AlgoFreaks: Sniper Long (Premium)The AlgoFreaks™ Sniper Long is a high-precision mean reversion system designed to catch "dip buying" opportunities within established bullish trends.
Instead of chasing green candles, this system patiently waits for extreme oversold conditions to execute "Sniper" entries with favorable risk-to-reward ratios.
### 🟢 How it Works
The strategy relies on a multi-timeframe confirmation logic:
1. **Trend Filter:** Ensures the asset is in a dominant uptrend using both Local EMA (200) and Higher Timeframe (4H) EMA filters.
2. **Sniper Entry:** Triggers only when the RSI collapses to extreme lows (e.g., RSI < 5), indicating a temporary panic selling moment within a bull run.
3. **Risk Management:** Uses a built-in Hard Stop Loss for protection and an advanced Trailing Stop system to let winners run while locking in profits.
### ⚡ Key Features
* **Visual Dashboard:** Real-time branding and signal status on your chart.
* **Automation Ready:** Fully optimized JSON alerts for 3Commas, Bybit, and PineConnector.
* **No Repainting:** All signals are confirmed on bar close.
### 🛡️ Risk Warning
Trading cryptocurrencies involves significant risk. This indicator is a tool for finding setups, not financial advice. Always use proper risk management.
### 🔐 How to Get Access
This is an Invite-Only script. To get access to the AlgoFreaks suite: algofreeks.com
Volatilidade
Volatility Squeeze Pro [JOAT]
Volatility Squeeze Pro — Advanced Volatility Compression Analysis System
This indicator addresses a specific analytical challenge in volatility analysis: how to identify periods when different volatility measurements show compression relationships that may indicate potential energy buildup in the market. It combines two distinct volatility calculation methods—standard deviation-based bands and ATR-based channels—with a momentum oscillator to provide comprehensive volatility state analysis.
Why This Combination Provides Unique Analytical Value
Traditional volatility indicators typically focus on single measurements, but markets exhibit different types of volatility that require different analytical approaches:
1. **Closing Price Volatility** (Standard Deviation): Measures how much closing prices deviate from their average
2. **Trading Range Volatility** (ATR): Measures the actual high-to-low trading ranges
3. **Directional Momentum**: Measures where price sits within its recent range
The problem with using these individually:
- Standard deviation alone doesn't account for intraday volatility
- ATR alone doesn't consider closing price clustering
- Momentum alone doesn't provide volatility context
- No single measurement captures the complete volatility picture
This indicator's originality lies in creating a comprehensive volatility analysis system that:
**Identifies Volatility Compression**: When closing price volatility contracts inside trading range volatility, it suggests potential energy buildup
**Provides Momentum Context**: Shows directional bias during compression periods
**Offers Multi-Dimensional Analysis**: Combines three different analytical approaches into one coherent system
**Delivers Real-Time Assessment**: Continuously monitors the relationship between different volatility types
Technical Innovation and Originality
While individual components (Bollinger Bands, Keltner Channels, Linear Regression) are standard, the innovation lies in:
1. **Volatility Relationship Detection**: The mathematical comparison between standard deviation bands and ATR channels creates a unique compression identification system
2. **Integrated Momentum Analysis**: Linear regression-based momentum calculation provides directional context specifically during volatility compression periods
3. **Multi-State Visualization**: The indicator provides clear visual encoding of different volatility states (compressed vs. normal) with momentum direction
4. **Adaptive Threshold System**: The squeeze detection automatically adapts to different instruments and timeframes without manual calibration
How the Components Work Together Analytically
The three components create a comprehensive volatility analysis framework:
**Standard Deviation Component**: Measures closing price dispersion around the mean
float bbBasis = ta.sma(close, bbLength)
float bbDev = bbMult * ta.stdev(close, bbLength)
float bbUpper = bbBasis + bbDev
float bbLower = bbBasis - bbDev
**ATR Channel Component**: Measures actual trading range volatility
float kcBasis = ta.ema(close, kcLength)
float kcRange = ta.atr(atrLength)
float kcUpper = kcBasis + kcRange * kcMult
float kcLower = kcBasis - kcRange * kcMult
**Squeeze Detection Logic**: Identifies when closing price volatility compresses within trading range volatility
bool squeezeOn = bbLower > kcLower and bbUpper < kcUpper
// This condition indicates closing prices are clustering more tightly
// than the typical trading range would suggest
**Momentum Context Component**: Provides directional bias during compression
float highestHigh = ta.highest(high, momLength)
float lowestLow = ta.lowest(low, momLength)
float momentum = ta.linreg(close - math.avg(highestHigh, lowestLow), momLength, 0)
float momSmooth = ta.sma(momentum, smoothLength)
The analytical relationship creates a system where:
- Squeeze detection identifies WHEN volatility compression occurs
- Momentum analysis shows WHERE price is positioned during compression
- Combined analysis provides both timing and directional context
How the Volatility Comparison Works
The indicator compares two volatility measurements:
Standard Deviation Bands
These measure how much closing prices deviate from their average. When prices cluster tightly around the average, the bands contract.
// Standard deviation bands calculation
float bbBasis = ta.sma(close, bbLength)
float bbDev = bbMult * ta.stdev(close, bbLength)
float bbUpper = bbBasis + bbDev
float bbLower = bbBasis - bbDev
ATR-Based Channels
These measure volatility using Average True Range—the typical distance between high and low prices. They respond to the actual trading range rather than closing price dispersion.
// ATR-based channels calculation
float kcBasis = ta.ema(close, kcLength)
float kcRange = ta.atr(atrLength)
float kcUpper = kcBasis + kcRange * kcMult
float kcLower = kcBasis - kcRange * kcMult
The Squeeze Condition
A "squeeze" is detected when the standard deviation bands are completely contained within the ATR channels:
// Squeeze detection
bool squeezeOn = bbLower > kcLower and bbUpper < kcUpper
This condition indicates that closing price volatility has compressed relative to the overall trading range.
The Momentum Component
The momentum oscillator measures where price sits relative to its recent high-low range, using linear regression for smoothing:
// Momentum calculation
float highestHigh = ta.highest(high, momLength)
float lowestLow = ta.lowest(low, momLength)
float momentum = ta.linreg(close - math.avg(highestHigh, lowestLow), momLength, 0)
float momSmooth = ta.sma(momentum, smoothLength)
Positive values indicate price is above the midpoint of its recent range; negative values indicate below.
Why Display Both Together
The squeeze detection shows WHEN volatility is compressed. The momentum reading shows the current directional bias of price within that compression. Together, they provide two pieces of information:
1. Is volatility currently compressed? (squeeze status)
2. Where is price leaning within the current range? (momentum)
These are observations about current conditions, not predictions about future movement.
Visual Elements
Momentum Histogram — Bars showing momentum value
- Green shades: Positive momentum (price above range midpoint)
- Red shades: Negative momentum (price below range midpoint)
- Brighter colors: Momentum increasing
- Faded colors: Momentum decreasing
Squeeze Dots — Circles on the zero line
- Red: Squeeze condition active
- Green: No squeeze condition
Release Markers — Triangle markers when squeeze condition ends
Dashboard — Current readings and status
Color Scheme
Squeeze Active — #FF5252 (red)
No Squeeze — #4CAF50 (green)
Momentum Positive — #00E676 / #81C784 (green shades)
Momentum Negative — #FF5252 / #E57373 (red shades)
Inputs
Standard Deviation Bands:
Length (default: 20)
Multiplier (default: 2.0)
ATR Channels:
Length (default: 20)
Multiplier (default: 1.5)
ATR Period (default: 10)
Momentum:
Length (default: 12)
Smoothing (default: 3)
How to Read the Display
Red dots indicate the squeeze condition is present
Green dots indicate normal volatility relationship
Histogram direction shows current momentum bias
Histogram color brightness shows whether momentum is increasing or decreasing
Alerts
Squeeze condition started
Squeeze condition ended
Squeeze ended with positive momentum
Squeeze ended with negative momentum
Extended squeeze (8+ bars)
Important Limitations and Realistic Expectations
Volatility compression detection is a mathematical relationship between calculations—it does not predict future price movements
Many compression periods do not result in significant price expansion or directional moves
Momentum direction during compression does not reliably indicate future breakout direction
This indicator analyzes current and historical volatility conditions only—it cannot predict future volatility
False signals are common—not every squeeze leads to tradeable price movement
Different parameter settings will produce different compression detection sensitivity
Market conditions, news events, and fundamental factors often override technical volatility patterns
No volatility indicator can predict the timing, direction, or magnitude of future price movements
This tool should be used as one component of comprehensive market analysis
Appropriate Use Cases
This indicator is designed for:
- Volatility state analysis and monitoring
- Educational study of volatility relationships
- Multi-dimensional volatility assessment
- Supplementary analysis alongside other technical tools
- Understanding market compression/expansion cycles
This indicator is NOT designed for:
- Standalone trading signal generation
- Guaranteed breakout prediction
- Automated trading system triggers
- Market timing precision
- Replacement of fundamental analysis
Understanding Volatility Analysis Limitations
Volatility analysis, while useful for understanding market conditions, has inherent limitations:
- Past volatility patterns do not guarantee future patterns
- Compression periods can extend much longer than expected
- Expansion periods may be brief and insufficient for trading
- External factors (news, fundamentals) often override technical patterns
- Different markets and timeframes exhibit different volatility characteristics
— Made with passion by officialjackofalltrades
BAVC (Clone) Rolling Curves, Peak MarkersBAVC (Clone) — Rolling Curves + Peak Markers
BAVC (Clone) is a volume-based momentum and participation indicator designed to visualize aggressive buying vs aggressive selling pressure using rolling volume curves and structural peak detection.
This script is a functional clone of a Bid/Ask Volume Curve concept, implemented using approximated volume splitting (uptick/downtick or close vs open) so it works on standard TradingView data without requiring true bid/ask feeds.
What the Indicator Shows
1. Rolling Buy & Sell Volume Curves
Volume is split into Buy (aggressive buyers) and Sell (aggressive sellers) using a selectable approximation method.
Each side is accumulated over a configurable lookback window.
Optional EMA smoothing is applied to reduce noise and highlight participation trends.
