Trend Breakout Description:
This Pine Script indicator identifies pivot high and pivot low points based on user-defined left and right candle legs, detecting breakouts to signal potential trend changes. It plots horizontal lines at pivot highs (lime) and pivot lows (red), marking breakout signals with labels ("Br") when the price crosses above a pivot high or below a pivot low. The indicator also changes the background color to reflect the trend (green for uptrend, red for downtrend) with adjustable transparency. The indicator primarily focuses on recognizing specific pivot patterns to define trends and generate trading signals.
How It Works
• Pivot Detection: Identifies pivot highs and lows using configurable left (Left side Pivot Candle) and right (Right side Pivot Candle) periods.
• Pivot Highs (PH): A pivot high is identified when a candle's high is greater than a specified number of preceding candles (left leg) and succeeding candles (right leg).
• Pivot Lows (PL): Similarly, a pivot low is identified when a candle's low is less than a specified number of preceding and succeeding candles.
The script then tracks the last three pivot highs and pivot lows.
Trend Detection and Breakouts
1. High Line (Resistance): When a middle pivot high (out of the three tracked) is higher than both the previous and the next pivot high, a lime green line is drawn from that pivot high. This line acts as a dynamic resistance level.
2. Low Line (Support): Conversely, when a middle pivot low is lower than both the previous and the next pivot low, a red line is drawn from that pivot low. This line acts as a dynamic support level.
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Trading Signals : The indicator generates signals based on price crossing these dynamically drawn lines .
• Long Signal (Uptrend):
o A "Long" signal is triggered when the close price crosses above the current high line (resistance), and the indicator is not already in an uptrend.
o When a long signal occurs, the background turns green, and the high line becomes dotted and thinner. A "Br" (Breakout) label appears below the candle.
• Short Signal (Downtrend):
o A "Short" signal is triggered when the close price crosses below the current low line (support), and the indicator is not already in a downtrend.
o When a short signal occurs, the background turns red, and the low line becomes dotted and thinner. A "Br" (Breakout) label appears above the candle.
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Customizable Settings
The indicator provides three user-adjustable inputs:
• Right Side Pivot Candle (fpivotLeg): This setting (default 10) determines the number of candles to the right that must have lower highs/higher lows for a pivot to be confirmed.
• Left Side Pivot Candle (bpivotLeg): This setting (default 15) determines the number of candles to the left that must have lower highs/higher lows for a pivot to be confirmed.
• Adjust Color Visualization (Colortrnp): This setting (default 85) controls the transparency of the background color changes, allowing you to adjust how prominently the green (uptrend) and red (downtrend) backgrounds are displayed.
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How to Use It
This indicator can be used by traders to:
• Identify potential reversals: The formation of new pivot highs and lows can signal shifts in market direction.
• Spot breakout opportunities: Crossing above the high line or below the low line can indicate the start of a new trend or the continuation of an existing one.
• Confirm trend strength: The presence and extension of the high and low lines can provide visual cues about the prevailing trend.
• Ideal for swing traders or trend-following strategies.
• Use the breakout labels ("Br") and background color to confirm trend direction.
• Adjust pivot leg inputs to fine-tune sensitivity for different timeframes or assets.
• Customize transparency to suit chart readability.
Example:
On a breakout above a pivot high, a green "Br" label appears, the background turns green, and the pivot line becomes dotted. This signals a potential uptrend, helping traders identify entry points or trend confirmations.
Disclaimer: No indicator guarantees profits. Always use this indicator in conjunction with other analysis methods and proper risk management.
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Angled Gann Time-Price Squares with S/RThis is a Pine Script indicator that implements Angled Gann Time-Price Squares based on W.D. Gann's trading theory. Here's what it does:
Core Functionality
Detects pivot highs and lows using a configurable lookback period
Creates angled squares by connecting pivot points to current price action when specific geometric conditions are met
Validates square formation by checking if the price movement follows proper Gann angles (typically 45°, 135°, etc.) within a tolerance range
Key Features
Real-time square tracking: Shows both completed squares and forming squares in progress
Support/Resistance levels: Automatically generates S/R lines from:
Square edge extensions
Diagonal extensions (pivot centers)
Quarter/half levels within squares (25%, 50%, 75%)
Visual feedback: Color-coded squares (green for up, red for down, orange for forming)
Projection lines: Predicts where squares might complete based on Gann angle theory
Gann Theory Application
The indicator follows Gann's principle that time and price move in geometric harmony. It looks for price movements that form perfect squares when plotted on a chart, where the diagonal of the square represents the natural flow of price and time at specific angles.
The generated support/resistance levels are particularly valuable because they're based on completed geometric patterns rather than just horizontal price levels, making them potentially more significant according to Gann methodology.
Max Value Gap [MOT]📊 Max Value Gap — Intraday Fill Zones + Stats Dashboard
Max Value Gap is a real-time gap fill detection system that visualizes institutional-style intraday price inefficiencies on major indices like SPX and NDX. Built for scalpers and short-term traders, it helps identify prime reversal areas where price is likely to return — often within the same session.
This script tracks U.S. regular market hour gaps only (9:30 AM to 4:00 PM ET) and is designed for high-precision execution on the 1-minute chart.
🧠 What Is an SPX Intraday Gap?
An SPX intraday gap occurs when the market creates a void between candles due to rapid price movement — often following volatility spikes, liquidation breaks, or aggressive buyer/seller imbalances. These unfilled zones act like magnetic targets, drawing price back into them as liquidity rebalances.
Unlike overnight gaps, these are formed and resolved within the same session, making them ideal for intraday strategies.
🔍 Key Features
✅ 1. Automatic Gap Detection
Scans only during official U.S. equity market hours (9:30 AM – 4:00 PM EST)
Gap Up: A green candle opens above the previous high
Gap Down: A red candle opens below the previous low
Each valid gap is outlined using colored boxes:
🟩 Green Box = Gap Up
🟥 Red Box = Gap Down
📸 Image : Chart with both green and red boxes marking gaps on SPX.
✅ 2. Dynamic Gap Zone Tracking
Once a gap is identified, the box extends forward until price fills the zone
A gap is considered filled when:
Price trades back into the gap zone
For gap ups: price crosses below the bottom of the gap
For gap downs: price crosses above the top of the gap
Users have the option to auto-delete filled boxes for clarity
📸 Image: Chart with price re-entering and completing a gap fill with box extending only until that point.
✅ 3. Real-Time Statistics Table
Located in the bottom-right of your chart, the built-in dashboard shows:
Total gaps formed
Gaps filled intraday
Gaps filled same day
Percentages of successful fills
📸 Image: Picture of statistics table
This live table helps assess whether the current day’s gaps are behaving in line with historical probabilities — no guesswork required.
🔄 Futures Execution Strategy
While the gaps are plotted on the SPX (or index) chart, the actual trades are taken on MNQ, NQ, or ES, using the gap levels as entry targets.
Sample Trading Flow:
A gap down forms on SPX at 1:45 PM (EST)
Price starts showing reversal signs back toward the gap
Enter long MNQ or NQ targeting a move into the gap zone
Take profit once price fully fills the zone
Repeat throughout the session — trend or chop, gaps are a magnet
This method mirrors institutional mean reversion techniques, capitalizing on market inefficiencies without chasing momentum.
📸 SPX Gap Being Filled with Corresponding MNQ Move Overlay
✅ Best Practices
Works best during morning session volatility (9:30–11:30 AM ET)
Combine with reversal candles or momentum tools for high-quality entries
Avoid during low-volume lunch chop unless tracking larger gap zones
Use on SPX while executing trades on MNQ/NQ/ES
⚠️ Disclaimer
This script is provided for educational and informational purposes only. It does not offer investment advice or trade signals. Past performance does not guarantee future results. Use appropriate risk management. Redistribution or resale is strictly prohibited.
Supply & Demand MTF[E7T]This is not your average supply and demand tool. it’s a powerful, flexible indicator that helps traders spot high-probability opportunities by adapting to real-time market conditions. It uses a smart combination of volatility (ATR), volume, and price action to identify key zones where the market is likely to react. Perfect for scalpers and swing traders alike, this strategy brings together adaptive zone detection, trend bias (pivot line), two-tiered signals (S1 and S2), volume filtering, built-in Fibonacci targets, and even a debug mode for transparency and performance tracking.
KEY FEATURES
1. ADAPTIVE ZONE DETECTION; This feature highlights areas where price is likely to bounce or reversebullish demand zones and bearish supply zones. Instead of using fixed levels, it adjusts based on market volatility.
HOW IT WORKS:
Uses Average True Range (ATR) to measure volatility.
TWO MODES:
Low Volatility Mode: Makes zones tighter for calm markets.
High Volatility Mode: Expands zones during choppy or fast-moving conditions.
Plots red boxes for supply zones and blue for demand zones. Zones extend until broken or naturally expire.
WHY IT MATTERS: Traditional zone indicators often fall short in fast-changing conditions. This one adjusts automatically, helping you stay one step ahead.
EXAMPLE: On a 4H BTCUSD chart, a demand zone will form at a key support level and adjust its size depending on whether the market is quiet or volatile.
2. MARKET BIAS PIVOT LINE; This dynamic line helps you quickly see whether the market is trending up or down so you can trade in the direction of strength.
HOW IT WORKS:
Based on recent swing highs and lows (default: last 4 bars).
Line is green when price is above (bullish), red when below (bearish).
Updates live and can be turned on/off in settings.
WHY IT MATTERS: It’s a built-in trend filter. Use it to avoid fighting the market.
EXAMPLE: If SPY is above a green pivot and enters a demand zone, it’s a solid bullish setup.
3. DUAL ENTRY SIGNALS (S1 and S2) The strategy gives you two signal types depending on your risk style:
S1 SIGNALS: Early entry, based on basic confirmation (like a bullish engulfing pattern).
S2 SIGNALS: Stronger entry, requiring solid candle confirmation, volume spike, and close near the zone.
HOW IT WORKS:
S1 = good for aggressive traders or small size entries.
S2 = better for high-conviction trades and bigger position sizes.
Both signals follow your selected market mood (bullish or bearish).
WHY IT MATTERS: Flexibility! Most indicators only offer one signal style. This one gives you choice.
EXAMPLE: In EURUSD, S1 might show up when price taps a demand zone and forms a small bullish candle. If volume increases and the next candle closes strong, S2 confirms the entry.
4. VOLUME CONFIRMATION This filters out weak signals by checking for real buying/selling interest.
HOW IT WORKS:
Compares current volume to previous bar and a 10–14 bar average.
Adjustable volume thresholds for S1 and S2.
Can be disabled for markets with unreliable volume (like certain forex pairs).
WHY IT MATTERS: It adds a layer of quality control. High-volume moves usually mean higher conviction.
EXAMPLE: On AAPL, an S2 will only trigger if volume jumps by 1.3x the average, signaling strong seller presence.
5. BUILT-IN FIBONACCI TARGETS (TP1, TP2, SL) No more guessing exits. The strategy draws take profit (TP) and stop loss (SL) levels automatically based on zone size.
HOW IT WORKS:
TP1 = 2.12x the zone height
TP2 = 3.3x the zone height
SL = 1x the zone height (all adjustable)
These are shown as dashed (TP) and solid (SL) lines with labels
WHY IT MATTERS: Reduces emotional decision-making. Helps you plan trades with consistent risk/reward.
Example: In GOLD, if the demand zone is $20 tall, TP1 would be ~$42.40 higher, TP2 ~$66 higher, and SL $20 lower.
