Scalping Acciones PRO (Entradas + TP + SL) leo
How to use it correctly
• Timeframe: 1m or 5m
• High-volume stocks (SPY, AAPL, TSLA, NVDA…)
• Take Profit (TP): VWAP or EMA 21
• Stop Loss (SL): low/high of the signal candle
⸻
If you want, in the next message I can:
• 🔧 add automatic Stop Loss and Take Profit
• 🚀 convert it into a strategy (Strategy Tester)
• 🎯 filter only strong reversals (fewer false signals)
Cari dalam skrip untuk "spy"
"Clean Market Structure & Trend Confirmation" Clean Market Structure & Trend Confirmation is a high-probability Market Structure and Trend Confirmation indicator trading system designed specifically for SPY and QQQ.
It combines trend structure, multi-timeframe confirmation, momentum gating, and market-state filtering to deliver clean, disciplined BUY and SELL signals — without noise, chop, or over-trading.
This script is built for traders who want clarity first, execution second.
Market Regime# MARKET REGIME IDENTIFICATION & TRADING SYSTEM
## Complete User Guide
---
## 📋 TABLE OF CONTENTS
1. (#overview)
2. (#regimes)
3. (#indicator-usage)
4. (#entry-signals)
5. (#exit-signals)
6. (#regime-strategies)
7. (#confluence)
8. (#backtesting)
9. (#optimization)
10. (#examples)
---
## OVERVIEW
### What This System Does
This is a **complete market regime identification and trading system** that:
1. **Identifies 6 distinct market regimes** automatically
2. **Adapts trading tactics** to each regime
3. **Provides high-probability entry signals** with confluence scoring
4. **Shows optimal exit points** for each trade
5. **Can be backtested** to validate performance
### Two Components Provided
1. **Indicator** (`market_regime_indicator.pine`)
- Visual regime identification
- Entry/exit signals on chart
- Dynamic support/resistance
- Info tables with live data
- Use for manual trading
2. **Strategy** (`market_regime_strategy.pine`)
- Fully automated backtestable version
- Same logic as indicator
- Position sizing and risk management
- Performance metrics
- Use for backtesting and automation
---
## THE 6 MARKET REGIMES
### 1. 🟢 BULL TRENDING
**Characteristics:**
- Strong uptrend
- Price above SMA50 and SMA200
- ADX > 25 (strong trend)
- Higher highs and higher lows
- DI+ > DI- (bullish momentum)
**What It Means:**
- Market has clear upward direction
- Buyers in control
- Pullbacks are buying opportunities
- Strongest regime for long positions
**How to Trade:**
- ✅ **BUY dips to EMA20 or SMA20**
- ✅ Enter when RSI < 60 on pullback
- ✅ Hold through minor corrections
- ❌ Don't short against the trend
- ❌ Don't sell too early
**Expected Behavior:**
- Pullbacks are shallow (5-10%)
- Bounces are strong
- Support at moving averages holds
- Volume increases on rallies
---
### 2. 🔴 BEAR TRENDING
**Characteristics:**
- Strong downtrend
- Price below SMA50 and SMA200
- ADX > 25 (strong trend)
- Lower highs and lower lows
- DI- > DI+ (bearish momentum)
**What It Means:**
- Market has clear downward direction
- Sellers in control
- Rallies are selling opportunities
- Strongest regime for short positions
**How to Trade:**
- ✅ **SELL rallies to EMA20 or SMA20**
- ✅ Enter when RSI > 40 on bounce
- ✅ Hold through minor bounces
- ❌ Don't buy against the trend
- ❌ Don't cover shorts too early
**Expected Behavior:**
- Rallies are weak (5-10%)
- Selloffs are strong
- Resistance at moving averages holds
- Volume increases on declines
---
### 3. 🔵 BULL RANGING
**Characteristics:**
- Bullish bias but consolidating
- Price near or above SMA50
- ADX < 20 (weak trend)
- Trading in range
- Choppy price action
**What It Means:**
- Uptrend is pausing
- Accumulation phase
- Support and resistance zones clear
- Lower volatility
**How to Trade:**
- ✅ **BUY at support zone**
- ✅ Enter when RSI < 40
- ✅ Take profits at resistance
- ⚠️ Smaller position sizes
- ⚠️ Tighter stops
**Expected Behavior:**
- Range-bound oscillations
- Support bounces repeatedly
- Resistance rejections common
- Eventually breaks higher (usually)
---
### 4. 🟠 BEAR RANGING
**Characteristics:**
- Bearish bias but consolidating
- Price near or below SMA50
- ADX < 20 (weak trend)
- Trading in range
- Choppy price action
**What It Means:**
- Downtrend is pausing
- Distribution phase
- Support and resistance zones clear
- Lower volatility
**How to Trade:**
- ✅ **SELL at resistance zone**
- ✅ Enter when RSI > 60
- ✅ Take profits at support
- ⚠️ Smaller position sizes
- ⚠️ Tighter stops
**Expected Behavior:**
- Range-bound oscillations
- Resistance holds repeatedly
- Support bounces are weak
- Eventually breaks lower (usually)
---
### 5. ⚪ CONSOLIDATION
**Characteristics:**
- No clear direction
- Range compression
- Very low ADX (< 15 often)
- Price inside tight range
- Neutral sentiment
**What It Means:**
- Market is coiling
- Building energy for next move
- Indecision between buyers/sellers
- Calm before the storm
**How to Trade:**
- ✅ **WAIT for breakout direction**
- ✅ Enter on high-volume breakout
- ✅ Direction becomes clear
- ❌ Don't trade inside the range
- ❌ Avoid choppy scalping
**Expected Behavior:**
- Narrow range
- Low volume
- False breakouts possible
- Explosive move when it breaks
---
### 6. 🟣 CHAOS (High Volatility)
**Characteristics:**
- Extreme volatility
- No clear direction
- Erratic price swings
- ATR > 2x average
- Unpredictable
**What It Means:**
- Market panic or euphoria
- News-driven moves
- Emotion dominates logic
- Highest risk environment
**How to Trade:**
- ❌ **STAY OUT!**
- ❌ No positions
- ❌ Wait for stability
- ✅ Protect existing positions
- ✅ Reduce risk
**Expected Behavior:**
- Large intraday swings
- Gaps up/down
- Stop hunts
- Whipsaws
- Eventually calms down
---
## INDICATOR USAGE
### Visual Elements
#### 1. Background Colors
- **Light Green** = Bull Trending (go long)
- **Light Red** = Bear Trending (go short)
- **Light Teal** = Bull Ranging (buy dips)
- **Light Orange** = Bear Ranging (sell rallies)
- **Light Gray** = Consolidation (wait)
- **Purple** = Chaos (stay out!)
#### 2. Regime Labels
- Appear when regime changes
- Show new regime name
- Positioned at highs (bullish) or lows (bearish)
#### 3. Entry Signals
- **Green "LONG"** labels = Buy here
- **Red "SHORT"** labels = Sell here
- Number shows confluence score (X/5 signals)
- Hover for details (stop, target, RSI, etc.)
#### 4. Exit Signals
- **Orange "EXIT LONG"** = Close long position
- **Orange "EXIT SHORT"** = Close short position
- Shows exit reason in tooltip
#### 5. Support/Resistance Lines
- **Green line** = Dynamic support (buy zone)
- **Red line** = Dynamic resistance (sell zone)
- Adapts to regime automatically
#### 6. Moving Averages
- **Blue** = SMA 20 (short-term trend)
- **Orange** = SMA 50 (medium-term trend)
- **Purple** = SMA 200 (long-term trend)
### Information Tables
#### Top Right Table (Main Info)
Shows real-time market conditions:
- **Current Regime** - What regime we're in
- **Bias** - Long, Short, Breakout, or Stay Out
- **ADX** - Trend strength (>25 = strong)
- **Trend** - Strong, Moderate, or Weak
- **Volatility** - High or Normal
- **Vol Ratio** - Current vs average volatility
- **RSI** - Momentum (>70 overbought, <30 oversold)
- **vs SMA50/200** - Price position relative to MAs
- **Support/Resistance** - Exact price levels
- **Long/Short Signals** - Confluence scores (X/5)
#### Bottom Right Table (Regime Guide)
Quick reference for each regime:
- What action to take
- What strategy to use
- Color-coded for quick identification
---
## ENTRY SIGNALS EXPLAINED
### Confluence Scoring System (5 Factors)
Each entry signal is scored 0-5 based on how many factors align:
#### For LONG Entries:
1. ✅ **Regime Alignment** - In Bull Trending or Bull Ranging
2. ✅ **RSI Pullback** - RSI between 35-50 (not overbought)
3. ✅ **Near Support** - Price within 2% of dynamic support
4. ✅ **MACD Turning Up** - Momentum shifting bullish
5. ✅ **Volume Confirmation** - Above average volume
#### For SHORT Entries:
1. ✅ **Regime Alignment** - In Bear Trending or Bear Ranging
2. ✅ **RSI Rejection** - RSI between 50-65 (not oversold)
3. ✅ **Near Resistance** - Price within 2% of dynamic resistance
4. ✅ **MACD Turning Down** - Momentum shifting bearish
5. ✅ **Volume Confirmation** - Above average volume
### Confluence Requirements
**Minimum Confluence** (default = 2):
- 2/5 = Entry signal triggered
- 3/5 = Good signal
- 4/5 = Strong signal
- 5/5 = Excellent signal (rare)
**Higher confluence = Higher probability = Better trades**
### Specific Entry Patterns
#### 1. Bull Trending Entry
```
Requirements:
- Regime = Bull Trending
- Price pulls back to EMA20
- Close above EMA20 (bounce)
- Up candle (close > open)
- RSI < 60
- Confluence ≥ 2
```
#### 2. Bear Trending Entry
```
Requirements:
- Regime = Bear Trending
- Price rallies to EMA20
- Close below EMA20 (rejection)
- Down candle (close < open)
- RSI > 40
- Confluence ≥ 2
```
#### 3. Bull Ranging Entry
```
Requirements:
- Regime = Bull Ranging
- RSI < 40 (oversold)
- Price at or below support
- Up candle (reversal)
- Confluence ≥ 1 (more lenient)
```
#### 4. Bear Ranging Entry
```
Requirements:
- Regime = Bear Ranging
- RSI > 60 (overbought)
- Price at or above resistance
- Down candle (rejection)
- Confluence ≥ 1 (more lenient)
```
#### 5. Consolidation Breakout
```
Requirements:
- Regime = Consolidation
- Price breaks above/below range
- Volume > 1.5x average (explosive)
- Strong directional candle
```
---
## EXIT SIGNALS EXPLAINED
### Three Types of Exits
#### 1. Regime Change Exits (Automatic)
- **Long Exit**: Regime changes to Bear Trending or Chaos
- **Short Exit**: Regime changes to Bull Trending or Chaos
- **Reason**: Market character changed, strategy no longer valid
#### 2. Support/Resistance Break Exits
- **Long Exit**: Price breaks below support by 2%
- **Short Exit**: Price breaks above resistance by 2%
- **Reason**: Key level violated, trend may be reversing
#### 3. Momentum Exits
- **Long Exit**: RSI > 70 (overbought) AND down candle
- **Short Exit**: RSI < 30 (oversold) AND up candle
- **Reason**: Overextension, take profits
### Stop Loss & Take Profit
**Stop Loss** (Automatic in strategy):
- Placed at Entry - (ATR × 2)
- Adapts to volatility
- Protected from whipsaws
- Typically 2-4% for stocks, 5-10% for crypto
**Take Profit** (Automatic in strategy):
- Placed at Entry + (Stop Distance × R:R Ratio)
- Default 2.5:1 reward:risk
- Example: $2 risk = $5 reward target
- Allows winners to run
---
## TRADING EACH REGIME
### BULL TRENDING - Most Profitable Long Environment
**Strategy: Buy Every Dip**
**Entry Rules:**
1. Wait for pullback to EMA20 or SMA20
2. Look for RSI < 60
3. Enter when candle closes above MA
4. Confluence should be 2+
**Stop Loss:**
- Below the recent swing low
- Or 2 × ATR below entry
**Take Profit:**
- At previous high
- Or 2.5:1 R:R minimum
**Position Size:**
- Can use full size (2% risk)
- High win rate regime
**Example Trade:**
```
Price: $100, pulls back to $98 (EMA20)
Entry: $98.50 (close above EMA)
Stop: $96.50 (2 ATR)
Target: $103.50 (2.5:1)
Risk: $2, Reward: $5
```
---
### BEAR TRENDING - Most Profitable Short Environment
**Strategy: Sell Every Rally**
**Entry Rules:**
1. Wait for bounce to EMA20 or SMA20
2. Look for RSI > 40
3. Enter when candle closes below MA
4. Confluence should be 2+
**Stop Loss:**
- Above the recent swing high
- Or 2 × ATR above entry
**Take Profit:**
- At previous low
- Or 2.5:1 R:R minimum
**Position Size:**
- Can use full size (2% risk)
- High win rate regime
**Example Trade:**
```
Price: $100, rallies to $102 (EMA20)
Entry: $101.50 (close below EMA)
Stop: $103.50 (2 ATR)
Target: $96.50 (2.5:1)
Risk: $2, Reward: $5
```
---
### BULL RANGING - Buy Low, Sell High
**Strategy: Range Trading (Long Bias)**
**Entry Rules:**
1. Wait for price at support zone
2. Look for RSI < 40
3. Enter on reversal candle
4. Confluence should be 1-2+
**Stop Loss:**
- Below support zone
- Tighter than trending (1.5 ATR)
**Take Profit:**
- At resistance zone
- Don't hold through resistance
**Position Size:**
- Reduce to 1-1.5% risk
- Lower win rate than trending
**Example Trade:**
```
Range: $95-$105
Entry: $96 (at support, RSI 35)
Stop: $94 (below support)
Target: $104 (at resistance)
Risk: $2, Reward: $8 (4:1)
```
---
### BEAR RANGING - Sell High, Buy Low
**Strategy: Range Trading (Short Bias)**
**Entry Rules:**
1. Wait for price at resistance zone
2. Look for RSI > 60
3. Enter on rejection candle
4. Confluence should be 1-2+
**Stop Loss:**
- Above resistance zone
- Tighter than trending (1.5 ATR)
**Take Profit:**
- At support zone
- Don't hold through support
**Position Size:**
- Reduce to 1-1.5% risk
- Lower win rate than trending
**Example Trade:**
```
Range: $95-$105
Entry: $104 (at resistance, RSI 65)
Stop: $106 (above resistance)
Target: $96 (at support)
Risk: $2, Reward: $8 (4:1)
```
---
### CONSOLIDATION - Wait for Breakout
**Strategy: Breakout Trading**
**Entry Rules:**
1. Identify consolidation range
2. Wait for VOLUME SURGE (1.5x+ avg)
3. Enter on close outside range
4. Direction must be clear
**Stop Loss:**
- Opposite side of range
- Or 2 ATR
**Take Profit:**
- Measure range height, project it
- Example: $10 range = $10 move expected
**Position Size:**
- Reduce to 1% risk
- 50% false breakout rate
**Example Trade:**
```
Consolidation: $98-$102 (4-point range)
Breakout: $102.50 (high volume)
Entry: $103
Stop: $100 (back in range)
Target: $107 (4-point range projected)
