FOMC Sweep Reaction AP Capital – FOMC Sweep Reaction v1.0
AP Capital – FOMC Sweep Reaction v1.0 is a news-reaction and liquidity-based trading tool designed specifically to track and trade FOMC volatility on Gold (XAUUSD) and other highly reactive instruments.
The indicator focuses on liquidity sweeps, structure breaks, and EMA reclaims that commonly occur around Federal Reserve interest-rate decisions and Powell speeches, helping traders identify high-probability reversal or continuation moves after the initial spike.
🔍 What This Indicator Detects
This tool highlights the most repeatable FOMC behaviours observed across multiple months of broker data:
• Sweeps of previous day’s high or low
• Stop-hunt wicks into liquidity pools
• EMA13 reclaim after the news spike
• Break and close beyond short-term structure
• Momentum shift following volatility exhaustion
The goal is not to predict the news, but to react to confirmed price behaviour after liquidity has been taken.
📌 Core Features
• FOMC Sweep Detection
Identifies aggressive wicks into prior highs/lows during news volatility
• EMA Reclaim Confirmation
Uses EMA13 to validate momentum shift after the sweep
• Market Structure Awareness
Filters reactions that fail to break structure to avoid false reversals
• Session-Aligned Logic
Designed around London → NY → FOMC release timing
• Clean Visuals
Minimal chart clutter for fast decision-making during volatile conditions
🧠 How to Use
Wait for FOMC release / Powell speech
Allow price to sweep previous liquidity (PDH / PDL / local extremes)
Observe reclaim of EMA13
Enter only after structure confirmation
Manage trade using EMA trailing or structure-based exits
⚠️ This is a reaction system, not a prediction tool.
📊 Best Use Cases
• XAUUSD (Gold)
• NASDAQ / US indices
• High-impact macro news events
• 5-min to 15-min timeframes
⚠️ Important Notes
• News volatility is extreme — risk management is essential
• Not designed for low-volatility or ranging markets
• Best combined with a clear trading plan and strict risk rules
📎 Disclaimer
This indicator is for educational purposes only and does not constitute financial advice. Trading during high-impact news events involves significant risk.
Search in scripts for "GOLD"
Zee's A+ MOMO BreakThis just shows an indicator when you have a 5 minute momentum candle that breaks PMH under specific parameters, i.e candle size, wick size, relative volume, time of day, etc. It will plot the PMH with a gold line automatically. Entry would be at the close of the MOMO break. I highly encourage you to back test your results and see how strong this setup is. Any questions feel free to comment or reach out, thanks.
able FRVP Reversal# able FRVP Reversal - Complete User Guide
## 📌 Overview
**able FRVP Reversal** is a professional-grade Volume Profile indicator with an integrated reversal detection system. It combines Fixed Range Volume Profile (FRVP) analysis with a confluence-based reversal scoring system to identify high-probability turning points at key volume levels.
---
## ✨ Key Features
| Feature | Description |
|---------|-------------|
| **Session-Based Volume Profile** | Automatically resets at the beginning of each regular trading session |
| **POC (Point of Control)** | Highest volume price level - strongest support/resistance |
| **VAH (Value Area High)** | Upper boundary of the 70% value area - resistance zone |
| **VAL (Value Area Low)** | Lower boundary of the 70% value area - support zone |
| **Confluence Scoring System** | 5-point scoring system for reversal detection |
| **Smart Cooldown** | Prevents signal spam with customizable cooldown period |
| **Real-time Info Table** | Displays all key metrics in a retro-style dashboard |
---
## 🔧 Installation
1. Open TradingView and go to **Pine Editor**
2. Delete any existing code and paste the indicator code
3. Click **"Add to Chart"**
4. Configure settings as needed
---
## ⚙️ Settings Explained
### 📊 Volume Profile Settings
| Setting | Default | Description |
|---------|---------|-------------|
| **Number of Rows** | 50 | Resolution of the volume profile (more rows = finer detail) |
| **Value Area %** | 70 | Percentage of volume to include in Value Area (industry standard: 70%) |
| **Profile Width** | 40 | Visual width of the histogram on chart |
| **Show Histogram** | ✓ | Display volume histogram bars |
| **Show POC/VAH/VAL** | ✓ | Display the three key levels |
| **Show Labels** | ✓ | Display price labels for each level |
| **Extend Lines** | ✓ | Extend levels to the right of current price |
| **Extend Length** | 100 | How far to extend the lines (in bars) |
### 🔄 Reversal Detection Settings
| Setting | Default | Description |
|---------|---------|-------------|
| **Enable Reversal Detection** | ✓ | Turn reversal signals on/off |
| **Min Confluence Score** | 3 | Minimum score required to trigger signal (1-5) |
| **Cooldown Bars** | 10 | Minimum bars between signals to prevent spam |
#### Understanding Min Confluence Score:
- **Score 1-2**: Very sensitive, many signals (not recommended)
- **Score 3**: Balanced - good for most traders ⭐ Recommended
- **Score 4**: Conservative - fewer but higher quality signals
- **Score 5**: Very strict - only strongest reversals
### 🎨 Color Settings
All colors are fully customizable:
- **POC Line**: Default Gold (#FFD700)
- **VAH Line**: Default Coral Red (#FF6B6B)
- **VAL Line**: Default Teal (#4ECDC4)
- **Bullish Reversal**: Default Green (#00E676)
- **Bearish Reversal**: Default Red (#FF5252)
---
## 📖 How to Read the Indicator
### Volume Profile Histogram
```
█████████████ ← High volume = Strong S/R
████████ ← Medium volume
████ ← Low volume = Weak S/R
██
```
- **Darker/Longer bars** = More trading activity at that price
- **Inside Value Area** = Colored based on session direction (Bull/Bear)
- **Outside Value Area** = Muted gray color
### Key Levels
| Level | Color | Meaning |
|-------|-------|---------|
| **POC** | Yellow | Price with highest volume - Strongest magnet |
| **VAH** | Red | Upper resistance - Look for bearish reversals |
| **VAL** | Teal | Lower support - Look for bullish reversals |
---
## 🔄 Reversal Detection System
### How the Scoring System Works
The indicator uses a **5-point confluence scoring system**. Each condition adds 1 point:
#### 🟢 Bullish Reversal Score (at VAL)
| Condition | Points | Description |
|-----------|--------|-------------|
| Price at VAL Zone | +1 | Price is within VAL ± 0.2 ATR |
| Bullish Candle | +1 | Close > Open (green candle) |
| RSI Oversold | +1 | RSI < 35 |
| Rejection Wick | +1 | Lower wick > 1.5× body size |
| Failed Breakdown | +1 | Touched below VAL but closed above |
#### 🔴 Bearish Reversal Score (at VAH)
| Condition | Points | Description |
|-----------|--------|-------------|
| Price at VAH Zone | +1 | Price is within VAH ± 0.2 ATR |
| Bearish Candle | +1 | Close < Open (red candle) |
| RSI Overbought | +1 | RSI > 65 |
| Rejection Wick | +1 | Upper wick > 1.5× body size |
| Failed Breakout | +1 | Touched above VAH but closed below |
### Signal Quality Ratings
| Score | Rating | Meaning |
|-------|--------|---------|
| 5/5 | ★★★ | Excellent - Highest probability |
| 4/5 | ★★ | Good - High probability |
| 3/5 | ★ | Acceptable - Moderate probability |
| <3 | - | No signal triggered |
---
## 📋 Info Table Explained
```
╔═ able-REV ═╗ 15 ████████ SCR
─────────────────────────────────────
ZONE UPPER VA ▒▒▓▓████ ▲
POC 4272.680 ██████·· ▲
VAH 4322.745 ████···· ·
VAL 4264.977 ██████·· ·
═ SCORE ═════════════════════════════
BULL 0/5 ········ ·
BEAR 1/5 ░······· ·
RSI 49 ▒▒▓▓···· ·
◄SIGNAL► WAIT ········ ·
```
| Row | Description |
|-----|-------------|
| **ZONE** | Current price position relative to Value Area |
| **POC/VAH/VAL** | Price levels with distance indicators |
| **BULL Score** | Current bullish confluence score |
| **BEAR Score** | Current bearish confluence score |
| **RSI** | RSI value with OB/OS status |
| **SIGNAL** | Current signal status (BUY/SELL/WAIT) |
### Zone Types
| Zone | Meaning | Bias |
|------|---------|------|
| ABOVE VAH | Price broke above resistance | Bullish (but watch for rejection) |
| ⚠ AT VAH | Price testing resistance | Watch for bearish reversal |
| UPPER VA | Price in upper value area | Slight bullish bias |
| LOWER VA | Price in lower value area | Slight bearish bias |
| ⚠ AT VAL | Price testing support | Watch for bullish reversal |
| BELOW VAL | Price broke below support | Bearish (but watch for rejection) |
---
## 📈 Trading Strategies
### Strategy 1: VAH Rejection (Bearish Reversal)
**Setup:**
1. Price approaches or touches VAH (red dashed line)
2. BEAR score reaches 3+ (or your minimum setting)
3. REV signal appears above the candle
**Entry:**
- Enter SHORT on signal candle close
- Or wait for confirmation candle
**Stop Loss:**
- Above the signal candle high
- Or above VAH + 0.5 ATR
**Take Profit:**
- First target: POC (yellow line)
- Second target: VAL (teal line)
---
### Strategy 2: VAL Bounce (Bullish Reversal)
**Setup:**
1. Price approaches or touches VAL (teal dashed line)
2. BULL score reaches 3+ (or your minimum setting)
3. REV signal appears below the candle
**Entry:**
- Enter LONG on signal candle close
- Or wait for confirmation candle
**Stop Loss:**
- Below the signal candle low
- Or below VAL - 0.5 ATR
**Take Profit:**
- First target: POC (yellow line)
- Second target: VAH (red line)
---
### Strategy 3: POC Bounce
**Setup:**
1. Price pulls back to POC after trending
2. POC acts as support/resistance
3. Watch for reversal candle patterns
**Entry:**
- Long if bullish candle at POC from below
- Short if bearish candle at POC from above
**Stop Loss:**
- Other side of POC ± buffer
---
## ⚠️ Important Notes
### When Signals Work Best
✅ **High Probability Setups:**
- Score 4-5 with clear rejection wick
- RSI confirms (oversold for long, overbought for short)
- First test of VAH/VAL in the session
- Clear trend before reversal
❌ **Low Probability Setups:**
- Score barely meeting minimum (3/5)
- Multiple tests of same level (level weakening)
- Low volume/choppy market
- News events pending
### Risk Management Rules
1. **Never risk more than 1-2% per trade**
2. **Always use stop loss** - place beyond the level
3. **Wait for candle close** - don't enter on wick touches
4. **Respect the cooldown** - avoid overtrading
5. **Consider the trend** - counter-trend reversals are riskier
---
## 🔔 Alerts
The indicator includes built-in alerts:
| Alert | Trigger |
|-------|---------|
| VAL Bullish Reversal | BULL score meets minimum at VAL |
| VAH Bearish Reversal | BEAR score meets minimum at VAH |
### Setting Up Alerts:
1. Right-click on the chart
2. Select "Add Alert"
3. Choose "able FRVP Reversal" as condition
4. Select desired alert type
5. Configure notification method
---
## 💡 Pro Tips
1. **Combine with trend analysis** - Reversals in trend direction are more reliable
2. **Watch for confluence with other S/R** - If VAH/VAL aligns with round numbers, previous highs/lows, or fib levels, the level is stronger
3. **Volume confirmation** - Higher volume on reversal candle = stronger signal
4. **Time of day matters** - Reversals during active trading hours are more reliable
5. **Adjust sensitivity by market** - Volatile assets may need higher Min Confluence Score
6. **Use multiple timeframes** - Check if reversal level aligns with higher timeframe levels
---
## 🔧 Recommended Settings by Trading Style
| Style | Min Confluence | Cooldown | Best For |
|-------|----------------|----------|----------|
| Scalping | 3 | 5-7 | Quick trades, more signals |
| Day Trading | 3-4 | 10-15 | Balanced approach |
| Swing Trading | 4-5 | 20+ | Fewer, higher quality signals |
---
## ❓ Troubleshooting
| Issue | Solution |
|-------|----------|
| No signals appearing | Lower Min Confluence Score or check if market is ranging |
| Too many signals | Increase Min Confluence Score or Cooldown Bars |
| Levels not showing | Enable Show POC/VAH/VAL in settings |
| Histogram too wide/narrow | Adjust Profile Width setting |
---
## 📞 Support
For questions, suggestions, or bug reports, please contact the developer.
---
**Version:** 1.0
**Last Updated:** 2024
**Platform:** TradingView (Pine Script v6)
VixTrixVixTrix - Because markets move in both directions.
VixTrix was born from a fundamental limitation in traditional volatility indicators: they only measure downside panic, completely missing the greed-driven extremes that form market tops.
How It Works:
Dual-Component Analysis:
vixBear = Panic selling intensity (distance from recent highs)
vixBull = FOMO buying intensity (distance from recent lows)
Oscillator = vixBear - vixBull = Net fear/greed imbalance
When the oscillator is positive, fear dominates (potential bottom forming). When negative, greed dominates (potential top forming).
Professional-Grade Filtering:
The magic happens with the symmetric RMS (Root Mean Square) bands. Unlike fixed percentage bands or standard deviation, RMS:
Creates mathematically symmetric positive/negative thresholds
Naturally adapts to changing volatility regimes
Provides statistical significance to extremes
VixTrix also adds selectable MA smoothing for the RMS calculation:
WMA (default): Balanced – middle-ground approach
VWMA: Volume-weighted – filters low-volume noise
EMA: Responsive – catches quick reversals
SMA: Stable – for swing trading
HMA: Fast and smooth – ideal for day trading
Signals require triple confirmation:
Statistical Extreme: Oscillator beyond RMS band
Price Action Confirmation: Correct candle color (bullish for bottoms, bearish for tops)
Momentum Continuation: Oscillator still moving toward extreme (exhaustion)
This multi-filter approach reduces premature entries and false signals while maintaining early positioning at potential reversal points.
Why This Matters for Your Trading:
In bull markets, traditional fear indicators sit near zero, giving no warning of impending tops.
VixTrix identifies when greed becomes excessive – when FOMO buying reaches statistical extremes that often precede corrections.
In range-bound markets, VixTrix excels at identifying overreactions in both directions, providing high-probability mean reversion opportunities.
During crashes, it captures the panic selling with the same precision as VixFix, but with better timing through its momentum confirmation.
VixTrix spots continuations through:
"No Signal" = Healthy Trend – Oscillator stays between RMS bands (no exhaustion)
Failed Extremes – Touches band but no triple confirmation = trend likely continues
Hidden Divergence – Price makes higher low while oscillator makes shallower low = uptrend continues
Controlled Emotions – Oscillator negative but not extreme in uptrends (greed present but not excessive)
Key Insight: When VixTrix doesn't give a signal during a pullback, institutions aren't panicking – they're just pausing before resuming the trend.
Green columns = Bullish exhaustion (potential bottoms)
Red columns = Bearish exhaustion (potential tops)
Golden RMS bands = Dynamic thresholds adapting to current volatility
Background highlights = Active signal conditions
The Result: A professional-grade oscillator that works in all market conditions – trending up, trending down, or ranging – by measuring the complete emotional spectrum driving price action.
Optimal Daily MA Suite [MTF]Title: Optimal Daily MA Suite
Description: This is a comprehensive Multi-Timeframe (MTF) analysis suite designed to streamline chart layouts. Instead of loading multiple separate indicators to track various trend lines, this single tool allows traders to overlay higher-timeframe Moving Averages and key support/resistance levels directly onto their intraday charts.
