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.
Волатильность
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.
VDUB Bands - MTF WMA+ATR Volatility Lanes (6 Alerts)VDUB Bands draws volatility-scaled “trend lanes” around a Weighted Moving Average (WMA) using ATR (or a WMA of True Range). It can display up to four tiers (L1–L4), with higher tiers sourced from higher timeframes to show local structure → higher-timeframe structure on a single chart.
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1. What it does (plain English)
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Think of each tier as a lane system around the trend:
• Inner rails = “normal volatility lane” around the WMA
• Outer rails = “extension / extreme zone” for that tier
• Higher tiers (L3/L4) show bigger structure
• Lower tiers (L1/L2) show active lane behavior
Typical interpretation:
• Price inside inner rails → normal variance around the trend lane
• Between inner and outer → stretched, but not extreme
• Outside outer rails → extended vs that tier’s volatility band
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2) Why it’s useful (and why it’s not a mashup)
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This is not a bundle of unrelated indicators. Everything serves one cohesive purpose:
• Visualize trend + volatility lanes across multiple time horizons
• Keep rails consistent and readable (levels, fills, outlines)
• Optional multi-timeframe aggregation for structure context
• A compact 6-alert set to catch key transitions without alert spam
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3) What you see on the chart
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For each level (L1–L4), you can show:
• Upper/Lower Inner rails
• Upper/Lower Outer rails
• Optional center fill (between outer rails) = operating range
• Optional MA line per tier (off by default to reduce clutter)
• Base WMA line (L1 MA) if enabled
Suggested workflow:
• Start with L1 + L2 only
• Add L3/L4 once you like the structure view
• Use Dynamic Opacity if the chart feels crowded
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4) How it works (transparent formula)
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For each tier:
• MA = WMA(source, baseLen × levelMultiplier)
• ATR_like = Wilder ATR (default)
OR WMA(TrueRange, atrLen × levelMultiplier)
Inner rails:
• upperInner = MA + ATR_like × innerMult
• lowerInner = MA - ATR_like × innerMult
Outer rails:
• upperOuter = MA + ATR_like × outerMult
• lowerOuter = MA - ATR_like × outerMult
Tier behavior:
• L1 uses the chart timeframe
• L2–L4 can use user-selected HTFs (defaults: 4H / D / W)
or optional auto-selection
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5) Multi-timeframe behavior + interpolation
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• L2–L4 use request.security() with lookahead OFF (no future data).
• HTF bands naturally “step” when the HTF candle confirms.
• Interpolate HTF Bands (optional): visually blends from the prior confirmed HTF value to the current confirmed HTF value to reduce stepping. This is display smoothing, not prediction.
Repaint note:
• If Live Interp (Repaints) is enabled, the HTF lines can update intrabar and may repaint. Keep it OFF for strict non-repainting behavior.
────────────────────────────────────────
6) Auto-select L2/L3/L4 (optional)
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Two modes:
A) Ladder (deterministic)
• Picks “bigger” timeframes relative to the chart (simple and fast).
B) Score (data-driven)
• Tests candidate timeframes and scores them using:
• Coverage: % of closes inside the OUTER band over Score Lookback
• Width: average outer-band width as a fraction of MA
• Targets: Target Coverage + Target Width
• Weights: Coverage Weight + Width Weight
Performance notes:
• Score mode is heavier (many candidates).
• “Lock auto-select after first pick” is recommended to reduce load and avoid platform limits.
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7) Alerts (6 total, aggregated across L1–L4)
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Alerts trigger if ANY tier meets the condition:
• Cross ABOVE an OUTER band
• Cross BELOW an OUTER band
• Cross ABOVE an INNER band
• Cross BELOW an INNER band
• Price is OUTSIDE ABOVE an OUTER band
• Price is OUTSIDE BELOW an OUTER band
These are intentionally aggregated to keep the alert count small while catching meaningful transitions.
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8) Limitations & transparency
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• Indicator only (not a strategy). No performance claims.
• MTF values update when the higher timeframe candle confirms.
• Interpolation is visual smoothing; it does not forecast.
• Non-standard chart types (Heikin Ashi/Renko/etc) may behave differently from standard candles.
• If you enable repainting options, signals/levels may change intrabar.
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9) Credits/reuse disclosure
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• Conceptual inspiration: VDUB and the community “VDUB_BINARY_PRO_3_V2” idea of WMA ± TR/ATR × multipliers.
• This version is a reimplementation + extension, adding:
o Multi-tier architecture (L1–L4)
o Higher-timeframe sourcing + optional interpolation
o Optional scoring-based timeframe selection
o Dynamic opacity + streamlined plotting
o Aggregated 6-alert set
No code was copied directly from the older script; this is a rewritten implementation with additional features and different structure.
www.tradingview.com
1H ETH Volume Breakout [ADX Filtered]Title: 1H ETH Volume Breakout w/ ADX Filter
Description:
🚀 Strategy Overview
This strategy is a high-precision Volatility Breakout system designed specifically for Ethereum (ETH) on the 1H timeframe. It focuses on catching explosive moves while aggressively filtering out market noise and "chop" to protect capital.
