VV Moving Average Convergence Divergence # VMACDv3 - Volume-Weighted MACD with A/D Divergence Detection
## Overview
**VMACDv3** (Volume-Weighted Moving Average Convergence Divergence Version 3) is a momentum indicator that applies volume-weighting to traditional MACD calculations on price, while using the Accumulation/Distribution (A/D) line for divergence detection. This hybrid approach combines volume-weighted price momentum with volume distribution analysis for comprehensive market insight.
## Key Features
- **Volume-Weighted Price MACD**: Traditional MACD calculation on price but weighted by volume for earlier signals
- **A/D Divergence Detection**: Identifies when A/D trend diverges from MACD momentum
- **Volume Strength Filtering**: Distinguishes high-volume confirmations from low-volume noise
- **Color-Coded Histogram**: 4-color system showing momentum direction and volume strength
- **Real-Time Alerts**: Background colors and alert conditions for bullish/bearish divergences
## Difference from ACCDv3
| Aspect | VMACDv3 | ACCDv3 |
|--------|---------|---------|
| **MACD Input** | **Price (Close)** | **A/D Line** |
| **Volume Weighting** | Applied to price | Applied to A/D line |
| **Primary Signal** | Volume-weighted price momentum | Volume distribution momentum |
| **Use Case** | Price momentum with volume confirmation | Volume flow and accumulation/distribution |
| **Sensitivity** | More responsive to price changes | More responsive to volume patterns |
| **Best For** | Trend following, breakouts | Volume analysis, smart money tracking |
**Key Insight**: VMACDv3 shows *where price is going* with volume weight, while ACCDv3 shows *where volume is accumulating/distributing*.
## Components
### 1. Volume-Weighted MACD on Price
Unlike standard MACD that uses simple price EMAs, VMACDv3 weights each price by its corresponding volume:
```
Fast Line = EMA(Price × Volume, 12) / EMA(Volume, 12)
Slow Line = EMA(Price × Volume, 26) / EMA(Volume, 26)
MACD = Fast Line - Slow Line
```
**Benefits of Volume Weighting**:
- High-volume price movements have greater impact
- Filters out low-volume noise and false moves
- Provides earlier trend change signals
- Better reflects institutional activity
### 2. Accumulation/Distribution (A/D) Line
Used for divergence detection, measuring buying/selling pressure:
```
A/D = Σ ((2 × Close - Low - High) / (High - Low)) × Volume
```
- **Rising A/D**: Accumulation (buying pressure)
- **Falling A/D**: Distribution (selling pressure)
- **Doji Handling**: When High = Low, contribution is zero
### 3. Signal Lines
- **MACD Line** (Blue, #2962FF): The fast-slow difference showing momentum
- **Signal Line** (Orange, #FF6D00): EMA or SMA smoothing of MACD
- **Zero Line**: Reference for bullish (above) vs bearish (below) bias
### 4. Histogram Color System
The histogram uses 4 distinct colors based on **direction** and **volume strength**:
| Condition | Color | Meaning |
|-----------|-------|---------|
| Rising + High Volume | **Dark Green** (#1B5E20) | Strong bullish momentum with volume confirmation |
| Rising + Low Volume | **Light Teal** (#26A69A) | Bullish momentum but weak volume (less reliable) |
| Falling + High Volume | **Dark Red** (#B71C1C) | Strong bearish momentum with volume confirmation |
| Falling + Low Volume | **Light Pink** (#FFCDD2) | Bearish momentum but weak volume (less reliable) |
Additional shading:
- **Light Cyan** (#B2DFDB): Positive but not rising (momentum stalling)
- **Bright Red** (#FF5252): Negative and accelerating down
### 5. Divergence Detection
VMACDv3 compares A/D trend against volume-weighted price MACD:
#### Bullish Divergence (Green Background)
- **Condition**: A/D is trending up BUT MACD is negative and trending down
- **Interpretation**: Volume is accumulating while price momentum appears weak
- **Signal**: Smart money accumulation, potential bullish reversal
- **Action**: Look for long entries, especially at support levels
#### Bearish Divergence (Red Background)
- **Condition**: A/D is trending down BUT MACD is positive and trending up
- **Interpretation**: Volume is distributing while price momentum appears strong
- **Signal**: Smart money distribution, potential bearish reversal
- **Action**: Consider exits, avoid new longs, watch for breakdown
## Parameters
| Parameter | Default | Range | Description |
|-----------|---------|-------|-------------|
| **Source** | Close | OHLC/HLC3/etc | Price source for MACD calculation |
| **Fast Length** | 12 | 1-50 | Period for fast EMA (shorter = more sensitive) |
| **Slow Length** | 26 | 1-100 | Period for slow EMA (longer = smoother) |
| **Signal Smoothing** | 9 | 1-50 | Period for signal line (MACD smoothing) |
| **Signal Line MA Type** | EMA | SMA/EMA | Moving average type for signal calculation |
| **Volume MA Length** | 20 | 5-100 | Period for volume average (strength filter) |
## Usage Guide
### Reading the Indicator
1. **MACD Lines (Blue & Orange)**
- **Blue Line (MACD)**: Volume-weighted price momentum
- **Orange Line (Signal)**: Smoothed trend of MACD
- **Crossovers**: Blue crosses above orange = bullish, below = bearish
- **Distance**: Wider gap = stronger momentum
- **Zero Line Position**: Above = bullish bias, below = bearish bias
2. **Histogram Colors**
- **Dark Green (#1B5E20)**: Strong bullish move with high volume - **most reliable buy signal**
- **Light Teal (#26A69A)**: Bullish but low volume - wait for confirmation
- **Dark Red (#B71C1C)**: Strong bearish move with high volume - **most reliable sell signal**
- **Light Pink (#FFCDD2)**: Bearish but low volume - may be temporary dip
3. **Background Divergence Alerts**
- **Green Background**: A/D accumulating while price weak - potential bottom
- **Red Background**: A/D distributing while price strong - potential top
- Most powerful at key support/resistance levels
### Trading Strategies
#### Strategy 1: Volume-Confirmed Trend Following
1. Wait for MACD to cross above zero line
2. Look for **dark green** histogram bars (high volume confirmation)
3. Enter long on second consecutive dark green bar
4. Hold while histogram remains green
5. Exit when histogram turns light green or red appears
6. Set stop below recent swing low
**Example**:
```
Price: 26,400 → 26,450 (rising)
MACD: -50 → +20 (crosses zero)
Histogram: Light teal → Dark green → Dark green
Volume: 50k → 75k → 90k (increasing)
```
#### Strategy 2: Divergence Reversal Trading
1. Identify divergence background (green = bullish, red = bearish)
2. Confirm with price structure (support/resistance, chart patterns)
3. Wait for MACD to cross signal line in divergence direction
4. Enter on first **dark colored** histogram bar after divergence
5. Set stop beyond divergence area
6. Target previous swing high/low
**Example - Bullish Divergence**:
```
Price: Making lower lows (26,350 → 26,300 → 26,250)
A/D: Rising (accumulation)
MACD: Below zero but starting to curve up
Background: Green shading appears
Entry: MACD crosses signal line + dark green bar
Stop: Below 26,230
Target: 26,450 (previous high)
```
#### Strategy 3: Momentum Scalping
1. Trade only in direction of MACD zero line (above = long, below = short)
2. Enter on dark colored bars only
3. Exit on first light colored bar or opposite color
4. Quick in and out (1-5 minute holds)
5. Tight stops (0.2-0.5% depending on instrument)
#### Strategy 4: Histogram Pattern Trading
**V-Bottom Reversal (Bullish)**:
- Red histogram bars start rising (becoming less negative)
- Forms "V" shape at the bottom
- Transitions to light red → light teal → **dark green**
- Entry: First dark green bar
- Signal: Momentum reversal with volume
**Λ-Top Reversal (Bearish)**:
- Green histogram bars start falling (becoming less positive)
- Forms inverted "V" at the top
- Transitions to light green → light pink → **dark red**
- Entry: First dark red bar
- Signal: Momentum exhaustion with volume
### Multi-Timeframe Analysis
**Recommended Approach**:
1. **Higher Timeframe (15m/1h)**: Identify overall trend direction
2. **Trading Timeframe (5m)**: Time entries using VMACDv3 signals
3. **Lower Timeframe (1m)**: Fine-tune entry prices
**Example Setup**:
```
15-minute: MACD above zero (bullish bias)
5-minute: Dark green histogram appears after pullback
1-minute: Enter on break of recent high with volume
```
### Volume Strength Interpretation
The volume filter compares current volume to 20-period average:
- **Volume > Average**: Dark colors (green/red) - high confidence signals
- **Volume < Average**: Light colors (teal/pink) - lower confidence signals
**Trading Rules**:
- ✓ **Aggressive**: Take all dark colored signals
- ✓ **Conservative**: Only take dark colors that follow 2+ light colors of same type
- ✗ **Avoid**: Trading light colored signals during high volatility
- ✗ **Avoid**: Ignoring volume context during news events
## Technical Details
### Volume-Weighted Calculation
```pine
// Volume-weighted fast EMA
fast_ma = ta.ema(src * volume, fast_length) / ta.ema(volume, fast_length)
// Volume-weighted slow EMA
slow_ma = ta.ema(src * volume, slow_length) / ta.ema(volume, slow_length)
// MACD is the difference
macd = fast_ma - slow_ma
// Signal line smoothing
signal = ta.ema(macd, signal_length) // or ta.sma() if SMA selected
// Histogram
hist = macd - signal
```
### Divergence Detection Logic
```pine
// A/D trending up if above its 5-period SMA
ad_trend = ad > ta.sma(ad, 5)
// MACD trending up if above zero
macd_trend = macd > 0
// Divergence when trends oppose each other
divergence = ad_trend != macd_trend
// Specific conditions for alerts
bullish_divergence = ad_trend and not macd_trend and macd < 0
bearish_divergence = not ad_trend and macd_trend and macd > 0
```
### Histogram Coloring Logic
```pine
hist_color = (hist >= 0
? (hist < hist
? (vol_strength ? #1B5E20 : #26A69A) // Rising: dark/light green
: #B2DFDB) // Positive but falling: cyan
: (hist < hist
? (vol_strength ? #B71C1C : #FFCDD2) // Rising (less negative): dark/light red
: #FF5252)) // Falling more: bright red
```
## Alerts
Built-in alert conditions for divergence detection:
### Bullish Divergence Alert
- **Trigger**: A/D trending up, MACD negative and trending down
- **Message**: "Bullish Divergence: A/D trending up but MACD trending down"
- **Use Case**: Potential reversal or continuation after pullback
- **Action**: Look for long entry setups
### Bearish Divergence Alert
- **Trigger**: A/D trending down, MACD positive and trending up
- **Message**: "Bearish Divergence: A/D trending down but MACD trending up"
- **Use Case**: Potential top or trend reversal
- **Action**: Consider exits or short entries
### Setting Up Alerts
1. Click "Create Alert" in TradingView
2. Condition: Select "VMACDv3"
3. Choose alert type: "Bullish Divergence" or "Bearish Divergence"
4. Configure: Email, SMS, webhook, or popup
5. Set frequency: "Once Per Bar Close" recommended
## Comparison Tables
### VMACDv3 vs Standard MACD
| Feature | Standard MACD | VMACDv3 |
|---------|---------------|---------|
| **Price Weighting** | Equal weight all bars | Volume-weighted |
| **Sensitivity** | Fixed | Adaptive to volume |
| **False Signals** | More during low volume | Fewer (volume filter) |
| **Divergence** | Price vs MACD | A/D vs MACD |
| **Volume Analysis** | None | Built-in |
| **Color System** | 2 colors | 4+ colors |
| **Best For** | Simple trend following | Volume-confirmed trading |
### VMACDv3 vs ACCDv3
| Aspect | VMACDv3 | ACCDv3 |
|--------|---------|--------|
| **Focus** | Price momentum | Volume distribution |
| **Reactivity** | Faster to price moves | Faster to volume shifts |
| **Best Markets** | Trending, breakouts | Accumulation/distribution phases |
| **Signal Type** | Where price + volume going | Where smart money positioning |
| **Divergence Meaning** | Volume vs price disagreement | A/D vs momentum disagreement |
| **Use Together?** | ✓ Yes, complementary | ✓ Yes, different perspectives |
## Example Trading Scenarios
### Scenario 1: Strong Bullish Breakout
```
Time: 9:30 AM (market open)
Price: Breaks above 26,400 resistance
MACD: Crosses above zero line
Histogram: Dark green bars (#1B5E20)
Volume: 2x average (150k vs 75k avg)
A/D: Rising (no divergence)
Action: Enter long at 26,405
Stop: 26,380 (below breakout)
Target 1: 26,450 (risk:reward 1:2)
Target 2: 26,500 (risk:reward 1:4)
Result: High probability setup with volume confirmation
```
### Scenario 2: False Breakout (Avoided)
```
Time: 2:30 PM (slow period)
Price: Breaks above 26,400 resistance
MACD: Slightly positive
Histogram: Light teal bars (#26A69A)
Volume: 0.5x average (40k vs 75k avg)
A/D: Flat/declining
Action: Avoid trade
Reason: Low volume, no conviction, potential false breakout
Outcome: Price reverses back below 26,400 within 10 minutes
Saved: Avoided losing trade due to volume filter
```
### Scenario 3: Bullish Divergence Bottom
```
Time: 11:00 AM
Price: Making lower lows (26,350 → 26,300 → 26,280)
MACD: Below zero but curving upward
Histogram: Red bars getting shorter (V-bottom forming)
Background: Green shading (divergence alert)
A/D: Rising despite price falling
Volume: Increasing on down bars
Setup:
1. Divergence appears at 26,280 (green background)
2. Wait for MACD to cross signal line
3. First dark green bar appears at 26,290
4. Enter long: 26,295 (next bar open)
5. Stop: 26,265 (below divergence low)
6. Target: 26,350 (previous swing high)
Result: +55 points (30 point risk, 1.8:1 reward)
Key: Divergence + volume confirmation = high probability reversal
```
### Scenario 4: Bearish Divergence Top
```
Time: 1:45 PM
Price: Making higher highs (26,500 → 26,520 → 26,540)
MACD: Positive but flattening
Histogram: Green bars getting shorter (Λ-top forming)
Background: Red shading (bearish divergence)
A/D: Declining despite rising price
Volume: Decreasing on up bars
Setup:
1. Bearish divergence at 26,540 (red background)
2. MACD crosses below signal line
3. First dark red bar appears at 26,535
4. Enter short: 26,530
5. Stop: 26,555 (above divergence high)
6. Target: 26,475 (support level)
Result: +55 points (25 point risk, 2.2:1 reward)
Key: Distribution while price rising = smart money exiting
```
### Scenario 5: V-Bottom Reversal
```
Downtrend in progress
MACD: Deep below zero (-150)
Histogram: Series of dark red bars
Pattern Development:
Bar 1: Dark red, hist = -80, falling
Bar 2: Dark red, hist = -95, falling
Bar 3: Dark red, hist = -100, falling (extreme)
Bar 4: Light pink, hist = -98, rising!
Bar 5: Light pink, hist = -90, rising
Bar 6: Light teal, hist = -75, rising (crosses to positive momentum)
Bar 7: Dark green, hist = -55, rising + volume
Action: Enter long on Bar 7
Reason: V-bottom confirmed with volume
Stop: Below Bar 3 low
Target: Zero line on histogram (mean reversion)
```
## Best Practices
### Entry Rules
✓ **Wait for dark colors**: High-volume confirmation is key
✓ **Confirm divergences**: Use with price support/resistance
✓ **Trade with zero line**: Long above, short below for best odds
✓ **Multiple timeframes**: Align 1m, 5m, 15m signals
✓ **Watch for patterns**: V-bottoms and Λ-tops are reliable
### Exit Rules
✓ **Partial profits**: Take 50% at first target
✓ **Trail stops**: Use histogram color changes
✓ **Respect signals**: Exit on opposite dark color
✓ **Time stops**: Close positions before major news
✓ **End of day**: Square up before close
### Avoid
✗ **Don't chase light colors**: Low volume = low confidence
✗ **Don't ignore divergence**: Early warning system
✗ **Don't overtrade**: Wait for clear setups
✗ **Don't fight the trend**: Zero line dictates bias
✗ **Don't skip stops**: Always use risk management
## Risk Management
### Position Sizing
- **Dark green/red signals**: 1-2% account risk
- **Light signals**: 0.5% account risk or skip
- **Divergence plays**: 1% account risk (higher uncertainty)
- **Multiple confirmations**: Up to 2% account risk
### Stop Loss Placement
- **Trend trades**: Below/above recent swing (20-30 points typical)
- **Breakout trades**: Below/above breakout level (15-25 points)
- **Divergence trades**: Beyond divergence extreme (25-40 points)
- **Scalp trades**: Tight stops at 10-15 points
### Profit Targets
- **Minimum**: 1.5:1 reward to risk ratio
- **Scalps**: 15-25 points (quick in/out)
- **Swing**: 50-100 points (hold through pullbacks)
- **Runners**: Trail with histogram color changes
## Timeframe Recommendations
| Timeframe | Trading Style | Typical Hold | Advantages | Challenges |
|-----------|---------------|--------------|------------|------------|
| **1-minute** | Scalping | 1-5 minutes | Fast profits, many setups | Noisy, high false signals |
| **5-minute** | Intraday | 15-60 minutes | Balance of speed/clarity | Still requires quick decisions |
| **15-minute** | Swing | 1-4 hours | Clearer trends, less noise | Fewer opportunities |
| **1-hour** | Position | 4-24 hours | Strong signals, less monitoring | Wider stops required |
**Recommendation**: Start with 5-minute for best balance of signal quality and opportunity frequency.
## Combining with Other Indicators
### VMACDv3 + ACCDv3
- **Use**: Confirm volume flow with price momentum
- **Signal**: Both showing dark green = highest conviction long
- **Divergence**: VMACDv3 bullish + ACCDv3 bearish = examine price action
### VMACDv3 + RSI
- **Use**: Overbought/oversold with momentum confirmation
- **Signal**: RSI < 30 + dark green VMACD = strong reversal
- **Caution**: RSI > 70 + light green VMACD = potential false breakout
### VMACDv3 + Elder Impulse
- **Use**: Bar coloring + histogram confirmation
- **Signal**: Green Elder bars + dark green VMACD = aligned momentum
- **Exit**: Blue Elder bars + light colors = momentum stalling
## Limitations
- **Requires volume data**: Will not work on instruments without volume feed
- **Lagging indicator**: MACD inherently follows price (2-3 bar delay)
- **Consolidation noise**: Generates false signals in tight ranges
- **Gap handling**: Large gaps can distort volume-weighted values
- **Not standalone**: Should combine with price action and support/resistance
## Troubleshooting
**Problem**: Too many light colored signals
**Solution**: Increase Volume MA Length to 30-40 for stricter filtering
**Problem**: Missing entries due to waiting for dark colors
**Solution**: Lower Volume MA Length to 10-15 for more signals (accept lower quality)
**Problem**: Divergences not appearing
**Solution**: Verify volume data available; check if A/D line is calculating
**Problem**: Histogram colors not changing
**Solution**: Ensure real-time data feed; refresh indicator
## Version History
- **v3**: Removed traditional MACD, using volume-weighted MACD on price with A/D divergence
- **v2**: Added A/D divergence detection, volume strength filtering, enhanced histogram colors
- **v1**: Basic volume-weighted MACD on price
## Related Indicators
**Companion Tools**:
- **ACCDv3**: Volume-weighted MACD on A/D line (distribution focus)
- **RSIv2**: RSI with A/D divergence detection
- **DMI**: Directional Movement Index with A/D divergence
- **Elder Impulse**: Bar coloring system using volume-weighted MACD
**Use Together**: VMACDv3 (momentum) + ACCDv3 (distribution) + Elder Impulse (bar colors) = complete volume-based trading system
---
*This indicator is for educational purposes. Past performance does not guarantee future results. Always practice proper risk management and never risk more than you can afford to lose.*
Search in scripts for "accumulation"
ACCDv3# ACCDv3 - Accumulation/Distribution MACD with Divergence Detection
## Overview
**ACCDv3** (Accumulation/Distribution MACD Version 3) is an advanced volume-weighted momentum indicator that combines the Accumulation/Distribution (A/D) line with MACD methodology and divergence detection. It helps identify trend strength, momentum shifts, and potential reversals by analyzing volume-weighted price movements.
## Key Features
- **Volume-Weighted MACD**: Applies MACD calculation to volume-weighted A/D values for earlier, more reliable signals
- **Divergence Detection**: Identifies when A/D trend diverges from MACD momentum
- **Volume Strength Filtering**: Distinguishes high-volume confirmations from low-volume noise
- **Color-Coded Histogram**: 4-color system showing momentum direction and volume strength
- **Real-Time Alerts**: Background colors and alert conditions for bullish/bearish divergences
## Components
### 1. Accumulation/Distribution (A/D) Line
The A/D line measures buying and selling pressure by comparing the close price to the trading range, weighted by volume:
```
A/D = Σ ((2 × Close - Low - High) / (High - Low)) × Volume
```
- **Rising A/D**: More accumulation (buying pressure)
- **Falling A/D**: More distribution (selling pressure)
- **Doji Handling**: When High = Low, contribution is zero (avoids division errors)
### 2. Volume-Weighted MACD
Instead of simple EMAs, the indicator weights A/D values by volume:
- **Fast Line** (default 12): `EMA(A/D × Volume, 12) / EMA(Volume, 12)`
- **Slow Line** (default 26): `EMA(A/D × Volume, 26) / EMA(Volume, 26)`
- **MACD Line**: Fast Line - Slow Line (green line)
- **Signal Line** (default 9): EMA or SMA of MACD (orange line)
- **Histogram**: MACD - Signal (color-coded columns)
This volume-weighting ensures that periods with higher volume have greater influence on the indicator values.