Utility & Workflow: Swing traders and day traders often need to monitor "Big Picture" Daily Moving Averages (like the Daily 200 SMA or Daily 50 EMA) while executing trades on lower timeframes like the 15m or 1H. This tool automates that process, ensuring the major trend context is always visible without cluttering the indicator list.
Key Features:
Multi-Timeframe Engine: By default, all MAs are calculated on the Daily ("D") timeframe, regardless of the chart's current timeframe. This creates a stable "anchor" for trend analysis. The timeframe is fully customizable in the settings (e.g., set to "W" for Weekly analysis).
10 Customizable Slots: Toggle up to 10 different Moving Averages on/off individually.
Flexible Calculation Types: Supports SMA, EMA, WMA, VWMA, RMA (SMMA), and SWMA for every single line.
Trend Cloud Crossovers: Includes two dedicated "Cloud" setups to visualize crossovers (e.g., Golden Cross or Death Cross) with fill shading between the fast and slow lines.
Price Action Crossovers: Optional markers to highlight when the closing price crosses specific MAs.
Contextual Levels: Includes Previous Day High (PDH) and Previous Day Low (PDL) markers for immediate intraday support/resistance context.
How to Use:
Settings: Open the settings menu to select your "Indicator Timeframe" (Default: Daily).
Customization: Enable only the MAs relevant to your strategy (e.g., Enable MA 8 for the 50 SMA and MA 10 for the 200 SMA).
Clouds: Use the "Crossover Set" inputs to define a Bullish/Bearish trend cloud between two moving averages of your choice.
Technical Note: This script uses request.security with lookahead=barmerge.lookahead_off to ensure no repainting of historical data while providing accurate higher-timeframe values on closed bars.
Credits: Standard Moving Average calculations based on TradingView built-in functions.
XAUUSD Psychological Key Levels (v6)Unlock the key price levels of XAU/USD with precision! This indicator identifies critical support and resistance zones, helping traders spot high-probability entries and exits. Designed for both swing and intraday trading, it provides clear visual cues to navigate gold’s volatility.
BALANCED Strategy: Intraday Pro + Smart DashboardWelcome to the BALANCED Strategy: Intraday Pro.
This all-in-one indicator is designed for Intraday traders looking to capture trend movements while effectively filtering out sideways market noise. It combines the power of Supertrend for direction, EMA 100 for the baseline trend, and rigorous validation via RSI and ADX.
The script also integrates a complete Risk Management system with targets based on the Golden Ratio (Fibonacci) and a real-time Dashboard.
⏳ Recommended Timeframes
This algorithm is optimized for Intraday volatility:
M5 (5 Minutes) ⭐️: Ideal for quick Scalping. The ADX filter is crucial here to avoid false signals.
M15 (15 Minutes) 🏆: The "Sweet Spot." It offers the best balance between signal frequency and trend reliability.
M30 / H1: For a "Swing Intraday" approach—calmer, fewer signals, but higher precision.
Not recommended for M1 (1 Minute) with default settings (too much noise).
🚀 How It Works
The algorithm follows a strict 3-step logic to generate high-quality signals:
1. Trend Identification (The Engine)
Supertrend: Determines the immediate direction.
EMA 100: Acts as a background trend filter. We only buy above and sell below the EMA.
2. Noise Filtering (Safety)
ADX (Average Directional Index): The signal is only validated if there is sufficient volatility (Configurable threshold, default 12) to avoid "chop markets" (flat markets).
RSI (Relative Strength Index): Strict momentum filter. Buy only if RSI > 50, Sell if RSI < 50.
3. Entry Confirmation (The Trigger)
The script doesn't just rely on a crossover. It waits for "Price Action" confirmation: the candle must close higher than the previous one (for Long) or lower (for Short) to validate the entry.
🛡️ Risk Management (Money Management)
This is the core strength of this tool. Upon signal validation, the script automatically calculates and plots:
Stop Loss (SL): Based on volatility (ATR). It places the stop at the recent Low/High with a safety padding.
Take Profit (TP): Two modes available:
Fibonacci Mode (Default): Targets the 1.618 extension (Golden Ratio) of the risk taken.
Fixed Ratio Mode: Targets a manual Risk/Reward ratio (e.g., 2.0).
📊 The Dashboard
Located at the bottom right, the smart dashboard provides vital info at a glance:
Signal Time: To check if the alert is fresh.
Type (LONG/SHORT): Color-coded (Green/Pink).
Tech Data: RSI and ADX values at the moment of the signal.
Exact Prices: Entry Level, Target (TP), and Stop Loss (SL).
⚙️ Configurable Settings
Sensitivity: Adjust the Supertrend factor (Default 2.0).
Filters: Toggle the RSI filter ON/OFF or adjust the ADX threshold.
Execution: Choose between Fibonacci Target (1.618) or a Manual Ratio.
⚠️ Disclaimer: This tool is a technical decision aid and does not constitute financial investment advice. Always use prudent risk management and backtest the indicator on your preferred assets before live use.
Smart Money Alpha Signals (Performance Dashboard) Smart Money Alpha Signals: Identifying Market Leaders & Generating Alpha
GMP Alpha Signals (Global Market Performance Alpha) is a specialized analysis tool designed not merely to find stocks that are rising, but to identify "Alpha" assets—Market Leaders that defend their price or rise even under adverse conditions where the market index falls or consolidates.
This indicator visualizes the concept of Comparative Relative Strength (RS) and Smart Money accumulation patterns, helping traders capture profit opportunities even during bearish market phases.
Key Objectives (Purpose)
Alpha Capture: Identifying assets generating 'excess returns' that outperform the market Beta.
Smart Money Tracking: Detecting traces of 'institutional buying' and 'accumulation' that defend prices during index plunges.
Decoupling Identification: Spotting assets moving on independent catalysts or momentum, regardless of the broader market direction.
Stop Hunt Filtering: Distinguishing 'fake drops' where price dips temporarily, but Relative Strength remains intact.
Dashboard Guide
Interpretation of the information panel (Table) displayed on the chart.
Rel. Performance: Shows the excess return compared to the index over the set period. (Positive/Green = Stronger than the market).
Decoupling Strength: The correlation coefficient with the index. Lower values (0 or negative) indicate movement independent of market risk.
Bullish: The count/rate of rising or limiting losses when the index drops sharply (e.g., < -0.5%). (Gold = Market Crash Leader).
Defended: The count/rate of holding support levels when the index shows mild weakness (e.g., < -0.05%). (Gold = Strong Accumulation).
Bench. Defense: The defense rate of the comparison benchmark (e.g., TSLA, ETH). Your target asset must be higher to be considered the sector leader.
Input Options & Settings Guide
You can optimize settings according to your trading style and asset class (Stocks/Crypto).
(1) Main Settings
Major Index: The baseline market index for comparison.
(US Stocks: NASDAQ:NDX or TVC:SPX / Crypto: BINANCE:BTCUSDT)
Benchmark Symbol: A competitor within the sector.
(e.g., Set NVDA when analyzing Semiconductor stocks).
Correlation Lookback: The lookback period for judging decoupling. (Default: 30)
Performance Lookback: The number of bars to calculate cumulative returns and defense rates. (Default: 60)
(2) Dashboard Thresholds
These settings define the criteria for what qualifies as "Defended" or "Bullish".
Performance (Max %): Used to find assets that haven't pumped yet. Signals trigger only when Alpha is below this value.
Defended Logic:
Index Drop Condition: The index must drop by at least this amount to start checking. (e.g., -0.05%)
Asset Buffer: How much the asset must outperform the index drop.
(Example: If Index drops -1.0% and Buffer is 0.2%, the asset must be at least -0.8% to count as 'Defended').
Bullish Logic: Measures resilience during steeper market dumps (e.g., -0.5% drop) compared to the Defended Logic.
Volume Settings: Decides whether to count Defended/Bullish instances only when accompanied by volume above the SMA.
(3) Signal Logic Settings (Crucial)
Customize conditions to trigger alerts. The choice between AND / OR is crucial.
AND: Condition must be met SIMULTANEOUSLY with other active conditions (Conservative/High Certainty).
OR: Condition triggers the signal INDEPENDENTLY (Aggressive/Opportunity Capture).
Performance: Is the relative performance within the threshold? (Basic Filter).
Decoupling: Has the correlation dropped? (Start of independent move).
Bullish Rate: Is the Bullish rate high during market dumps?
Defended Rate (High): (Recommended) Is there continuous price defense occurring? (Accumulation detection).
Defended Rate (Low): (Warning) Has the defense rate broken down? (For Stop Loss).
Defended > Benchmark: Is it stronger than the Benchmark (2nd tier)?
Volume Spike: Has volume surged compared to the average? (Institutional involvement).
RSI Oversold: Is it in oversold territory? (Counter-trend trading).
Decoupling Move: Does the current bar show the "Index Down / Asset Up" pattern?
Min USD Volume: Transaction value filter (To exclude low liquidity assets).
The Reaper WhistleThe Reaper Whistle is a high-precision RSI momentum system engineered for scalpers and intraday traders.
It combines a customizable RSI with a dynamic moving average signal line to detect micro-shifts in momentum, early reversals, and continuation setups with extreme speed.
The indicator includes five key zones used by liquidity and SMC-style traders:
• Strong Sell (90) – Extreme momentum exhaustion
• Sell (80) – Overextension area
• TP Zone (50) – Momentum balance / decision point
• Buy (20) – Discount area
• Strong Buy (10) – Extreme sell-side exhaustion
By tracking how RSI interacts with its MA inside these zones, traders can identify high-probability sniper entries on the 1m, 3m, and 5m charts.
⸻
⭐ HOW IT WORKS (Quick Breakdown)
• RSI Period: defines momentum sensitivity
• MA Period: smooths RSI noise and clarifies direction shifts
• MA Type: SMA, EMA, or WMA for different reaction speeds
• Crossovers: show momentum flips or trend continuation
• Zones: filter out weak signals and highlight only premium setups
⸻
⚡ STRATEGY EXAMPLES
1️⃣ Liquidity Sweep Reversal (Most Powerful Setup)
Use case: Gold, NAS100, NQ, US30
1. Price sweeps a previous high/low
2. RSI spikes into Strong Sell (90) or Strong Buy (10)
3. RSI crosses its MA back inside the zone
4. Enter on candle confirmation
5. TP at the next imbalance, VWAP, or volume cluster
This setup catches V-shaped reversals and trap plays.
⸻
2️⃣ Trend Continuation Pullback
Use case: Trending markets
1. Identify trend direction (EMA 200, structure, etc.)
2. Wait for RSI to pull back to the TP (50) zone
3. Watch for RSI crossing its MA in trend direction
4. Enter with trend
5. TP at previous swing high/low
This setup filters out weak pullbacks and catches clean momentum continuation.
⸻
3️⃣ Breakout Confirmation
Use case: Range breakouts, opening range breaks
1. Price breaks a consolidation high/low
2. RSI holds above Sell (80) in uptrend or below Buy (20) in downtrend
3. RSI crosses its MA with momentum
4. Enter breakout
5. TP at HTF zone or liquidity target
Perfect for fast markets like NAS100 and Bitcoin.
⸻
4️⃣ Divergence + Whistle Flip
Use case: Slow markets or pre-session moves
1. Look for bullish or bearish RSI divergence
2. Wait for RSI to cross the MA in direction of divergence
3. Enter once momentum confirms
4. TP at imbalance, FVG, or mid-range
This increases divergence accuracy dramatically.
⸻
🔥 RECOMMENDED SETTINGS
• Scalping (1m–3m):
• RSI: 5
• MA: 3
• Type: EMA
• Intraday 5m–15m:
• RSI: 7–14
• MA: 5
• Type: SMA
⸻
⭐ WHO IT’S BUILT FOR
• Liquidity + SMC traders
• Scalpers who need fast confirmation
• Traders who want clean, simple entries
• Beginners who want visual guidance
• Professionals who want momentum precision
The Reaper Whistle is intentionally designed for speed, clarity, and reliability — no clutter, no lag, just pure momentum read.
— Created by TheTrendSniper (ChartReaper)
“When the market whispers… the Reaper whistles.”
Open Range BreakoutOpen Range Breakout (ORB)
The Open Range Breakout (ORB) is a classic intraday strategy used across stocks, indices, FX and futures. It focuses on how price behaves during the first minutes of a major session, when liquidity and volatility are highest.
This indicator fully automates the ORB process with session detection, box drawing, breakout & retest logic, and final Buy/Sell signals.
Multi-Session Support
Choose between the three most important global opens:
Asia (Tokyo) – JPY pairs, Asian indices, gold, crypto
London – FX majors, European indices, strong volatility
New York – US indices, USD pairs, gold, oil, highest volume
The Opening Range is calculated only during the selected session.
ORB Range (5 / 15 / 30 min)
The indicator builds the ORB High/Low from the first X minutes of the session, draws the box, and waits for price action once the range is complete.
How It Works
ORB Window → High/Low of the opening minutes are recorded.
Breakout → Price closes above/below the ORB → “BREAKOUT” label.
Retest → Price returns to the ORB box → “RETEST” label.
Confirmation Levels Freeze → Upper/lower structure set.
Final Signal
Close above frozen upper level → BUY
Close below frozen lower level → SELL
This filters out false breakouts and provides structured continuation signals.
Alerts
Includes built-in alert conditions for:
ORB BUY Signal
ORB SELL Signal
Alerts trigger exactly when the Buy or Sell label appears.
Works On
Stocks & indices
Forex
Futures
Variance Ratio & Efficiency Ratio (Quant Lab)1️⃣ Variance Ratio (VR)
Formula:
VR ≈ Var(q-step returns) / (q × Var(1-step returns))
Interpretation:
• VR ≈ 1 → The market is like a random walk; neither trend nor mean-reversion is dominant.
• VR > 1 → Trend behavior is dominant.
• Trend-following systems (EMA, Supertrend, breakout) work better.
• VR < 1 → Mean-reversion is dominant.
• Range/reversal strategies (Z-score, Bollinger fade, RSI reversal) work better.
In short:
• VR > 1 → Trending market
• VR < 1 → Mean-reverting market
This tells you:
“Should I build a trend system or a mean-reversion system for this instrument?”
⸻
2️⃣ Efficiency Ratio (ER)
Formula logic:
ER = |Close_now – Close_n-bars-ago| / Σ|Close_i – Close_{i+1}|
In other words:
• Numerator → Net movement over N bars
• Denominator → Total noise over N bars
Interpretation:
• ER ≈ 1 → The price has moved in almost a straight line in one direction.
→ The trend is very efficient, noise is low.
• ER ≈ 0 → The price has fluctuated a lot but hasn't gone anywhere definitively.
→ A complete noise/range market.
This tells you:
“How clear is the trend in this last N bars, and how much noise is there?”
⸻
🔥 The intelligence provided by both together:
• VR > 1 and ER is high (0.6–1.0) →
➜ Strong, high-quality trend. Golden age for trend-following.
• VR > 1 but ER is low (0.2–0.4) →
➜ Trend exists but there is a lot of noise, many fake movements. • VR < 1 and ER is low →
➜ Net range / sideways market. Ideal for mean-reversion.
RSI Median DeviationRSI Median Deviation – Adaptive Statistical RSI for High-Probability Extremes
The Relative Strength Index (RSI) is a momentum oscillator developed by J. Welles Wilder in 1978 to measure the magnitude of recent price changes and identify potential overbought or oversold conditions. It calculates the ratio of upward to downward price movements over a specified period, scaled to 0-100. However, standard RSI often relies on fixed thresholds like 70/30, which can produce unreliable signals in varying market regimes due to their lack of adaptability to the actual distribution of RSI values.
