Low Volatility Profiles [BigBeluga]🔵 OVERVIEW
Low Volatility Profiles is a market compression and breakout-anticipation tool that identifies phases of low volatility using ADX and then builds a real-time volume profile inside the detected range.
This helps traders spot accumulation/distribution zones and prepare for explosive moves when volatility expands.
When volatility is low ➜ price coils ➜ volume organizes ➜ breakouts become highly actionable.
This tool visualizes that process with dynamic range boxes + volume bins + PoC extension.
🔵 CONCEPTS
Low-Volatility Detection — Uses ADX threshold & cross logic to define volatility contraction regimes.
Range Construction — Draws a price box that expands with highs/lows during the compression phase.
Micro Volume Profile — Builds a volume histogram inside the range using bins (micro volume nodes).
Delta Calculation — Tracks positive vs negative volume to gauge buyer/seller pressure within range.
Point of Control (PoC) — Highlights the price level with max traded volume inside the range.
PoC Extension — Optionally extends PoC into future bars to show potential reaction zone after breakout.
Breakout Validation — Ends the profile zone when price breaks above or below the modeled range.
Noise Removal — Automatically removes invalid or small ranges to prevent chart clutter.
This tool turns consolidation into actionable structure by exposing where smart money accumulates before trending moves.
🔵 FEATURES
ADX-Driven Range Detection — Identify when market transitions into low-volatility compression.
Configurable ADX Threshold — Set sensitivity for contraction zones.
Cross-Type Option — Detect low volatility via cross under / crossover logic.
Dynamic Range Box — Expands live with price as contraction unfolds.
Micro Volume Profile (Bins) — Distributes volume across bins inside range for micro POC mapping.
Volume Delta Visualization — Shows imbalance inside consolidation (accumulation vs distribution).
Real-Time PoC Highlight — Instantly shows most traded price inside the compression.
PoC Extension Mode — Extend PoC forward to project reaction levels post-breakout.
Clean Auto-Reset Logic — Removes boxes if range invalid or breakout occurs too fast.
Optional Filled Boxes — Heatmap-style profile visualization inside range body.
ADX Line + Threshold Plot — Visual assistance for volatility state monitoring.
🔵 HOW TO USE
Identify Accumulation Zones — When price enters low-volatility ADX condition and profile builds.
Watch the PoC — PoC acts as battle zone; move above/below can signal initiator strength.
Breakout Strategy — Trade break above/below the range after compression.
Mean Reversion Inside Range — Fade edges while price remains inside compression box.
Combine With Trend Tools — Use trend confirmation (MA/EMA/Flow indicators) after breakout.
Use Delta Clues — Positive delta tilt suggests accumulation; negative suggests distribution.
Monitor Range Size — Longer build + high PoC volume = stronger potential breakout energy.
🔵 CONCLUSION
Low Volatility Profiles isolates accumulation phases and maps volume concentration before volatility expansion.
By combining ADX compression, micro volume distribution, and PoC tracing, traders gain an edge in anticipating powerful breakout cycles and institutional positioning.
Trade the quiet moment before the storm — where smart money prepares the move, and the real opportunity emerges.
Volatilty
OTT Volatility [RunRox]📊 OTT Volatility is an indicator developed by the RunRox team to pinpoint the most optimal time to trade across different markets.
OTT stands for Optimal Trade Time Volatility and is designed primarily for markets without a fixed trading session, such as cryptocurrencies that trade 24/7. At the same time, it works equally well on any other market.
🔶 The concept is straightforward. The indicator takes a specified number of historical periods (Samples) and statistically evaluates which hours of the day or which days show the highest volatility for the selected asset.
As a result, it highlights time windows with elevated volatility where traders can focus on searching for trade setups and building positions.
🔶 As the core volatility metric, the indicator uses ATR (Average True Range) to measure intraday volatility. Then it calculates the average ATR value over the last N Samples, creating a statistically stable estimate of typical volatility for the selected asset.
🔶 Statistically, during these highlighted periods the market shows higher-than-average volatility.
This means that in these time windows price is more likely to be subject to stronger moves and potential manipulation, making them attractive for active trade execution and position management.
⚠️ However, historical behavior does not guarantee future results.
These periods should be treated only as zones where volatility has a higher probability of being above normal, not as a promise of movement.
As shown in the screenshot above, the indicator also projects potential future volatility based on historical data. This helps you better plan your trading hours and align your activity with periods where volatility is statistically expected to be higher or lower.
🔶 Current Volatility – as shown in the screenshot above, you can also monitor the real-time volatility of the market without any statistical averaging.
On top of that, you can overlay the current volatility on top of the statistical volatility levels, which makes it easy to see whether the market is now trading in a high- or low-volatility regime relative to its usual behavior.
4 display modes – you can choose any visualization style that fits your trading workflow:
Absolute – displays the raw volatility values.
Relative – shows volatility relative to its typical levels.
Average Centered – centers volatility around its average value.
Trim Low Value – filters out low-volatility noise and highlights only more significant moves.
This indicator helps you define the most effective trading hours on any market by relying on historical volatility statistics.
Use it to quickly see when your market tends to be more active and to structure your trading sessions around those periods.
✅ We hope this tool becomes a useful part of your trading toolkit and helps you improve the quality of your decisions and timing.
Liquidity Void Zone Detector [PhenLabs]📊 Liquidity Void Zone Detector
Version: PineScript™v6
📌 Description
The Liquidity Void Zone Detector is a sophisticated technical indicator designed to identify and visualize areas where price moved with abnormally low volume or rapid momentum, creating "voids" in market liquidity. These zones represent areas where insufficient trading activity occurred during price movement, often acting as magnets for future price action as the market seeks to fill these gaps.
Built on PineScript v6, this indicator employs a dual-detection methodology that analyzes both volume depletion patterns and price movement intensity relative to ATR. The revolutionary 3D visualization system uses three-layer polyline rendering with adaptive transparency and vertical offsets, creating genuine depth perception where low liquidity zones visually recede and high liquidity zones protrude forward. This makes critical market structure immediately apparent without cluttering your chart.
🚀 Points of Innovation
Dual detection algorithm combining volume threshold analysis and ATR-normalized price movement sensitivity for comprehensive void identification
Three-layer 3D visualization system with progressive transparency gradients (85%, 78%, 70%) and calculated vertical offsets for authentic depth perception
Intelligent state machine logic that tracks consecutive void bars and only renders zones meeting minimum qualification requirements
Dynamic strength scoring system (0-100 scale) that combines inverted volume ratios with movement intensity for accurate void characterization
Adaptive ATR-based spacing calculation that automatically adjusts 3D layering depth to match instrument volatility
Efficient memory management system supporting up to 100 simultaneous void visualizations with automatic array-based cleanup
🔧 Core Components
Volume Analysis Engine: Calculates rolling volume averages and compares current bar volume against dynamic thresholds to detect abnormally thin trading conditions
Price Movement Analyzer: Normalizes bar range against ATR to identify rapid price movements that indicate liquidity exhaustion regardless of instrument or timeframe
Void Tracking State Machine: Maintains persistent tracking of void start bars, price boundaries, consecutive bar counts, and cumulative strength across multiple bars
3D Polyline Renderer: Generates three-layer rectangular polylines with precise timestamp-to-bar index conversion and progressive offset calculations
Strength Calculation System: Combines volume component (inverted ratio capped at 100) with movement component (ATR intensity × 30) for comprehensive void scoring
🔥 Key Features
Automatic Void Detection: Continuously scans price action for low volume conditions or rapid movements, triggering void tracking when thresholds are exceeded
Real-Time Visualization: Creates 3D rectangular zones spanning from void initiation to termination, with color-coded depth indicating liquidity type
Adjustable Sensitivity: Configure volume threshold multiplier (0.1-2.0x), price movement sensitivity (0.5-5.0x), and minimum qualifying bars (1-10) for customized detection
Dual Color Coding: Separate visual treatment for low liquidity voids (receding red) and high liquidity zones (protruding green) based on 50-point strength threshold
Optional Compact Labels: Toggle LV (Low Volume) or HV (High Volume) circular labels at void centers for quick identification without visual clutter
Lookback Period Control: Adjust analysis window from 5 to 100 bars to match your trading timeframe and market volatility characteristics
Memory-Efficient Design: Automatically manages polyline and label arrays, deleting oldest elements when user-defined maximum is reached
Data Window Integration: Plots void detection binary, current strength score, and average volume for detailed analysis in TradingView's data window
🎨 Visualization
Three-Layer Depth System: Each void is rendered as three stacked polylines with progressive transparency (85%, 78%, 70%) and calculated vertical offsets creating authentic 3D appearance
Directional Depth Perception: Low liquidity zones recede with back layer most transparent; high liquidity zones protrude with front layer most transparent for instant visual differentiation
Adaptive Offset Spacing: Vertical separation between layers calculated as ATR(14) × 0.001, ensuring consistent 3D effect across different instruments and volatility regimes
Color Customization: Fully configurable base colors for both low liquidity zones (default: red with 80 transparency) and high liquidity zones (default: green with 80 transparency)
Minimal Chart Clutter: Closed polylines with matching line and fill colors create clean rectangular zones without unnecessary borders or visual noise
Background Highlight: Subtle yellow background (96% transparency) marks bars where void conditions are actively detected in real-time
Compact Labeling: Optional tiny circular labels with 60% transparent backgrounds positioned at void center points for quick reference
📖 Usage Guidelines
Detection Settings
Lookback Period: Default: 10 | Range: 5-100 | Number of bars analyzed for volume averaging and void detection. Lower values increase sensitivity to recent changes; higher values smooth detection across longer timeframes. Adjust based on your trading timeframe: short-term traders use 5-15, swing traders use 20-50, position traders use 50-100.
Volume Threshold: Default: 1.0 | Range: 0.1-2.0 (step 0.1) | Multiplier applied to average volume. Bars with volume below (average × threshold) trigger void conditions. Lower values detect only extreme volume depletion; higher values capture more moderate low-volume situations. Start with 1.0 and decrease to 0.5-0.7 for stricter detection.