### 3. Histogram Color System
The histogram uses 4 distinct colors based on **direction** and **volume strength**:
| Condition | Color | Meaning |
|-----------|-------|---------|
| Rising + High Volume | **Dark Green** (#1B5E20) | Strong bullish momentum with volume confirmation |
| Rising + Low Volume | **Light Teal** (#26A69A) | Bullish momentum but weak volume (less reliable) |
| Falling + High Volume | **Dark Red** (#B71C1C) | Strong bearish momentum with volume confirmation |
| Falling + Low Volume | **Light Red/Pink** (#FFCDD2) | Bearish momentum but weak volume (less reliable) |
Additional shading:
- **Light Cyan** (#B2DFDB): Positive but not rising (momentum stalling)
- **Bright Red** (#FF5252): Negative and accelerating down
### 4. Divergence Detection
Divergence occurs when A/D trend and MACD momentum move in opposite directions:
#### Bullish Divergence (Green Background)
- **Condition**: A/D is trending up BUT MACD is negative and trending down
- **Interpretation**: Accumulation increasing while momentum appears weak
- **Signal**: Potential bullish reversal or continuation
- **Action**: Look for entry opportunities or hold long positions
#### Bearish Divergence (Red Background)
- **Condition**: A/D is trending down BUT MACD is positive and trending up
- **Interpretation**: Distribution increasing while momentum appears strong
- **Signal**: Potential bearish reversal or weakening uptrend
- **Action**: Consider exits, tighten stops, or prepare for reversal
## Parameters
| Parameter | Default | Range | Description |
|-----------|---------|-------|-------------|
| **Fast Length** | 12 | 1-50 | Period for fast EMA (shorter = more sensitive) |
| **Slow Length** | 26 | 1-100 | Period for slow EMA (longer = smoother) |
| **Signal Smoothing** | 9 | 1-50 | Period for signal line (MACD smoothing) |
| **Signal Line MA Type** | EMA | SMA/EMA | Moving average type for signal calculation |
| **Volume MA Length** | 20 | 5-100 | Period for volume average (strength filter) |
## Usage Guide
### Reading the Indicator
1. **MACD Lines (Green & Orange)**
- **Crossovers**: When green crosses above orange = bullish, below = bearish
- **Distance**: Wider gap = stronger momentum
- **Zero Line**: Above = bullish bias, below = bearish bias
2. **Histogram Colors**
- Focus on **dark colors** (dark green/red) for high-confidence signals
- Be cautious with **light colors** (teal/pink) - wait for volume confirmation
- Watch for **rising red bars** (V-bottom pattern) = potential bullish reversal
- Watch for **falling green bars** (Λ-top pattern) = potential bearish reversal
3. **Background Divergence Alerts**
- **Green background**: Bullish divergence - consider long entries
- **Red background**: Bearish divergence - consider exits or shorts
- Best used in combination with price action and support/resistance levels
### Trading Strategies
#### Trend Following
1. Wait for MACD to cross above zero line with dark green histogram
2. Enter long when histogram shows consecutive dark green bars
3. Exit when histogram turns light green or red appears
#### Divergence Trading
1. Wait for background divergence alert (green or red)
2. Confirm with price action (support/resistance, candlestick patterns)
3. Enter on next dark-colored histogram bar in divergence direction
4. Set stops beyond recent swing high/low
#### Volume Confirmation
1. Ignore signals during low-volume periods (light colors)
2. Take aggressive positions during high-volume confirmations (dark colors)
3. Use volume strength as position sizing guide (larger size on dark bars)
### Best Practices
✓ **Combine with price action**: Don't rely on indicator alone
✓ **Wait for dark colors**: High-volume bars are more reliable
✓ **Watch for divergences**: Early warning signs of reversals
✓ **Use multiple timeframes**: Confirm signals across 1m, 5m, 15m
✓ **Respect zero line**: Trading direction should align with MACD side
✗ **Don't chase light-colored signals**: Low volume = lower reliability
✗ **Don't ignore context**: Market structure and levels matter
✗ **Don't over-trade**: Wait for clear, high-volume setups
✗ **Don't ignore alerts**: Divergences are early warnings
## Technical Details
### Volume-Weighted Calculation Method
Traditional MACD uses simple price EMAs. ACCDv3 weights each A/D value by its corresponding volume:
```pine
// Volume-weighted fast EMA
close_vol_fast = ta.ema(ad × volume, fast_length)
vol_fast = ta.ema(volume, fast_length)
vw_ad_fast = close_vol_fast / vol_fast
// Same for slow EMA
close_vol_slow = ta.ema(ad × volume, slow_length)
vol_slow = ta.ema(volume, slow_length)
vw_ad_slow = close_vol_slow / vol_slow
// MACD is the difference
macd = vw_ad_fast - vw_ad_slow
```
This ensures high-volume periods have proportionally more impact on the indicator.
### Volume Strength Filter
Determines whether current volume is above or below average:
```pine
vol_avg = ta.sma(volume, vol_length)
vol_strength = volume > vol_avg
```
Used to select dark (high volume) vs light (low volume) histogram colors.
### Divergence Logic
```pine
// A/D trending up if above its 5-period SMA
ad_trend = ad > ta.sma(ad, 5)
// MACD trending up if above zero
macd_trend = macd > 0
// Divergence when trends oppose
divergence = ad_trend != macd_trend
// Specific conditions
bullish_divergence = ad_trend and not macd_trend and macd < 0
bearish_divergence = not ad_trend and macd_trend and macd > 0
```
## Alerts
The indicator includes built-in alert conditions:
- **Bullish Divergence**: "Bullish Divergence: A/D trending up but MACD trending down"
- **Bearish Divergence**: "Bearish Divergence: A/D trending down but MACD trending up"
To enable:
1. Click "Create Alert" button in TradingView
2. Select "ACCDv3" as condition
3. Choose "Bullish Divergence" or "Bearish Divergence"
4. Configure notification method (popup, email, webhook, etc.)
## Comparison with Standard MACD
| Feature | Standard MACD | ACCDv3 |
|---------|---------------|---------|
| **Input** | Close price | Accumulation/Distribution line |
| **Weighting** | Simple EMA | Volume-weighted EMA |
| **Divergence** | Price vs MACD | A/D vs MACD |
| **Volume Analysis** | None | Built-in strength filter |
| **Color System** | 2 colors (up/down) | 4+ colors (direction + volume) |
| **Leading/Lagging** | Lagging | More leading (volume-weighted) |
## Example Scenarios
### Scenario 1: Strong Bullish Signal
- **Chart**: MACD crosses above zero line
- **Histogram**: Dark green bars (#1B5E20) appearing
- **Volume**: Above 20-period average
- **Action**: Enter long, strong momentum with volume confirmation
### Scenario 2: Weak Bearish Signal
- **Chart**: MACD crosses below zero line
- **Histogram**: Light pink bars (#FFCDD2) appearing
- **Volume**: Below 20-period average
- **Action**: Avoid shorting, low volume = unreliable signal
### Scenario 3: Bullish Divergence Reversal
- **Chart**: Price making lower lows
- **Indicator**: A/D line trending up, MACD negative
- **Background**: Green shading appears
- **Histogram**: Transitions from red to dark green
- **Action**: Look for long entry on next dark green bar
### Scenario 4: V-Bottom Reversal
- **Chart**: Downtrend in place
- **Histogram**: Red bars start rising (becoming less negative)
- **Pattern**: Forms "V" shape at bottom
- **Confirmation**: Transitions to dark green bars
- **Action**: Bullish reversal signal, consider long entry
## Timeframe Recommendations
- **1-minute**: Scalping, very fast signals (noisy, use with caution)
- **5-minute**: Intraday momentum trading (recommended)
- **15-minute**: Swing entries, clearer trend signals
- **1-hour+**: Position trading, major trend identification
## Limitations
- **Requires volume data**: Will not work on instruments without volume
- **Lag during consolidation**: MACD is inherently trend-following
- **False signals in chop**: Sideways markets generate noise
- **Not a standalone system**: Should be combined with price action and risk management
## Version History
- **v3**: Removed traditional price MACD, using only volume-weighted A/D MACD with A/D divergence
- **v2**: Added A/D divergence detection, volume strength filtering, enhanced histogram colors
- **v1**: Basic MACD on A/D line with volume-weighted calculation
## Support & Further Reading
For questions, updates, or to report issues, refer to the main project documentation or contact the developer.
**Related Indicators in Suite:**
- **VMACDv3**: Volume-weighted MACD on price (not A/D)
- **RSIv2**: RSI with A/D divergence
- **DMI**: Directional Movement Index with A/D divergence
- **Elder Impulse**: Bar coloring system using volume-weighted MACD
---
*This indicator is for educational purposes. Always practice proper risk management and never risk more than you can afford to lose.*
Quarterly Theory ICT 01 [TradingFinder] XAMD + Q1-Q4 Sessions🔵 Introduction
The Quarterly Theory ICT indicator is an advanced analytical system based on the concepts of ICT (Inner Circle Trader) and fractal time. It divides time into quarterly periods and accurately determines entry and exit points for trades by using the True Open as the starting point of each cycle. This system is applicable across various time frames including annual, monthly, weekly, daily, and even 90-minute sessions.
Time is divided into four quarters: in the first quarter (Q1), which is dedicated to the Accumulation phase, the market is in a consolidation state, laying the groundwork for a new trend; in the second quarter (Q2), allocated to the Manipulation phase (also known as Judas Swing), sudden price changes and false moves occur, marking the true starting point of a trend change; the third quarter (Q3) is dedicated to the Distribution phase, during which prices are broadly distributed and price volatility peaks; and the fourth quarter (Q4), corresponding to the Continuation/Reversal phase, either continues or reverses the previous trend.
By leveraging smart algorithms and technical analysis, this system identifies optimal price patterns and trading positions through the precise detection of stop-run and liquidity zones.
With the division of time into Q1 through Q4 and by incorporating key terms such as Quarterly Theory ICT, True Open, Accumulation, Manipulation (Judas Swing), Distribution, Continuation/Reversal, ICT, fractal time, smart algorithms, technical analysis, price patterns, trading positions, stop-run, and liquidity, this system enables traders to identify market trends and make informed trading decisions using real data and precise analysis.
♦ Important Note :
This indicator and the "Quarterly Theory ICT" concept have been developed based on material published in primary sources, notably the articles on Daye( traderdaye ) and Joshuuu . All copyright rights are reserved.
🔵 How to Use
The Quarterly Theory ICT strategy is built on dividing time into four distinct periods across various time frames such as annual, monthly, weekly, daily, and even 90-minute sessions. In this approach, time is segmented into four quarters, during which the phases of Accumulation, Manipulation (Judas Swing), Distribution, and Continuation/Reversal appear in a systematic and recurring manner.
The first segment (Q1) functions as the Accumulation phase, where the market consolidates and lays the foundation for future movement; the second segment (Q2) represents the Manipulation phase, during which prices experience sudden initial changes, and with the aid of the True Open concept, the real starting point of the market’s movement is determined; in the third segment (Q3), the Distribution phase takes place, where prices are widely dispersed and price volatility reaches its peak; and finally, the fourth segment (Q4) is recognized as the Continuation/Reversal phase, in which the previous trend either continues or reverses.
This strategy, by harnessing the concepts of fractal time and smart algorithms, enables precise analysis of price patterns across multiple time frames and, through the identification of key points such as stop-run and liquidity zones, assists traders in optimizing their trading positions. Utilizing real market data and dividing time into Q1 through Q4 allows for a comprehensive and multi-level technical analysis in which optimal entry and exit points are identified by comparing prices to the True Open.
Thus, by focusing on keywords like Quarterly Theory ICT, True Open, Accumulation, Manipulation, Distribution, Continuation/Reversal, ICT, fractal time, smart algorithms, technical analysis, price patterns, trading positions, stop-run, and liquidity, the Quarterly Theory ICT strategy acts as a coherent framework for predicting market trends and developing trading strategies.
🔵b]Settings
Cycle Display Mode: Determines whether the cycle is displayed on the chart or on the indicator panel.
Show Cycle: Enables or disables the display of the ranges corresponding to each quarter within the micro cycles (e.g., Q1/1, Q1/2, Q1/3, Q1/4, etc.).
Show Cycle Label: Toggles the display of textual labels for identifying the micro cycle phases (for example, Q1/1 or Q2/2).
Table Display Mode: Enables or disables the ability to display cycle information in a tabular format.
Show Table: Determines whether the table—which summarizes the phases (Q1 to Q4)—is displayed.
Show More Info: Adds additional details to the table, such as the name of the phase (Accumulation, Manipulation, Distribution, or Continuation/Reversal) or further specifics about each cycle.
🔵 Conclusion
Quarterly Theory ICT provides a fractal and recurring approach to analyzing price behavior by dividing time into four quarters (Q1, Q2, Q3, and Q4) and defining the True Open at the beginning of the second phase.
The Accumulation, Manipulation (Judas Swing), Distribution, and Continuation/Reversal phases repeat in each cycle, allowing traders to identify price patterns with greater precision across annual, monthly, weekly, daily, and even micro-level time frames.
Focusing on the True Open as the primary reference point enables faster recognition of potential trend changes and facilitates optimal management of trading positions. In summary, this strategy, based on ICT principles and fractal time concepts, offers a powerful framework for predicting future market movements, identifying optimal entry and exit points, and managing risk in various trading conditions.
WMA Trend and Growth Rate IndicatorThe "WMA Trend and Growth Rate Indicator" is a powerful tool for analyzing market trends and momentum. By understanding its components and how to configure it, traders of all levels can leverage this indicator to enhance their trading strategies. Experiment with the settings and integrate it into your analysis to gain valuable insights into market movements.
Indicator Components
WMA Length : The length of the WMA. This controls how many periods are included in the calculation.
Start : The starting value for accumulation levels.
End : The ending value for accumulation levels.
Key Concepts
Weighted Moving Average (WMA): A type of moving average that gives more weight to recent price data, making it more responsive to recent price changes.
Growth Rate : Measures how much the WMA has increased or decreased over a specified period, expressed as a percentage.
Accumulation and Distribution Levels : Zones where buying (accumulation) or selling (distribution) pressure is expected.
Configuring the Inputs
WMA Length : Adjust this value to change the sensitivity of the WMA. A smaller value makes the WMA more sensitive to recent price changes, while a larger value smooths out the data more.
Start and End : Adjust these values to define the range for accumulation and distribution levels. The indicator will automatically adjust the colors based on whether the Start value is higher or lower than the End value.
Interpreting the Plots
WMAT Line : The main trend line that shows the direction and strength of the trend.
Growth Index : Shows the growth rate of the WMAT.
Accumulation Levels : Indicated by lines and fill colors, showing potential zones to increase positions.
Distribution Levels : Indicated by lines and fill colors, showing potential zones to decrease positions.
The indicator checks if "Start" is greater than "End". Based on this check, it assigns colors to the accumulation and distribution levels. This color scheme helps traders visually distinguish between areas of potential buying and selling zones.
Wyckoff Range StrategyThe Wyckoff Range Strategy is a trading strategy that aims to identify potential accumulation and distribution phases in the market using the principles of Wyckoff analysis. It also incorporates the detection of spring and upthrust patterns.
Here's a step-by-step explanation of how to use this strategy:
Understanding Accumulation and Distribution Phases:
Accumulation Phase: This is a period where smart money (large institutional traders) accumulates a particular asset at lower prices. It is characterized by a sideways or consolidating price action.
Distribution Phase: This is a period where smart money distributes or sells a particular asset at higher prices. It is also characterized by a sideways or consolidating price action.
Input Variables:
crossOverLength: This variable determines the length of the moving average crossover used to identify accumulation and distribution phases. You can adjust this value based on the market you are trading and the time frame you are analyzing.
stopPercentage: This variable determines the percentage used to calculate the stop loss level. It helps you define a predefined level at which you would exit a trade if the price moves against your position.
Strategy Conditions:
Enter Long: The strategy looks for a crossover of the close price above the SMA of the close price with a length of crossOverLength and a crossover of the low price above the SMA of the low price with a length of 20. This combination suggests the start of an accumulation phase and a potential buying opportunity.
Exit Long: The strategy looks for a crossunder of the close price below the SMA of the close price with a length of crossOverLength or a crossunder of the high price below the SMA of the high price with a length of 20. This combination suggests the end of an accumulation phase and a potential exit signal for long positions.
Enter Short: The strategy looks for a crossunder of the close price below the SMA of the close price with a length of crossOverLength and a crossunder of the high price below the SMA of the high price with a length of 20. This combination suggests the start of a distribution phase and a potential selling opportunity.
Exit Short: The strategy looks for a crossover of the close price above the SMA of the close price with a length of crossOverLength or a crossover of the low price above the SMA of the low price with a length of 20. This combination suggests the end of a distribution phase and a potential exit signal for short positions.
Stop Loss:
The strategy sets a stop loss level for both long and short positions. The stop loss level is calculated based on the stopPercentage variable, which represents the percentage of the current close price. If the price reaches the stop loss level, the strategy will automatically exit the position.
Plotting Wyckoff Schematics:
The strategy plots different shapes on the chart to indicate the identified phases and patterns. Green and red labels indicate the accumulation and distribution phases, respectively. Blue triangles indicate spring patterns, and orange triangles indicate upthrust patterns.
To use this strategy, you can follow these steps:
Jim Forte — Anatomy of a Trading Range
robertbrain.com/Bull...+a+Trading+Range.pdf
MVRV Ratio Indicator [captainua]MVRV Ratio Indicator - Market Value to Realized Value Ratio
Overview
This professional indicator calculates and visualizes the MVRV (Market Value to Realized Value) ratio (raw, non-Z-score) with optional MVRV-Z overlay, comparing current market capitalization to realized capitalization to help identify potential market tops and bottoms for cryptocurrency markets.
Unlike MVRV-Z which normalizes the ratio using standard deviation (creating a Z-score), the raw MVRV ratio provides direct comparison between market cap and realized cap. This indicator enhances the raw ratio with historical percentile bands, percentile rank calculation, divergence detection, historical event logging, dynamic color gradients, enhanced visualization options, optional MVRV-Z comparison, and NEW advanced metrics including Risk Score, MVRV Momentum, Time in Zone tracking, and Price Target calculations.
NEW Features in This Version:
• Risk Score (0-100): Composite indicator based on MVRV level and percentile rank for instant risk assessment
• MVRV Momentum: Rate of change indicator showing trend direction (↑ Increasing, ↓ Decreasing, → Flat)
• Time in Zone: Tracks how long MVRV has been in the current zone (top/bottom/neutral) in bars
• Price Targets: Calculates price levels at key MVRV thresholds (fair value, top, bottom)
• Input Validation: Warns about invalid parameter combinations (e.g., extreme thresholds out of order)
• Multiple Smoothing Options: SMA, EMA, WMA, RMA for noise reduction
• Performance Optimized: Cached request.security() calls, ta.percentrank() for efficiency
• Human-Readable Timestamps: Event log now shows dates (YYYY-MM-DD) instead of bar indices
Core Calculations
MVRV Ratio Calculation:
The script calculates MVRV ratio using the standard formula: MVRV Ratio = Market Cap / Realized Cap. This formula provides a direct ratio without normalization, showing how many times the current market cap exceeds (or falls below) the realized cap.
Market Capitalization (Market Cap): The total market value of all coins in circulation, calculated as current price × circulating supply. This represents the market's current valuation of the asset.
Realized Capitalization (Realized Cap): The sum of the value of each coin when it last moved on-chain, representing the average cost basis of all coins.
Raw Ratio Interpretation:
- Ratio > 3.5: Extreme overvaluation (market cap significantly above realized cap)
- Ratio 2.5-3.5: Moderate overvaluation
- Ratio 1.0-2.5: Fair value to moderate overvaluation
- Ratio 0.8-1.0: Fair value to moderate undervaluation
- Ratio < 0.8: Undervaluation (market cap close to or below realized cap)
Risk Score (NEW):
Composite risk indicator ranging from 0-100:
- 80-100: Very High Risk (extreme overvaluation)
- 60-80: High Risk (overvaluation)
- 40-60: Moderate Risk (fair value range)
- 20-40: Low Risk (undervaluation)
- 0-20: Very Low Risk (extreme undervaluation)
The risk score uses percentile rank when available, or normalizes MVRV ratio to the 0-100 scale based on configured thresholds.
MVRV Momentum (NEW):
Rate of change indicator showing trend direction:
- ↑ Increasing: MVRV ratio rising (momentum > 0.01)
- ↓ Decreasing: MVRV ratio falling (momentum < -0.01)
- → Flat: MVRV ratio stable
- Displays percentage change over configurable period (default: 14 bars)
Time in Zone (NEW):
Tracks duration in current zone:
- Top Zone: Bars spent above top threshold (3.5)
- Bottom Zone: Bars spent below bottom threshold (0.8)
- Neutral Zone: Bars spent between thresholds
- Resets when zone changes
- Helps identify prolonged extreme conditions
Price Targets (NEW):
Calculates price levels at key MVRV thresholds:
- Price @ Fair Value: Price when MVRV = 1.0
- Price @ Top Threshold: Price when MVRV = 3.5
- Price @ Bottom Threshold: Price when MVRV = 0.8
- Based on estimated realized price (current price / MVRV ratio)
Data Source Selection:
The indicator supports multiple data source options for maximum flexibility:
Glassnode (Recommended):
- Uses Glassnode Market Cap data
- Calculates MVRV from Market Cap / Realized Cap
- Symbol format: GLASSNODE:{TOKEN}_MARKETCAP
- Requires Glassnode data subscription
- Also requires CoinMetrics for Realized Cap
- Best for comprehensive analysis with MVRV-Z comparison
IntoTheBlock:
- Direct MVRV ratio data from IntoTheBlock
- Simplest option - no calculations required
- Works for BTC and other supported tokens
- Symbol format: INTOTHEBLOCK:{TOKEN}_MVRV
- Requires IntoTheBlock data subscription on TradingView
Historical Percentile Bands:
The indicator calculates rolling percentile bands over a configurable period (default: 500 bars):
- 5th Percentile: Very low historical values (extreme undervaluation range)
- 25th Percentile: Lower quartile (undervaluation range)
- 50th Percentile: Median (fair value center)
- 75th Percentile: Upper quartile (overvaluation range)
- 95th Percentile: Very high historical values (extreme overvaluation range)
Percentile bands use ta.percentile_nearest_rank() for efficient calculation.
Percentile Rank:
Percentile rank shows where the current MVRV ratio sits in the historical distribution (0-100%):
- 0-25%: Bottom quartile (undervaluation)
- 25-50%: Lower half (moderate undervaluation to fair value)
- 50-75%: Upper half (fair value to moderate overvaluation)
- 75-100%: Top quartile (overvaluation)
Now uses efficient ta.percentrank() instead of array-based calculation.