6. FULLY CUSTOMIZABLE INPUTS Tweak the settings to match your style and asset type.
KEY INPUTS:
Market Mood: Choose bullish (1) or bearish (2)
Timeframe Filter: Focus only on reliable zones (30M or 4H) or can disable to show on every timeframe
Zone Limit: Limit how many zones show (e.g., max 4)
Breakout Buffer: Defines how much price must move to break a zone
Zone Opacity: Make zones more/less visible
WHY IT MATTERS: This lets you dial in the indicator for scalping, swing trading, crypto, stocks, or forex.
Example: A scalper might use tighter zones and a low breakout buffer, while a swing trader prefers more zones and higher volatility mode.
7. DEBUG MODE (Optional) Get under the hood and see exactly how the strategy works.
HOW IT WORKS:
Shows metrics like ATR, volatility mode, memory usage, signal win rate, etc.
Plots visual lines showing zone age and success rate (TP1 hit tracking)
WHY IT MATTERS: Very few indicators show their math. This one does—great for power users who want to optimize.
EXAMPLE: You might discover that signals perform best in high volatility mode during news events, helping you adjust settings accordingly.
HOW TO USE IT
1. Add it to your TradingView chart (30M or 4H timeframes recommended).
2. Adjust inputs:
Market Mood = 1 (bullish) or 2 (bearish)
Pick your Volatility Mode
Set Zone Collector Limit (3–4 works well)
Use Timeframe Filter for better signals
3. Watch for S1 and S2:
S1 = quicker trades, lighter risk
S2 = stronger confirmation, bigger trades
4. Use the Pivot Line for trade direction.
5. Manage exits with auto TP/SL levels.
6. Turn on Debug Mode if you want detailed stats.
WORKS VERY WELL WITHOUT REPAINTING
Why It’s a Game-Changer; IT takes the guesswork out of zone trading. It’s not just smart—it’s adaptive. From volatility and volume to dynamic signals and exit plans, everything adjusts based on what the market is doing. And with a built-in trend filter and real-time debug info, it’s like having a trading co-pilot that’s always alert.
Why It’s Different Most zone indicators are basic. This one isn’t. Here’s why:
Adaptive zones that change with the market
Dual signal system (S1/S2) for flexibility
Volume confirmation to filter noise
Built-in Fibonacci targets for clean exits
Debug mode that shows you how it works
YOU CAN SET ALERTS WITHOUT repainting
THIS isn’t just another tool—it’s a smarter, more responsive way to trade.
Morning Structure – Live 30 Min Range📝 Description:
This indicator captures the morning price structure by tracking the high and low during the first 30 minutes after market open (default: 9:30 AM to 10:00 AM, New York time).
🔧 How it works:
At market open, it begins tracking the highest high and lowest low
The high and low lines are dynamic and update in real-time during the first 30 minutes
Once the 30-minute range completes, the lines freeze at their final values
Lines extend horizontally across the rest of the session to mark the "Morning Range"
✅ Key Features:
Tracks live price action during the morning session
Freezes the structure after 30 minutes (or user-defined)
Automatically resets each new trading day
Built-in timezone setting (America/New_York) to align with standard U.S. market hours
Clean visual lines that scroll naturally with the chart
⚙️ Use Cases:
Identify morning breakout zones
Define support and resistance early in the session
Combine with breakout, fade, or range-trading strategies
⚠️ Note:
This version does not include alerts or labels, by design (clean and focused).
Those can be added easily for custom strategies.
PRICE MOVEMENT STATISTICS# Price Movement Statistics - Advanced Pattern Recognition System
## Foundation
Price Movement Statistics (PMS) represents a fundamentally different approach to market analysis compared to traditional indicators like RSI, Moving Averages, or Bollinger Bands. While most indicators rely on mathematical transformations of price data, PMS implements a **machine learning-inspired nearest-neighbor algorithm** that compares current market conditions against thousands of historical patterns across multiple correlated instruments.
### What Makes This Original
Unlike standard indicators that follow predetermined formulas, PMS:
1. **Multi-Symbol Pattern Database**: Analyzes up to 4 different but correlated symbols simultaneously, creating a massive historical pattern database that single-symbol indicators cannot access
2. **8-Feature Normalized Vector Comparison**: Converts each candlestick into 8 numerical features (body-to-range ratios, wick proportions, relative positioning, momentum characteristics) and uses Manhattan distance calculations to find statistically similar historical situations
3. **Forward-Looking Statistical Validation**: Instead of just identifying patterns, PMS tracks what actually happened 1-5 bars after similar patterns occurred historically, providing probabilistic forecasts with sample sizes and confidence levels
4. **Adaptive Similarity Scoring**: Uses real-time distance calculations between current conditions and historical patterns, allowing traders to see exactly how many similar cases existed and their outcomes
## Technical Methodology Explained
### Pattern Recognition Engine
The core algorithm transforms each market condition into a normalized 8-dimensional vector containing:
- Short vs. long-term range ratios computed using proprietary envelope calculations
- Price position relative to recent ranges using adaptive scaling methods
- Volatility comparisons across multiple timeframes with logarithmic return analysis
- Momentum divergences between short and long-term linear regression slopes
- Volume behavior patterns using statistical deviation scoring
- Candlestick structure metrics including ATR ratios and boundary touch frequencies
### Advanced Code Architecture
**Multi-Symbol Data Pipeline**: The system employs Pine Script's `request.security()` function in a sophisticated loop structure that simultaneously processes up to 4 different instruments. Each symbol contributes its own 8-feature vector, creating a 32-dimensional search space that dramatically expands pattern recognition capabilities beyond single-symbol analysis.
**Adaptive Normalization Engine**: Rather than using simple percentage changes, the code implements a custom `scale_adaptive()` function that ranks current values against rolling historical distributions. This percentile-based approach ensures pattern recognition remains consistent across different market volatility regimes and price levels.
**Distance Matrix Calculations**: The matching algorithm runs nested loops through thousands of historical bars, computing Manhattan distances for each potential match. The code optimizes performance by using vectorized operations and early termination conditions when similarity thresholds aren't met.
**Forward-Looking Analysis Pipeline**: Once matches are identified, the system implements a sophisticated outcome tracking mechanism that categorizes future price movements, volume behaviors, and candle characteristics. This requires careful index management to avoid look-ahead bias while maintaining real-time calculation efficiency.
### Similarity Matching Process
1. **Data Normalization**: Features are processed through custom percentile ranking against 500-bar rolling windows
2. **Distance Calculation**: Optimized Manhattan distance computation across 8-dimensional vectors with early exit conditions
3. **Multi-Symbol Aggregation**: Matches from different symbols are weighted and combined using statistical averaging techniques
4. **Threshold Filtering**: Dynamic similarity boundaries that adapt to market volatility conditions
5. **Outcome Analysis**: Forward-looking statistical compilation with bias tracking and magnitude calculations
### Statistical Output Generation
The system's proprietary aggregation engine provides:
- **Win/Loss Ratios**: Calculated from actual forward-price movements with statistical weighting
- **Sample Sizes**: Match counts across all symbols with confidence scoring algorithms
- **Average Magnitude**: Expected move calculations using historical outcome distributions
- **Volume Context**: Pattern-specific volume analysis using normalized scoring methods
- **Directional Bias**: Multi-timeframe probability calculations with cross-symbol validation
## Why This Approach is Worth the Investment
### Beyond Traditional Indicators
Standard indicators like RSI or MACD give you oversold/overbought signals or momentum divergences, but they don't answer the crucial question: "What happened historically when similar conditions occurred?" PMS bridges this gap by providing:
1. **Quantified Probabilities**: Instead of subjective pattern recognition, you get actual win rates and sample sizes
2. **Cross-Market Validation**: Patterns confirmed across multiple correlated instruments carry more statistical weight
3. **Sample Size Transparency**: You can see whether a signal is based on 5 occurrences or 500, adjusting confidence accordingly
4. **Magnitude Expectations**: Historical data shows not just direction, but expected move sizes
### Practical Trading Applications
**Entry Timing**: When PMS shows >70% historical win rate with 100+ matches, you have statistical evidence supporting your entry rather than relying on visual pattern interpretation.
**Risk Management**: Historical magnitude data helps size positions appropriately based on expected adverse moves in similar past situations.
**Confirmation**: Multi-symbol analysis provides cross-market confirmation that single-symbol indicators cannot offer.
## How to Use the System
### Signal Interpretation
- **Bias Ratio >1.5**: Historically bullish (more winning long trades than losing ones)
- **Bias Ratio <0.67**: Historically bearish (more winning short trades than losing ones)
- **Sample Size >50**: High confidence (sufficient historical data)
- **Sample Size <20**: Low confidence (limited historical precedent)
### Setup Optimization
- **Symbol Selection**: Choose 3-4 correlated instruments (e.g., stock + sector ETF + index, or currency pairs with base currency relationships)
- **Timeframe Coordination**: Use higher timeframes for broader context, lower timeframes for precise entry timing
- **Threshold Adjustment**: Lower similarity thresholds find more specific matches; higher thresholds increase sample sizes
## Technical Requirements and Limitations
**Data Depth**: Requires minimum 1000 bars per symbol for meaningful analysis; 3000+ bars recommended for optimal performance.
**Computational Load**: Real-time pattern matching across multiple symbols and thousands of historical bars requires TradingView's advanced Pine Script capabilities.
**Market Applicability**: Most effective in liquid markets with sufficient historical data; less reliable in newly listed instruments or during unprecedented market conditions.
## Important Disclaimers
This system identifies historical statistical patterns under similar conditions—it does not predict future movements with certainty. Effectiveness depends on intelligent symbol selection, appropriate timeframe usage, and integration with proper risk management. Past performance patterns do not guarantee future results, and all trading involves substantial risk of loss.
The algorithm's sophistication lies not in complex mathematical formulas, but in its ability to efficiently search through massive historical datasets and quantify pattern outcomes—something impossible to do manually and unavailable in standard technical indicators.
Wavelet-Trend ML Integration [Alpha Extract]Alpha-Extract Volatility Quality Indicator
The Alpha-Extract Volatility Quality (AVQ) Indicator provides traders with deep insights into market volatility by measuring the directional strength of price movements. This sophisticated momentum-based tool helps identify overbought and oversold conditions, offering actionable buy and sell signals based on volatility trends and standard deviation bands.
🔶 CALCULATION
The indicator processes volatility quality data through a series of analytical steps:
Bar Range Calculation: Measures true range (TR) to capture price volatility.
Directional Weighting: Applies directional bias (positive for bullish candles, negative for bearish) to the true range.
VQI Computation: Uses an exponential moving average (EMA) of weighted volatility to derive the Volatility Quality Index (VQI).
Smoothing: Applies an additional EMA to smooth the VQI for clearer signals.
Normalization: Optionally normalizes VQI to a -100/+100 scale based on historical highs and lows.
Standard Deviation Bands: Calculates three upper and lower bands using standard deviation multipliers for volatility thresholds.
Signal Generation: Produces overbought/oversold signals when VQI reaches extreme levels (±200 in normalized mode).
Formula:
Bar Range = True Range (TR)
Weighted Volatility = Bar Range × (Close > Open ? 1 : Close < Open ? -1 : 0)
VQI Raw = EMA(Weighted Volatility, VQI Length)
VQI Smoothed = EMA(VQI Raw, Smoothing Length)
VQI Normalized = ((VQI Smoothed - Lowest VQI) / (Highest VQI - Lowest VQI) - 0.5) × 200
Upper Band N = VQI Smoothed + (StdDev(VQI Smoothed, VQI Length) × Multiplier N)
Lower Band N = VQI Smoothed - (StdDev(VQI Smoothed, VQI Length) × Multiplier N)
🔶 DETAILS
Visual Features:
VQI Plot: Displays VQI as a line or histogram (lime for positive, red for negative).