Price Movement Sensitivity: Default: 1.5 | Range: 0.5-5.0 (step 0.1) | Multiplier for ATR-normalized price movement detection. Values above this threshold indicate rapid price changes suggesting liquidity voids. Increase to 2.0-3.0 for volatile instruments; decrease to 0.8-1.2 for ranging or low-volatility conditions.
Minimum Void Bars: Default: 10 | Range: 1-10 | Minimum consecutive bars exhibiting void conditions required before visualization is created. Filters out brief anomalies and ensures only sustained voids are displayed. Use 1-3 for scalping, 5-10 for intraday trading, 10+ for swing trading to match your time horizon.
Visual Settings
Low Liquidity Color: Default: Red (80% transparent) | Base color for zones where volume depletion or rapid movement indicates thin liquidity. These zones recede visually (back layer most transparent). Choose colors that contrast with your chart theme for optimal visibility.
High Liquidity Color: Default: Green (80% transparent) | Base color for zones with relatively higher liquidity compared to void threshold. These zones protrude visually (front layer most transparent). Ensure clear differentiation from low liquidity color.
Show Void Labels: Default: True | Toggle display of compact LV/HV labels at void centers. Disable for cleaner charts when trading; enable for analysis and review to quickly identify void types across your chart.
Max Visible Voids: Default: 50 | Range: 10-100 | Maximum number of void visualizations kept on chart. Each void uses 3 polylines, so setting of 50 maintains 150 total polylines. Higher values preserve more history but may impact performance on lower-end systems.
✅ Best Use Cases
Gap Fill Trading: Identify unfilled liquidity voids that price frequently returns to, providing high-probability retest and reversal opportunities when price approaches these zones
Breakout Validation: Distinguish genuine breakouts through established liquidity from false breaks into void zones that lack sustainable volume support
Support/Resistance Confluence: Layer void detection over key horizontal levels to validate structural integrity—levels within high liquidity zones are stronger than those in voids
Trend Continuation: Monitor for new void formation in trend direction as potential continuation zones where price may accelerate due to reduced resistance
Range Trading: Identify void zones within consolidation ranges that price tends to traverse quickly, helping to avoid getting caught in rapid moves through thin areas
Entry Timing: Wait for price to reach void boundaries rather than entering mid-void, as voids tend to be traversed quickly with limited profit-taking opportunities
⚠️ Limitations
Historical Pattern Indicator: Identifies past liquidity voids but cannot predict whether price will return to fill them or when filling might occur
No Volume on Forex: Indicator uses tick volume for forex pairs, which approximates but doesn't represent true trading volume, potentially affecting detection accuracy
Lagging Confirmation: Requires minimum consecutive bars (default 10) before void is visualized, meaning detection occurs after void formation begins
Trending Market Behavior: Strong trends driven by fundamental catalysts may create voids that remain unfilled for extended periods or permanently
Timeframe Dependency: Detection sensitivity varies significantly across timeframes; settings optimized for one timeframe may not perform well on others
No Directional Bias: Indicator identifies liquidity characteristics but provides no predictive signal for price direction after void detection
Performance Considerations: Higher max visible void settings combined with small minimum void bars can generate numerous visualizations impacting chart rendering speed
💡 What Makes This Unique
Industry-First 3D Visualization: Unlike flat volume or liquidity indicators, the three-layer rendering with directional depth perception provides instant visual hierarchy of liquidity quality
Dual-Mode Detection: Combines both volume-based and movement-based detection methodologies, capturing voids that single-approach indicators miss
Intelligent Qualification System: State machine logic prevents premature visualization by requiring sustained void conditions, reducing false signals and chart clutter
ATR-Normalized Analysis: All detection thresholds adapt to instrument volatility, ensuring consistent performance across stocks, forex, crypto, and futures without constant recalibration
Transparency-Based Depth: Uses progressive transparency gradients rather than colors or patterns to create depth, maintaining visual clarity while conveying information hierarchy
Comprehensive Strength Metrics: 0-100 void strength calculation considers both the degree of volume depletion and the magnitude of price movement for nuanced zone characterization
🔬 How It Works
Phase 1: Real-Time Detection
On each bar close, the indicator calculates average volume over the lookback period and compares current bar volume against the volume threshold multiplier
Simultaneously measures current bar's high-low range and normalizes it against ATR, comparing the result to price movement sensitivity parameter
If either volume falls below threshold OR movement exceeds sensitivity threshold, the bar is flagged as exhibiting void characteristics
Phase 2: Void Tracking & Qualification
When void conditions first appear, state machine initializes tracking variables: start bar index, initial top/bottom prices, consecutive bar counter, and cumulative strength accumulator
Each subsequent bar with void conditions extends the tracking, updating price boundaries to envelope all bars and accumulating strength scores
When void conditions cease, system checks if consecutive bar count meets minimum threshold; if yes, proceeds to visualization; if no, discards the tracking and resets
Phase 3: 3D Visualization Construction
Calculates average void strength by dividing cumulative strength by number of bars, then determines if void is low liquidity (>50 strength) or high liquidity (≤50 strength)
Generates three polyline layers spanning from start bar to end bar and from top price to bottom price, each with calculated vertical offset based on ATR
Applies progressive transparency (85%, 78%, 70%) with layer ordering creating recession effect for low liquidity zones and protrusion effect for high liquidity zones
Creates optional center label and pushes all visual elements into arrays for memory management
Phase 4: Memory Management & Display
Continuously monitors polyline array size (each void creates 3 polylines); when total exceeds max visible voids × 3, deletes oldest polylines via array.shift()
Similarly manages label array, removing oldest labels when count exceeds maximum to prevent memory accumulation over extended chart history
Plots diagnostic data to TradingView’s data window (void detection binary, current strength, average volume) for detailed analysis without cluttering main chart
💡 Note:
This indicator is designed to enhance your market structure analysis by revealing liquidity characteristics that aren’t visible through standard price and volume displays. For best results, combine void detection with your existing support/resistance analysis, trend identification, and risk management framework. Liquidity voids are descriptive of past market behavior and should inform positioning decisions rather than serve as standalone entry/exit signals. Experiment with detection parameters across different timeframes to find settings that align with your trading style and instrument characteristics.
Rons Custom WatermarkRon's Custom Watermark (RCW)
This is a lightweight, all-in-one watermark indicator that displays essential fundamental and technical data directly on your chart. It's designed to give you a quick, at-a-glance overview of any asset without cluttering your screen.
Features
The watermark displays the following information in a clean table:
* Company Info: Full Name & Market Cap (e.g., "AST SpaceMobile, Inc. (18.85B)")
* Symbol & Timeframe: Ticker and current chart period (e.g., "ASTS, 1D")
* Sector & Industry: The asset's classification.
* Technical Status (MA): Shows if the price is Above or Below the SMA (with a 🟢/🔴 emoji).
* Technical Status (EMA): Shows if the price is Above or Below the EMA (with a 🟢/🔴 emoji).
* Earnings: A countdown showing "X days remaining" until the next earnings report.
* (Optional) Volatility: The 14-day ATR value and its percentage of the current price.
DAO - Demand Advanced Oscillator# DAO - Demand Advanced Oscillator
## 📊 Overview
DAO (Demand Advanced Oscillator) is a powerful momentum oscillator that measures buying and selling pressure by analyzing consecutive high-low relationships. It helps identify market extremes, divergences, and potential trend reversals.
**Values range from 0 to 1:**
- **Above 0.70** = Overbought (potential reversal down)
- **Below 0.30** = Oversold (potential reversal up)
- **0.30 - 0.70** = Neutral zone
---
## ✨ Key Features
✅ **Automatic Divergence Detection**
- Bullish divergences (price lower low + DAO higher low)
- Bearish divergences (price higher high + DAO lower high)
- Visual lines connecting divergence points
✅ **Multi-Timeframe Analysis**
- View higher timeframe DAO on current chart
- Perfect for trend alignment strategies
✅ **Signal Line (EMA)**
- Customizable EMA for trend confirmation
- Crossover signals for momentum shifts
✅ **Real-Time Statistics Dashboard**
- Current DAO value
- Market status (Overbought/Oversold/Neutral)
- Trend direction indicator
✅ **Complete Alert System**
- Overbought/Oversold signals
- Bullish/Bearish divergences
- Signal line crosses
- Level crosses
✅ **Fully Customizable**
- Adjustable periods and levels
- Customizable colors and zones
- Toggle features on/off
---
## 📈 Trading Signals
### 1. Divergences (Most Powerful)
**Bullish Divergence:**
- Price makes lower low
- DAO makes higher low
- Signal: Strong reversal up likely
**Bearish Divergence:**
- Price makes higher high
- DAO makes lower high
- Signal: Strong reversal down likely
### 2. Overbought/Oversold
**Overbought (>0.70):**
- Market may be overextended
- Consider taking profits or looking for shorts
- Can remain overbought in strong trends
**Oversold (<0.30):**
- Market may be oversold
- Consider buying opportunities
- Can remain oversold in strong downtrends
### 3. Signal Line Crossovers
**Bullish Cross:**
- DAO crosses above signal line
- Momentum turning positive
**Bearish Cross:**
- DAO crosses below signal line
- Momentum turning negative
### 4. Level Crosses
**Cross Above 0.30:** Exiting oversold zone (potential uptrend)
**Cross Below 0.70:** Exiting overbought zone (potential downtrend)
---
## ⚙️ Default Settings
📊 Oscillator Period: 14
Number of bars for calculation
📈 Signal Line Period: 9
EMA period for signal line
🔴 Overbought Level: 0.70
Upper threshold
🟢 Oversold Level: 0.30
Lower threshold
🎯 Divergence Detection: ON
Auto divergence identification
⏰ Multi-Timeframe: OFF
Higher TF overlay (optional)
All parameters are fully customizable!