This indicator was developed because I needed a reliable tool for spotting intermediate high-probability bottoms and tops. Instead of arbitrary horizontal lines, it uses the RSI’s own historical median as a dynamic centerline and measures how far the current RSI deviates from that median over a chosen lookback period. The main signals are triggered only at 2 standard deviation (2σ) extremes — statistically rare events that occur roughly 5 % of the time under a normal distribution. I selected 2σ because it is extreme enough to be meaningful yet frequent enough for practical trading. For oversold signals I further require RSI to be below 42, a filter that significantly improved results in my mean-reversion tests (enter on oversold, exit on the first bar the condition is no longer true).
The combination of percentile median + standard deviation bands is deliberate: the median is far more robust to outliers than a simple average, while the SD bands automatically adjust to the current volatility of the RSI itself, producing adaptive envelopes that work equally well in ranging and trending markets.
Underlying Concepts and Calculations
Base RSI: RSI = 100 − (100 / (1 + RS)), RS = average gain / average loss (default length 10).
Percentile Median: 50th percentile of the last "N" RSI values (default 28 = 4 weeks)
→ dynamic, outlier-resistant centerline.
Standard Deviation Bands: rolling stdev of RSI (default length 27 = = 4 weeks (almost))
→ bands = median ± 1σ / 2σ.
Optional Dynamic MA Envelopes: user-selectable moving average (TEMA, WMA, etc., default WMA length 37) for additional momentum context.
Trend Bias Coloring
Independent of the statistical extremes, the RSI line itself is colored green when above the user-defined Long Threshold (default 60) and red when below the Short Threshold (default 47). This provides an instant bullish/bearish bias overlay similar to classic RSI usage, without interfering with the main 2σ extreme signals.
Extremes are highlighted with background color (green for oversold 2σ + RSI<42, magenta for overbought 2σ) and small diamond markers for ultra-extremes (RSI <25 or >85).
Originality and Development Rationale
The indicator was built and refined through extensive testing on dozens of assets including major cryptocurrencies:
(BTC, ETH, SOL, SUI, BNB, XRP, TRX, DOGE, LINK, PAXG, CVX, HYPE, VIRTUAL and many more),
the Magnificent 7 stocks,, QQQ, SPX, and gold.
Default parameters were chosen to deliver consistent profitability in simple mean-reversion setups while maximizing Sortino ratio and minimizing maximum drawdown across this broad universe — ensuring the settings are robust and not overfitted to any single instrument or timeframe.
How to Use It
Ideal for swing / position trading on the 1h to daily charts (the same defaults work).
Oversold (high-probability long): RSI crosses below lower 2σ band AND RSI < 42
→ green background
→ enter long, exit the first bar the condition disappears.
Overbought (high-probability short): RSI crosses above upper 2σ band
→ magenta background
→ enter short, exit on opposite signal or at median. (Shorts were not tested, it's only an idea)
Use the green/red RSI line coloring for quick trend context and to avoid fighting strong momentum.
Always confirm with price action and manage risk appropriately.
This indicator is not a standalone trading system.
Disclaimer: This is not financial advice. Backtests are based on past results and are not indicative of future performance.
Multi-MA + RSI Pullback Strategy (Jordan)1️⃣ Strategy logic I’ll code
From your screenshots:
Indicators
• EMAs: 600 / 200 / 100 / 50
• RSI: length 6, levels 80 / 20
Rules (simplified so a script can handle them):
• Use a higher-timeframe trend filter (15m or 1h) using the EMAs.
• Take entries on the chart timeframe (you can use 1m or 5m).
• Long:
• Higher-TF trend is up.
• Price is pulling back into a zone (between 50 EMA and 100 EMA on the entry timeframe – this approximates your 50–61% retrace).
• RSI crosses below 20 (oversold).
• Short:
• Higher-TF trend is down.
• Price pulls back between 50 & 100 EMAs.
• RSI crosses above 80 (overbought).
• Exits: ATR-based stop + take-profit with adjustable R:R (2:1 or 3:1).
• Max 4 trades per day.
News filter & “only trade gold” you handle manually (run it on XAUUSD and avoid news times yourself – TradingView can’t read the economic calendar from code).
Pivots + MAs ISRSPivots + MAs ISRS is a complete market-structure tool designed for traders who want clear institutional levels combined with trend confirmation from moving averages and Fibonacci zones.
This indicator helps you identify breakouts, pullbacks, and reversal points with much higher accuracy.
It combines the best of three worlds:
🔹 1. Advanced Pivot Points (Standard TV Engine)
Includes every major professional pivot type:
Traditional
Fibonacci
Woodie
Classic
DM
Camarilla
You can choose pivot anchors such as:
Daily, Weekly, Monthly, Quarterly, Yearly, and extended periods (2, 3, 5, and 10 years).
✔ Fully customizable colors
✔ Show/hide each level individually
✔ Dynamic labels (left or right)
✔ Works with intraday + extended sessions
🔹 2. Built-in Moving Averages
The indicator includes:
3 EMAs to measure trend direction and momentum
A 5-period SMA for micro-structure and scalping precision
Great for identifying confluences between trend direction + pivot levels.
🔹 3. FiboISRS Zones
Fibonacci-based zones designed to enhance price-reaction detection:
Retracement levels
Liquidity zones
Confluences with EMAs + Pivot Points
Perfect for spotting high-probability reversal areas.
🎯 What This Indicator Helps You Do
✔ See active institutional levels on any timeframe
✔ Detect real breakouts (not fakeouts) using Pivots + MAs
✔ Identify clean pullbacks into key zones
✔ Spot reactions at S1/S2/S3 or R1/R2/R3
✔ Keep your chart clean with minimal noise
Works extremely well on:
Crypto with solid liquidity
Major indices (SPX, NASDAQ, Dow)
Forex
Gold and commodities
🧠 Pro Tip
The highest-probability setups occur when price touches:
👉 A Pivot Level
👉 An EMA (20, 50, or 200)
👉 A FiboISRS zone
When these three overlap, the market often reacts strongly.
⚡ Creator
Indicator created by Ismael Robles (ISRS) to bring a clean, institutional-grade structure to everyday traders.
5MA＋TrendMagic + Disparity + Volume Spikes5MA + TrendMagic + Disparity Scalping + Volume Spikes is an all-in-one trend and momentum indicator designed for fast entries, trend confirmation, and volatility detection.
Main Features
Multiple EMAs (9/21/50/100/200) for trend structure
TrendMagic for dynamic trend direction and stop levels
Ultra Fast Disparity Scalper (EMA disparity + RSI + RVI momentum)
Volume Spike Detection with smart filters (valid highs/lows, candle types, color match, session filter)
Gold Volatility Signals using ATR, Bollinger Bands, HV/RV spread
Clear BUY/SELL markers, overheat filters, and full alert support
This tool helps identify early reversals, confirm major trends, and highlight strong volume-driven turning points.
TDI Fibonacci Volatility Bands Candle Coloring [cryptalent]"This is an advanced Traders Dynamic Index (TDI) candle coloring system, designed for traders seeking precise dynamic analysis. Unlike traditional TDI, which typically relies on a 50 midline with a single standard deviation band (±1 SD), this indicator innovatively incorporates Fibonacci golden ratio multiples (1.618, 2.618, 3.618 times standard deviation) to create multi-layered dynamic bands. It precisely divides the RSI fast line (green line) position into five distinct strength zones, instantly reflecting them on the candle colors, allowing you to grasp market sentiment in real-time without switching to a sub-chart.
Core Calculation Logic:
RSI Period (default 20), Band Length (default 50), and Fast MA Smoothing Period (default 1) are all adjustable.
The midline is the Simple Moving Average (SMA) of RSI, with upper and lower bands calculated by multiplying Fibonacci multiples with Standard Deviation (STDEV), generating three dynamic band sets: 1.618, 2.618, and 3.618.
Traders can quickly identify the following scenarios:
Extreme Overbought Zone (Strong Bullish, Red): Fast line exceeds custom threshold (default 82) and breaks above the specified band (default 2.618). This often signals overheating, potentially a profit-taking point or reversal short entry, especially at trend tops.
Extreme Oversold Zone (Strong Bearish, Green): Fast line drops below custom threshold (default 28) and breaks below the specified band (default 2.618). This is a potential strong rebound starting point, ideal for bottom-fishing or long entries.
Medium Bullish Zone (Yellow): Fast line surpasses medium threshold (default 66) and stands above the specified band (default 1.618), indicating bullish dominance in trend continuation.
Medium Bearish Zone (Orange): Fast line falls below medium threshold (default 33) and breaks below the specified band (default 1.618), signaling bearish control in segment transitions.
Neutral Zone (No Color Change): Fast line within custom upper and lower limits (default 34~65), retaining original candle colors to avoid noise interference during consolidation.
Color priority logic flows from strong to weak (Extreme > Medium > Neutral), ensuring no conflicts. All parameters are highly customizable, including thresholds, band selections (1.618/2.618/3.618/Midline/None), color schemes, and even optional semi-transparent background coloring (default off, transparency 90%) for enhanced visual layering.
Applicable Scenarios:
Intraday Trading: Capture extreme color shifts as entry/exit signals.
Swing Trading: Use medium colors to confirm trend extensions.
Long-Term Trend Following: Filter noise in neutral zones to focus on major trends.
Supports various markets like forex, stocks, and cryptocurrencies. After installation, adjust parameters in settings to match your strategy, and combine with other indicators like moving averages or support/resistance for improved accuracy.
If you're a TDI enthusiast, this will make your trading more intuitive and efficient!
Intermarket Swing Projection [LuxAlgo]The Intermarket Swing Projection allows traders to plot price movement swings from any user-selected asset directly onto the chart in the form of zigzags and/or horizontal support and resistance levels.
This tool rescale the external asset price on the user chart, enabling traders to make direct comparisons.
It answers the question of how different the price behavior is between two assets, accounting for each asset's volatility.
🔶 USAGE
This tool is based on swing detection of two different assets: the chart and a user-selected asset. It allows traders to compare two assets on an equal footing while accounting for volatility and price behavior.
Traders can customize the detection by selecting a custom ticker, timeframe, the number of swings and length for swing detection. This makes the tool a Swiss army knife for asset comparison.
As we can see in the image below, the Show Last, Pivot Length, and Spread parameters are key to defining the final output of the tool.
"Show Last" defines how many pivots are displayed. "Pivot Length" is used for pivot detection; a larger value will detect larger market structures. "Spread" defines how far apart the horizontal levels will be from their original location in terms of volatility.
🔹 Comparing different assets
This image shows the Nasdaq 100 futures contract compared to four other futures contracts: S&P 500, gold, bitcoin, and euro/U.S. dollar.
Plotting all of these assets in Nasdaq 100 terms makes it easy to compare and analyze price behaviors and identify key levels.
In the top left chart, we have NQ vs. ES. It's no surprise that they are practically an exact match; a large portion of the S&P 500 is technology.
In the top right chart, NQ vs. GC, we see totally different behaviors. We can clearly see the summer consolidation in gold and the resumption of the uptrend, which took gold above 29,200 NQ points, up from 21,200.
In the bottom right chart, we see bitcoin making new highs, way above the Nasdaq in May, July, and October. However, the last high was way below the Nasdaq prices on October 27—the first lower high in a while. Sellers are pushing down.
Finally, the bottom left chart is NQ vs. 6E. We can see large volatility in the uptrend since February, with NQ unable to catch up until now. The last swing low was almost a match, and 6E is in a range.
As we can see, this tool allows us to perform intermarket analysis properly by accounting for each asset's volatility and price behavior. Then, we plot them on the same scale on equal terms, which makes performing this kind of analysis easy.
As we can see in the chart above, the assets are the same as in the previous image, but the timeframe is 1H with different settings.
Note the horizontal levels acting as support and resistance, as well as how NQ prices react to the zones marked with white circles. These levels are derived from custom assets selected by the user.
🔹 Displaying Elements
Zig-zag allows traders to clearly see the path that the selected asset's price took, as well as its turning points.
Horizontal levels are displayed from those turning points to the present and can be used as support or resistance. Traders can adjust the spread parameter in the settings panel to expand or contract those levels' volatility.
There are two color modes for the levels: average and pivots. In the first mode, green is used for levels below the average and red for levels above the average. The second uses green for swing lows and red for swing highs.
The backpaint feature is enabled by default and allows the swings to be displayed in the correct location. With this feature disabled, the swings will be displayed in the current location when a new swing is detected.
🔶 DETAILS
On a more technical note, the rescaling is formed by calculating three main elements from all the swings detected on the custom and chart assets:
The chart asset's average of all swing points
The chart asset's standard deviation of all swing points
The custom asset's z-score for each swing point
Then, the re-scaled swing point is calculated as the average plus the z-score multiplied by the standard deviation. This makes it possible to plot AAPL swings on an NQ chart, for example.
Thanks to re-scaling, we can directly compare the price behavior of two assets with different price ranges and volatility on the same chart.
🔶 SETTINGS
🔹 Trendlines
Ticker: Select the custom ticker.
Timeframe: Select a custom timeframe.
Show Last: Select how many swing points to display.
Pivot Length: Select the size for swing point detection.
Spread: Volatility multiplier for horizontal levels. Larger values mean the levels are farther apart.
Backpaint: Enable or disable the backpaint feature. When enabled, the drawings will be displayed where they were detected. When disabled, the drawings will be displayed at the moment of detection.
🔹 Style
Show ZigZag: Enable or disable the ZigZag display and choose a line style.
Show Levels: Enable or disable the levels display and choose a line style.
Color Mode: Choose between Average Mode, which colors all levels below the average bullish and all levels above bearish, and Pivot Mode, which colors swing highs bearish and swing lows bullish.
Bullish: Select a bullish color.
Bearish: Select a bearish color.
ZigZag: Select the ZigZag color.
Granger Causality Flow IndicatorGranger Causality Flow Indicator
█ OVERVIEW
The Granger Causality Flow Indicator is a statistical analysis tool designed to identify predictive relationships between two assets (Symbol X and Symbol Y). In econometrics, "Granger Causality" does not test for actual physical causation (e.g., rain causes mud); rather, it tests for predictive causality .
This script is designed to answer a specific question for traders: "Does the past price action of Asset X provide statistically significant information about the future price of Asset Y, beyond what is already contained in the past prices of Asset Y itself?"
This tool is particularly useful for Pairs Traders , Arbitrageurs , and Macro Analysts looking to identify lead-lag relationships between correlated assets (e.g., BTC vs. ETH, NASDAQ vs. SPY, or Gold vs. Silver).
█ CONCEPTS & CALCULATIONS
To determine if Symbol X "Granger-causes" Symbol Y, this script utilizes a variance-reduction approach based on Auto-Regressive (AR) models. Due to the runtime constraints of Pine Script™, we employ an optimized proxy for the standard Granger test using an AR(1) logic (looking back 1 period).
The calculation performs a comparative test over a rolling window (Default: 50 bars):
The Restricted Model (Baseline):
We attempts to predict the current value of Y using only the previous value of Y (Auto-Regression). We measure the error of this prediction (the "Residuals") and calculate the Variance of the Restricted Model (Var_R) .
The Unrestricted Model (Proxy):
We then test if the past value of X can explain the errors made by the Restricted Model. If X contains predictive power, including it should reduce the error variance. We calculate the remaining Variance of the Unrestricted Model (Var_UR) .
The GC Score:
The script calculates a score based on the ratio of variance reduction:
Score = 1 - (Var_UR / Var_R)
If the Score is High (> 0) : It implies that including X significantly reduced the prediction error for Y. Therefore, X "Granger-causes" Y.
If the Score is Low or 0 : It implies X added no predictive value.
█ HOW TO USE
This indicator is not a simple Buy/Sell signal generator; it is a context filter for cross-asset analysis.