Standard Deviation Bands: Plots three upper and lower bands (teal for upper, grayscale for lower) to indicate volatility thresholds.
Reference Levels: Horizontal lines at 0 (neutral), +100, and -100 (in normalized mode) for context.
Zone Highlighting: Overbought (⋎ above bars) and oversold (⋏ below bars) signals for extreme VQI levels (±200 in normalized mode).
Candle Coloring: Optional candle overlay colored by VQI direction (lime for positive, red for negative).
Interpretation:
VQI ≥ 200 (Normalized): Overbought condition, strong sell signal.
VQI 100–200: High volatility, potential selling opportunity.
VQI 0–100: Neutral bullish momentum.
VQI 0 to -100: Neutral bearish momentum.
VQI -100 to -200: High volatility, strong bearish momentum.
VQI ≤ -200 (Normalized): Oversold condition, strong buy signal.
🔶 EXAMPLES
Overbought Signal Detection: When VQI exceeds 200 (normalized), the indicator flags potential market tops with a red ⋎ symbol.
Example: During strong uptrends, VQI reaching 200 has historically preceded corrections, allowing traders to secure profits.
Oversold Signal Detection: When VQI falls below -200 (normalized), a lime ⋏ symbol highlights potential buying opportunities.
Example: In bearish markets, VQI dropping below -200 has marked reversal points for profitable long entries.
Volatility Trend Tracking: The VQI plot and bands help traders visualize shifts in market momentum.
Example: A rising VQI crossing above zero with widening bands indicates strengthening bullish momentum, guiding traders to hold or enter long positions.
Dynamic Support/Resistance: Standard deviation bands act as dynamic volatility thresholds during price movements.
Example: Price reversals often occur near the third standard deviation bands, providing reliable entry/exit points during volatile periods.
🔶 SETTINGS
Customization Options:
VQI Length: Adjust the EMA period for VQI calculation (default: 14, range: 1–50).
Smoothing Length: Set the EMA period for smoothing (default: 5, range: 1–50).
Standard Deviation Multipliers: Customize multipliers for bands (defaults: 1.0, 2.0, 3.0).
Normalization: Toggle normalization to -100/+100 scale and adjust lookback period (default: 200, min: 50).
Display Style: Switch between line or histogram plot for VQI.
Candle Overlay: Enable/disable VQI-colored candles (lime for positive, red for negative).
The Alpha-Extract Volatility Quality Indicator empowers traders with a robust tool to navigate market volatility. By combining directional price range analysis with smoothed volatility metrics, it identifies overbought and oversold conditions, offering clear buy and sell signals. The customizable standard deviation bands and optional normalization provide precise context for market conditions, enabling traders to make informed decisions across various market cycles.
Distribution & Accumulation Days# Distribution & Accumulation Days Indicator
## Overview
This powerful institutional activity tracker identifies **Distribution Days** (selling pressure) and **Accumulation Days** (buying pressure) based on the proven methodology used by Investor's Business Daily (IBD). Perfect for detecting when "smart money" institutions are actively buying or selling, helping you align your trades with institutional flow.
## What It Does
- **Distribution Days**: Identifies days when price drops significantly on higher volume (institutional selling)
- **Accumulation Days**: Identifies days when price rises significantly on higher volume (institutional buying)
- **Real-time Counting**: Tracks the number of each type over your specified lookback period
- **Net Analysis**: Shows whether buying or selling pressure is dominant
## Key Features
### 🎯 **Customizable Threshold**
- Set your own price change percentage (default 0.2%) to filter out minor moves
- Focus only on significant institutional activity
### 📊 **Moving Average Filter**
- Optional MA filter to eliminate noise during strong downtrends
- Choose from SMA, WMA, or EMA
- Only counts signals when price is above the moving average
### 📈 **Visual Markers**
- **Red 'D'** markers above bars = Distribution (selling pressure)
- **Green 'A'** markers below bars = Accumulation (buying pressure)
- Numbers show current count within your lookback period
### 📋 **Information Dashboard**
Real-time table displays:
- Total Distribution Days in period
- Total Accumulation Days in period
- Net difference (positive = more buying, negative = more selling)
## How to Use
### Market Analysis
- **4-5 Distribution Days** in 25 sessions = Potential market weakness
- **Multiple Accumulation Days** after decline = Potential bottom formation
- **Net positive** = Institutional buying dominance
- **Net negative** = Institutional selling dominance
### Trade Setup
- Look for accumulation clusters near support levels for long entries
- Watch for distribution clusters near resistance for potential short setups
- Use in conjunction with your existing technical analysis
## Settings
| Parameter | Description | Default |
|-----------|-------------|---------|
| Days Back | Lookback period for counting | 25 |
| Price Change Threshold | Minimum % move required | 0.2% |
| Moving Average Filter | Enable/disable MA filter | Off |
| MA Type | SMA, WMA, or EMA | EMA |
| MA Length | Moving average period | 50 |
## Best Practices
- Use on **daily timeframe only** (automatically restricts to daily)
- Works best on major indices (SPY, QQQ, IWM) and liquid stocks
- Combine with support/resistance levels for better entries
- Monitor both individual counts and net difference for complete picture
## Important Notes
- Based on proven IBD methodology used by professional traders
- Requires significant volume confirmation - price moves without volume are ignored
- Most effective when used as part of a complete trading system
- Works only on daily charts (designed for institutional timeframe analysis)
---
*This indicator helps you see the market through institutional eyes. When the big players are buying or selling, you'll know.*
**Tags**: Distribution, Accumulation, IBD, Institutional, Volume Analysis, Smart Money, Market Structure
MÈGAS ALGO : NMS (Nexora Momentum Synchronizer) [INDICATOR]Overview
The NMS (Nexora Momentum Synchronizer) is a multi-timeframe indicator that aggregates and analyzes data of multiple momentum oscillators across different timeframes (1m, 5m, 15m, 30m, 45m, 1h, 2h, 4h, 8h, 12h and 24h).
A user-friendly table displaying the indicator’s current values for each timeframe simultaneously.
The script, thanks to the best technical momentum indicators provided by Tradingview, evaluates trend strength and market momentum through synchronized readings of TRSI , TSI , RSI , Stochastic RSI , Williams %R , and CCI.
In addition to the indicator also tracks:
-percentage change in price from the last bar's open across each timeframes
-countdown time to bar close
This indicator caters to the diverse needs of traders, whether they are focused on short-term momentum bursts or long-term trend-following strategies.
By synchronizing momentum indicators, real-time price change(%) from last open and countdow time to close, across multiple timeframes, this tool provides a holistic view of market dynamics, empowering traders to make informed decisions with confidence.
Key Features
1.Multi-Timeframe Momentum Analysis
The Nexora Momentum Synchronizer performs an analysis of key momentum indicator :
—Trend Strength Index (TSI) , True Strength Index (TSI) , Relative Strength Index (RSI) , Stochastic Oscillator (STOCH), Williams Percent Range (W%R) and Commodity Channel Index (CCI) —across multiple timeframes. This ensures traders receive a
comprehensive understanding of momentum alignment, helping them identify high-probability
trade setups with reduced noise and false signals.
In addition to oscillator alignment and regression-based zone detection, the script includes:
-real-time price change(%) from last open for each timeframe, providing insight into intrabar momentum and directional bias.
-real-time countdown to bar close , displayed directly in the table, which enhances timing precision and supports scalping or event-based trading strategies.
These tools combine to offer a comprehensive, real-time framework for both discretionary and alert-driven trading systems.
2.Customizable Parameters
Fully adjustable settings allow traders to tailor the indicator to their specific preferences and
adapt to diverse market conditions. From adjusting overbought and oversold levels to selecting preferred timeframes for alignment alerts, the Nexora Momentum Synchronizer offers unparalleled flexibility to meet individual trading styles.
3.Multi-Timeframe Alerts
Traders can set up alerts for momentum alignment across up to four different timeframes. These alerts ensure that no opportunity is missed, regardless of the trading horizon or strategy being employed.
These alerts can be set up to three different mode : All (to never miss opportunity), Once_for_Bar (to limit to one alert triggered during bar's period) or Bar_Close (to avoid earlier bias).
4.User-Friendly Interface
Designed with simplicity in mind, the Nexora Momentum Synchronizer features an intuitive
table interface that makes complex data easy to interpret. Clear visual cues and
interactive elements allow traders to focus on executing strategies without being
overwhelmed by cluttered charts.
Advantages of Nexora Momentum Synchronizer
Flexibility : Fully customizable parameters ensure the indicator adapts to diverse market
conditions and trader preferences.
Comprehensive Analysis : Multi-timeframe evaluation of momentum indicators provides a
holistic view of market dynamics, enhancing trade confidence.
Real-Time Alerts : Multi-timeframe alert functionality keeps traders informed of critical
market movements and momentum shifts across different horizons.
Please Note:
This indicator is provided for informational and educational purposes only. It is not financial advice, and it should not be considered a recommendation to buy, sell, or trade any financial instrument. Trading involves significant risks, including the potential loss of your entire investment. Always conduct your own research and consult with a licensed financial advisor before making any trading decisions.
The results and images provided are based on algorithms and historical/paid real-time market data but do not guarantee future results or accuracy. Use this tool at your own risk, and understand that past performance is not indicative of future outcomes.
Smarter Money Flow Divergence Detector [PhenLabs]📊 Smarter Money Flow Divergence Detector
Version: PineScript™ v6
📌 Description
SMFD was developed to help give you guys a better ability to “read” what is going on behind the scenes without directly having access to that level of data. SMFD is an enhanced divergence detection indicator that identifies money flow patterns from advanced volume analysis and price action correspondence. The detection portion of this indicator combines intelligent money flow calculations with multi timeframe volume analysis to help you see hidden accumulation and distribution phases before major price movements occur.
The indicator measures institutional trading activity by looking at volume surges, price volume dynamics, and the factors of momentum to construct an overall picture of market sentiment. It’s built to assist traders in identifying high probability entries by identifying if smart money is positioning against price action.
🚀 Points of Innovation
● Advanced Smart Money Flow algorithm with volume spike detection and large trade weighting
● Multi timeframe volume analysis for enhanced institutional activity detection
● Dynamic overbought/oversold zones that adapt to current market conditions
● Enhanced divergence detection with pivot confirmation and strength validation
● Color themes with customizable visual styling options
● Real time institutional bias tracking through accumulation/distribution analysis
🔧 Core Components
● Smart Money Flow Calculation: Combines price momentum, volume expansion, and VWAP analysis
● Institutional Bias Oscillator: Tracks accumulation/distribution patterns with volume pressure analysis
● Enhanced Divergence Engine: Detects bullish/bearish divergences with multiple confirmation factors
● Dynamic Zone Detection: Automatically adjusts overbought/oversold levels based on market volatility
● Volume Pressure Analysis: Measures buying vs selling pressure over configurable periods
● Multi factor Signal System: Generates entries with trend alignment and strength validation
🔥 Key Features
● Smart Money Flow Period: Configurable calculation period for institutional activity detection
● Volume Spike Threshold: Adjustable multiplier for detecting unusual institutional volume
● Large Trade Weight: Emphasis factor for high volume periods in flow calculations
● Pivot Detection: Customizable lookback period for accurate divergence identification
● Signal Sensitivity: Three tier system (Conservative/Medium/Aggressive) for signal generation
● Themes: Four color schemes optimized for different chart backgrounds
🎨 Visualization
● Main Oscillator: Line, Area, or Histogram display styles with dynamic color coding
● Institutional Bias Line: Real time tracking of accumulation/distribution phases
● Dynamic Zones: Adaptive overbought/oversold boundaries with gradient fills
● Divergence Lines: Automatic drawing of bullish/bearish divergence connections
● Entry Signals: Clear BUY/SELL labels with signal strength indicators
● Information Panel: Real time statistics and status updates in customizable positions
📖 Usage Guidelines
Algorithm Settings
● Smart Money Flow Period
○ Default: 20
○ Range: 5-100
○ Description: Controls the calculation period for institutional flow analysis.