---
## 🔔 Alerts
Six pre-configured alerts available:
1. DAO Overbought
2. DAO Oversold
3. DAO Bullish Divergence
4. DAO Bearish Divergence
5. DAO Signal Cross Up
6. DAO Signal Cross Down
**Setup:** Right-click indicator → Add Alert → Choose condition
---
## 💡 How to Use
### Best Practices:
✅ Focus on divergences (strongest signals)
✅ Combine with support/resistance levels
✅ Use multiple timeframes for confirmation
✅ Wait for price action confirmation
✅ Practice proper risk management
### Avoid:
❌ Trading on indicator alone
❌ Fighting strong trends
❌ Ignoring market context
❌ Overtrading
### Recommended Settings by Trading Style:
**Day Trading:** Period 7-10, All alerts ON
**Swing Trading:** Period 14-21, Divergence alerts
**Scalping:** Period 5-7, Signal crosses
**Position Trading:** Period 21-30, Weekly/Daily TF
---
## 🌍 Markets & Timeframes
**Works on all markets:**
- Forex (all pairs)
- Stocks (all exchanges)
- Cryptocurrencies
- Commodities
- Indices
- Futures
**Works on all timeframes:** 1m to Monthly
---
## 📊 How It Works
DAO calculates the ratio of buying pressure to total market pressure:
1. **Calculate Buying Pressure (DemandMax):**
- If current high > previous high: DemandMax = difference
- Otherwise: DemandMax = 0
2. **Calculate Selling Pressure (DemandMin):**
- If previous low > current low: DemandMin = difference
- Otherwise: DemandMin = 0
3. **Apply Smoothing:**
- Calculate SMA of DemandMax over N periods
- Calculate SMA of DemandMin over N periods
4. **Final Formula:**
```
DAO = SMA(DemandMax) / (SMA(DemandMax) + SMA(DemandMin))
```
This produces a normalized value (0-1) representing market demand strength.
---
## 🎯 Trading Strategies
### Strategy 1: Divergence Trading
- Wait for divergence label
- Confirm at support/resistance
- Enter on confirming candle
- Stop loss beyond recent swing
- Target: opposite level or 0.50
### Strategy 2: Overbought/Oversold
- Best for ranging markets
- Wait for extreme readings
- Enter on reversal from extremes
- Target: middle line (0.50)
### Strategy 3: Trend Following
- Identify trend direction first
- Use DAO to time entries in trend direction only
- Enter on pullbacks to oversold (uptrend) or overbought (downtrend)
- Trade with the trend
### Strategy 4: Multi-Timeframe
- Enable MTF feature
- Trade only when both timeframes align
- Higher TF = trend direction
- Lower TF = precise entry
---
## 📂 Category
**Primary:** Oscillators
**Secondary:** Statistics, Volatility, Momentum
---
## 🏷️ Tags
dao, oscillator, momentum, overbought-oversold, divergence, reversal, demand-indicator, price-exhaustion, statistics, volatility, forex, stocks, crypto, multi-timeframe, technical-analysis
---
## ⚠️ Disclaimer
**This indicator is for educational purposes only.** It does not constitute financial advice. Trading involves substantial risk of loss. Always conduct your own research, use proper risk management, and consult with financial professionals before making trading decisions. Past performance does not guarantee future results.
---
## 📄 License
Open source - Free to use for personal trading, modify as needed, and share with attribution.
---
**Version:** 1.0
**Status:** Production Ready ✅
**Pine Script:** v5
**Trademark-Free:** 100% Safe to Publish
---
*Made with 💙 for traders worldwide*
Adaptive Momentum Pressure (AMP)🔹 Adaptive Momentum Pressure (AMP)
A hybrid momentum oscillator that adapts to volatility and trend dynamics.
AMP measures the rate of change of price pressure and automatically adjusts its sensitivity based on market volatility.
It reacts faster in trending markets and smooths out noise during consolidation — helping traders identify genuine momentum shifts early while avoiding whipsaws.
🧠 Core Concept
AMP fuses three elements into one adaptive momentum model:
Normalized Momentum (ROC) – captures directional acceleration of price.
Adaptive Smoothing – the smoothing length dynamically contracts when volatility rises and expands when it falls.
Directional Bias – derived from the short-term EMA slope to weight momentum toward the prevailing trend.
Combined, these form a pressure value oscillating between –100 and +100, revealing when momentum expands or fades.
⚙️ How It Works
Calculates a normalized rate of change (ROC) relative to recent volatility.
Adjusts its effective length using the ATR — more volatile periods shorten the lookback for quicker reaction.
Applies a custom EMA that adapts in real time.
Modulates momentum by a normalized EMA slope (“trend bias”).
Produces a smoothed AMP line with a Signal line and crossover markers.
🔍 How to Read It
Green AMP line rising above Signal → Building bullish momentum.
Red AMP line falling below Signal → Fading or bearish momentum.
White Signal line = smoothed confirmation of trend energy.
Green dots = early bullish crossovers.
Red dots = early bearish crossovers.
Typical interpretations:
AMP crossing above 0 from below → early bullish impulse.
AMP peaking near +50–100 and curling down → potential momentum exhaustion.
Crosses below 0 with red pressure → bearish confirmation.
⚡ Advantages
✅ Adaptive across all markets and timeframes
✅ Built-in trend bias filters false signals
✅ Reacts earlier than RSI/MACD while reducing noise
✅ No manual retuning required
🧩 Suggested Use
Combine with structure or volume tools to confirm breakouts.
Works well as a momentum confirmation filter for entries/exits.
Optimal display: separate oscillator pane (not overlay).
Use it responsibly — AMP is an analytical tool, not financial advice.
Stochastic + Bollinger Bands Multi-Timeframe StrategyThis strategy fuses the Stochastic Oscillator from the 4-hour timeframe with Bollinger Bands from the 1-hour timeframe, operating on a 10-hour chart to capture a unique volatility rhythm and temporal alignment discovered through observational alpha.
By blending momentum confirmation from the higher timeframe with short-term volatility extremes, the strategy leverages what some traders refer to as “rotating volatility” — a phenomenon where multi-timeframe oscillations sync to reveal hidden trade opportunities.
🧠 Strategy Logic
✅ Long Entry Condition:
Stochastic on the 4H timeframe:
%K crosses above %D
Both %K and %D are below 20 (oversold zone)
Bollinger Bands on the 1H timeframe:
Price crosses above the lower Bollinger Band, indicating a potential reversal
→ A long trade is opened when both momentum recovery and volatility reversion align.
✅ Long Exit Condition:
Stochastic on the 4H:
%K crosses below %D
Both %K and %D are above 80 (overbought zone)
Bollinger Bands on the 1H:
Price reaches or exceeds the upper Bollinger Band, suggesting exhaustion
→ The long trade is closed when either signal suggests a potential reversal or overextension.
🧬 Temporal Structure & Alpha
This strategy is deployed on a 10-hour chart — a non-standard timeframe that may align more effectively with multi-timeframe mean reversion dynamics.
This subtle adjustment exploits what some traders identify as “temporal drift” — the desynchronization of volatility across timeframes that creates hidden rhythm in price action.
→ For example, Stochastic on 4H (lookback 17) and Bollinger Bands on 1H (lookback 20) may periodically sync around 10H intervals, offering unique alpha windows.
📊 Indicator Components
🔹 Stochastic Oscillator (4H, Length 17)
Detects momentum reversals using %K and %D crossovers
Helps define overbought/oversold zones from a mid-term view
🔹 Bollinger Bands (1H, Length 20, ±2 StdDev)
Measures price volatility using standard deviation around a moving average
Entry occurs near lower band (support), exits near upper band (resistance)
🔹 Multi-Timeframe Logic
Uses request.security() to safely reference 4H and 1H indicators from a 10H chart
Avoids repainting by using closed higher-timeframe candles only
📈 Visualization
A plot selector input allows toggling between:
Stochastic Plot (%K & %D, with overbought/oversold levels)
Bollinger Bands Plot (Upper, Basis, Lower from 1H data)
This helps users visually confirm entry/exit triggers in real time.
🛠 Customization
Fully configurable Stochastic and BB settings
Timeframes are independently adjustable
Strategy settings like position sizing, slippage, and commission are editable
⚠️ Disclaimer
This strategy is intended for educational and informational purposes only.
It does not constitute financial advice or a recommendation to buy or sell any asset.
Market conditions vary, and past performance does not guarantee future results.
Always test any trading strategy in a simulated environment and consult a licensed financial advisor before making real-world investment decisions.
McMillan Volatility Bands (MVB) – with Entry Logic// McMillan Volatility Bands (MVB) with signal + entry logic
// Author: ChatGPT for OneRyanAlexander
// Notes:
// - Bands are computed using percentage volatility (log returns), per the Black‑Scholes framing.
// - Inner band (default 3σ) and outer band (default 4σ) are configurable.
// - A setup occurs when price closes outside the outer band, then closes back within the inner band.
// The bar that re‑enters is the "signal bar." We then require price to trade beyond the signal bar's
// extreme by a user‑defined cushion (default 0.34 * signal bar range) to confirm entry.
// - Includes alertconditions for both setups and confirmed entries.
Quantura - Trendchange ZonesIntroduction
“Quantura – Trendchange Zones” is an advanced technical indicator that identifies and visualizes potential market reversal zones using dynamic RSI-based logic. It highlights areas of overbought and oversold conditions, marking them as visual zones directly on the price chart, and generates corresponding bullish and bearish signals when the RSI exits these extremes. The tool helps traders anticipate possible trend change regions and confirm momentum shifts in a clean, intuitive way.
Originality & Value
Unlike traditional RSI indicators that only show a static oscillator, this tool transforms RSI behavior into on-chart visual zones that represent structural overbought and oversold phases. It converts RSI threshold breaches into price-based regions (boxes) and marks reversal signals at the moment of momentum change.
The indicator’s originality and usefulness come from its:
Direct visualization of RSI overbought and oversold areas as dynamic chart zones.