Unlike standard breakout strategies that get wrecked in sideways markets, this script uses a multi-layer confirmation system (Volume + Trend + Momentum + ADX) to ensure high-probability entries.
🧠 The Logic (How it works)
Keltner Channel Breakout: We use Keltner Channels (Length 22, Multiplier 2.0) instead of Bollinger Bands because they adapt better to ETH's unique volatility, reducing fake-outs.
Volume Confirmation: A trade is only taken if the current volume spikes above the moving average. "No Volume = No Trade."
Trend Filter (220 EMA): We only trade Long when price is above the 220 EMA, and Short when below. We trade with the dominant trend, never against it.
The "Chop Killer" (ADX Filter): An added ADX filter ensures the trend has real strength before entering. If the market is flat (ADX < 20), the strategy sits on the sideline.
🛡️ Risk Management (The "Fee Crusher")
Dynamic Stop Loss: Uses ATR (4.0) to give trades room to breathe without getting wicked out.
Trailing Stop: Activates after a 3% gain to lock in profits during big pumps.
Money Management: Includes a built-in Compounding feature (Optional).
⚙️ Recommended Settings
Coin: ETH/USD or ETH/USDT
Timeframe: 1 Hour (1H)
Leverage: 2x (Recommended)
Exchange Fees: Tuned for 0.1% fees.
⚠️ Disclaimer
Past performance is not indicative of future results. Please backtest with your own exchange settings before using real capital. This is an open-source tool for educational purposes.
ULTIMATE SMC FUSION HIGHER TIME FRAMES🔥 ULTIMATE SMC FUSION ADAPTED FOR HIGH TIME FRAMES
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The high-performance, refined edition of the v4.1 Fusion suite. This Core version brings the signature "Balanced Entry" logic to your charts with enhanced HTF optimization and a zero-latency interface.
🚀 KEY FEATURES:
• BALANCED SIGNAL ENGINE: A proven mix of structure breaks and momentum-based institutional entries.
• HTF TURN DETECTION: Enhanced logic for Higher Timeframes to find major swing reversal opportunities.
• ON-CHART PERFORMANCE PANEL: Live tracking for win rates and growth stats to keep you in the flow.
• DYNAMIC ATR TARGETS: Take Profit and Stop Loss levels that adapt automatically to market volatility.
• OPTIMIZED SMC OVERLAYS: Clean, professional structure lines and order block visualizers.
• PURE LOCAL PROCESSING: No external API overhead—maximum responsiveness for fast decision making.
BEST FOR: Forex Scalp/Swing, Professional Charting, and Multi-Asset Analysis.
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Feel free to adjust the settings to your own needs.
Make your own decisions when you trade, do not put all confidence into a script, it may fail also.
ATR Table (Top Right) - Multi Rangejust your friendly atr table to multiple ranges and for the sense of what is brewing
COMBO: LuxAlgo SFP + EXTREMOS + VWAP 3rd Band + LG (15m)This is the best indicator 1h chart
High and low points daily
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.
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.
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.
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.
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.
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.
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## 🔬 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.
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⚙️ 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.
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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
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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.
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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.
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🔵 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.
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🔄 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**
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🧠 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
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🎯 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.
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📌 Key Characteristics
✔ Non-repainting
✔ Statistically normalized
✔ Adaptive to volatility
✔ Works on all timeframes
✔ Futures & crypto ready
✔ No lagging indicators
✔ No moving average crosses
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Liquidation Bubbles does not predict the future.
It shows you where the market is most likely to break.
— OmegaTools
Zenith MACD Evolution [JOAT]
Zenith MACD Evolution - Volatility-Normalized Momentum Oscillator
Introduction and Purpose
Zenith MACD Evolution is an open-source oscillator indicator that takes the classic MACD and normalizes it by ATR (Average True Range) to create consistent overbought/oversold levels across different market conditions. The core problem this indicator solves is that traditional MACD values are incomparable across different volatility regimes. A MACD reading of 50 might be extreme in a quiet market but normal in a volatile one.
This indicator addresses that by dividing MACD by ATR and scaling to a consistent range, allowing traders to use fixed overbought/oversold levels that work across all market conditions.
Why ATR Normalization Works
Traditional MACD problems:
- Values vary wildly based on price and volatility
- No consistent overbought/oversold levels
- Hard to compare across different instruments
- Extreme readings in one period may be normal in another
ATR-normalized MACD (Zenith) solves these:
- Values scaled to consistent range
- Fixed overbought/oversold levels work across all conditions
- Comparable across different instruments
- Extreme readings are truly extreme regardless of volatility
How the Normalization Works
// Classic MACD
= ta.macd(close, fastLength, slowLength, signalLength)
// ATR for normalization
float atrValue = ta.atr(atrNormLength)
// Volatility-Normalized MACD
float zenithMACD = atrValue != 0 ? (histLine / atrValue) * 100 : 0
float zenithSignal = ta.ema(zenithMACD, signalLength)
The result is a MACD that typically ranges from -200 to +200, with consistent levels:
- Above +150 = Overbought
- Below -150 = Oversold
- Above +200 = Extreme overbought
- Below -200 = Extreme oversold
Signal Types
Zero Cross Up/Down - Zenith crosses zero line (trend change)
Overbought/Oversold Entry - Zenith enters extreme zones
Overbought/Oversold Exit - Zenith leaves extreme zones (potential reversal)
Momentum Shift - Histogram direction changes (early warning)
Divergence - Price makes new high/low but Zenith does not
Histogram Coloring
The histogram uses four colors to show momentum state:
- Strong Bull (Teal) - Positive and rising
- Weak Bull (Light Teal) - Positive but falling
- Strong Bear (Red) - Negative and falling
- Weak Bear (Light Red) - Negative but rising
This helps identify momentum shifts before crossovers occur.