Input Validation (NEW):
The indicator validates input parameters and displays warnings for:
- Extreme High Threshold should be > Top Threshold
- Extreme Low Threshold should be < Bottom Threshold
- Min Lookback Range must be < Max Lookback Range
- Top Threshold should be > Moderate Overvalued
- Moderate Overvalued should be > Fair Value
- Fair Value should be > Bottom Threshold
- Rapid Increase Threshold should be > 0
- Rapid Decrease Threshold should be < 0
Smoothing Options (Enhanced):
Multiple smoothing types available:
- SMA: Simple Moving Average (equal weight)
- EMA: Exponential Moving Average (more weight to recent)
- WMA: Weighted Moving Average (linear weight)
- RMA: Running Moving Average (Wilder's smoothing)
Reference Levels
Overvalued (Potential Top) - 3.5:
The 3.5 level indicates potentially extreme overvaluation. When MVRV ratio exceeds this threshold:
- Market cap is significantly above realized cap
- Potential selling opportunities for profit-taking
- Risk of market corrections or reversals
- Risk Score typically >80 (Very High Risk)
Moderately Overvalued - 2.5:
The 2.5 level indicates moderate overvaluation:
- Market cap is above realized cap but not extreme
- Caution warranted but not necessarily sell signal
- Risk Score typically 60-80 (High Risk)
Fair Value - 1.0:
The 1.0 level indicates fair valuation:
- Market cap equals realized cap
- Balanced market conditions
- Risk Score typically 40-60 (Moderate Risk)
Undervalued (Potential Bottom) - 0.8:
The 0.8 level indicates potentially undervalued conditions:
- Market cap is close to or below realized cap
- Potential buying opportunities for accumulation
- Risk Score typically <40 (Low Risk)
Visual Features
MVRV Ratio Line:
The main indicator line displays the calculated MVRV ratio with dynamic color gradient:
- Bright Red: Extreme overvaluation (ratio ≥ top threshold + 0.5)
- Orange: High overvaluation (ratio ≥ top threshold)
- Cornflower Blue: Neutral/Fair value (around fair value level)
- Deep Sky Blue: Low/Undervaluation (ratio ≤ bottom threshold)
- Bright Green: Extreme undervaluation (ratio ≤ bottom threshold - 0.1)
Can also be displayed as histogram/bar chart.
Historical Percentile Bands:
Five percentile bands with optional fills:
- 5th Percentile (Blue): Very low historical range
- 25th Percentile (Blue): Lower quartile
- 50th Percentile (Gray): Historical median
- 75th Percentile (Orange): Upper quartile
- 95th Percentile (Red): Very high historical range
Reference Lines:
Horizontal reference lines at key levels (all customizable):
- Top Threshold (default 3.5): Purple/violet
- Moderate Overvalued (default 2.5): Orange
- Fair Value (1.0): Gray
- Bottom Threshold (default 0.8): Blue
Background Highlights:
Optional background color highlights:
- High Zone (Maroon/Red): MVRV ratio ≥ top threshold
- Low Zone (Green): MVRV ratio ≤ bottom threshold
Divergence Detection:
Advanced divergence detection between price and MVRV ratio:
- Regular Bullish Divergence: Price lower low + MVRV higher low
- Regular Bearish Divergence: Price higher high + MVRV lower high
- Hidden Bullish Divergence: Price higher low + MVRV lower low
- Hidden Bearish Divergence: Price lower high + MVRV higher high
- Visual markers with icons (🐂/🐻) and connecting lines
Historical Event Log (Enhanced):
Comprehensive event tracking:
- Tracks zone entries/exits, extreme values, cross events
- Now displays human-readable dates (YYYY-MM-DD) instead of bar indices
- Color-coded events (red for top/high, green for bottom/low)
- Configurable log size (5-50 events)
Information Table (Enhanced):
Comprehensive on-chart table with NEW metrics:
Current Values:
- MVRV Ratio: Current ratio value
- Percentile Rank: Position in historical distribution (0-100%)
- Risk Score (NEW): Composite risk indicator (0-100) with risk level
- Market Status: Current market condition
- Signal: Trading signal (Strong Buy/Buy/Hold/Sell/Strong Sell)
- MVRV Momentum (NEW): Trend direction with percentage change
- Time in Zone (NEW): Current zone and duration in bars
Price Information (Enhanced):
- Current Price: Current market price
- Est. Realized Price: Estimated realized price
- Price @ Fair Value (NEW): Price when MVRV = 1.0
- Price @ Top Threshold (NEW): Price when MVRV = 3.5
- Price @ Bottom Threshold (NEW): Price when MVRV = 0.8
Other Metrics:
- Percentile Bands: Range from 5th to 95th percentile
- MVRV-Z Score: Z-score value (when comparison enabled)
- Change (1D/1W/1M): Ratio change over timeframes
- To Top/Bottom: Percentage distance to key levels
- Historical Range: Percentage below ATH / above ATL
- 30D Volatility: Standard deviation
Historical Event Log:
- Recent events with dates and values
- Color-coded for quick identification
Alert System
Comprehensive alerting capabilities:
Zone Alerts:
- Top Zone Entry/Exit
- Bottom Zone Entry/Exit
Cross Alerts:
- Cross Above/Below Top Threshold
- Cross Above/Below Fair Value (1.0)
Extreme Value Alerts:
- Extreme High (configurable, default: 4.5)
- Extreme Low (configurable, default: 0.7)
Rate of Change Alerts:
- Rapid Increase/Decrease
Divergence Alerts:
- Bullish/Bearish Divergence
- Hidden Bullish/Bearish Divergence
All alerts support cooldown to prevent spam.
Usage Instructions
Getting Started:
1. Select data source (Glassnode recommended)
2. Enable Risk Score for composite risk assessment (0-100)
3. Enable MVRV Momentum to track trend direction
4. Enable Time in Zone to see zone duration
5. Enable Price Targets to see price levels at key thresholds
6. Use weekly timeframe for cleaner signals
Risk-Based Position Sizing:
Use Risk Score to guide position sizing:
- Risk Score >80 (Very High Risk): Reduce/exit positions
- Risk Score 60-80 (High Risk): Smaller positions, caution
- Risk Score 40-60 (Moderate Risk): Normal positions
- Risk Score 20-40 (Low Risk): Larger positions opportunity
- Risk Score <20 (Very Low Risk): Strong accumulation zone
Momentum-Based Analysis:
Use MVRV Momentum for trend confirmation:
- ↑ Increasing + High MVRV: Late bull market, caution
- ↑ Increasing + Low MVRV: Recovery phase, bullish
- ↓ Decreasing + High MVRV: Distribution, potential top
- ↓ Decreasing + Low MVRV: Capitulation, accumulation opportunity
Zone Duration Analysis:
Use Time in Zone for context:
- Extended time in Top Zone: Late cycle, increased reversal risk
- Extended time in Bottom Zone: Accumulation opportunity
- Quick zone transitions: Higher volatility regime
Price Target Usage:
Use Price Targets for planning:
- Price @ Fair Value: Natural equilibrium level
- Price @ Top Threshold: Potential distribution target
- Price @ Bottom Threshold: Potential accumulation target
Technical Specifications
- Pine Script Version: v6
- Indicator Type: Non-overlay (displays in separate panel)
- Repainting Behavior: Minimal - calculations based on confirmed bar data
- Performance: Optimized with cached request.security() calls and ta.percentrank()
- Input Validation: Validates parameter combinations with warnings
- Compatibility: Works on all timeframes (data sources provide daily resolution)
- Edge Case Handling: Zero-division protection, NA value handling, boundary checks
Performance Optimizations:
- Cached request.security() calls for Market Cap, Realized Cap, and IntoTheBlock data
- Efficient ta.percentrank() replaces array-based percentile calculation
- Consolidated duplicate code (color functions, state tracking)
- Single-line ternary expressions for Pine Script compatibility
Constants:
- MAX_HISTORY_BARS = 5000 (TradingView's limit)
- PERCENTILE_EXTREME_HIGH = 90.0
- PERCENTILE_HIGH = 75.0
- PERCENTILE_MID = 50.0
- PERCENTILE_LOW = 25.0
- MIN_PERCENTILE_SAMPLES = 10
- DEFAULT_VOLATILITY_HIGH = 0.1
Known Limitations
- Data availability: Requires valid data subscription (IntoTheBlock, Glassnode, or CoinMetrics)
- Token support: Works with tokens supported by the selected data source
- Historical data: Percentile calculations require sufficient history (200+ bars recommended)
- Timeframe: Always uses daily resolution data from providers; works on all chart timeframes
- History limit: All lookback periods capped at 5000 bars
Changelog
Latest Version:
- Added Risk Score (0-100) composite indicator
- Added MVRV Momentum with trend direction
- Added Time in Zone tracking
- Added Price Target calculations
- Added Input Validation with warnings
- Added multiple smoothing options (SMA, EMA, WMA, RMA)
- Improved performance with cached security calls
- Replaced array-based percentile with ta.percentrank()
- Human-readable timestamps in event log (YYYY-MM-DD)
- Fixed hline() conditional value bug
- Consolidated duplicate code
- Updated indicator name for clarity
For detailed usage instructions, see the script comments.
Trend Strength [OmegaTools]Trend Strength is a quantitative regime oscillator designed to measure directional pressure and trend quality by blending price structure, return-dependence, realized intrabar expansion, and volume participation into a single normalized signal. The goal is not to predict, but to classify market state: when price action is in an expansionary/distributionary phase versus when it is in a contractionary/accumulation phase, so you can align execution and risk with the prevailing environment.
Core concept and methodology
The indicator aggregates four components computed on stable rolling windows and mapped into comparable ranges:
1. Price location / structural positioning (100-bar range)
A normalized price-location metric (position of close within the rolling high–low range) is transformed into a non-linear “strength” profile. This emphasizes meaningful departures from the middle of the range and penalizes indecision, producing a structure-aware contribution rather than a raw oscillator.
2. Return-dependence / directional persistence (100 bars)
A correlation term measures the relationship between the current return (close − close ) and the prior price level (close ). This helps detect environments where movement is more persistent or more mean-reverting, providing a statistical component that complements pure price-location signals.
3. Realized expansion / volatility proxy (50-bar accumulation, 300-bar normalization)
Intrabar expansion is approximated via the absolute candle body relative to the full range, aggregated over a short window to represent realized “effort” and then normalized over a longer window. This captures whether price is moving with meaningful body expansion versus compressing and stalling.
4. Volume participation (11-bar accumulation, 300-bar normalization)
A rolling volume sum is normalized over a longer window to quantify participation. This helps separate “thin” moves from moves supported by broader activity, without relying on exchange-specific volume assumptions.
The final oscillator is a weighted blend of these four normalized components, scaled for readability. The output is intentionally centered around two actionable regimes rather than a symmetric overbought/oversold framework.
How to read the oscillator
Trend Strength is designed around two main thresholds:
- Distribution / Expansion regime (oscillator above 0)
When the oscillator is above 0, the market is classified as being in a higher-pressure expansion regime. This often corresponds to directional continuation potential, stronger impulse behavior, and reduced suitability for tight mean-reversion tactics.
- Accumulation / Contraction regime (oscillator below −1.3)
When the oscillator is below −1.3, the market is classified as being in a contraction/accumulation regime. This frequently corresponds to compression, rotation, and lower directional efficiency, where breakouts may be more fragile and mean-reversion tactics may be more appropriate (depending on instrument and session conditions).
Values between 0 and −1.3 are treated as transitional/neutral, where the market is not clearly committing to either regime.
Continuous Mode vs Standard Mode
Trend Strength includes an optional Continuous Mode to improve interpretability during regime transitions:
- Standard Mode colors only when the oscillator is firmly in one of the two regimes (above 0 or below −1.3). Neutral zones remain uncolored, keeping the display conservative.
- Continuous Mode adds persistence logic: once a regime is confirmed, intermediate values are rendered with a lighter shade of the last confirmed regime until the opposite regime is confirmed. This reduces visual noise, helps maintain a consistent directional bias framework, and is particularly useful for intraday execution and session trend management.
Visual design and bar coloring
The oscillator line is color-coded:
- Purple: distribution / expansion regime
- Orange: accumulation / contraction regime
Neutral/transitional values are displayed in grey (or lightly shaded in Continuous Mode based on last confirmed regime).
Optionally, the indicator can color price bars using the same regime logic, allowing rapid at-a-glance regime recognition directly on the chart.
Practical use cases
- Regime filter for strategies: enable trend-following logic only in expansion regimes; enable mean-reversion or range logic in contraction regimes.
- Risk adjustment: increase/decrease position sizing or tighten/widen stops based on regime classification.
- Confirmation layer: combine with structure tools (market structure, VWAP, key levels) to validate whether conditions support continuation or imply compression.
- Session management: identify when a session is behaving as a trend day versus a rotational day, improving trade selection and reducing overtrading.
Notes
Trend Strength is a regime classifier and contextual tool. It does not guarantee future direction and should be integrated into a complete decision process (risk management, market structure, session context, and instrument-specific behavior).
© OmegaTools
Teemo Volume Delta & Market HUDTeemo Volume Delta & Market HUD
Description:
Teemo Volume Delta goes beyond simple volume indicators to provide expert-level analysis of Buy and Sell pressure within the market. It visualizes supply/demand imbalances inside candles and provides an immediate grasp of market control via a real-time HUD.
With the v1.2.0 update, we have removed unnecessary overlays (like EMAs) to focus on Pure Delta Analysis and a flexible Smart Accumulation System, making the tool lighter and more powerful.
🚀 Key Features
1. Dual Calculation Modes Offers two calculation methods tailored to your trading environment and goals:
Estimation: Rapidly estimates buy/sell volume based on candle shape (OHLC) and price range. It features fast loading times and works instantly on all assets.
Intraday: Analyzes lower timeframe data (e.g., 1-minute bars) to calculate the precise delta of the current timeframe. (Loading time may vary depending on TradingView data limits.)
2. Smart Accumulation System Supports strategic analysis beyond simple summation with two distinct modes:
Time Based: Resets the Cumulative Delta to 0 at specific intervals (e.g., every 4 hours, Daily). This is optimized for session-based analysis or day trading.
Infinite: Continuously accumulates data without resetting, ideal for analyzing long-term Divergences between price and delta.
3. Intuitive HUD (Heads-Up Display) Displays critical market data on the chart for instant decision-making:
Delta Panel: Shows real-time Buy/Sell volume and Net Delta for the current candle.
Market HUD: Provides a comprehensive view of Trend Strength (ADX), Momentum (RSI), and the Cumulative Buy/Sell status for the current period.
4. Teemo Design System (v1.2) Provides optimized color themes for visual comfort during long trading sessions:
Teemo Neon: High-contrast Mint/Purple theme optimized for dark backgrounds.
Classic Soft: A calming Soft Green/Red theme designed to reduce eye strain (Recommended for all backgrounds).
⚙️ Settings Guide
Calculation Mode: Choose between Estimation (Speed) or Intraday (Precision).
Accumulation Mode: Choose Time Based (Periodic Reset) or Infinite (Continuous).
Reset Period: Set the reset interval for Time Based mode (e.g., 1D = Daily Reset).
Color Preset: Select between Teemo Neon or Classic Soft themes.
💡 Trading Tips
Delta Divergence: If the price makes a higher high but the Cumulative Delta (HUD) makes a lower high, it signals weakening buying pressure and a potential reversal.
Candle Coloring: A solid Mint (or Green) candle body indicates a price rise accompanied by strong actual buying volume, offering higher reliability than standard candles.
HUD Confluence: Consider trend-following entries when the ADX is above 25 and the Delta is heavily skewed in one direction.
This indicator is for informational purposes only and does not constitute financial advice. The Estimation mode provides approximations based on algorithms, and the Intraday mode's accuracy depends on the quality of the lower timeframe data provided by the exchange.
Developed by Teemo Trading Systems
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Teemo Volume Delta & Market HUD
설명 본문:
Teemo Volume Delta는 단순한 거래량 지표를 넘어, 시장 내부의 매수(Buy)와 매도(Sell) 압력을 정밀하게 분석하는 전문가용 도구입니다. 캔들 내부의 수급 불균형을 시각화하고, 실시간 HUD를 통해 시장의 주도권이 누구에게 있는지 즉각적으로 파악할 수 있도록 돕습니다.
v1.2.0 업데이트를 통해 불필요한 보조지표(EMA)를 제거하고, 순수한 델타 분석과 유연한 누적(Accumulation) 시스템에 집중하여 더욱 가볍고 강력해졌습니다.
🚀 주요 기능 (Key Features)
1. 듀얼 계산 모드 (Dual Calculation Modes) 사용자의 환경과 목적에 맞춰 두 가지 계산 방식을 제공합니다.
Estimation (추정 모드): 캔들의 형태(OHLC)와 가격 변동폭을 기반으로 매수/매도 볼륨을 빠르게 추정합니다. 로딩 속도가 빠르며 모든 자산에 즉시 적용 가능합니다.
Intraday (정밀 분석 모드): 하위 타임프레임(예: 1분봉)의 데이터를 분석하여 상위 타임프레임의 델타를 정밀하게 계산합니다. (TradingView 데이터 제한에 따라 로딩 시간이 소요될 수 있습니다.)
2. 스마트 누적 시스템 (Smart Accumulation) 단순 누적을 넘어, 전략적 분석을 위한 두 가지 모드를 지원합니다.
Time Based: 지정한 주기(예: 4시간, 1일)마다 누적 델타를 **0으로 초기화(Reset)**합니다. 세션별 수급 분석이나 데이 트레이딩에 최적화되어 있습니다.
Infinite: 초기화 없이 데이터를 계속 누적하여, 장기적인 가격과 델타의 **다이버전스(Divergence)**를 분석하는 데 유용합니다.
3. 직관적인 HUD (Heads-Up Display) 차트 우측과 좌측에 핵심 정보를 요약하여 보여줍니다.
Delta Panel: 현재 캔들의 매수/매도 거래량과 순매수(Net Delta) 상태를 실시간으로 표시합니다.
Market HUD: ADX(추세 강도), RSI(모멘텀), 그리고 현재 구간의 누적 매수/매도 현황을 한눈에 볼 수 있습니다.
4. Teemo Design System (v1.2) 장시간 차트를 보는 트레이더를 위해 시인성이 뛰어난 컬러 테마를 제공합니다.
Teemo Neon: 어두운 배경에 최적화된 고대비 민트/퍼플 테마.
Classic Soft: 눈의 피로를 줄여주는 차분한 그린/레드 테마 (밝은/어두운 배경 모두 추천).
⚙️ 설정 가이드 (Settings)
Calculation Mode: Estimation(속도 중심) 또는 Intraday(정확도 중심) 중 선택.
Accumulation Mode: Time Based(주기별 리셋) 또는 Infinite(무한 누적) 선택.
Reset Period: Time Based 모드 사용 시 리셋할 주기 설정 (예: 1D = 매일 리셋).
Color Preset: Teemo Neon 또는 Classic Soft 테마 선택.
💡 활용 팁 (Trading Tips)
델타 다이버전스: 가격은 신고가를 갱신하지만 누적 델타(Cum Delta)는 낮아진다면, 매수세가 약화되고 있다는 강력한 반전 신호입니다.
캔들 컬러링: 캔들의 몸통 색상이 짙은 민트색(또는 그린)이라면 강력한 매수세가 동반된 상승을 의미하며, 신뢰도가 높습니다.
HUD 활용: ADX가 25 이상이면서 델타가 한쪽 방향으로 쏠릴 때 추세 매매를 고려하세요.
이 지표는 정보 제공의 목적으로만 사용되며, 재정적 조언이 아닙니다. Estimation 모드는 근사치를 제공하며, Intraday 모드는 거래소에서 제공하는 하위 데이터의 품질에 따라 정확도가 달라질 수 있습니다.
Smart Trader, Episode 02, by Ata Sabanci | Battle of Candles ⚠️ CRITICAL: READ BEFORE USING ⚠️
This indicator is 100% VOLUME-BASED and requires Lower Timeframe (LTF) intrabar data for accurate calculations. Please understand the following limitations before using:
📊 DATA ACCURACY LEVELS:
• 1T (Tick) — Most accurate, real volume distribution per tick
• 1S (1 Second) — Reasonably accurate approximation
• 15S (15 Seconds) — Good approximation, longer historical data available
• 1M (1 Minute) — Rough approximation, maximum historical data range
⚠️ BACKTEST & REPLAY LIMITATIONS:
• Replay mode results may differ from live trading due to data availability
• For longer back test periods, use higher LTF settings (15S or 1M)
• Not all symbols/exchanges support tick-level data
• Crypto and Forex typically have better LTF data availability than stocks
💡 A NOTE ON TOOLS:
Successful trading requires proper tools. Higher TradingView plans provide access to more historical intrabar data, which directly impacts the accuracy of volume-based calculations. More precise volume data leads to more reliable signals. Consider this when evaluating your trading infrastructure.
📌 OVERVIEW
Smart Trader Episode 02: Battle of Candles is an advanced educational indicator that combines multiple analysis engines to help traders identify market scenarios and understand market dynamics. This is NOT financial advice or a trading signal service — it's a learning tool designed to help you understand how institutional traders might interpret price action.
The indicator integrates 7 major analysis engines into a unified dashboard, providing real-time insights into volume flow, trend structure, market phases, and potential trade setups.
⚡ KEY FEATURES
🎯 16-Pattern Scenario Engine
Automatically detects and classifies market conditions into 16 distinct scenarios, from strong continuation moves to potential reversals and traps.
💰 Trade Advisor Panel
Aggregates all signals into actionable suggestions with confidence levels, suggested entry/SL/TP levels, and risk/reward calculations.
📊 Volume Engine
Splits volume into buy/sell components using either Geometry (candle shape) or Intrabar (LTF data) methods for precise delta analysis.
📈 CVD (Cumulative Volume Delta)
Tracks the running total of buying vs selling pressure to identify accumulation, distribution, and divergences.
🎯 Stop-Hunt Detection
Identifies potential stop-hunt patterns where price sweeps liquidity levels before reversing.
📐 Pure Structure Trend Engine
Zero-lag trend detection based on swing highs/lows (HH/HL/LH/LL) without any lagging indicators.
⚡ Effort vs Result Analysis
Measures energy spent (volume) versus ground taken (price movement) to detect stalls, breakthroughs, and exhaustion.
🎯 SCENARIO ENGINE — 16 Market Patterns
The Scenario Engine analyzes multiple factors (candle anatomy, volume, forces, CVD, wick analysis) to classify each candle into one of 16 scenarios:
Continuation Scenarios (1-3)
1. ⚔️ STRONG MOVE — Big body candle (>60%) with volume confirming direction. Indicates strong momentum continuation.
2. 🛡️ ABSORPTION — One side attacks but the other absorbs the pressure. Price holds despite volume. Continuation expected in the absorbing side's favor.
3. 📉 PULLBACK — Small move against the trend with low volume. Indicates a healthy retracement before trend continuation.
Reversal Scenarios (4-6, 13-16)
4. 💥 REJECTION — Big wick (>40%) with small body and high volume. Price was rejected
at a level, potential reversal.
5. 🪤 TRAP — Pin direction disagrees with delta. Extreme wick size. Looks bullish/bearish but the opposite may happen.
6. 😫 EXHAUSTION — High energy spent (volume) but low ground taken (price movement). Both sides active but momentum fading.
13. 🔄 CVD BULL DIV — Price falling but CVD rising. Hidden buying detected (accumulation). Potential bullish reversal.
14. 🔄 CVD BEAR DIV — Price rising but CVD falling. Hidden selling detected (distribution). Potential bearish reversal.
15. 🎯 STOP HUNT BULL — Shorts were liquidated below support. Price swept liquidity and reversed. Expect bullish move.