Automatic detection of potential reversal regions where momentum exhaustion is likely.
Integration of RSI-based signals and visual cues without requiring users to monitor the RSI window.
Adjustable sensitivity for RSI length and upper/lower levels.
Clear color-coded separation of bullish and bearish phases.
Functionality & Core Logic
The indicator continuously monitors RSI values relative to the user-defined thresholds.
When RSI moves above the upper level, an Overbought Zone is created and extends until RSI falls back below that threshold.
When RSI moves below the lower level, an Oversold Zone is generated and extends until RSI returns above that level.
When RSI exits one of these zones, a corresponding Trendchange Signal (▲ bullish or ▼ bearish) appears at the transition point.
Each zone dynamically adjusts its high and low levels during formation, representing the complete range of the exhaustion phase.
Parameters & Customization
RSI Length: Defines the sensitivity of RSI calculation. Shorter lengths make signals more responsive; longer lengths filter noise.
Upper Level / Lower Level: Set thresholds for overbought and oversold conditions (default 70 / 30).
Signals: Toggle on/off for displaying bullish (▲) and bearish (▼) reversal signals.
Zones: Toggle the visualization of shaded RSI-based zones.
Colors: Fully customizable bullish and bearish colors for both signals and zones.
Visualization & Display
Bullish reversal zones (oversold exits) are shaded using the chosen bullish color (default: blue).
Bearish reversal zones (overbought exits) are shaded using the chosen bearish color (default: red).
Each completed zone is outlined and filled with transparent shading for better clarity.
Reversal arrows (▲ for bullish, ▼ for bearish) are displayed at the bar where RSI exits the extreme level.
Clean overlay design ensures compatibility with any chart style or color scheme.
Use Cases
Identify overbought and oversold periods directly on the price chart without switching to the RSI window.
Anticipate potential market reversals or exhaustion points based on RSI momentum shifts.
Combine with trend indicators, moving averages, or volume tools for confirmation.
Apply across multiple timeframes to align short-term reversal signals with higher timeframe momentum.
Use zone width and duration to assess the strength and persistence of overbought/oversold conditions.
Limitations & Recommendations
The indicator is not a standalone trading system but a visual confirmation tool.
False signals may occur in strongly trending markets where RSI remains overextended.
Optimal RSI settings may differ between assets (e.g., crypto vs. equities).
Combining this indicator with additional trend or structure filters can enhance accuracy.
Markets & Timeframes
The “Quantura – Trendchange Zones” indicator works across all markets and timeframes, including cryptocurrencies, Forex, stocks, and commodities. It is suitable for both short-term scalping and long-term swing analysis.
Author & Access
Developed 100% by Quantura. Published as a Open-source script indicator. Access is free.
Important
This description complies with TradingView’s Script Publishing and House Rules. It provides a clear explanation of the indicator’s originality, logic, and function while avoiding unrealistic performance or predictive claims.
Zero Lag Trend Signals (MTF) [Quant Trading] V7Overview
The Zero Lag Trend Signals (MTF) V7 is a comprehensive trend-following strategy that combines Zero Lag Exponential Moving Average (ZLEMA) with volatility-based bands to identify high-probability trade entries and exits. This strategy is designed to reduce lag inherent in traditional moving averages while incorporating dynamic risk management through ATR-based stops and multiple exit mechanisms.
This is a longer term horizon strategy that takes limited trades. It is not a high frequency trading and therefore will also have limited data and not > 100 trades.
How It Works
Core Signal Generation:
The strategy uses a Zero Lag EMA (ZLEMA) calculated by applying an EMA to price data that has been adjusted for lag:
Calculate lag period: floor((length - 1) / 2)
Apply lag correction: src + (src - src )
Calculate ZLEMA: EMA of lag-corrected price
Volatility bands are created using the highest ATR over a lookback period multiplied by a band multiplier. These bands are added to and subtracted from the ZLEMA line to create upper and lower boundaries.
Trend Detection:
The strategy maintains a trend variable that switches between bullish (1) and bearish (-1):
Long Signal: Triggers when price crosses above ZLEMA + volatility band
Short Signal: Triggers when price crosses below ZLEMA - volatility band
Optional ZLEMA Trend Confirmation:
When enabled, this filter requires ZLEMA to show directional momentum before entry:
Bullish Confirmation: ZLEMA must increase for 4 consecutive bars
Bearish Confirmation: ZLEMA must decrease for 4 consecutive bars
This additional filter helps avoid false signals in choppy or ranging markets.
Risk Management Features:
The strategy includes multiple stop-loss and take-profit mechanisms:
Volatility-Based Stops: Default stop-loss is placed at ZLEMA ± volatility band
ATR-Based Stops: Dynamic stop-loss calculated as entry price ± (ATR × multiplier)
ATR Trailing Stop: Ratcheting stop-loss that follows price but never moves against position
Risk-Reward Profit Target: Take-profit level set as a multiple of stop distance
Break-Even Stop: Moves stop to entry price after reaching specified R:R ratio
Trend-Based Exit: Closes position when price crosses EMA in opposite direction
Performance Tracking:
The strategy includes optional features for monitoring and analyzing trades:
Floating Statistics Table: Displays key metrics including win rate, GOA (Gain on Account), net P&L, and max drawdown
Trade Log Labels: Shows entry/exit prices, P&L, bars held, and exit reason for each closed trade
CSV Export Fields: Outputs trade data for external analysis
Default Strategy Settings
Commission & Slippage:
Commission: 0.1% per trade
Slippage: 3 ticks
Initial Capital: $1,000
Position Size: 100% of equity per trade
Main Calculation Parameters:
Length: 70 (range: 70-7000) - Controls ZLEMA calculation period
Band Multiplier: 1.2 - Adjusts width of volatility bands
Entry Conditions (All Disabled by Default):
Use ZLEMA Trend Confirmation: OFF - Requires ZLEMA directional momentum
Re-Enter on Long Trend: OFF - Allows multiple entries during sustained trends
Short Trades:
Allow Short Trades: OFF - Strategy is long-only by default
Performance Settings (All Disabled by Default):
Use Profit Target: OFF
Profit Target Risk-Reward Ratio: 2.0 (when enabled)
Dynamic TP/SL (All Disabled by Default):
Use ATR-Based Stop-Loss & Take-Profit: OFF
ATR Length: 14
Stop-Loss ATR Multiplier: 1.5
Profit Target ATR Multiplier: 2.5
Use ATR Trailing Stop: OFF
Trailing Stop ATR Multiplier: 1.5
Use Break-Even Stop-Loss: OFF
Move SL to Break-Even After RR: 1.5
Use Trend-Based Take Profit: OFF
EMA Exit Length: 9
Trade Data Display (All Disabled by Default):
Show Floating Stats Table: OFF
Show Trade Log Labels: OFF
Enable CSV Export: OFF
Trade Label Vertical Offset: 0.5
Backtesting Date Range:
Start Date: January 1, 2018
End Date: December 31, 2069
Important Usage Notes
Default Configuration: The strategy operates in its most basic form with default settings - using only ZLEMA crossovers with volatility bands and volatility-based stop-losses. All advanced features must be manually enabled.
Stop-Loss Priority: If multiple stop-loss methods are enabled simultaneously, the strategy will use whichever condition is hit first. ATR-based stops override volatility-based stops when enabled.
Long-Only by Default: Short trading is disabled by default. Enable "Allow Short Trades" to trade both directions.
Performance Monitoring: Enable the floating stats table and trade log labels to visualize strategy performance during backtesting.
Exit Mechanisms: The strategy can exit trades through multiple methods: stop-loss hit, take-profit reached, trend reversal, or trailing stop activation. The trade log identifies which exit method was used.
Re-Entry Logic: When "Re-Enter on Long Trend" is enabled with ZLEMA trend confirmation, the strategy can take multiple long positions during extended uptrends as long as all entry conditions remain valid.
Capital Efficiency: Default setting uses 100% of equity per trade. Adjust "default_qty_value" to manage position sizing based on risk tolerance.
Realistic Backtesting: Strategy includes commission (0.1%) and slippage (3 ticks) to provide realistic performance expectations. These values should be adjusted based on your broker and market conditions.
Recommended Use Cases
Trending Markets: Best suited for markets with clear directional moves where trend-following strategies excel
Medium to Long-Term Trading: The default length of 70 makes this strategy more appropriate for swing trading rather than scalping
Risk-Conscious Traders: Multiple stop-loss options allow traders to customize risk management to their comfort level
Backtesting & Optimization: Comprehensive performance tracking features make this strategy ideal for testing different parameter combinations
Limitations & Considerations
Like all trend-following strategies, performance may suffer in choppy or ranging markets
Default 100% position sizing means full capital exposure per trade - consider reducing for conservative risk management
Higher length values (70+) reduce signal frequency but may improve signal quality
Multiple simultaneous risk management features may create conflicting exit signals
Past performance shown in backtests does not guarantee future results
Customization Tips
For more aggressive trading:
Reduce length parameter (minimum 70)
Decrease band multiplier for tighter bands
Enable short trades
Use lower profit target R:R ratios
For more conservative trading:
Increase length parameter
Enable ZLEMA trend confirmation
Use wider ATR stop-loss multipliers
Enable break-even stop-loss
Reduce position size from 100% default
For optimal choppy market performance:
Enable ZLEMA trend confirmation
Increase band multiplier
Use tighter profit targets
Avoid re-entry on trend continuation
Visual Elements
The strategy plots several elements on the chart:
ZLEMA line (color-coded by trend direction)
Upper and lower volatility bands
Long entry markers (green triangles)
Short entry markers (red triangles, when enabled)
Stop-loss levels (when positions are open)
Take-profit levels (when enabled and positions are open)
Trailing stop lines (when enabled and positions are open)
Optional ZLEMA trend markers (triangles at highs/lows)
Optional trade log labels showing complete trade information
Exit Reason Codes (for CSV Export)
When CSV export is enabled, exit reasons are coded as:
0 = Manual/Other
1 = Trailing Stop-Loss
2 = Profit Target
3 = ATR Stop-Loss
4 = Trend Change
Conclusion
Zero Lag Trend Signals V7 provides a robust framework for trend-following with extensive customization options. The strategy balances simplicity in its core logic with sophisticated risk management features, making it suitable for both beginner and advanced traders. By reducing moving average lag while incorporating volatility-based signals, it aims to capture trends earlier while managing risk through multiple configurable exit mechanisms.