Interpretation:
Rising Buy Curve → increasing buyer dominance
Rising Sell Curve → increasing seller dominance
Expanding separation → stronger directional conviction
Convergence / flattening → balance, absorption, or transition
2. Adaptive Color Intensity (Optional)
Curve opacity can remain fixed or
Automatically adapt based on relative dominance strength
Stronger imbalances visually stand out without adding extra indicators
3. Structural Peak & Trough Detection
The script identifies significant local extremes in both curves:
Buy-side peaks & troughs
Sell-side peaks & troughs
Each peak is filtered using:
Swing width (bars left/right)
Relative strength vs recent maximum
Minimum depth for troughs
Markers can be displayed as:
Circles directly on the curves, or
Minimal labels (▲ / ▼)
Interpretation:
Buy-side highs → possible exhaustion or distribution
Buy-side lows → loss of initiative / absorption
Sell-side highs → aggressive selling climax
Sell-side lows → selling pressure weakening
4. Alerts
Optional alerts fire when:
A significant Buy-side peak forms
A significant Buy-side trough forms
A significant Sell-side peak forms
A significant Sell-side trough forms
These are intended as contextual signals, not standalone trade triggers.
5. Status Line Helper
An optional real-time status label displays:
Lookback settings
Current rolling Buy and Sell volume sums
This is useful for quick confirmation without opening the settings panel.
Important Notes
This indicator uses volume behavior, not price.
It is best used as a confirmation tool alongside:
Structure
Time-based context
VWAP / trend filters
It does not generate buy or sell signals by itself.
Best Use Cases
Spotting institutional participation
Confirming trend strength or exhaustion
Identifying absorption before reversals
Filtering low-quality entries during choppy periods
Complete G4 | CG4 (DTD)This script was built with the intention of improving day trading capabilities for the Futures market, namely for NQ.
The novelty of the script are the Ghetto Fibonacci Opening Range Retracement (G4) levels themselves and HOW they are calculated, providing Fibonacci pivot projections after the first 1-minute candle of the day. It is believed and understood that some major algorithms establish their positions within the first 30 seconds, defining a traded range for the day. With the help of some familiar Fibonacci levels and some custom ones, we can identify strong potential areas of support and resistance throughout the session. This process is repeated at New York and Globex open to obtain the projected full daily candle range for a futures instrument.
To support trade location context, signal alerts are provided for candles that interact with the lines given certain criteria. Some of the criteria deals with previous data such as high, low, open, and close, relative to the last N candles. An ATR gate is included and adjustable to filter for candle significance as well. The intention is to turn the indicator into a strategy that is used for algorithmic trading.
To make this indicator more of a one-stop-shop, I've also added some other public scripts as optionable toggles, but extremely helpful to build context for trade bias. Both SHLFE ( ) and Order Block ( ) indicators were added, with the Order Block indicator getting a buff that allows users to pick a second timeframe to display recent order blocks.
I do recommend starting with just the G4 lines in the beginning to learn how to read price action around the lines, then adding in the context from the other two indicators:
There will be many updates to come that improves functionality and reliability of the trade signals with improved logic.
Access will be temporary until the end of Q1 2026.
'Then Jesus said, “Come to me, all of you who are weary and carry heavy burdens, and I will give you rest. Take my yoke upon you. Let me teach you, because I am humble and gentle at heart, and you will find rest for your souls. For my yoke is easy to bear, and the burden I give you is light.”'
Matthew 11:28-30
Market Acceptance Envelope [Interakktive]The Market Acceptance Envelope (MAE) is a diagnostic tool that shows where price statistically belongs — not where it might go. Unlike traditional bands that expand with volatility, MAE expands with acceptance: regions where price rotates comfortably, efficiency drops, and the market agrees on fair value.
This is the anti-Bollinger thesis: bands should represent where price IS accepted, not where it MIGHT reach based on standard deviation.
█ USAGE
The filled corridor represents the current acceptance zone — where price has demonstrated rotational behavior with low directional efficiency. When price is inside the corridor, it's "home." When outside, it's exploring territory the market hasn't yet accepted.
For discretionary traders, MAE provides instant context: "Is price where it belongs, or is it extended?"
For systematic traders, the exported values (confidence, asymmetry, position) can inform position sizing and filter logic.
█ ACCEPTANCE CENTROID
Unlike traditional bands centered on a moving average, MAE uses an Acceptance Centroid — a time-weighted price level where acceptance behavior concentrates. The centroid is calculated by weighting price by:
• Inverse efficiency (low efficiency = high acceptance)
• Volatility stability (stable vol = higher weight)
• Dwell factor (time spent near level)
This means the centroid drifts toward where price actually rotates, not simply where it averages.
█ ASYMMETRIC BOUNDARIES
MAE calculates upper and lower boundaries independently. Markets rarely treat up and down equally — during uptrends, the upper boundary may be wider (more accepted upside exploration), while the lower boundary stays tight (quick rejection of dips).
This asymmetry is visible on the chart and exported as a metric (-1 to +1).
█ CONFIDENCE-BASED VISIBILITY
The corridor's opacity reflects acceptance confidence:
• High confidence → clearly visible corridor (price is in accepted rotation)
• Low confidence → faded corridor (trending/directional market, acceptance not established)
When the corridor fades, it's telling you: "Acceptance hasn't been earned here yet."
█ WHAT THIS INDICATOR IS
• A diagnostic acceptance envelope showing where price statistically belongs
• Asymmetric by design — upper and lower calculated independently
• Confidence-weighted visibility — fades when acceptance is not earned
• Non-repainting — uses closed-bar data only
█ WHAT THIS INDICATOR IS NOT
• NOT Bollinger Bands (no standard deviation around a mean)
• NOT Keltner Channels (no ATR-scaled envelope)
• NOT a signal generator — no touches = signals philosophy
• NO arrows, NO entries/exits, NO buy/sell recommendations
█ HOW IT WORKS
MAE uses an acceptance-weighted calculation approach:
1. ACCEPTANCE WEIGHT
Each bar receives a weight based on:
• Efficiency: (1 - efficiency) — low efficiency = rotational = high acceptance
• Volatility Stability: stable vol environment = higher weight
• Dwell Factor: price staying near central tendency = higher weight
2. ACCEPTANCE CENTROID
Weighted average of price using acceptance weights:
centroid = Σ(price × weight) / Σ(weight)
Smoothed adaptively — faster during drift, slower when stable.
3. ASYMMETRIC BOUNDARIES
Upper and lower distances calculated separately:
• rngUp = acceptance-weighted average of (price - centroid) when price > centroid
• rngDn = acceptance-weighted average of (centroid - price) when price < centroid
4. CONFIDENCE SCORE
Composite of average acceptance weight, volatility stability, and centroid stability.
Maps to corridor opacity: high confidence = visible, low confidence = faded.
█ SETTINGS
Market Acceptance Envelope — Core
• Acceptance Lookback (20): Bars to evaluate for acceptance conditions. Higher = smoother, slower response.
• Preset (Swing): Scalper = tight/fast, Swing = balanced, Position = wide/stable.
• Envelope Sensitivity (1.0): Width multiplier. Higher = wider corridor.
Market Acceptance Envelope — Visuals
• Show Corridor (true): Display the acceptance corridor.
• Show Centroid (false): Display the acceptance centroid line.
Market Acceptance Envelope — Data Window
• Show Data Window Values (false): Export MAE metrics for external use.
█ EXPORTED VALUES
When Data Window is enabled:
• mae_upper: Upper boundary value
• mae_lower: Lower boundary value
• mae_centroid: Acceptance centroid value
• mae_width: Corridor width (upper - lower)
• mae_asymmetry: Asymmetry ratio (-1 to +1, negative = lower wider)
• mae_confidence: Acceptance confidence (0-100)
• mae_position: Price position (-1 = below, 0 = inside, +1 = above)
█ SUITABLE MARKETS
Works on all markets: Stocks, Futures, Forex, Crypto, Indices.
Works on all timeframes. Higher timeframes show more stable acceptance zones.
█ DISCLAIMER
This indicator is for educational and informational purposes only. It does not constitute financial advice. Past performance does not guarantee future results. Always conduct your own analysis and use proper risk management. This is a diagnostic tool — it provides context, not signals.
Dual-Timeframe ABR DashboardDual-Timeframe ABR Dashboard 是一款专为日内交易者设计的波动率参考工具，用于同时评估当前周期与日线级别的平均K线波幅（ABR）。
该指标基于 Average Bar Range（高低差的简单平均），帮助交易者快速判断：
单根K线的“正常”波动范围
当前价格相对于 ABR 的百分比位置
当日是否已接近日线级别的常规波动极限
指标不会在图表上绘制干扰性线条，而是通过状态栏与固定表格实时展示最新 ABR 数值，适合用于：
目标利润（TP）与止盈管理
趋势是否具备延续空间的判断
避免在“已走完波幅”的位置追价入场
这是一个为实盘决策服务，而非视觉美观的专业级日内交易辅助指标。
======================================================================
Dual-Timeframe ABR Dashboard is a volatility reference tool designed specifically for day traders, providing a clear view of Average Bar Range (ABR) on both the current timeframe and the daily timeframe.
By measuring the simple average of each bar’s high–low range, this indicator helps traders quickly assess:
What constitutes a “normal” bar movement on the active timeframe
Current price movement expressed as a percentage of ABR
Whether the session has already consumed most of its typical daily range
Instead of plotting lines on the chart, the indicator presents real-time ABR values via the status line and a fixed dashboard table, keeping the chart clean and execution-focused.
This tool is particularly useful for:
Profit target and trade management
Evaluating remaining trend potential during the session
Avoiding late entries after the daily range is largely exhausted
Built for practical intraday decision-making, not visual clutter.
Market State Intelligence [Interakktive]Market State Intelligence (MSI) is a diagnostic market-context indicator that reveals how the market is behaving — not where price "should" go.
MSI does not generate buy/sell signals. Instead, it classifies market conditions into clear behavioural regimes by continuously measuring:
- DRIVE (directional effort)
- OPPOSITION (absorption / resistance)
- STABILITY (structural persistence)
MSI is designed to answer three practical questions:
- What state is the market in right now?
- Is energy building, releasing, or decaying?
- Is participation aligned with price, or opposing it?