16. 🎯 STOP HUNT BEAR — Longs were liquidated above resistance. Price swept liquidity and reversed. Expect bearish move.
Range/Stalemate Scenarios (7-9)
7. ⚖️ DEADLOCK — Market in balance. Force ratio between 0.4-0.6. Low volume. No side winning.
8. 🔥 BATTLE — High volume fight in a range. Both sides attacking. Wicks on both ends of candle.
9. 🎯 WAITING — Building phase with quiet volume. Market is preparing but no trigger yet. Wait for breakout.
Pre-Breakout Scenarios (10-12)
10. 🚀 BULL SETUP — Buyers accumulating in a building phase. Positive delta building. Bullish pressure growing.
11. 💣 BEAR SETUP — Sellers distributing in a building phase. Negative delta building. Bearish pressure growing.
12. ⚡ BREAKOUT — Price at boundary with strong candle and volume supporting. Imminent breakout expected.
💰 TRADE ADVISOR ENGINE
The Trade Advisor aggregates all signals from the different engines into a single actionable output. It uses a weighted scoring system:
Scoring Weights:
• Scenario Signal: 30%
• Trend Alignment: 20%
• CVD Momentum: 15% + Divergence Bonus
• Pin Forces: 15%
• Liquidity Sweep: 12%
• Stop-Hunt Detection: 10%
• Effort vs Result: 10%
Possible Actions:
• ⏳ WAIT — Edge not strong enough (stay patient)
• 🟢 LONG ENTRY — Buyers have strong advantage + signals align
• 🔴 SHORT ENTRY — Sellers have strong advantage + signals align
• ⚠️ CLOSE LONG/SHORT — Position at risk (reversal/trend flip)
• 🛑 STOP LOSS — Price hit risk threshold
• 💰 TAKE PROFIT — Target threshold reached
📊 EXTENDED INFO PANEL (Detailed Explanations)
The Extended Info panel is hidden by default (toggle: Show Extended Info in settings). It provides detailed metrics that feed into the main engines:
CVD ANALYSIS
What is CVD?
Cumulative Volume Delta (CVD) is the running total of Buy Volume minus Sell Volume. It reveals the underlying buying/selling pressure that may not be visible in price alone.
CVD Value & Slope:
• ↗ Rising: CVD increasing = net buying pressure (bullish)
• ↘ Falling: CVD decreasing = net selling pressure (bearish)
• → Flat: No clear pressure direction
Accumulation vs Distribution:
• Accumulation %: Shows buying pressure strength (0-100). High accumulation with CVD rising = strong bullish bias.
• Distribution %: Shows selling pressure strength (0-100). High distribution with CVD falling = strong bearish bias.
Divergence Alerts:
• ⚠️ BULLISH DIVERGENCE: Price falling but CVD rising. Hidden buying = potential reversal UP.
• ⚠️ BEARISH DIVERGENCE: Price rising but CVD falling. Hidden selling = potential reversal DOWN.
WICK ANALYSIS
Wick Torque:
Torque measures the "rotational force" from wicks. It's calculated from wick length, volume, and body efficiency.
• Positive Torque (Bullish): Bottom wick power dominates. Buyers defended lower prices.
• Negative Torque (Bearish): Top wick power dominates. Sellers defended higher prices.
• ⚡ High Torque (>30): Strong signal, significant wick rejection occurred.
Stop-Hunt Detection:
The engine detects when price has likely swept stop-losses clustered at key levels:
• Stop Hunt Risk %: Likelihood score (0-100). Above 55% = confirmed hunt.
• "Shorts hunted": Price swept below support, liquidating shorts, expect bounce UP.
• "Longs hunted": Price swept above resistance, liquidating longs, expect drop DOWN.
LIQUIDITY SWEEPS
This section appears only when a liquidity sweep is detected. The engine monitors for price sweeping recent highs/lows and then reversing:
• 🎯 LIQUIDITY SWEPT ABOVE: Price broke recent highs but closed back below. Longs trapped, expect DOWN.
• 🎯 LIQUIDITY SWEPT BELOW: Price broke recent lows but closed back above. Shorts trapped, expect UP.
POWER BALANCE
The Power Balance meter shows the real-time strength comparison between buyers and sellers.
Force Ratio:
• 0% = Complete seller dominance
• 50% = Perfect balance
• 100% = Complete buyer dominance
Visual Bar:
• Left side (▓): Bear territory
• Right side (▓): Bull territory
• The bar is smoothed over recent history to reduce noise.
EFFORT vs RESULT
This section measures the efficiency of price movement relative to volume expended.
Energy:
How much volume was spent relative to the average. Energy > 1.0x means above-average volume activity.
Ground:
How much price movement occurred relative to average range. Ground > 1.0x means above-average price movement.
STALL Warning:
A STALL is detected when high energy is spent but low ground is taken (high effort, low result). This often indicates institutional battle, exhaustion, or imminent reversal.
MARKET PHASE
The Phase Engine classifies the current market regime:
RANGE : No clear trend. Price confined to middle of channel. Low ADX. Balanced forces. Trade breakouts with caution.
BUILDING : Compression/preparation phase. Channel tightening or boundary penetration without follow-through. Watch for breakout direction.
TRENDING : Active directional move. Clear slope, good efficiency, price on trending side of channel. Favor pullback entries.
Strength:
0-100% score combining slope, volume validity, and force/efficiency filters.
Bars: How many candles the current phase has persisted.
TRACK RECORD (Validation Panel)
Enable with Show Validation Panel in settings. This section tracks the historical accuracy of scenario predictions:
Accuracy: Percentage of validated predictions that were correct.
Best/Worst Scenario: Shows which scenarios have the highest and lowest accuracy on the current symbol.
Recent Signals: Last 5 predictions with their outcomes. ✓ = correct, ✗ = wrong, ⏳ = pending validation.
⚙️ SETTINGS GUIDE
📊 Volume Analysis
Volume Calculation: Choose Geometry (estimates from candle shape) or Intrabar (precise LTF data).
Intrabar Resolution: LTF for precise mode. Try 1S, 15S, or 1T. Must be lower than chart timeframe.
History Depth: Candles stored in memory (5-50). Higher = more context, slower.
Memory Lookback: Bars for moving averages and Z-scores (10-100).
🏷️ Market Phase
Range Zone Width: How much of channel center is considered "range" (0.1-0.8).
Trend Sensitivity: Minimum slope to detect trending. Lower = more sensitive.
Min Episode Length: Minimum bars before phase can change. Prevents flickering.
🎯 Scenarios
Min Confidence to Show: Only display scenarios above this confidence level (30-90).
Bars to Validate: How many bars to wait before checking if prediction was correct.
Success Move %: Minimum price movement to consider prediction successful.
💰 Trade Advisor
Min Confidence for Entry: Minimum confidence to suggest a trade entry (50-90).
Default Risk %: Stop loss distance as % of price (0.5-5.0).
Min Risk/Reward: Minimum acceptable R:R ratio (1.0-5.0).
🔔 ALERT CONDITIONS
The indicator provides the following alert conditions you can configure:
• 🟢 LONG Entry Signal
• 🔴 SHORT Entry Signal
• ⚠️ Close LONG Signal
• ⚠️ Close SHORT Signal
• 🛑 STOP LOSS Alert
• 💰 Take Profit Alert
• 🚨 High Urgency Signal
⚠️ IMPORTANT DISCLAIMER
EDUCATIONAL TOOL ONLY
This indicator is designed for educational purposes to help users identify different market scenarios and understand how various signals might be interpreted.
The Trade Advisor is NOT a recommendation to buy, sell, or invest.
• Past performance does not guarantee future results
• All trading involves risk of loss
• The creator is not a licensed financial advisor
• Always do your own research (DYOR)
• Consult a qualified financial advisor before making any investment decisions
By using this indicator, you acknowledge that you understand these risks and accept full responsibility for your trading decisions.
Delta Reaction Zones [BOSWaves]Delta Reaction Zones - Cumulative Delta-Based Supply and Demand Identification with Flow-Weighted Zone Construction
Overview
Delta Reaction Zones is a volume flow-aware supply and demand detection system that identifies price levels where significant buying or selling pressure accumulated, constructing adaptive zones around cumulative delta extremes with intelligent flow composition analysis.
Instead of relying on traditional price-based support and resistance or fixed pivot structures, zone placement, thickness, and directional characterization are determined through delta accumulation patterns, volatility-adaptive sizing, and the proportional composition of positive versus negative volume flow.
This creates dynamic reaction boundaries that reflect actual order flow imbalances rather than arbitrary price levels - contracting during low volatility environments, expanding during elevated volatility periods, and incorporating flow composition statistics to reveal whether zones formed under buying or selling dominance.
Price is therefore evaluated relative to zones anchored at delta extremes rather than conventional technical levels.
Conceptual Framework
Delta Reaction Zones is founded on the principle that meaningful support and resistance emerge where cumulative volume flow reaches local extremes rather than where price alone forms patterns.
Traditional support and resistance methods identify turning points through price structure, which often ignores the underlying order flow dynamics that drive those reversals. This framework replaces price-centric logic with delta-driven zone construction informed by actual buying and selling pressure.
Three core principles guide the design:
Zone placement should correspond to cumulative delta extremes, not price pivots alone.
Zone thickness must adapt to current market volatility conditions.
Flow composition context reveals whether zones formed under accumulation or distribution.
This shifts supply and demand analysis from static price levels into adaptive, flow-anchored reaction boundaries.
Theoretical Foundation
The indicator combines delta proxy methodology, cumulative volume tracking, adaptive volatility measurement, and flow decomposition analysis.
A signed volume delta proxy estimates directional order flow on each bar, which accumulates into a running cumulative delta series. Pivot detection identifies local extremes in either cumulative delta or its rate of change, marking levels where flow momentum reached inflection points. Average True Range (ATR) provides volatility-responsive zone sizing, while impulse window analysis decomposes recent flow into positive and negative components with percentage weighting.
Four internal systems operate in tandem:
Delta Accumulation Engine : Computes smoothed signed volume and maintains cumulative delta tracking for directional flow measurement.
Pivot Detection System : Identifies significant turning points in cumulative delta or delta rate of change to anchor zone placement.
Adaptive Zone Construction : Scales zone thickness dynamically using ATR-based volatility measurement around pivot anchors.
Flow Composition Analysis : Calculates positive and negative flow percentages over a configurable impulse window to characterize zone formation context.
This design allows zones to reflect actual order flow behavior rather than reacting mechanically to price formations.
How It Works
Delta Reaction Zones evaluates price through a sequence of flow-aware processes:
Signed Volume Delta Calculation : Each bar's volume is directionally signed based on close-open relationship, creating a proxy for buying versus selling pressure.
Cumulative Delta Tracking : Signed volume accumulates into a running total, revealing sustained directional flow over time.
Pivot Identification : Local highs and lows in cumulative delta (or its rate of change) mark significant flow inflection points where zones anchor.
Volatility-Adaptive Sizing : ATR multiplier determines zone half-width, automatically adjusting thickness to current market conditions.
Flow Decomposition : Positive and negative volume components are separated and percentage-weighted over the impulse window to reveal dominant flow direction.
Intelligent Zone Merging : Overlapping zones of the same type automatically merge into broader reaction areas, with flow statistics blended proportionally.
Dynamic Extension and Visualization : Zones extend forward with gradient-filled composition segments showing buy versus sell flow proportions.
Breach Detection and Cleanup : Zones invalidate automatically when price closes beyond their boundaries, maintaining chart clarity.
Together, these elements form a continuously updating supply and demand framework anchored in order flow reality.
Interpretation
Delta Reaction Zones should be interpreted as flow-anchored supply and demand boundaries:
Support Zones (Green) : Form at cumulative delta lows, marking levels where selling exhaustion or buying accumulation occurred.
Resistance Zones (Red) : Establish at cumulative delta highs, identifying areas where buying exhaustion or selling distribution dominated.
Flow Composition Segments : Visual gradient within each zone reveals the buy/sell flow proportion during zone formation. The upper segment (red tint) represents negative (selling) flow percentage while the lower segment (green tint) represents positive (buying) flow percentage.
BUY FLOW / SELL FLOW / MIXED Labels : Indicate dominant flow character when one direction exceeds 60% of total impulse window activity.
Net Delta Statistics : Display cumulative flow totals (Δ) alongside percentage breakdowns for immediate context.
Zone Thickness : Reflects current volatility environment - wider zones in volatile conditions, tighter zones in calm markets.
Zone Merging : Multiple nearby pivots consolidate into broader reaction areas, weighted by their respective flow magnitudes.
Flow composition, volatility context, and delta magnitude outweigh isolated price reactions.
Signal Logic & Visual Cues
Delta Reaction Zones presents two primary interaction signals:
Support Reclaim (RC) : Green label appears when price crosses back above a support zone's midline after trading below it, suggesting renewed buying interest.
Resistance Re-enter (RE) : Red label displays when price crosses back below a resistance zone's midline after trading above it, indicating resumed selling pressure.
Alert generation covers zone creation and midline reclaim/re-entry events for systematic monitoring.
Strategy Integration
Delta Reaction Zones fits within order flow-informed and supply/demand trading approaches:
Flow-Anchored Entry Zones : Use zones as high-probability reaction areas where historical order flow imbalances occurred.
Composition-Based Bias : Favor trades aligning with dominant flow character - long setups near zones formed under buying dominance, short setups near selling-dominated zones.
Volatility-Aware Targeting : Expect wider reaction ranges when ATR expands zones, tighter ranges when ATR contracts them.
Merge-Informed Conviction : Broader merged zones represent multiple flow inflection points, potentially offering stronger support/resistance.
Midline Reclaim Validation : Use RC/RE signals as confirmation of zone respect rather than standalone entry triggers.
Multi-Timeframe Flow Context : Apply higher-timeframe delta zones to inform lower-timeframe entry precision.
Technical Implementation Details
Core Engine : Signed volume delta proxy with EMA smoothing
Accumulation Model : Persistent cumulative delta tracking with optional rate-of-change pivot detection
Zone Construction : ATR-scaled thickness around pivot anchors
Flow Analysis : Positive/negative decomposition over configurable impulse window
Visualization : Gradient-filled zones with embedded flow statistics and percentage segments
Signal Logic : Midline crossover detection with breach-based invalidation
Merge System : Proximity-based consolidation with weighted flow blending
Performance Profile : Optimized for real-time execution with configurable zone limits
Optimal Application Parameters
Timeframe Guidance:
1 - 5 min : Micro-structure flow zones for scalping and short-term reversals
15 - 60 min : Intraday supply/demand identification with flow context
4H - Daily : Swing-level reaction zones with macro flow characterization
Suggested Baseline Configuration:
Delta Smoothing Length : 3
Pivot Length : 12
Pivot Source : Cumulative Delta
Impulse Window : 100
ATR Length : 14
ATR Multiplier : 0.35 (reduce for lower timeframes)
Maximum Zones : 8
Merge Overlapping Zones : Enabled
Merge Gap : 20 ticks
These suggested parameters should be used as a baseline; their effectiveness depends on the asset's volume profile, tick structure, and preferred zone density, so fine-tuning is expected for optimal performance.
Parameter Calibration Notes
Use the following adjustments to refine behavior without altering the core logic:
Zones appearing oversized : Reduce ATR Multiplier to tighten zone thickness, especially on lower timeframes.
Excessive zone clutter : Increase Pivot Length to demand stronger delta extremes before zone creation.
Unstable delta readings : Increase Delta Smoothing Length to reduce bar-to-bar noise in flow calculation.
Missing significant levels : Decrease Pivot Length or switch Pivot Source to "Cumulative Delta RoC" for flow acceleration sensitivity.
Flow percentages feel stale : Reduce Impulse Window Length to emphasize more recent buying/selling composition.
Too many merged zones : Decrease Merge Gap (ticks) or disable merging to preserve individual pivot zones.
Adjustments should be incremental and evaluated across multiple session types rather than isolated market conditions.
Performance Characteristics
High Effectiveness:
Markets with consistent volume and order flow characteristics
Instruments where delta proxy correlates well with actual tape reading
Mean-reversion strategies targeting flow exhaustion zones
Trend continuation entries at zones aligned with dominant flow direction
Reduced Effectiveness:
Extremely low volume environments where delta proxy becomes unreliable
News-driven or gapped markets with discontinuous flow
Highly manipulated or illiquid instruments with erratic volume patterns
Integration Guidelines
Confluence : Combine with BOSWaves structure, market profile, or traditional supply/demand analysis
Flow Respect : Trust zones formed with strong net delta magnitude and clear flow dominance
Context Awareness : Consider whether current market regime matches zone formation conditions
Merge Recognition : Treat merged zones as higher-conviction areas due to multiple flow inflections
Breach Discipline : Exit zone-based setups cleanly when price invalidates boundaries
Disclaimer
Delta Reaction Zones is a professional-grade order flow and supply/demand analysis tool. It uses a volume-based delta proxy that estimates directional pressure but does not access true order book data. Results depend on market conditions, volume reliability, parameter selection, and disciplined execution. BOSWaves recommends deploying this indicator within a broader analytical framework that incorporates price structure, volatility context, and comprehensive risk management.
PEAD ScreenerPEAD Screener - Post-Earnings Announcement Drift Scanner
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WHY EARNINGS ANNOUNCEMENTS CREATE OPPORTUNITY
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The days immediately following an earnings announcement are among the noisiest periods for any stock. Within hours, the market must digest new information about a company's profits, revenue, and future outlook. Analysts scramble to update their models. Institutions rebalance positions. Retail traders react to headlines.
This chaos creates a well-documented phenomenon called Post-Earnings Announcement Drift (PEAD): stocks that beat expectations tend to keep rising, while those that miss tend to keep falling - often for weeks after the initial announcement. Academic research has confirmed this pattern persists across decades and markets.
But not every earnings surprise is equal. A company that beats estimates by 5 cents might move very differently than one that beats by 5 cents with unusually high volume, or one where both earnings AND revenue exceeded expectations. Raw numbers alone don't tell the full story.
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HOW "STANDARDIZED UNEXPECTED" METRICS CUT THROUGH THE NOISE
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This screener uses a statistical technique to measure how "surprising" a result truly is - not just whether it beat or missed, but how unusual that beat or miss was compared to the company's own history.
The core idea: convert raw surprises into Z-scores.
A Z-score answers the question: "How many standard deviations away from normal is this result?"
- A Z-score of 0 means the result was exactly average
- A Z-score of +2 means the result was unusually high (better than ~95% of historical results)
- A Z-score of -2 means the result was unusually low
By standardizing surprises this way, we can compare apples to apples. A small-cap biotech's $0.02 beat might actually be more significant than a mega-cap's $0.50 beat, once we account for each company's typical variability.
This screener applies this standardization to three dimensions: earnings (SUE), revenue (SURGE), and volume (SUV).
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THE 9 SCREENING CRITERIA
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1. SUE (Standardized Unexpected Earnings)
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WHAT IT IS:
SUE measures how surprising an earnings result was, adjusted for the company's historical forecast accuracy.
Calculation: Take the earnings surprise (actual EPS minus analyst estimate), then divide by the standard deviation of past forecast errors. This uses a rolling window of the last 8 quarters by default.
Formula: SUE = (Actual EPS - Estimated EPS) / Standard Deviation of Past Errors
HOW TO INTERPRET:
- SUE > +2.0: Strongly positive surprise - earnings beat expectations by an unusually large margin. These stocks often continue drifting higher.
- SUE between 0 and +2.0: Modest positive surprise - beat expectations, but within normal range.
- SUE between -2.0 and 0: Modest negative surprise - missed expectations, but within normal range.
- SUE < -2.0: Strongly negative surprise - significant miss. These stocks often continue drifting lower.
For long positions, look for SUE values above +2.0, ideally combined with positive SURGE.
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2. SURGE (Standardized Unexpected Revenue)
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WHAT IT IS:
SURGE applies the same standardization technique to revenue surprises. While earnings can be manipulated through accounting choices, revenue is harder to fake - it represents actual sales.
Calculation: Take the revenue surprise (actual revenue minus analyst estimate), then divide by the standard deviation of past revenue forecast errors.
Formula: SURGE = (Actual Revenue - Estimated Revenue) / Standard Deviation of Past Errors
HOW TO INTERPRET:
- SURGE > +1.5: Strongly positive revenue surprise - the company sold significantly more than expected.
- SURGE between 0 and +1.5: Modest positive surprise.
- SURGE < 0: Revenue missed expectations.
The most powerful signals occur when BOTH SUE and SURGE are positive and elevated (ideally SUE > 2.0 AND SURGE > 1.5). This indicates the company beat on both profitability AND top-line growth - a much stronger signal than either alone.
When SUE and SURGE diverge significantly (e.g., high SUE but negative SURGE), treat with caution - the earnings beat may have come from cost-cutting rather than genuine growth.
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3. SUV (Standardized Unexpected Volume)
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WHAT IT IS:
SUV detects unusual trading volume after accounting for how volatile the stock is. More volatile stocks naturally have higher volume, so raw volume comparisons can be misleading.
Calculation: This uses regression analysis to model the expected relationship between price volatility and volume. The "unexpected" volume is the residual - how much actual volume deviated from what the model predicted. This residual is then standardized into a Z-score.
In plain terms: SUV asks "Given how much this stock typically moves, is today's volume unusually high or low?"
HOW TO INTERPRET:
- SUV > +2.0: Exceptionally high volume relative to the stock's volatility. This often signals institutional activity - big players moving in or out.
- SUV between +1.0 and +2.0: Elevated volume - above normal interest.
- SUV between -1.0 and +1.0: Normal volume range.
- SUV < -1.0: Unusually quiet - less activity than expected.
High SUV combined with positive price movement suggests accumulation (buying). High SUV combined with negative price movement suggests distribution (selling).
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4. % From D0 Close
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WHAT IT IS:
This measures how far the current price has moved from the closing price on its initial earnings reaction day (D0). The "reaction day" is the first trading day that fully reflects the earnings news - typically the day after an after-hours announcement, or the announcement day itself for pre-market releases.
Calculation: ((Current Price - D0 Close) / D0 Close) × 100
HOW TO INTERPRET:
- Positive values: Stock has gained ground since earnings. The higher the percentage, the stronger the post-earnings drift.
- 0% to +5%: Modest positive drift - earnings were received well but momentum is limited.
- +5% to +15%: Strong drift - buyers continue accumulating.
- > +15%: Exceptional drift - significant institutional interest likely.
- Negative values: Stock has given back gains or extended losses since earnings. May indicate the initial reaction was overdone, or that sentiment is deteriorating.
This metric is most meaningful within the first 5-20 trading days after earnings. Extended drift (maintaining gains over 2+ weeks) is a stronger signal than a quick spike that fades.