1. Setup
Symbol 1 (X): The potential "Leader" (e.g., BINANCE:BTCUSDT).
Symbol 2 (Y): The potential "Follower" (e.g., BINANCE:ETHUSDT).
Differencing: Enabled by default. This checks the changes in price rather than absolute price, which is crucial for statistical stationarity.
2. Interpreting the Visuals
The script changes the background color and displays a table to indicate the current flow of causality:
Green Background (X → Y): Symbol 1 is leading Symbol 2. Price moves in Symbol 1 are statistically likely to foreshadow moves in Symbol 2.
Orange Background (Y → X): Symbol 2 is leading Symbol 1. The relationship has inverted.
Blue Background (Bidirectional): Both assets are predicting each other (tight coupling or feedback loop).
Gray/No Color: No statistically significant relationship detected.
3. Trading Application
Trend Confirmation: If you trade Symbol Y, wait for the background to turn Green . This indicates that the "Leader" (Symbol X) is currently exerting predictive influence, potentially making trend-following setups on Symbol Y more reliable.
Divergence Warning: If you are trading a correlation pair and the causality breaks (turns Gray), the correlation may be weakening, signaling a higher risk of divergence.
█ SETTINGS
Symbol 1 (X) & Symbol 2 (Y): The two tickers to analyze.
Use Differencing: (Default: True) Converts prices to price-changes. Highly recommended for accurate statistical results to avoid spurious regression.
Calculation Window: The number of bars used to compute the variance and coefficients. Larger windows provide smoother, more stable signals but react slower to regime changes.
Significance Threshold: (0.01 - 0.99) The minimum variance reduction score required to trigger a causal signal.
█ DISCLAIMER
This tool provides statistical analysis of historical price data and does not guarantee future performance. Granger Causality is a measure of predictive capability, not necessarily fundamental causation. Always use appropriate risk management.
Adaptive Genesis Engine [AGE]ADAPTIVE GENESIS ENGINE (AGE)
Pure Signal Evolution Through Genetic Algorithms
Where Darwin Meets Technical Analysis
🧬 WHAT YOU'RE GETTING - THE PURE INDICATOR
This is a technical analysis indicator - it generates signals, visualizes probability, and shows you the evolutionary process in real-time. This is NOT a strategy with automatic execution - it's a sophisticated signal generation system that you control .
What This Indicator Does:
Generates Long/Short entry signals with probability scores (35-88% range)
Evolves a population of up to 12 competing strategies using genetic algorithms
Validates strategies through walk-forward optimization (train/test cycles)
Visualizes signal quality through premium gradient clouds and confidence halos
Displays comprehensive metrics via enhanced dashboard
Provides alerts for entries and exits
Works on any timeframe, any instrument, any broker
What This Indicator Does NOT Do:
Execute trades automatically
Manage positions or calculate position sizes
Place orders on your behalf
Make trading decisions for you
This is pure signal intelligence. AGE tells you when and how confident it is. You decide whether and how much to trade.
🔬 THE SCIENCE: GENETIC ALGORITHMS MEET TECHNICAL ANALYSIS
What Makes This Different - The Evolutionary Foundation
Most indicators are static - they use the same parameters forever, regardless of market conditions. AGE is alive . It maintains a population of competing strategies that evolve, adapt, and improve through natural selection principles:
Birth: New strategies spawn through crossover breeding (combining DNA from fit parents) plus random mutation for exploration
Life: Each strategy trades virtually via shadow portfolios, accumulating wins/losses, tracking drawdown, and building performance history
Selection: Strategies are ranked by comprehensive fitness scoring (win rate, expectancy, drawdown control, signal efficiency)
Death: Weak strategies are culled periodically, with elite performers (top 2 by default) protected from removal
Evolution: The gene pool continuously improves as successful traits propagate and unsuccessful ones die out
This is not curve-fitting. Each new strategy must prove itself on out-of-sample data through walk-forward validation before being trusted for live signals.
🧪 THE DNA: WHAT EVOLVES
Every strategy carries a 10-gene chromosome controlling how it interprets market data:
Signal Sensitivity Genes
Entropy Sensitivity (0.5-2.0): Weight given to market order/disorder calculations. Low values = conservative, require strong directional clarity. High values = aggressive, act on weaker order signals.
Momentum Sensitivity (0.5-2.0): Weight given to RSI/ROC/MACD composite. Controls responsiveness to momentum shifts vs. mean-reversion setups.
Structure Sensitivity (0.5-2.0): Weight given to support/resistance positioning. Determines how much price location within swing range matters.
Probability Adjustment Genes
Probability Boost (-0.10 to +0.10): Inherent bias toward aggressive (+) or conservative (-) entries. Acts as personality trait - some strategies naturally optimistic, others pessimistic.
Trend Strength Requirement (0.3-0.8): Minimum trend conviction needed before signaling. Higher values = only trades strong trends, lower values = acts in weak/sideways markets.
Volume Filter (0.5-1.5): Strictness of volume confirmation. Higher values = requires strong volume, lower values = volume less important.
Risk Management Genes
ATR Multiplier (1.5-4.0): Base volatility scaling for all price levels. Controls whether strategy uses tight or wide stops/targets relative to ATR.
Stop Multiplier (1.0-2.5): Stop loss tightness. Lower values = aggressive profit protection, higher values = more breathing room.
Target Multiplier (1.5-4.0): Profit target ambition. Lower values = quick scalping exits, higher values = swing trading holds.
Adaptation Gene
Regime Adaptation (0.0-1.0): How much strategy adjusts behavior based on detected market regime (trending/volatile/choppy). Higher values = more reactive to regime changes.
The Magic: AGE doesn't just try random combinations. Through tournament selection and fitness-weighted crossover, successful gene combinations spread through the population while unsuccessful ones fade away. Over 50-100 bars, you'll see the population converge toward genes that work for YOUR instrument and timeframe.
📊 THE SIGNAL ENGINE: THREE-LAYER SYNTHESIS
Before any strategy generates a signal, AGE calculates probability through multi-indicator confluence:
Layer 1 - Market Entropy (Information Theory)
Measures whether price movements exhibit directional order or random walk characteristics:
The Math:
Shannon Entropy = -Σ(p × log(p))
Market Order = 1 - (Entropy / 0.693)
What It Means:
High entropy = choppy, random market → low confidence signals
Low entropy = directional market → high confidence signals
Direction determined by up-move vs down-move dominance over lookback period (default: 20 bars)
Signal Output: -1.0 to +1.0 (bearish order to bullish order)
Layer 2 - Momentum Synthesis
Combines three momentum indicators into single composite score:
Components:
RSI (40% weight): Normalized to -1/+1 scale using (RSI-50)/50
Rate of Change (30% weight): Percentage change over lookback (default: 14 bars), clamped to ±1
MACD Histogram (30% weight): Fast(12) - Slow(26), normalized by ATR
Why This Matters: RSI catches mean-reversion opportunities, ROC catches raw momentum, MACD catches momentum divergence. Weighting favors RSI for reliability while keeping other perspectives.
Signal Output: -1.0 to +1.0 (strong bearish to strong bullish)
Layer 3 - Structure Analysis
Evaluates price position within swing range (default: 50-bar lookback):
Position Classification:
Bottom 20% of range = Support Zone → bullish bounce potential
Top 20% of range = Resistance Zone → bearish rejection potential
Middle 60% = Neutral Zone → breakout/breakdown monitoring
Signal Logic:
At support + bullish candle = +0.7 (strong buy setup)
At resistance + bearish candle = -0.7 (strong sell setup)
Breaking above range highs = +0.5 (breakout confirmation)
Breaking below range lows = -0.5 (breakdown confirmation)
Consolidation within range = ±0.3 (weak directional bias)
Signal Output: -1.0 to +1.0 (bearish structure to bullish structure)
Confluence Voting System
Each layer casts a vote (Long/Short/Neutral). The system requires minimum 2-of-3 agreement (configurable 1-3) before generating a signal:
Examples:
Entropy: Bullish, Momentum: Bullish, Structure: Neutral → Signal generated (2 long votes)
Entropy: Bearish, Momentum: Neutral, Structure: Neutral → No signal (only 1 short vote)
All three bullish → Signal generated with +5% probability bonus
This is the key to quality. Single indicators give too many false signals. Triple confirmation dramatically improves accuracy.
📈 PROBABILITY CALCULATION: HOW CONFIDENCE IS MEASURED
Base Probability:
Raw_Prob = 50% + (Average_Signal_Strength × 25%)
Then AGE applies strategic adjustments:
Trend Alignment:
Signal with trend: +4%
Signal against strong trend: -8%
Weak/no trend: no adjustment
Regime Adaptation:
Trending market (efficiency >50%, moderate vol): +3%
Volatile market (vol ratio >1.5x): -5%
Choppy market (low efficiency): -2%
Volume Confirmation:
Volume > 70% of 20-bar SMA: no change
Volume below threshold: -3%
Volatility State (DVS Ratio):
High vol (>1.8x baseline): -4% (reduce confidence in chaos)
Low vol (<0.7x baseline): -2% (markets can whipsaw in compression)
Moderate elevated vol (1.0-1.3x): +2% (trending conditions emerging)
Confluence Bonus:
All 3 indicators agree: +5%
2 of 3 agree: +2%
Strategy Gene Adjustment:
Probability Boost gene: -10% to +10%
Regime Adaptation gene: scales regime adjustments by 0-100%
Final Probability: Clamped between 35% (minimum) and 88% (maximum)
Why These Ranges?
Below 35% = too uncertain, better not to signal
Above 88% = unrealistic, creates overconfidence
Sweet spot: 65-80% for quality entries
🔄 THE SHADOW PORTFOLIO SYSTEM: HOW STRATEGIES COMPETE
Each active strategy maintains a virtual trading account that executes in parallel with real-time data:
Shadow Trading Mechanics
Entry Logic:
Calculate signal direction, probability, and confluence using strategy's unique DNA
Check if signal meets quality gate:
Probability ≥ configured minimum threshold (default: 65%)
Confluence ≥ configured minimum (default: 2 of 3)
Direction is not zero (must be long or short, not neutral)
Verify signal persistence:
Base requirement: 2 bars (configurable 1-5)
Adapts based on probability: high-prob signals (75%+) enter 1 bar faster, low-prob signals need 1 bar more
Adjusts for regime: trending markets reduce persistence by 1, volatile markets add 1
Apply additional filters:
Trend strength must exceed strategy's requirement gene
Regime filter: if volatile market detected, probability must be 72%+ to override
Volume confirmation required (volume > 70% of average)
If all conditions met for required persistence bars, enter shadow position at current close price
Position Management:
Entry Price: Recorded at close of entry bar
Stop Loss: ATR-based distance = ATR × ATR_Mult (gene) × Stop_Mult (gene) × DVS_Ratio
Take Profit: ATR-based distance = ATR × ATR_Mult (gene) × Target_Mult (gene) × DVS_Ratio
Position: +1 (long) or -1 (short), only one at a time per strategy
Exit Logic:
Check if price hit stop (on low) or target (on high) on current bar
Record trade outcome in R-multiples (profit/loss normalized by ATR)
Update performance metrics:
Total trades counter incremented
Wins counter (if profit > 0)
Cumulative P&L updated
Peak equity tracked (for drawdown calculation)
Maximum drawdown from peak recorded
Enter cooldown period (default: 8 bars, configurable 3-20) before next entry allowed
Reset signal age counter to zero
Walk-Forward Tracking:
During position lifecycle, trades are categorized:
Training Phase (first 250 bars): Trade counted toward training metrics
Testing Phase (next 75 bars): Trade counted toward testing metrics (out-of-sample)
Live Phase (after WFO period): Trade counted toward overall metrics
Why Shadow Portfolios?
No lookahead bias (uses only data available at the bar)
Realistic execution simulation (entry on close, stop/target checks on high/low)
Independent performance tracking for true fitness comparison
Allows safe experimentation without risking capital
Each strategy learns from its own experience
🏆 FITNESS SCORING: HOW STRATEGIES ARE RANKED
Fitness is not just win rate. AGE uses a comprehensive multi-factor scoring system:
Core Metrics (Minimum 3 trades required)
Win Rate (30% of fitness):
WinRate = Wins / TotalTrades
Normalized directly (0.0-1.0 scale)
Total P&L (30% of fitness):
Normalized_PnL = (PnL + 300) / 600
Clamped 0.0-1.0. Assumes P&L range of -300R to +300R for normalization scale.
Expectancy (25% of fitness):
Expectancy = Total_PnL / Total_Trades
Normalized_Expectancy = (Expectancy + 30) / 60
Clamped 0.0-1.0. Rewards consistency of profit per trade.
Drawdown Control (15% of fitness):
Normalized_DD = 1 - (Max_Drawdown / 15)
Clamped 0.0-1.0. Penalizes strategies that suffer large equity retracements from peak.
Sample Size Adjustment
Quality Factor:
<50 trades: 1.0 (full weight, small sample)
50-100 trades: 0.95 (slight penalty for medium sample)
100 trades: 0.85 (larger penalty for large sample)
Why penalize more trades? Prevents strategies from gaming the system by taking hundreds of tiny trades to inflate statistics. Favors quality over quantity.
Bonus Adjustments
Walk-Forward Validation Bonus:
if (WFO_Validated):
Fitness += (WFO_Efficiency - 0.5) × 0.1
Strategies proven on out-of-sample data receive up to +10% fitness boost based on test/train efficiency ratio.
Signal Efficiency Bonus (if diagnostics enabled):
if (Signals_Evaluated > 10):
Pass_Rate = Signals_Passed / Signals_Evaluated
Fitness += (Pass_Rate - 0.1) × 0.05
Rewards strategies that generate high-quality signals passing the quality gate, not just profitable trades.
Final Fitness: Clamped at 0.0 minimum (prevents negative fitness values)
Result: Elite strategies typically achieve 0.50-0.75 fitness. Anything above 0.60 is excellent. Below 0.30 is prime candidate for culling.
🔬 WALK-FORWARD OPTIMIZATION: ANTI-OVERFITTING PROTECTION
This is what separates AGE from curve-fitted garbage indicators.
The Three-Phase Process
Every new strategy undergoes a rigorous validation lifecycle:
Phase 1 - Training Window (First 250 bars, configurable 100-500):
Strategy trades normally via shadow portfolio
All trades count toward training performance metrics
System learns which gene combinations produce profitable patterns
Tracks independently: Training_Trades, Training_Wins, Training_PnL
Phase 2 - Testing Window (Next 75 bars, configurable 30-200):
Strategy continues trading without any parameter changes
Trades now count toward testing performance metrics (separate tracking)
This is out-of-sample data - strategy has never seen these bars during "optimization"
Tracks independently: Testing_Trades, Testing_Wins, Testing_PnL
Phase 3 - Validation Check:
Minimum_Trades = 5 (configurable 3-15)
IF (Train_Trades >= Minimum AND Test_Trades >= Minimum):
WR_Efficiency = Test_WinRate / Train_WinRate
Expectancy_Efficiency = Test_Expectancy / Train_Expectancy
WFO_Efficiency = (WR_Efficiency + Expectancy_Efficiency) / 2
IF (WFO_Efficiency >= 0.55): // configurable 0.3-0.9
Strategy.Validated = TRUE
Strategy receives fitness bonus
ELSE:
Strategy receives 30% fitness penalty
ELSE:
Validation deferred (insufficient trades in one or both periods)
What Validation Means
Validated Strategy (Green "✓ VAL" in dashboard):
Performed at least 55% as well on unseen data compared to training data
Gets fitness bonus: +(efficiency - 0.5) × 0.1
Receives priority during tournament selection for breeding
More likely to be chosen as active trading strategy
Unvalidated Strategy (Orange "○ TRAIN" in dashboard):
Failed to maintain performance on test data (likely curve-fitted to training period)
Receives 30% fitness penalty (0.7x multiplier)
Makes strategy prime candidate for culling
Can still trade but with lower selection probability
Insufficient Data (continues collecting):
Hasn't completed both training and testing periods yet
OR hasn't achieved minimum trade count in both periods
Validation check deferred until requirements met
Why 55% Efficiency Threshold?