Risk: $3, Reward: $4
```
---
### CHAOS - STAY OUT!
**Strategy: Preservation**
**What to Do:**
- ❌ NO new positions
- ✅ Close existing positions if near entry
- ✅ Tighten stops on profitable trades
- ✅ Reduce position sizes dramatically
- ✅ Wait for regime to stabilize
**Why It's Dangerous:**
- Stop hunts are common
- Whipsaws everywhere
- News-driven volatility
- No technical reliability
- Even "perfect" setups fail
**When Does It End:**
- Volatility ratio drops < 1.5
- ADX starts rising (direction appears)
- Price respects support/resistance again
- Usually 1-5 days
---
## CONFLUENCE SYSTEM
### How It Works
The system scores each potential entry on 5 factors. More factors aligning = higher probability.
### Confluence Requirements by Regime
**Trending Regimes** (strictest):
- Minimum 2/5 required
- 3/5 = Good
- 4-5/5 = Excellent
**Ranging Regimes** (moderate):
- Minimum 1-2/5 required
- 2/5 = Good
- 3+/5 = Excellent
**Consolidation** (breakout only):
- Volume is most critical
- Direction confirmation
- Less confluence needed
### Adjusting Minimum Confluence
**If too few signals:**
- Lower from 2 to 1
- More trades, lower quality
**If too many false signals:**
- Raise from 2 to 3
- Fewer trades, higher quality
**Recommendation:**
- Start at 2
- Adjust based on win rate
- Aim for 55-65% win rate
---
## STRATEGY BACKTESTING
### Loading the Strategy
1. Copy `market_regime_strategy.pine`
2. Open Pine Editor in TradingView
3. Paste and "Add to Chart"
4. Strategy Tester tab opens at bottom
### Initial Settings
```
Risk Per Trade: 2%
ATR Stop Multiplier: 2.0
Reward:Risk Ratio: 2.5
Trade Longs: ✓
Trade Shorts: ✓
Trade Trending Only: ✗ (test both)
Avoid Chaos: ✓
Minimum Confluence: 2
```
### What to Look For
**Good Results:**
- Win Rate: 50-60%
- Profit Factor: 1.8-2.5
- Net Profit: Positive
- Max Drawdown: <20%
- Consistent equity curve
**Warning Signs:**
- Win Rate: <45% (too many losses)
- Profit Factor: <1.5 (barely profitable)
- Max Drawdown: >30% (too risky)
- Erratic equity curve (unstable)
### Testing Different Regimes
**Test 1: Trending Only**
```
Trade Trending Only: ✓
Result: Higher win rate, fewer trades
```
**Test 2: All Regimes**
```
Trade Trending Only: ✗
Result: More trades, potentially lower win rate
```
**Test 3: Long Only**
```
Trade Longs: ✓
Trade Shorts: ✗
Result: Works in bull markets
```
**Test 4: Short Only**
```
Trade Longs: ✗
Trade Shorts: ✓
Result: Works in bear markets
```
---
## SETTINGS OPTIMIZATION
### Key Parameters to Adjust
#### 1. Risk Per Trade (Most Important)
- **0.5%** = Very conservative
- **1.0%** = Conservative (recommended for beginners)
- **2.0%** = Moderate (recommended)
- **3.0%** = Aggressive
- **5.0%** = Very aggressive (not recommended)
**Impact:** Higher risk = higher returns BUT bigger drawdowns
#### 2. Reward:Risk Ratio
- **2:1** = More wins needed, hit target faster
- **2.5:1** = Balanced (recommended)
- **3:1** = Fewer wins needed, hold longer
- **4:1** = Very patient, best in trending
**Impact:** Higher R:R = can have lower win rate
#### 3. Minimum Confluence
- **1** = More signals, lower quality
- **2** = Balanced (recommended)
- **3** = Fewer signals, higher quality
- **4** = Very selective
- **5** = Almost never triggers
**Impact:** Higher = fewer but better trades
#### 4. ADX Thresholds
- **Trending: 20-30** (default 25)
- Lower = detect trends earlier
- Higher = only strong trends
- **Ranging: 15-25** (default 20)
- Lower = identify ranging earlier
- Higher = only weak trends
#### 5. Trend Period (SMA)
- **20-50** = Short-term trends
- **50** = Medium-term (default, recommended)
- **100-200** = Long-term trends
**Impact:** Longer period = slower regime changes, more stable
### Optimization Workflow
**Step 1: Baseline**
- Use all default settings
- Test on 3+ years
- Record: Win Rate, PF, Drawdown
**Step 2: Risk Optimization**
- Test 1%, 1.5%, 2%, 2.5%
- Find best risk-adjusted return
- Balance profit vs drawdown
**Step 3: R:R Optimization**
- Test 2:1, 2.5:1, 3:1
- Check which maximizes profit factor
- Consider holding time
**Step 4: Confluence Optimization**
- Test 1, 2, 3
- Find sweet spot for win rate
- Aim for 55-65% win rate
**Step 5: Regime Filter**
- Test with/without trend filter
- Test with/without chaos filter
- Find what works for your asset
---
## REAL TRADING EXAMPLES
### Example 1: Bull Trending - SPY
**Setup:**
- Regime: BULL TRENDING
- Price pulls back from $450 to $445
- EMA20 at $444
- RSI drops to 45
- Confluence: 4/5
**Entry:**
- Price closes at $445.50 (above EMA20)
- LONG signal appears
- Enter at $445.50
**Risk Management:**
- Stop: $443 (2 ATR = $2.50)
- Target: $451.75 (2.5:1 = $6.25)
- Risk: $2.50 per share
- Position: 80 shares (2% of $10k = $200 risk)
**Outcome:**
- Price rallies to $452 in 3 days
- Target hit
- Profit: $6.50 × 80 = $520
- Return: 2.6 × risk (excellent)
---
### Example 2: Bear Ranging - AAPL
**Setup:**
- Regime: BEAR RANGING
- Range: $165-$175
- Price rallies to $174
- Resistance at $175
- RSI at 68
- Confluence: 3/5
**Entry:**
- Rejection candle at $174
- SHORT signal appears
- Enter at $173.50
**Risk Management:**
- Stop: $176 (above resistance)
- Target: $166 (support)
- Risk: $2.50
- Position: 80 shares
**Outcome:**
- Price drops to $167 in 2 days
- Target hit
- Profit: $6.50 × 80 = $520
- Return: 2.6 × risk
---
### Example 3: Consolidation Breakout - BTC
**Setup:**
- Regime: CONSOLIDATION
- Range: $28,000 - $30,000
- Compressed for 2 weeks
- Volume declining
**Breakout:**
- Price breaks $30,000
- Volume surges 200%
- Close at $30,500
- LONG signal
**Entry:**
- Enter at $30,500
**Risk Management:**
- Stop: $29,500 (back in range)
- Target: $32,000 (range height = $2k)
- Risk: $1,000
- Position: 0.2 BTC ($200 risk on $10k)
**Outcome:**
- Price runs to $33,000
- Target exceeded
- Profit: $2,500 × 0.2 = $500
- Return: 2.5 × risk
---
### Example 4: Avoiding Chaos - Tesla
**Setup:**
- Regime: BULL TRENDING
- LONG position from $240
- Elon tweets something crazy
- Regime changes to CHAOS
**Action:**
- EXIT signal appears
- Close position immediately
- Current price: $242 (small profit)
**Outcome:**
- Next 3 days: wild swings
- High $255, Low $230
- By staying out, avoided:
- Potential stop out
- Whipsaw losses
- Stress
**Result:**
- Small profit preserved
- Capital protected
- Re-enter when regime stabilizes
---
## ALERTS SETUP
### Available Alerts
1. **Bull Trending Regime** - Market goes bullish
2. **Bear Trending Regime** - Market goes bearish
3. **Chaos Regime** - High volatility, stay out
4. **Long Entry Signal** - Buy opportunity
5. **Short Entry Signal** - Sell opportunity
6. **Long Exit Signal** - Close long
7. **Short Exit Signal** - Close short
### How to Set Up
1. Click **⏰ (Alert)** icon in TradingView
2. Select **Condition**: Choose indicator + alert type
3. **Options**: Popup, Email, Webhook, etc.
4. **Message**: Customize notification
5. Click **Create**
### Recommended Alert Strategy
**For Active Traders:**
- Long Entry Signal
- Short Entry Signal
- Long Exit Signal
- Short Exit Signal
**For Position Traders:**
- Bull Trending Regime (enter longs)
- Bear Trending Regime (enter shorts)
- Chaos Regime (exit all)
**For Conservative:**
- Only regime change alerts
- Manually review entries
- More selective
---
## TIPS FOR SUCCESS
### 1. Start Small
- Paper trade first
- Then 0.5% risk
- Build to 1-2% over time
### 2. Follow the Regime
- Don't fight it
- Adapt your style
- Different tactics for each
### 3. Trust the Confluence
- 4-5/5 = Best trades
- 2-3/5 = Good trades
- 1/5 = Skip unless desperate
### 4. Respect Exits
- Don't hope and hold
- Cut losses quickly
- Take profits at targets
### 5. Avoid Chaos
- Seriously, just stay out
- Protect your capital
- Wait for clarity
### 6. Keep a Journal
- Record every trade
- Note regime and confluence
- Review weekly
- Learn patterns
### 7. Backtest Thoroughly
- 3+ years minimum
- Multiple market conditions
- Different assets
- Walk-forward test
### 8. Be Patient
- Best setups are rare
- 1-3 trades per week is normal
- Quality over quantity
- Compound over time
---
## COMMON QUESTIONS
**Q: How many trades per month should I expect?**
A: Depends on timeframe and settings. Daily chart: 5-15 trades/month. 4H chart: 15-30 trades/month.
**Q: What's a good win rate?**
A: 55-65% is excellent. 50-55% is good. Below 50% needs adjustment.
**Q: Should I trade all regimes?**
A: Beginners: Only trending. Intermediate: Trending + ranging. Advanced: All except chaos.
**Q: Can I use this on any timeframe?**
A: Best on Daily and 4H. Works on 1H with more noise. Not recommended <1H.
**Q: What if I'm in a trade and regime changes?**
A: Exit immediately (if using indicator) or let strategy handle it automatically.
**Q: How do I know if I'm over-optimizing?**
A: If results are perfect on one period but fail on another. Use walk-forward testing.
**Q: Should I always take 5/5 confluence trades?**
A: Yes, but they're rare (1-2/month). Don't wait only for these.
**Q: Can I combine this with other indicators?**
A: Yes, but keep it simple. RSI, MACD already included. Maybe add volume profile.
**Q: What assets work best?**
A: Liquid stocks, major crypto, futures. Avoid forex spot (use futures), penny stocks.
**Q: How long to hold positions?**
A: Trending: Days to weeks. Ranging: Hours to days. Breakout: Days. Let the regime guide you.
---
## FINAL THOUGHTS
This system gives you:
- ✅ Clear market context (regime)
- ✅ High-probability entries (confluence)
- ✅ Defined exits (automatic signals)
- ✅ Adaptable tactics (regime-specific)
- ✅ Backtestable results (strategy version)
**Success requires:**
- 📚 Understanding each regime
- 🎯 Following the signals
- 💪 Discipline to wait
- 🧠 Emotional control
- 📊 Proper risk management
**Start your journey:**
1. Load the indicator
2. Watch for 1 week (no trading)
3. Identify regime patterns
4. Paper trade for 1 month
5. Go live with small size
6. Scale up as you gain confidence
**Remember:** The market will always be here. There's no rush. Master one regime at a time, and you'll be profitable in all conditions!
Good luck! 🚀
Pair Creation🙏🏻 The one and only pair construction tech you need, unlike others:
Applies one consistent operation to all the data features (not only prices). Then, the script outputs these, so you can apply other calculations on these outputs.
calculates a very fast and native volatility based hedge ratio, that also takes into account point value (think SPY vs ES) so you can easily use it in position sizing
Has built-in forward pricing aka cost of carry model , so you can de-drift pairs from cost of carry, discover spot price of oil based on futures, and ofc find arbitrage opportunities
Also allows to make a pair as a product of 2 series, useful for triangular arbitrage
This script can make a pair in 2 ways:
Ratio, by dividing leg 1 by leg 2
Product, by multiplying leg 1 by leg 2
The real mathematically right way to construct a pair is a ratio/product (Spreads are in fact = 2 legged portfolio, but I ain't told ya that ok). Why? Because a pair of 2 entities has a mathematically unique beauty, it allows direct comparisons and relationship analysis, smth you can't do directly with 3 and more components.