Higher values provide smoother signals but reduce responsiveness to recent activity
● Volume Spike Threshold
○ Default: 1.8
○ Range: 1.0-5.0
○ Description: Multiplier for detecting unusual volume activity indicating institutional participation. Higher values require more extreme volume for detection
● Large Trade Weight
○ Default: 2.5
○ Range: 1.5-5.0
○ Description: Weight applied to high volume periods in smart money calculations. Increases emphasis on institutional sized transactions
Divergence Detection
● Pivot Detection Period
○ Default: 12
○ Range: 5-50
○ Description: Bars to analyze for pivot high/low identification.
Affects divergence accuracy and signal frequency
● Minimum Divergence Strength
○ Default: 0.25
○ Range: 0.1-1.0
○ Description: Required price change percentage for valid divergence patterns.
Higher values filter out weaker signals
✅ Best Use Cases
● Trading with intraday to daily timeframes for institutional position identification
● Confirming trend reversals when divergences align with support/resistance levels
● Entry timing in trending markets when institutional bias supports the direction
● Risk management by avoiding trades against strong institutional positioning
● Multi timeframe analysis combining short term signals with longer term bias
⚠️ Limitations
● Requires sufficient volume for accurate institutional detection in low volume markets
● Divergence signals may have false positives during highly volatile news events
● Best performance on liquid markets with consistent institutional participation
● Lagging nature of volume based calculations may delay signal generation
● Effectiveness reduced during low participation holiday periods
💡 What Makes This Unique
● Multi Factor Analysis: Combines volume, price, and momentum for comprehensive institutional detection
● Adaptive Zones: Dynamic overbought/oversold levels that adjust to market conditions
● Volume Intelligence: Advanced algorithms identify institutional sized transactions
● Professional Visualization: Multiple display styles with customizable themes
● Confirmation System: Multiple validation layers reduce false signal generation
🔬 How It Works
1. Volume Analysis Phase:
● Analyzes current volume against historical averages to identify institutional activity
● Applies multi timeframe analysis for enhanced detection accuracy
● Calculates volume pressure through buying vs selling momentum
2. Smart Money Flow Calculation:
● Combines typical price with volume weighted analysis
● Applies institutional trade weighting for high volume periods
● Generates directional flow based on price momentum and volume expansion
3. Divergence Detection Process:
● Identifies pivot highs/lows in both price and indicator values
● Validates divergence strength against minimum threshold requirements
● Confirms signals through multiple technical factors before generation
💡 Note: This indicator works best when combined with proper risk management and position sizing. The institutional bias component helps identify market sentiment shifts, while divergence signals provide specific entry opportunities. For optimal results, use on liquid markets with consistent institutional participation and combine with additional technical analysis methods.
Adaptive Momentum Deviation Oscillator | QuantMACAdaptive Momentum Deviation Oscillator | QuantMAC 📊
Overview 🎯
The Adaptive Momentum Deviation Oscillator (AMDO) is an advanced technical analysis indicator that combines the power of Bollinger Bands with adaptive momentum calculations to identify optimal entry and exit points in financial markets. This sophisticated oscillator creates dynamic bands that adapt to market volatility while providing clear visual signals for both trending and ranging market conditions.
How It Works 🔧
Core Methodology
The AMDO employs a sophisticated multi-layered approach to market analysis through four distinct phases:
Bollinger Band Foundation : The indicator begins by establishing a volatility baseline using traditional Bollinger Bands. These bands are calculated using a simple moving average as the center line, with upper and lower bands positioned at a specific number of standard deviations away from this centerline. The distance between these bands expands and contracts based on market volatility, creating a dynamic envelope around price action.
BB% Normalization Process : The raw price data is then transformed into a normalized percentage format that represents where the current price sits within the Bollinger Band envelope. When price is at the lower band, this percentage reads 0%; at the upper band, it reads 100%. This normalization allows for consistent comparison across different timeframes and price levels, creating a standardized oscillator that oscillates between extreme values.
Adaptive Momentum Band Construction : The normalized BB% values undergo a secondary volatility analysis where their own standard deviation is calculated over a specified period. This creates "bands around the bands" - upper and lower boundaries that adapt to the volatility of the normalized price position itself. These adaptive bands expand during periods of high momentum volatility and contract during consolidation phases.
Intelligent Signal Synthesis : The final layer combines the adaptive momentum bands with user-defined threshold levels to create a sophisticated trigger system. The indicator monitors when the dynamic bands cross above or below these thresholds, filtering out noise while capturing significant momentum shifts. This creates a dual-confirmation system where both volatility adaptation and threshold breaches must align for signal generation.
Key Components 🛠️
Adaptive Momentum Bands 📈
Dynamic Volatility Response : These bands automatically widen during periods of high momentum volatility and narrow during consolidation phases. Unlike fixed oscillator boundaries, they continuously recalibrate based on recent price behavior within the Bollinger Band framework.
Dual-Layer Calculation : The bands are derived from the volatility of the normalized price position itself, creating a "volatility of volatility" measurement. This provides early warning signals when momentum characteristics are changing, even before price breakouts occur.
State-Aware Visualization : The bands employ intelligent color coding that transitions between active and neutral states based on their interaction with threshold levels. Active states indicate high-probability momentum conditions, while neutral states suggest consolidation or indecision.
Momentum Persistence Tracking : The bands maintain memory of recent momentum characteristics, allowing them to distinguish between genuine momentum shifts and temporary price spikes or dips.
Threshold Levels 🎚️
Statistical Significance Boundaries : The threshold levels (default 83 for long, 40 for short) are positioned to capture statistically significant momentum events while filtering out market noise. These levels represent points where momentum probability shifts meaningfully in favor of directional moves.
Asymmetric Design Philosophy : The intentional asymmetry between long and short thresholds (83 vs 40) reflects the natural upward bias of many financial markets and the different risk/reward profiles of long versus short positions.
Contextual Sensitivity : The thresholds work in conjunction with the adaptive bands to create context-sensitive triggers. A threshold breach is only meaningful when it occurs in the proper sequence with band interactions.
Risk-Adjusted Positioning : The threshold levels are calibrated to provide favorable risk-adjusted entry points, considering both the probability of success and the potential magnitude of subsequent moves.
Bollinger Bands Overlay 📊
Multi-Timeframe Context : The price chart overlay provides essential context by showing traditional Bollinger Bands alongside the oscillator. This dual perspective allows traders to see both the absolute price position and the momentum characteristics simultaneously.
Support/Resistance Identification : The filled band area creates a visual representation of dynamic support and resistance levels. Price interaction with these bands provides additional confirmation for oscillator signals.
Volatility Environment Assessment : The width and slope of the bands offer immediate visual feedback about the current volatility environment, helping traders adjust their expectations and risk management accordingly.
Confluence Analysis : The overlay enables traders to identify confluence between price action at Bollinger Band levels and oscillator signals, creating higher-probability trade setups.
Signal Generation ⚡
The AMDO generates signals through precise mathematical crossover events:
Long Signals 🟢
Momentum Accumulation Detection : Long signals are generated when the lower adaptive momentum band crosses above the 83 threshold, indicating that downside momentum has exhausted and bullish momentum is beginning to accumulate. This represents a shift from defensive to offensive market posture.
Statistical Edge Confirmation : The crossing event occurs only when momentum characteristics have shifted sufficiently to provide a statistical edge for long positions. The adaptive nature ensures the signal quality remains consistent across different market volatility regimes.
Visual State Synchronization : Upon signal generation, the entire indicator ecosystem shifts to a bullish state - bar colors change, band states update, and the visual hierarchy emphasizes the long bias until conditions change.
Momentum Persistence Validation : The signal incorporates momentum persistence analysis to distinguish between genuine trend starts and false breakouts, reducing whipsaw trades in choppy market conditions.
Short Signals 🔴
Momentum Exhaustion Recognition : Short signals trigger when the upper adaptive momentum band crosses below the 40 threshold, signaling that bullish momentum has peaked and bearish momentum is emerging. This asymmetric threshold reflects the different dynamics of bullish versus bearish market phases.
Volatility-Adjusted Timing : The adaptive band system ensures that short signals are generated with appropriate timing regardless of the underlying volatility environment, maintaining signal quality in both high and low volatility conditions.
Regime-Aware Activation : Short signals are only active in Long/Short trading mode, recognizing that not all trading strategies benefit from short positions. The indicator adapts its behavior based on the selected trading approach.
Risk-Calibrated Thresholds : The 40 threshold is specifically calibrated to capture meaningful bearish momentum shifts while accounting for the higher risk typically associated with short positions.
Cash Signals 💰
Defensive Positioning Logic : In Long/Cash mode, cash signals are generated when short conditions are met, allowing traders to move to a defensive cash position rather than taking on short exposure. This preserves capital during unfavorable market conditions.
Risk Mitigation Strategy : Cash signals represent a risk-off approach that removes market exposure when momentum conditions favor the short side, protecting long-biased portfolios from adverse market movements.
Opportunity Cost Optimization : The cash position allows traders to avoid negative returns while maintaining flexibility to re-enter long positions when momentum conditions improve, optimizing the risk-adjusted return profile.
Features & Customization ⚙️
Color Schemes 🎨
9 pre-built color schemes (Classic through Classic9)
Custom color override option
Dynamic color changes based on signal states
Trading Modes 📈
Long/Short : Full bidirectional trading capability
Long/Cash : Long-only strategy with cash positions
Performance Metrics 📊
The indicator includes a comprehensive suite of advanced performance analytics that provide deep insights into strategy effectiveness:
Risk-Adjusted Return Metrics
Sortino Ratio : Measures returns relative to downside deviation only, providing a more accurate assessment of risk-adjusted performance by focusing on harmful volatility rather than total volatility. This metric is particularly valuable for asymmetric return distributions.
Sharpe Ratio : Calculates excess return per unit of total risk, offering a standardized measure of risk-adjusted performance that allows for comparison across different strategies and timeframes.
Omega Ratio : Employs probability-weighted analysis to compare the likelihood and magnitude of gains versus losses, providing insights into the overall shape of the return distribution and tail risk characteristics.
Drawdown and Risk Analysis
Maximum Drawdown : Tracks the largest peak-to-trough equity decline, providing crucial information about the worst-case scenario and helping traders understand the emotional and financial stress they might encounter.
Dynamic Drawdown Monitoring : Continuously updates drawdown calculations in real-time, allowing traders to monitor current drawdown levels relative to historical maximums.
Trade Statistics and Profitability
Profit Factor Analysis : Compares gross profits to gross losses, revealing the efficiency of the trading approach and the relationship between winning and losing trades.
Win Rate Calculation : Provides the percentage of profitable trades, which must be interpreted in conjunction with profit factor and average trade size for meaningful analysis.
Trade Frequency Tracking : Monitors total trade count to assess strategy turnover and transaction cost implications.
Position Sizing Guidance
Half Kelly Percentage : Calculates optimal position sizing based on Kelly Criterion methodology, then applies a conservative 50% reduction to account for parameter uncertainty and reduce volatility. This provides mathematically-based position sizing guidance that balances growth with risk management.