If a strategy earned 10R during training but only 5.5R during testing, it still proved an edge exists beyond random luck. Requiring 100% efficiency would be unrealistic - market conditions change between periods. But requiring >50% ensures the strategy didn't completely degrade on fresh data.
The Protection: Strategies that work great on historical data but fail on new data are automatically identified and penalized. This prevents the population from being polluted by overfitted strategies that would fail in live trading.
🌊 DYNAMIC VOLATILITY SCALING (DVS): ADAPTIVE STOP/TARGET PLACEMENT
AGE doesn't use fixed stop distances. It adapts to current volatility conditions in real-time.
Four Volatility Measurement Methods
1. ATR Ratio (Simple Method):
Current_Vol = ATR(14) / Close
Baseline_Vol = SMA(Current_Vol, 100)
Ratio = Current_Vol / Baseline_Vol
Basic comparison of current ATR to 100-bar moving average baseline.
2. Parkinson (High-Low Range Based):
For each bar: HL = log(High / Low)
Parkinson_Vol = sqrt(Σ(HL²) / (4 × Period × log(2)))
More stable than close-to-close volatility. Captures intraday range expansion without overnight gap noise.
3. Garman-Klass (OHLC Based):
HL_Term = 0.5 × ²
CO_Term = (2×log(2) - 1) × ²
GK_Vol = sqrt(Σ(HL_Term - CO_Term) / Period)
Most sophisticated estimator. Incorporates all four price points (open, high, low, close) plus gap information.
4. Ensemble Method (Default - Median of All Three):
Ratio_1 = ATR_Current / ATR_Baseline
Ratio_2 = Parkinson_Current / Parkinson_Baseline
Ratio_3 = GK_Current / GK_Baseline
DVS_Ratio = Median(Ratio_1, Ratio_2, Ratio_3)
Why Ensemble?
Takes median to avoid outliers and false spikes
If ATR jumps but range-based methods stay calm, median prevents overreaction
If one method fails, other two compensate
Most robust approach across different market conditions
Sensitivity Scaling
Scaled_Ratio = (Raw_Ratio) ^ Sensitivity
Sensitivity 0.3: Cube root - heavily dampens volatility impact
Sensitivity 0.5: Square root - moderate dampening
Sensitivity 0.7 (Default): Balanced response to volatility changes
Sensitivity 1.0: Linear - full 1:1 volatility impact
Sensitivity 1.5: Exponential - amplified response to volatility spikes
Safety Clamps: Final DVS Ratio always clamped between 0.5x and 2.5x baseline to prevent extreme position sizing or stop placement errors.
How DVS Affects Shadow Trading
Every strategy's stop and target distances are multiplied by the current DVS ratio:
Stop Loss Distance:
Stop_Distance = ATR × ATR_Mult (gene) × Stop_Mult (gene) × DVS_Ratio
Take Profit Distance:
Target_Distance = ATR × ATR_Mult (gene) × Target_Mult (gene) × DVS_Ratio
Example Scenario:
ATR = 10 points
Strategy's ATR_Mult gene = 2.5
Strategy's Stop_Mult gene = 1.5
Strategy's Target_Mult gene = 2.5
DVS_Ratio = 1.4 (40% above baseline volatility - market heating up)
Stop = 10 × 2.5 × 1.5 × 1.4 = 52.5 points (vs. 37.5 in normal vol)
Target = 10 × 2.5 × 2.5 × 1.4 = 87.5 points (vs. 62.5 in normal vol)
Result:
During volatility spikes: Stops automatically widen to avoid noise-based exits, targets extend for bigger moves
During calm periods: Stops tighten for better risk/reward, targets compress for realistic profit-taking
Strategies adapt risk management to match current market behavior
🧬 THE EVOLUTIONARY CYCLE: SPAWN, COMPETE, CULL
Initialization (Bar 1)
AGE begins with 4 seed strategies (if evolution enabled):
Seed Strategy #0 (Balanced):
All sensitivities at 1.0 (neutral)
Zero probability boost
Moderate trend requirement (0.4)
Standard ATR/stop/target multiples (2.5/1.5/2.5)
Mid-level regime adaptation (0.5)
Seed Strategy #1 (Momentum-Focused):
Lower entropy sensitivity (0.7), higher momentum (1.5)
Slight probability boost (+0.03)
Higher trend requirement (0.5)
Tighter stops (1.3), wider targets (3.0)
Seed Strategy #2 (Entropy-Driven):
Higher entropy sensitivity (1.5), lower momentum (0.8)
Slight probability penalty (-0.02)
More trend tolerant (0.6)
Wider stops (1.8), standard targets (2.5)
Seed Strategy #3 (Structure-Based):
Balanced entropy/momentum (0.8/0.9), high structure (1.4)
Slight probability boost (+0.02)
Lower trend requirement (0.35)
Moderate risk parameters (1.6/2.8)
All seeds start with WFO validation bypassed if WFO is disabled, or must validate if enabled.
Spawning New Strategies
Timing (Adaptive):
Historical phase: Every 30 bars (configurable 10-100)
Live phase: Every 200 bars (configurable 100-500)
Automatically switches to live timing when barstate.isrealtime triggers
Conditions:
Current population < max population limit (default: 8, configurable 4-12)
At least 2 active strategies exist (need parents)
Available slot in population array
Selection Process:
Run tournament selection 3 times with different seeds
Each tournament: randomly sample active strategies, pick highest fitness
Best from 3 tournaments becomes Parent 1
Repeat independently for Parent 2
Ensures fit parents but maintains diversity
Crossover Breeding:
For each of 10 genes:
Parent1_Fitness = fitness
Parent2_Fitness = fitness
Weight1 = Parent1_Fitness / (Parent1_Fitness + Parent2_Fitness)
Gene1 = parent1's value
Gene2 = parent2's value
Child_Gene = Weight1 × Gene1 + (1 - Weight1) × Gene2
Fitness-weighted crossover ensures fitter parent contributes more genetic material.
Mutation:
For each gene in child:
IF (random < mutation_rate):
Gene_Range = GENE_MAX - GENE_MIN
Noise = (random - 0.5) × 2 × mutation_strength × Gene_Range
Mutated_Gene = Clamp(Child_Gene + Noise, GENE_MIN, GENE_MAX)
Historical mutation rate: 20% (aggressive exploration)
Live mutation rate: 8% (conservative stability)
Mutation strength: 12% of gene range (configurable 5-25%)
Initialization of New Strategy:
Unique ID assigned (total_spawned counter)
Parent ID recorded
Generation = max(parent generations) + 1
Birth bar recorded (for age tracking)
All performance metrics zeroed
Shadow portfolio reset
WFO validation flag set to false (must prove itself)
Result: New strategy with hybrid DNA enters population, begins trading in next bar.
Competition (Every Bar)
All active strategies:
Calculate their signal based on unique DNA
Check quality gate with their thresholds
Manage shadow positions (entries/exits)
Update performance metrics
Recalculate fitness score
Track WFO validation progress
Strategies compete indirectly through fitness ranking - no direct interaction.
Culling Weak Strategies
Timing (Adaptive):
Historical phase: Every 60 bars (configurable 20-200, should be 2x spawn interval)
Live phase: Every 400 bars (configurable 200-1000, should be 2x spawn interval)
Minimum Adaptation Score (MAS):
Initial MAS = 0.10
MAS decays: MAS × 0.995 every cull cycle
Minimum MAS = 0.03 (floor)
MAS represents the "survival threshold" - strategies below this fitness level are vulnerable.
Culling Conditions (ALL must be true):
Population > minimum population (default: 3, configurable 2-4)
At least one strategy has fitness < MAS
Strategy's age > culling interval (prevents premature culling of new strategies)
Strategy is not in top N elite (default: 2, configurable 1-3)
Culling Process:
Find worst strategy:
For each active strategy:
IF (age > cull_interval):
Fitness = base_fitness
IF (not WFO_validated AND WFO_enabled):
Fitness × 0.7 // 30% penalty for unvalidated
IF (Fitness < MAS AND Fitness < worst_fitness_found):
worst_strategy = this_strategy
worst_fitness = Fitness
IF (worst_strategy found):
Count elite strategies with fitness > worst_fitness
IF (elite_count >= elite_preservation_count):
Deactivate worst_strategy (set active flag = false)
Increment total_culled counter
Elite Protection:
Even if a strategy's fitness falls below MAS, it survives if fewer than N strategies are better. This prevents culling when population is generally weak.
Result: Weak strategies removed from population, freeing slots for new spawns. Gene pool improves over time.
Selection for Display (Every Bar)
AGE chooses one strategy to display signals:
Best fitness = -1
Selected = none
For each active strategy:
Fitness = base_fitness
IF (WFO_validated):
Fitness × 1.3 // 30% bonus for validated strategies
IF (Fitness > best_fitness):
best_fitness = Fitness
selected_strategy = this_strategy
Display selected strategy's signals on chart
Result: Only the highest-fitness (optionally validated-boosted) strategy's signals appear as chart markers. Other strategies trade invisibly in shadow portfolios.
🎨 PREMIUM VISUALIZATION SYSTEM
AGE includes sophisticated visual feedback that standard indicators lack:
1. Gradient Probability Cloud (Optional, Default: ON)
Multi-layer gradient showing signal buildup 2-3 bars before entry:
Activation Conditions:
Signal persistence > 0 (same directional signal held for multiple bars)
Signal probability ≥ minimum threshold (65% by default)
Signal hasn't yet executed (still in "forming" state)
Visual Construction:
7 gradient layers by default (configurable 3-15)
Each layer is a line-fill pair (top line, bottom line, filled between)
Layer spacing: 0.3 to 1.0 × ATR above/below price
Outer layers = faint, inner layers = bright
Color transitions from base to intense based on layer position
Transparency scales with probability (high prob = more opaque)
Color Selection:
Long signals: Gradient from theme.gradient_bull_mid to theme.gradient_bull_strong
Short signals: Gradient from theme.gradient_bear_mid to theme.gradient_bear_strong
Base transparency: 92%, reduces by up to 8% for high-probability setups
Dynamic Behavior:
Cloud grows/shrinks as signal persistence increases/decreases
Redraws every bar while signal is forming
Disappears when signal executes or invalidates
Performance Note: Computationally expensive due to linefill objects. Disable or reduce layers if chart performance degrades.
2. Population Fitness Ribbon (Optional, Default: ON)
Histogram showing fitness distribution across active strategies:
Activation: Only draws on last bar (barstate.islast) to avoid historical clutter
Visual Construction:
10 histogram layers by default (configurable 5-20)
Plots 50 bars back from current bar
Positioned below price at: lowest_low(100) - 1.5×ATR (doesn't interfere with price action)
Each layer represents a fitness threshold (evenly spaced min to max fitness)
Layer Logic:
For layer_num from 0 to ribbon_layers:
Fitness_threshold = min_fitness + (max_fitness - min_fitness) × (layer / layers)
Count strategies with fitness ≥ threshold
Height = ATR × 0.15 × (count / total_active)
Y_position = base_level + ATR × 0.2 × layer
Color = Gradient from weak to strong based on layer position
Line_width = Scaled by height (taller = thicker)
Visual Feedback:
Tall, bright ribbon = healthy population, many fit strategies at high fitness levels
Short, dim ribbon = weak population, few strategies achieving good fitness
Ribbon compression (layers close together) = population converging to similar fitness
Ribbon spread = diverse fitness range, active selection pressure
Use Case: Quick visual health check without opening dashboard. Ribbon growing upward over time = population improving.
3. Confidence Halo (Optional, Default: ON)
Circular polyline around entry signals showing probability strength:
Activation: Draws when new position opens (shadow_position changes from 0 to ±1)
Visual Construction:
20-segment polyline forming approximate circle
Center: Low - 0.5×ATR (long) or High + 0.5×ATR (short)
Radius: 0.3×ATR (low confidence) to 1.0×ATR (elite confidence)
Scales with: (probability - min_probability) / (1.0 - min_probability)
Color Coding:
Elite (85%+): Cyan (theme.conf_elite), large radius, minimal transparency (40%)
Strong (75-85%): Strong green (theme.conf_strong), medium radius, moderate transparency (50%)
Good (65-75%): Good green (theme.conf_good), smaller radius, more transparent (60%)
Moderate (<65%): Moderate green (theme.conf_moderate), tiny radius, very transparent (70%)
Technical Detail:
Uses chart.point array with index-based positioning
5-bar horizontal spread for circular appearance (±5 bars from entry)
Curved=false (Pine Script polyline limitation)
Fill color matches line color but more transparent (88% vs line's transparency)
Purpose: Instant visual probability assessment. No need to check dashboard - halo size/brightness tells the story.
4. Evolution Event Markers (Optional, Default: ON)
Visual indicators of genetic algorithm activity:
Spawn Markers (Diamond, Cyan):
Plots when total_spawned increases on current bar
Location: bottom of chart (location.bottom)
Color: theme.spawn_marker (cyan/bright blue)
Size: tiny
Indicates new strategy just entered population
Cull Markers (X-Cross, Red):
Plots when total_culled increases on current bar
Location: bottom of chart (location.bottom)
Color: theme.cull_marker (red/pink)
Size: tiny
Indicates weak strategy just removed from population
What It Tells You:
Frequent spawning early = population building, active exploration
Frequent culling early = high selection pressure, weak strategies dying fast
Balanced spawn/cull = healthy evolutionary churn
No markers for long periods = stable population (evolution plateaued or optimal genes found)
5. Entry/Exit Markers
Clear visual signals for selected strategy's trades:
Long Entry (Triangle Up, Green):
Plots when selected strategy opens long position (position changes 0 → +1)
Location: below bar (location.belowbar)
Color: theme.long_primary (green/cyan depending on theme)
Transparency: Scales with probability:
Elite (85%+): 0% (fully opaque)
Strong (75-85%): 10%
Good (65-75%): 20%
Acceptable (55-65%): 35%
Size: small
Short Entry (Triangle Down, Red):
Plots when selected strategy opens short position (position changes 0 → -1)
Location: above bar (location.abovebar)
Color: theme.short_primary (red/pink depending on theme)
Transparency: Same scaling as long entries
Size: small
Exit (X-Cross, Orange):
Plots when selected strategy closes position (position changes ±1 → 0)
Location: absolute (at actual exit price if stop/target lines enabled)
Color: theme.exit_color (orange/yellow depending on theme)
Transparency: 0% (fully opaque)
Size: tiny
Result: Clean, probability-scaled markers that don't clutter chart but convey essential information.