Multiplication (think inversions like (EURUSD -> USDEUR), and use cases for triangular arbitrage) is useful sometimes too.
...
Quickguide:
First, "Legs" are pair components: make a pair of related assets. Don’t be guided exclusively by clustering, cointegrations, mutual information etc. Common sense and exogenous info can easily made them all Forward pricing model: is useful when u work with spot vs futures pairs. Otherwise: put financing, storage and yield all on zeros, this way u will turn it off and have a pure ratio/product of 2 legs.
Look at the 2 numbers on the script’s status line: the first one would always be 1), and the second one is a variable.
First number (always 1) is multiplier for your position size on leg 1
The second number is the multiplier for your position size on leg 2 in the opposite direction.
If both legs are related, trading your sizes with these multipliers makes you do statistical arbitrage -> trading ~ volatility in risk free mode, while the relationship between the assets is still in place.
Also guys srsly, nobody ‘ever’ made a universal law that somewhy somehow for whatever secret conspiracy reason one shall only trade pairs in mean reverting style xd. You can do whatever you want:
Tilt hedge ratio significantly based on relative strength of legs
Trade the pair in momentum style
Ignore hedge ratio all together
And more and more, the limit is your imagination, e.g.:
Anticipate hedge ratio changes based on exogenous info and act accordingly
Scalp a pair just like any other asset
Make a pair out of 2 pairs
Like I mean it, whatever you desire
About forward pricing model:
It’s applied only to leg 2;
Direct: takes spot price and finds out implied futures price
Inverse: takes futures price and finds out implied spot price (try on oil)
Pls read online how to choose parameters, it’s open access reliable info
About the hedge ratio I use:
You prolly noticed the way I prefer to use inferred volumes vs the “real” ones. In pairs it’s especially meaningful, because real volumes lose sense in pair creation. And while volumes are closely tied to volatility, the inferred volumes ‘Are’ volatility irl (and later can be converted to currency space by using point value, allowing direct comparisons symbol vs symbol).
This hedge ratio is a good example of how discovering the real nature of entities beats making 100s of inventions, why domain knowledge and proper feature engineering beats difficult bulky models, neural networks etc. How simple data understanding & operations on it is all you need.
This script simply does this:
Takes inferred volume delta of both assets, makes a ratio, normalizes it by tick sizes and points values of both legs, calculates a typical value of this series.
That’s it, no step 2, we’re done. No Kalman filters, no TLS regression, no vine copulas, or whatever new fancy keywords you can come up with etc.
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^^ comparing real ES prices vs theoretical ones by forward-pricing model. Financing: 0.04, yield 0.0175
^^ EURUSD, 6E futures with theoretical futures price calculated with interest rate differential 0.02 (4% USD - 2% EUR interest rates)
^^4 different pairs (RTY/ES, YM/ES, NQ/ES, ES/ZN) each with different plot style (pick one you like in script's Style settings)
^^ YM/RTY pair, each plot represents ratio of different features: ratio of prices, ratio of inferred volume deltas, ratio of inferred volumes, ratio of inferred tick counts (also can be turned on/off in Style settings)
...
How can u upgrade it and make a step forward yourself:
On tradingview missing values are automatically fixed by backfilling, and this never becomes a thing until you hit high frequency data. You can do better and use Kalman filter for filling missing values.
Script contains the functions I use everywhere to calculate inferred volume delta, inferred volume, and inferred tick count.
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∞
Quality Detector (Buffett Style) + Beta [Solid]This indicator acts as an on-chart fundamental screener, designed to instantly evaluate the quality and financial health of a company directly on your price chart.
The concept is inspired by "Buffettology" principles: looking for large, profitable companies with low debt. Additionally, it includes a Beta calculation to assess market volatility risk.
The tool displays a panel in the bottom-right corner featuring four key metrics and a final verdict.
How it Works & Metrics Used
The script retrieves quarterly fundamental data ("FQ") and performs calculations to verify if the asset meets specific criteria.
1. Market Cap (Size)
What it is: The total market value of the company's outstanding shares.
Goal: To identify established, large-cap companies.
Default Threshold: Must be greater than $10 Billion.
2. ROE - Return on Equity (Quality)
What it is: A measure of financial performance calculated by dividing net income by shareholders' equity.
Goal: To find companies that are efficient at generating profits from shareholders' capital.
Default Threshold: Must be higher than 15%.
3. Total Debt to Equity (Health)
What it is: A ratio indicating the relative proportion of shareholders' equity and debt used to finance a company's assets.
Calculation: This script manually calculates this ratio by fetching TOTAL_DEBT and dividing it by TOTAL_EQUITY from fundamental data to ensure robustness across different symbols.
Goal: To ensure the company is not overly leveraged.
Default Threshold: Must be lower than 1.5.
4. Beta (Risk/Volatility)
What it is: A measure of a stock's volatility in relation to the overall market (S&P 500).
Calculation: It is calculated by comparing the asset's returns against SPY (S&P 500 ETF) returns over a 252-day period (approx. 1 trading year).
Goal: To understand if the stock is more volatile (Beta > 1) or less volatile (Beta < 1) than the market.
Note: Beta does not affect the final "Quality" score but serves as an extra risk indicator, highlighting in orange if Beta > 1.
The Verdict (Scoring System)
The indicator assigns a score from 0 to 3 based on the first three fundamental metrics (Size, ROE, and Debt/Equity).
If a metric passes the threshold, it gets a green background and +1 point.
If it fails, it gets a red background.
Final Verdict:
💎 QUALITY GEM: The company passed all 3 fundamental checks (Score = 3/3).
⚠️ DISCARD: The company failed one or more fundamental checks.
Settings
You can customize the thresholds to fit your own investment strategy in the indicator settings:
Minimum Market Cap (in Billions).
Minimum ROE (%).
Maximum Debt/Equity Ratio.
Disclaimer: This tool is for informational and educational purposes only. It relies on third-party fundamental data which may sometimes be delayed or unavailable. Do not base investment decisions solely on this indicator.
Trinity ATR Real Move DetectorTrinity ATR Real Move Detector
This ATR Energy Table indicator is one of the simplest yet most powerful filters you can have on a chart when trading short-dated or 0DTE options or swing trades on any timeframe from 1-minute up to 4-hour. Its entire job is to answer the single most important question in intraday and swing trading: “Does the underlying actually have enough short-term explosive energy right now to make a directional position worth the theta and the spread, or is this just pretty candles that will die in ten minutes?”
Most losing 0DTE and short-dated option trades happen because people buy or sell direction on a “nice-looking” breakout or pullback while the underlying is actually in low-energy grind mode. The premium decays faster than the move develops, and you lose even when you’re “right” on direction. This little table stops that from ever happening again.
Here’s what it does in plain English:
Every bar it measures two things:
- The current ATR on whatever timeframe you are using (1 min, 3 min, 5 min, 10 min, etc.). This tells you how big the average true range of the last 14 bars has been — in other words, how violently the stock or index is actually moving right now.
- The daily ATR (14-period on the daily chart). This is your benchmark for “normal” daily movement over the last two–three weeks.
It then multiplies the daily ATR by a small number (the multiplier you set) and compares the two. If the short-term ATR is bigger than that percentage of the daily ATR, the table turns bright green and says “ENOUGH ENERGY”. If not, it stays red and says “NOT ENOUGH”.
Why this works so well:
- Real explosive moves that carry for 0DTE and 1–3 DTE options almost always show a short-term ATR spike well above the recent daily average. Quiet grind moves never do.
- The comparison is completely adaptive — on a high-vol day the threshold automatically rises, on a low-vol day it automatically drops. You never have to guess if “2 points on SPY is big today”.
- It removes emotion completely. You simply wait for green before you even think about clicking buy or sell on an option.
Key settings and what to do with them:
- Energy Multiplier — this is the only number you ever touch. It is expressed as a decimal (0.15 = 15 % of the daily ATR). Lower = more signals, higher = stricter and higher win rate. The tooltip gives you the exact sweet-spot numbers for every popular timeframe (0.09 for 1-minute scalping, 0.13 for 3-minute, 0.14–0.16 for 5-minute, 0.15–0.19 for 10-minute, etc.). Just pick your timeframe once and type the number — done forever.
- ATR Length — leave it at 14. That’s the standard and works perfectly.
- Table Position — move the table to wherever you want on the chart (top-right, bottom-right, bottom-left, top-left).
- Table Size — make the text Tiny, Small, Normal or Large depending on how much screen space you have.
How this helps you make money and stop losing it:
- On most days you will see red 80–90 % of the time — that’s good! It is forcing you to sit on your hands instead of overtrading low-energy chop that eats premium.
- When it finally flips green you know institutions are actually pushing size right now — follow-through probability jumps from ~40 % to 65–75 % depending on the stock and timeframe.
- You stop buying calls on every green candle and puts on every red candle. You only strike when the market is genuinely “awake”.
- Over a week you take dramatically fewer trades, but your win rate and average winner size go way up — which is exactly how consistent intraday option profits are made.
In short, this tiny table is the closest thing to an “edge on/off switch” that exists for short-dated options. Red = preserve capital and go do something else. Green = pull the trigger with confidence. Use it religiously and you’ll immediately feel the difference in your P&L.
Advanced Confluence DashboardAdvanced Confluence Dashboard - Multi-Indicator Technical Analysis Tool
OVERVIEW
The Advanced Confluence Dashboard is a comprehensive technical analysis tool designed to help traders identify high-probability trade setups by tracking multiple technical indicators simultaneously. The indicator displays up to 13 different technical confluences in an easy-to-read dashboard format, providing both individual signals and an overall market bias percentage. Switch between full table view and condensed view for maximum chart flexibility.
FEATURES
- 13 Technical Confluences: RSI, VWAP, EMA Cross (9/21), MACD, Stochastic, Trend (50 EMA), Bollinger Bands, ADX Strength, Price Momentum, Volume Breakout, VWAP Bands, 200 EMA, and Price Action (Higher Highs/Lower Lows)
- Real-time Confluence Scoring: Automatically calculates bullish vs bearish signal strength
- Multi-Timeframe Support: Analyze indicators on any timeframe while viewing your chart on another
- Customizable Display: Toggle individual indicators on/off, adjust table position, size, and transparency
- ATR Information: Optional ATR display for volatility-based position sizing
- Condensed View Mode: Ultra-minimal display showing only confluence score and ATR (perfect for scalpers who want maximum chart visibility)
- Full Table View: Detailed breakdown of each indicator's value and signal
- Color-Coded Signals: Green (bullish), red (bearish), white (neutral) for instant visual clarity
HOW IT WORKS
The indicator evaluates each enabled technical indicator and assigns it either a bullish or bearish signal based on its current state. The confluence score shows how many indicators are aligned in each direction, giving you a clear percentage-based view of market bias. For example, if 8 out of 13 indicators are bullish, you'll see a 62% LONG BIAS signal.
DISPLAY MODES
Full View: Shows all enabled indicators with their current values and signals in a detailed table format. Perfect for understanding exactly which indicators are bullish or bearish and why.
Condensed View: Shows only the confluence score (e.g., "4/13 LONG | 9/13 SHORT - SHORT BIAS 69%") and optional ATR information. This minimal display keeps your chart clean while still providing the essential confluence data you need for quick trading decisions. Ideal for scalpers and traders who want maximum chart space.
CONFLUENCES EXPLAINED
- RSI: Momentum oscillator (>50 bullish, <50 bearish, shows overbought/oversold)
- VWAP: Volume-weighted average price (above = bullish, below = bearish)
- EMA Cross: Fast EMA (9) vs Slow EMA (21) with price position
- MACD: Trend-following momentum (line above signal = bullish)
- Stochastic: Momentum oscillator (>50 bullish, <50 bearish)
- Trend (50 EMA): Price position relative to 50-period EMA
- Bollinger Bands: Volatility and mean reversion (above middle = bullish)
- ADX Strength: Trend strength indicator (shows strong trends)
- Price Momentum: Rate of price change over specified period
- Volume Breakout: Detects unusual volume with directional bias
- VWAP Bands: Standard deviation bands around VWAP
- 200 EMA: Long-term trend indicator
- Price Action: Higher Highs and Lower Lows pattern detection
SETTINGS
Timeframe Settings:
- Indicator Timeframe: Analyze indicators on a different timeframe than your chart
Display Options:
- Condensed View: Toggle between full table and minimal display
- Show ATR Info: Display/hide ATR information
- Table Position: 9 positions (top/middle/bottom + left/center/right)
- Text Size: Auto, tiny, small, normal, large, huge
- Table Transparency: 0-100%
- Border Width: 1-5 pixels
Confluence Toggles:
- Enable/disable any of the 13 confluences individually
- Confluence score automatically adjusts based on enabled indicators
Indicator Settings:
- RSI Length (default: 14)
- ATR Length (default: 14)
- Fast/Slow EMA (default: 9/21)
- Trend EMA (default: 50)
- Volume SMA Length (default: 20)
- Volume Breakout Multiplier (default: 2.0x)
- Bollinger Bands Length/StdDev (default: 20/2.0)
- ADX Length (default: 14)
- ADX Strength Threshold (default: 25)
- Momentum Length (default: 10)
IDEAL USE CASES
- Scalping: Quick identification of confluence for fast entries/exits - use condensed view for clean charts
- Day Trading: Multi-timeframe analysis for intraday setups
- Swing Trading: Confirmation of longer-term bias
- Risk Management: Higher confluence = higher probability trades
- Trade Filtering: Only take trades when confluence reaches your threshold
- Multi-Monitor Setups: Use condensed view on execution charts, full view on analysis charts
HOW TO USE
1. Add the indicator to your chart
2. Toggle on/off the confluences you prefer to use
3. Choose between Full View (detailed) or Condensed View (minimal)
4. Adjust the table position and size to your preference
5. Look for high confluence percentages (70%+ is strong bias)
6. Use the individual indicator signals (full view) to understand market structure
7. Combine with your trading strategy for entry/exit confirmation
TIPS
- Use Condensed View when scalping to keep your chart clean and uncluttered
- Switch to Full View when you need to analyze which specific indicators are conflicting
- Higher confluence doesn't guarantee success - always use proper risk management
- Consider using 60%+ confluence as a minimum threshold for trades
- Pay attention to which specific indicators are aligned vs conflicting
- Use the ATR display for quick reference on position sizing
- Experiment with different timeframes to find what works for your style
- Disable indicators you don't use to simplify your confluence scoring
DISCLAIMER
This indicator is for educational and informational purposes only. It does not constitute financial advice, investment advice, trading advice, or any other type of advice. Trading and investing in financial markets involves substantial risk of loss and is not suitable for every investor. Past performance is not indicative of future results. Always do your own research and consult with a qualified financial advisor before making any investment decisions.