Parameters & Settings 🔧
BMD Settings
- Base Length : Period for Bollinger Band calculation (default: 10)
- Source : Price data source (default: close)
- Standard Deviation Length : Period for volatility calculation (default: 35)
- SD Multiplier : Bollinger Band width multiplier (default: 1.0)
- BB% Multiplier : Scaling factor for BB% calculation (default: 100)
BMD Settings
Base Length : Period for Bollinger Band calculation (default: 10)
Source : Price data source (default: close)
Standard Deviation Length : Period for volatility calculation (default: 35)
SD Multiplier : Bollinger Band width multiplier (default: 1.0)
BB% Multiplier : Scaling factor for BB% calculation (default: 100)
Signal Thresholds 🎯
Long Threshold : Trigger level for long signals (default: 83)
Short Threshold : Trigger level for short signals (default: 40)
Display Options 🖥️
Toggleable metrics table with 6 position options
Customizable date range limiter
Multiple visual elements for comprehensive analysis
Use Cases & Applications 💡
Trend Following
Identifies momentum shifts in trending markets
Provides early entry signals during trend continuations
Adaptive bands adjust to changing volatility conditions
Mean Reversion
Detects oversold/overbought conditions
Signals potential reversal points
Works effectively in ranging markets
Risk Management
Built-in performance metrics for strategy evaluation
Half Kelly percentage for position sizing guidance
Maximum drawdown monitoring
Advantages ✅
Adaptive Nature : Automatically adjusts to market volatility
Dual Display : Oscillator and price chart components work together
Comprehensive Metrics : Built-in performance analysis
Flexible Trading Modes : Supports different trading strategies
Visual Clarity : Color-coded signals and states
Customizable : Extensive parameter adjustment options
Important Considerations ⚠️
This indicator is designed for educational and analysis purposes
Should be used in conjunction with other technical analysis tools
Proper risk management is essential when trading
Backtest thoroughly before implementing in live trading
Market conditions can change rapidly, affecting indicator performance
Disclaimer ⚠️
Past performance is not indicative of future results. Trading involves substantial risk of loss and is not suitable for all investors. The information provided by this indicator should not be considered as financial advice. Always conduct your own research.
No indicator guarantees profitable trades - Always use proper risk management! 🛡️
Volatility Quality [Alpha Extract]The Alpha-Extract Volatility Quality (AVQ) Indicator provides traders with deep insights into market volatility by measuring the directional strength of price movements. This sophisticated momentum-based tool helps identify overbought and oversold conditions, offering actionable buy and sell signals based on volatility trends and standard deviation bands.
🔶 CALCULATION
The indicator processes volatility quality data through a series of analytical steps:
Bar Range Calculation: Measures true range (TR) to capture price volatility.
Directional Weighting: Applies directional bias (positive for bullish candles, negative for bearish) to the true range.
VQI Computation: Uses an exponential moving average (EMA) of weighted volatility to derive the Volatility Quality Index (VQI).
vqiRaw = ta.ema(weightedVol, vqiLen)
Smoothing: Applies an additional EMA to smooth the VQI for clearer signals.
Normalization: Optionally normalizes VQI to a -100/+100 scale based on historical highs and lows.
Standard Deviation Bands: Calculates three upper and lower bands using standard deviation multipliers for volatility thresholds.
vqiStdev = ta.stdev(vqiSmoothed, vqiLen)
upperBand1 = vqiSmoothed + (vqiStdev * stdevMultiplier1)
upperBand2 = vqiSmoothed + (vqiStdev * stdevMultiplier2)
upperBand3 = vqiSmoothed + (vqiStdev * stdevMultiplier3)
lowerBand1 = vqiSmoothed - (vqiStdev * stdevMultiplier1)
lowerBand2 = vqiSmoothed - (vqiStdev * stdevMultiplier2)
lowerBand3 = vqiSmoothed - (vqiStdev * stdevMultiplier3)
Signal Generation: Produces overbought/oversold signals when VQI reaches extreme levels (±200 in normalized mode).
Formula:
Bar Range = True Range (TR)
Weighted Volatility = Bar Range × (Close > Open ? 1 : Close < Open ? -1 : 0)
VQI Raw = EMA(Weighted Volatility, VQI Length)
VQI Smoothed = EMA(VQI Raw, Smoothing Length)
VQI Normalized = ((VQI Smoothed - Lowest VQI) / (Highest VQI - Lowest VQI) - 0.5) × 200
Upper Band N = VQI Smoothed + (StdDev(VQI Smoothed, VQI Length) × Multiplier N)
Lower Band N = VQI Smoothed - (StdDev(VQI Smoothed, VQI Length) × Multiplier N)
🔶 DETAILS
Visual Features:
VQI Plot: Displays VQI as a line or histogram (lime for positive, red for negative).
Standard Deviation Bands: Plots three upper and lower bands (teal for upper, grayscale for lower) to indicate volatility thresholds.
Reference Levels: Horizontal lines at 0 (neutral), +100, and -100 (in normalized mode) for context.
Zone Highlighting: Overbought (⋎ above bars) and oversold (⋏ below bars) signals for extreme VQI levels (±200 in normalized mode).
Candle Coloring: Optional candle overlay colored by VQI direction (lime for positive, red for negative).
Interpretation:
VQI ≥ 200 (Normalized): Overbought condition, strong sell signal.
VQI 100–200: High volatility, potential selling opportunity.
VQI 0–100: Neutral bullish momentum.
VQI 0 to -100: Neutral bearish momentum.
VQI -100 to -200: High volatility, strong bearish momentum.
VQI ≤ -200 (Normalized): Oversold condition, strong buy signal.
🔶 EXAMPLES
Overbought Signal Detection: When VQI exceeds 200 (normalized), the indicator flags potential market tops with a red ⋎ symbol.
Example: During strong uptrends, VQI reaching 200 has historically preceded corrections, allowing traders to secure profits.
Oversold Signal Detection: When VQI falls below -200 (normalized), a lime ⋏ symbol highlights potential buying opportunities.
Example: In bearish markets, VQI dropping below -200 has marked reversal points for profitable long entries.
Volatility Trend Tracking: The VQI plot and bands help traders visualize shifts in market momentum.
Example: A rising VQI crossing above zero with widening bands indicates strengthening bullish momentum, guiding traders to hold or enter long positions.
Dynamic Support/Resistance: Standard deviation bands act as dynamic volatility thresholds during price movements.
Example: Price reversals often occur near the third standard deviation bands, providing reliable entry/exit points during volatile periods.
🔶 SETTINGS
Customization Options:
VQI Length: Adjust the EMA period for VQI calculation (default: 14, range: 1–50).
Smoothing Length: Set the EMA period for smoothing (default: 5, range: 1–50).
Standard Deviation Multipliers: Customize multipliers for bands (defaults: 1.0, 2.0, 3.0).
Normalization: Toggle normalization to -100/+100 scale and adjust lookback period (default: 200, min: 50).
Display Style: Switch between line or histogram plot for VQI.
Candle Overlay: Enable/disable VQI-colored candles (lime for positive, red for negative).
The Alpha-Extract Volatility Quality Indicator empowers traders with a robust tool to navigate market volatility. By combining directional price range analysis with smoothed volatility metrics, it identifies overbought and oversold conditions, offering clear buy and sell signals. The customizable standard deviation bands and optional normalization provide precise context for market conditions, enabling traders to make informed decisions across various market cycles.
Magnificent 7 OscillatorThe Magnificent 7 Oscillator is a sophisticated momentum-based technical indicator designed to analyze the collective performance of the seven largest technology companies in the U.S. stock market (Apple, Microsoft, Alphabet, Amazon, NVIDIA, Tesla, and Meta). This indicator incorporates established momentum factor research and provides three distinct analytical modes: absolute momentum tracking, equal-weighted market comparison, and relative performance analysis. The tool integrates five different oscillator methodologies and includes advanced breadth analysis capabilities.
Theoretical Foundation
Momentum Factor Research
The indicator's foundation rests on seminal momentum research in financial markets. Jegadeesh and Titman (1993) demonstrated that stocks with strong price performance over 3-12 month periods tend to continue outperforming in subsequent periods¹. This momentum effect was later incorporated into formal factor models by Carhart (1997), who extended the Fama-French three-factor model to include a momentum factor (UMD - Up Minus Down)².
The momentum calculation methodology follows the academic standard:
Momentum(t) = / P(t-n) × 100
Where P(t) is the current price and n is the lookback period.
The focus on the "Magnificent 7" stocks reflects the increasing market concentration observed in recent years. Fama and French (2015) noted that a small number of large-cap stocks can drive significant market movements due to their substantial index weights³. The combined market capitalization of these seven companies often exceeds 25% of the total S&P 500, making their collective momentum a critical market indicator.
Indicator Architecture
Core Components
1. Data Collection and Processing
The indicator employs robust data collection with error handling for missing or invalid security data. Each stock's momentum is calculated independently using the specified lookback period (default: 14 periods).
2. Composite Oscillator Calculation
Following Fama-French factor construction methodology, the indicator offers two weighting schemes:
- Equal Weight: Each active stock receives identical weighting (1/n)
- Market Cap Weight: Reserved for future enhancement
3. Oscillator Transformation Functions
The indicator provides five distinct oscillator types, each with established technical analysis foundations:
a) Momentum Oscillator (Default)
- Pure rate-of-change calculation
- Centered around zero
- Direct implementation of Jegadeesh & Titman methodology
b) RSI (Relative Strength Index)
- Wilder's (1978) relative strength methodology
- Transformed to center around zero for consistency
- Scale: -50 to +50
c) Stochastic Oscillator
- George Lane's %K methodology
- Measures current position within recent range
- Transformed to center around zero
d) Williams %R
- Larry Williams' range-based oscillator
- Inverse stochastic calculation
- Adjusted for zero-centered display
e) CCI (Commodity Channel Index)
- Donald Lambert's mean reversion indicator
- Measures deviation from moving average
- Scaled for optimal visualization
Operational Modes
Mode 1: Magnificent 7 Analysis
Tracks the collective momentum of the seven constituent stocks. This mode is optimal for:
- Technology sector analysis
- Growth stock momentum assessment
- Large-cap performance tracking
Mode 2: S&P 500 Equal Weight Comparison
Analyzes momentum using an equal-weighted S&P 500 reference (typically RSP ETF). This mode provides:
- Broader market momentum context
- Size-neutral market analysis
- Comparison baseline for relative performance
Mode 3: Relative Performance Analysis
Calculates the momentum differential between Magnificent 7 and S&P 500 Equal Weight. This mode enables:
- Sector rotation analysis
- Style factor assessment (Growth vs. Value)
- Relative strength identification
Formula: Relative Performance = MAG7_Momentum - SP500EW_Momentum
Signal Generation and Thresholds
Signal Classification
The indicator generates three signal states:
- Bullish: Oscillator > Upper Threshold (default: +2.0%)
- Bearish: Oscillator < Lower Threshold (default: -2.0%)
- Neutral: Oscillator between thresholds
Relative Performance Signals
In relative performance mode, specialized thresholds apply:
- Outperformance: Relative momentum > +1.0%
- Underperformance: Relative momentum < -1.0%
Alert System
Comprehensive alert conditions include:
- Threshold crossovers (bullish/bearish signals)
- Zero-line crosses (momentum direction changes)
- Relative performance shifts
- Breadth Analysis Component
The indicator incorporates market breadth analysis, calculating the percentage of constituent stocks with positive momentum. This feature provides insights into:
- Strong Breadth (>60%): Broad-based momentum
- Weak Breadth (<40%): Narrow momentum leadership
- Mixed Breadth (40-60%): Neutral momentum distribution
Visual Design and User Interface
Theme-Adaptive Display
The indicator automatically adjusts color schemes for dark and light chart themes, ensuring optimal visibility across different user preferences.