The modular design allows traders to start with basic trend-following and progressively add complexity through ZLEMA confirmation, multiple stop-loss methods, and advanced exit strategies. Comprehensive performance tracking and export capabilities make this strategy an excellent tool for systematic testing and optimization.
Note: This strategy is provided for educational and backtesting purposes. All trading involves risk. Past performance does not guarantee future results. Always test thoroughly with paper trading before risking real capital, and adjust position sizing and risk parameters according to your risk tolerance and account size.
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TAGS:
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trend following, ZLEMA, zero lag, volatility bands, ATR stops, risk management, swing trading, momentum, trend confirmation, backtesting
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CATEGORY:
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Strategies
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CHART SETUP RECOMMENDATIONS:
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For optimal visualization when publishing:
Use a clean chart with no other indicators overlaid
Select a timeframe that shows multiple trade signals (4H or Daily recommended)
Choose a trending asset (crypto, forex major pairs, or trending stocks work well)
Show at least 6-12 months of data to demonstrate strategy across different market conditions
Enable the floating stats table to display key performance metrics
Ensure all indicator lines (ZLEMA, bands, stops) are clearly visible
Use the default chart type (candlesticks) - avoid Heikin Ashi, Renko, etc.
Make sure symbol information and timeframe are clearly visible
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COMPLIANCE NOTES:
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✅ Open-source publication with complete code visibility
✅ English-only title and description
✅ Detailed explanation of methodology and calculations
✅ Realistic commission (0.1%) and slippage (3 ticks) included
✅ All default parameters clearly documented
✅ Performance limitations and risks disclosed
✅ No unrealistic claims about performance
✅ No guaranteed results promised
✅ Appropriate for public library (original trend-following implementation with ZLEMA)
✅ Educational disclaimers included
✅ All features explained in detail
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[Kpt-Ahab] Assistant: Risk & DCA PlannerScript Description – Assistant: Risk & DCA Planner
The Risk & DCA Planner is a technical assistant for position and risk management.
It automatically calculates, based on volatility (ATR%), swing structure, and your settings:
Stop-Loss (SL) and corresponding Take-Profit targets (TPs) in R-multiples
DCA (Dollar-Cost-Averaging) levels — both price and amount
A market suitability check (based on volatility & volume)
Plus a clear table and summary label displayed on the chart
The script helps you plan risk, scaling, and profit targets consistently and quantitatively.
Core Logic
Risk Profile
Three modes: Low, Normal, High.
These define how reactive the script behaves internally:
Low → conservative, longer lookbacks, tighter analysis
Normal → balanced
High → aggressive, faster reaction, wider stops
Stop-Loss (SL)
Automatically calculated from ATR% and recent swing structure, limited by minimum and maximum thresholds.
The SL percentage defines the R-unit, which all TPs and DCA levels are based on.
Take-Profits (TPs)
Up to six targets, each a multiple of the defined risk (e.g., 1R, 2R, 3R).
Prices are automatically adjusted depending on long or short direction.
DCA Strategy
Optional. Adds scaling levels evenly between Entry and SL or in multiples of the ATR.
Each DCA allocation grows geometrically until the maximum position size is reached.
Suitability Check
Evaluates whether the market is within an appropriate ATR% range and has sufficient volume.
The table displays “OK” or “Caution” depending on volatility and historical consistency.
Visualization
Lines for SL, TPs, and DCA levels
A table with all parameters, prices, and risk data
A chart label summarizing key info (profile, direction, SL%, TPs, DCA, etc.)
Renko BandsThis is renko without the candles, just the endpoint plotted as a line with bands around it that represent the brick size. The idea came from thinking about what renko actually gives you once you strip away the visual brick format. At its core, renko is a filtered price series that only updates when price moves a fixed amount, which means it's inherently a trend-following mechanism with built-in noise reduction. By plotting just the renko price level and surrounding it with bands at the brick threshold distances, you get something that works like regular volatility bands while still behaving as a trend indicator.
The center line is the current renko price, which trails actual price based on whichever brick sizing method you've selected. When price moves enough to complete a brick in the renko calculation, the center line jumps to the new brick level. The bands sit at plus and minus one brick size from that center line, showing you exactly how far price needs to move before the next brick would form. This makes the bands function as dynamic breakout levels. When price touches or crosses a band, you know a new renko brick is forming and the trend calculation is updating.
What makes this cool is the dual-purpose nature. You can use it like traditional volatility bands where the outer edges represent boundaries of normal price movement, and breaks beyond those boundaries signal potential trend continuation or exhaustion. But because the underlying calculation is renko rather than standard deviation or ATR around a moving average, the bands also give you direct insight into trend state. When the center line is rising consistently and price stays near the upper band, you're in a clean uptrend. When it's falling and price hugs the lower band, downtrend. When the center line is flat and price is bouncing between both bands, you're ranging.
The three brick sizing methods work the same way as standard renko implementations. Traditional sizing uses a fixed price range, so your bands are always the same absolute distance from the center line. ATR-based sizing calculates brick range from historical volatility, which makes the bands expand and contract based on the ATR measurement you chose at startup. Percentage-based sizing scales the brick size with price level, so the bands naturally widen as price increases and narrow as it decreases. This automatic scaling is particularly useful for instruments that move proportionally rather than in fixed increments.
The visual simplicity compared to full renko bricks makes this more practical for overlay use on your main chart. Instead of trying to read brick patterns in a separate pane or cluttering your price chart with boxes and lines, you get a single smoothed line with two bands that convey the same information about trend state and momentum. The center line shows you the filtered trend direction, the bands show you the threshold levels, and the relationship between price and the bands tells you whether the current move has legs or is stalling out.
From a trend-following perspective, the renko line naturally stays flat during consolidation and only moves when directional momentum is strong enough to complete bricks. This built-in filter removes a lot of the whipsaw that affects moving averages during choppy periods. Traditional moving averages continue updating with every bar regardless of whether meaningful directional movement is happening, which leads to false signals when price is just oscillating. The renko line only responds to sustained moves that meet the brick size threshold, so it tends to stay quiet when price is going nowhere and only signals when something is actually happening.
The bands also serve as natural stop-loss or profit-target references since they represent the distance price needs to move before the trend calculation changes. If you're long and the renko line is rising, you might place stops below the lower band on the theory that if price falls far enough to reverse the renko trend, your thesis is probably invalidated. Conversely, the upper band can mark levels where you'd expect the current brick to complete and potentially see some consolidation or pullback before the next brick forms.
What this really highlights is that renko's value isn't just in the brick visualization, it's in the underlying filtering mechanism. By extracting that mechanism and presenting it in a more traditional band format, you get access to renko's trend-following properties without needing to commit to the brick chart aesthetic or deal with the complications of overlaying brick drawings on a time-based chart. It's renko after all, so you get the trend filtering and directional clarity that makes renko useful, but packaged in a way that integrates more naturally with standard technical analysis workflows.
MACD-V Adaptive FluxProMACD-V Adaptive FluxPro
Type: Multi-Factor Volatility-Normalized Momentum & Regime Framework
Overlay: ✅ Yes (on price chart)
Purpose: Detect high-probability trend continuation or reversal zones through volatility-adjusted momentum, VWAP structure, and adaptive filters.
🧩 Concept Overview
MACD-V Adaptive FluxPro is a next-generation, multi-factor analytical framework that merges the principles of Linda Raschke’s 3-10-16 MACD with modern volatility normalization and adaptive filtering.
Instead of generating raw buy/sell signals, it builds a probability-driven environment model — showing when price action, volatility, and structure align for high-confidence trades.
The “V” in MACD-V stands for Volatility Normalization: every MACD component is divided by ATR to stabilize amplitude across fast or slow markets.
This enables the indicator to remain consistent across timeframes, instruments, and volatility regimes.
⚙️ Core Components
1️⃣ Volatility-Normalized MACD (MACD-V)
A traditional MACD built on Linda Raschke’s 3-10-16 structure, but adjusted by ATR to create a volatility-invariant momentum profile.
You can toggle to alternative presets (Scalp / Swing / Trend) for faster or slower environments.
2️⃣ Dynamic Regime Detection
A slope-based classifier that identifies whether the market is:
Trend Up 🟢
Trend Down 🔴
Compression / Squeeze 🟧
Transition / Neutral ⚫
The background color updates dynamically as momentum, volatility, and slope shift between these states.
3️⃣ VWAP Structure Bands
Adaptive VWAP with inner and outer ATR-scaled envelopes.
These act as short-term mean-reversion and breakout zones.
The indicator can optionally gate entries to occur only within defined VWAP proximity.
4️⃣ EMAs for Micro-Trend Confirmation
Includes 9-EMA and 21-EMA, color-configurable for visual crossovers and short-term momentum bias.
5️⃣ Multi-Timeframe Confirmation Tiles
Top-center dashboard tiles display directional bias from higher timeframes (e.g., 15m / 1h / 4h).
When all align, it confirms multi-frame trend coherence.
6️⃣ Adaptive Probability Engine
All subsystems — MACD-V, slope, compression, volume z-score, and VWAP distance — feed into a logistic scoring model that outputs a real-time AOI Probability (0-100%).
When conditions align, probabilities rise above 60% (long bias) or drop below 40% (short bias).
These are your high-probability “Areas of Interest.”