Granger Causality Flow IndicatorGranger Causality Flow Indicator
█ OVERVIEW
The Granger Causality Flow Indicator is a statistical analysis tool designed to identify predictive relationships between two assets (Symbol X and Symbol Y). In econometrics, "Granger Causality" does not test for actual physical causation (e.g., rain causes mud); rather, it tests for predictive causality .
This script is designed to answer a specific question for traders: "Does the past price action of Asset X provide statistically significant information about the future price of Asset Y, beyond what is already contained in the past prices of Asset Y itself?"
This tool is particularly useful for Pairs Traders , Arbitrageurs , and Macro Analysts looking to identify lead-lag relationships between correlated assets (e.g., BTC vs. ETH, NASDAQ vs. SPY, or Gold vs. Silver).
█ CONCEPTS & CALCULATIONS
To determine if Symbol X "Granger-causes" Symbol Y, this script utilizes a variance-reduction approach based on Auto-Regressive (AR) models. Due to the runtime constraints of Pine Script™, we employ an optimized proxy for the standard Granger test using an AR(1) logic (looking back 1 period).
The calculation performs a comparative test over a rolling window (Default: 50 bars):
The Restricted Model (Baseline):
We attempts to predict the current value of Y using only the previous value of Y (Auto-Regression). We measure the error of this prediction (the "Residuals") and calculate the Variance of the Restricted Model (Var_R) .
The Unrestricted Model (Proxy):
We then test if the past value of X can explain the errors made by the Restricted Model. If X contains predictive power, including it should reduce the error variance. We calculate the remaining Variance of the Unrestricted Model (Var_UR) .
The GC Score:
The script calculates a score based on the ratio of variance reduction:
Score = 1 - (Var_UR / Var_R)
If the Score is High (> 0) : It implies that including X significantly reduced the prediction error for Y. Therefore, X "Granger-causes" Y.
If the Score is Low or 0 : It implies X added no predictive value.
█ HOW TO USE
This indicator is not a simple Buy/Sell signal generator; it is a context filter for cross-asset analysis.
1. Setup
Symbol 1 (X): The potential "Leader" (e.g., BINANCE:BTCUSDT).
Symbol 2 (Y): The potential "Follower" (e.g., BINANCE:ETHUSDT).
Differencing: Enabled by default. This checks the changes in price rather than absolute price, which is crucial for statistical stationarity.
2. Interpreting the Visuals
The script changes the background color and displays a table to indicate the current flow of causality:
Green Background (X → Y): Symbol 1 is leading Symbol 2. Price moves in Symbol 1 are statistically likely to foreshadow moves in Symbol 2.
Orange Background (Y → X): Symbol 2 is leading Symbol 1. The relationship has inverted.
Blue Background (Bidirectional): Both assets are predicting each other (tight coupling or feedback loop).
Gray/No Color: No statistically significant relationship detected.
3. Trading Application
Trend Confirmation: If you trade Symbol Y, wait for the background to turn Green . This indicates that the "Leader" (Symbol X) is currently exerting predictive influence, potentially making trend-following setups on Symbol Y more reliable.
Divergence Warning: If you are trading a correlation pair and the causality breaks (turns Gray), the correlation may be weakening, signaling a higher risk of divergence.
█ SETTINGS
Symbol 1 (X) & Symbol 2 (Y): The two tickers to analyze.
Use Differencing: (Default: True) Converts prices to price-changes. Highly recommended for accurate statistical results to avoid spurious regression.
Calculation Window: The number of bars used to compute the variance and coefficients. Larger windows provide smoother, more stable signals but react slower to regime changes.
Significance Threshold: (0.01 - 0.99) The minimum variance reduction score required to trigger a causal signal.
█ DISCLAIMER
This tool provides statistical analysis of historical price data and does not guarantee future performance. Granger Causality is a measure of predictive capability, not necessarily fundamental causation. Always use appropriate risk management.
Relative Value & Risk Analytics DashboardThis is your risk-adjusted alpha analysis tool - exactly what hedge fund and insurance company clients want to see.
Attractiveness Score | Composite score combining RV and Risk (0-100)
Relative Performance | vs Benchmark (SET/SPY), RS Ratio Trend, 52W Position, Spread Z-Score
Risk Metrics | Beta, Alpha, Sharpe, Sortino, Information Ratio, Volatility
Correlation | Benchmark Correlation, R-Squared, Regime Change Detection
Pair Trade | Peer Correlation, Pair Z-Score, Long/Short Signals
Factor Exposure | Momentum (1/3/6M), Mean Reversion Signal, Distance from SMA50
Drawdown | Current DD, Max DD, Recovery Needed, Ulcer Index, Calmar, VaR
Key Features:
Benchmark-Relative Analysis: Compare any stock vs SET Index or any other benchmark
Pair Trade Signals: Automatically generates long/short signals based on Z-score
Risk-Adjusted Returns: Sharpe, Sortino, Information Ratio - what your clients actually care about
Regime Change Detection: Alert when correlation dynamics shift
Drawdown Risk: VaR, Ulcer Index, Calmar Ratio for risk-conscious clients
Reversal WaveThis is the type of quantitative system that can get you hated on investment forums, now that the Random Walk Theory is back in fashion. The strategy has simple price action rules, zero over-optimization, and is validated by a historical record of nearly a century on both Gold and the S&P 500 index.
Recommended Markets
SPX (Weekly, Monthly)
SPY (Monthly)
Tesla (Weekly)
XAUUSD (Weekly, Monthly)
NVDA (Weekly, Monthly)
Meta (Weekly, Monthly)
GOOG (Weekly, Monthly)
MSFT (Weekly, Monthly)
AAPL (Weekly, Monthly)
System Rules and Parameters
Total capital: $10,000
We will use 10% of the total capital per trade
Commissions will be 0.1% per trade
Condition 1: Previous Bearish Candle (isPrevBearish) (the closing price was lower than the opening price).
Condition 2: Midpoint of the Body The script calculates the exact midpoint of the body of that previous bearish candle.
• Formula: (Previous Open + Previous Close) / 2.
Condition 3: 50% Recovery (longCondition) The current candle must be bullish (green) and, most importantly, its closing price must be above the midpoint calculated in the previous step.
Once these parameters are met, the system executes a long entry and calculates the exit parameters:
Stop Loss (SL): Placed at the low of the candle that generated the entry signal.
Take Profit (TP): Calculated by projecting the risk distance upward.
• Calculation: Entry Price + (Risk * 1).
Risk:Reward Ratio of 1:1.
About the Profit Factor
In my experience, TradingView calculates profits and losses based on the percentage of movement, which can cause returns to not match expectations. This doesn’t significantly affect trending systems, but it can impact systems with a high win rate and a well-defined risk-reward ratio. It only takes one large entry candle that triggers the SL to translate into a major drop in performance.
For example, you might see a system with a 60% win rate and a 1:1 risk-reward ratio generating losses, even though commissions are under control relative to the number of trades.
My recommendation is to manually calculate the performance of systems with a well-defined risk-reward ratio, assuming you will trade using a fixed amount per trade and limit losses to a fixed percentage.
Remember that, even if candles are larger or smaller in size, we can maintain a fixed loss percentage by using leverage (in cases of low volatility) or reducing the capital at risk (when volatility is high).
Implementing leverage or capital reduction based on volatility is something I haven’t been able to incorporate into the code, but it would undoubtedly improve the system’s performance dramatically, as it would fix a consistent loss percentage per trade, preventing losses from fluctuating with volatility swings.
For example, we can maintain a fixed loss percentage when volatility is low by using the following formula:
Leverage = % of SL you’re willing to risk / % volatility from entry point to exit or SL
And if volatility is high and exceeds the fixed percentage we want to expose per trade (if SL is hit), we could reduce the position size.
For example, imagine we only want to risk 15% per SL on Tesla, where volatility is high and would cause a 23.57% loss. In this case, we subtract 23.57% from 15% (the loss percentage we’re willing to accept per trade), then subtract the result from our usual position size.
23.57% - 15% = 8.57%
Suppose I use $200 per trade.
To calculate 8.57% of $200, simply multiply 200 by 8.57/100. This simple calculation shows that 8.57% equals about $17.14 of the $200. Then subtract that value from $200:
$200 - $17.14 = $182.86
In summary, if we reduced the position size to $182.86 (from the usual $200, where we’re willing to lose 15%), no matter whether Tesla moves up or down 23.57%, we would still only gain or lose 15% of the $200, thus respecting our risk management.
Final Notes
The code is extremely simple, and every step of its development is detailed within it.
If you liked this strategy, which complements very well with others I’ve already published, stay tuned. Best regards.
Absorption RatioThe Hidden Connections Between Markets
Financial markets are not isolated islands. When panic spreads, seemingly unrelated assets suddenly begin moving in lockstep. Stocks, bonds, commodities, and currencies that normally provide diversification benefits start falling together. This phenomenon, where correlations spike during crises, has devastated portfolios throughout history. The Absorption Ratio provides a quantitative measure of this hidden fragility.
The concept emerged from research at State Street Associates, where Mark Kritzman, Yuanzhen Li, Sebastien Page, and Roberto Rigobon developed a novel application of principal component analysis to measure systemic risk. Their 2011 paper in the Journal of Portfolio Management demonstrated that when markets become tightly coupled, the variance explained by the first few principal components increases dramatically. This concentration of variance signals elevated systemic risk.
What the Absorption Ratio Measures
Principal component analysis, or PCA, is a statistical technique that identifies the underlying factors driving a set of variables. When applied to asset returns, the first principal component typically captures broad market movements. The second might capture sector rotations or risk-on/risk-off dynamics. Additional components capture increasingly idiosyncratic patterns.
The Absorption Ratio measures the fraction of total variance absorbed or explained by a fixed number of principal components. In the original research, Kritzman and colleagues used the first fifth of the eigenvectors. When this fraction is high, it means a small number of factors are driving most of the market movements. Assets are moving together, and diversification provides less protection than usual.
Consider an analogy: imagine a room full of people having independent conversations. Each person speaks at different times about different topics. The total "variance" of sound in the room comes from many independent sources. Now imagine a fire alarm goes off. Suddenly everyone is talking about the same thing, moving in the same direction. The variance is now dominated by a single factor. The Absorption Ratio captures this transition from diverse, independent behavior to unified, correlated movement.
The Implementation Approach
TradingView does not support matrix algebra required for true principal component analysis. This implementation uses a closely related proxy: the average absolute correlation across a universe of major asset classes. This approach captures the same underlying phenomenon because when assets are highly correlated, the first principal component explains more variance by mathematical necessity.
The asset universe includes eight ETFs representing major investable categories: SPY and QQQ for large cap US equities, IWM for small caps, EFA for developed international markets, EEM for emerging markets, TLT for long-term treasuries, GLD for gold, and USO for oil. This selection provides exposure to equities across geographies and market caps, plus traditional diversifying assets.
From eight assets, there are twenty-eight unique pairwise correlations. The indicator calculates each using a rolling window, takes the absolute value to measure coupling strength regardless of direction, and averages across all pairs. This average correlation is then transformed to match the typical range of published Absorption Ratio values.
The transformation maps zero average correlation to an AR of 0.50 and perfect correlation to an AR of 1.00. This scaling aligns with empirical observations that the AR typically fluctuates between 0.60 and 0.95 in practice.
Interpreting the Regimes
The indicator classifies systemic risk into four regimes based on AR levels.
The Extreme regime occurs when the AR exceeds 0.90. At this level, nearly all asset classes are moving together. Diversification has largely failed. Historically, this regime has coincided with major market dislocations: the 2008 financial crisis, the 2020 COVID crash, and significant correction periods. Portfolios constructed under normal correlation assumptions will experience larger drawdowns than expected.
The High regime, between 0.80 and 0.90, indicates elevated systemic risk. Correlations across asset classes are above normal. This often occurs during the build-up to stress events or during volatile periods where fear is spreading but has not reached panic levels. Risk management should be more conservative.
The Normal regime covers AR values between 0.60 and 0.80. This represents typical market conditions where some correlation exists between assets but diversification still provides meaningful benefits. Standard portfolio construction assumptions are reasonable.
The Low regime, below 0.60, indicates that assets are behaving relatively independently. Diversification is working well. Idiosyncratic factors dominate returns rather than systematic risk. This environment is favorable for active management and security selection strategies.