█ WHAT MSI DOES
MSI operates as a real-time regime classification engine that processes each closed bar through three independent measurement systems:
DRIVE — Directional Effort (0–100)
- Displacement efficiency (net progress vs total path)
- Range expansion quality (actual range vs expected ATR range)
- Body dominance (body vs candle range)
OPPOSITION — Absorption / Resistance (0–100)
- Wick pressure (rejection relative to attempt)
- Effort–result gap (high effort, low progress)
- Reversal density (counter-moves frequency)
STABILITY — Persistence (0–100)
- Condition persistence (how long conditions hold)
- Variance score (flip frequency)
- Follow-through consistency (reaction continuity)
These three forces feed a deterministic classifier with hysteresis (anti-flicker) to identify five regimes:
COMPRESSION — low drive, low opposition, higher stability (pressure building, direction unclear)
EXPANSION — high drive, low opposition (directional energy release)
TREND — medium-high drive, higher stability, low-medium opposition (healthy continuation)
DISTRIBUTION — medium drive, high opposition (effort absorbed; progress blocked)
TRANSITION — rapidly rising opposition, low stability (regime breakdown / uncertainty)
█ WHAT MSI DOES NOT DO
- No buy/sell signals, entries/exits, or performance claims
- No prediction of future direction
- No repainting: calculations use closed-bar data only
MSI is a market state layer intended to support your execution framework.
█ VISUAL SYSTEM
MSI uses a layered visual grammar designed to remain readable on live charts:
Regime Ribbon
A thin horizontal band showing the current regime via colour. Ribbon opacity reflects regime confidence (stronger confidence = more visible).
Pressure Envelope (core visual)
A soft corridor around price that expands with Drive and becomes more visible as Opposition increases. This visualises "pressure thickness" around current action (not a volatility band for entries).
Structural Memory
Faint background stains appear where regimes previously failed (e.g., expansion collapsing into absorption). These are behavioural context zones showing where market intention was rejected — not support/resistance.
Regime Change Markers (optional)
Subtle labels appear when regimes transition after confirmation. Useful for replay and education.
Effort Halo (optional)
Candle highlighting when Opposition materially exceeds Drive, indicating absorption/inefficiency.
█ HUD PANEL
The HUD displays:
- Current regime name + colour indicator
- A context gate showing whether conditions are aligned with long-bias or short-bias context (not an entry/exit system)
█ REGIME LEGEND
When enabled, displays:
- A one-line definition of the current regime
- Live Drive / Opposition / Stability values for interpretation
█ TIME-TO-DECISION METER
A visual pressure gauge that tends to fill during Compression (energy building) and drain during Expansion (energy releasing). It is a state-tracking meter, not a timing tool.
█ SETTINGS
MSI — Settings
- Preset Mode: Scalper / Swing / Position
- Analysis Mode (Minimal): ON = subtle visuals, OFF = full intensity
- Regime Ribbon, Structural Memory, HUD Panel, Time-to-Decision Meter, Effort Halo
MSI — Visual Options
- Show Regime Changes: Labels when regime transitions occur
- Show Regime Legend: Definition and live values display
- Panel Position: Move the entire panel anywhere on chart
MSI — Advanced (Tuning)
- Sensitivity (0.5–2.0)
- Smoothing (0.5–2.0)
- Memory Decay (0.5–2.0)
- Visual Intensity (Low / Medium / High)
█ PRESETS EXPLAINED
Scalper
Higher sensitivity + lower smoothing + faster memory decay. Best for 1m–15m monitoring.
Swing (default)
Balanced behaviour. Best for 15m–4H analysis.
Position
Lower sensitivity + higher smoothing + slower memory decay. Best for 4H–1D macro context.
█ STRUCTURAL MEMORY
When a regime fails (example: Expansion → Distribution), MSI creates a memory imprint:
- Fixed stain window (preset dependent)
- Strength decays over time
- Limited to a maximum number of imprints to reduce chart clutter
These zones represent behavioural rejection, not levels.
█ SUITABLE MARKETS
MSI is designed for Forex, Crypto, Indices, Stocks, and Commodities.
Works from intraday to Daily, with particularly strong readability on 15m–4H.
█ DISCLAIMER
This indicator is for educational and informational purposes only. It does not constitute financial advice, trading recommendations, or solicitation. Trading involves substantial risk. Always use proper risk management and make independent decisions.
Volume Weighted ATRThis script implements a Volume‑Weighted Average True Range (VWATR) indicator, a variation of ATR that incorporates trading volume into the volatility calculation. Instead of treating all price movements equally, it amplifies true range during high‑volume periods and dampens it during low‑volume periods, producing a volatility measure that adapts to liquidity conditions. The script begins by allowing the user to choose a lookback length and a smoothing method, offering RMA, SMA, EMA, or WMA for flexibility in how responsive the indicator should be.
The core of the calculation starts with the standard true range, which captures the most meaningful price movement of each bar. This true range is then multiplied by volume, creating a volume‑weighted true range that gives more importance to bars where market participation is higher. To ensure consistency, the script defines a custom moving‑average function that applies the selected smoothing method to any input series. This function is used twice: once to smooth the volume‑weighted true range and once to smooth volume itself.
The final VWATR value is obtained by dividing the smoothed volume‑weighted true range by the smoothed volume. Mathematically, this produces a volume‑weighted mean of true range, making the indicator more sensitive to volatility expansions that occur with strong participation and less reactive to low‑volume noise. The script concludes by plotting this VWATR line, giving traders a clean, adaptive measure of volatility that can be used for regime detection, breakout confirmation, or dynamic stop sizing
Quantum Wolf Model Options CoreQuantum Wolf Model — Options Core
Overview
Quantum Wolf Model — Options Core is a decision-support indicator designed to assist traders with options market evaluation, risk awareness, and position sizing guidance.
The script does not place trades, does not generate automatic buy/sell orders, and does not predict future price movements.
How the Indicator Works
The model evaluates market conditions using a layered framework:
Market regime analysis to identify trend or range environments
Higher-timeframe bias alignment for directional context
Volatility assessment using ATR and implied-volatility ranking
Liquidity and volume participation to filter low-quality conditions
Session context awareness to account for active vs thin trading periods
Price-derived Greek-style sensitivity metrics (Delta, Gamma, Theta) to assess directional responsiveness, volatility expansion, and time-decay risk
These factors are combined into an internal scoring and filtering process that helps determine when options exposure may be more appropriate and how risk could be scaled based on current conditions.
Risk & Usage Notes
This indicator is for informational and analytical purposes only.
It is not financial advice and should not be used as a standalone trading system.
Options trading involves significant risk, and users are responsible for all execution and risk management decisions.
Intended Audience
Designed for traders who understand options mechanics and want an additional market-condition and risk-governance layer to support their own strategy.
Disclaimer
Past market behavior does not guarantee future results.
Use at your own discretion.
Spike Detector (Ticks/Points)Spike Detector (Ticks / Points)
What This Indicator Does
Spike Detector (Ticks / Points) helps you easily spot large, high-volatility candles on your chart. These “spike” candles often happen during strong momentum, breakouts, stop runs, or sudden reversals.
Instead of guessing whether a candle is “big enough,” this indicator automatically measures each candle’s size and highlights it when it exceeds a threshold you choose.
How It Works (Simple Explanation)
The indicator measures the high-to-low range of every candle
It converts that range into ticks using the instrument’s minimum tick size
If the candle size is equal to or greater than your selected threshold, it is marked as a spike
Spike candles are:
Colored green for bullish candles
Colored red for bearish candles
A label is placed on the chart showing the candle size in ticks or points
This logic is non-repainting and works on all timeframes.
Inputs Explained
Spike Size Threshold
The minimum candle size required to be considered a spike (measured in ticks)
Display Unit (Ticks / Points)
Choose whether the label shows the candle size in:
Ticks (recommended for futures)
Points (useful for stocks and indices)
Label Offset
Adjusts how far above or below the candle the label appears
How to Use This Indicator
This indicator is meant to be used as a visual tool, not a standalone trading system.
Common ways traders use it:
Identify momentum ignition candles
Spot stop runs or liquidity grabs
Confirm breakouts with strong candle expansion
Avoid entering trades during abnormally volatile bars
Study volatility behavior during specific sessions
Many traders combine this with:
Market structure
Support & resistance
Trend direction
Volume or session context
Tips for Best Results
Start with a moderate threshold and adjust based on the market you trade
Higher timeframes usually need larger thresholds
Futures traders may prefer tick mode, while stock traders may prefer points
Use spike candles as context, not signals by themselves
Notes
Works on all symbols that support tick size data
Does not repaint
Designed to be lightweight and easy to read
Disclaimer
This indicator is for educational and informational purposes only. It does not provide trade signals or financial advice. Always manage risk appropriately.
Equilibrium Reversal Channel [BOSWaves]Equilibrium Reversal Channel - Volatility-Based Risk Geometry for Mean Reversion Scenarios
Overview
The Equilibrium Reversal Channel is a volatility-weighted price channel designed to highlight statistically stretched price conditions and assist traders in identifying mean-reversion opportunities within broader market structure. The indicator is not intended to predict market direction in isolation, but rather to contextualize price movement relative to volatility, trend balance, and exhaustion zones.
At its foundation, this tool operates on the assumption that price oscillates around a dynamic equilibrium. When price deviates too far from that equilibrium - particularly under expanding volatility - the probability of a reaction, pause, or reversal increases. The Reversal Channel visualizes these deviations clearly, continuously, and without relying on fixed thresholds or static support/resistance levels.
This indicator is best used as a contextual framework, not as a standalone trading system. Its strength lies in defining where reactions are statistically more likely to occur and when price has moved far enough to warrant caution or contrarian attention.
Use Cases
Primary Use Case 1: Volatility-Anchored Trade Framing (TP / SL Construction)
The Equilibrium Reversal Channel is used to construct trade reference levels directly from live market structure and volatility behavior, rather than from arbitrary price distances.
Stop invalidation is framed around the outer displacement boundary. This boundary represents the point at which price is no longer statistically stretched but instead entering a new volatility regime, invalidating the original mean-reversion premise. In other words, if price accepts beyond this zone, the imbalance thesis is structurally broken.
Take-profit projections are derived from measured rebalancing paths back toward equilibrium, scaled using configurable payoff ratios. These projections reflect how far price typically resolves once imbalance conditions unwind, rather than relying on fixed targets or discretionary exits.
This use case turns the channel into a risk geometry tool — defining where a trade idea is wrong, where resolution is likely to occur, and whether the opportunity offers asymmetric payoff before capital is committed.