7️⃣ Dashboard HUD
The top-right status console provides a one-glance view of system state:
Field Meaning
AOI Prob Long Real-time probability of bullish bias
Regime Market state (Trend, Transition, Compression)
Risk Gate ATR-based volatility filter
News Mute Manual toggle for event-risk suppression
ATR (≈ risk) Real-time volatility readout
Status ✅ Trading OK / 🧱 Risk Gate / 🔇 News Mute / 🟧 Compression
🎯 Interpretation Guide
Visual Meaning
🟢 Green background Confirmed uptrend regime
🔴 Red background Confirmed downtrend regime
🟧 Orange background Volatility compression (squeeze forming)
⚫ Gray background Transitional / indecisive structure
Teal % (AOI Prob Long) Bullish probability > 60%
Arrows Optional: appear only when all gates align (rare, filtered signals)
🧮 Mathematical Notes
MACD-V = (EMA_fast(src) − EMA_slow(src)) / ATR(n)
Normalized score is smoothed, scaled 0–100 via logistic curve
Slope = Δ(EMA(src, n)) / ATR(n)
Probabilities gated by:
Minimum slope magnitude (minAbsSlope)
VWAP proximity (maxVWAPDistATR)
Multi-TF agreement
Cooldown interval (cooldownBars)
ATR-based risk gate
No repainting — all calculations use barstate.isconfirmed.
⚡ Use Cases
✅ Identify trend regime changes before major expansions
✅ Filter breakout vs. compression setups
✅ Quantify volatility conditions before entries
✅ Confirm multi-timeframe alignment
✅ Serve as a visual regime map for automated systems or discretionary traders
🧠 Recommended Presets
Market Type Setting Preset Behavior
Index Futures (ES/NQ) LBR 3-10-16 SMA (default) Classic swing/momentum balance
Scalping (1m–5m) Fast Adaptive Higher frequency, shorter cooldown
Swing Trading (1h–4h) Smooth ATR Broader, trend-only signals
Trend-Following Futures Wide ATR Bands Filters noise, favors strong continuation
⚠️ Notes
Non-repainting, bar-confirmed calculations
Signal arrows are optional and rare — intended for precision setups
ATR and slope thresholds should be tuned per instrument
Compatible with all TradingView markets and resolutions
🏁 Summary
“MACD-V Adaptive FluxPro” is not a simple MACD — it’s a volatility-normalized market state engine that adapts to changing conditions.
It fuses Linda Raschke’s timeless MACD logic with modern volatility, slope, and multi-timeframe analytics — giving you a live market dashboard that tells you when not to trade just as clearly as when you should.
Adaptive Vol Gauge [ParadoxAlgo]This is an overlay tool that measures and shows market ups and downs (volatility) based on daily high and low prices. It adjusts automatically to recent price changes and highlights calm or wild market periods. It colors the chart background and bars in shades of blue to cyan, with optional small labels for changes in market mood. Use it for info only—combine with your own analysis and risk controls. It's not a buy/sell signal or promise of results.Key FeaturesSmart Volatility Measure: Tracks price swings with a flexible time window that reacts to market speed.
Market Mood Detection: Spots high-energy (wild) or low-energy (calm) phases to help see shifts.
Visual Style: Uses smooth color fades on the background and bars—cyan for calm, deep blue for wild—to blend nicely on your chart.
Custom Options: Change settings like time periods, sensitivity, colors, and labels.
Chart Fit: Sits right on your main price chart without extra lines, keeping things clean.
How It WorksThe tool figures out volatility like this:Adjustment Factor:Looks at recent price ranges compared to longer ones.
Tweaks the time window (between 10-50 bars) based on how fast prices are moving.
Volatility Calc:Adds up logs of high/low ranges over the adjusted window.
Takes the square root for the final value.
Can scale it to yearly terms for easy comparison across chart timeframes.
Mood Check:Compares current volatility to its recent average and spread.
Flags "high" if above your set level, "low" if below.
Neutral in between.
This setup makes it quicker in busy markets and steadier in quiet ones.Settings You Can ChangeAdjust in the tool's menu:Base Time Window (default: 20): Starting point for calculations. Bigger numbers smooth things out but might miss quick changes.
Adjustment Strength (default: 0.5): How much it reacts to price speed. Low = steady; high = quick changes.
Yearly Scaling (default: on): Makes values comparable across short or long charts. Turn off for raw numbers.
Mood Sensitivity (default: 1.0): How strict for calling high/low moods. Low = more shifts; high = only big ones.
Show Labels (default: on): Adds tiny "High Vol" or "Low Vol" tags when moods change. They point up or down from bars.
Background Fade (default: 80): How see-through the color fill is (0 = invisible, 100 = solid).
Bar Fade (default: 50): How much color blends into your candles or bars (0 = none, 100 = full).
How to Read and Use ItColor Shifts:Background and bars fade based on mood strength:Cyan shades mean calm markets (good for steady, back-and-forth trades).
Deep blue shades mean wild markets (watch for big moves or turns).
Smooth changes show volatility building or easing.
Labels:"High Vol" (deep blue, from below bar): Start of wild phase.
"Low Vol" (cyan, from above bar): Start of calm phase.
Only shows at changes to avoid clutter. Use for timing strategy tweaks.
Trading Ideas:Mood-Based Plays: In wild phases (deep blue), try chase-momentum or breakout trades since swings are bigger. In calm phases (cyan), stick to bounce-back or range trades.
Risk Tips: Cut trade sizes in wild times to handle bigger losses. Use calm times for longer holds with close stops.
Chart Time Tips: Turn on yearly scaling for matching short and long views. Test settings on past data—loosen for quick trades (more alerts), tighten for longer ones (fewer, stronger).
Mix with Others: Add trend lines or averages—buy in calm up-moves, sell in wild down-moves. Check with volume or key levels too.
Special Cases: In big news events, it reacts faster. On slow assets, it might overstate swings—ease the adjustment strength.
Limits and TipsIt looks back at past data, so it trails real-time action and can't predict ahead.
Results differ by stock or timeframe—test on history first.
Colors and tags are just visuals; set your own alerts if needed.
Follows TradingView rules: No win promises, for learning only. Open for sharing; share thoughts in forums.
With this, you can spot market energy and tweak your trades smarter. Start on practice charts.
Bollinger Band ToolkitBollinger Band Toolkit
An advanced, adaptive Bollinger Band system for traders who want more context, precision, and edge.
This indicator expands on the classic Bollinger Bands by combining statistical and volatility-based methods with modern divergence and squeeze detection tools. It helps identify volatility regimes, potential breakouts, and early momentum shifts — all within one clean overlay.
🔹 Core Features
1. Adaptive Bollinger Bands (σ + ATR)
Classic 20-period bands enhanced with an ATR-based volatility adjustment, making them more responsive to true market movement rather than just price variance.
Reduces “overreacting” during chop and avoids bands collapsing too tightly during trends.
2. %B & RSI Divergence Detection
🟢 Green dots: Positive %B divergence — price makes a lower low, but %B doesn’t confirm (bullish).
🔴 Red dots: Negative %B divergence — price makes a higher high, but %B doesn’t confirm (bearish).
✚ Red/green crosses: RSI divergence confirmation — momentum fails to confirm the price’s new extreme.
These signals highlight potential reversal or slowdown zones that are often invisible to the naked eye.
3. Bollinger Band Squeeze (with Volume Filter)
Yellow squares (■) show periods when Bollinger Bands are at their narrowest relative to recent history.
Volume confirmation ensures the squeeze only triggers when both volatility and participation contract.
Often marks the “calm before the storm” — breakout potential zones.
4. Multi-Timeframe Breakout Markers
Optionally displays breakouts from higher or lower timeframes using different colors/symbols.
Lets you see when a higher timeframe band break aligns with your current chart — a strong trend continuation signal.
5. Dual- and Triple-Band Visualization (±1σ, ±2σ, ±3σ)
Optional inner (±1σ) and outer (±3σ) bands provide a layered volatility map:
Price holding between ±1σ → stable range / mean-reverting behavior
Price riding near ±2σ → trending phase, sustained momentum
Price touching or exceeding ±3σ → volatility expansion or exhaustion zone
This triple-band layout visually distinguishes normal movement from statistical extremes, helping you read when the market is balanced, expanding, or approaching its limits.
⚙️ Inputs & Customization
Choose band type (SMA/EMA/SMMA/WMA/VWMA)
Adjust deviation multiplier (σ) and ATR multiplier
Toggle individual features (divergence dots, squeeze markers, inner bands, etc.)
Multi-timeframe and colour controls for advanced users
🧠 How to Use
Watch for squeeze markers followed by a breakout bar beyond ±2σ → volatility expansion signal.
Combine divergence dots with RSI or price structure to anticipate slowdowns or reversals.
Confirm direction using multi-timeframe breakouts and volume expansion.
💬 Why It Works
This toolkit transforms qualitative chart reading (tight bands, hidden divergence) into quantitative, testable conditions — giving you objective insights that can be backtested, coded, or simply trusted in live setups.
1m Scalping ATR (with SL & Zones)A universal ATR indicator that anchors volatility to your stop-loss.
Read any market (FX, JPY pairs, Gold/Silver, indices, crypto) consistently—regardless of pip/point conventions and timeframe.
Why this indicator?
Classic ATR is absolute (pips/points) and feels different across markets/TFs. ATR Takeoff normalizes ATR to your stop-loss in pips and highlights clear zones for “quiet / ideal / too volatile,” so you instantly know if a 10-pip SL fits current conditions.
Key features
Auto pip detection (FX, JPY, XAU/XAG, indices, BTC/ETH).
Selectable ATR source: chart timeframe or fixed ATR TF (e.g., “15”, “30”, “60”).
Display modes:
Percent of SL – ATR relative to SL in %, great for M1 (typical 10–30%).
Multiple of SL – ATR as a multiple of SL (e.g., 0.6× / 1.0× / 1.2×).
Panel zones:
Green = “Ready for takeoff” (≤ Low), Yellow = reference (Mid), Red = too volatile (≥ High).
Status badge (top-right): Quiet / ATR ok / Wild, current ATR/SL value, ATR TF used.