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5. # Pocket Pivots
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WHAT IT IS:
Pocket Pivots are a volume-based pattern developed by Chris Kacher and Gil Morales. They identify days where institutional buyers are likely accumulating shares without causing obvious breakouts.
Calculation: A Pocket Pivot occurs when:
- The stock closes higher than it opened (up day)
- The stock closes higher than the previous day's close
- Today's volume exceeds the highest down-day volume of the prior 10 trading sessions
The screener counts how many Pocket Pivots have occurred since the earnings announcement.
HOW TO INTERPRET:
- 0 Pocket Pivots: No detected institutional accumulation patterns since earnings.
- 1-2 Pocket Pivots: Some institutional buying interest - worth monitoring.
- 3+ Pocket Pivots: Strong accumulation signal - institutions appear to be building positions.
Pocket Pivots are most significant when they occur:
- Immediately following earnings announcements
- Near moving average support (10-day, 21-day, or 50-day)
- On above-average volume
- After a period of price consolidation
Multiple Pocket Pivots in a short period suggest sustained institutional demand, not just a one-day event.
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6. ADX/DI (Trend Strength and Direction)
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WHAT IT IS:
ADX (Average Directional Index) measures trend strength regardless of direction. DI (Directional Indicator) shows whether the trend is bullish or bearish.
Calculation: ADX uses a 14-period lookback to measure how directional (trending) price movement is. Values range from 0 to 100. The +DI and -DI components compare upward and downward movement.
The screener shows:
- ADX value (trend strength)
- Direction indicator: "+" for bullish (price trending up), "-" for bearish (price trending down)
HOW TO INTERPRET:
- ADX < 20: Weak trend - the stock is moving sideways, choppy. Not ideal for momentum trading.
- ADX 20-25: Trend is emerging - potentially starting a directional move.
- ADX 25-40: Strong trend - clear directional movement. Good for momentum plays.
- ADX > 40: Very strong trend - powerful move in progress, but may be extended.
The direction indicator (+/-) tells you which way:
- "25+" means ADX of 25 with bullish direction (uptrend)
- "25-" means ADX of 25 with bearish direction (downtrend)
For post-earnings plays, ideal setups show ADX rising above 25 with positive direction, confirming the earnings reaction is developing into a sustained trend rather than a one-day spike.
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7. Institutional Buying PASS
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WHAT IT IS:
This proprietary composite indicator detects patterns consistent with institutional accumulation at three stages after earnings:
EARLY (Days 0-4): Looks for "large block" buying on the earnings reaction day (exceptionally high volume with a close in the upper half of the day's range) combined with follow-through buying on the next day.
MID (Days 5-9): Checks for sustained elevated volume (averaging 1.5x the 20-day average) combined with positive drift and consistent upward price movement (more up days than down days).
LATE (Days 10+): Detects either visible accumulation (positive drift with high volume) OR stealth accumulation (positive drift with unusually LOW volume - suggesting smart money is quietly building positions without attracting attention).
HOW TO INTERPRET:
- Check mark/value of '1': Institutional buying pattern detected. The stock shows characteristics consistent with large players accumulating shares.
- X mark/value of '0': No institutional buying pattern detected. This doesn't mean institutions aren't buying - just that the typical footprints aren't visible.
A passing grade here adds conviction to other bullish signals. Institutions have research teams, information advantages, and long time horizons. When their footprints appear in the data, it often precedes sustained moves.
Important: This is a pattern detection tool, not a guarantee. Always combine with other analysis.
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8. Strong ATR Drift PASS
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WHAT IT IS:
This measures whether the stock has drifted significantly relative to its own volatility. Instead of asking "did it move 10%?", it asks "did it move more than 1.5 ATRs?"
ATR (Average True Range) measures a stock's typical daily movement. A volatile stock might move 5% daily, while a stable stock might move 0.5%. Using ATR normalizes for this difference.
Calculation:
ATR Drift = (Current Close - D0 Close) / D0 ATR in dollars
The indicator passes when ATR Drift exceeds 1.5 AND at least 5 days have passed since earnings.
HOW TO INTERPRET:
- Check mark/value of '1': The stock has drifted more than 1.5 times its average daily range since earnings - a statistically significant move that suggests genuine momentum, not just noise.
- X mark/value of '0': The drift (if any) is within normal volatility bounds - could just be random fluctuation.
Why wait 5 days? The immediate post-earnings reaction (days 0-2) often includes gap fills and noise. By day 5, if the stock is still extended beyond 1.5 ATRs from the earnings close, it suggests real buying pressure, not just a reflexive gap.
A passing grade here helps filter out stocks that "beat earnings" but haven't actually moved meaningfully. It focuses attention on stocks where the market is voting with real capital.
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9. Days Since D0
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WHAT IT IS:
Simply counts the number of trading days since the earnings reaction day (D0).
HOW TO INTERPRET:
- Days 0-5 (Green): Fresh earnings - the information is new, institutional repositioning is active, and momentum trades are most potent. This is the "sweet spot" for PEAD strategies.
- Days 6-10 (Neutral): Mid-period - some edge remains but diminishing. Good for adding to winning positions, less ideal for new entries.
- Days 11+ (Red): Extended period - most of the post-earnings drift has typically played out. Higher risk that momentum fades or reverses.
Research shows PEAD effects are strongest in the first 5-10 days after earnings, then decay. Beyond 20-30 days, the informational advantage of the earnings surprise is largely priced in.
Use this to prioritize: focus on stocks with strong signals that are still in the early window, and be more selective about entries as days accumulate.
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PUTTING IT ALL TOGETHER
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You can use this screener in the chart view or in the Screener.
One combination of the above filters to develop a shortlist of positive drift candidates may be:
- SUE > 2.0 (significant earnings beat)
- SURGE > 1.5 (significant revenue beat)
- Positive % From D0 Close (price confirming the good news)
- Institutional Buying PASS (big players accumulating)
- Strong ATR Drift PASS (statistically significant movement)
- Days Since D0 < 10 (still in the active drift window)
No single indicator is sufficient. The power comes from convergence - when multiple independent measures all point the same direction.
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SETTINGS
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Key adjustable parameters:
- SUE Method: "Analyst-based" uses consensus estimates; "Time-series" uses year-over-year comparison
- Window Size: Number of quarters used for standardization (default: 8)
- ATR Drift Threshold: Minimum ATR multiple for "strong" classification (default: 1.5)
- Institutional Buying thresholds: Adjustable volume and CLV parameters
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DISCLAIMER
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This screener is a research tool, not financial advice. Past patterns do not guarantee future results. Always conduct your own due diligence and manage risk appropriately. Post-earnings trading involves significant uncertainty and volatility. The 'SUE' in this indicator does not represent a real person; any similarity to actual Sue's (or Susans for that matter) living or dead is quite frankly ridiculous, not to mention coincidental.
Macros+AMD [NW]Macros + AMD - Daily & Weekly Time-Based Analysis
Multi-timeframe AMD (Accumulation, Manipulation, Distribution) visualization with ICT Macro timing windows for time-based market analysis.
Overview
This indicator visualizes the AMD (Accumulation, Manipulation, Distribution) framework on both daily and weekly timeframes, combined with ICT Macro timing windows. It is designed as an educational tool to help traders study time-based market structure and algorithmic price delivery concepts.
The AMD model is based on the idea that markets move through distinct phases within each trading period:
Accumulation (A) - Initial range formation, liquidity building
Manipulation (M) - False moves to trap traders, liquidity sweeps
Distribution (D) - True directional move, price delivery to targets
What This Indicator Displays
Daily AMD Phases
Displays the intraday AMD cycle based on New York trading hours:
A Phase (Blue): 4:00 AM - 8:35 AM EST — Morning accumulation, Asian/London overlap
M Phase (Red): 8:35 AM - 11:25 AM EST — NY session manipulation, news events
D Phase (Green): 11:25 AM - 4:00 PM EST — Afternoon distribution and price delivery
Weekly AMD Phases
Displays the weekly AMD cycle from Monday to Monday:
A Phase: Monday 00:00 - Tuesday 21:56 EST — Weekly high/low formation begins
M Phase: Tuesday 21:56 - Thursday 02:04 EST — Mid-week reversal zone
D Phase: Thursday 02:04 - Monday 00:00 EST — Weekly price delivery
Inner M Phase Fibs
When enabled, subdivides the M (Manipulation) phase using Fibonacci levels:
0.382 level — Inner accumulation ends
0.500 level — Mid-point of manipulation
0.618 level — Inner distribution begins
This helps identify potential reversal points within the manipulation phase.
ICT Macro Windows
Horizontal lines marking the XX:42 to XX:15 macro periods (33-minute windows):
2:42 - 3:15 AM
3:42 - 4:15 AM (London)
7:42 - 8:15 AM
8:42 - 9:15 AM
9:42 - 10:15 AM (Prime AM session)
10:42 - 11:15 AM
11:42 - 12:15 PM
12:42 - 1:15 PM
1:42 - 2:15 PM
2:42 - 3:15 PM
These windows represent times when algorithmic price delivery is more likely to occur.
How To Use
Understanding the AMD Framework
During the A Phase:
Observe range formation and initial liquidity pools
Note the high and low established during this phase
Wait for manipulation before committing to direction
During the M Phase:
Watch for false breakouts and stop hunts
Look for reversal patterns after liquidity sweeps
The inner fibs (0.382, 0.5, 0.618) can help time entries within this phase
Mid-week (Wednesday) often sees key reversals on weekly AMD
During the D Phase:
This is typically when the true move occurs
Price tends to deliver toward draw on liquidity targets
The direction is often opposite to the manipulation move
Using the Macro Windows
The XX:42 to XX:15 windows are times to pay attention to price action:
These 33-minute periods often see increased algorithmic activity
Look for displacement, fair value gaps, or order blocks forming
The 9:42-10:15 AM window is considered particularly significant for NY session
Weekly Day Labels
Monday/Tuesday: "H/L of Week" — Watch for weekly high or low formation
Wednesday: "Reversal Day" — Mid-week reversal probability increases
Thursday/Friday: "Reversal Day" — Continuation or secondary reversal
Settings Guide
Main Settings
Timezone: Set to your broker's timezone or preferred timezone
Macros On Top: Toggle macro lines above or below AMD boxes
Show All Text Labels: Master toggle for all text (turn off for clean charts on HTF)
Daily/Weekly AMD
Show: Enable/disable the AMD visualization
Opacity: Adjust transparency of the phase boxes (higher = more transparent)
AMD Colors
Customize colors for each phase (A, M, D)
Default: Blue (A), Red (M), Green (D)
Inner M Style
Customize the inner M phase fib lines and text colors
Default: Black lines for clean visibility
Macro Settings
Adjust macro line color and thickness
Toggle individual macro windows on/off
Important Notes
This indicator is for educational purposes and time-based analysis
It does not provide buy/sell signals
Always use in conjunction with proper price action analysis
Past price behavior during these time windows does not guarantee future results
The AMD framework is one lens for viewing market structure — use it as part of a complete methodology
Credits
This indicator is based on concepts taught by ICT (Inner Circle Trader) and the broader Smart Money Concepts community. The AMD framework, macro timing windows, and weekly profile concepts are derived from this educational methodology.
Timeframe Recommendations
Best viewed on 1-minute to 15-minute charts
Text labels automatically hide on 9-minute and higher timeframes for cleaner visualization
Indicator hides completely on 1-hour and higher timeframes
Changelog
v1.0 - Initial release
Daily AMD phases (4am-4pm EST)
Weekly AMD phases (Monday-Monday)
Inner M phase Fibonacci subdivisions
10 ICT Macro timing windows
Full customization options
Automatic 9-day cleanup
Low Volatility Profiles [BigBeluga]🔵 OVERVIEW
Low Volatility Profiles is a market compression and breakout-anticipation tool that identifies phases of low volatility using ADX and then builds a real-time volume profile inside the detected range.
This helps traders spot accumulation/distribution zones and prepare for explosive moves when volatility expands.
When volatility is low ➜ price coils ➜ volume organizes ➜ breakouts become highly actionable.
This tool visualizes that process with dynamic range boxes + volume bins + PoC extension.
🔵 CONCEPTS
Low-Volatility Detection — Uses ADX threshold & cross logic to define volatility contraction regimes.
Range Construction — Draws a price box that expands with highs/lows during the compression phase.
Micro Volume Profile — Builds a volume histogram inside the range using bins (micro volume nodes).
Delta Calculation — Tracks positive vs negative volume to gauge buyer/seller pressure within range.
Point of Control (PoC) — Highlights the price level with max traded volume inside the range.
PoC Extension — Optionally extends PoC into future bars to show potential reaction zone after breakout.
Breakout Validation — Ends the profile zone when price breaks above or below the modeled range.
Noise Removal — Automatically removes invalid or small ranges to prevent chart clutter.
This tool turns consolidation into actionable structure by exposing where smart money accumulates before trending moves.
🔵 FEATURES
ADX-Driven Range Detection — Identify when market transitions into low-volatility compression.
Configurable ADX Threshold — Set sensitivity for contraction zones.
Cross-Type Option — Detect low volatility via cross under / crossover logic.
Dynamic Range Box — Expands live with price as contraction unfolds.
Micro Volume Profile (Bins) — Distributes volume across bins inside range for micro POC mapping.
Volume Delta Visualization — Shows imbalance inside consolidation (accumulation vs distribution).
Real-Time PoC Highlight — Instantly shows most traded price inside the compression.
PoC Extension Mode — Extend PoC forward to project reaction levels post-breakout.
Clean Auto-Reset Logic — Removes boxes if range invalid or breakout occurs too fast.
Optional Filled Boxes — Heatmap-style profile visualization inside range body.
ADX Line + Threshold Plot — Visual assistance for volatility state monitoring.
🔵 HOW TO USE
Identify Accumulation Zones — When price enters low-volatility ADX condition and profile builds.
Watch the PoC — PoC acts as battle zone; move above/below can signal initiator strength.
Breakout Strategy — Trade break above/below the range after compression.
Mean Reversion Inside Range — Fade edges while price remains inside compression box.
Combine With Trend Tools — Use trend confirmation (MA/EMA/Flow indicators) after breakout.
Use Delta Clues — Positive delta tilt suggests accumulation; negative suggests distribution.
Monitor Range Size — Longer build + high PoC volume = stronger potential breakout energy.
🔵 CONCLUSION
Low Volatility Profiles isolates accumulation phases and maps volume concentration before volatility expansion.
By combining ADX compression, micro volume distribution, and PoC tracing, traders gain an edge in anticipating powerful breakout cycles and institutional positioning.
Trade the quiet moment before the storm — where smart money prepares the move, and the real opportunity emerges.
Momentum Squeeze Candle [Darwinian]# Momentum Squeeze Candle
Professional squeeze detection indicator with Wyckoff accumulation/distribution analysis and multi-method momentum signals.
## Overview
Identifies volatility compression (squeeze) periods and provides intelligent momentum direction signals based on institutional accumulation/distribution patterns.
## Features
6 Squeeze Detection Methods:
• BB + KC (Classic) - John Carter's TTM Squeeze
• ATR Ratio - Volatility compression detection
• Choppiness Index - Ranging vs trending analysis
• BB Width - Bollinger Band contraction
• Volume Contraction - Drying volume detection
• Hybrid Multi-Method - Ensemble approach (3+ methods must agree)
Smart Momentum Direction:
• Priority 1: Wyckoff signals (ATR compression + volume analysis)
• Priority 2: RSI momentum (55/45 thresholds)
• Priority 3: Hybrid slope + momentum confirmation
Visual Indicators:
• Blue candle coloring during squeeze
• Green circles = Bullish momentum (accumulation detected)
• Red circles = Bearish momentum (distribution detected)
• Optional BB/KC band overlay
## How It Works
Wyckoff Accumulation (Bullish):
ATR compressing + volume drying + price holding above MA = Smart money accumulating
→ Green circle signals
Wyckoff Distribution (Bearish):
ATR expanding + volume surging + price failing below MA = Smart money distributing
→ Red circle signals
## Recommended Settings
Swing Trading (Daily/4H):
Method: BB + KC or Hybrid | Sensitivity: 1.2-1.5
Day Trading (15m-1H):
Method: ATR Ratio or BB Width | Sensitivity: 0.8-1.0
Scalping (1m-5m):
Method: Volume Contraction | Sensitivity: 0.7-0.9
High Probability:
Method: Hybrid Multi-Method | Min Score: 4/5 | Sensitivity: 1.5
## Key Advantages
✓ Multiple squeeze detection algorithms for different market conditions
✓ Wyckoff methodology for institutional activity detection
✓ Priority-based momentum system reduces false signals
✓ Clean, optimized code (70% faster than typical indicators)
✓ Fully customizable sensitivity and visual settings
## Usage
1. Choose squeeze detection method based on your trading style
2. Watch for blue candles (squeeze active)
3. Monitor momentum signals:
- Green circles below bars = Accumulation phase (bullish)
- Red circles below bars = Distribution phase (bearish)
4. Trade the breakout in the direction of momentum signals
## Notes
• All inputs hidden from status line by default for clean charts
• Works on all timeframes and asset classes
• Combine with your trading strategy for confirmation
• Best results when multiple priority signals align
Perfect for traders looking to identify consolidation periods and predict breakout direction using institutional accumulation/distribution patterns.
Volume BubblesVolume Bubbles Indicator
Introduction
The Volume Bubbles indicator is a powerful tool designed to visually highlight significant volume spikes on your TradingView charts. It helps traders identify potential areas of whale accumulation (large buying activity) or dumping (large selling activity) by displaying colored bubbles on candles where volume exceeds a customizable threshold. Green bubbles indicate bullish (buy) volume on up candles, suggesting possible accumulation, while red bubbles signal bearish (sell) volume on down candles, indicating potential dumping. The bubble size scales with the volume magnitude, making it easy to spot major market moves at a glance.
This indicator is particularly useful for crypto, forex, and stock traders looking to gauge market sentiment and large player involvement without cluttering the chart. It's built in Pine Script v5 and overlays directly on your price action.
How It Works
The indicator calculates a moving average of volume (default: 20-period SMA) and detects spikes when current volume exceeds this average by a multiplier (default: 2x).
Buy Bubbles (Green): Appear on bullish candles (close >= open) at the low wick, representing potential whale buying or accumulation zones.
Sell Bubbles (Red): Appear on bearish candles (close < open) at the high wick, indicating potential whale selling or dumping zones.
Bubble Size: Dynamically sized based on volume thresholds – huge for >1M, large for 500K-1M, normal for <500K.
Transparency: Increases with volume ratio for better visibility on extreme spikes.
Tooltip:
Hover over a bubble to see detailed info like total volume, average volume, and ratio.
By focusing on these high-volume events, traders can spot key support/resistance levels where whales might be active.
How to Use for Whale Accumulation and Dumping
Whales (large holders) often move markets with high-volume trades. This indicator helps spot them:
Accumulation (Buying): Look for clusters of large green bubbles at price lows or during consolidations. This suggests whales are buying dips, potentially signaling a reversal or uptrend start. Combine with support levels for confirmation.
Dumping (Selling): Watch for big red bubbles at price highs or after rallies. This indicates whales unloading positions, which could lead to downtrends or corrections. Pair with resistance levels.
Tips:
Use on higher timeframes (e.g., 1H+) for reliable signals.
Confirm with other indicators like RSI or MACD to avoid false positives.
In trending markets, buy bubbles in uptrends confirm strength; sell bubbles in downtrends signal continuation.
Credits and Disclaimer
Inspired by volume analysis techniques. This is free to use; feedback welcome! Not financial advice – trade at your own risk.
UDVR + OBV Combo — MTF (v6)The UDVR + OBV Combo is a multi-timeframe volume analysis tool that blends the Up/Down Volume Ratio with a normalized On-Balance Volume signal. It highlights when accumulation or distribution truly supports price action, adds higher-timeframe context, and shades the background when both indicators align. Use it to confirm breakouts, spot divergences, and filter trades with the backing of real volume flows.
1.Up/Down Volume Ratio (UDVR)
•Compares the rolling sum of up-volume (bars where price closed higher) vs down-volume (bars where price closed lower).
•A ratio > 1.0 = more accumulation (bullish pressure).
•A ratio < 1.0 = more distribution (bearish pressure).
•Optional histogram shows deviations from the 1.0 baseline.
•Customizable handling of equal closes (count as up, down, split, or ignore).
•Configurable lookback length and optional EMA smoothing.
2. On-Balance Volume (OBV)
•Classic cumulative OBV implemented natively (adds volume on up-bars, subtracts on down-bars).
•Normalized with a z-score so it can be compared across different symbols/timeframes.
•Includes an EMA signal line for slope detection.
•Alignment of OBV vs its EMA highlights rising or waning participation.
3. Multi-Timeframe Support
•Both UDVR and OBV can be plotted from a higher timeframe (HTF) (e.g. Daily UDVR shown on a 1h chart).
•Lets you see big-money accumulation/distribution while trading intraday.
•Shaded background when current TF and HTF agree (both bullish or both bearish).
How to read it
• Bullish confirmation = UDVR > 1 (accumulation) and OBV above EMA (rising participation).
• Bearish confirmation = UDVR < 1 (distribution) and OBV below EMA (falling participation).
• Mixed signals (e.g. UDVR > 1 but OBV falling) = caution; price may lack conviction.
• Divergences : If price makes a new high but OBV or UDVR does not, it’s a warning of weakening trend.
• Higher timeframe context : set HTF = Daily or Weekly and watch how short-term signals align with institutional flows. A long trade on the 15m chart is stronger when Daily UDVR is also above 1.
Inputs
•UDVR Lookback: number of bars for rolling volume sums.
•Smoothing EMA: smooths UDVR for stability.
•Equal Close Handling: decide how equal closes affect UDVR.
•Signal Band: optional UDVR extreme thresholds.
•Show Histogram: toggle UDVR histogram around baseline.
•Higher Timeframe UDVR: overlay Daily/Weekly UDVR on lower timeframe charts.
•OBV EMA length: slope proxy for normalized OBV.
•OBV Normalization window: controls z-score sensitivity.
•Higher Timeframe OBV: overlay higher timeframe OBV.
Alerts
•UDVR Bullish/Bearish cross at the 1.0 baseline.
•OBV slope up/down when OBV crosses its EMA.
•Alignment signals when UDVR and OBV agree (both confirm bullish or bearish conditions).
Why it’s useful
•Combines trend, momentum, and participation in one place.
•Helps avoid false breakouts by checking if volume supports the move.
•Lets you spot accumulation/distribution shifts before they show up in price.
•Gives a higher timeframe context so you’re not trading against the “big picture.”
Once applied, the indicator creates a dedicated pane below price with the following components:
UDVR Line (green/red)
• Green when UDVR > 1.0 (more up-volume than down-volume → accumulation).
• Red when UDVR < 1.0 (more down-volume → distribution).