The Relationship to Portfolio Construction
The implications for portfolio management are significant. Modern portfolio theory assumes correlations are stable and uses historical estimates to construct efficient portfolios. The Absorption Ratio reveals that this assumption is violated precisely when it matters most.
When AR is elevated, the effective number of independent bets in a diversified portfolio shrinks. A portfolio holding stocks, bonds, commodities, and real estate might behave as if it holds only one or two positions during high AR periods. Position sizing based on normal correlation estimates will underestimate portfolio risk.
Conversely, when AR is low, true diversification opportunities expand. The same nominal portfolio provides more independent return streams. Risk can be deployed more aggressively while maintaining the same effective exposure.
Component Analysis
The indicator separately tracks equity correlations and cross-asset correlations. These components tell different stories about market structure.
Equity correlations measure coupling within the stock market. High equity correlation indicates broad risk-on or risk-off behavior where all stocks move together. This is common during both rallies and selloffs driven by macroeconomic factors. Stock pickers face headwinds when equity correlations are elevated because individual company fundamentals matter less than market beta.
Cross-asset correlations measure coupling between different asset classes. When stocks, bonds, and commodities start moving together, traditional hedges fail. The classic 60/40 stock/bond portfolio, for example, assumes negative or low correlation between equities and treasuries. When cross-asset correlation spikes, this assumption breaks down.
During the 2022 market environment, for instance, both stocks and bonds fell significantly as inflation and rate hikes affected all assets simultaneously. High cross-asset correlation warned that the usual defensive allocations would not provide their expected protection.
Mean Reversion Characteristics
Like most risk metrics, the Absorption Ratio tends to mean-revert over time. Extremely high AR readings eventually normalize as panic subsides and assets return to more independent behavior. Extremely low readings tend to rise as some level of systematic risk always reasserts itself.
The indicator tracks AR in statistical terms by calculating its Z-score relative to the trailing distribution. When AR reaches extreme Z-scores, the probability of normalization increases. This creates potential opportunities for strategies that bet on mean reversion in systemic risk.
A buy signal triggers when AR recovers from extremely elevated levels, suggesting the worst of the correlation spike may be over. A sell signal triggers when AR rises from unusually low levels, warning that complacency about diversification benefits may be excessive.
Momentum and Trend
The rate of change in AR carries information beyond the absolute level. Rapidly rising AR suggests correlations are increasing and systemic risk is building. Even if AR has not yet reached the high regime, acceleration in coupling should prompt increased vigilance.
Falling AR momentum indicates normalizing conditions. Correlations are decreasing and assets are returning to more independent behavior. This often occurs in the recovery phase following stress events.
Practical Application
For asset allocators, the AR provides guidance on how much diversification benefit to expect from a given allocation. During high AR periods, reducing overall portfolio risk makes sense because the usual diversifiers provide less protection. During low AR periods, standard or even aggressive allocations are more appropriate.
For risk managers, the AR serves as an early warning indicator. Rising AR often precedes large market moves and volatility spikes. Tightening risk limits before correlations reach extreme levels can protect capital.
For systematic traders, the AR provides a regime filter. Mean reversion strategies may work better during high AR periods when panics create overshooting. Momentum strategies may work better during low AR periods when trends can develop independently across assets.
Limitations and Considerations
The proxy methodology introduces some approximation error relative to true PCA-based AR calculations. The asset universe, while representative, does not include all possible diversifiers. Correlation estimates are inherently backward-looking and can change rapidly.
The transformation from average correlation to AR scale is calibrated to match typical published ranges but is not mathematically equivalent to the eigenvalue ratio. Users should interpret levels directionally rather than as precise measurements.
Correlation regimes can persist longer than expected. Mean reversion signals indicate elevated probability of normalization but do not guarantee timing. High AR can remain elevated throughout extended crisis periods.
References
Kritzman, M., Li, Y., Page, S., and Rigobon, R. (2011). Principal Components as a Measure of Systemic Risk. Journal of Portfolio Management, 37(4), 112-126.
Kritzman, M., and Li, Y. (2010). Skulls, Financial Turbulence, and Risk Management. Financial Analysts Journal, 66(5), 30-41.
Billio, M., Getmansky, M., Lo, A., and Pelizzon, L. (2012). Econometric Measures of Connectedness and Systemic Risk in the Finance and Insurance Sectors. Journal of Financial Economics, 104(3), 535-559.
VMDM - Volume, Momentum & Divergence Master [BullByte]VMDM - Volume, Momentum and Divergence Master
Educational Multi-Layer Market Structure Analysis System
Multi-factor divergence engine that scores RSI momentum, volume pressure, and institutional footprints into one non-repainting confluence rating (0-100).
WHAT THIS INDICATOR IS
VMDM is an educational indicator designed to teach traders how to recognize high-probability reversal and continuation patterns by analyzing four independent market dimensions simultaneously. Instead of relying on a single indicator that may produce frequent false signals, VMDM creates a confluence-based scoring system that weights multiple confirmation factors, helping you understand which setups have stronger technical backing and which are lower quality.
This is NOT a trading system or signal generator. It is a learning tool that visualizes complex market structure concepts in an accessible format for both coders and non-coders.
THE PROBLEM IT SOLVES
Most traders face these common challenges:
Challenge 1 - Indicator Overload: Running RSI, volume analysis, and divergence detection separately creates chart clutter and conflicting signals. You waste time cross-referencing multiple windows trying to determine if all factors align.
Challenge 2 - False Divergences: Standard divergence indicators trigger on every minor pivot, creating noise. Many divergences fail because they lack supporting evidence from volume or market structure.
Challenge 3 - Missed Context: A bullish RSI divergence means nothing if it occurs during weak volume or in the middle of strong distribution. Context determines quality.
Challenge 4 - Repainting Confusion: Many divergence scripts repaint, showing perfect historical signals that never actually triggered in real-time, leading to false confidence.
Challenge 5 - Institutional Pattern Recognition: Absorption zones, stop hunts, and exhaustion patterns are taught in trading education but difficult to identify systematically without manual analysis.
VMDM addresses all five challenges by combining complementary analytical layers into one transparent, non-repainting, confluence-weighted system with visual clarity.
WHY THIS SPECIFIC COMBINATION - MASHUP JUSTIFICATION
This indicator is NOT a random mashup of popular indicators. Each of the four layers serves a specific analytical purpose and together they create a complete market structure assessment framework.
THE FOUR ANALYTICAL LAYERS
LAYER 1 - RSI MOMENTUM DIVERGENCE (Trend Exhaustion Detection)
Purpose: Identifies when price momentum is weakening before price itself reverses.
Why RSI: The Relative Strength Index measures momentum on a bounded 0-100 scale, making divergence detection mathematically consistent across all assets and timeframes. Unlike raw price oscillators, RSI normalizes momentum regardless of volatility regime.
How It Contributes: Divergence between price pivots and RSI pivots reveals early momentum exhaustion. A lower price low with a higher RSI low (bullish regular divergence) signals sellers are losing strength even as price makes new lows. This is the PRIMARY signal generator in VMDM.
Limitation If Used Alone: RSI divergence by itself produces many false signals because momentum can remain weak during continued trends. It needs confirmation from volume and structural evidence.
LAYER 2 - VOLUME PRESSURE ANALYSIS (Buying vs Selling Intensity)
Purpose: Quantifies whether the current bar's volume reflects buying pressure or selling pressure based on where price closed within the bar's range.
Methodology: Instead of just measuring volume size, VMDM calculates WHERE in the bar range the close occurred. A close near the high on high volume indicates strong buying absorption. A close near the low indicates selling pressure. The calculation accounts for wick size (wicks reduce pressure quality) and uses percentile ranking over a lookback period to normalize pressure strength on a 0-100 scale.
Formula Concept:
Buy Pressure = Volume × (Close - Low) / (High - Low) × Wick Quality Factor
Sell Pressure = Volume × (High - Close) / (High - Low) × Wick Quality Factor
Net Pressure = Buy Pressure - Sell Pressure
Pressure Strength = Percentile Rank of Net Pressure over lookback period
Why Percentile Ranking: Absolute volume varies by asset and session. Percentile ranking makes 85th percentile pressure on low-volume crypto comparable to 85th percentile pressure on high-volume forex.
How It Contributes: When a bullish divergence occurs at a pivot low AND pressure strength is above 60 (strong buying), this adds 25 confluence points. It confirms that the divergence is occurring during actual accumulation, not just weak selling.
Limitation If Used Alone: Pressure analysis shows current bar intensity but cannot identify trend exhaustion or reversal timing. High buying pressure can exist during a strong uptrend with no reversal imminent.
LAYER 3 - BEHAVIORAL FOOTPRINT PATTERNS (Volume Anomaly Detection)
CRITICAL DISCLAIMER: The terms "institutional footprint," "absorption," "stop hunt," and "exhaustion" used in this indicator are EDUCATIONAL LABELS for specific price and volume behavioral patterns. These patterns are detected through technical analysis of publicly available price, volume, and bar structure data. This indicator does NOT have access to actual institutional order flow, market maker data, broker stop-loss locations, or any non-public data source. These pattern names are used because they are common terminology in trading education to describe these technical behaviors. The analysis is interpretive and based on observable price action, not privileged information.
Purpose: Detect volume anomalies and price patterns that historically correlate with potential reversal zones or trend continuation failure.
Pattern Type 1 - Absorption (Labeled as "ACCUMULATION" or "DISTRIBUTION")
Detection Criteria: Volume is more than 2x the moving average AND bar range is less than 50 percent of the average bar range.
Interpretation: High volume compressed into a tight range suggests large participants are absorbing supply (accumulation) or distribution (distribution) without allowing price to move significantly. This often precedes directional moves once absorption completes.
Visual: Colored box zone highlighting the absorption area.
Pattern Type 2 - Stop Hunt (Labeled as "BULL HUNT" or "BEAR HUNT")
Detection Criteria: Price penetrates a recent 10-bar high or low by a small margin (0.2 percent), then closes back inside the range on above-average volume (1.5x+).
Interpretation: Price briefly spikes beyond recent structure (likely triggering stop losses placed just beyond obvious levels) then reverses. This is a classic false breakout pattern often seen before reversals.
Visual: Label at the wick extreme showing hunt direction.
Pattern Type 3 - Exhaustion (Labeled as "SELL EXHAUST" or "BUY EXHAUST")
Detection Criteria: Lower wick is more than 2.5x the body size with volume above 1.8x average and RSI below 35 (sell exhaustion), OR upper wick more than 2.5x body size with volume above 1.8x average and RSI above 65 (buy exhaustion).
Interpretation: Large wicks with high volume and extreme RSI suggest aggressive buying or selling was met with equally aggressive rejection. This exhaustion often marks short-term extremes.
Visual: Label showing exhaustion type.
How These Contribute: When a divergence forms at a pivot AND one of these behavioral patterns is active, the confluence score increases by 20 points. This confirms the divergence is occurring during structural anomaly activity, not just normal price flow.
Limitation If Used Alone: These patterns can occur mid-trend and do not indicate direction without momentum context. Absorption in a strong uptrend may just be continuation accumulation.
LAYER 4 - CONFLUENCE SCORING MATRIX (Quality Weighting System)
Purpose: Translate all detected conditions into a single 0-100 quality score so you can objectively compare setups.
Scoring Breakdown:
Divergence Present: +30 points (primary signal)
Pressure Confirmation: +25 points (volume supports direction)
Behavioral Footprint Active: +20 points (structural anomaly present)
RSI Extreme: +15 points (RSI below 30 or above 70 at pivot)
Volume Spike: +10 points (current volume above 1.5x average)
Maximum Possible Score: 100 points
Why These Weights: The weights reflect reliability hierarchy based on backtesting observation. Divergence is the core signal (30 points), but without volume confirmation (25 points) many fail. Behavioral patterns add meaningful context (20 points). RSI extremes and volume spikes are secondary confirmations (15 and 10 points).
Quality Tiers:
90-100: TEXTBOOK (all factors aligned)
75-89: HIGH QUALITY (strong confluence)
60-74: VALID (meets minimum threshold)
Below 60: DEVELOPING (not displayed unless threshold lowered)
How It Contributes: The confluence score allows you to filter noise. You can set your minimum quality threshold in settings. Higher thresholds (75+) show fewer but higher-quality patterns. Lower thresholds (50-60) show more patterns but include lower-confidence setups. This teaches you to distinguish strong setups from weak ones.
Limitation: Confluence scoring is historical observation-based, not predictive guarantee. A 95-point setup can still fail. The score represents technical alignment, not future certainty.
WHY THIS COMBINATION WORKS TOGETHER
Each layer addresses a limitation in the others:
RSI Divergence identifies WHEN momentum is exhausting (timing)
Volume Pressure confirms WHETHER the exhaustion is accompanied by opposite-side accumulation (confirmation)
Behavioral Footprint shows IF structural anomalies support the reversal hypothesis (context)
Confluence Scoring weights ALL factors into an objective quality metric (filtering)
Using only RSI divergence gives you timing without confirmation. Using only volume pressure gives you intensity without directional context. Using only pattern detection gives you anomalies without trend exhaustion context. Using all four together creates a complete analytical framework where each layer compensates for the others' weaknesses.
This is not a mashup for the sake of combining indicators. It is a structured analytical system where each component has a defined role in a multi-dimensional market assessment process.
HOW TO READ THE INDICATOR - VISUAL ELEMENTS GUIDE
VMDM displays up to five visual layer types. You can enable or disable each layer independently in settings under "Visual Layers."