Direction-agnostic: Works the same for longs and shorts.
Inputs (at a glance)
Length / Smoothing (RMA/SMA/EMA/WMA): ATR base settings.
Your Stop-Loss (Pips): Reference SL (e.g., 10).
ATR Timeframe (empty = chart): Use chart TF or a fixed TF.
Display Mode: “Percent of SL” or “Multiple of SL.”
Low/Mid/High (Percent Mode): Zone thresholds in % of SL.
Low/Mid/High (Multiple Mode): Zone thresholds in ×SL.
Recommended defaults
Length 14, Smoothing RMA, SL 10 pips
Display Mode: Percent of SL
Low/Mid/High (%): 15 / 20 / 25
ATR Timeframe: empty (= chart) for reactive, or “30” for smoother M30 context with M1 entries.
How to use
Set SL (pips). 2) Choose display mode. 3) Optionally pick ATR TF.
Interpretation:
≤ Low (green): setups allowed.
≈ Mid (yellow): neutral reference.
≥ High (red): too volatile → adjust SL/size or wait.
Note: Auto-pip relies on common ticker naming; verify on exotic symbols.
Disclaimer: For research/education. Not financial advice.
Risk Recommender — (Heatmap)📊 Risk Recommender — Per-Trade & Annualized (Heatmap Columns)
Estimate the optimal risk percentage for any market regime.
This tool dynamically recommends how much of your account equity to risk — either per trade or at a portfolio (annualized) level — using volatility as the guide.
⚙️ How it works
Two distinct modes give you flexibility:
1️⃣ Per-Trade (ATR-based)
• Calculates the current Average True Range (ATR) compared to its long-term baseline.
• When volatility is high (ATR ↑), risk per trade decreases to maintain constant dollar risk.
• When volatility is low (ATR ↓), risk per trade increases within your defined floor and ceiling.
• The display is normalized by stop distance (× ATR) and smoothed to avoid noise.
2️⃣ Annualized (Volatility Targeting)
• Computes realized volatility (standard deviation of log returns) and an EWMA forecast of future volatility.
• Blends current and forecast volatilities to estimate “effective” volatility.
• Scales your base risk so that portfolio volatility converges toward your chosen annual target (e.g., 20%).
• Useful for portfolio-level or systematic strategies that maintain constant volatility exposure.
🎨 Heatmap Visualization
The vertical column graph acts like a thermometer:
• 🟥 Red → “Reduce risk” (volatility high).
• 🟩 Green → “Increase risk” (volatility low).
• Smoothed and bounded between your Floor and Ceiling risk levels.
• Optional dotted guides mark those bounds.
• Label shows the current mode, recommended risk %, and key metrics (ATR ratio or effective volatility).
🔧 Key Inputs
• Base max risk per trade (%) — your normal per-trade risk budget.
• ATR length / Baseline ATR length — control sensitivity to short- vs. long-term volatility.
• Target annualized volatility (%) — portfolio volatility target for quant mode.
• λ (lambda) — smoothing factor for the EWMA volatility forecast (0.90–0.99 typical).
• Floor & Ceiling — clamps the output to avoid extreme sizing.
• Smoothing & Hysteresis — prevent rapid changes in risk recommendations.
🧮 Interpreting the Output
• “Recommended Risk (%)” = suggested portion of equity to risk on the next trade (or current exposure).
• In Per-Trade mode: reflects current ATR ÷ baseline ATR .
• In Annualized mode: reflects target volatility ÷ effective volatility .
• Use the color and height of the column as a quick visual cue for aggressiveness.
💡 Typical Use Cases
• Position-sizing overlay for discretionary traders.
• Volatility-targeting component for algorithmic or multi-asset systems.
• Educational tool to understand how volatility governs prudent risk management.
📘 Notes
• This indicator provides risk suggestions only ; it does not place trades.
• Works on any symbol or timeframe.
• Combine with your own strategy or alerts for full automation.
• All calculations use built-in Pine functions; no proprietary logic.
Tags:
#RiskManagement #ATR #Volatility #Quant #PositionSizing #SystematicTrading #AlgorithmicTrading #Portfolio #TradingStrategy #Heatmap #EWMA #Risk
Market Pressure Differential (MPD) [SharpStrat]Market Pressure Differential (MPD)
Concept & Purpose
The Market Pressure Differential (MPD) is a proprietary indicator designed to measure the internal balance of buying and selling pressure directly on the price chart.
Unlike standard momentum or trend indicators, MPD analyzes the structural behavior of each candle—its body, wicks, and overall range—to determine whether the market is dominated by expansion (buying aggression) or contraction (selling absorption).
This indicator provides a visual overlay of market pressure that adapts dynamically to volatility, helping traders see real-time shifts in participation intensity without using oscillators.
In simple terms:
When MPD expands upward → buyer pressure dominates.
When MPD contracts downward → seller pressure dominates.
Calculation Overview
MPD uses a structural candle formula to compute directional pressure:
Body Ratio = (Close − Open) / (High − Low)
Wick Differential = (Lower Wick − Upper Wick) / (High − Low)
Raw Pressure = (Body Ratio × Body Weight) + (Wick Differential × Wick Weight)
Then it applies:
EMA smoothing (to stabilize short-term noise)
Standard deviation normalization (to maintain consistent scaling)
ATR projection (to adapt the signal visually to volatility)
This produces the MPD projection line and the pressure ribbon, drawn directly on the main chart.
Customizable Inputs
Users can adjust color schemes, EMA smoothing length, ATR parameters, normalization length, and body/wick weighting to adapt the indicator’s sensitivity and aesthetic to different markets or chart themes.
How to Use
The Market Pressure Differential (MPD) visualizes the real-time balance between buying and selling pressure. It should be used as a contextual bias tool, not a standalone signal generator.
The white line represents the MPD projection, showing how market pressure evolves in real time based on candle structure and volatility.
The red line represents the ATR envelope, which defines the market’s expected volatility range.
MPD reacts quickly to candle structure, so trend bias is based on how its projection behaves relative to the ATR envelope:
Above the ATR band → positive pressure and bullish bias.
Below the ATR band → negative pressure and bearish bias.
Hovering near the ATR band → neutral or indecisive conditions.
The MPD percentage in the label represents the normalized strength of pressure relative to recent volatility.
Positive % = buying dominance.
Negative % = selling dominance.
Higher absolute values = stronger momentum compared to volatility.
To trade with MPD:
Watch candle colors and the projection line — green or positive % shows buyer control, red or negative % shows seller control.
Note transitions above or below the ATR level for early signs of momentum shifts.
Combine MPD signals with price structure, key levels, or volume for confirmation.
This helps reveal which side controls the market and whether that pressure is strong enough to overcome typical volatility.
Disclaimer
It introduces a novel structural–pressure approach to visualizing market dynamics.
For educational and analytical purposes only; this does not constitute financial advice.
Ichimoku Cloud Indicator [TradingFinder] Kinko Hyo Cross Alerts🔵 Introduction
The Ichimoku Cloud (Ichimoku Kinko Hyo) is one of the most powerful and complete trading indicators in technical analysis. Originally developed by Japanese journalist Goichi Hosoda, the Ichimoku system combines multiple tools in one indicator, providing traders with instant insights into trend direction, support and resistance levels, and momentum. Unlike simple moving averages (SMA – Simple Moving Average), the Ichimoku Cloud (Kumo – Cloud) integrates dynamic elements that help traders forecast potential price action with greater clarity.
The Ichimoku Indicator (Ichimoku Signal System) is widely used across global markets, from Forex trading (FX – Foreign Exchange) to stocks, indices, and even cryptocurrencies. Its popularity comes from its ability to generate clear buy signals and sell signals based on the interaction of its components: Tenkan Sen (Conversion Line), Kijun Sen (Base Line), Senkou Span A, Senkou Span B, and Chikou Span (Lagging Line). When combined, these lines create the Ichimoku Cloud, which visually represents the balance between price action and market structure.
Ichimoku Cloud Lines Formulas :
Conversion Line (Tenkan Sen / Conversion Line) : Average of the highest high and lowest low over the past 9 periods => (9-PH + 9-PL) ÷ 2
Base Line (Kijun Sen / Base Line) : Average of the highest high and lowest low over the past 26 periods => (26-PH + 26-PL) ÷ 2
Leading Span A (Senkou Span A / Leading Span A) : Average of the Conversion Line and Base Line, plotted 26 periods ahead => (Tenkan Sen + Kijun Sen) ÷ 2
Leading Span B (Senkou Span B / Leading Span B) : Average of the highest high and lowest low over the past 52 periods, plotted 26 periods ahead => (52-PH + 52-PL) ÷ 2
Lagging Span (Chikou Span / Lagging Span) : Current closing price, plotted 26 periods behind.
One of the biggest advantages of the Ichimoku Trading Strategy (Ichimoku Cloud Trading System) is that it allows traders to identify the market condition at a glance. When the price is above the Kumo (Cloud), it indicates a bullish trend (uptrend). When the price is below the Kumo, the market is in a bearish trend (downtrend). And when the price is inside the cloud, the market is ranging (sideways trend). This simplicity and visual clarity make Ichimoku an essential indicator for both beginner traders and professional analysts.
The Ichimoku Cloud Indicator (Ichimoku Technical Analysis Tool) continues to be one of the most reliable charting methods. Traders often consider it superior to basic moving averages (MA – Moving Average) or exponential moving averages (EMA – Exponential Moving Average), because it not only shows trend direction but also highlights potential future support and resistance levels. With its unique combination of trend analysis, price forecasting, and trading signals, Ichimoku remains a core strategy in modern trading systems.
🔵 How to Use
The Ichimoku Cloud is more than just a set of lines; it’s a complete trading system that helps traders identify trends, momentum, and key support and resistance levels. By combining its five lines Conversion Line, Base Line, Leading Span A, Leading Span B, and Lagging Span traders can develop clear buy and sell strategies.