UDVR Baseline and Bands
• Grey baseline at 1.0 = balance between buying and selling volume.
• Optional upper/lower bands (default 1.5 and 0.67) highlight extreme imbalances.
• Shaded areas between baseline and bands provide visual context for strength/weakness.
UDVR Histogram (optional)
• Columns around the baseline showing (UDVR – 1.0).
• Quick way to gauge how far above/below balance the ratio is.
Higher-Timeframe UDVR (teal line)
• Overlays the UDVR from a higher timeframe (e.g. Daily) on your intraday chart.
• Lets you see whether institutional flows support your shorter-term signals.
OBV Normalized (blue/orange line)
• Classic OBV, but normalized with a z-score so it stays readable across assets.
• Blue when OBV is above its EMA (rising participation).
• Orange when below its EMA (waning participation).
OBV EMA (grey line)
• Signal line showing the slope of OBV.
• Crosses between OBV and this line mark shifts in participation.
Higher-Timeframe OBV (purple line, optional)
• Plots OBV from a higher timeframe for additional context.
Background Shading
• Light green = both UDVR > 1 and OBV > OBV-EMA (bullish alignment).
• Light red = both UDVR < 1 and OBV < OBV-EMA (bearish alignment).
Tensor Market Analysis Engine (TMAE)# Tensor Market Analysis Engine (TMAE)
## Advanced Multi-Dimensional Mathematical Analysis System
*Where Quantum Mathematics Meets Market Structure*
---
## 🎓 THEORETICAL FOUNDATION
The Tensor Market Analysis Engine represents a revolutionary synthesis of three cutting-edge mathematical frameworks that have never before been combined for comprehensive market analysis. This indicator transcends traditional technical analysis by implementing advanced mathematical concepts from quantum mechanics, information theory, and fractal geometry.
### 🌊 Multi-Dimensional Volatility with Jump Detection
**Hawkes Process Implementation:**
The TMAE employs a sophisticated Hawkes process approximation for detecting self-exciting market jumps. Unlike traditional volatility measures that treat price movements as independent events, the Hawkes process recognizes that market shocks cluster and exhibit memory effects.
**Mathematical Foundation:**
```
Intensity λ(t) = μ + Σ α(t - Tᵢ)
```
Where market jumps at times Tᵢ increase the probability of future jumps through the decay function α, controlled by the Hawkes Decay parameter (0.5-0.99).
**Mahalanobis Distance Calculation:**
The engine calculates volatility jumps using multi-dimensional Mahalanobis distance across up to 5 volatility dimensions:
- **Dimension 1:** Price volatility (standard deviation of returns)
- **Dimension 2:** Volume volatility (normalized volume fluctuations)
- **Dimension 3:** Range volatility (high-low spread variations)
- **Dimension 4:** Correlation volatility (price-volume relationship changes)
- **Dimension 5:** Microstructure volatility (intrabar positioning analysis)
This creates a volatility state vector that captures market behavior impossible to detect with traditional single-dimensional approaches.
### 📐 Hurst Exponent Regime Detection
**Fractal Market Hypothesis Integration:**
The TMAE implements advanced Rescaled Range (R/S) analysis to calculate the Hurst exponent in real-time, providing dynamic regime classification:
- **H > 0.6:** Trending (persistent) markets - momentum strategies optimal
- **H < 0.4:** Mean-reverting (anti-persistent) markets - contrarian strategies optimal
- **H ≈ 0.5:** Random walk markets - breakout strategies preferred
**Adaptive R/S Analysis:**
Unlike static implementations, the TMAE uses adaptive windowing that adjusts to market conditions:
```
H = log(R/S) / log(n)
```
Where R is the range of cumulative deviations and S is the standard deviation over period n.
**Dynamic Regime Classification:**
The system employs hysteresis to prevent regime flipping, requiring sustained Hurst values before regime changes are confirmed. This prevents false signals during transitional periods.
### 🔄 Transfer Entropy Analysis
**Information Flow Quantification:**
Transfer entropy measures the directional flow of information between price and volume, revealing lead-lag relationships that indicate future price movements:
```
TE(X→Y) = Σ p(yₜ₊₁, yₜ, xₜ) log
```
**Causality Detection:**
- **Volume → Price:** Indicates accumulation/distribution phases
- **Price → Volume:** Suggests retail participation or momentum chasing
- **Balanced Flow:** Market equilibrium or transition periods
The system analyzes multiple lag periods (2-20 bars) to capture both immediate and structural information flows.
---
## 🔧 COMPREHENSIVE INPUT SYSTEM
### Core Parameters Group
**Primary Analysis Window (10-100, Default: 50)**
The fundamental lookback period affecting all calculations. Optimization by timeframe:
- **1-5 minute charts:** 20-30 (rapid adaptation to micro-movements)
- **15 minute-1 hour:** 30-50 (balanced responsiveness and stability)
- **4 hour-daily:** 50-100 (smooth signals, reduced noise)
- **Asset-specific:** Cryptocurrency 20-35, Stocks 35-50, Forex 40-60
**Signal Sensitivity (0.1-2.0, Default: 0.7)**
Master control affecting all threshold calculations:
- **Conservative (0.3-0.6):** High-quality signals only, fewer false positives
- **Balanced (0.7-1.0):** Optimal risk-reward ratio for most trading styles
- **Aggressive (1.1-2.0):** Maximum signal frequency, requires careful filtering
**Signal Generation Mode:**
- **Aggressive:** Any component signals (highest frequency)
- **Confluence:** 2+ components agree (balanced approach)
- **Conservative:** All 3 components align (highest quality)
### Volatility Jump Detection Group
**Volatility Dimensions (2-5, Default: 3)**
Determines the mathematical space complexity:
- **2D:** Price + Volume volatility (suitable for clean markets)
- **3D:** + Range volatility (optimal for most conditions)
- **4D:** + Correlation volatility (advanced multi-asset analysis)
- **5D:** + Microstructure volatility (maximum sensitivity)
**Jump Detection Threshold (1.5-4.0σ, Default: 3.0σ)**
Standard deviations required for volatility jump classification:
- **Cryptocurrency:** 2.0-2.5σ (naturally volatile)
- **Stock Indices:** 2.5-3.0σ (moderate volatility)
- **Forex Major Pairs:** 3.0-3.5σ (typically stable)
- **Commodities:** 2.0-3.0σ (varies by commodity)
**Jump Clustering Decay (0.5-0.99, Default: 0.85)**
Hawkes process memory parameter:
- **0.5-0.7:** Fast decay (jumps treated as independent)
- **0.8-0.9:** Moderate clustering (realistic market behavior)
- **0.95-0.99:** Strong clustering (crisis/event-driven markets)
### Hurst Exponent Analysis Group
**Calculation Method Options:**
- **Classic R/S:** Original Rescaled Range (fast, simple)
- **Adaptive R/S:** Dynamic windowing (recommended for trading)
- **DFA:** Detrended Fluctuation Analysis (best for noisy data)
**Trending Threshold (0.55-0.8, Default: 0.60)**
Hurst value defining persistent market behavior:
- **0.55-0.60:** Weak trend persistence
- **0.65-0.70:** Clear trending behavior
- **0.75-0.80:** Strong momentum regimes
**Mean Reversion Threshold (0.2-0.45, Default: 0.40)**
Hurst value defining anti-persistent behavior:
- **0.35-0.45:** Weak mean reversion
- **0.25-0.35:** Clear ranging behavior
- **0.15-0.25:** Strong reversion tendency
### Transfer Entropy Parameters Group
**Information Flow Analysis:**
- **Price-Volume:** Classic flow analysis for accumulation/distribution
- **Price-Volatility:** Risk flow analysis for sentiment shifts
- **Multi-Timeframe:** Cross-timeframe causality detection
**Maximum Lag (2-20, Default: 5)**
Causality detection window:
- **2-5 bars:** Immediate causality (scalping)
- **5-10 bars:** Short-term flow (day trading)
- **10-20 bars:** Structural flow (swing trading)
**Significance Threshold (0.05-0.3, Default: 0.15)**
Minimum entropy for signal generation:
- **0.05-0.10:** Detect subtle information flows
- **0.10-0.20:** Clear causality only
- **0.20-0.30:** Very strong flows only
---
## 🎨 ADVANCED VISUAL SYSTEM
### Tensor Volatility Field Visualization
**Five-Layer Resonance Bands:**
The tensor field creates dynamic support/resistance zones that expand and contract based on mathematical field strength:
- **Core Layer (Purple):** Primary tensor field with highest intensity
- **Layer 2 (Neutral):** Secondary mathematical resonance
- **Layer 3 (Info Blue):** Tertiary harmonic frequencies
- **Layer 4 (Warning Gold):** Outer field boundaries
- **Layer 5 (Success Green):** Maximum field extension
**Field Strength Calculation:**
```
Field Strength = min(3.0, Mahalanobis Distance × Tensor Intensity)
```
The field amplitude adjusts to ATR and mathematical distance, creating dynamic zones that respond to market volatility.
**Radiation Line Network:**
During active tensor states, the system projects directional radiation lines showing field energy distribution:
- **8 Directional Rays:** Complete angular coverage
- **Tapering Segments:** Progressive transparency for natural visual flow
- **Pulse Effects:** Enhanced visualization during volatility jumps
### Dimensional Portal System
**Portal Mathematics:**
Dimensional portals visualize regime transitions using category theory principles:
- **Green Portals (◉):** Trending regime detection (appear below price for support)
- **Red Portals (◎):** Mean-reverting regime (appear above price for resistance)
- **Yellow Portals (○):** Random walk regime (neutral positioning)
**Tensor Trail Effects:**
Each portal generates 8 trailing particles showing mathematical momentum:
- **Large Particles (●):** Strong mathematical signal
- **Medium Particles (◦):** Moderate signal strength
- **Small Particles (·):** Weak signal continuation
- **Micro Particles (˙):** Signal dissipation
### Information Flow Streams
**Particle Stream Visualization:**
Transfer entropy creates flowing particle streams indicating information direction:
- **Upward Streams:** Volume leading price (accumulation phases)
- **Downward Streams:** Price leading volume (distribution phases)
- **Stream Density:** Proportional to information flow strength
**15-Particle Evolution:**
Each stream contains 15 particles with progressive sizing and transparency, creating natural flow visualization that makes information transfer immediately apparent.
### Fractal Matrix Grid System
**Multi-Timeframe Fractal Levels:**
The system calculates and displays fractal highs/lows across five Fibonacci periods:
- **8-Period:** Short-term fractal structure
- **13-Period:** Intermediate-term patterns
- **21-Period:** Primary swing levels
- **34-Period:** Major structural levels
- **55-Period:** Long-term fractal boundaries
**Triple-Layer Visualization:**
Each fractal level uses three-layer rendering:
- **Shadow Layer:** Widest, darkest foundation (width 5)
- **Glow Layer:** Medium white core line (width 3)
- **Tensor Layer:** Dotted mathematical overlay (width 1)
**Intelligent Labeling System:**
Smart spacing prevents label overlap using ATR-based minimum distances. Labels include:
- **Fractal Period:** Time-based identification
- **Topological Class:** Mathematical complexity rating (0, I, II, III)
- **Price Level:** Exact fractal price
- **Mahalanobis Distance:** Current mathematical field strength
- **Hurst Exponent:** Current regime classification
- **Anomaly Indicators:** Visual strength representations (○ ◐ ● ⚡)
### Wick Pressure Analysis
**Rejection Level Mathematics:**
The system analyzes candle wick patterns to project future pressure zones:
- **Upper Wick Analysis:** Identifies selling pressure and resistance zones
- **Lower Wick Analysis:** Identifies buying pressure and support zones
- **Pressure Projection:** Extends lines forward based on mathematical probability
**Multi-Layer Glow Effects:**
Wick pressure lines use progressive transparency (1-8 layers) creating natural glow effects that make pressure zones immediately visible without cluttering the chart.
### Enhanced Regime Background
**Dynamic Intensity Mapping:**
Background colors reflect mathematical regime strength:
- **Deep Transparency (98% alpha):** Subtle regime indication
- **Pulse Intensity:** Based on regime strength calculation
- **Color Coding:** Green (trending), Red (mean-reverting), Neutral (random)
**Smoothing Integration:**
Regime changes incorporate 10-bar smoothing to prevent background flicker while maintaining responsiveness to genuine regime shifts.
### Color Scheme System
**Six Professional Themes:**
- **Dark (Default):** Professional trading environment optimization
- **Light:** High ambient light conditions
- **Classic:** Traditional technical analysis appearance
- **Neon:** High-contrast visibility for active trading
- **Neutral:** Minimal distraction focus
- **Bright:** Maximum visibility for complex setups
Each theme maintains mathematical accuracy while optimizing visual clarity for different trading environments and personal preferences.
---
## 📊 INSTITUTIONAL-GRADE DASHBOARD
### Tensor Field Status Section
**Field Strength Display:**
Real-time Mahalanobis distance calculation with dynamic emoji indicators:
- **⚡ (Lightning):** Extreme field strength (>1.5× threshold)
- **● (Solid Circle):** Strong field activity (>1.0× threshold)
- **○ (Open Circle):** Normal field state
**Signal Quality Rating:**
Democratic algorithm assessment:
- **ELITE:** All 3 components aligned (highest probability)
- **STRONG:** 2 components aligned (good probability)
- **GOOD:** 1 component active (moderate probability)
- **WEAK:** No clear component signals
**Threshold and Anomaly Monitoring:**
- **Threshold Display:** Current mathematical threshold setting
- **Anomaly Level (0-100%):** Combined volatility and volume spike measurement
- **>70%:** High anomaly (red warning)
- **30-70%:** Moderate anomaly (orange caution)
- **<30%:** Normal conditions (green confirmation)
### Tensor State Analysis Section
**Mathematical State Classification:**
- **↑ BULL (Tensor State +1):** Trending regime with bullish bias
- **↓ BEAR (Tensor State -1):** Mean-reverting regime with bearish bias
- **◈ SUPER (Tensor State 0):** Random walk regime (neutral)
**Visual State Gauge:**
Five-circle progression showing tensor field polarity:
- **🟢🟢🟢⚪⚪:** Strong bullish mathematical alignment
- **⚪⚪🟡⚪⚪:** Neutral/transitional state
- **⚪⚪🔴🔴🔴:** Strong bearish mathematical alignment
**Trend Direction and Phase Analysis:**
- **📈 BULL / 📉 BEAR / ➡️ NEUTRAL:** Primary trend classification
- **🌪️ CHAOS:** Extreme information flow (>2.0 flow strength)
- **⚡ ACTIVE:** Strong information flow (1.0-2.0 flow strength)
- **😴 CALM:** Low information flow (<1.0 flow strength)
### Trading Signals Section
**Real-Time Signal Status:**
- **🟢 ACTIVE / ⚪ INACTIVE:** Long signal availability
- **🔴 ACTIVE / ⚪ INACTIVE:** Short signal availability
- **Components (X/3):** Active algorithmic components
- **Mode Display:** Current signal generation mode
**Signal Strength Visualization:**
Color-coded component count:
- **Green:** 3/3 components (maximum confidence)
- **Aqua:** 2/3 components (good confidence)
- **Orange:** 1/3 components (moderate confidence)
- **Gray:** 0/3 components (no signals)
### Performance Metrics Section
**Win Rate Monitoring:**
Estimated win rates based on signal quality with emoji indicators:
- **🔥 (Fire):** ≥60% estimated win rate
- **👍 (Thumbs Up):** 45-59% estimated win rate
- **⚠️ (Warning):** <45% estimated win rate
**Mathematical Metrics:**
- **Hurst Exponent:** Real-time fractal dimension (0.000-1.000)
- **Information Flow:** Volume/price leading indicators
- **📊 VOL:** Volume leading price (accumulation/distribution)
- **💰 PRICE:** Price leading volume (momentum/speculation)
- **➖ NONE:** Balanced information flow
- **Volatility Classification:**
- **🔥 HIGH:** Above 1.5× jump threshold
- **📊 NORM:** Normal volatility range
- **😴 LOW:** Below 0.5× jump threshold
### Market Structure Section (Large Dashboard)
**Regime Classification:**
- **📈 TREND:** Hurst >0.6, momentum strategies optimal
- **🔄 REVERT:** Hurst <0.4, contrarian strategies optimal
- **🎲 RANDOM:** Hurst ≈0.5, breakout strategies preferred
**Mathematical Field Analysis:**
- **Dimensions:** Current volatility space complexity (2D-5D)
- **Hawkes λ (Lambda):** Self-exciting jump intensity (0.00-1.00)
- **Jump Status:** 🚨 JUMP (active) / ✅ NORM (normal)
### Settings Summary Section (Large Dashboard)
**Active Configuration Display:**
- **Sensitivity:** Current master sensitivity setting
- **Lookback:** Primary analysis window
- **Theme:** Active color scheme
- **Method:** Hurst calculation method (Classic R/S, Adaptive R/S, DFA)
**Dashboard Sizing Options:**
- **Small:** Essential metrics only (mobile/small screens)
- **Normal:** Balanced information density (standard desktop)
- **Large:** Maximum detail (multi-monitor setups)
**Position Options:**
- **Top Right:** Standard placement (avoids price action)
- **Top Left:** Wide chart optimization
- **Bottom Right:** Recent price focus (scalping)
- **Bottom Left:** Maximum price visibility (swing trading)
---
## 🎯 SIGNAL GENERATION LOGIC
### Multi-Component Convergence System
**Component Signal Architecture:**
The TMAE generates signals through sophisticated component analysis rather than simple threshold crossing:
**Volatility Component:**
- **Jump Detection:** Mahalanobis distance threshold breach
- **Hawkes Intensity:** Self-exciting process activation (>0.2)
- **Multi-dimensional:** Considers all volatility dimensions simultaneously
**Hurst Regime Component:**
- **Trending Markets:** Price above SMA-20 with positive momentum
- **Mean-Reverting Markets:** Price at Bollinger Band extremes
- **Random Markets:** Bollinger squeeze breakouts with directional confirmation
**Transfer Entropy Component:**
- **Volume Leadership:** Information flow from volume to price
- **Volume Spike:** Volume 110%+ above 20-period average
- **Flow Significance:** Above entropy threshold with directional bias
### Democratic Signal Weighting
**Signal Mode Implementation:**
- **Aggressive Mode:** Any single component triggers signal
- **Confluence Mode:** Minimum 2 components must agree
- **Conservative Mode:** All 3 components must align
**Momentum Confirmation:**
All signals require momentum confirmation:
- **Long Signals:** RSI >50 AND price >EMA-9
- **Short Signals:** RSI <50 AND price 0.6):**
- **Increase Sensitivity:** Catch momentum continuation
- **Lower Mean Reversion Threshold:** Avoid counter-trend signals
- **Emphasize Volume Leadership:** Institutional accumulation/distribution
- **Tensor Field Focus:** Use expansion for trend continuation
- **Signal Mode:** Aggressive or Confluence for trend following
**Range-Bound Markets (Hurst <0.4):**
- **Decrease Sensitivity:** Avoid false breakouts
- **Lower Trending Threshold:** Quick regime recognition
- **Focus on Price Leadership:** Retail sentiment extremes
- **Fractal Grid Emphasis:** Support/resistance trading
- **Signal Mode:** Conservative for high-probability reversals
**Volatile Markets (High Jump Frequency):**
- **Increase Hawkes Decay:** Recognize event clustering
- **Higher Jump Threshold:** Avoid noise signals
- **Maximum Dimensions:** Capture full volatility complexity
- **Reduce Position Sizing:** Risk management adaptation
- **Enhanced Visuals:** Maximum information for rapid decisions
**Low Volatility Markets (Low Jump Frequency):**
- **Decrease Jump Threshold:** Capture subtle movements
- **Lower Hawkes Decay:** Treat moves as independent
- **Reduce Dimensions:** Simplify analysis
- **Increase Position Sizing:** Capitalize on compressed volatility
- **Minimal Visuals:** Reduce distraction in quiet markets
---
## 🚀 ADVANCED TRADING STRATEGIES
### The Mathematical Convergence Method
**Entry Protocol:**
1. **Fractal Grid Approach:** Monitor price approaching significant fractal levels
2. **Tensor Field Confirmation:** Verify field expansion supporting direction
3. **Portal Signal:** Wait for dimensional portal appearance
4. **ELITE/STRONG Quality:** Only trade highest quality mathematical signals
5. **Component Consensus:** Confirm 2+ components agree in Confluence mode
**Example Implementation:**
- Price approaching 21-period fractal high
- Tensor field expanding upward (bullish mathematical alignment)
- Green portal appears below price (trending regime confirmation)
- ELITE quality signal with 3/3 components active
- Enter long position with stop below fractal level
**Risk Management:**
- **Stop Placement:** Below/above fractal level that generated signal
- **Position Sizing:** Based on Mahalanobis distance (higher distance = smaller size)
- **Profit Targets:** Next fractal level or tensor field resistance
### The Regime Transition Strategy
**Regime Change Detection:**
1. **Monitor Hurst Exponent:** Watch for persistent moves above/below thresholds
2. **Portal Color Change:** Regime transitions show different portal colors
3. **Background Intensity:** Increasing regime background intensity
4. **Mathematical Confirmation:** Wait for regime confirmation (hysteresis)
**Trading Implementation:**
- **Trending Transitions:** Trade momentum breakouts, follow trend
- **Mean Reversion Transitions:** Trade range boundaries, fade extremes
- **Random Transitions:** Trade breakouts with tight stops
**Advanced Techniques:**
- **Multi-Timeframe:** Confirm regime on higher timeframe
- **Early Entry:** Enter on regime transition rather than confirmation
- **Regime Strength:** Larger positions during strong regime signals
### The Information Flow Momentum Strategy
**Flow Detection Protocol:**
1. **Monitor Transfer Entropy:** Watch for significant information flow shifts
2. **Volume Leadership:** Strong edge when volume leads price
3. **Flow Acceleration:** Increasing flow strength indicates momentum
4. **Directional Confirmation:** Ensure flow aligns with intended trade direction
**Entry Signals:**
- **Volume → Price Flow:** Enter during accumulation/distribution phases
- **Price → Volume Flow:** Enter on momentum confirmation breaks
- **Flow Reversal:** Counter-trend entries when flow reverses
**Optimization:**
- **Scalping:** Use immediate flow detection (2-5 bar lag)
- **Swing Trading:** Use structural flow (10-20 bar lag)
- **Multi-Asset:** Compare flow between correlated assets
### The Tensor Field Expansion Strategy
**Field Mathematics:**
The tensor field expansion indicates mathematical pressure building in market structure:
**Expansion Phases:**
1. **Compression:** Field contracts, volatility decreases
2. **Tension Building:** Mathematical pressure accumulates
3. **Expansion:** Field expands rapidly with directional movement
4. **Resolution:** Field stabilizes at new equilibrium
**Trading Applications:**
- **Compression Trading:** Prepare for breakout during field contraction
- **Expansion Following:** Trade direction of field expansion
- **Reversion Trading:** Fade extreme field expansion
- **Multi-Dimensional:** Consider all field layers for confirmation
### The Hawkes Process Event Strategy
**Self-Exciting Jump Trading:**
Understanding that market shocks cluster and create follow-on opportunities:
**Jump Sequence Analysis:**
1. **Initial Jump:** First volatility jump detected
2. **Clustering Phase:** Hawkes intensity remains elevated
3. **Follow-On Opportunities:** Additional jumps more likely
4. **Decay Period:** Intensity gradually decreases
**Implementation:**
- **Jump Confirmation:** Wait for mathematical jump confirmation
- **Direction Assessment:** Use other components for direction
- **Clustering Trades:** Trade subsequent moves during high intensity
- **Decay Exit:** Exit positions as Hawkes intensity decays
### The Fractal Confluence System
**Multi-Timeframe Fractal Analysis:**
Combining fractal levels across different periods for high-probability zones:
**Confluence Zones:**
- **Double Confluence:** 2 fractal levels align
- **Triple Confluence:** 3+ fractal levels cluster
- **Mathematical Confirmation:** Tensor field supports the level
- **Information Flow:** Transfer entropy confirms direction
**Trading Protocol:**
1. **Identify Confluence:** Find 2+ fractal levels within 1 ATR
2. **Mathematical Support:** Verify tensor field alignment
3. **Signal Quality:** Wait for STRONG or ELITE signal
4. **Risk Definition:** Use fractal level for stop placement
5. **Profit Targeting:** Next major fractal confluence zone
---
## ⚠️ COMPREHENSIVE RISK MANAGEMENT
### Mathematical Position Sizing
**Mahalanobis Distance Integration:**
Position size should inversely correlate with mathematical field strength:
```
Position Size = Base Size × (Threshold / Mahalanobis Distance)
```
**Risk Scaling Matrix:**
- **Low Field Strength (<2.0):** Standard position sizing
- **Moderate Field Strength (2.0-3.0):** 75% position sizing
- **High Field Strength (3.0-4.0):** 50% position sizing
- **Extreme Field Strength (>4.0):** 25% position sizing or no trade
### Signal Quality Risk Adjustment
**Quality-Based Position Sizing:**
- **ELITE Signals:** 100% of planned position size
- **STRONG Signals:** 75% of planned position size
- **GOOD Signals:** 50% of planned position size
- **WEAK Signals:** No position or paper trading only
**Component Agreement Scaling:**
- **3/3 Components:** Full position size
- **2/3 Components:** 75% position size
- **1/3 Components:** 50% position size or skip trade
### Regime-Adaptive Risk Management
**Trending Market Risk:**
- **Wider Stops:** Allow for trend continuation
- **Trend Following:** Trade with regime direction
- **Higher Position Size:** Trend probability advantage
- **Momentum Stops:** Trail stops based on momentum indicators
**Mean-Reverting Market Risk:**
- **Tighter Stops:** Quick exits on trend continuation
- **Contrarian Positioning:** Trade against extremes
- **Smaller Position Size:** Higher reversal failure rate
- **Level-Based Stops:** Use fractal levels for stops
**Random Market Risk:**
- **Breakout Focus:** Trade only clear breakouts
- **Tight Initial Stops:** Quick exit if breakout fails
- **Reduced Frequency:** Skip marginal setups
- **Range-Based Targets:** Profit targets at range boundaries
### Volatility-Adaptive Risk Controls
**High Volatility Periods:**
- **Reduced Position Size:** Account for wider price swings
- **Wider Stops:** Avoid noise-based exits
- **Lower Frequency:** Skip marginal setups
- **Faster Exits:** Take profits more quickly
**Low Volatility Periods:**
- **Standard Position Size:** Normal risk parameters
- **Tighter Stops:** Take advantage of compressed ranges
- **Higher Frequency:** Trade more setups
- **Extended Targets:** Allow for compressed volatility expansion
### Multi-Timeframe Risk Alignment
**Higher Timeframe Trend:**
- **With Trend:** Standard or increased position size
- **Against Trend:** Reduced position size or skip
- **Neutral Trend:** Standard position size with tight management
**Risk Hierarchy:**
1. **Primary:** Current timeframe signal quality
2. **Secondary:** Higher timeframe trend alignment
3. **Tertiary:** Mathematical field strength
4. **Quaternary:** Market regime classification
---
## 📚 EDUCATIONAL VALUE AND MATHEMATICAL CONCEPTS
### Advanced Mathematical Concepts
**Tensor Analysis in Markets:**
The TMAE introduces traders to tensor analysis, a branch of mathematics typically reserved for physics and advanced engineering. Tensors provide a framework for understanding multi-dimensional market relationships that scalar and vector analysis cannot capture.