6. Stop Loss & Take Profit Lines (Optional, Default: ON)
Visual representation of shadow portfolio risk levels:
Stop Loss Line:
Plots when selected strategy has active position
Level: shadow_stop value from selected strategy
Color: theme.short_primary with 60% transparency (red/pink, subtle)
Width: 2
Style: plot.style_linebr (breaks when no position)
Take Profit Line:
Plots when selected strategy has active position
Level: shadow_target value from selected strategy
Color: theme.long_primary with 60% transparency (green, subtle)
Width: 2
Style: plot.style_linebr (breaks when no position)
Purpose:
Shows where shadow portfolio would exit for stop/target
Helps visualize strategy's risk/reward ratio
Useful for manual traders to set similar levels
Disable for cleaner chart (recommended for presentations)
7. Dynamic Trend EMA
Gradient-colored trend line that visualizes trend strength:
Calculation:
EMA(close, trend_length) - default 50 period (configurable 20-100)
Slope calculated over 10 bars: (current_ema - ema ) / ema × 100
Color Logic:
Trend_direction:
Slope > 0.1% = Bullish (1)
Slope < -0.1% = Bearish (-1)
Otherwise = Neutral (0)
Trend_strength = abs(slope)
Color = Gradient between:
- Neutral color (gray/purple)
- Strong bullish (bright green) if direction = 1
- Strong bearish (bright red) if direction = -1
Gradient factor = trend_strength (0 to 1+ scale)
Visual Behavior:
Faint gray/purple = weak/no trend (choppy conditions)
Light green/red = emerging trend (low strength)
Bright green/red = strong trend (high conviction)
Color intensity = trend strength magnitude
Transparency: 50% (subtle, doesn't overpower price action)
Purpose: Subconscious awareness of trend state without checking dashboard or indicators.
8. Regime Background Tinting (Subtle)
Ultra-low opacity background color indicating detected market regime:
Regime Detection:
Efficiency = directional_movement / total_range (over trend_length bars)
Vol_ratio = current_volatility / average_volatility
IF (efficiency > 0.5 AND vol_ratio < 1.3):
Regime = Trending (1)
ELSE IF (vol_ratio > 1.5):
Regime = Volatile (2)
ELSE:
Regime = Choppy (0)
Background Colors:
Trending: theme.regime_trending (dark green, 92-93% transparency)
Volatile: theme.regime_volatile (dark red, 93% transparency)
Choppy: No tint (normal background)
Purpose:
Subliminal regime awareness
Helps explain why signals are/aren't generating
Trending = ideal conditions for AGE
Volatile = fewer signals, higher thresholds applied
Choppy = mixed signals, lower confidence
Important: Extremely subtle by design. Not meant to be obvious, just subconscious context.
📊 ENHANCED DASHBOARD
Comprehensive real-time metrics in single organized panel (top-right position):
Dashboard Structure (5 columns × 14 rows)
Header Row:
Column 0: "🧬 AGE PRO" + phase indicator (🔴 LIVE or ⏪ HIST)
Column 1: "POPULATION"
Column 2: "PERFORMANCE"
Column 3: "CURRENT SIGNAL"
Column 4: "ACTIVE STRATEGY"
Column 0: Market State
Regime (📈 TREND / 🌊 CHAOS / ➖ CHOP)
DVS Ratio (current volatility scaling factor, format: #.##)
Trend Direction (▲ BULL / ▼ BEAR / ➖ FLAT with color coding)
Trend Strength (0-100 scale, format: #.##)
Column 1: Population Metrics
Active strategies (count / max_population)
Validated strategies (WFO passed / active total)
Current generation number
Total spawned (all-time strategy births)
Total culled (all-time strategy deaths)
Column 2: Aggregate Performance
Total trades across all active strategies
Aggregate win rate (%) - color-coded:
Green (>55%)
Orange (45-55%)
Red (<45%)
Total P&L in R-multiples - color-coded by positive/negative
Best fitness score in population (format: #.###)
MAS - Minimum Adaptation Score (cull threshold, format: #.###)
Column 3: Current Signal Status
Status indicator:
"▲ LONG" (green) if selected strategy in long position
"▼ SHORT" (red) if selected strategy in short position
"⏳ FORMING" (orange) if signal persisting but not yet executed
"○ WAITING" (gray) if no active signal
Confidence percentage (0-100%, format: #.#%)
Quality assessment:
"🔥 ELITE" (cyan) for 85%+ probability
"✓ STRONG" (bright green) for 75-85%
"○ GOOD" (green) for 65-75%
"- LOW" (dim) for <65%
Confluence score (X/3 format)
Signal age:
"X bars" if signal forming
"IN TRADE" if position active
"---" if no signal
Column 4: Selected Strategy Details
Strategy ID number (#X format)
Validation status:
"✓ VAL" (green) if WFO validated
"○ TRAIN" (orange) if still in training/testing phase
Generation number (GX format)
Personal fitness score (format: #.### with color coding)
Trade count
P&L and win rate (format: #.#R (##%) with color coding)
Color Scheme:
Panel background: theme.panel_bg (dark, low opacity)
Panel headers: theme.panel_header (slightly lighter)
Primary text: theme.text_primary (bright, high contrast)
Secondary text: theme.text_secondary (dim, lower contrast)
Positive metrics: theme.metric_positive (green)
Warning metrics: theme.metric_warning (orange)
Negative metrics: theme.metric_negative (red)
Special markers: theme.validated_marker, theme.spawn_marker
Update Frequency: Only on barstate.islast (current bar) to minimize CPU usage
Purpose:
Quick overview of entire system state
No need to check multiple indicators
Trading decisions informed by population health, regime state, and signal quality
Transparency into what AGE is thinking
🔍 DIAGNOSTICS PANEL (Optional, Default: OFF)
Detailed signal quality tracking for optimization and debugging:
Panel Structure (3 columns × 8 rows)
Position: Bottom-right corner (doesn't interfere with main dashboard)
Header Row:
Column 0: "🔍 DIAGNOSTICS"
Column 1: "COUNT"
Column 2: "%"
Metrics Tracked (for selected strategy only):
Total Evaluated:
Every signal that passed initial calculation (direction ≠ 0)
Represents total opportunities considered
✓ Passed:
Signals that passed quality gate and executed
Green color coding
Percentage of evaluated signals
Rejection Breakdown:
⨯ Probability:
Rejected because probability < minimum threshold
Most common rejection reason typically
⨯ Confluence:
Rejected because confluence < minimum required (e.g., only 1 of 3 indicators agreed)
⨯ Trend:
Rejected because signal opposed strong trend
Indicates counter-trend protection working
⨯ Regime:
Rejected because volatile regime detected and probability wasn't high enough to override
Shows regime filter in action
⨯ Volume:
Rejected because volume < 70% of 20-bar average
Indicates volume confirmation requirement
Color Coding:
Passed count: Green (success metric)
Rejection counts: Red (failure metrics)
Percentages: Gray (neutral, informational)
Performance Cost: Slight CPU overhead for tracking counters. Disable when not actively optimizing settings.
How to Use Diagnostics
Scenario 1: Too Few Signals
Evaluated: 200
Passed: 10 (5%)
⨯ Probability: 120 (60%)
⨯ Confluence: 40 (20%)
⨯ Others: 30 (15%)
Diagnosis: Probability threshold too high for this strategy's DNA.
Solution: Lower min probability from 65% to 60%, or allow strategy more time to evolve better DNA.
Scenario 2: Too Many False Signals
Evaluated: 200
Passed: 80 (40%)
Strategy win rate: 45%
Diagnosis: Quality gate too loose, letting low-quality signals through.
Solution: Raise min probability to 70%, or increase min confluence to 3 (all indicators must agree).
Scenario 3: Regime-Specific Issues
⨯ Regime: 90 (45% of rejections)
Diagnosis: Frequent volatile regime detection blocking otherwise good signals.
Solution: Either accept fewer trades during chaos (recommended), or disable regime filter if you want signals regardless of market state.
Optimization Workflow:
Enable diagnostics
Run 200+ bars
Analyze rejection patterns
Adjust settings based on data
Re-run and compare pass rate
Disable diagnostics when satisfied
⚙️ CONFIGURATION GUIDE
🧬 Evolution Engine Settings
Enable AGE Evolution (Default: ON):
ON: Full genetic algorithm (recommended for best results)
OFF: Uses only 4 seed strategies, no spawning/culling (static population for comparison testing)
Max Population (4-12, Default: 8):
Higher = more diversity, more exploration, slower performance
Lower = faster computation, less exploration, risk of premature convergence
Sweet spot: 6-8 for most use cases
4 = minimum for meaningful evolution
12 = maximum before diminishing returns
Min Population (2-4, Default: 3):
Safety floor - system never culls below this count
Prevents population extinction during harsh selection
Should be at least half of max population
Elite Preservation (1-3, Default: 2):
Top N performers completely immune to culling
Ensures best genes always survive
1 = minimal protection, aggressive selection
2 = balanced (recommended)
3 = conservative, slower gene pool turnover
Historical: Spawn Interval (10-100, Default: 30):
Bars between spawning new strategies during historical data
Lower = faster evolution, more exploration
Higher = slower evolution, more evaluation time per strategy
30 bars = ~1-2 hours on 15min chart
Historical: Cull Interval (20-200, Default: 60):
Bars between culling weak strategies during historical data
Should be 2x spawn interval for balanced churn
Lower = aggressive selection pressure
Higher = patient evaluation
Live: Spawn Interval (100-500, Default: 200):
Bars between spawning during live trading
Much slower than historical for stability
Prevents population chaos during live trading
200 bars = ~1.5 trading days on 15min chart
Live: Cull Interval (200-1000, Default: 400):
Bars between culling during live trading
Should be 2x live spawn interval
Conservative removal during live trading
Historical: Mutation Rate (0.05-0.40, Default: 0.20):
Probability each gene mutates during breeding (20% = 2 out of 10 genes on average)
Higher = more exploration, slower convergence
Lower = more exploitation, faster convergence but risk of local optima
20% balances exploration vs exploitation
Live: Mutation Rate (0.02-0.20, Default: 0.08):
Mutation rate during live trading
Much lower for stability (don't want population to suddenly degrade)
8% = mostly inherits parent genes with small tweaks
Mutation Strength (0.05-0.25, Default: 0.12):
How much genes change when mutated (% of gene's total range)
0.05 = tiny nudges (fine-tuning)
0.12 = moderate jumps (recommended)
0.25 = large leaps (aggressive exploration)
Example: If gene range is 0.5-2.0, 12% strength = ±0.18 possible change
📈 Signal Quality Settings
Min Signal Probability (0.55-0.80, Default: 0.65):
Quality gate threshold - signals below this never generate
0.55-0.60 = More signals, accept lower confidence (higher risk)
0.65 = Institutional-grade balance (recommended)
0.70-0.75 = Fewer but higher-quality signals (conservative)
0.80+ = Very selective, very few signals (ultra-conservative)
Min Confluence Score (1-3, Default: 2):
Required indicator agreement before signal generates
1 = Any single indicator can trigger (not recommended - too many false signals)
2 = Requires 2 of 3 indicators agree (RECOMMENDED for balance)
3 = All 3 must agree (very selective, few signals, high quality)
Base Persistence Bars (1-5, Default: 2):
Base bars signal must persist before entry
System adapts automatically:
High probability signals (75%+) enter 1 bar faster
Low probability signals (<68%) need 1 bar more
Trending regime: -1 bar (faster entries)
Volatile regime: +1 bar (more confirmation)
1 = Immediate entry after quality gate (responsive but prone to whipsaw)
2 = Balanced confirmation (recommended)
3-5 = Patient confirmation (slower but more reliable)
Cooldown After Trade (3-20, Default: 8):
Bars to wait after exit before next entry allowed
Prevents overtrading and revenge trading
3 = Minimal cooldown (active trading)
8 = Balanced (recommended)
15-20 = Conservative (position trading)
Entropy Length (10-50, Default: 20):
Lookback period for market order/disorder calculation
Lower = more responsive to regime changes (noisy)
Higher = more stable regime detection (laggy)
20 = works across most timeframes
Momentum Length (5-30, Default: 14):
Period for RSI/ROC calculations
14 = standard (RSI default)
Lower = more signals, less reliable
Higher = fewer signals, more reliable
Structure Length (20-100, Default: 50):
Lookback for support/resistance swing range
20 = short-term swings (day trading)
50 = medium-term structure (recommended)
100 = major structure (position trading)
Trend EMA Length (20-100, Default: 50):
EMA period for trend detection and direction bias
20 = short-term trend (responsive)
50 = medium-term trend (recommended)
100 = long-term trend (position trading)
ATR Period (5-30, Default: 14):
Period for volatility measurement
14 = standard ATR
Lower = more responsive to vol changes
Higher = smoother vol calculation
📊 Volatility Scaling (DVS) Settings
Enable DVS (Default: ON):
Dynamic volatility scaling for adaptive stop/target placement
Highly recommended to leave ON
OFF only for testing fixed-distance stops
DVS Method (Default: Ensemble):
ATR Ratio: Simple, fast, single-method (good for beginners)
Parkinson: High-low range based (good for intraday)
Garman-Klass: OHLC based (sophisticated, considers gaps)
Ensemble: Median of all three (RECOMMENDED - most robust)
DVS Memory (20-200, Default: 100):
Lookback for baseline volatility comparison
20 = very responsive to vol changes (can overreact)
100 = balanced adaptation (recommended)
200 = slow, stable baseline (minimizes false vol signals)
DVS Sensitivity (0.3-1.5, Default: 0.7):
How much volatility affects scaling (power-law exponent)
0.3 = Conservative, heavily dampens vol impact (cube root)
0.5 = Moderate dampening (square root)
0.7 = Balanced response (recommended)
1.0 = Linear, full 1:1 vol response
1.5 = Aggressive, amplified response (exponential)
🔬 Walk-Forward Optimization Settings
Enable WFO (Default: ON):
Out-of-sample validation to prevent overfitting
Highly recommended to leave ON
OFF only for testing or if you want unvalidated strategies
Training Window (100-500, Default: 250):
Bars for in-sample optimization
100 = fast validation, less data (risky)
250 = balanced (recommended) - about 1-2 months on daily, 1-2 weeks on 15min
500 = patient validation, more data (conservative)
Testing Window (30-200, Default: 75):
Bars for out-of-sample validation
Should be ~30% of training window
30 = minimal test (fast validation)
75 = balanced (recommended)
200 = extensive test (very conservative)
Min Trades for Validation (3-15, Default: 5):
Required trades in BOTH training AND testing periods
3 = minimal sample (risky, fast validation)
5 = balanced (recommended)
10+ = conservative (slow validation, high confidence)
WFO Efficiency Threshold (0.3-0.9, Default: 0.55):
Minimum test/train performance ratio required
0.30 = Very loose (test must be 30% as good as training)
0.55 = Balanced (recommended) - test must be 55% as good
0.70+ = Strict (test must closely match training)
Higher = fewer validated strategies, lower risk of overfitting
🎨 Premium Visuals Settings
Visual Theme:
Neon Genesis: Cyberpunk aesthetic (cyan/magenta/purple)
Carbon Fiber: Industrial look (blue/red/gray)
Quantum Blue: Quantum computing (blue/purple/pink)
Aurora: Northern lights (teal/orange/purple)
⚡ Gradient Probability Cloud (Default: ON):
Multi-layer gradient showing signal buildup
Turn OFF if chart lags or for cleaner look
Cloud Gradient Layers (3-15, Default: 7):
More layers = smoother gradient, more CPU intensive
Fewer layers = faster, blockier appearance
🎗️ Population Fitness Ribbon (Default: ON):
Histogram showing fitness distribution
Turn OFF for cleaner chart
Ribbon Layers (5-20, Default: 10):
More layers = finer fitness detail
Fewer layers = simpler histogram
⭕ Signal Confidence Halo (Default: ON):
Circular indicator around entry signals
Size/brightness scales with probability
Minimal performance cost
🔬 Evolution Event Markers (Default: ON):
Diamond (spawn) and X (cull) markers
Shows genetic algorithm activity
Minimal performance cost
🎯 Stop/Target Lines (Default: ON):
Shows shadow portfolio stop/target levels
Turn OFF for cleaner chart (recommended for screenshots/presentations)
📊 Enhanced Dashboard (Default: ON):
Comprehensive metrics panel
Should stay ON unless you want zero overlays
🔍 Diagnostics Panel (Default: OFF):
Detailed signal rejection tracking
Turn ON when optimizing settings
Turn OFF during normal use (slight performance cost)
📈 USAGE WORKFLOW - HOW TO USE THIS INDICATOR
Phase 1: Initial Setup & Learning
Add AGE to your chart
Recommended timeframes: 15min, 30min, 1H (best signal-to-noise ratio)
Works on: 5min (day trading), 4H (swing trading), Daily (position trading)
Load 1000+ bars for sufficient evolution history
Let the population evolve (100+ bars minimum)
First 50 bars: Random exploration, poor results expected
Bars 50-150: Population converging, fitness improving
Bars 150+: Stable performance, validated strategies emerging
Watch the dashboard metrics
Population should grow toward max capacity
Generation number should advance regularly
Validated strategies counter should increase
Best fitness should trend upward toward 0.50-0.70 range
Observe evolution markers
Diamond markers (cyan) = new strategies spawning
X markers (red) = weak strategies being culled
Frequent early activity = healthy evolution
Activity slowing = population stabilizing
Be patient. Evolution takes time. Don't judge performance before 150+ bars.