Professional Data Table
A comprehensive data table displays:
- Current oscillator value and percentage
- Active mode and oscillator type
- Signal status and strength
- Component breakdowns (in relative performance mode)
- Breadth percentage
- Active threshold levels
Custom Color Options
Users can override default colors with custom selections for:
- Neutral conditions (default: Material Blue)
- Bullish signals (default: Material Green)
- Bearish signals (default: Material Red)
Practical Applications
Portfolio Management
- Sector Allocation: Use relative performance mode to time technology sector exposure
- Risk Management: Monitor breadth deterioration as early warning signal
- Entry/Exit Timing: Utilize threshold crossovers for position sizing decisions
Market Analysis
- Trend Identification: Zero-line crosses indicate momentum regime changes
- Divergence Analysis: Compare MAG7 performance against broader market
- Volatility Assessment: Oscillator range and frequency provide volatility insights
Strategy Development
- Factor Timing: Implement growth factor timing strategies
- Momentum Strategies: Develop systematic momentum-based approaches
- Risk Parity: Use breadth metrics for risk-adjusted portfolio construction
Configuration Guidelines
Parameter Selection
- Momentum Period (5-100): Shorter periods (5-20) for tactical analysis, longer periods (50-100) for strategic assessment
- Smoothing Period (1-50): Higher values reduce noise but increase lag
- Thresholds: Adjust based on historical volatility and strategy requirements
Timeframe Considerations
- Daily Charts: Optimal for swing trading and medium-term analysis
- Weekly Charts: Suitable for long-term trend analysis
- Intraday Charts: Useful for short-term tactical decisions
Limitations and Considerations
Market Concentration Risk
The indicator's focus on seven stocks creates concentration risk. During periods of significant rotation away from large-cap technology stocks, the indicator may not represent broader market conditions.
Momentum Persistence
While momentum effects are well-documented, they are not permanent. Jegadeesh and Titman (1993) noted momentum reversal effects over longer time horizons (2-5 years).
Correlation Dynamics
During market stress, correlations among the constituent stocks may increase, reducing the diversification benefits and potentially amplifying signal intensity.
Performance Metrics and Backtesting
The indicator includes hidden plots for comprehensive backtesting:
- Individual stock momentum values
- Composite breadth percentage
- S&P 500 Equal Weight momentum
- Relative performance calculations
These metrics enable quantitative strategy development and historical performance analysis.
References
¹Jegadeesh, N., & Titman, S. (1993). Returns to buying winners and selling losers: Implications for stock market efficiency. Journal of Finance, 48(1), 65-91.
Carhart, M. M. (1997). On persistence in mutual fund performance. Journal of Finance, 52(1), 57-82.
Fama, E. F., & French, K. R. (2015). A five-factor asset pricing model. Journal of Financial Economics, 116(1), 1-22.
Wilder, J. W. (1978). New concepts in technical trading systems. Trend Research.
Stop Hunt Indicator ║ BullVision 🧠 Overview
The Stop Hunt Indicator (SmartTrap Radar) is an original tool designed to identify potential liquidity traps caused by institutional stop hunts. It visually maps out historically significant levels where price has repeatedly reversed or rejected — and dynamically detects real-time sweep patterns based on volume, structure, and candle rejection behavior.
This script does not repurpose existing public indicators, nor does it use default TradingView built-ins such as RSI, MACD, or MAs. Its core logic is fully proprietary and was developed from scratch to support discretionary and data-driven traders in visualizing volatility risks and manipulation zones.
🔍 What the Indicator Does
This indicator identifies and visualizes potential stop hunt zones using:
Historical structure analysis: Swing highs/lows are identified via a configurable lookback period.
Liquidity level tracking: Once detected, levels are monitored for touches, age, and volume strength.
Proprietary scoring model: Each level receives a real-time significance score based on:
Age (how long the level has held)
Number of rejections (touches)
Relative volume strength
Proximity to current price
The glow intensity of plotted levels is dynamically mapped based on this score. Bright glow = higher institutional interest probability.
⚙️ Stop Hunt Detection Logic
A stop hunt is flagged when all of the following are met:
Price sweeps through a high/low beyond a user-defined penetration threshold
Wick rejection occurs (i.e., candle closes back inside the level)
Volume spikes above the average in a recent window
The script automatically:
Detects bullish stop hunts (below support) and bearish ones (above resistance)
Marks detected sweeps on-chart with optional 🔰/🚨 signals
Adjusts glow visuals based on score even after the sweep occurs
These sweeps often precede local reversals or high-volatility zones — this is not predictive, but rather a reactive mapping of market manipulation behavior.
📌 Why This Is Not Just Another Liquidity Tool
Unlike typical liquidity heatmaps or S/R indicators, this script includes:
A proprietary significance score instead of fixed rules
Multi-layer glow rendering to reflect level importance visually
Real-time scoring updates as new volume and touches occur
Combined volume × rejection × structure logic to validate stop hunts
Fully customizable detection logic (lookback, wick %, volume filters, max bars, etc.)
This indicator provides a specialized view focused solely on visualizing trap setups — not generic trend signals.
🧪 Usage Recommendations
To get started:
Add the indicator to your chart (volume-enabled instruments only)
Customize detection:
Lookback Period for structure
Penetration % for how far price must sweep
Volume Spike Multiplier
Wick rejection strength
Enable/disable features:
Glow effects
Hunt markers
Score labels
Volume highlights
Watch for:
🔰 Bullish Sweeps (below support)
🚨 Bearish Sweeps (above resistance)
Bright glowing zones = high-liquidity targets
This tool can be used for both confluence and risk assessment, especially around high-impact sessions, liquidation events, or range extremes.
📊 Volume Dependency Notice
⚠️ This indicator requires real volume data to function correctly. On instruments without volume (e.g., synthetic pairs), certain features like spike detection and scoring will be disabled or inaccurate.
🔐 Closed-Source Disclosure
This script is published as invite-only to protect its proprietary scoring, glow mapping, and detection logic. While the full implementation remains confidential, this description outlines all key mechanics and configurable logic for user transparency.
Bounce Zone📘 Bounce Zone – Indicator Description
The "Bounce Zone" indicator is a custom tool designed to highlight potential reversal zones on the chart based on volume exhaustion and price structure. It identifies sequences of candles with low volume activity and marks key price levels that could act as "bounce zones", where price is likely to react.
🔍 How It Works
Volume Analysis:
The indicator calculates a Simple Moving Average (SMA) of volume (default: 20 periods).
It looks for at least 6 consecutive candles (configurable) where the volume is below this volume SMA.
Color Consistency:
The candles must all be of the same color:
Green candles (bullish) for potential downward bounce zones.
Red candles (bearish) for potential upward bounce zones.
Zone Detection:
When a valid sequence is found:
For green candles: it draws a horizontal line at the low of the last red candle before the sequence.
For red candles: it draws a horizontal line at the high of the last green candle before the sequence.
Bounce Tracking:
Each horizontal line remains on the chart until it is touched twice by price (high or low depending on direction).
After two touches, the line is automatically removed, indicating the zone has fulfilled its purpose.
📈 Use Cases
Identify areas of price exhaustion after strong directional pushes.
Spot liquidity zones where institutions might step in.
Combine with candlestick confirmation for reversal trades.
Useful in both trending and range-bound markets for entry or exit signals.
⚙️ Parameters
min_consecutive: Minimum number of consecutive low-volume candles of the same color (default: 6).
vol_ma_len: Length of the volume moving average (default: 20).
🧠 Notes
The indicator does not repaint and is based purely on historical candle and volume structure.
Designed for manual strategy confirmation or support for algorithmic setups.
Cross-Sectional Altcoin Portfolio [BackQuant]Cross-Sectional Altcoin Portfolio
Introducing BackQuant's Cross-Sectional Altcoin Portfolio, a sophisticated trading system designed to dynamically rotate among a selection of major altcoins. This portfolio strategy compares multiple assets based on real-time performance metrics, such as momentum and trend strength, to select the strongest-performing coins. It uses a combination of adaptive scoring and regime filters to ensure the portfolio is aligned with favorable market conditions, minimizing exposure during unfavorable trends.
This system offers a comprehensive solution for crypto traders who want to optimize portfolio allocation based on cross-asset performance, while also accounting for market regimes. It allows traders to compare multiple altcoins dynamically and allocate capital to the top performers, ensuring the portfolio is always positioned in the most promising assets.
Key Features
1. Dynamic Asset Rotation:
The portfolio constantly evaluates the relative strength of 10 major altcoins: SOLUSD, RUNEUSD, ORDIUSD, DOGEUSDT, ETHUSD, ENAUSDT, RAYUSDT, PENDLEUSD, UNIUSD, and KASUSDT.
Using a ratio matrix, the system selects the strongest asset based on momentum and trend performance, dynamically adjusting the allocation as market conditions change.
2. Long-Only Portfolio with Cash Reserve:
The portfolio only takes long positions or remains in cash. The system does not enter short positions, reducing the risk of exposure during market downturns.
A powerful regime filter ensures the system is inactive during periods of market weakness, defined by the Universal Trend Performance Indicator (TPI) and other market data.
3. Equity Tracking:
The script provides real-time visualizations of portfolio equity compared to buy-and-hold strategies.
Users can compare the performance of the portfolio against holding individual assets (e.g., BTC, ETH) and see the benefits of the dynamic allocation.
4. Performance Metrics:
The system provides key performance metrics such as:
Sharpe Ratio: Measures risk-adjusted returns.
Sortino Ratio: Focuses on downside risk.
Omega Ratio: Evaluates returns relative to risk.
Maximum Drawdown: The maximum observed loss from a peak to a trough.
These metrics allow traders to assess the effectiveness of the strategy versus simply holding the assets.
5. Regime Filter:
The system incorporates a regime filter that evaluates the overall market trend using the TPI and other indicators. If the market is in a downtrend, the system exits positions and moves to cash, avoiding exposure to negative market conditions.
Users can customize the thresholds for the long and short trends to fit their risk tolerance.
6. Customizable Parameters:
Traders can adjust key parameters, such as the backtest start date, starting capital, leverage multiplier, and visualization options, including equity plot colors and line widths.
The system supports different levels of customizations for traders to optimize their strategies.
7. Equity and Buy-and-Hold Comparisons:
This script enables traders to see the side-by-side comparison of the portfolio’s equity curve and the equity curve of a buy-and-hold strategy for each asset.
The comparison allows users to evaluate the performance of the dynamic strategy versus holding the altcoins in isolation.
8. Forward Test (Out-of-Sample Testing):
The system includes a note that the portfolio provides out-of-sample forward tests, ensuring the robustness of the strategy. This is crucial for assessing the portfolio's performance beyond historical backtesting and validating its ability to adapt to future market conditions.
9. Visual Feedback:
The system offers detailed visual feedback on the current asset allocation and performance. Candles are painted according to the trend of the selected assets, and key metrics are displayed in real-time, including the momentum scores for each asset.
10. Alerts and Notifications:
Real-time alerts notify traders when the system changes asset allocations or moves to cash, ensuring they stay informed about portfolio adjustments.
Visual labels on the chart provide instant feedback on which asset is currently leading the portfolio allocation.
How the Rotation Works
The portfolio evaluates 10 different assets and calculates a momentum score for each based on their price action. This score is processed through a ratio matrix, which compares the relative performance of each asset.