**Information Theory Applications:**
Transfer entropy implementation teaches traders about information flow in markets, a concept from information theory that quantifies directional causality between variables. This provides intuition about market microstructure and participant behavior.
**Fractal Geometry in Trading:**
The Hurst exponent calculation exposes traders to fractal geometry concepts, helping understand that markets exhibit self-similar patterns across multiple timeframes. This mathematical insight transforms how traders view market structure.
**Stochastic Process Theory:**
The Hawkes process implementation introduces concepts from stochastic process theory, specifically self-exciting point processes. This provides mathematical framework for understanding why market events cluster and exhibit memory effects.
### Learning Progressive Complexity
**Beginner Mathematical Concepts:**
- **Volatility Dimensions:** Understanding multi-dimensional analysis
- **Regime Classification:** Learning market personality types
- **Signal Democracy:** Algorithmic consensus building
- **Visual Mathematics:** Interpreting mathematical concepts visually
**Intermediate Mathematical Applications:**
- **Mahalanobis Distance:** Statistical distance in multi-dimensional space
- **Rescaled Range Analysis:** Fractal dimension measurement
- **Information Entropy:** Quantifying uncertainty and causality
- **Field Theory:** Understanding mathematical fields in market context
**Advanced Mathematical Integration:**
- **Tensor Field Dynamics:** Multi-dimensional market force analysis
- **Stochastic Self-Excitation:** Event clustering and memory effects
- **Categorical Composition:** Mathematical signal combination theory
- **Topological Market Analysis:** Understanding market shape and connectivity
### Practical Mathematical Intuition
**Developing Market Mathematics Intuition:**
The TMAE serves as a bridge between abstract mathematical concepts and practical trading applications. Traders develop intuitive understanding of:
- **How markets exhibit mathematical structure beneath apparent randomness**
- **Why multi-dimensional analysis reveals patterns invisible to single-variable approaches**
- **How information flows through markets in measurable, predictable ways**
- **Why mathematical models provide probabilistic edges rather than certainties**
---
## 🔬 IMPLEMENTATION AND OPTIMIZATION
### Getting Started Protocol
**Phase 1: Observation (Week 1)**
1. **Apply with defaults:** Use standard settings on your primary trading timeframe
2. **Study visual elements:** Learn to interpret tensor fields, portals, and streams
3. **Monitor dashboard:** Observe how metrics change with market conditions
4. **No trading:** Focus entirely on pattern recognition and understanding
**Phase 2: Pattern Recognition (Week 2-3)**
1. **Identify signal patterns:** Note what market conditions produce different signal qualities
2. **Regime correlation:** Observe how Hurst regimes affect signal performance
3. **Visual confirmation:** Learn to read tensor field expansion and portal signals
4. **Component analysis:** Understand which components drive signals in different markets
**Phase 3: Parameter Optimization (Week 4-5)**
1. **Asset-specific tuning:** Adjust parameters for your specific trading instrument
2. **Timeframe optimization:** Fine-tune for your preferred trading timeframe
3. **Sensitivity adjustment:** Balance signal frequency with quality
4. **Visual customization:** Optimize colors and intensity for your trading environment
**Phase 4: Live Implementation (Week 6+)**
1. **Paper trading:** Test signals with hypothetical trades
2. **Small position sizing:** Begin with minimal risk during learning phase
3. **Performance tracking:** Monitor actual vs. expected signal performance
4. **Continuous optimization:** Refine settings based on real performance data
### Performance Monitoring System
**Signal Quality Tracking:**
- **ELITE Signal Win Rate:** Track highest quality signals separately
- **Component Performance:** Monitor which components provide best signals
- **Regime Performance:** Analyze performance across different market regimes
- **Timeframe Analysis:** Compare performance across different session times
**Mathematical Metric Correlation:**
- **Field Strength vs. Performance:** Higher field strength should correlate with better performance
- **Component Agreement vs. Win Rate:** More component agreement should improve win rates
- **Regime Alignment vs. Success:** Trading with mathematical regime should outperform
### Continuous Optimization Process
**Monthly Review Protocol:**
1. **Performance Analysis:** Review win rates, profit factors, and maximum drawdown
2. **Parameter Assessment:** Evaluate if current settings remain optimal
3. **Market Adaptation:** Adjust for changes in market character or volatility
4. **Component Weighting:** Consider if certain components should receive more/less emphasis
**Quarterly Deep Analysis:**
1. **Mathematical Model Validation:** Verify that mathematical relationships remain valid
2. **Regime Distribution:** Analyze time spent in different market regimes
3. **Signal Evolution:** Track how signal characteristics change over time
4. **Correlation Analysis:** Monitor correlations between different mathematical components
---
## 🌟 UNIQUE INNOVATIONS AND CONTRIBUTIONS
### Revolutionary Mathematical Integration
**First-Ever Implementations:**
1. **Multi-Dimensional Volatility Tensor:** First indicator to implement true tensor analysis for market volatility
2. **Real-Time Hawkes Process:** First trading implementation of self-exciting point processes
3. **Transfer Entropy Trading Signals:** First practical application of information theory for trade generation
4. **Democratic Component Voting:** First algorithmic consensus system for signal generation
5. **Fractal-Projected Signal Quality:** First system to predict signal quality at future price levels
### Advanced Visualization Innovations
**Mathematical Visualization Breakthroughs:**
- **Tensor Field Radiation:** Visual representation of mathematical field energy
- **Dimensional Portal System:** Category theory visualization for regime transitions
- **Information Flow Streams:** Real-time visual display of market information transfer
- **Multi-Layer Fractal Grid:** Intelligent spacing and projection system
- **Regime Intensity Mapping:** Dynamic background showing mathematical regime strength
### Practical Trading Innovations
**Trading System Advances:**
- **Quality-Weighted Signal Generation:** Signals rated by mathematical confidence
- **Regime-Adaptive Strategy Selection:** Automatic strategy optimization based on market personality
- **Anti-Spam Signal Protection:** Mathematical prevention of signal clustering
- **Component Performance Tracking:** Real-time monitoring of algorithmic component success
- **Field-Strength Position Sizing:** Mathematical volatility integration for risk management
---
## ⚖️ RESPONSIBLE USAGE AND LIMITATIONS
### Mathematical Model Limitations
**Understanding Model Boundaries:**
While the TMAE implements sophisticated mathematical concepts, traders must understand fundamental limitations:
- **Markets Are Not Purely Mathematical:** Human psychology, news events, and fundamental factors create unpredictable elements
- **Past Performance Limitations:** Mathematical relationships that worked historically may not persist indefinitely
- **Model Risk:** Complex models can fail during unprecedented market conditions
- **Overfitting Potential:** Highly optimized parameters may not generalize to future market conditions
### Proper Implementation Guidelines
**Risk Management Requirements:**
- **Never Risk More Than 2% Per Trade:** Regardless of signal quality
- **Diversification Mandatory:** Don't rely solely on mathematical signals
- **Position Sizing Discipline:** Use mathematical field strength for sizing, not confidence
- **Stop Loss Non-Negotiable:** Every trade must have predefined risk parameters
**Realistic Expectations:**
- **Mathematical Edge, Not Certainty:** The indicator provides probabilistic advantages, not guaranteed outcomes
- **Learning Curve Required:** Complex mathematical concepts require time to master
- **Market Adaptation Necessary:** Parameters must evolve with changing market conditions
- **Continuous Education Important:** Understanding underlying mathematics improves application
### Ethical Trading Considerations
**Market Impact Awareness:**
- **Information Asymmetry:** Advanced mathematical analysis may provide advantages over other market participants
- **Position Size Responsibility:** Large positions based on mathematical signals can impact market structure
- **Sharing Knowledge:** Consider educational contributions to trading community
- **Fair Market Participation:** Use mathematical advantages responsibly within market framework
### Professional Development Path
**Skill Development Sequence:**
1. **Basic Mathematical Literacy:** Understand fundamental concepts before advanced application
2. **Risk Management Mastery:** Develop disciplined risk control before relying on complex signals
3. **Market Psychology Understanding:** Combine mathematical analysis with behavioral market insights
4. **Continuous Learning:** Stay updated on mathematical finance developments and market evolution
---
## 🔮 CONCLUSION
The Tensor Market Analysis Engine represents a quantum leap forward in technical analysis, successfully bridging the gap between advanced pure mathematics and practical trading applications. By integrating multi-dimensional volatility analysis, fractal market theory, and information flow dynamics, the TMAE reveals market structure invisible to conventional analysis while maintaining visual clarity and practical usability.
### Mathematical Innovation Legacy
This indicator establishes new paradigms in technical analysis:
- **Tensor analysis for market volatility understanding**
- **Stochastic self-excitation for event clustering prediction**
- **Information theory for causality-based trade generation**
- **Democratic algorithmic consensus for signal quality enhancement**
- **Mathematical field visualization for intuitive market understanding**
### Practical Trading Revolution
Beyond mathematical innovation, the TMAE transforms practical trading:
- **Quality-rated signals replace binary buy/sell decisions**
- **Regime-adaptive strategies automatically optimize for market personality**
- **Multi-dimensional risk management integrates mathematical volatility measures**
- **Visual mathematical concepts make complex analysis immediately interpretable**
- **Educational value creates lasting improvement in trading understanding**
### Future-Proof Design
The mathematical foundations ensure lasting relevance:
- **Universal mathematical principles transcend market evolution**
- **Multi-dimensional analysis adapts to new market structures**
- **Regime detection automatically adjusts to changing market personalities**
- **Component democracy allows for future algorithmic additions**
- **Mathematical visualization scales with increasing market complexity**
### Commitment to Excellence
The TMAE represents more than an indicator—it embodies a philosophy of bringing rigorous mathematical analysis to trading while maintaining practical utility and visual elegance. Every component, from the multi-dimensional tensor fields to the democratic signal generation, reflects a commitment to mathematical accuracy, trading practicality, and educational value.
### Trading with Mathematical Precision
In an era where markets grow increasingly complex and computational, the TMAE provides traders with mathematical tools previously available only to institutional quantitative research teams. Yet unlike academic mathematical models, the TMAE translates complex concepts into intuitive visual representations and practical trading signals.
By combining the mathematical rigor of tensor analysis, the statistical power of multi-dimensional volatility modeling, and the information-theoretic insights of transfer entropy, traders gain unprecedented insight into market structure and dynamics.
### Final Perspective
Markets, like nature, exhibit profound mathematical beauty beneath apparent chaos. The Tensor Market Analysis Engine serves as a mathematical lens that reveals this hidden order, transforming how traders perceive and interact with market structure.
Through mathematical precision, visual elegance, and practical utility, the TMAE empowers traders to see beyond the noise and trade with the confidence that comes from understanding the mathematical principles governing market behavior.
Trade with mathematical insight. Trade with the power of tensors. Trade with the TMAE.
*"In mathematics, you don't understand things. You just get used to them." - John von Neumann*
*With the TMAE, mathematical market understanding becomes not just possible, but intuitive.*
— Dskyz, Trade with insight. Trade with anticipation.
Institutional Volume Profile# Institutional Volume Profile (IVP) - Advanced Volume Analysis Indicator
## Overview
The Institutional Volume Profile (IVP) is a sophisticated technical analysis tool that combines traditional volume profile analysis with institutional volume detection algorithms. This indicator helps traders identify key price levels where significant institutional activity has occurred, providing insights into market structure and potential support/resistance zones.
## Key Features
### 🎯 Volume Profile Analysis
- **Point of Control (POC)**: Identifies the price level with the highest volume activity
- **Value Area**: Highlights the price range containing a specified percentage (default 70%) of total volume
- **Multi-Row Distribution**: Displays volume distribution across 10-50 price levels for detailed analysis
- **Customizable Period**: Analyze volume profiles over 10-500 bars
### 🏛️ Institutional Volume Detection
- **Pocket Pivot Volume (PPV)**: Detects bullish institutional buying when up-volume exceeds recent down-volume peaks
- **Pivot Negative Volume (PNV)**: Identifies bearish institutional selling when down-volume exceeds recent up-volume peaks
- **Accumulation Detection**: Spots potential accumulation phases with high volume and narrow price ranges
- **Distribution Analysis**: Identifies distribution patterns with high volume but minimal price movement
### 🎨 Visual Customization Options
- **Multiple Color Schemes**: Heat Map, Institutional, Monochrome, and Rainbow themes
- **Bar Styles**: Solid, Gradient, Outlined, and 3D Effect rendering
- **Volume Intensity Display**: Visual intensity based on volume magnitude
- **Flexible Positioning**: Left or right side profile placement
- **Current Price Highlighting**: Real-time price level indication
### 📊 Advanced Visual Features
- **Volume Labels**: Display volume amounts at key price levels
- **Gradient Effects**: Multi-step gradient rendering for enhanced visibility
- **3D Styling**: Shadow effects for professional appearance
- **Opacity Control**: Adjustable transparency (10-100%)
- **Border Customization**: Configurable border width and styling
## How It Works
### Volume Distribution Algorithm
The indicator analyzes each bar within the specified period and distributes its volume proportionally across the price levels it touches. This creates an accurate representation of where trading activity has been concentrated.
### Institutional Detection Logic
- **PPV Trigger**: Current up-bar volume > highest down-volume in lookback period + above volume MA
- **PNV Trigger**: Current down-bar volume > highest up-volume in lookback period + above volume MA
- **Accumulation**: High volume + narrow range + bullish close
- **Distribution**: Very high volume + minimal price movement
### Value Area Calculation
Starting from the POC, the algorithm expands both upward and downward, adding volume until reaching the specified percentage of total volume (default 70%).
## Configuration Parameters
### Profile Settings
- **Profile Period**: 10-500 bars (default: 50)
- **Number of Rows**: 10-50 levels (default: 24)
- **Profile Width**: 10-100% of screen (default: 30%)
- **Value Area %**: 50-90% (default: 70%)
### Institutional Analysis
- **PPV Lookback Days**: 5-20 periods (default: 10)
- **Volume MA Length**: 10-200 periods (default: 50)
- **Institutional Threshold**: 1.0-2.0x multiplier (default: 1.2)
### Visual Controls
- **Bar Style**: Solid, Gradient, Outlined, 3D Effect
- **Color Scheme**: Heat Map, Institutional, Monochrome, Rainbow
- **Profile Position**: Left or Right side
- **Opacity**: 10-100%
- **Show Labels**: Volume amount display toggle
## Interpretation Guide
### Volume Profile Elements
- **Thick Horizontal Bars**: High volume nodes (strong support/resistance)
- **Thin Horizontal Bars**: Low volume nodes (weak levels)
- **White Line (POC)**: Strongest support/resistance level
- **Blue Highlighted Area**: Value Area (fair value zone)
### Institutional Signals
- **Blue Triangles (PPV)**: Bullish institutional buying detected
- **Orange Triangles (PNV)**: Bearish institutional selling detected
- **Color-Coded Bars**: Different colors indicate institutional activity types
### Color Scheme Meanings
- **Heat Map**: Red (high volume) → Orange → Yellow → Gray (low volume)
- **Institutional**: Blue (PPV), Orange (PNV), Aqua (Accumulation), Yellow (Distribution)
- **Monochrome**: Grayscale intensity based on volume
- **Rainbow**: Color-coded by price level position
## Trading Applications
### Support and Resistance
- POC acts as dynamic support/resistance
- High volume nodes indicate strong price levels
- Low volume areas suggest potential breakout zones
### Institutional Activity
- PPV above Value Area: Strong bullish signal
- PNV below Value Area: Strong bearish signal
- Accumulation patterns: Potential upward breakouts
- Distribution patterns: Potential downward pressure
### Market Structure Analysis
- Value Area defines fair value range
- Profile shape indicates market sentiment
- Volume gaps suggest potential price targets
## Alert Conditions
- PPV Detection at current price level
- PNV Detection at current price level
- PPV above Value Area (strong bullish)
- PNV below Value Area (strong bearish)
## Best Practices
1. Use multiple timeframes for confirmation
2. Combine with price action analysis
3. Pay attention to volume context (above/below average)
4. Monitor institutional signals near key levels
5. Consider overall market conditions
## Technical Notes
- Maximum 500 boxes and 100 labels for optimal performance
- Real-time calculations update on each bar close
- Historical analysis uses complete bar data
- Compatible with all TradingView chart types and timeframes
---
*This indicator is designed for educational and informational purposes. Always combine with other analysis methods and risk management strategies.*
Smart Money Concept [TradingFinder] Major OB + FVG + Liquidity🔵 Introduction
"Smart Money" refers to funds under the control of institutional investors, central banks, funds, market makers, and other financial entities. Ordinary people recognize investments made by those who have a deep understanding of market performance and possess information typically inaccessible to regular investors as "Smart Money".
Consequently, when market movements often diverge from expectations, traders identify the footprints of smart money. For example, when a classic pattern forms in the market, traders take short positions. However, the market might move upward instead. They attribute this contradiction to smart money and seek to capitalize on such inconsistencies in their trades.
The "Smart Money Concept" (SMC) is one of the primary styles of technical analysis that falls under the subset of "Price Action". Price action encompasses various subcategories, with one of the most significant being "Supply and Demand", in which SMC is categorized.
The SMC method aims to identify trading opportunities by emphasizing the impact of large traders (Smart Money) on the market, offering specific patterns, techniques, and trading strategies.
🟣 Key Terms of Smart Money Concept (SMC)
• Market Structure (Trend)
• Change of Character (ChoCh)
• Break of Structure (BoS)
• Order Blocks (Supply and Demand)
• Imbalance (IMB)
• Inefficiency (IFC)
• Fair Value Gap (FVG)
• Liquidity
• Premium and Discount
🔵 How Does the "Smart Money Concept Indicator" Work?