Phase 2: Signal Observation
Watch signals form
Gradient cloud builds up 2-3 bars before entry
Cloud brightness = probability strength
Cloud thickness = signal persistence
Check signal quality
Look at confidence halo size when entry marker appears
Large bright halo = elite setup (85%+)
Medium halo = strong setup (75-85%)
Small halo = good setup (65-75%)
Verify market conditions
Check trend EMA color (green = uptrend, red = downtrend, gray = choppy)
Check background tint (green = trending, red = volatile, clear = choppy)
Trending background + aligned signal = ideal conditions
Review dashboard signal status
Current Signal column shows:
Status (Long/Short/Forming/Waiting)
Confidence % (actual probability value)
Quality assessment (Elite/Strong/Good)
Confluence score (2/3 or 3/3 preferred)
Only signals meeting ALL quality gates appear on chart. If you're not seeing signals, population is either still learning or market conditions aren't suitable.
Phase 3: Manual Trading Execution
When Long Signal Fires:
Verify confidence level (dashboard or halo size)
Confirm trend alignment (EMA sloping up, green color)
Check regime (preferably trending or choppy, avoid volatile)
Enter long manually on your broker platform
Set stop loss at displayed stop line level (if lines enabled), or use your own risk management
Set take profit at displayed target line level, or trail manually
Monitor position - exit if X marker appears (signal reversal)
When Short Signal Fires:
Same verification process
Confirm downtrend (EMA sloping down, red color)
Enter short manually
Use displayed stop/target levels or your own
AGE tells you WHEN and HOW CONFIDENT. You decide WHETHER and HOW MUCH.
Phase 4: Set Up Alerts (Never Miss a Signal)
Right-click on indicator name in legend
Select "Add Alert"
Choose condition:
"AGE Long" = Long entry signal fired
"AGE Short" = Short entry signal fired
"AGE Exit" = Position reversal/exit signal
Set notification method:
Sound alert (popup on chart)
Email notification
Webhook to phone/trading platform
Mobile app push notification
Name the alert (e.g., "AGE BTCUSD 15min Long")
Save alert
Recommended: Set alerts for both long and short, enable mobile push notifications. You'll get alerted in real-time even if not watching charts.
Phase 5: Monitor Population Health
Weekly Review:
Check dashboard Population column:
Active count should be near max (6-8 of 8)
Validated count should be >50% of active
Generation should be advancing (1-2 per week typical)
Check dashboard Performance column:
Aggregate win rate should be >50% (target: 55-65%)
Total P&L should be positive (may fluctuate)
Best fitness should be >0.50 (target: 0.55-0.70)
MAS should be declining slowly (normal adaptation)
Check Active Strategy column:
Selected strategy should be validated (✓ VAL)
Personal fitness should match best fitness
Trade count should be accumulating
Win rate should be >50%
Warning Signs:
Zero validated strategies after 300+ bars = settings too strict or market unsuitable
Best fitness stuck <0.30 = population struggling, consider parameter adjustment
No spawning/culling for 200+ bars = evolution stalled (may be optimal or need reset)
Aggregate win rate <45% sustained = system not working on this instrument/timeframe
Health Check Pass:
50%+ strategies validated
Best fitness >0.50
Aggregate win rate >52%
Regular spawn/cull activity
Selected strategy validated
Phase 6: Optimization (If Needed)
Enable Diagnostics Panel (bottom-right) for data-driven tuning:
Problem: Too Few Signals
Evaluated: 200
Passed: 8 (4%)
⨯ Probability: 140 (70%)
Solutions:
Lower min probability: 65% → 60% or 55%
Reduce min confluence: 2 → 1
Lower base persistence: 2 → 1
Increase mutation rate temporarily to explore new genes
Check if regime filter is blocking signals (⨯ Regime high?)
Problem: Too Many False Signals
Evaluated: 200
Passed: 90 (45%)
Win rate: 42%
Solutions:
Raise min probability: 65% → 70% or 75%
Increase min confluence: 2 → 3
Raise base persistence: 2 → 3
Enable WFO if disabled (validates strategies before use)
Check if volume filter is being ignored (⨯ Volume low?)
Problem: Counter-Trend Losses
⨯ Trend: 5 (only 5% rejected)
Losses often occur against trend
Solutions:
System should already filter trend opposition
May need stronger trend requirement
Consider only taking signals aligned with higher timeframe trend
Use longer trend EMA (50 → 100)
Problem: Volatile Market Whipsaws
⨯ Regime: 100 (50% rejected by volatile regime)
Still getting stopped out frequently
Solutions:
System is correctly blocking volatile signals
Losses happening because vol filter isn't strict enough
Consider not trading during volatile periods (respect the regime)
Or disable regime filter and accept higher risk
Optimization Workflow:
Enable diagnostics
Run 200+ bars with current settings
Analyze rejection patterns and win rate
Make ONE change at a time (scientific method)
Re-run 200+ bars and compare results
Keep change if improvement, revert if worse
Disable diagnostics when satisfied
Never change multiple parameters at once - you won't know what worked.
Phase 7: Multi-Instrument Deployment
AGE learns independently on each chart:
Recommended Strategy:
Deploy AGE on 3-5 different instruments
Different asset classes ideal (e.g., ES futures, EURUSD, BTCUSD, SPY, Gold)
Each learns optimal strategies for that instrument's personality
Take signals from all 5 charts
Natural diversification reduces overall risk
Why This Works:
When one market is choppy, others may be trending
Different instruments respond to different news/catalysts
Portfolio-level win rate more stable than single-instrument
Evolution explores different parameter spaces on each chart
Setup:
Same settings across all charts (or customize if preferred)
Set alerts for all
Take every validated signal across all instruments
Position size based on total account (don't overleverage any single signal)
⚠️ REALISTIC EXPECTATIONS - CRITICAL READING
What AGE Can Do
✅ Generate probability-weighted signals using genetic algorithms
✅ Evolve strategies in real-time through natural selection
✅ Validate strategies on out-of-sample data (walk-forward optimization)
✅ Adapt to changing market conditions automatically over time
✅ Provide comprehensive metrics on population health and signal quality
✅ Work on any instrument, any timeframe, any broker
✅ Improve over time as weak strategies are culled and fit strategies breed
What AGE Cannot Do
❌ Win every trade (typical win rate: 55-65% at best)
❌ Predict the future with certainty (markets are probabilistic, not deterministic)
❌ Work perfectly from bar 1 (needs 100-150 bars to learn and stabilize)
❌ Guarantee profits under all market conditions
❌ Replace your trading discipline and risk management
❌ Execute trades automatically (this is an indicator, not a strategy)
❌ Prevent all losses (drawdowns are normal and expected)
❌ Adapt instantly to regime changes (re-learning takes 50-100 bars)
Performance Realities
Typical Performance After Evolution Stabilizes (150+ bars):
Win Rate: 55-65% (excellent for trend-following systems)
Profit Factor: 1.5-2.5 (realistic for validated strategies)
Signal Frequency: 5-15 signals per 100 bars (quality over quantity)
Drawdown Periods: 20-40% of time in equity retracement (normal trading reality)
Max Consecutive Losses: 5-8 losses possible even with 60% win rate (probability says this is normal)
Evolution Timeline:
Bars 0-50: Random exploration, learning phase - poor results expected, don't judge yet
Bars 50-150: Population converging, fitness climbing - results improving
Bars 150-300: Stable performance, most strategies validated - consistent results
Bars 300+: Mature population, optimal genes dominant - best results
Market Condition Dependency:
Trending Markets: AGE excels - clear directional moves, high-probability setups
Choppy Markets: AGE struggles - fewer signals generated, lower win rate
Volatile Markets: AGE cautious - higher rejection rate, wider stops, fewer trades
Market Regime Changes:
When market shifts from trending to choppy overnight
Validated strategies can become temporarily invalidated
AGE will adapt through evolution, but not instantly
Expect 50-100 bar re-learning period after major regime shifts
Fitness may temporarily drop then recover
This is NOT a holy grail. It's a sophisticated signal generator that learns and adapts using genetic algorithms. Your success depends on:
Patience during learning periods (don't abandon after 3 losses)
Proper position sizing (risk 0.5-2% per trade, not 10%)
Following signals consistently (cherry-picking defeats statistical edge)
Not abandoning system prematurely (give it 200+ bars minimum)
Understanding probability (60% win rate means 40% of trades WILL lose)
Respecting market conditions (trending = trade more, choppy = trade less)
Managing emotions (AGE is emotionless, you need to be too)
Expected Drawdowns:
Single-strategy max DD: 10-20% of equity (normal)
Portfolio across multiple instruments: 5-15% (diversification helps)
Losing streaks: 3-5 consecutive losses expected periodically
No indicator eliminates risk. AGE manages risk through:
Quality gates (rejecting low-probability signals)
Confluence requirements (multi-indicator confirmation)
Persistence requirements (no knee-jerk reactions)
Regime awareness (reduced trading in chaos)
Walk-forward validation (preventing overfitting)
But it cannot prevent all losses. That's inherent to trading.
🔧 TECHNICAL SPECIFICATIONS
Platform: TradingView Pine Script v5
Indicator Type: Overlay indicator (plots on price chart)
Execution Type: Signals only - no automatic order placement
Computational Load:
Moderate to High (genetic algorithms + shadow portfolios)
8 strategies × shadow portfolio simulation = significant computation
Premium visuals add additional load (gradient cloud, fitness ribbon)
TradingView Resource Limits (Built-in Caps):
Max Bars Back: 500 (sufficient for WFO and evolution)
Max Labels: 100 (plenty for entry/exit markers)
Max Lines: 150 (adequate for stop/target lines)
Max Boxes: 50 (not heavily used)
Max Polylines: 100 (confidence halos)
Recommended Chart Settings:
Timeframe: 15min to 1H (optimal signal/noise balance)
5min: Works but noisier, more signals
4H/Daily: Works but fewer signals
Bars Loaded: 1000+ (ensures sufficient evolution history)
Replay Mode: Excellent for testing without risk
Performance Optimization Tips:
Disable gradient cloud if chart lags (most CPU intensive visual)
Disable fitness ribbon if still laggy
Reduce cloud layers from 7 to 3
Reduce ribbon layers from 10 to 5
Turn off diagnostics panel unless actively tuning
Close other heavy indicators to free resources
Browser/Platform Compatibility:
Works on all modern browsers (Chrome, Firefox, Safari, Edge)
Mobile app supported (full functionality on phone/tablet)
Desktop app supported (best performance)
Web version supported (may be slower on older computers)
Data Requirements:
Real-time or delayed data both work
No special data feeds required
Works with TradingView's standard data
Historical + live data seamlessly integrated
🎓 THEORETICAL FOUNDATIONS
AGE synthesizes advanced concepts from multiple disciplines:
Evolutionary Computation
Genetic Algorithms (Holland, 1975): Population-based optimization through natural selection metaphor
Tournament Selection: Fitness-based parent selection with diversity preservation
Crossover Operators: Fitness-weighted gene recombination from two parents
Mutation Operators: Random gene perturbation for exploration of new parameter space
Elitism: Preservation of top N performers to prevent loss of best solutions
Adaptive Parameters: Different mutation rates for historical vs. live phases
Technical Analysis
Support/Resistance: Price structure within swing ranges
Trend Following: EMA-based directional bias
Momentum Analysis: RSI, ROC, MACD composite indicators
Volatility Analysis: ATR-based risk scaling
Volume Confirmation: Trade activity validation
Information Theory
Shannon Entropy (1948): Quantification of market order vs. disorder
Signal-to-Noise Ratio: Directional information vs. random walk
Information Content: How much "information" a price move contains
Statistics & Probability
Walk-Forward Analysis: Rolling in-sample/out-of-sample optimization
Out-of-Sample Validation: Testing on unseen data to prevent overfitting
Monte Carlo Principles: Shadow portfolio simulation with realistic execution
Expectancy Theory: Win rate × avg win - loss rate × avg loss
Probability Distributions: Signal confidence quantification
Risk Management
ATR-Based Stops: Volatility-normalized risk per trade
Volatility Regime Detection: Market state classification (trending/choppy/volatile)
Drawdown Control: Peak-to-trough equity measurement
R-Multiple Normalization: Performance measurement in risk units
Machine Learning Concepts
Online Learning: Continuous adaptation as new data arrives
Fitness Functions: Multi-objective optimization (win rate + expectancy + drawdown)
Exploration vs. Exploitation: Balance between trying new strategies and using proven ones
Overfitting Prevention: Walk-forward validation as regularization
Novel Contribution:
AGE is the first TradingView indicator to apply genetic algorithms to real-time indicator parameter optimization while maintaining strict anti-overfitting controls through walk-forward validation.
Most "adaptive" indicators simply recalibrate lookback periods or thresholds. AGE evolves entirely new strategies through competitive selection - it's not parameter tuning, it's Darwinian evolution of trading logic itself.
The combination of:
Genetic algorithm population management
Shadow portfolio simulation for realistic fitness evaluation
Walk-forward validation to prevent overfitting
Multi-indicator confluence for signal quality
Dynamic volatility scaling for adaptive risk
...creates a system that genuinely learns and improves over time while avoiding the curse of curve-fitting that plagues most optimization approaches.
🏗️ DEVELOPMENT NOTES
This project represents months of intensive development, facing significant technical challenges:
Challenge 1: Making Genetics Actually Work
Early versions spawned garbage strategies that polluted the gene pool:
Random gene combinations produced nonsensical parameter sets
Weak strategies survived too long, dragging down population
No clear convergence toward optimal solutions
Solution:
Comprehensive fitness scoring (4 factors: win rate, P&L, expectancy, drawdown)
Elite preservation (top 2 always protected)
Walk-forward validation (unproven strategies penalized 30%)
Tournament selection (fitness-weighted breeding)
Adaptive culling (MAS decay creates increasing selection pressure)
Challenge 2: Balancing Evolution Speed vs. Stability
Too fast = population chaos, no convergence. Too slow = can't adapt to regime changes.