Based on the rankings, the portfolio allocates capital to the top performers, ensuring it rotates between the strongest assets while minimizing exposure to underperforming assets.
If no asset shows strong performance, the system defaults to cash to preserve capital.
Final Thoughts
BackQuant’s Cross-Sectional Altcoin Portfolio provides a dynamic and systematic approach to altcoin portfolio management. By employing real-time performance metrics, adaptive scoring, and regime filters, this strategy aims to optimize returns while minimizing exposure to market downturns. The inclusion of out-of-sample forward tests ensures that the system remains robust in live market conditions, making it an ideal tool for crypto traders seeking to enhance their portfolio's performance with a data-driven, momentum-based approach.
atr stop loss for double SMA v6Strategy Name
atr stop loss for double SMA v6
Credit: This v6 update is based on Daveatt’s “BEST ATR Stop Multiple Strategy.”
Core Logic
Entry: Go long when the 15-period SMA crosses above the 45-period SMA; go short on the inverse cross.
Stop-Loss: On entry, compute ATR(14)×2.0 and set a fixed stop at entry ± that amount. Stop remains static until hit.
Trend Tracking: Uses barssince() to ensure only one active long or short position; stop is only active while that trend persists.
Visualization
Plots fast/slow SMA lines in teal/orange.
On each entry bar, displays a label showing “ATR value” and “ATR×multiple” positioned at the 30-bar low (long) or high (short).
Draws an “×” at the stop-price level in green (long) or red (short) while the position is open.
Execution Settings
Initial Capital: $100 000, Size = 100 shares per trade.
Commission: 0.075% per trade.
Pyramiding: 1.
Calculations: Only on bar close (no intra-bar ticks).
Usage Notes
Static ATR stop adapts to volatility but does not trail.
Ideal for trending, liquid markets (stocks, futures, FX).
Adjust SMA lengths or ATR multiple for faster/slower signals.
NSE/BSE Derivative - Next Expiry Date With HolidaysNSE & BSE Expiry Tracker with Holiday Adjustments
This Pine Script is a TradingView indicator that helps traders monitor upcoming expiry dates for major Indian derivative contracts. It dynamically adjusts these expiry dates based on weekends and holidays, and highlights any expiry that falls on the current day.
⸻
Key Features
1. Tracks Expiry Dates for Major Contracts
The script calculates and displays the next expiry dates for the following instruments:
• NIFTY (weekly expiry every Thursday)
• BANKNIFTY, FINNIFTY, MIDCPNIFTY, NIFTYNXT50 (monthly expiry on the last Thursday of the month)
• SENSEX (weekly expiry every Tuesday)
• BANKEX and SENSEX 50 (monthly expiry on the last Tuesday of the month)
• Stocks in the F&O segment (monthly expiry on the last Thursday)
2. Holiday Awareness
Users can input a list of holiday dates in the format YYYY-MM-DD,YYYY-MM-DD,.... If any calculated expiry falls on one of these holidays or a weekend, the script automatically adjusts the expiry to the previous working day (Monday to Friday).
3. Customization Options
The user can:
• Choose the position of the expiry table on the chart (e.g. top right, bottom left).
• Select the font size for the expiry table.
• Enable or disable the table entirely (if implemented as an input toggle).
4. Visual Expiry Highlighting
If today is an expiry day for any instrument, the script highlights that instrument in the display. This makes it easy to spot significant expiry days, which are often associated with increased volatility and trading volume.
⸻
How It Works
• The script calculates the next expiry for each index using built-in date/time functions.
• For weekly expiries, it finds the next occurrence of the designated weekday.
• For monthly expiries, it finds the last Thursday or Tuesday of the month.
• Each expiry date is passed through a check to adjust for holidays or weekends.
• If today matches the adjusted expiry date, that row is visually emphasized.
⸻
Use Case
This script is ideal for traders who want a quick glance at which instruments are expiring soon — especially those managing options, futures, or expiry-based strategies.
Mandelbrot-Fibonacci Cascade Vortex (MFCV)Mandelbrot-Fibonacci Cascade Vortex (MFCV) - Where Chaos Theory Meets Sacred Geometry
A Revolutionary Synthesis of Fractal Mathematics and Golden Ratio Dynamics
What began as an exploration into Benoit Mandelbrot's fractal market hypothesis and the mysterious appearance of Fibonacci sequences in nature has culminated in a groundbreaking indicator that reveals the hidden mathematical structure underlying market movements. This indicator represents months of research into chaos theory, fractal geometry, and the golden ratio's manifestation in financial markets.
The Theoretical Foundation
Mandelbrot's Fractal Market Hypothesis Traditional efficient market theory assumes normal distributions and random walks. Mandelbrot proved markets are fractal - self-similar patterns repeating across all timeframes with power-law distributions. The MFCV implements this through:
Hurst Exponent Calculation: H = log(R/S) / log(n/2)
Where:
R = Range of cumulative deviations
S = Standard deviation
n = Period length
This measures market memory:
H > 0.5: Trending (persistent) behavior
H = 0.5: Random walk
H < 0.5: Mean-reverting (anti-persistent) behavior
Fractal Dimension: D = 2 - H
This quantifies market complexity, where higher dimensions indicate more chaotic behavior.
Fibonacci Vortex Theory Markets don't move linearly - they spiral. The MFCV reveals these spirals using Fibonacci sequences:
Vortex Calculation: Vortex(n) = Price + sin(bar_index × φ / Fn) × ATR(Fn) × Volume_Factor
Where:
φ = 0.618 (golden ratio)
Fn = Fibonacci number (8, 13, 21, 34, 55)
Volume_Factor = 1 + (Volume/SMA(Volume,50) - 1) × 0.5
This creates oscillating spirals that contract and expand with market energy.
The Volatility Cascade System
Markets exhibit volatility clustering - Mandelbrot's "Noah Effect." The MFCV captures this through cascading volatility bands:
Cascade Level Calculation: Level(i) = ATR(20) × φ^i
Each level represents a different fractal scale, creating a multi-dimensional view of market structure. The golden ratio spacing ensures harmonic resonance between levels.
Implementation Architecture
Core Components:
Fractal Analysis Engine
Calculates Hurst exponent over user-defined periods
Derives fractal dimension for complexity measurement
Identifies market regime (trending/ranging/chaotic)
Fibonacci Vortex Generator
Creates 5 independent spiral oscillators
Each spiral follows a Fibonacci period
Volume amplification creates dynamic response
Cascade Band System
Up to 8 volatility levels
Golden ratio expansion between levels
Dynamic coloring based on fractal state
Confluence Detection
Identifies convergence of vortex and cascade levels
Highlights high-probability reversal zones
Real-time confluence strength calculation
Signal Generation Logic
The MFCV generates two primary signal types:
Fractal Signals: Generated when:
Hurst > 0.65 (strong trend) AND volatility expanding
Hurst < 0.35 (mean reversion) AND RSI < 35
Trend strength > 0.4 AND vortex alignment
Cascade Signals: Triggered by:
RSI > 60 AND price > SMA(50) AND bearish vortex
RSI < 40 AND price < SMA(50) AND bullish vortex
Volatility expansion AND trend strength > 0.3
Both signals implement a 15-bar cooldown to prevent overtrading.
Advanced Input System
Mandelbrot Parameters:
Cascade Levels (3-8):
Controls number of volatility bands
Crypto: 5-7 (high volatility)
Indices: 4-5 (moderate volatility)
Forex: 3-4 (low volatility)
Hurst Period (20-200):
Lookback for fractal calculation
Scalping: 20-50
Day Trading: 50-100
Swing Trading: 100-150
Position Trading: 150-200
Cascade Ratio (1.0-3.0):
Band width multiplier
1.618: Golden ratio (default)
Higher values for trending markets
Lower values for ranging markets
Fractal Memory (21-233):
Fibonacci retracement lookback
Uses Fibonacci numbers for harmonic alignment
Fibonacci Vortex Settings:
Spiral Periods:
Comma-separated Fibonacci sequence
Fast: "5,8,13,21,34" (scalping)
Standard: "8,13,21,34,55" (balanced)
Extended: "13,21,34,55,89" (swing)
Rotation Speed (0.1-2.0):
Controls spiral oscillation frequency
0.618: Golden ratio (balanced)
Higher = more signals, more noise
Lower = smoother, fewer signals
Volume Amplification:
Enables dynamic spiral expansion
Essential for stocks and crypto
Disable for forex (no central volume)
Visual System Architecture
Cascade Bands:
Multi-level volatility envelopes
Gradient coloring from primary to secondary theme
Transparency increases with distance from price
Fill between bands shows fractal structure
Vortex Spirals:
5 Fibonacci-period oscillators
Blue above price (bullish pressure)
Red below price (bearish pressure)
Multiple display styles: Lines, Circles, Dots, Cross
Dynamic Fibonacci Levels:
Auto-updating retracement levels
Smart update logic prevents disruption near levels
Distance-based transparency (closer = more visible)
Updates every 50 bars or on volatility spikes
Confluence Zones:
Highlighted boxes where indicators converge
Stronger confluence = stronger support/resistance
Key areas for reversal trades
Professional Dashboard System
Main Fractal Dashboard: Displays real-time:
Hurst Exponent with market state
Fractal Dimension with complexity level
Volatility Cascade status
Vortex rotation impact
Market regime classification
Signal strength percentage
Active indicator levels
Vortex Metrics Panel: Shows:
Individual spiral deviations
Convergence/divergence metrics
Real-time vortex positioning
Fibonacci period performance
Fractal Metrics Display: Tracks:
Dimension D value
Market complexity rating
Self-similarity strength
Trend quality assessment
Theory Guide Panel: Educational reference showing:
Mandelbrot principles
Fibonacci vortex concepts
Dynamic trading suggestions
Trading Applications
Trend Following:
High Hurst (>0.65) indicates strong trends
Follow cascade band direction
Use vortex spirals for entry timing
Exit when Hurst drops below 0.5
Mean Reversion:
Low Hurst (<0.35) signals reversal potential
Trade toward vortex spiral convergence
Use Fibonacci levels as targets
Tighten stops in chaotic regimes
Breakout Trading:
Monitor cascade band compression
Watch for vortex spiral alignment
Volatility expansion confirms breakouts
Use confluence zones for targets
Risk Management:
Position size based on fractal dimension
Wider stops in high complexity markets
Tighter stops when Hurst is extreme
Scale out at Fibonacci levels
Market-Specific Optimization
Cryptocurrency:
Cascade Levels: 5-7
Hurst Period: 50-100
Rotation Speed: 0.786-1.2
Enable volume amplification
Stock Indices:
Cascade Levels: 4-5
Hurst Period: 80-120
Rotation Speed: 0.5-0.786
Moderate cascade ratio
Forex:
Cascade Levels: 3-4
Hurst Period: 100-150
Rotation Speed: 0.382-0.618
Disable volume amplification
Commodities:
Cascade Levels: 4-6
Hurst Period: 60-100
Rotation Speed: 0.5-1.0
Seasonal adjustment consideration
Innovation and Originality
The MFCV represents several breakthrough innovations:
First Integration of Mandelbrot Fractals with Fibonacci Vortex Theory
Unique synthesis of chaos theory and sacred geometry
Novel application of Hurst exponent to spiral dynamics
Dynamic Volatility Cascade System
Golden ratio-based band expansion
Multi-timeframe fractal analysis
Self-adjusting to market conditions
Volume-Amplified Vortex Spirals
Revolutionary spiral calculation method
Dynamic response to market participation
Multiple Fibonacci period integration
Intelligent Signal Generation
Cooldown system prevents overtrading
Multi-factor confirmation required
Regime-aware signal filtering
Professional Analytics Dashboard
Institutional-grade metrics display
Real-time fractal analysis
Educational integration
Development Journey
Creating the MFCV involved overcoming numerous challenges:
Mathematical Complexity: Implementing Hurst exponent calculations efficiently
Visual Clarity: Displaying multiple indicators without cluttering
Performance Optimization: Managing array operations and calculations
Signal Quality: Balancing sensitivity with reliability
User Experience: Making complex theory accessible
The result is an indicator that brings PhD-level mathematics to practical trading while maintaining visual elegance and usability.