Primary Use Case 2: Identifying Statistically Stretched Price Conditions
The second core function of the Reversal Channel is identifying when price is operating far enough from its volatility-adjusted balance state to justify contrarian attention.
Sustained interaction with the outer displacement zones signals that price has entered a statistically inefficient regime. Continuation may still occur, but the marginal return on momentum decreases while reaction probability increases. The channel highlights these conditions in real time, without relying on fixed thresholds or static reference levels.
Rather than predicting reversals, this framework defines where continuation becomes fragile and where rebalancing pressure historically emerges - particularly when reinforced by higher-timeframe structure or liquidity context.
Central Basis Line (Market Equilibrium)
At the core of the Reversal Channel is a dynamically adaptive balance line derived from recent price behavior. This line represents the market’s evolving equilibrium - the point around which price naturally oscillates under normal conditions.
The balance calculation prioritizes recent market information while maintaining smooth continuity, allowing it to adjust efficiently as conditions change without overreacting to short-term noise. Rather than acting as a directional signal, this axis serves as a reference framework for measuring price displacement, volatility expansion, and rebalancing pressure.
Extended acceptance above the equilibrium suggests sustained bullish pressure, while prolonged activity below reflects bearish dominance. However, the Reversal Channel is intentionally agnostic to directional bias - its focus is on distance from balance, not trend prediction.
Volatility-Weighted Channel Construction
Surrounding the equilibrium line are three upper and three lower displacement bands, each derived from a real-time volatility normalization process. This process measures actual market expansion and contraction rather than relying on static price offsets, allowing the channel to adapt fluidly across assets, sessions, and regime shifts.
Each successive band represents an increasing degree of statistical displacement from equilibrium:
The first tier reflects mild volatility expansion
The second tier captures elevated deviation
The outer tier represents extreme statistical stretch
Because the channel geometry is volatility-responsive, it expands during high-energy conditions and contracts during quieter phases. This prevents structural distortion - avoiding channels that are either too restrictive in low volatility or meaningless during aggressive expansion.
To maintain visual coherence and structural continuity, displacement boundaries are processed through a secondary smoothing mechanism. This refinement preserves volatility information while ensuring the channel flows naturally with price action instead of reacting mechanically to isolated candles.
Zone Interpretation (Green, Yellow, Red)
The channel is visually segmented into three color-coded zones on both the upper and lower side of the basis. These zones are not signals - they are probability regions.
The green zone, closest to the basis, represents normal price fluctuation. Price entering this area does not imply exhaustion or reversal; it simply reflects routine movement around equilibrium.
The yellow zone indicates price is becoming extended. Momentum may still continue, but risk increases. This zone often corresponds with late-trend behavior, reduced reward-to-risk for continuation trades, and early contrarian interest.
The red zone represents extreme deviation relative to recent volatility. Price reaching this area suggests the market is operating far from equilibrium. While reversals are not guaranteed, this zone statistically favors slowing momentum, rejection, or reversion, especially when combined with structural or higher-timeframe confluence.
Importantly, these zones are symmetrical. Extreme conditions exist on both the upside and downside, allowing the channel to function in bullish, bearish, and ranging markets.
Reversal Sensitivity Logic
Rather than generating signals immediately when price enters a zone, the indicator uses a confirmation counter mechanism. This means price must remain beyond the first volatility boundary for a user-defined number of consecutive bars before a reversal signal is allowed.
This approach reduces false positives caused by single-candle spikes or transient wicks. By requiring persistence, the indicator attempts to confirm that price is genuinely operating in an extended state rather than momentarily probing it.
Sensitivity inputs allow traders to control how strict this confirmation process is. Lower sensitivity values produce faster signals with higher frequency but lower confirmation. Higher values demand more sustained extension, reducing signal count but increasing contextual reliability.
Buy and Sell Signal Logic
A buy signal is generated only after price has remained below the lower volatility boundary for the required number of consecutive bars and no active trade condition is present. Conceptually, this reflects downside exhaustion relative to volatility.
A sell signal follows the same logic on the upper side, triggering only after sustained price extension above the upper volatility boundary.
These signals are contrarian by design. They are not trend continuation entries. They assume that when price stretches too far, too quickly, the probability of reaction increases - particularly in markets that oscillate rather than trend cleanly.
Trade State Awareness and Exit Logic
The indicator internally tracks whether a trade condition is active. This prevents repeated signals from firing continuously while price remains extended.
Once a trade condition is active, the indicator monitors price relative to the basis line. The basis acts as a logical exit reference, representing a return toward equilibrium. When price crosses back through the basis in the direction of the trade, the condition is reset.
This design reinforces the indicator’s purpose: capturing mean reversion back toward balance, not trend continuation beyond it.
Risk Reference Levels (TP / SL Framework)
Optional take-profit and stop-loss reference levels are derived directly from channel structure rather than arbitrary values. Stop placement is anchored near the outermost volatility band, reflecting the point at which the statistical premise of the trade is invalidated.
Multiple take-profit projections are calculated using configurable risk-to-reward ratios. These levels are not recommendations; they exist to provide structure, visual planning, and consistency when evaluating potential trades.
The indicator does not manage trades. It provides spatial context so the trader can make informed decisions.
Practical Use & Context
The Equilibrium Reversal Channel performs best in markets that exhibit rotational behavior or frequent volatility expansion and contraction. In strong, one-directional trends, extreme zones may persist longer than expected. For this reason, the indicator should always be used alongside higher-timeframe structure, trend context, or directional filters.
Its purpose is not to outperform trend systems, but to define statistical stretch clearly and consistently across assets and timeframes.
Final Notes
Equilibrium Reversal Channel is designed as a contextual decision-support framework rather than a predictive system. It visualizes price behavior relative to dynamically adjusted equilibrium and volatility boundaries, offering insight into statistically stretched conditions and potential mean-reversion opportunities. Its outputs are guidance-oriented, not guarantees, and should be interpreted alongside broader market structure, higher-timeframe context, and sound risk management practices. Every visual element, zone, and signal is intended to enhance situational awareness, empower disciplined decision-making, and provide probabilistic insight into market behavior, not dictate outcomes. Traders are strongly encouraged to combine this framework with their own strategy execution and capital management protocols.
Risk Disclaimer
This indicator is provided for educational and informational purposes only and does not constitute financial advice. Trading involves significant risk, and past performance is not indicative of future results. Users are responsible for their own analysis, risk management, and execution decisions.
Big Trades / Intrabar Volume Clusters by HKDescription:
This indicator brings professional Order Flow and Footprint capabilities to your chart. It detects and visualizes high-volume trade clusters inside the candle, allowing you to see exactly at which price level big market participants were active.
Unlike standard volume bars, this tool uses Intrabar Data to map significant buying and selling pressure precisely within the candle body.
ℹ️ IMPORTANT: Resolution Setting (Read First) To ensure this indicator works immediately for all users (including Free/Basic accounts), the default resolution is set to "1 Minute".
Basic/Free Users: Please keep the setting at "1" (Second-based intervals often require a paid plan).
Premium Users: For the best precision and the exact look shown in the screenshots, we highly recommend changing the Resolution setting to "5S" (5 Seconds)!
🚀 Key Features
Intrabar Precision: Leverages request.security_lower_tf to look inside the candle structure.
Noise Filtering: Only displays clusters that exceed your defined Minimum Volume threshold, filtering out retail noise.
Smart Coloring:
Green: Buying pressure (Close >= Open on the lower timeframe).
Red: Selling pressure (Close < Open on the lower timeframe).
🆕 Independent Sizing: A unique feature: You can control the Font Size and Circle Size independently.
This allows for small, non-intrusive circles with large, readable text.
⚙️ Settings
Resolution: Default is 1 (Minute). Premium users should switch to 5S for true order flow precision.
Minimum Volume: The most important filter. Determines how large a trade cluster must be to appear (e.g., 150+ for ETH, higher for BTC).
Visuals: Customize Buy/Sell colors, Circle Size, and Text Size separately.
⚠️ Visual Tip (If text is hidden)
If the bubbles or numbers appear behind the candles or disappear when clicking away:
Right-click on any of the indicator bubbles.
Select Visual Order -> Bring to Front.
This ensures the Big Trades data always floats on top of your price bars.
Statistical Reversion FrameworkIntroduction and Core Philosophy
The Statistical Reversion Framework constitutes a sophisticated quantitative trading instrument designed to identify high-probability mean reversion opportunities across financial markets. Unlike traditional technical indicators that rely on a single dimension of market data, this framework adopts a multi-faceted approach, synthesizing statistical probability, volume profile analysis, institutional money flow proxies, and standard technical momentum into a singular composite score. The core philosophy driving this script is the concept of confluence through heterogeneity; by combining uncorrelated or loosely correlated market factors—such as price deviation (statistics), participant commitment (volume), and macro sentiment (intermarket data)—the algorithm aims to filter out the noise inherent in standard oscillators and isolate moments where market pricing has deviated unsustainably from its intrinsic equilibrium. This tool is specifically engineered to detect market extremes—tops and bottoms—where the probability of a counter-trend move or a snap-back to the mean is mathematically significant. It operates on the premise that while asset prices can remain irrational in the short term, they are bound by statistical variance and mean-reverting properties over longer horizons, particularly when institutional flows and volume exhaustion patterns align with those statistical extremes.
Methodology: The Composite Scoring Architecture
The underlying methodology of the framework relies on a weighted composite scoring system. Rather than generating binary buy or sell signals based on a threshold crossover, the script calculates a granular score ranging from zero to one hundred for various market dimensions. These dimension-specific scores are then weighted according to user-defined inputs to produce a final "Composite Score." This approach allows for a nuanced assessment of market conditions; a setup might have extreme statistical deviation but lack volume confirmation, resulting in a lower confidence score than a setup where price, volume, and macro factors all align. The algorithm normalizes all input data into a standardized scale, typically converting raw values—such as Z-Scores or volume ratios—into a zero-to-ten ranking before aggregating them. This normalization process is critical because it allows the algorithm to compare apples to oranges mathematically, treating a standard deviation of 3.0 and a Relative Strength Index (RSI) of 20 as compatible inputs within the same equation. By summing these normalized values and applying regime-based confidence adjustments, the framework produces a dynamic signal that adapts to the volatility and trend intensity of the current market environment.