Dashboard Information
Zenith - Current normalized MACD value with signal line
Zone - Current zone (EXTREME OB/OVERBOUGHT/NORMAL/OVERSOLD/EXTREME OS)
Momentum - Direction (RISING/FALLING/FLAT)
Histogram - Current histogram value
ATR Norm - Current ATR value used for normalization
Classic - Traditional MACD value for reference
How to Use This Indicator
For Mean-Reversion:
1. Wait for Zenith to reach extreme zones (+200/-200)
2. Look for momentum shift (histogram color change)
3. Enter counter-trend when exiting extreme zone
For Trend Following:
1. Enter long on zero cross up
2. Enter short on zero cross down
3. Use histogram color to gauge momentum strength
For Divergence Trading:
1. Watch for DIV labels (price vs Zenith divergence)
2. Bullish divergence at support = potential long
3. Bearish divergence at resistance = potential short
Input Parameters
Fast/Slow/Signal Length (12/26/9) - Standard MACD parameters
ATR Normalization Period (26) - Period for ATR calculation
Overbought/Oversold Zone (150/-150) - Zone thresholds
Extreme Level (200) - Extreme threshold
Show Classic MACD Lines (false) - Toggle traditional lines
Show Divergence Detection (true) - Toggle divergence signals
Divergence Lookback (14) - Bars to scan for divergence
Timeframe Recommendations
All timeframes work due to normalization
Higher timeframes provide smoother signals
Normalization makes cross-timeframe comparison meaningful
Limitations
ATR normalization adds slight lag
Divergence detection is simplified
Extreme zones can persist in strong trends
Works best when combined with price action analysis
Open-Source and Disclaimer
This script is published as open-source under the Mozilla Public License 2.0 for educational purposes.
This indicator does not constitute financial advice. Momentum analysis does not guarantee profitable trades. Always use proper risk management.
- Made with passion by officialjackofalltrades
Strength Relative to XXX [Hysteresis Smoothed]Strength Relative to XXX
█ OVERVIEW
This versatile indicator measures the relative strength of the current charted asset against any user-selected benchmark symbol (e.g., BTC, ETH, SP:SPX, TVC:GOLD, or any other asset). Green fill = Current asset outperforming the benchmark (bullish relative strength).
Red fill = Current asset underperforming the benchmark (bearish relative weakness). Perfect for rotation strategies across crypto, stocks, forex, and commodities — quickly identify assets gaining momentum edge over a chosen benchmark.
█ HOW IT WORKS
• Relative Ratio : Calculates current close / benchmark close for normalized comparison.
• Smoothing : Applies a Simple Moving Average (SMA) to the ratio (adjustable length).
• Oscillator : Plots deviation from the SMA, centered around zero.
• Hysteresis Enhancement : Adds a small relative threshold (~0.03% default) to prevent rapid color flips from minor noise. Color persists until a convincing cross — stable blocks without lag.
█ FEATURES & INPUTS
• Compare to : Symbol input for any benchmark (match exchange for accuracy).
• MA Length : Smoothing period (default 10).
• Relative Hysteresis Threshold : Noise filter strength (default 0.0003; tweak for responsiveness vs. stability).
█ USAGE TIPS
• Apply to ALT/BTC pairs for crypto rotations, stocks vs. SP:SPX for sector strength, or any custom comparison.
• Works on all timeframes — ideal for short-term scans on 4H/daily.
• Green zones = potential outperformance; red = caution.
• Combine with volume or momentum for confluence.
This refined relative strength oscillator delivers clean, reliable visuals in volatile markets.
Volume-Weighted RSI [VWRSI 2D Pro]A modular, volume-weighted RSI indicator built for clarity and control.
✅ Profile-based auto modes (Scalping → Macro)
✅ Toggleable Buy/Sell signals with strict mode
✅ RSI MA overlays for smoother entries
Buy Signal
RSI crosses above RSI MA
RSI > 50 (or > 55 in strict mode)
Sell Signal
RSI crosses below RSI MA
RSI < 50 (or < 45 in strict mode)
Strict mode filters out weak signals for higher conviction entries.
Volatility-Adaptive RSI Thresholds:
Traditional RSI uses static levels (70/30).
VWRSI Pro replaces these with dynamic bands:
🔹dynHigh = mean + mult × deviation
🔹 dynLow = mean − mult × deviation
Technical write-up can be found here: github.com