Solution:
Dual-phase timing: Fast evolution during historical (30/60 bar intervals), slow during live (200/400 bar intervals)
Adaptive mutation rates: 20% historical, 8% live
Spawn/cull ratio: Always 2:1 to prevent population collapse
Challenge 3: Shadow Portfolio Accuracy
Needed realistic trade simulation without lookahead bias:
Can't peek at future bars for exits
Must track multiple portfolios simultaneously
Stop/target checks must use bar's high/low correctly
Solution:
Entry on close (realistic)
Exit checks on current bar's high/low (realistic)
Independent position tracking per strategy
Cooldown periods to prevent unrealistic rapid re-entry
ATR-normalized P&L (R-multiples) for fair comparison across volatility regimes
Challenge 4: Pine Script Compilation Limits
Hit TradingView's execution limits multiple times:
Too many array operations
Too many variables
Too complex conditional logic
Solution:
Optimized data structures (single DNA array instead of 8 separate arrays)
Minimal visual overlays (only essential plots)
Efficient fitness calculations (vectorized where possible)
Strategic use of barstate.islast to minimize dashboard updates
Challenge 5: Walk-Forward Implementation
Standard WFO is difficult in Pine Script:
Can't easily "roll forward" through historical data
Can't re-optimize strategies mid-stream
Must work in real-time streaming environment
Solution:
Age-based phase detection (first 250 bars = training, next 75 = testing)
Separate metric tracking for train vs. test
Efficiency calculation at fixed interval (after test period completes)
Validation flag persists for strategy lifetime
Challenge 6: Signal Quality Control
Early versions generated too many signals with poor win rates:
Single indicators produced excessive noise
No trend alignment
No regime awareness
Instant entries on single-bar spikes
Solution:
Three-layer confluence system (entropy + momentum + structure)
Minimum 2-of-3 agreement requirement
Trend alignment checks (penalty for counter-trend)
Regime-based probability adjustments
Persistence requirements (signals must hold multiple bars)
Volume confirmation
Quality gate (probability + confluence thresholds)
The Result
A system that:
Truly evolves (not just parameter sweeps)
Truly validates (out-of-sample testing)
Truly adapts (ongoing competition and breeding)
Stays within TradingView's platform constraints
Provides institutional-quality signals
Maintains transparency (full metrics dashboard)
Development time: 3+ months of iterative refinement
Lines of code: ~1500 (highly optimized)
Test instruments: ES, NQ, EURUSD, BTCUSD, SPY, AAPL
Test timeframes: 5min, 15min, 1H, Daily
🎯 FINAL WORDS
The Adaptive Genesis Engine is not just another indicator - it's a living system that learns, adapts, and improves through the same principles that drive biological evolution. Every bar it observes adds to its experience. Every strategy it spawns explores new parameter combinations. Every strategy it culls removes weakness from the gene pool.
This is evolution in action on your charts.
You're not getting a static formula locked in time. You're getting a system that thinks , that competes , that survives through natural selection. The strongest strategies rise to the top. The weakest die. The gene pool improves generation after generation.
AGE doesn't claim to predict the future - it adapts to whatever the future brings. When markets shift from trending to choppy, from calm to volatile, from bullish to bearish - AGE evolves new strategies suited to the new regime.
Use it on any instrument. Any timeframe. Any market condition. AGE will adapt.
This indicator gives you the pure signal intelligence. How you choose to act on it - position sizing, risk management, execution discipline - that's your responsibility. AGE tells you when and how confident . You decide whether and how much .
Trust the process. Respect the evolution. Let Darwin work.
"In markets, as in nature, it is not the strongest strategies that survive, nor the most intelligent - but those most responsive to change."
Taking you to school. — Dskyz, Trade with insight. Trade with anticipation.
— Happy Holiday's
BTC - FRIC: Friction & Realized Intensity CompositeTitle: BTC - FRIC: Friction & Realized Intensity Composite
Data: IntoTheBlock
Overview & Philosophy
FRIC (Friction & Realized Intensity Composite) is a specialized on-chain oscillator designed to visualize the "psychological battlegrounds" of the Bitcoin network.
Most indicators focus on Price or Momentum. FRIC focuses on Cost Basis. It operates on the thesis that the market experiences maximum "Friction" when the price revisits the cost basis of a large number of holders. These are the zones where investors are emotionally triggered to react—either to exit "at breakeven" after a loss (creating resistance) or to defend their entry (creating support).
This indicator answers two questions simultaneously:
Intensity: Is the market hitting a Wall (High Friction) or a Vacuum (Low Friction)?
Valuation: Is this happening at a market bottom or a top?
The "Alpha" (Wall vs. Vacuum)
Why we visualize both extremes: This indicator filters out the "Noise" (the middle range) to show you only the statistically significant anomalies.
1. The "Wall" (Positive Z-Score Bars)
What it is : A statistically high number of addresses are at breakeven.
The Implication : Expect a grind. Price action often slows down or reverses here because "Bag Holders" are selling into strength to get out flat, or new buyers are establishing a floor.
2. The "Vacuum" (Negative Z-Score Bars)
What it is : A statistically low number of addresses are at breakeven.
The Implication : Expect acceleration. The price is moving through a zone where very few people have a cost basis. With no natural "breakeven supply" to block the path, price often enters Price Discovery or Free Fall.
Methodology
The indicator constructs a composite view using two premium metrics from IntoTheBlock:
1. The "Activity" (Friction Z-Score): We utilize the Breakeven Addresses Percentage. This measures the % of all addresses where the current price equals the average cost basis.
- Normalization: We apply a rolling Z-Score (Standard Deviation) to this data.
- The Filter: We hide the "Noise" (e.g., Z-Scores between -2.0 and +2.0) to isolate only the events where market structure is truly stretched.
2. The "Context" (Valuation Heatmap): We utilize the MVRV Ratio to color-code the friction.
Deep Value (< 1.0): Price is below the average "Fair Value" of the network.
Overheated (> 3.0): Price is significantly extended above the "Fair Value."
Credit: The MVRV Ratio was originally conceptualized by Murad Mahmudov and David Puell. It remains one of the gold standards for detecting Bitcoin's fair value deviations.
How to Read the Indicator
The chart is visualized as a Noise-Filtered Heatmap.
1. The Bars (Intensity)
Bars Above Zero: High Friction (Congestion). The market is fighting through a supply wall.
Bars Below Zero: Low Friction (Vacuum). The market is accelerating through thin air.
Gray/Ghosted: Noise. Routine market activity; no significant signal.
2. The Colors (Valuation Context) The color tells you why the friction is happening:
🟦 Deep Blue (The "Capitulation Buy"):
Signal: High Friction + Low MVRV.
Meaning : Investors are panic-selling at breakeven/loss, but the asset is fundamentally undervalued. Historically, these are high-conviction cycle bottoms.
🟥 Dark Red (The "FOMO Sell"):
Signal: High Friction + High MVRV.
Meaning : Investors are churning at high valuations. Smart money is often distributing to late retail arrivers. Historically marks cycle tops.
🟨 Yellow/Orange (The "Trend Battle"):
Signal: High Friction + Neutral MVRV.
Meaning : The market is contesting a level within a trend (e.g., a mid-cycle correction).
Visual Guide & Features
10-Zone Heatmap: A granular color gradient that shifts from Dark Blue (Deep Value) → Sky Blue → Grey (Neutral) → Orange → Dark Red (Top).
Noise Filter
A unique feature that "ghosts out" insignificant data, leaving only the statistically relevant signals visible.
Data Check Monitor
A diagnostic table in the bottom-right corner that confirms the live connection to IntoTheBlock data streams and displays the current regime in real-time.
Settings
Lookback Period (Default: 90): The rolling window used for the Z-Score calculation. Shortening this (e.g., to 30) makes the indicator more sensitive to local volatility; lengthening it (e.g., to 365) aligns it with macro cycles.
Noise Threshold (Default: 2.0): The strictness of the filter. Only friction events exceeding this Z-Score will be highlighted in full color.
Show Status Table : Toggles the on-screen dashboard.
Disclaimer
This script is for research and educational purposes only. It relies on third-party on-chain data which may be subject to latency or revision. Past performance of on-chain metrics does not guarantee future price action.
Tags
bitcoin, btc, on-chain, mvrv, intotheblock, friction, z-score, fundamental, valuation, cycle
Momentum Candle by DNDFXMomentum Candle v2 is a simple yet powerful indicator designed to detect strong momentum candles based on candle body size and the ratio between the body and total wick.
This indicator is ideal for traders who focus on:
Momentum trading
Breakout strategies
XAUUSD (Gold) scalping
Supply & Demand / Smart Money Concepts (SMC) confirmation
🔧 How the Indicator Works
The indicator analyzes each candle and classifies it as a Bullish Momentum or Bearish Momentum candle when these conditions are met:
✅ The candle body exceeds the minimum size
✅ The total wick is smaller compared to the body
✅ The Body-to-Wick ratio meets the strength filter
Visual signals include:
Green background for bullish momentum
Red background for bearish momentum
Up/Down triangle markers as entry guidance
⚙️ Customizable Parameters
Min Body Size (Points) – Sets the minimum candle body size
Min Body : Wick Ratio – Controls how dominant the body is compared to the wicks
All parameters can be optimized according to your trading style and timeframe.
✅ Best Use Cases
This indicator is useful for:
Breakout confirmation
Momentum validation
Filtering false breakouts
Scalping and intraday trading on XAUUSD
🧠 Trading Tips
For better accuracy, combine this indicator with:
Support & Resistance
Supply & Demand zones
Break of Structure (BOS) / CHoCH
Best performance on M5 – H1 timeframes.
⚠️ DISCLAIMER
This indicator is a supporting tool, not a guaranteed profit system. Always apply proper risk management. You are fully responsible for your trading decisions.
TTM Squeeze Pro Enhanced v1.5.1 [pyrevo]# TTM Squeeze Pro Enhanced
**Version:** 1.5.1
**Author:** pyrevo
**License:** MPL 2.0
## Credits
This indicator is a collective work based on the contributions of the TradingView community:
* **John Carter**: Creator of the original TTM Squeeze and TTM Squeeze Pro concepts.
* **Lazybear**: Original interpretation of the TTM Squeeze (Squeeze Momentum Indicator).
* **Makit0**: Evolution of Lazybear's script to factor in TTM Squeeze Pro upgrades (Squeeze PRO Arrows).
* **marsrides**: Some aesthetics solutions.
* **Beardy_Fred**: The base code from which this enhanced version was derived.
## Overview
**TTM Squeeze Pro Enhanced** is a professional-grade momentum and volatility indicator designed to identify explosive breakout opportunities. It is a refined version of the community's collective works, with amendments primarily to the Squeeze Conditions and visual aesthetics to provide a clearer, more actionable reading of market state.
### The Concept
For those unfamiliar with the TTM Squeeze, it is a visual way of seeing how Bollinger Bands (standard deviations from a simple moving average) relate to Keltner Channels (average true range bands) compared with the momentum of the price action.
The concept is that as Bollinger Bands compress within Keltner Channels, price volatility decreases, giving way for a potential explosive price movement up or down.
### TTM Squeeze vs. TTM Squeeze Pro
* **Original TTM Squeeze:** Uses a 1.5 ATR Keltner Channel.
* **TTM Squeeze Pro (Enhanced):** Uses 1.0, 1.5, and 2.0 ATR Keltner Channels.
This helps differentiate between levels of squeeze (compression). The greater the compression (Bollinger Bands moving deeper into tighter Keltner Channels), the more potential for explosive moves.
## Indicator Analysis
### 1. Squeeze Detection (Dots)
The colored dots along the zero line represent the state of market volatility. This enhanced version uses a distinct color palette to indicate compression levels:
* **🔴 Red Dots (High Compression):** Extreme squeeze. One or both Bollinger Bands are inside the 1.0 ATR Keltner Channel.
* **🟠 Orange Dots (Medium Compression):** Significant squeeze. One or both BBs are inside the 1.5 ATR Keltner Channel.
* **⚪ Gray Dots (Low Compression):** Standard squeeze. One or both BBs are inside the 2.0 ATR Keltner Channel.
* **◽ Light Gray Dots (No Squeeze):** Volatility is normal or expanding. Squeeze has "fired".
### 2. Momentum (Histogram)
The histogram bars show price momentum relative to the squeeze:
* **Bright Green:** Positive, increasing momentum (Bullish).
* **Dark Green:** Positive, decreasing momentum (Bullish exhaustion).
* **Bright Red:** Negative, increasing momentum (Bearish).
* **Dark Red:** Negative, decreasing momentum (Bearish exhaustion).
### 3. Dual Momentum System
An optional secondary system to gauge trend strength:
* **Fast & Slow Momentum Lines:** Moving averages of the momentum to help identify crossovers.
* **Trend Crossovers:** Triangle markers indicate when fast momentum crosses slow momentum.
## Ideal Scenario
As the ticker enters the squeeze, **Gray dots** would warn of the beginning of a low compression squeeze. As the Bollinger bands continue to constrict, **Orange dots** would highlight a medium compression. As the price action and momentum continues to compress, a **Red dot** shows warning of high compression.
As price action leaves the squeeze, the coloring would reverse (Red → Orange → Gray → Light Gray). Any compression squeeze is considered "fired" at the first Light Gray dot that appears.
*Note: This is an ideal progression, however any type of squeeze sequence may appear at anytime.*
## Entry and Exit Guide
* **Entry:** John Carter recommends entering a position after at least 5 dots of compression (Gray/Orange/Red) or waiting for the first "No Squeeze" dot (Light Gray) to appear with confirming momentum.
* **Exit:** Exit on the second bar of decreasing momentum (Dark Green or Dark Red), or remain in the position after confirming a continuing trend through a separate indicator.
## Settings & Customization
* **Timeframe:** Built-in Multi-Timeframe (MTF) support allowing you to view higher-timeframe squeeze signals on lower-timeframe charts.
* **Appearance Modes:**
* **Default:** Standard enhanced palette.
* **Modern:** High-contrast palette (Teal/Red/Gold).
* **Classic MACD:** Traditional Blue/Orange line configuration.
* **Dashboard:** An on-chart table providing real-time data on squeeze status, momentum value, and trend strength.
5MA＋スーパートレンド + Disparity Scalping (SIMPLE FILTER)5MA + ATR Trend Filter + Disparity Scalping
This indicator combines a five-EMA trend framework, an ATR-based trailing trend line, a volatility breakout detector, and an ultra-fast scalping module using RSI and custom momentum prediction.
It is designed for both trend continuation and rapid reversal trading.
🔹 Main Components
1️⃣ Five-EMA Trend Framework
Uses 9 / 20 / 50 / 100 / 200 EMAs
Identifies short-term and long-term market direction
Provides dynamic support and resistance
Helpful for determining breakout vs. pullback conditions
2️⃣ ATR-Based Trailing Trend Line
Uses ATR multiplier to build a trailing stop line
Color change indicates directional shift
Works as a trend filter or trailing stop reference
Helps avoid counter-trend trades during strong trends
3️⃣ High-Volatility Breakout Detector (Optimized for Fast Markets)
Uses ATR expansion, Bollinger band breakout, and volatility comparison (HV vs RV)
Detects sudden market acceleration
Generates breakout BUY/SELL signals when volatility pressure aligns with direction
Useful for explosive markets such as gold or crypto, but compatible with all assets
4️⃣ Ultra-Fast Disparity Scalper
Measures price distance from EMA5 and EMA10
Uses RSI for exhaustion filtering
Predicts momentum turns with a custom RVI-based algorithm
Generates early reversal BUY/SELL signals before full market reaction
Designed for scalping in high-speed environments
5️⃣ Simple Overheat Filter
Blocks trades in extremely overbought/oversold zones
Gray signals indicate low-quality trade setups to avoid
Helps remove “chasing” entries during excessive deviation
🎯 Best Use Cases
Scalping fast reversals
Entering trends after confirmed volatility breakouts
Filtering entries during extreme overbought/oversold phases
Combining EMA structure with breakout momentum
⚠️ Important Notice
This tool is designed to support decision making, not guarantee trade results.
For best performance, combine with:
Price action (market structure)
Volume/volatility context
Support and resistance analysis
🏷️ Short Description (for compact summary)
Five-EMA trend structure with ATR trailing filter, volatility breakout detection, and ultra-fast scalping using RSI + momentum prediction. Suitable for both rapid reversals and trend continuation setups.