VISUAL LAYER 1 - MARKET STRUCTURE (Pivot Points and Lines)
What You See:
Small labels at swing highs and lows marked "PH" (Pivot High) and "PL" (Pivot Low) with horizontal dashed lines extending right from each pivot.
What It Means:
These are CONFIRMED pivots, not real-time. A pivot low appears AFTER the required right-side confirmation bars pass (default 3 bars). This creates a delay but prevents repainting. The pivot only appears once it is mathematically confirmed.
The horizontal lines represent support (from pivot lows) and resistance (from pivot highs) levels where price previously found significant rejection.
Color Coding:
Green label and line: Pivot Low (potential support)
Red label and line: Pivot High (potential resistance)
How To Use:
These pivots are the foundation for divergence detection. Divergence is only calculated between confirmed pivots, ensuring all signals are non-repainting. The lines help you see historical structure levels.
VISUAL LAYER 2 - PRESSURE ZONES (Background Color)
What You See:
Subtle background color shading on bars - light green or light red tint.
What It Means:
This visualizes volume pressure strength in real-time.
Color Coding:
Light Green Background: Pressure Strength above 70 (strong buying pressure - price closing near highs on volume)
Light Red Background: Pressure Strength below 30 (strong selling pressure - price closing near lows on volume)
No Color: Neutral pressure (pressure between 30-70)
How To Use:
When a bullish divergence pattern appears during green pressure zones, it suggests the divergence is forming during accumulation. When a bearish divergence appears during red zones, distribution is occurring. Pressure zones help you filter divergences - those forming in supportive pressure environments have higher probability.
VISUAL LAYER 3 - DIVERGENCE LINES (Dotted Connectors)
What You See:
Dotted lines connecting two pivot points (either two pivot lows or two pivot highs).
What It Means:
A divergence has been detected between those two pivots. The line connects the price pivots where RSI showed opposite behavior.
Color Coding:
Bright Green Line: Bullish divergence (regular or hidden)
Bright Red Line: Bearish divergence (regular or hidden)
How To Use:
The divergence line appears ONLY after the second pivot is confirmed (delayed by right-side confirmation bars). This is intentional to prevent repainting. When you see the line appear, it means:
For Bullish Regular Divergence:
Price made a lower low (second pivot lower than first)
RSI made a higher low (RSI at second pivot higher than first)
Interpretation: Downtrend losing momentum
For Bullish Hidden Divergence:
Price made a higher low (second pivot higher than first)
RSI made a lower low (RSI at second pivot lower than first)
Interpretation: Uptrend continuation likely (pullback within uptrend)
For Bearish Regular Divergence:
Price made a higher high (second pivot higher than first)
RSI made a lower high (RSI at second pivot lower than first)
Interpretation: Uptrend losing momentum
For Bearish Hidden Divergence:
Price made a lower high (second pivot lower than first)
RSI made a higher high (RSI at second pivot higher than first)
Interpretation: Downtrend continuation likely (bounce within downtrend)
If "Show Consolidated Analysis Label" is disabled, a small label will appear on the divergence line showing the divergence type abbreviation.
VISUAL LAYER 4 - BEHAVIORAL FOOTPRINT MARKERS
What You See:
Boxes, labels, and markers at specific bars showing pattern detection.
ABSORPTION ZONES (Boxes):
Colored rectangular boxes spanning one or more bars.
Purple Box: Accumulation absorption zone (high volume, tight range, bullish close)
Red Box: Distribution absorption zone (high volume, tight range, bearish close)
If absorption continues for multiple consecutive bars, the box extends and a counter appears in the label showing how many bars the absorption lasted.
What It Means: Large volume is being absorbed without significant price movement. This often precedes directional breakouts once the absorption phase completes.
STOP HUNT MARKERS (Labels):
Small labels below or above wicks labeled "BULL HUNT" or "BEAR HUNT" (may show bar count if consecutive).
What It Means:
BULL HUNT : Price spiked below recent lows then reversed back up on volume - likely triggered sell stops before reversing
BEAR HUNT : Price spiked above recent highs then reversed back down on volume - likely triggered buy stops before reversing
EXHAUSTION MARKERS (Labels):
Labels showing "SELL EXHAUST" or "BUY EXHAUST."
What It Means:
SELL EXHAUST : Large lower wick with high volume and low RSI - aggressive selling met with strong rejection
BUY EXHAUST : Large upper wick with high volume and high RSI - aggressive buying met with strong rejection
How To Use:
These markers help you identify WHERE structural anomalies occurred. When a divergence signal appears AT THE SAME TIME as one of these patterns, the confluence score increases. You are looking for alignment - divergence + behavioral pattern + pressure confirmation = high-quality setup.
VISUAL LAYER 5 - CONSOLIDATED ANALYSIS LABEL (Main Pattern Signal)
What You See:
A large label appearing at pivot points (or in real-time mode, at current bar) containing full pattern analysis.
Label Appearance:
Depending on your "Use Compact Label Format" setting:
COMPACT MODE (Single Line):
Example: "BULLISH REGULAR | Q:HIGH QUALITY C:82"
Breakdown:
BULLISH REGULAR: Divergence type detected
Q:HIGH QUALITY: Pattern quality tier
C:82: Confluence score (82 out of 100)
FULL MODE (Multi-Line Detailed):
Example:
PATTERN DETECTED
-------------------
BULLISH REGULAR
Quality: HIGH QUALITY
Price: Lower Low
Momentum: Higher Low
Signal: Weakening Downtrend
CONFLUENCE: 82/100
-------------------
Divergence: 30
Pressure: 25
Institutional: 20
RSI Extreme: 0
Volume: 10
Breakdown:
Top section: Pattern type and quality
Middle section: Divergence explanation (what price did vs what RSI did)
Bottom section: Confluence score with itemized breakdown showing which factors contributed
Label Position:
In Confirmed modes: Label appears AT the pivot point (delayed by confirmation bars)
In Real-time mode: Label appears at current bar as conditions develop
Label Color:
Gold: Textbook quality (90+ confluence)
Green: High quality (75-89 confluence)
Blue: Valid quality (60-74 confluence)
How To Use:
This is your primary decision-making label. When it appears:
Check the divergence type (regular divergences are reversal signals, hidden divergences are continuation signals)
Review the quality tier (textbook and high quality have better historical win rates)
Examine the confluence breakdown to see which factors are present and which are missing
Look at the chart context (trend, support/resistance, timeframe)
Use this information to assess whether the setup aligns with your strategy
The label does NOT tell you to buy or sell. It tells you a technical pattern has formed and provides the quality assessment. Your trading decision must incorporate risk management, market context, and your strategy rules.
UNDERSTANDING THE THREE DETECTION MODES
VMDM offers three signal detection modes in settings to accommodate different trading styles and learning objectives.
MODE 1: "Confluence Only (Real-Time)"
How It Works: Displays signals AS THEY DEVELOP on the current bar without waiting for pivot confirmation. The system calculates confluence score from pressure, volume, RSI extremes, and behavioral patterns. Divergence signals are NOT required in this mode.
Delay: ZERO - signals appear immediately.
Use Case: Real-time scanning for high-confluence zones without divergence requirement. Useful for intraday traders who want immediate alerts when multiple factors align.
Tradeoff: More frequent signals but includes setups without confirmed divergence. Higher false signal rate. Signals can change as the bar develops (not repainting in historical bars, but current bar updates).
Visual Behavior: Labels appear at the current bar. No divergence lines unless divergence happens to be present.
MODE 2: "Divergence + Confluence (Confirmed)" - DEFAULT RECOMMENDED
How It Works: Full system engagement. Signals appear ONLY when:
A pivot is confirmed (requires right-side confirmation bars to pass)
Divergence is detected between current pivot and previous pivot
Total confluence score meets or exceeds your minimum threshold
Delay: Equal to your "Pivot Right Bars" setting (default 3 bars). This means signals appear 3 bars AFTER the actual pivot formed.
Use Case: Highest-quality, non-repainting signals for swing traders and learners who want to study confirmed pattern completion.
Tradeoff: Delayed signals. You will not receive the signal until confirmation occurs. In fast-moving markets, price may have already moved significantly by the time the signal appears.
Visual Behavior: Labels appear at the historical pivot location (in the past). Divergence lines connect the two pivots. This is the most educational mode because it shows completed, confirmed patterns.
Non-Repainting Guarantee: Yes. Once a signal appears, it never disappears or changes.
MODE 3: "Divergence + Confluence (Relaxed)"
How It Works: Same as Confirmed mode but with adaptive thresholds. If confluence is very high (10 points above threshold), the signal may appear even if some factors are weak. If divergence is present but confluence is slightly below threshold (within 10 points), it may still appear.
Delay: Same as Confirmed mode (right-side confirmation bars).
Use Case: Slightly more signals than Confirmed mode for traders willing to accept near-threshold setups.
Tradeoff: More signals but lower average quality than Confirmed mode.
Visual Behavior: Same as Confirmed mode.
DASHBOARD GUIDE - READING THE METRICS
The dashboard appears in the corner of your chart (position selectable in settings) and provides real-time market state analysis.
You can choose between four dashboard detail levels in settings: Off, Compact, Optimized (default), Full.
DASHBOARD ROW EXPLANATIONS
ROW 1 - Header Information
Left: Current symbol and timeframe
Center: "VMDM "
Right: Version number
ROW 2 - Mode and Delay
Shows which detection mode you are using and the signal delay.
Example: "CONFIRMED | Delay: 3 bars"
This reminds you that signals in confirmed mode appear 3 bars after the pivot forms.
ROW 3 - Market Regime
Format: "TREND UP HV" or "RANGING NV"
First Part - Trend State:
TREND UP: 20 EMA above 50 EMA with strong separation
TREND DOWN: 20 EMA below 50 EMA with strong separation
RANGING: EMAs close together, low trend strength
TRANSITION: Between trending and ranging states
Second Part - Volatility State:
HV: High Volatility (current ATR more than 1.3x the 50-bar average ATR)
NV: Normal Volatility (current ATR between 0.7x and 1.3x average)
LV: Low Volatility (current ATR less than 0.7x average)
Third Column: Volatility ratio (example: "1.45x" means current ATR is 1.45 times normal)
How To Use: Regime context helps you interpret signals. Reversal divergences are more reliable in ranging or transitional regimes. Continuation divergences (hidden) are more reliable in trending regimes. High volatility means wider stops may be needed.
ROW 4 - Pressure
Shows current volume pressure state.
Format: "BUYING | ██████████░░░░░░░░░"
States:
BUYING : Pressure strength above 60 (closes near highs)
SELLING : Pressure strength below 40 (closes near lows)
NEUTRAL : Pressure strength between 40-60
Bar Visualization: Each block represents 10 percentile points. A full bar (10 filled blocks) = 100th percentile pressure.
Color: Green for buying, red for selling, gray for neutral.
How To Use: When pressure aligns with divergence direction (bullish divergence during buying pressure), confluence is stronger.
ROW 5 - Volume and RSI
Format: "1.8x | RSI 68 | OB"
First Value: Current volume ratio (1.8x = volume is 1.8 times the moving average)
Second Value: Current RSI reading
Third Value: RSI state
OB: Overbought (RSI above 70)
OS: Oversold (RSI below 30)
Blank: Neutral RSI
How To Use: Volume spikes (above 1.5x) during divergence formation add confluence. RSI extremes at pivots add confluence.
ROW 6 - Behavioral Footprint
Format: "BULL HUNT | 2 bars"
Shows the most recent behavioral pattern detected and how long ago.
States:
ACCUMULATION / DISTRIBUTION: Absorption detected
BULL HUNT / BEAR HUNT: Stop hunt detected
SELL EXHAUST / BUY EXHAUST: Exhaustion detected
SCANNING: No recent pattern
NOW: Pattern is active on current bar
How To Use: When footprint activity is recent (within 50 bars) or active now, it adds context to divergence signals forming in that area.
ROW 7 - Current Pattern
Shows the divergence type currently detected (if any).
Examples: "BULLISH REGULAR", "BEARISH HIDDEN", "Scanning..."
Quality: Shows pattern quality (TEXTBOOK, HIGH QUALITY, VALID)
How To Use: This tells you what type of signal is active. Regular divergences are reversal setups. Hidden divergences are continuation setups.
ROW 8 - Session Summary
Format: "14 events | A3 H8 E3"
First Value: Total institutional events this session
Breakdown:
A: Absorption events
H: Stop hunt events
E: Exhaustion events
How To Use: High event counts suggest an active, volatile session with frequent structural anomalies. Low counts suggest quiet, orderly price action.
ROW 9 - Confluence Score (Optimized/Full mode only)
Format: "78/100 | ████████░░"
Shows current real-time confluence score even if no pattern is confirmed yet.
How To Use: Watch this in real-time to see how close you are to pattern formation. When it exceeds your threshold and divergence forms, a signal will appear (after confirmation delay).
ROW 10 - Patterns Studied (Optimized/Full mode only)
Format: "47 patterns | 12 bars ago"
First Value: Total confirmed patterns detected since chart loaded
Second Value: How many bars since the last confirmed pattern appeared
How To Use: Helps you understand pattern frequency on your selected symbol and timeframe. If many bars have passed since last pattern, market may be trending without reversal opportunities.
ROW 11 - Bull/Bear Ratio (Optimized/Full mode only)
Format: "28:19 | BULL"
Shows count of bullish vs bearish patterns detected.
Balance:
BULL: More bullish patterns detected (suggests market has had more bullish reversals/continuations)
BEAR: More bearish patterns detected
BAL: Equal counts
How To Use: Extreme imbalances can indicate directional bias in the studied period. A heavily bullish ratio in a downtrend might suggest frequent failed rallies (bearish continuation). Context matters.
ROW 12 - Volume Ratio Detail (Optimized/Full mode only)
Shows current volume vs average volume in absolute terms.