Algorithmic Component I: Statistical Analysis via Multi-Timeframe Z-Scores
The backbone of the framework is the Statistical Component, which utilizes the Z-Score (or Standard Score) to quantify the degree of price deviation. The Z-Score measures how many standard deviations the current price is from its moving average. A crucial aspect of this algorithm is its fractal nature; it does not rely on a single lookback period. Instead, it computes Z-Scores across three distinct timeframes—Daily, Weekly, and Monthly—and within each timeframe, it calculates deviations for short, medium, and long-term periods. For instance, on the daily timeframe, it assesses deviation from 50-day, 200-day, and 500-day means simultaneously. This multi-timeframe approach is designed to filter out ephemeral noise. A price move that appears extreme on a 10-day basis but is normal on a 200-day basis is likely a trend pull-back rather than a reversal. Conversely, when the Z-Scores across daily, weekly, and monthly timeframes all register values beyond significant thresholds (such as 2.0 or 3.0 standard deviations), it indicates a rare fractal alignment where the asset is historically overextended on all relevant scales. The algorithm aggregates these nine distinct Z-Score data points to form the "Statistical Score," heavily rewarding scenarios where multiple timeframes show directional alignment, as these synchronized deviations often precede powerful mean-reversion events.
Algorithmic Component II: Volume Signature and Participation Analysis
While statistical deviation highlights where the price is, the Volume Component analyzes the conviction behind the move to determine if a reversal is imminent. This section of the code employs several sophisticated logic gates to identify specific volume signatures known as Capitulation and Exhaustion. The algorithm compares current volume against a 50-day moving average to generate a volume ratio. It then correlates this ratio with price action. For example, the script identifies "Capitulation" when price collapses significantly (more than 2%) on volume that is at least three times the average. This specific signature—panic selling—often marks the psychological wash-out necessary for a market bottom. Conversely, the script detects "Volume Exhaustion" when prices drift without conviction on extremely low volume, indicating a lack of participant interest in pushing the trend further. Furthermore, the algorithm integrates On-Balance Volume (OBV) analysis, specifically looking for divergences. It detects subtle shifts where the price makes a new low, but the OBV makes a higher low, signaling that smart money is accumulating positions despite the falling price. This divergence logic is automated using pivot-based high/low detection arrays, adding a layer of foreshadowing that price-only indicators often miss.
Algorithmic Component III: Institutional Proxy and Intermarket Correlations
The Institutional Component distinguishes this framework from standard retail indicators by incorporating intermarket data that serves as a proxy for macro sentiment and institutional flow. The script pulls data from extraneous tickers—specifically the VIX (Volatility Index), Government Bond Yields (10-year and 2-year), Copper, Gold, and the Dollar Index (DXY). The logic here is grounded in fundamental market mechanics. For instance, the script analyzes the VIX to gauge market fear; however, it applies a contrarian logic. An extremely high VIX (panic) coincident with a low equity price is scored as a bullish factor, while a complacently low VIX at market highs is viewed as bearish. Similarly, the algorithm analyzes the Yield Curve (the spread between 10-year and 2-year yields). A steepening or flattening curve provides context on economic expectations, influencing the score based on whether the environment is "risk-on" or "risk-off." The Copper/Gold ratio is utilized as a barometer for global economic health; rising copper relative to gold suggests industrial demand and growth, confirming bullish setups, whereas falling copper prices signal contraction. By integrating these non-price variables, the framework ensures that a trade signal is not just technically sound but is also supported by the broader macroeconomic undercurrents that drive institutional capital allocation.
Algorithmic Component IV: Technical Momentum and Structure
The final layer of input comes from standard Technical Analysis, which serves to fine-tune the timing of the entry. This component aggregates readings from the Relative Strength Index (RSI), Moving Average Convergence Divergence (MACD), Bollinger Bands, and Support/Resistance proximity. While Z-Scores measure linear distance from the mean, the RSI and Bollinger Bands measure the velocity and elasticity of that move. The algorithm assigns higher scores when RSI hits extreme levels (below 20 or above 80) and when price action pierces the outer bounds of the Bollinger Bands. Additionally, the MACD is monitored for histogram reversals and signal line crosses that align with the mean reversion bias. A unique feature of this component is the proximity logic, which calculates how close the current price is to a 50-period high or low. If a statistical extreme coincides with a retest of a major structural support level, the technical score is maximized. This ensures that the trader is not catching a falling knife in a void, but rather identifying a reversal at a location where technical structure provides a natural floor or ceiling for price.
Regime Detection and Confidence Adjustment
A critical vulnerability of mean reversion strategies is that they can suffer severe drawdowns during strong, unidirectional trending markets (momentum regimes). To mitigate this, the framework incorporates a Regime Detection module using the Average Directional Index (ADX) and volatility thresholds. The script calculates the ADX to measure trend strength regardless of direction. If the ADX is above a certain threshold (default 25), the market is classified as "Trending." The script then cross-references this with volatility data to classify the environment into regimes such as "Crisis," "Trending," "Range," or "Mean-Revert." This classification is not merely cosmetic; it actively influences the final output through a "Regime Confidence" multiplier. If the system detects a strong trending regime, it dampens the Composite Score, requiring extraordinary evidence from the other components to trigger a signal. Conversely, if the market is detected as "Mean-Revert" or "Low-Vol Range," the confidence multiplier boosts the score, making the system more sensitive to reversion signals. This adaptive logic helps protect the trader from fading strong breakouts while aggressively capitalizing on ranging markets.
Usage Instructions and Dashboard Interpretation
Traders utilizing this framework should primarily interact with the on-screen Dashboard, which provides a real-time summary of all computed metrics. The dashboard is organized hierarchically, with the "Composite Score" and "Signal Status" at the top. A Composite Score above 70 is generally considered actionable, with scores above 85 representing "Exceptional" setups. The Dashboard is color-coded: green hues indicate bullish/oversold conditions suitable for buying, while red hues indicate bearish/overbought conditions suitable for selling or shorting. Traders should look for "Confluence" across the rows. Ideally, a robust signal will show a high Statistical score (indicating price is cheap/expensive), a high Volume score (indicating capitulation or accumulation), and a supportive Institutional score. If the Composite Score is high but the Institutional score is low, the trader should proceed with caution, as the macro environment may not support the trade.
The chart visuals provide immediate entry triggers. "Strong Bottom" (Green Triangle) and "Strong Top" (Red Triangle) shapes appear when the Composite Score breaches the high threshold and Z-Scores are at extremes. These are the primary execution signals. Smaller "Potential" markers indicate developing setups that may require lower timeframe confirmation. Additionally, specific volume icons (Diamonds) will appear to denote Capitulation or Climax events. A trader should ideally wait for the candle to close to confirm these signals. The alerts configured in the script allow the trader to be notified of these events remotely. For risk management, because this is a mean reversion tool, stop-losses should typically be placed below the swing low of the capitulation candle (for longs) or above the swing high of the climax candle (for shorts), anticipating that the statistical extreme marks the distinct turning point. By systematically waiting for the Composite Score to align with the visual signals and verifying the regime context on the dashboard, the trader effectively filters out low-probability trades, engaging only when statistics, volume, and macro-economics align.
VIX Percentile OscillatorWhat is this script?
This is a trading tool that helps you decide when to buy or sell options based on market volatility. Think of it as a "fear meter" for the stock market.
What is VIX?
VIX = Volatility Index (also called the "fear index")
When VIX is HIGH → Market is scared/volatile → Options are EXPENSIVE
When VIX is LOW → Market is calm → Options are CHEAP
What does "Percentile" mean?
Instead of just showing VIX price, this script shows where VIX is compared to history.
Example: If VIX Percentile = 85%
This means VIX is higher than 85% of all past readings
Only 15% of the time was VIX higher than now
Translation: Volatility is unusually HIGH
The 5 Trading Zones
The script divides the market into 5 zones:
🔴 EXTREME SELLING ZONE (90-100%)
VIX is in the top 10% historically
Action: AGGRESSIVELY SELL OPTIONS (collect big premiums)
Market panic = expensive options = profit for sellers
🟠 SELLING ZONE (80-89%)
VIX is elevated but not extreme
Action: SELL OPTIONS (good premiums available)
⚪ NEUTRAL ZONE (20-79%)
VIX is normal
Action: WAIT or use other strategies
🟢 BUYING ZONE (10-19%)
VIX is low
Action: BUY OPTIONS (they're cheap)
🟢 EXTREME BUYING ZONE (0-9%)
VIX is in the bottom 10% historically
Action: AGGRESSIVELY BUY OPTIONS (bargain prices)
Market complacency = cheap options = opportunity
Understanding the Chart
Main Line (Blue/Red/Green):
Shows current VIX percentile
Color changes based on zone
Thick line = easy to see
Histogram (Background bars):
Red bars = above 50% (high volatility)
Green bars = below 50% (low volatility)
Purple Momentum Line:
Shows if VIX is rising or falling
Helps you catch trends early
Background Colors:
Light red/orange = Selling zones
Light green = Buying zones
Triangle Markers:
Appear when entering new zones
"EXTREME" label = strongest signals
The Statistics Table (Top Right)
VIX Price: Current VIX value (e.g., 16.50)
Percentile: Where VIX ranks (0-100%)
Z-Score: Statistical measure
Above +2 or below -2 = extreme
Red text = unusually high/low
Momentum: Rate of change
Red = rising (volatility increasing)
Green = falling (volatility decreasing)
Avg VIX: Average VIX over lookback period
Current Zone: Which zone you're in right now
Bars in Zone: How long you've been in this zone
Simple Trading Rules
FOR OPTION SELLERS (Premium Collectors):
✅ SELL when: Percentile > 80% (especially > 90%)
High premiums available
Examples: Sell covered calls, cash-secured puts, credit spreads
FOR OPTION BUYERS (Hedgers/Speculators):
✅ BUY when: Percentile < 20% (especially < 10%)
Cheap options available
Examples: Buy protective puts, long calls, debit spreads
Key Settings You Can Adjust
Lookback Period (default: 252)
How far back to compare (252 = 1 year of trading days)
Longer = smoother, more stable
Shorter = more sensitive to recent changes
Smoothing Period (default: 3)
Reduces noise/wiggling
Higher = smoother line
Lower = more responsive
Zone Thresholds:
Extreme Sell: 90%
Sell: 80%
Buy: 20%
Extreme Buy: 10%
You can customize these!