Best Practices and Guidelines
Start Simple: Use default settings initially
Match Timeframe: Adjust parameters to your trading style
Confirm Signals: Never trade MFCV signals in isolation
Respect Regimes: Adapt strategy to market state
Manage Risk: Use fractal dimension for position sizing
Color Themes
Six professional themes included:
Fractal: Balanced blue/purple palette
Golden: Warm Fibonacci-inspired colors
Plasma: Vibrant modern aesthetics
Cosmic: Dark mode optimized
Matrix: Classic green terminal
Fire: Heat map visualization
Disclaimer
This indicator is for educational and research purposes only. It does not constitute financial advice. While the MFCV reveals deep market structure through advanced mathematics, markets remain inherently unpredictable. Past performance does not guarantee future results.
The integration of Mandelbrot's fractal theory with Fibonacci vortex dynamics provides unique market insights, but should be used as part of a comprehensive trading strategy. Always use proper risk management and never risk more than you can afford to lose.
Acknowledgments
Special thanks to Benoit Mandelbrot for revolutionizing our understanding of markets through fractal geometry, and to the ancient mathematicians who discovered the golden ratio's universal significance.
"The geometry of nature is fractal... Markets are fractal too." - Benoit Mandelbrot
Revealing the Hidden Order in Market Chaos Trade with Mathematical Precision. Trade with MFCV.
— Created with passion for the TradingView community
Trade with insight. Trade with anticipation.
— Dskyz , for DAFE Trading Systems
Algo BOT 3.0Algo BOT 3.0 is a sophisticated, rule-based intraday trading strategy designed for index option traders who seek high-probability entries based on market structure, institutional zones, and controlled risk management. This strategy intelligently identifies BUY and SELL trade opportunities using price action, Fibonacci retracements, and pivot confluences, layered with dynamic trade management through trailing stop loss (TSL) and predefined profit/loss thresholds.
🔍 Strategic Foundation
Algo BOT 3.0 combines multiple proven intraday trading concepts into a single unified system:
Candle Behavior Analysis:
Detects strong green (bullish) and red (bearish) candles based on configurable range filters, wick/body ratios, and volume-backed movement.
Ensures only impactful candles are considered for signal generation, filtering out noise.
Dynamic Candle Range Filtering:
Filters out low-momentum candles by comparing their range against a dynamically calculated threshold (based on recent 30-minute close).
Prevents premature or weak entries by focusing on high-volatility structures.
Fibonacci Entry Zones:
Automatically calculates 0.382 and 0.618 Fibonacci levels between the most recent key candles (highest green & lowest red).
These fib levels are used to define entry zones for BUY (above red fib 0.382) and SELL (below green fib 0.382).
Optional fib zones can be visually shown on the chart with real-time drawing.
📈 Signal Generation Logic
The core BUY/SELL signals are triggered based on a combination of:
Green/Red Candle Identification:
A green candle qualifies if:
Open is near the bottom 38.2% of its range.
Close is above the top 61.8% of the range.
High is above a pivot or institutional level.
A red candle qualifies if:
Open is near the top 38.2% of its range.
Close is below the bottom 61.8% of the range.
Low is below a pivot or institutional level.
Support/Resistance Touch Confirmation:
Signals are only considered valid if the qualifying candle touches:
CPR Top/Bottom
Daily Pivot Points (PP, R1–R4, S1–S4)
VWAP or MVWAP
CE Entry (BOT BUY):
Occurs when the price crosses above red fib 0.382 after red candle touch at support.
PE Entry (BOT SELL):
Occurs when the price crosses below green fib 0.382 after green candle touch at resistance.
Signal Controls:
Only one active signal per type (BUY/SELL) at a time.
Real-time tracking of active trade with condition-based resets.
🎯 Exit Management
Built-in risk and profit control with dynamic logic:
Trailing Stop Loss (TSL):
TSL is dynamically adjusted based on peak price after entry.
Trail distance is customizable via input (% below peak).
Visual alerts notify when TSL is hit.
Profit Target:
Trade exits automatically when desired % profit is achieved from entry.
Loss Limit:
Trade exits immediately if unrealized loss exceeds a set % threshold.
Helps prevent large drawdowns during volatile market moves.
🧠 Technical Indicator Integration
To enhance trade accuracy, the strategy includes several optional filters:
RSI: Momentum confirmation or divergence filtering.
SMA/EMA: Trend direction confirmation.
MVWAP: Modified VWAP for smoother institutional bias tracking.
🖼️ Visuals & Alerts
BOT BUY and BOT SELL Signal Labels appear directly on the chart with trade type and candle reference.
TSL, Target, and SL Exits shown as label markers with optional background highlight.
Live Alerts:
BOT BUY (CE Entry)
BOT SELL (PE Entry)
Trailing Stop Loss Triggered
Profit Target Hit
Stop Loss Triggered
⚙️ Customizable Settings
Users can fine-tune the strategy using the following input options:
MVWAP Length
RSI / SMA / EMA Lengths
Candle Range Sensitivity
TSL Distance (%)
Profit Target (%)
Loss Limit (%)
Enable/Disable Background Highlights & Labels
Display Fib Zones
⏱️ Best Use Case & Timeframes
Multi-Layer Volume Profile [BigBeluga]A powerful multi-resolution volume analysis tool that stacks multiple profiles of historical trading activity to reveal true market structure.
This indicator breaks down total and delta volume distribution across time at four adjustable depths — enabling traders to spot major POCs, volume shelves, and zones of price acceptance or rejection with unmatched clarity.
🔵 KEY FEATURES
Multi-Layer Volume Profiles:
Up to 4 separate volume profiles are stacked on the chart:
- Profile 1: Full period
- Profile 2: Half-length
- Profile 3: Quarter-length
- Profile 4: One-eighth-length
This layering helps traders assess confluence across different time horizons.
Custom Bin Resolution:
Each profile uses a customizable number of bins to control visual precision.
More bins = higher granularity, fewer bins = smoother profile.
Precise POC Highlighting:
The price level with the maximum traded volume in each profile is highlighted with a thick blue POC line.
This key level shows the most accepted price for each period.
Total and Delta Volume Labels:
- Total Volume: Displays cumulative volume over the profile period at the top of the profile box.
- Delta Volume: The difference between bullish and bearish volume is labeled at the base, showing directional pressure.
Positive delta = buyer dominance, negative delta = seller dominance.
Range Levels:
Each profile includes horizontal reference lines showing its high, low, bounds.
These edges often align with price reaction zones and become future resistance/support.
🔵 HOW IT WORKS
For each active profile, the indicator:
- Collects price range (highs/lows) across the selected `length`
- Divides this range into equal bins
- Assigns volume into bins based on candle close location
- Aggregates volume per bin to form the profile (polylines)
Separately tracks:
- Total volume (sum of all candles in range)
- Delta volume (sum of candle volumes: positive for bullish, negative for bearish closes)
Highlights the bin with maximum volume (POC)
and marks it with a thick blue line.
Adds auxiliary lines for high/low of each profile box
and total/delta volume tags with tooltips.
🔵 USAGE
Spot Acceptance Zones:
Thick, flat areas on the profile show where price stayed longest — ideal for building positions.
Identify Rejection Zones:
Thin volume areas signal price rejection and are often used for stop placement or entries.
Delta Confirmation:
Use strong positive/negative delta readings as directional bias confirmation for breakout trades.
Confluence Detection:
Watch for overlapping POCs between layers to identify extremely strong support/resistance zones.
🔵 CONCLUSION
Multi-Layer Volume Profile equips traders with a deeply layered market structure view.
Whether you're scalping intraday levels or analyzing macro support zones, the ability to stack volume perspectives, visualize directional delta, and anchor POCs provides an edge in anticipating market moves.
Use this tool to validate entries, confirm structure, and make more informed, volume-aware trading decisions.
MC High/LowMC High/Low is a minimalist precision tool designed to show traders the most critical price levels — the High and Low of the current Day and Week — in real-time, without any visual clutter or historical trails.
It automatically tracks:
🔼 HOD – High of Day
🔽 LOD – Low of Day
📈 HOW – High of Week
📉 LOW – Low of Week
Each level is plotted using simple black horizontal lines, updated dynamically as the session evolves. Labels are clearly marked and positioned to the right of the screen for easy reference.
There’s no trailing history, no background colors, and no distractions — just pure price structure for clean confluence.
Perfect for:
Intraday scalpers
Swing traders
Liquidity & range traders
This is a tool built for sniper-level execution — straight from the MadCharts mindset.
🛠 Created by:
🔒 Version: Public Release
🎯 Use this with your favorite price action, liquidity, or market structure strategies.
Adaptive Signal OracleAdaptive Signal Oracle – Precision Forecasting with Weighted KNN & HMA Trend Logic
🔍 Overview
Adaptive Signal Oracle is a forward-looking trend prediction strategy that merges non-repainting technical analysis with a machine-learning-inspired forecasting model. Built from scratch, it is not a mashup of off-the-shelf indicators. Instead, it uses a handcrafted K-Nearest Neighbors (KNN)-style prediction engine combined with a classic HMA (Hull Moving Average) trend filter to deliver actionable, high-confidence entries.
📈 Core Components Explained
🔸 1. KNN-Weighted Future Predictor (Custom Engine)
Simulates a machine learning process using historical price behavior.
Compares current conditions to a rolling dataset of past feature/label pairs.
Assigns weights based on distance, forming a probabilistic directional bias.
Generates:
Prediction Probability (% confidence)
Expected Price Movement Magnitude
Dynamic Trade Targets (TP1/TP2)
🔸 2. HMA Trend Filter (Hull Moving Average)
Used for real-time trend confirmation.
Prevents entry during whipsaws by enforcing directional alignment.
Non-repainting and adaptive to volatility swings.
🔸 3. Risk-Managed Execution Logic
Built-in 2-level take-profit system:
TP1: Partial exit (50%)
TP2: Full exit (remaining 100%)
Hard-coded stop-loss at a configurable percentage (default: 2%)
Includes cooldown logic to prevent same-bar entries and exits
🔸 4. Integrated Visual Dashboard
Tracks:
Trade status
Entry price
TP/SL hits
Trend direction
Real-time PnL
Dashboard is resizable and repositionable for user control
🔸 5. Clean Bar Coloring
Highlights predicted direction with green (bullish) and red (bearish) candles
Enhances signal visibility without interfering with price action
⚠️ Important Notes
This script does not repaint.
All calculations are based on confirmed historical data, using bar-closed logic only.
Ideal for crypto, forex, and trending asset classes, especially on the 1H+ timeframes.
Not intended for use as financial advice or automated investment decision-making.
🧠 How to Use
Set desired TP/SL levels in the strategy inputs.
Adjust k-value and lookback for best fit with your instrument.
Monitor the dashboard and colored bars for trade entries.
Use as part of a broader system with structure, support/resistance, or volume confirmation if needed.
🛡️ Disclaimer
This script is for educational and informational purposes only. It does not constitute financial advice. Past performance does not guarantee future results. Always test on historical data and demo environments before applying to live trading. The author is not liable for any financial decisions made based on this script.