Example: "1.4x | 45230 / 32300"
How To Use: Confirms whether current activity is above or below normal.
ROW 13 - Last Institutional Event (Full mode only)
Shows the most recent institutional pattern type and how many bars ago it occurred.
Example: "DISTRIBUTION | 23 bars"
How To Use: Tracks recency of last anomaly for context.
SETTINGS GUIDE - EVERY PARAMETER EXPLAINED
PERFORMANCE SECTION
Enable All Visuals (Master Toggle)
Default: ON
What It Does: Master kill switch for ALL visual elements (labels, lines, boxes, background colors, dashboard). When OFF, only plot outputs remain (invisible unless you open data window).
When To Change: Turn OFF on mobile devices, 1-second charts, or slow computers to improve performance. You can still receive alerts even with visuals disabled.
Impact: Dramatic performance improvement when OFF, but you lose all visual feedback.
Maximum Object History
Default: 50 | Range: 10-100
What It Does: Limits how many of each object type (labels, lines, boxes) are kept in memory. Older objects beyond this limit are deleted.
When To Change: Lower to 20-30 on fast timeframes (1-minute charts) to prevent slowdown. Increase to 100 on daily charts if you want more historical pattern visibility.
Impact: Lower values = better performance but less historical visibility. Higher values = more history visible but potential slowdown on fast timeframes.
Alert Cooldown (Bars)
Default: 5 | Range: 1-50
What It Does: Minimum number of bars that must pass before another alert of the same type can fire. Prevents alert spam when multiple patterns form in quick succession.
When To Change: Increase to 20+ on 1-minute charts to reduce noise. Decrease to 1-2 on daily charts if you want every pattern alerted.
Impact: Higher cooldown = fewer alerts. Lower cooldown = more alerts.
USER EXPERIENCE SECTION
Show Enhanced Tooltips
Default: ON
What It Does: Enables detailed hover-over tooltips on labels and visual elements.
When To Change: Turn OFF if you encounter Pine Script compilation errors related to tooltip arguments (rare, platform-specific issue).
Impact: Minimal. Just adds helpful hover text.
MARKET STRUCTURE DETECTION SECTION
Pivot Left Bars
Default: 3 | Range: 2-10
What It Does: Number of bars to the LEFT of the center bar that must be higher (for pivot low) or lower (for pivot high) than the center bar for a pivot to be valid.
Example: With value 3, a pivot low requires the center bar's low to be lower than the 3 bars to its left.
When To Change:
Increase to 5-7 on noisy timeframes (1-minute charts) to filter insignificant pivots
Decrease to 2 on slow timeframes (daily charts) to catch more pivots
Impact: Higher values = fewer, more significant pivots = fewer signals. Lower values = more frequent pivots = more signals but more noise.
Pivot Right Bars
Default: 3 | Range: 2-10
What It Does: Number of bars to the RIGHT of the center bar that must pass for confirmation. This creates the non-repainting delay.
Example: With value 3, a pivot is confirmed 3 bars AFTER it forms.
When To Change:
Increase to 5-7 for slower, more confirmed signals (better for swing trading)
Decrease to 2 for faster signals (better for intraday, but still non-repainting)
Impact: Higher values = longer delay but more reliable confirmation. Lower values = faster signals but less confirmation. This setting directly controls your signal delay in Confirmed and Relaxed modes.
Minimum Confluence Score
Default: 60 | Range: 40-95
What It Does: The threshold score required for a pattern to be displayed. Patterns with confluence scores below this threshold are not shown.
When To Change:
Increase to 75+ if you only want high-quality textbook setups (fewer signals)
Decrease to 50-55 if you want to see more developing patterns (more signals, lower average quality)
Impact: This is your primary signal filter. Higher threshold = fewer, higher-quality signals. Lower threshold = more signals but includes weaker setups. Recommended starting point is 60-65.
TECHNICAL PERIODS SECTION
RSI Period
Default: 14 | Range: 5-50
What It Does: Lookback period for RSI calculation.
When To Change:
Decrease to 9-10 for faster, more sensitive RSI that detects shorter-term momentum changes
Increase to 21-28 for slower, smoother RSI that filters noise
Impact: Lower values make RSI more volatile (more frequent extremes and divergences). Higher values make RSI smoother (fewer but more significant divergences). 14 is industry standard.
Volume Moving Average Period
Default: 20 | Range: 10-200
What It Does: Lookback period for calculating average volume. Current volume is compared to this average to determine volume ratio.
When To Change:
Decrease to 10-14 for shorter-term volume comparison (more sensitive to recent volume changes)
Increase to 50-100 for longer-term volume comparison (smoother, less sensitive)
Impact: Lower values make volume ratio more volatile. Higher values make it more stable. 20 is standard.
ATR Period
Default: 14 | Range: 5-100
What It Does: Lookback period for Average True Range calculation used for volatility measurement and label positioning.
When To Change: Rarely needs adjustment. Use 7-10 for faster volatility response, 21-28 for slower.
Impact: Affects volatility ratio calculation and visual label spacing. Minimal impact on signals.
Pressure Percentile Lookback
Default: 50 | Range: 10-300
What It Does: Lookback period for calculating volume pressure percentile ranking. Your current pressure is ranked against the pressure of the last X bars.
When To Change:
Decrease to 20-30 for shorter-term pressure context (more responsive to recent changes)
Increase to 100-200 for longer-term pressure context (smoother rankings)
Impact: Lower values make pressure strength more sensitive to recent bars. Higher values provide more stable, long-term pressure assessment. Capped at 300 for performance reasons.
SIGNAL DETECTION SECTION
Signal Detection Mode
Default: "Divergence + Confluence (Confirmed)"
Options:
Confluence Only (Real-time)
Divergence + Confluence (Confirmed)
Divergence + Confluence (Relaxed)
What It Does: Selects which detection logic mode to use (see "Understanding The Three Detection Modes" section above).
When To Change: Use Confirmed for learning and non-repainting signals. Use Real-time for live scanning without divergence requirement. Use Relaxed for slightly more signals than Confirmed.
Impact: Fundamentally changes when and how signals appear.
VISUAL LAYERS SECTION
All toggles default to ON. Each controls visibility of one visual layer:
Show Market Structure: Pivot markers and support/resistance lines
Show Pressure Zones: Background color shading
Show Divergence Lines: Dotted lines connecting pivots
Show Institutional Footprint Markers: Absorption boxes, hunt labels, exhaustion labels
Show Consolidated Analysis Label: Main pattern detection label
Use Compact Label Format
Default: OFF
What It Does: Switches consolidated label between single-line compact format and multi-line detailed format.
When To Change: Turn ON if you find full labels too large or distracting.
Impact: Visual clarity vs. information density tradeoff.
DASHBOARD SECTION
Dashboard Mode
Default: "Optimized"
Options: Off, Compact, Optimized, Full
What It Does: Controls how much information the dashboard displays.
Off: No dashboard
Compact: 8 rows (essential metrics only)
Optimized: 12 rows (recommended balance)
Full: 13 rows (every available metric)
Dashboard Position
Default: "Top Right"
Options: Top Right, Top Left, Bottom Right, Bottom Left
What It Does: Screen corner where dashboard appears.
HOW TO USE VMDM - PRACTICAL WORKFLOW
STEP 1 - INITIAL SETUP
Add VMDM to your chart
Select your detection mode (Confirmed recommended for learning)
Set your minimum confluence score (start with 60-65)
Adjust pivot parameters if needed (default 3/3 is good for most timeframes)
Enable the visual layers you want to see
STEP 2 - CHART ANALYSIS
Let the indicator load and analyze historical data
Review the patterns that appear historically
Examine the confluence scores - notice which patterns had higher scores
Observe which patterns occurred during supportive pressure zones
Notice the divergence line connections - understand what price vs RSI did
STEP 3 - PATTERN RECOGNITION LEARNING
When a consolidated analysis label appears:
Read the divergence type (regular or hidden, bullish or bearish)
Check the quality tier (textbook, high quality, or valid)
Review the confluence breakdown - which factors contributed
Look at the chart context - where is price relative to structure, trend, etc.
Observe the behavioral footprint markers nearby - do they support the pattern
STEP 4 - REAL-TIME MONITORING
Watch the dashboard for real-time regime and pressure state
Monitor the current confluence score in the dashboard
When it approaches your threshold, be alert for potential pattern formation
When a new pattern appears (after confirmation delay), evaluate it using the workflow above
Use your trading strategy rules to decide if the setup aligns with your criteria
STEP 5 - POST-PATTERN OBSERVATION
After a pattern appears:
Mark the level on your chart
Observe what price does after the pattern completes
Did price respect the reversal/continuation signal
What was the confluence score of patterns that worked vs. those that failed
Learn which quality tiers and confluence levels produce better results on your specific symbol and timeframe
RECOMMENDED TIMEFRAMES AND ASSET CLASSES
VMDM is timeframe-agnostic and works on any asset with volume data. However, optimal performance varies:
BEST TIMEFRAMES
15-Minute to 1-Hour: Ideal balance of signal frequency and reliability. Pivot confirmation delay is acceptable. Sufficient volume data for pressure analysis.
4-Hour to Daily: Excellent for swing trading. Very high-quality signals. Lower frequency but higher significance. Recommended for learning because patterns are clearer.
1-Minute to 5-Minute: Works but requires adjustment. Increase pivot bars to 5-7 for filtering. Decrease max object history to 30 for performance. Expect more noise.
Weekly/Monthly: Works but very infrequent signals. Increase confluence threshold to 70+ to ensure only major patterns appear.
BEST ASSET CLASSES
Forex Majors: Excellent volume data and clear trends. Pressure analysis works well.
Crypto (Major Pairs): Good volume data. High volatility makes divergences more pronounced. Works very well.
Stock Indices (SPY, QQQ, etc.): Excellent. Clean price action and reliable volume.
Individual Stocks: Works well on high-volume stocks. Low-volume stocks may produce unreliable pressure readings.
Commodities (Gold, Oil, etc.): Works well. Clear trends and reactions.
WHAT THIS INDICATOR CANNOT DO - LIMITATIONS
LIMITATION 1 - It Does Not Predict The Future
VMDM identifies when technical conditions align historically associated with potential reversals or continuations. It does not predict what will happen next. A textbook 95-confluence pattern can still fail if fundamental events, news, or larger timeframe structure override the setup.
LIMITATION 2 - Confirmation Delay Means You Miss Early Entry
In Confirmed and Relaxed modes, the non-repainting design means you receive signals AFTER the pivot is confirmed. Price may have already moved significantly by the time you receive the signal. This is the tradeoff for non-repainting reliability. You can use Real-time mode for faster signals but sacrifice divergence confirmation.
LIMITATION 3 - It Does Not Tell You Position Sizing or Risk Management
VMDM provides technical pattern analysis. It does not calculate stop loss levels, take profit targets, or position sizing. You must apply your own risk management rules. Never risk more than you can afford to lose based on a technical signal.
LIMITATION 4 - Volume Pressure Analysis Requires Reliable Volume Data
On assets with thin volume or unreliable volume reporting, pressure analysis may be inaccurate. Stick to major liquid assets with consistent volume data.
LIMITATION 5 - It Cannot Detect Fundamental Events
VMDM is purely technical. It cannot predict earnings reports, central bank decisions, geopolitical events, or other fundamental catalysts that can override technical patterns.
LIMITATION 6 - Divergence Requires Two Pivots
The indicator cannot detect divergence until at least two pivots of the same type have formed. In strong trends without pullbacks, you may go long periods without signals.
LIMITATION 7 - Institutional Pattern Names Are Interpretive
The behavioral footprint patterns are named using common trading education terminology, but they are detected through technical analysis, not actual institutional data access. The patterns are interpretations based on price and volume behavior.
CONCEPT FOUNDATION - WHY THIS APPROACH WORKS
MARKET PRINCIPLE 1 - Momentum Divergence Precedes Price Reversal
Price is the final output of market forces, but momentum (the rate of change in those forces) shifts first. When price makes a new low but the momentum behind that move is weaker (higher RSI low), it signals that sellers are losing strength even though they temporarily pushed price lower. This precedes reversal. This is a fundamental principle in technical analysis taught by Charles Dow, widely observed in market behavior.
MARKET PRINCIPLE 2 - Volume Reveals Conviction
Price can move on low volume (low conviction) or high volume (high conviction). When price makes a new low on declining volume while RSI shows improving momentum, it suggests the new low is not confirmed by participant conviction. Adding volume pressure analysis to momentum divergence adds a confirmation layer that filters false divergences.
MARKET PRINCIPLE 3 - Anomalies Mark Structural Extremes
When volume spikes significantly but range contracts (absorption), or when price spikes beyond structure then reverses (stop hunt), or when aggressive moves are met with large-wick rejection (exhaustion), these anomalies often mark short-term extremes. Combining these structural observations with momentum analysis creates context.
MARKET PRINCIPLE 4 - Confluence Improves Probability
No single technical factor is reliable in isolation. RSI divergence alone fails frequently. Volume analysis alone cannot time entries. Combining multiple independent factors into a weighted system increases the probability that observed patterns have structural significance rather than random noise.
THE EDUCATIONAL VALUE
By visualizing all four layers simultaneously and breaking down the confluence scoring transparently, VMDM teaches you to think in terms of multi-dimensional analysis rather than single-indicator reliance. Over time, you will learn to recognize these patterns manually and understand which combinations produce better results on your traded assets.