Real-World Example
Scenario: VIX Percentile jumps to 92%
What this means:
VIX is higher than 92% of all past readings
Market is in panic mode
Option premiums are INFLATED
Trading Action:
✅ Sell covered calls on stocks you own
✅ Sell cash-secured puts on stocks you want to buy
✅ Sell credit spreads
❌ DON'T buy expensive options right now
Why it works: When fear is extreme, it usually calms down eventually. You profit as premiums deflate.
Important Reminders
⚠️ This is a TIMING tool, not a crystal ball
It tells you WHEN premiums are expensive/cheap
It doesn't tell you WHICH options to trade
You still need proper risk management
⚠️ Works on ALL timeframes
Daily charts = swing trading
Weekly charts = position trading
Intraday charts = day trading volatility
⚠️ Best for:
Option sellers during high VIX (>80%)
Option buyers during low VIX (<20%)
Portfolio hedging decisions
Volatility trading strategies
Bottom Line: This script helps you buy options when they're cheap and sell options when they're expensive. It's like shopping for sales, but for volatility!
DISCLAIMER: This information is provided for educational purposes only and should not be considered financial, investment, or trading advice. Please do boost if you like it. Happy Trading.
TZ - India VIX Volatility ZonesTZ – India VIX Volatility Zones is a long-term volatility analysis indicator designed to visually map important India VIX regimes using clearly defined horizontal zones and labels.
The indicator highlights how market volatility cycles between complacency, normal conditions, elevated risk, and panic phases. These zones are based on historical behavior of India VIX and help traders understand when risk is underpriced or overstretched.
This tool is especially useful for:
Index traders
Options sellers and buyers
Risk management and regime filtering
Long-term volatility study
How It Works
The script plots static, historically significant volatility zones on the India VIX chart and visually separates them using shaded bands and labels.
Volatility Zones Explained
1.Extreme Low Volatility (VIX 8–10)
Indicates market complacency and underpriced risk. Often precedes volatility expansion.
2.Low Volatility (VIX 10–13)
Stable market conditions with controlled movement.
3.Normal Volatility (VIX 13–18)
Healthy market behavior and balanced risk.
4.High Volatility (VIX 18–25)
Rising uncertainty and increased intraday swings.
5.Panic Zone (VIX 25–35+)
High fear environment, usually during major events or crises.
How Traders Can Use This Indicator
Identify volatility regimes before choosing option strategies
Avoid aggressive short-volatility trades during extreme zones
Prepare for volatility expansion during low-VIX phases
Use as a market risk context tool alongside price action
This indicator does not provide buy/sell signals. It is designed for contextual analysis and decision support.
Best Usage
Apply on India VIX (NSE:INDIAVIX)
Works best on Weekly and Monthly timeframes
Can be combined with index charts for volatility-based risk assessment
Disclaimer
This indicator is for educational and analytical purposes only.
It does not constitute financial advice or trade recommendations.
Users should apply proper risk management and confirm signals using additional analysis.
Kalman Hull Kijun [BackQuant]Kalman Hull Kijun
A trend baseline that merges three ideas into one clean overlay, Kalman filtering for noise control, Hull-style responsiveness, and a Kijun-like Donchian midline for structure and bias.
Context and lineage
This indicator sits in the same family as two related scripts:
Kalman Price Filter
This is the foundational building block. It introduces the Kalman filter concept, a state-estimation algorithm designed to infer an underlying “true” signal from noisy measurements, originally used in aerospace guidance and later adopted across robotics, economics, and markets.
Kalman Hull Supertrend
This is the original script made, which people loved. So it inspired me to create this one.
Kalman Hull Kijun uses the same core philosophy as the Supertrend variant, but instead of building a Supertrend band system, it produces a single structural baseline that behaves like a Kijun-style reference line.
What this indicator is trying to solve
Most trend baselines sit on a bad trade-off curve:
If you smooth hard, the line reacts late and misses turns.
If you react fast, the line whipsaws and tracks noise.
Kalman Hull Kijun is designed to land closer to the middle:
Cleaner than typical fast moving averages in chop.
More responsive than slow averages in directional phases.
More “structure aware” than pure averages because the baseline is range-derived (Kijun-like) after filtering.
Core idea in plain language
The plotted line is a Kijun-like baseline, but it is not built from raw candles directly.
High level flow:
Start with a chosen price stream (source input).
Reduce measurement noise using Kalman-style state estimation.
Add Hull-style responsiveness so the filtered stream stays usable for trend work.
Build a Kijun-like baseline by taking a Donchian midpoint of that filtered stream over the base period.
So the output is a single baseline that is intended to be:
Less jittery than a simple fast MA.
Less laggy than a slow MA.
More “range anchored” than standard smoothing lines.
How to read it
1) Trend and bias (the primary use)
Price above the baseline, bullish bias.
Price below the baseline, bearish bias.
Clean flips across the baseline are regime changes, especially when followed by a hold or retest.
2) Retests and dynamic structure
Treat the baseline like dynamic S/R rather than a signal generator:
In uptrends, pullbacks that respect the baseline can act as continuation context.
In downtrends, reclaim failures around the baseline can act as continuation context.
Repeated back-and-forth around the line usually means compression or chop, not clean trend.
3) Extension vs compression (using the fill)
The fill is meant to communicate “distance” and “pressure” visually:
Large separation between price and baseline suggests expansion.
Price compressing into the baseline suggests rebalancing and decision points.
Inputs and what they change
Kijun Base Period
Controls the structural memory of the baseline.
Higher values track broader swings and reduce flips.
Lower values track tighter swings and react faster.
Kalman Price Source
Defines what data the filter is estimating.
Close is usually the cleanest default.
HL2 often “feels” smoother as an average price.
High/Low sources can become more reactive and less stable depending on the market.
Measurement Noise
Think of this as the main smoothness knob:
Higher values generally produce a calmer filtered stream.
Lower values generally produce a faster, more reactive stream.
Process Noise
Think of this as adaptability:
Higher values adapt faster to changing conditions but can get twitchy.
Lower values adapt slower but stay stable.
Plotting and UI (what you see on chart)
1) Adaptive line coloring
Baseline turns bullish color when price is above it.
Baseline turns bearish color when price is below it.
This makes the state readable without extra panels.
2) Gradient “energy” fill
Bull fill appears between price and baseline when above.
Bear fill appears between price and baseline when below.
The goal is clarity on separation and control, not decoration.
3) Rim effect
A subtle band around price that only appears on the active side.
Helps highlight directional control without hiding candles.
4) Candle painting (optional)
Candles can be colored to match the current bias.
Useful for scanning many charts quickly.
Disable if you prefer raw candles.
Alerts
Long state alert when price is above the baseline.
Short state alert when price is below the baseline.
Best used as a bias or regime notification, not a standalone entry trigger.
Where it fits in a workflow
This is a context layer, it pairs well with:
Market structure tools, BOS/MSB, OBs, FVGs.
Momentum triggers that need a regime filter.
Mean reversion tools that need “do not fade trends” context.
Limitations
No baseline eliminates chop whipsaws, tuning only manages the trade-off.
Settings should not be copy pasted across assets without checking behavior.
This does not forecast, it estimates and smooths state, then expresses it as a structural baseline.
Disclaimer
Educational and informational only, not financial advice.
Not a complete trading system.
If you use it in any trading workflow, do proper backtesting, forward testing, and risk management before any live execution.
Buying Opportunity Score V2.2Buying Opportunity Indicator V2.2
What This Indicator Does
This indicator identifies potential buying opportunities during market fear and pullbacks by combining multiple technical signals into a single composite score (0-100). Higher scores indicate more fear/oversold conditions are present simultaneously.
Why These Components?
Market bottoms typically occur when multiple fear signals align. This indicator combines five complementary measurements that each capture different aspects of market stress:
1. VIX Level (30 points) - Measures implied volatility/fear. VIX spikes during selloffs as traders buy protection. Thresholds based on historical percentiles (VIX 25+ is ~85th percentile historically).
2. Price Drawdown (30 points) - Distance from 52-week high. Larger drawdowns create better risk/reward for mean reversion entries. A 10%+ drawdown from highs historically presents better entry points than buying at all-time highs.
3. RSI 14 (12 points) - Classic momentum oscillator measuring oversold conditions. RSI below 30 indicates short-term selling exhaustion.
4. Bollinger Band Position (13 points) - Statistical measure of price extension. Price below the lower band (2 standard deviations) indicates statistically unusual weakness.
5. VIX Timing (15 points) - Bonus points when VIX is declining from a recent peak. This helps avoid catching falling knives by waiting for fear to subside.
How The Score Works
- Each component contributes points based on severity
- Components are weighted by predictive value from historical analysis
- Score of 70+ means multiple fear signals are present
- Score of 80+ means extreme fear across most components
How To Use
1. Apply to SPY, QQQ, or IWM on daily timeframe
2. Monitor the Current Score in the statistics table
3. Scores below 50 = normal conditions, no action needed
4. Scores 60-69 = elevated fear, monitor closely
5. Scores 70+ = consider entering long positions
6. Scores 80+ = strongest historical entry points
Important Limitations
- This is a research tool, not financial advice
- Past patterns may not repeat in the future
- Signals are infrequent (typically 2-4 per year reaching 70+)
- Works best on broad market ETFs; not validated for individual stocks
- Always use proper position sizing and risk management
- The indicator identifies conditions that have historically been favorable, but cannot predict future returns
Statistics Table
The table shows:
- Current Score with context message
- Chart Results: Rolling 1Y/3Y/5Y statistics from your loaded chart data
Alerts
Multiple alert options available for different score thresholds.
Open Source
Code is fully visible for review and educational purposes.
ATR-Normalized VWMA DeviationThis indicator measures how far price deviates from the Volume-Weighted Moving Average ( VWMA ), normalized by market volatility ( ATR ). It identifies significant price reversal points by combining price structure and volatility-adjusted deviation behavior.
The core idea is to use VWMA as a dynamic trend anchor, then measure how far price travels away from it relative to recent volatility . This helps highlight when price has stretched too far and may be due for a reversal or pullback.
How it works:
VWMA deviation is calculated as the difference between price and the VWMA.
That deviation is divided by ATR (Average True Range) to normalize for current volatility.