🟣 Identifying Trend Direction
Bullish Trend (Uptrend) : Price is above the cloud (Kumo), and the cloud is green. Leading Span A is above Leading Span B, signaling strong upward momentum.
Bearish Trend (Downtrend) : Price is below the cloud, and the cloud is red. Leading Span A is below Leading Span B, confirming a downward momentum.
Ranging / Sideways Market : Price is inside the cloud, indicating indecision and consolidation. Traders often avoid opening strong positions during these periods.
🟣 Buy Strategies
Conversion/Base Line Crossover : A buy signal occurs when the Conversion Line (Tenkan Sen) crosses above the Base Line (Kijun Sen). The signal is strongest when this crossover happens above the cloud.
Price Above Base Line : If the price moves above the Base Line while in an uptrend, it confirms bullish momentum and provides a favorable entry point.
Cloud Support Pullback : During a pullback in an uptrend, the price may touch or slightly enter the cloud. Traders can use the cloud as a dynamic support zone for buying opportunities.
Lagging Span Confirmation : Ensure the Lagging Span (Chikou Span) is above the price of 26 periods ago to confirm the strength of the bullish trend.
🟣 Sell Strategies
Conversion/Base Line Crossover : A sell signal is generated when the Conversion Line (Tenkan Sen) crosses below the Base Line (Kijun Sen). This signal is strongest when it occurs below the cloud.
Price Below Base Line : If the price falls below the Base Line in a downtrend, it confirms bearish momentum and strengthens the sell setup.
Cloud Resistance Pullback : During a bounce in a downtrend, the cloud acts as a resistance zone. Traders can enter sell positions when price approaches or touches the cloud from below.
Lagging Span Confirmation : The Lagging Span should be below the price of 26 periods ago, confirming downward momentum.
🟣 Cloud Breakout Signals
A strong buy occurs when the price breaks above the cloud from below, signaling a potential trend reversal.
A strong sell occurs when the price breaks below the cloud from above, indicating a shift toward a bearish trend.
🟣 Combining Signals for Stronger Entries
For higher probability trades, combine multiple signals : trend direction (cloud color and position), crossovers (Tenkan/Kijun), and Lagging Span position.
Avoid trading against the overall trend. For example, avoid buying when price is below a red cloud or selling when price is above a green cloud.
🔵 Setting
Tenkan Sen Period : Lookback period for Conversion Line (default: 9).
Kijun Sen Period : Lookback period for Base Line (default: 26).
Span B Period : Lookback period for Leading Span B, forms one Cloud boundary (default: 52).
Shift Lines : Periods forward for Cloud / backward for Lagging Span (default: 26).
Cross Tenkan/Kijun Alert : Alert on Conversion/Base Line crossover.
Cross Price/Tenkan Alert : Alert when price crosses Tenkan Sen.
Cross Price/Kijun Alert : Alert when price crosses Kijun Sen
🔵 Conclusion
The Ichimoku Cloud (Ichimoku Kinko Hyo) is much more than a simple indicator it is a complete trading system that combines trend detection, momentum analysis, and support/resistance identification in one view. By interpreting the position of price relative to the cloud, the interaction between Tenkan Sen (Conversion Line) and Kijun Sen (Base Line), the leading spans (Senkou Span A and B), and the Chikou Span (Lagging Line), traders can identify potential buy and sell opportunities with higher confidence.
The main advantage of the Ichimoku Cloud is its ability to provide a “one-look equilibrium” snapshot of the market. It highlights bullish trends when the price is above the cloud, bearish conditions when the price is below it, and indecision or transition when the price is inside the cloud. Crossovers, cloud breakouts, and confirmations by the Chikou Span strengthen the trading signals.
However, traders should keep in mind the limitations of the Ichimoku system. It is based on historical data and should not be used in isolation. Combining it with other tools such as RSI, volume analysis, or candlestick patterns can significantly improve accuracy and reduce false signals.
ATR Volatility and Trend AnalysisATR Volatility and Trend Analysis
Unlock the power of the Average True Range (ATR) with the ATR Volatility and Trend Analysis indicator. This comprehensive tool is designed to provide traders with a multi-faceted view of market dynamics, combining volatility analysis, dynamic support and resistance levels, and trend detection into a single, easy-to-use indicator.
How It Works
The ATR Volatility and Trend Analysis indicator is built upon the core concept of the ATR, a classic measure of market volatility. It expands on this by providing several key features:
Dynamic ATR Bands: The indicator plots three sets of upper and lower bands around the price. These bands are calculated by multiplying the current ATR value by user-defined multipliers. They act as dynamic support and resistance levels, widening during volatile periods and contracting during calm markets.
Volatility Breakout Signals: Identify potential breakouts with precision. The indicator generates a signal when the current ATR value surges above its own moving average by a specified threshold, indicating a significant increase in volatility that could lead to a strong price move.
Trend Detection: The indicator determines the market trend by analyzing both price action and ATR behavior. A bullish trend is signaled when the price is above its moving average and volatility is increasing. Conversely, a bearish trend is signaled when the price is below its moving average and volatility is increasing.
How to Use the ATR Multi-Band Indicator
Identify Support and Resistance: Use the ATR bands as key levels. Price approaching the outer bands may indicate overbought or oversold conditions, while a break of the bands can signal a strong continuation.
Confirm Breakouts: Look for a volatility breakout signal to confirm the strength behind a price move. A breakout from a consolidation range accompanied by a volatility signal is a strong indicator of a new trend.
Trade with the Trend: Use the background coloring and trend signals to align your trades with the dominant market direction. Enter long positions during confirmed bullish trends and short positions during bearish trends.
Set Up Alerts: The indicator includes alerts for band crosses, trend changes, and volatility breakouts, ensuring you never miss a potential trading opportunity.
What makes it different?
While many indicators use ATR, the ATR Volatility and Trend Analysis tool is unique in its integration of multiple ATR-based concepts into a single, cohesive system. It doesn't just show volatility; it interprets it in the context of price action to deliver actionable trend and breakout signals, making it a complete solution for ATR-based analysis.
Disclaimer
This indicator is designed as a technical analysis tool and should be used in conjunction with other forms of analysis and proper risk management.
Past performance does not guarantee future results, and traders should thoroughly test any strategy before implementing it with real capital.
Bollinger Keltner Squeeze Indicator (BBKC)Bollinger Keltner Squeeze Indicator (BBKC)This single-pane indicator combines the power of Bollinger Bands (BB) and Keltner Channels (KC) to accurately identify periods of low volatility compression—the famous Squeeze—which often precedes large, directional moves.Designed for traders utilizing Accumulation, Manipulation, Distribution (AMD) strategies, this tool makes spotting the 'Accumulation' phase simple and visually clear, perfect for high BTC Beta equities or futures markets like MES and MNQ.Key Features:Clear Squeeze Visualization:The background of the main chart is shaded Orange when the Squeeze is active (BB is inside KC). This immediately highlights periods of extreme compression.A simple Red/Green Dot below the chart confirms the Squeeze state (Red = Squeeze ON, Green = Squeeze OFF).Momentum Histogram:A built-in momentum oscillator smooths price action and guides the anticipated direction of the breakout.Teal/Orange Bars: Indicate momentum direction while the Squeeze is active (building pressure).Bright Green/Red Bars: Indicate momentum direction after the Squeeze has broken (expansion/breakout).How to Find Maximum Volatility Compression (The "Tightest" Squeeze)To align this indicator with a strategy focused on catching only the most extreme volatility compression—the key to those explosive moves—traders should adjust the Keltner Channel Multiplier setting.Setting Name: KC Multiplier (ATR)Default Value: 1.5Recommended Adjustment: To filter for only the absolute tightest squeezes (where price is least volatile), decrease this multiplier value, typically down to 1.25 or even 1.0.By lowering the KC Multiplier (ATR), you narrow the Keltner Channel boundaries. This requires the Bollinger Bands to compress even further to fit inside, ensuring the indicator only signals the Squeeze state during moments of truly minimal volatility, setting you up for maximum opportunity.
⚪ Liquidity Spike Marker
Description:
The Liquidity Spike Marker indicator helps to identify abnormal bursts of liquidity in the market. The logic is based on comparing the product of the volume by the minimum candle price (Volume × Low) with the threshold value set by the user.
When the value exceeds the threshold, a white triangle appears under the candle, indicating a possible influx of liquidity. This can help traders pay attention to the key points where large participants may enter the market.
Features:
Displays a placemark (⚪ white triangle) when the threshold is exceeded.
Configurable parameter Volume × Low Threshold.
The ability to set an alert for automatic notification.
A lightweight and minimalistic tool without unnecessary elements.
Note: The indicator is not a trading recommendation. Use it in combination with your own trading system and other analysis methods.
Multi Straddle-Strangle ChartThis powerful indicator is designed for options traders who want to visualize and track the combined premium of multiple straddle and strangle strategies in a single, dedicated pane.
Quickly analyze and compare up to five different options strategies at a glance, directly on your chart. This tool is perfect for monitoring volatility, tracking potential profits/losses on a position, and spotting key support and resistance levels based on option premiums.
Key Features:
Plot Up to 5 Strategies: Simultaneously plot any combination of up to 5 straddles or strangles.
Real-Time Data: Fetches live data for both Call and Put options to give you an up-to-the-second view of the combined price.
Dynamic Symbol Generation: Automatically detects the underlying symbol (e.g., NIFTY, BANKNIFTY, stocks) and builds the correct option symbols based on your input.
Customizable Inputs: Easily configure the expiry date, strike prices and line colors for each of the 5 lines.
In-Chart Summary Table: A clean and clear table in the corner of your chart provides a quick summary of each enabled strategy and its current price.
Important Note on Usage:
This tool requires you to input a strike price in all fields, even if you do not plan to use all five lines. This is necessary because of a fundamental rule in the Pine Script language: every input must have a constant, non-empty default value. The indicator is optimized to only fetch data for the lines you have explicitly enabled with the "Enable Line X" checkbox.
