool Is For
Liquidation Bubbles is designed for:
* Advanced discretionary traders
* Order-flow & liquidity-based traders
* Macro & index traders
* Professionals seeking **context**, not signals
If you want **where the market is fragile**, not just where price moved — this tool was built for you.
---
📌 Key Characteristics
✔ Non-repainting
✔ Statistically normalized
✔ Adaptive to volatility
✔ Works on all timeframes
✔ Futures & crypto ready
✔ No lagging indicators
✔ No moving average crosses
---
Liquidation Bubbles does not predict the future.
It shows you where the market is most likely to break.
— OmegaTools