The script tracks the highest and lowest normalized deviations over the chosen lookback period.
It also tracks price structure (highest/lowest highs/lows) over the same period.
A reversal signal is generated when a historical extreme in deviation aligns with a price structure extreme, and a confirmed reversal candle forms.
You get visual signals and color highlights where these conditions occur.
Settings explained:
Lookback period defines how many bars the script uses to find recent extremes.
ATR length controls how volatility is measured.
VWMA length controls how the volume-weighted moving average is calculated.
Signal filters help refine entries based on price vs deviation behavior.
Display options let you customize how signals and levels appear on the chart.
This indicator is especially useful for spotting potential turning points where price has moved far from VWMA relative to volatility, suggesting possible exhaustion or overextension.
Tips for use:
Combine with broader trend context (higher timeframe support/resistance).
Use with risk management rules (position sizing, stops) — signals are guides, not guaranteed entries.
Adjust lookback and ATR settings based on your trading timeframe and asset volatility.
Futures Ultra CVD (Pure )Futures Ultra CVD (Pure)
Futures Ultra CVD (Pure) is a volume-driven Cumulative Volume Delta (CVD) indicator designed to expose real buying and selling pressure behind price movement. Unlike price-only indicators, this script analyzes how volume is distributed within each bar to determine whether aggressive buyers or sellers are in control, then tracks how that pressure evolves over time.
This version is intentionally pure and ungated: it does not rely on external symbols, market filters, session bias, or macro confirmation. All signals are derived strictly from price, volume, and delta behavior of the active chart, making it suitable for futures, equities, crypto, and FX.
Core Concept: How CVD Is Calculated
For each bar, volume is split into buying pressure and selling pressure using the bar’s price position:
Buying volume increases as price closes closer to the high
Selling volume increases as price closes closer to the low
The difference between buying and selling volume forms Delta:
Positive delta = net aggressive buying
Negative delta = net aggressive selling
This delta is then accumulated into Cumulative Volume Delta (CVD) using one of three user-selectable modes:
Total – running cumulative sum of all delta values
Periodic – rolling sum over a fixed lookback period
EMA – smoothed cumulative delta using an exponential average
This flexibility allows traders to choose between raw order-flow tracking or smoother, trend-like behavior depending on timeframe and instrument.
Visual Structure & Histogram Logic
The CVD is displayed as a column histogram, not a line, to emphasize momentum and pressure shifts.
Enhanced coloring provides additional context:
Brighter green/red bars indicate increasing momentum
Muted colors indicate stalling or weakening pressure
Optional footprint-style highlights appear when buy or sell volume overwhelms the opposite side by a user-defined imbalance factor
This allows traders to visually distinguish:
Strength vs weakness
Continuation vs exhaustion
Absorption and aggressive participation
Built-In Order Flow Signals
The script automatically detects and labels key order-flow events:
Strong Delta
Triggered when delta exceeds a user-defined threshold, highlighting unusually aggressive buying or selling.
Delta Surge
Detects sudden expansion in delta compared to the prior bar, often associated with breakout attempts or liquidation events.
Zero-Line Crosses
Marks transitions between net bullish and bearish participation as CVD crosses above or below zero.
CVD Continuation Logic (Trend Confirmation)
Beyond raw delta, the script evaluates CVD structure to identify continuation conditions:
A bullish continuation requires:
Positive and rising CVD
Strong buy delta
Confirmation from at least one of the following:
CVD above its EMA and SMA
Bullish price expansion
Sustained positive delta pressure
Bearish continuation follows the inverse logic.
These continuation signals are designed to confirm participation strength, not predict reversals.
Conflict Detection (Divergence Warning)
The indicator also flags conflict conditions, where:
Strong buying occurs while CVD remains negative
Strong selling occurs while CVD remains positive
These scenarios often precede failed breakouts, absorption zones, or short-term reversals and can be used as cautionary signals.
Alerts & Practical Use
All major events include built-in alerts:
Strong delta
Delta surge
CVD continuations
Zero-line crosses
Buy/sell imbalances
Conflict signals
Alerts can be set to trigger on bar close or intrabar in real time, depending on trader preference.
How Traders Typically Use This Indicator
Confirm breakouts with delta participation
Validate trends using CVD continuation instead of price alone
Identify absorption or exhaustion via conflicts and imbalances
Combine with price structure, VWAP, or market profile tools
This script is not a trading system by itself. It is a decision-support tool designed to reveal what price alone cannot: who is actually in control of the market.
On-Chart Symbols & What They Mean
This script uses a small number of visual symbols to communicate order-flow events clearly and consistently. All symbols are derived directly from the Cumulative Volume Delta calculations described above.
Δ+ (Green Up Arrow)
Strong Buy Delta
Indicates that buying pressure on the current bar exceeded the Strong Delta Threshold
Represents aggressive market buying dominating selling volume
Often appears during breakouts, trend acceleration, or initiative buying
This symbol does not imply direction by itself; it only confirms strong buyer participation.
Δ− (Red Down Arrow)
Strong Sell Delta
Indicates that selling pressure on the current bar exceeded the Strong Delta Threshold
Represents aggressive market selling dominating buying volume
Often appears during breakdowns, liquidation events, or initiative selling
Like Δ+, this symbol measures participation strength, not trade direction.
↑ (Green Label Up)
CVD Bullish Continuation
Appears when all of the following are present:
CVD is positive and increasing
Strong buy delta is detected
At least one confirmation condition is met:
CVD is above its EMA and SMA
Price shows bullish expansion
Consecutive positive delta bars (sustained buying pressure)
This symbol highlights trend continuation supported by volume, not a reversal signal.
↓ (Red Label Down)
CVD Bearish Continuation
Appears when:
CVD is negative and decreasing
Strong sell delta is detected
At least one confirmation condition is met:
CVD is below its EMA and SMA
Price shows bearish expansion
Consecutive negative delta bars (sustained selling pressure)
This indicates bearish continuation with participation confirmation.
Cyan / Orange Histogram Bars
Footprint-Style Volume Imbalance
Cyan bars indicate buy volume exceeds sell volume by the imbalance factor
Orange bars indicate sell volume exceeds buy volume by the imbalance factor
These bars highlight areas where one side is overwhelming the other, often associated with absorption, initiative moves, or failed auctions.
Bright vs Muted Histogram Colors
CVD Momentum State
Bright colors = CVD increasing in the direction of its current bias
Muted colors = CVD losing momentum or stalling
This allows quick visual identification of strengthening vs weakening participation.
Conflict Alerts (No Symbol by Default)
Delta vs CVD Disagreement
These conditions trigger alerts (but no fixed chart icon):
Strong buying while CVD remains negative
Strong selling while CVD remains positive
Conflicts often signal absorption, trap conditions, or short-term exhaustion.
Important Usage Notes
All symbols are informational, not trade entries.
Signals are calculated from price-based volume distribution, not true bid/ask data.
Results depend on the quality of volume data provided by the exchange and TradingView.
RegimeLens [JOAT]RegimeLens — Market Regime Detection and Classification
RegimeLens identifies whether the market is in a Trending, Ranging, or Volatile state using a proprietary combination of trend strength analysis, volatility measurement, and percentile-based classification. Understanding the current market regime helps traders adapt their approach to current conditions—because the strategy that works in a trend will fail in a range.
Why This Script is Protected
This script is published as closed-source to protect the proprietary regime classification algorithm and the specific threshold calibration methodology from unauthorized republishing. The unique combination of ADX analysis, Bollinger Band width percentiles, ATR percentile ranking, and the transition zone logic represents original work that goes beyond standard regime detection approaches.
What Makes This Indicator Unique
Unlike simple trend indicators, RegimeLens:
Classifies markets into four distinct regimes, not just "trending" or "not trending"
Uses percentile-based volatility analysis for more adaptive classification
Includes a transition zone logic to prevent rapid regime flip-flopping
Tracks regime duration and strength for additional context
Provides visual regime changes with on-chart labels
What This Indicator Does
Classifies market into four regimes: Trend Up, Trend Down, Ranging, or Volatile
Displays Bollinger Bands colored according to current regime
Marks regime changes with on-chart labels
Colors price bars according to detected regime
Tracks regime duration and strength metrics
Provides comprehensive dashboard with all regime metrics
Core Methodology
The indicator analyzes multiple market dimensions to determine the current regime:
Trend Strength Analysis (ADX) — Measures directional movement strength regardless of direction. High ADX indicates trending; low ADX indicates ranging.
Directional Bias (DI+ vs DI-) — Determines whether bullish or bearish forces dominate when a trend is detected.
Volatility Expansion/Contraction (BB Width) — Tracks Bollinger Band width relative to historical norms using percentile ranking.
ATR Percentile Ranking — Compares current ATR to its historical distribution to identify abnormally high volatility conditions.
Regime Definitions
Trend Up (Green) — ADX above trending threshold with DI+ > DI- and price above basis. Strong directional movement with bullish bias confirmed.
Trend Down (Red) — ADX above trending threshold with DI- > DI+ and price below basis. Strong directional movement with bearish bias confirmed.
Ranging (Yellow) — ADX below ranging threshold indicating sideways consolidation. Low directional strength suggests mean-reversion strategies may work better.
Volatile (Purple) — Both ATR percentile AND BB width percentile above the high volatility threshold. Indicates unstable, potentially dangerous conditions where normal strategies may fail.
The classification uses a priority system where high volatility conditions take precedence, followed by trend strength evaluation, with ranging as the default state for low-activity periods.
Regime Strength Calculation
Each regime has an associated strength score (0-100%) that indicates how firmly the market is in that state:
For trends: Based on ADX relative to threshold plus BB percentile
For ranging: Based on inverse ADX plus inverse BB percentile
For volatile: Based on ATR percentile
This helps identify when regime transitions may be approaching—declining strength often precedes regime changes.