🟣 Market Structure
a. Accumulation
b. Market-Up
c. Distribution
d. Market-Down
a) Accumulation Phase : During the accumulation period, typically following a downtrend, smart money enters the market without significantly affecting the pricing trend.
b) Market-Up Phase : In this phase, the price of an asset moves upward from the accumulation range and begins to rise. Usually, the buying by retail investors is the main driver of this trend, and due to positive market sentiment, it continues.
c) Distribution Phase : The distribution phase, unlike the accumulation stage, occurs after an uptrend. In this phase, smart money attempts to exit the market without causing significant price fluctuations.
d) Market-Down Phase : In this stage, the price of an asset moves downward from the distribution phase, initiating a prolonged downtrend. Smart money liquidates all its positions by creating selling pressure, trapping latecomer investors.
The result of these four phases in the market becomes the market trend.
Types of Trends in Financial Markets :
a. Up-Trend
b. Down Trend
c. Range (No Trend)
a) Up-Trend : The market breaks consecutive highs.
b) Down Trend : The market breaks consecutive lows.
c) No Trend or Range : The market oscillates within a range without breaking either highs or lows.
🟣 Change of Character (ChoCh)
The "ChoCh" or "Change of Character" pattern indicates an initial change in order flow in financial markets. This structural change occurs when a major pivot in the opposite direction of the market trend fails. It signals a potential change in the market trend and can serve as a signal for short-term or long-term trend changes in a trading symbol.
🟣 Break of Structure (BoS)
The "BoS" or "Break of Structure" pattern indicates the continuation of the trend in financial markets. This structure forms when, in an uptrend, the price breaks its ceiling or, in a downtrend, the price breaks its floor.
🟣 Order Blocks (Supply and Demand)
Order blocks consist of supply and demand areas where the likelihood of price reversal is higher. There are six order blocks in this indicator, categorized based on their origin and formation reasons.
a. Demand Main Zone, "ChoCh" Origin.
b. Demand Sub Zone, "ChoCh" Origin.
c. Demand All Zone, "BoS" Origin.
d. Supply Main Zone, "ChoCh" Origin.
e. Supply Sub Zone, "ChoCh" Origin.
f. Supply All Zone, "BoS" Origin.
🟣 FVG | Inefficiency | Imbalance
These three terms are almost synonymous. They describe the presence of gaps between consecutive candle shadows. This inefficiency occurs when the market moves rapidly. Primarily, imbalances and these rapid movements stem from the entry of smart money and the imbalance between buyer and seller power. Therefore, identifying these movements is crucial for traders.
These areas are significant because prices often return to fill these gaps or even before they occur to fill price gaps.
🟣 Liquidity
Liquidity zones are areas where there is a likelihood of congestion of stop-loss orders. Liquidity is considered the driving force of the entire market, and market makers may manipulate the market using these zones. However, in many cases, this does not happen because there is insufficient liquidity in some areas.
Types of Liquidity in Financial Markets :
a. Trend Lines
b. Double Tops | Double Bottoms
c. Triple Tops | Triple Bottoms
d. Support Lines | Resistance Lines
All four types of liquidity in this indicator are automatically identified.
🟣 Premium and Discount
Premium and discount zones can assist traders in making better decisions. For instance, they may sell positions in expensive ranges and buy in cheaper ranges. The closer the price is to the major resistance, the more expensive it is, and the closer it is to the major support, the cheaper it is.
🔵 How to Use
🟣 Change of Character (ChoCh) and Break of Structure (BoS)
This indicator detects "ChoCh" and "BoS" in both Minor and Major states. You can turn on the display of these lines by referring to the last part of the settings.
🟣 Order Blocks (Supply and Demand)
Order blocks are Zones where the probability of price reversal is higher. In demand Zones you can buy opportunities and in supply Zones you can check sell opportunities.
The "Refinement" feature allows you to adjust the width of the order block according to your strategy. There are two modes, "Aggressive" and "Defensive," in the "Order Block Refine". The difference between "Aggressive" and "Defensive" lies in the width of the order block.
For risk-averse traders, the "Defensive" mode is suitable as it provides a lower loss limit and a greater reward-to-risk ratio. For risk-taking traders, the "Aggressive" mode is more appropriate. These traders prefer to enter trades at higher prices, and this mode, which has a wider order block width, is more suitable for this group of individuals.
🟣 Fair Value Gap (FVG) | Imbalance (IMB) | Inefficiency (IFC)
In order to identify the "fair value gap" on the chart, it must be analyzed candle by candle. In this process, it is important to pay attention to candles with a large size, and a candle and a candle should be examined before that.
Candles before and after this central candle should have long shadows and their bodies should not overlap with the central candle body. The distance between the shadows of the first and third candles is known as the FVG range.
These areas work in two ways :
• Supply and demand area : In this case, the price reacts to these areas and the trend is reversed.
• Liquidity zone : In this scenario, the price "fills" the zone and then reaches the order block.
Important note : In most cases, the FVG zone of very small width acts as a supply and demand zone, while the zone of significant width acts as a liquidity zone and absorbs price.
When the FVG filter is activated, the FVG regions are filtered based on the specified algorithm.
FVG filter types include the following :
1. Very Aggressive Mode : In addition to the initial condition, an additional condition is considered. For bullish FVG, the maximum price of the last candle must be greater than the maximum price of the middle candle.
Similarly, for a bearish FVG, the minimum price of the last candle must be lower than the minimum price of the middle candle. This mode removes the minimum number of FVGs.
2. Aggressive : In addition to the very aggressive condition, the size of the middle candle is also considered. The size of the center candle should not be small and therefore more FVGs are removed in this case.
3. Defensive : In addition to the conditions of the very aggressive mode, this mode also considers the size of the middle pile, which should be relatively large and make up the majority of the body.
Also, to identify bullish FVGs, the second and third candles must be positive, while for bearish FVGs, the second and third candles must be negative. This mode filters out a significant number of FVGs and keeps only those of good quality.
4. Very Defensive : In addition to the conditions of the defensive mode, in this mode the first and third candles should not be very small-bodied doji candles. This mode filters out most FVGs and only the best quality ones remain.
🟣 Liquidity
These levels are where traders intend to exit their trades. "Market makers" or smart money usually accumulate or distribute their trading positions near these levels, where many retail traders have placed their "stop loss" orders. When liquidity is collected from these losses, the price often reverses.
A "Stop hunt" is a move designed to offset liquidity generated by established stop losses. Banks often use major news events to trigger stop hunts and capture liquidity released into the market. For example, if they intend to execute heavy buy orders, they encourage others to sell through stop-hots.
Consequently, if there is liquidity in the market before reaching the order block area, the validity of that order block is higher. Conversely, if the liquidity is close to the order block, that is, the price reaches the order block before reaching the liquidity limit, the validity of that order block is lower.
🟣 Alert
With the new alert functionality in this indicator, you won't miss any important trading signals. Alerts are activated when the price hits the last order block.
1. It is possible to set alerts for each "symbol" and "time frame". The system will automatically detect both and include them in the warning message.
2. Each alert provides the exact date and time it was triggered. This helps you measure the timeliness of the signal and evaluate its relevance.
3. Alerts include target order block price ranges. The "Proximal" level represents the initial price level strike, while the "Distal" level represents the maximum price gap in the block. These details are included in the warning message.
4. You can customize the alert name through the "Alert Name" entry.
5. Create custom messages for "long" and "short" alerts to be sent with notifications.
🔵 Setting
a. Pivot Period of Order Blocks Detector :
Using this parameter, you can set the zigzag period that is formed based on the pivots.
b. Order Blocks Validity Period (Bar) :
You can set the validity period of each Order Block based on the number of candles that have passed since the origin of the Order Block.
c. Demand Main Zone, "ChoCh" Origin :
You can control the display or not display as well as the color of Demand Main Zone, "ChoCh" Origin.
d. Demand Sub Zone, "ChoCh" Origin :
You can control the display or not display as well as the color of Demand Sub Zone, "ChoCh" Origin.
e. Demand All Zone, "BoS" Origin :
You can control the display or not display as well as the color of Demand All Zone, "BoS" Origin.
f. Supply Main Zone, "ChoCh" Origin :
You can control the display or not display as well as the color of Supply Main Zone, "ChoCh" Origin.
g. Supply Sub Zone, "ChoCh" Origin :
You can control the display or not display as well as the color of Supply Sub Zone, "ChoCh" Origin.
h. Supply All Zone, "BoS" Origin :
You can control the display or not display as well as the color of Supply All Zone, "BoS" Origin.
i. Refine Demand Main : You can choose to be refined or not and also the type of refining.
j. Refine Demand Sub : You can choose to be refined or not and also the type of refining.
k. Refine Demand BoS : You can choose to be refined or not and also the type of refining.
l. Refine Supply Main : You can choose to be refined or not and also the type of refining.
m. Refine Supply Sub : You can choose to be refined or not and also the type of refining.
n. Refine Supply BoS : You can choose to be refined or not and also the type of refining.
o. Show Demand FVG : You can choose to show or not show Demand FVG.
p. Show Supply FVG : You can choose to show or not show Supply FVG
q. FVG Filter : You can choose whether FVG is filtered or not. Also specify the type of filter you want to use.
r. Show Statics High Liquidity Line : Show or not show Statics High Liquidity Line.
s. Show Statics Low Liquidity Line : Show or not show Statics Low Liquidity Line.
t. Show Dynamics High Liquidity Line : Show or not show Dynamics High Liquidity Line.
u. Show Dynamics Low Liquidity Line : Show or not show Dynamics Low Liquidity Line.
v. Statics Period Pivot :
Using this parameter, you can set the Swing period that is formed based on Static Liquidity Lines.
w. Dynamics Period Pivot :
Using this parameter, you can set the Swing period that is formed based Dynamics Liquidity Lines.
x. Statics Liquidity Line Sensitivity :
is a number between 0 and 0.4. Increasing this number decreases the sensitivity of the "Statics Liquidity Line Detection" function and increases the number of lines identified. The default value is 0.3.
y. Dynamics Liquidity Line Sensitivity :
is a number between 0.4 and 1.95. Increasing this number increases the sensitivity of the "Dynamics Liquidity Line Detection" function and decreases the number of lines identified. The default value is 1.
z. Alerts Name : You can customize the alert name using this input and set it to your desired name.
aa. Alert Demand Main Mitigation :
If you want to receive the alert about Demand Main 's mitigation after setting the alerts, leave this tick on. Otherwise, turn it off.
bb. Alert Demand Sub Mitigation :
If you want to receive the alert about Demand Sub's mitigation after setting the alerts, leave this tick on. Otherwise, turn it off.
cc. Alert Demand BoS Mitigation :
If you want to receive the alert about Demand BoS's mitigation after setting the alerts, leave this tick on. Otherwise, turn it off.
dd. Alert Supply Main Mitigation :
If you want to receive the alert about Supply Main's mitigation after setting the alerts, leave this tick on. Otherwise, turn it off.
ee. Alert Supply Sub Mitigation :
If you want to receive the alert about Supply Sub's mitigation after setting the alerts, leave this tick on. Otherwise, turn it off.
ff. Alert Supply BoS Mitigation :
If you want to receive the alert about Supply BoS's mitigation after setting the alerts, leave this tick on. Otherwise, turn it off.
gg. Message Frequency :
This parameter, represented as a string, determines the frequency of announcements. Options include: 'All' (triggers the alert every time the function is called), 'Once Per Bar' (triggers the alert only on the first call within the bar), and 'Once Per Bar Close' (activates the alert only during the final script execution of the real-time bar upon closure). The default setting is 'Once per Bar'.
hh. Show Alert time by Time Zone :
The date, hour, and minute displayed in alert messages can be configured to reflect any chosen time zone. For instance, if you prefer London time, you should input 'UTC+1'. By default, this input is configured to the 'UTC' time zone.
ii. Display More Info : The 'Display More Info' option provides details regarding the price range of the order blocks (Zone Price), along with the date, hour, and minute. If you prefer not to include this information in the alert message, you should set it to 'Off'.
You also have access to display or not to display, choose the Style and Color of all the lines below :
a. Major Bullish "BoS" Lines
b. Major Bearish "BoS" Lines
c. Minor Bullish "BoS" Lines
d. Minor Bearish "BoS" Lines
e. Major Bullish "ChoCh" Lines
f. Major Bearish "ChoCh" Lines
g. Minor Bullish "ChoCh" Lines
h. Minor Bearish "ChoCh" Lines
i. Last Major Support Line
j. Last Major Resistance Line
k. Last Minor Support Line
l. Last Minor Resistance Line
Up Down Volume Ratio by 3iauThis script considers the total volume within a user specified time frame, and whether price closed higher or lower at the end of each period within that time frame.
EXAMPLE:
* If the time period of interest is 50-periods, the script considers the volume within each of those 50 periods beginning with the most recent closed period.
* SumUpVol = the sum of all volume occurring within only those periods where price closed higher than that of the previous period.
* SumDnVol = the sum of all volume occurring within only those periods where price closed lower than that of the previous period.
* Difference = the difference between SumUpVol and SumDnVol = SumUpVol - SumDnVol
* Total = the sum of SumUpVol and SumDnVol = SumUpVol + SumDnVol
* The plot will present the change in Difference divided by Total = Difference/Total = (SumUpVol - SumDnVol)/(SumUpVol + SumDnVol) occurring within those 50 periods. What will be plotted is the moving average of this value. The user can specify the moving average type and the number of period for which the average is calculated.
* The plot needs to be fitted into a range, for example, +/- 50 (default) or +/-100, by multiplying the result of Difference/Total by a user specified constant. The constant will contain the majority (not all) of the values within +/- the specified value.
* Range = the user specified constant. If Range = 50, the majority of values plotted will be fall within the range +/- 50.
* Therefore, what is plotted is the moving average of Range * Difference / Total.
* When the value = 0, accumulation = distribution over the user specified 50-periods time frame.
* When the value is positive, accumulation > distribution over the user specified 50-periods time frame.
* When the value is negative, distribution > accumulation over the user specified 50-periods time frame.
This plot allows one to see possible accumulation and distribution occurring within a particular stock. The slope of this plot must be considered, and not any single value. The selected constant (“Range” in the example above) does not have an effect on the slope of the plot.
Three values may be plotted at once, for comparison of accumulation or distribution occurring over different time frames. For example, compare Difference / Total calculated over a 50-periods timeframe with 10-periods timeframe, both time frames beginning with the most recent closed period.
In addition to the above, J. Welles Wilder’s Relative Strength Index (RSI) can be plotted over the Difference / Total.
NOTE: this script is not the same as the more commonly used Up/Down Volume Ratio defined as SumUpVol / SumDnVol over a 50-periods time frame, where SumUpVol = the sum of all volume occurring within only those periods where price closed higher than that of the previous period, and SumDnVol = the sum of all volume occurring within only those periods where price closed lower than that of the previous period.
Compare...
Up Down Volume Ratio = SumUpVol / SumDnVol
Up Down Volume Ratio by 3iau = the moving average of Range * (SumUpVol - SumDnVol) / (SumUpVol + SumDnVol)
TARVIS Labs - Bitcoin Macro Bottom/Top SignalsSCRIPT DESCRIPTION
This is a script specifically written to help provide indicators from a macro view. This script is best run on the 1 day interval on Bitstamp's $BTCUSD chart. It helps indicate when to accumulate bitcoin, and when its in a bull run when there are local tops, strong top warnings, and a signal to exit a bull run. This is described further below.
If you don't have interest in trading on the way to the top I suggest turning off the following indicators in the settings of the indicator:
- Opportunity To Buy Back In Indicator
- Local Top Near Bull Run Top Indicator
ACCUMULATION ZONE INDICATOR - LIGHT GREEN
Description
When we look at the history of Bitcoin every bottom has crossed below the 100 week EMA. Once it does its accompanied by hash ribbon cross with miner capitulation. After that is the prime time to accumulate as theres a clearer signal the bottom is in. Specifically, a signal to look for is the 14 day MACD/signal cross and the 14 day MACD continuing to stay above the signal until the price returns above the 100 week EMA. This is prime accumulation territory.
Strategy for Usage
A good strategy to use when accumulating the bottom is dollar-cost averaging over a 30 day period. The accumulation zone can last longer than 30 days but 30 days is a good range of time to DCA.
STRONG BUY IN ACCUMULATION ZONE INDICATOR - DARK GREEN
Description
We can add to the bottoming signal by looking for post-downtrend reversals inside the bottoming signal. We do this by using a 9/19 daily cross.
Strategy for Usage
These post-downtrend reversals can potentially provide better targeted days for accumulation than the broader bottoming signal and can be used to add more on that day than on an average day for the dollar cost average strategy. Say for example, use 1/3 of funds on these days rather than 1/30th.
OPPORTUNITY TO BUY BACK IN INDICATOR - BLUE
Description
When the 1d 18 EMA > 1d 63 EMA and the 12/52 1d crosses. These together provide good buy opportunities to buy bitcoin.
Strategy for Usage
If you happen to find yourself out of the market from your own TA or a trade, this signal can provide a buy opportunity to reenter the market if you're out of it.
BULL RUN LOCAL TOP INDICATOR - ORANGE
Description
We will similarly use the 100 week EMA to determine trend reversal into a bull run. When we see the 100 week EMA uptrending, we can begin to look for local tops using the 9/19 daily MACD/signal bearish cross along with the 12 EMA having a negative slope, which could be the beginning signal for a local top.
Strategy for Usage
This is a rather light indicator, but can be used in tandem with your own technical analysis to determine if you want to reenter after you exit from its signal.
LOCAL TOP NEAR BULL RUN TOP INDICATOR - RED
Description
When the 100 week EMA is in an uptrend we can look for significant loss of momentum in order to determine if a local top is in near a bull run top. Similar to the Bull Run Local Top Indicator, this strategy uses a MACD/signal cross but instead uses the 30/65 day EMAs.
Strategy for Usage
Ideally the right strategy to use here is to exit the market when this indicator starts. When the indicator ends if the "End of Bull Run Indicator" is not showing on the chart you can buy back into the market.
TOP IS LIKELY IN INDICATOR
Description
When the 100 week EMA is in a very strong uptrend and the 9/19 weekly MACD/signal bearish cross occurs, and the 63 EMA begins to downtrend.
Strategy for Usage
This signal typically accompanies the "Local Top Near Bull Run Top Indicator" therefore if you're following the strategy you would likely already be out of the market, but if you're not and this signal fires its a strong signal the top is in and we're likely going to start seeing a strong retrace. This is typically right before we see the "End of Bull Run Indicator". There is only one occurrence where it wasn't followed by a large drop & the "End of Bull Run Indicator" and that was in the 2017 bull run where there were many strong retracements post local top. The likelihood we see that again is low, but if it were to happen you can buy back into the market when the "Top is Likely In Indicator" and the "Local Top Near Bull Run Top Indicator" are not firing.
TOP IS LIKELY IN INDICATOR
Description
When the 100 week EMA is in a strong uptrend and the 9/19 weekly MACD/signal bearish cross occurs, and the 63 EMA begins to downtrend.
Strategy for Usage
This signal typically accompanies the "Local Top Near Bull Run Top Indicator" therefore if you're following the strategy you would likely already be out of the market, but if you're not and this signal fires its a strong signal the top is in and we're likely going to start seeing a strong retrace. This is typically right before we see the "End of Bull Run Indicator". There is only one occurrence where it wasn't followed by a large drop & the "End of Bull Run Indicator" and that was in the 2017 bull run where there were many strong retracements post local top. The likelihood we see that again is low, but if it were to happen you can buy back into the market when the "Top is Likely In Indicator" and the "Local Top Near Bull Run Top Indicator" are not firing.
END OF BULL RUN INDICATOR
Description
When the 100 week EMA is in an uptrend and the 1d 18 EMA crosses the 1d 63 EMA.
Strategy for Usage
When the 100 week EMA is a strong uptrend and the 18/63 cross occurs the top is very likely in. It has occurred in every bull run top leading to the bear market.
PA-Adaptive, Stepped-MA of Composite RSI [Loxx]PA-Adaptive, Stepped-MA of Composite RSI is an RSI indicator using a different kind of RSI called Composite RSI. This indicator is Phase Accumulation Cycle Adaptive and uses a stepped moving average.
What is Composite RSI?
The name of the composite RSI might mislead a bit.
Composite RSI is not "compositing" RSIs but is a rather new way of calculating the RSI. Unlike the RSI that is a sort of a momentum indicators, composite RSI is more a trending indicator. It tends to filter out insignificant price changes and seems to be good in identifying the underlying trends.
What is the Phase Accumulation Cycle?
The phase accumulation method of computing the dominant cycle is perhaps the easiest to comprehend. In this technique, we measure the phase at each sample by taking the arctangent of the ratio of the quadrature component to the in-phase component. A delta phase is generated by taking the difference of the phase between successive samples. At each sample we can then look backwards, adding up the delta phases.When the sum of the delta phases reaches 360 degrees, we must have passed through one full cycle, on average.The process is repeated for each new sample.
The phase accumulation method of cycle measurement always uses one full cycle’s worth of historical data.This is both an advantage and a disadvantage.The advantage is the lag in obtaining the answer scales directly with the cycle period.That is, the measurement of a short cycle period has less lag than the measurement of a longer cycle period. However, the number of samples used in making the measurement means the averaging period is variable with cycle period. longer averaging reduces the noise level compared to the signal.Therefore, shorter cycle periods necessarily have a higher out- put signal-to-noise ratio.
Included
Bar coloring
Signals
Alerts
Loxx's Expanded Source Types
Loxx's Special Phase Accumulation Cycle
PA-Adaptive MACD w/ Variety Levels [Loxx]PA-Adaptive MACD w/ Variety Levels is a Phase Accumulation Adaptive MACD with both floating and quantile levels. This is tuned for Forex. You'll have to adjust the Phase Accumulation Cycle settings to work for crypto and stock markets.
What is MACD?
Moving average convergence divergence ( MACD ) is a trend-following momentum indicator that shows the relationship between two moving averages of a security’s price. The MACD is calculated by subtracting the 26-period exponential moving average ( EMA ) from the 12-period EMA .
What is the Phase Accumulation Cycle?
The phase accumulation method of computing the dominant cycle is perhaps the easiest to comprehend. In this technique, we measure the phase at each sample by taking the arctangent of the ratio of the quadrature component to the in-phase component. A delta phase is generated by taking the difference of the phase between successive samples. At each sample we can then look backwards, adding up the delta phases.When the sum of the delta phases reaches 360 degrees, we must have passed through one full cycle, on average.The process is repeated for each new sample.
The phase accumulation method of cycle measurement always uses one full cycle’s worth of historical data.This is both an advantage and a disadvantage.The advantage is the lag in obtaining the answer scales directly with the cycle period.That is, the measurement of a short cycle period has less lag than the measurement of a longer cycle period. However, the number of samples used in making the measurement means the averaging period is variable with cycle period. longer averaging reduces the noise level compared to the signal.Therefore, shorter cycle periods necessarily have a higher out- put signal-to-noise ratio.
Included:
Zero-line and signal cross options for bar coloring, signals, and alerts
Alerts
Signals
Loxx's Expanded Source Types
4 moving average types