Visual Features
Regime-Colored Bollinger Bands — Upper, basis, and lower bands all colored by current regime
Band Fill — 85% transparent fill between bands in regime color
Background Highlighting — Optional 90% transparent background in regime color
Regime Change Labels — On-chart markers when regime changes (arrows for trends, diamond for range, X for volatile)
Bar Coloring — Optional price bar coloring by regime
Color Scheme
Trend Up Color — Default: #00C853 (bright green)
Trend Down Color — Default: #FF1744 (bright red)
Range Color — Default: #FFD600 (yellow)
Volatile Color — Default: #AA00FF (purple)
Dashboard Information
The on-chart table (top-right corner) displays:
Current regime name with color coding
ADX value (highlighted if above trend threshold)
DI+ / DI- comparison with directional coloring
Bollinger Band width percentage
Volatility percentile (highlighted if above volatile threshold)
Regime strength percentage
Duration in bars since last regime change
Inputs Overview
Detection Settings:
ADX Length — Period for ADX/DI calculation (default: 14, range: 5-50)
BB Length — Period for Bollinger Bands (default: 20, range: 10-100)
BB Multiplier — Standard deviation multiplier (default: 2.0, range: 1.0-4.0)
ATR Length — Period for ATR calculation (default: 14, range: 5-50)
Thresholds:
Trending ADX Threshold — ADX level above which market is considered trending (default: 25, range: 15-50)
Ranging ADX Threshold — ADX level below which market is considered ranging (default: 20, range: 10-40)
High Volatility Percentile — Percentile above which volatile regime is triggered (default: 75, range: 50-95)
Visual Settings:
Trend Up/Down/Range/Volatile Colors — Fully customizable color scheme
Show Background — Toggle regime-colored background
Show Regime Bands — Toggle Bollinger Bands display
Show Dashboard — Toggle the information table
Color Price Bars — Toggle bar coloring by regime
How to Use It
Strategy Selection:
Trend Up/Down — Use trend-following strategies (breakouts, pullbacks, moving average systems)
Ranging — Use mean-reversion strategies (support/resistance bounces, oscillator extremes)
Volatile — Reduce position size, widen stops, or stay flat until conditions stabilize
For Regime Change Trading:
Watch for regime change labels as potential entry points
Trend regime starting often signals breakout opportunity
Ranging regime starting after trend may signal consolidation before continuation
Volatile regime is a warning to be cautious
For Risk Management:
Increase position size during strong trend regimes
Decrease position size during volatile or ranging regimes
Use regime strength to gauge conviction
Monitor duration—very long regimes may be due for change
Alerts Available
MRD Trend Up — Market regime changed to trending bullish
MRD Trend Down — Market regime changed to trending bearish
MRD Ranging — Market regime changed to sideways consolidation
MRD Volatile — Market regime changed to high volatility state
MRD Any Change — Notification on any regime transition
Best Practices
Don't fight the regime—adapt your strategy to current conditions
Volatile regime is a warning sign, not a trading signal
Use regime strength to gauge how established the current state is
Combine with other indicators appropriate for the detected regime
This indicator is provided for educational purposes. It does not constitute financial advice. Past performance does not guarantee future results. Always conduct your own analysis and use proper risk management before making trading decisions.
— Made with passion by officialjackofalltrades
SD-Range Oscillator | QuantEdgeBSD-Range Oscillator | QuantEdgeB
🔍 Overview
SD-Range Oscillator | QuantEdgeB (SDRO) is a normalized momentum oscillator that compresses a low-lag trend core into a 0–100 style range using standard-deviation (SD) bands. It builds a smooth baseline from a fast triple-smoothed average, wraps it with ±2×SD volatility bounds, then normalizes the core value inside that envelope. Clear Long/Short regimes trigger when the normalized value crosses user-defined thresholds, with optional labels, regime-colored candles, and intuitive filled zones.
✨ Key Features
1.⚡ Low-Lag Core (Triple-Smooth Engine)
- Uses a fast, low-lag triple-smoothed average as the oscillator’s primary signal input.
- Helps keep momentum readings responsive while filtering noise.
2. 📏 SD Volatility Envelope (±2×SD)
- Builds a volatility channel around a smoothed baseline using standard deviation.
- Automatically adapts to changing market turbulence.
3. 🧮 Normalized Range Output
- Converts the core signal into a normalized value by mapping it between the upper/lower SD bounds.
- Makes readings consistent across assets and timeframes.
4. 🎯 Threshold-Based Regimes
- Long when the normalized value exceeds the Long threshold.
- Short when it falls below the Short threshold.
- Includes an additional safety filter to reduce “forced” longs when price is already extended near the upper envelope.
5. 🎨 Visual Clarity & Zones
- Regime-colored oscillator line and candles.
- Filled SD bands around the baseline for quick volatility context.
- Optional highlight fills between the oscillator and thresholds to show active long/short phases.
- Extra OB/OS background zones for quick overextension awareness.
6. 🔔 Signals & Alerts
- Optional “Long/Short” labels on confirmed regime flips.
- Alert conditions fire on long/short regime crossovers.
💼 Use Cases
• Momentum Confirmation: Validate breakouts by requiring SDRO to hold above the Long threshold.
• Mean-Reversion Awareness: Watch for extreme normalized readings near upper/lower bounds.
• Regime Filtering: Use SDRO state (Long/Short/Neutral) to filter trades from other systems.
• Cross-Market Comparison: Normalization makes it easier to compare momentum across different tickers.
🎯 For Who
• Trend traders who want a clean momentum filter with adaptive volatility context.
• System builders needing a simple regime variable (1 / -1 / neutral) to gate entries.
• Discretionary traders who like visual confirmation (fills, candle coloring, threshold zones).
• Multi-asset traders who benefit from normalized, comparable oscillator readings.
⚙️ Default Settings
• TEMA Period: 7
• Base Length (SMMA): 25
• Long Threshold: 55
• Short Threshold: 45
• SD Multiplier: 2× (fixed in code)
• Color Mode: Alpha
• Color Transparency: 60
• Labels: Off by default
📌 Conclusion
SD-Range Oscillator | QuantEdgeB blends a low-lag triple-smoothed core with an adaptive SD envelope to produce a normalized, easy-to-read momentum signal. With clear threshold regimes, volatility-aware context, and strong visuals (fills + candle coloring), SDRO helps separate meaningful momentum shifts from noise across any asset or timeframe.
🔹 Disclaimer: Past performance is not indicative of future results. Always backtest and align settings with your risk tolerance and objectives before live trading.
🔹 Strategic Advice: Always backtest, optimize, and align parameters with your trading objectives and risk tolerance before live trading.
Momentum Echo Oscillator [Community Edition]Concept: The Momentum Echo Oscillator (MEO) is a modern take on classical momentum oscillators. Most indicators only look at the "now". MEO introduces the concept of Momentum Echoes—historical momentum harmonics that are weighted and blended back into the current price velocity.
Why use MEO? Standard momentum tools (like ROC or RSI) can be very "jittery" or noisy. By integrating historical echoes, MEO provides a smoother, more rhythmic representation of price flow, making it easier to spot genuine trend reversals.
Key Elements:
Primary Momentum: The immediate speed of price.
Echo Harmonics: Two adjustable lookback points that act as a "memory" for the indicator, filtering out false breakouts.
Dynamic Histogram: Visualizes the gap between the Echo Engine and the Trigger Line, highlighting acceleration and deceleration.
Settings:
Echo Weight: Adjust how much "memory" you want the indicator to have.
Smoothing: Clean up the signals for higher timeframes.
This is an open-source tool for the TradingView community. Enjoy!
TwinSmooth ATR Bands | QuantEdgeBTwinSmooth ATR Bands | QuantEdgeB
🔍 Overview
TwinSmooth ATR Bands | QuantEdgeB is a dual-smoothing, ATR-adaptive trend filter that blends two complementary smoothing engines into a single baseline, then builds dynamic ATR bands around it to detect decisive breakouts. When price closes above the upper band it triggers a Long regime; when it closes below the lower band it flips to Short—otherwise it stays neutral. The script enhances clarity with regime-colored candles, an active-band fill, and an optional on-chart backtest table.
✨ Key Features
1. 🧠 Twin-Smooth Baseline (Dual Engine Blend)
- Computes two separate smoothed baselines (a slower “smooth” leg + a faster “responsive” leg).
- Blends them into a single midpoint baseline for balanced stability + speed.
- Applies an extra EMA smoothing pass to produce a clean trend_base.
2. 📏 ATR Volatility Bands
- Builds upper/lower bands using ATR × multiplier around the trend_base.
- Bands expand in volatile conditions and contract when markets quiet down—auto-adapting without manual tweaks.
3. ⚡ Clear Breakout Regime Logic
- Long when close > upperBand.
- Short when close < lowerBand.
- Neutral otherwise (no forced signals inside the band zone).
4. 🎨 Visual Clarity
- Plots only the active band (lower band in long regime, upper band in short regime).
- Fills between active band and price for instant regime context.
- Colors candles to match the current state (bullish / bearish / neutral).
- Multiple color palettes + transparency control.
💼 Use Cases
• Trend Confirmation Filter: Use the regime as a higher-confidence trend gate for entries from other indicators.
• Breakout/Breakdown Trigger: Trade closes outside ATR bands to catch momentum expansions.
• Volatility-Aware Stops/Targets: Bands naturally reflect volatility, making them useful as adaptive reference levels.
• Multi-Timeframe Alignment: Confirm higher-timeframe regime before executing on lower timeframes.
🎯 For Who
• Trend Traders who want clean regime shifts without constant whipsaw.
• Breakout Traders who prefer confirmation via ATR expansion rather than raw MA crossovers.
• System Builders needing a simple, robust “state engine” (Long / Short / Neutral) to plug into larger strategies.
• Analysts who want quick on-chart validation with a backtest table.
⚙️ Default Settings
• SMMA Length (Base Smooth Leg): 24
• TEMA Length (Base Responsive Leg): 8
• EMA Extra Smoothing: 14
• ATR Length: 14
• ATR Multiplier: 1.1
• Color Mode: Alpha
• Color Transparency: 30
• Backtest Table: On (toggleable)
• Backtest Start Date: 09 Oct 2017
• Labels: Off by default
📌 Conclusion
TwinSmooth ATR Bands | QuantEdgeB merges a dual-speed smoothing core into a single trend baseline, then wraps it with ATR-based bands to deliver clean, volatility-adjusted breakout signals. With regime coloring, active-band plotting, and optional backtest stats, it’s a compact, readable tool for spotting momentum shifts and trend continuation across any market and timeframe.
🔹 Disclaimer: Past performance is not indicative of future results. Always backtest and align settings with your risk tolerance and objectives before live trading.
🔹 Strategic Advice: Always backtest, optimize, and align parameters with your trading objectives and risk tolerance before live trading.