INSTITUTIONAL TERMINOLOGY - IMPORTANT CLARIFICATION
This indicator uses the following terms that are common in trading education:
Institutional Footprint
Absorption (Accumulation / Distribution)
Stop Hunt
Exhaustion
CRITICAL DISCLAIMER:
These terms are EDUCATIONAL LABELS for specific price action and volume behavior patterns detected through technical analysis of publicly available chart data (open, high, low, close, volume). This indicator does NOT have access to:
Actual institutional order flow or order book data
Market maker positions or intentions
Broker stop-loss databases
Non-public trading data
Proprietary institutional information
The patterns labeled as "institutional footprint" are interpretations based on observable price and volume behavior that educational trading literature often associates with potential large-participant activity. The detection is algorithmic pattern recognition, not privileged data access.
When this indicator identifies "absorption," it means it detected high volume within a small range - a condition that MAY indicate large orders being filled but is not confirmation of actual institutional participation.
When it identifies a "stop hunt," it means price briefly penetrated a structural level then reversed - a pattern that MAY have triggered stop losses but is not confirmation that stops were specifically targeted.
When it identifies "exhaustion," it means high volume with large rejection wicks - a pattern that MAY indicate aggressive participation meeting strong opposition but is not confirmation of institutional involvement.
These are technical analysis interpretations, not factual statements about market participant identity or intent.
DISCLAIMER AND RISK WARNING
EDUCATIONAL PURPOSE ONLY
This indicator is designed as an educational tool to help traders learn to recognize technical patterns, understand multi-factor analysis, and practice systematic market observation. It is NOT a trading system, signal service, or financial advice.
NO PERFORMANCE GUARANTEE
Past pattern behavior does not guarantee future results. A pattern that historically preceded price movement in one direction may fail in the future due to changing market conditions, fundamental events, or random variance. Confluence scores reflect historical technical alignment, not future certainty.
TRADING INVOLVES SUBSTANTIAL RISK
Trading financial instruments involves substantial risk of loss. You can lose more than your initial investment. Never trade with money you cannot afford to lose. Always use proper risk management including stop losses, position sizing, and portfolio diversification.
NO PREDICTIVE CLAIMS
This indicator does NOT predict future price movement. It identifies when technical conditions align in patterns that historically have been associated with potential reversals or continuations. Market behavior is probabilistic, not deterministic.
BACKTESTING LIMITATIONS
If you backtest trading strategies using this indicator, ensure you account for:
Realistic commission costs
Realistic slippage (difference between signal price and actual fill price)
Sufficient sample size (minimum 100 trades for statistical relevance)
Reasonable position sizing (risking no more than 1-2 percent of account per trade)
The confirmation delay inherent in the indicator (you cannot enter at the exact pivot in Confirmed mode)
Backtests that do not account for these factors will produce unrealistic results.
AUTHOR LIABILITY
The author (BullByte) is not responsible for any trading losses incurred using this indicator. By using this indicator, you acknowledge that all trading decisions are your sole responsibility and that you understand the risks involved.
NOT FINANCIAL ADVICE
Nothing in this indicator, its code, its description, or its visual outputs constitutes financial, investment, or trading advice. Consult a licensed financial advisor before making investment decisions.
FREQUENTLY ASKED QUESTIONS
Q: Why do signals appear in the past, not at the current bar
A: In Confirmed and Relaxed modes, signals appear at confirmed pivots, which requires waiting for right-side confirmation bars (default 3). This creates a delay but prevents repainting. Use Real-time mode if you want current-bar signals without pivot confirmation.
Q: Can I use this for automated trading
A: You can create alert-based automation, but understand that Confirmed mode signals appear AFTER the pivot with delay, so your entry will not be at the pivot price. Real-time mode signals can change as the current bar develops. Automation requires careful consideration of these factors.
Q: How do I know which confluence score to use
A: Start with 60. Observe which patterns work on your symbol/timeframe. If too many false signals, increase to 70-75. If too few signals, decrease to 55. Quality vs. quantity tradeoff.
Q: Do regular divergences mean I should enter a reversal trade immediately
A: No. Regular divergences indicate momentum exhaustion, which is a WARNING sign that trend may reverse, not a confirmation that it will. Use confluence score, market context, support/resistance, and your strategy rules to make entry decisions. Many divergences fail.
Q: What's the difference between regular and hidden divergence
A: Regular divergence = price and momentum move in opposite directions at extremes = potential reversal signal. Hidden divergence = price and momentum move in opposite directions during pullbacks = potential continuation signal. Hidden divergence suggests the pullback is just a correction within the larger trend.
Q: Why does the pressure zone color sometimes conflict with the divergence direction
A: Pressure is real-time current bar analysis. Divergence is confirmed pivot analysis from the past. They measure different things at different times. A bullish divergence confirmed 3 bars ago might appear during current selling pressure. This is normal.
Q: Can I use this on stocks without volume data
A: No. Volume is required for pressure analysis and behavioral pattern detection. Use only on assets with reliable volume reporting.
Q: How often should I expect signals
A: Depends on timeframe and settings. Daily charts might produce 5-10 signals per month. 1-hour charts might produce 20-30. 15-minute charts might produce 50-100. Adjust confluence threshold to control frequency.
Q: Can I modify the code
A: Yes, this is open source. You can modify for personal use. If you publish a modified version, please credit the original and ensure your publication meets TradingView guidelines.
Q: What if I disagree with a pattern's confluence score
A: The scoring weights are based on general observations and may not suit your specific strategy or asset. You can modify the code to adjust weights if you have data-driven reasons to do so.
Final Notes
VMDM - Volume, Momentum and Divergence Master is an educational multi-layer market analysis system designed to teach systematic pattern recognition through transparent, confluence-weighted signal detection. By combining RSI momentum divergence, volume pressure quantification, behavioral footprint pattern recognition, and quality scoring into a unified framework, it provides a comprehensive learning environment for understanding market structure.
Use this tool to develop your analytical skills, understand how multiple technical factors interact, and learn to distinguish high-quality setups from noise. Remember that technical analysis is probabilistic, not predictive. No indicator replaces proper education, risk management, and trading discipline.
Trade responsibly. Learn continuously. Risk only what you can afford to lose.
-BullByte
OBV + WaveTrend Volume Scalper [GratefulFutures]This script is a combination script of three different strategies that provides buy and sell signals based on the change of volume with momentum confirmations.
Sources used:
This script relies on the outstanding scripts of the great script writer LazyBear: LazyBear
The following scripts were used in this publication:
1. A modified "On-Balance Volume Oscillator" modified from LazyBear's original script:
2. Wavetrend Oscillator with crosses, Author: LazyBear
3. Squeeze Momentum Oscillator, Author: LazyBear
This script functions based on the following criteria being true:
1. On balance volume oscillator turning from negative to positive (buy) or positive to negative (sell)
2. Squeeze Momentum value is increasing (buy) or decreasing (sell)
3. Wavetrend 1 (wt1) is greater than wavetrend 2 (wt2) (buy)/ Wavetrend 1 (wt1) is less than wavetrend 2 (wt2) (sell)
By combining these factors the indicator is able to signal exactly when net buying turns to net selling (OBV) and when this change is most advantageous to continue based on the momentum and price action of the underlying asset (SQMOMO and Wavetrend).
This allows you to pair volume and price action for a powerful tool to identify where price will reverse or continue providing exceptional entries for short term trades, especially when combined with other aspects such as support and resistance, or volume profile.
How to use:
Simply adjust the settings to your preference and read the given signals as generated.
Settings
There are multiple ways to tune the signals generated. It is set standard for my preferred use on a 1 minute chart.
OBV Oscillator Settings
The first 4 dropdowns in the Inputs section tune the On Balance Volume Oscillator (OBVO) portion of the indicator. You can choose if you want it to calculate based on close, open, high, low, or other value.
The most impactful in the entire settings is going to be the length and smoothing of the OBVO EMA. Making this number lower increasing the sensitivity to changes in volume, making the signals come quicker but is more susceptible to quick fluctuations. A value of between (5-20) is reasonable for the OBVO EMA length. There is a separate smoothing factor titled OBV Smoothing Length and below that, OBV Smoothing Type , a value of (2) is standard with "SMA" for smoothing type with a value of between 2-10 being reasonable. You may also play with these values to see what you like for your trading style.
Wavetrend Settings
The next 3 options are to modify the wavetrend portion of the indicator. I do not modify these from standard, and feel that they work appropriately on all time frames at the following values: n1 length (10), n2 length (20), Wavetrend Signal SMA length (4)
Squeeze Momentum Settings
The following 5 options through the end modify the Squeeze momentum portion of the indicator. The only one that modifies the signals generated is the KC Length , Making this number lower increasing the sensitivity to changes in price action, making the signals come quicker but is more susceptible to quick fluctuations. A value of between (18-25) is reasonable for KC Length .
Style Setting
You may select if you want to see the buy and sell signals. The following 5 options Raw OBV Osc through Squeeze Momentum allow you to see where each specific requirement was met, posted as a vertical line, but for live use it is recommended to turn all of these vertical lines off and only use the buy and sell signals.
Time Frames:
While this script is most effective on shorter time frames (1 minute for scalping and daytrading) it is also viable to use it on longer timeframes, due to the nature of its components being independent of time frame.
Examples of use - (Green and red vertical lines are for visualization purpose and are not part of the script)
SPY 1 Minute (Factory Settings):
SPX 15 minutes (Factory Settings):
Considerations
This script is meant primarily for short term trading, trades on the basis of seconds to minutes primarily. While they can be a good indication of volume lining up with momentum, it is always wise to use them in combination with other factors such as support, resistance, market structure, volume levels, or the many other techniques out there...
As Always... Happy Trading.
-Not_A_Mad_Scientist (GreatfulFutures Trade University)
VB Finviz-style MTF Screener📊 VB Multi-Timeframe Stock Screener (Daily + 4H + 1H)
A structured, high-signal stock screener that blends Daily fundamentals, 4H trend confirmation, and 1H entry timing to surface strong trading opportunities with institutional discipline.
🟦 1. Daily Screener — Core Stock Selection
All fundamental and structural filters run strictly on Daily data for maximum stability and signal quality.
Daily filters include:
📈 Average Volume & Relative Volume
💲 Minimum Price Threshold
📊 Beta vs SPY
🏢 Market Cap (Billions)
🔥 ATR Liquidity Filter
🧱 Float Requirements
📘 Price Above Daily SMA50
🚀 Minimum Gap-Up Condition
This layer acts like a Finviz-style engine, identifying stocks worth trading before momentum or timing is considered.
🟩 2. 4H Trend Confirmation — Momentum Check
Once a stock passes the Daily screen, the 4-hour timeframe validates trend strength:
🔼 Price above 4H MA
📈 MA pointing upward
This removes structurally good stocks that are not in a healthy trend.
🟧 3. 1H Entry Alignment — Timing Layer
The Hourly timeframe refines near-term timing:
🔼 Price above 1H MA
📉 Short-term upward movement detected
This step ensures the stock isn’t just good on paper—it’s moving now.
🧪 MTF Debug Table (Your Transparency Engine)
A live diagnostic table shows:
All Daily values
All 4H checks
All 1H checks
Exact PASS/FAIL per condition
Perfect for tuning thresholds or understanding why a ticker qualifies or fails.
🎯 Who This Screener Is For
Swing traders
Momentum/trend traders
Systematic and rules-based traders
Traders who want clean, multi-timeframe alignment
By combining Daily fundamentals, 4H trend structure, and 1H momentum, this screener filters the market down to the stocks that are strong, aligned, and ready.
Sector Rotation - Risk Preference Indicator# Sector Rotation - Risk Preference Indicator
## Overview
This indicator measures market risk appetite by comparing the relative strength between **Aggressive** and **Defensive** sectors. It provides a clean, single-line visualization to help traders identify market sentiment shifts and potential trend reversals.
## How It Works
The indicator calculates a **Bullish/Bearish Ratio** by dividing the average price of aggressive sector ETFs by defensive sector ETFs, then normalizing to a baseline of 100.
**Formula:**
- Ratio = (Aggressive Sectors Average / Defensive Sectors Average) × 100
**Interpretation:**
- **Ratio > 100**: Risk-on sentiment (Aggressive sectors outperforming Defensive)
- **Ratio < 100**: Risk-off sentiment (Defensive sectors outperforming Aggressive)
- **Ratio ≈ 100**: Neutral (Both sector groups performing equally)
## Default Sectors
**Defensive Sectors** (Safe havens during uncertainty):
- XLP - Consumer Staples Select Sector SPDR Fund
- XLU - Utilities Select Sector SPDR Fund
- XLV - Health Care Select Sector SPDR Fund
**Aggressive Sectors** (Growth-oriented, higher risk):
- XLK - Technology Select Sector SPDR Fund
- XBI - SPDR S&P Biotech ETF
- XRT - SPDR S&P Retail ETF
## Features
✅ **Fully Customizable Sectors** - Choose any ETFs/tickers for each sector group
✅ **Smoothing Control** - Adjustable SMA period to reduce noise (default: 2)
✅ **Clean Visualization** - Single blue line for easy interpretation
✅ **Multi-timeframe Support** - Works on any timeframe
✅ **Lightweight** - Minimal calculations for fast performance
## Settings
### Defensive Sectors Group
- **Defensive Sector 1**: First defensive ETF ticker (default: XLP)
- **Defensive Sector 2**: Second defensive ETF ticker (default: XLU)
- **Defensive Sector 3**: Third defensive ETF ticker (default: XLV)
### Aggressive Sectors Group
- **Aggressive Sector 1**: First aggressive ETF ticker (default: XLK)
- **Aggressive Sector 2**: Second aggressive ETF ticker (default: XBI)
- **Aggressive Sector 3**: Third aggressive ETF ticker (default: XRT)
### Display Settings
- **Smoothing Length**: SMA period for ratio smoothing (default: 2, range: 1-50)
- Lower values = More responsive but noisier
- Higher values = Smoother but more lagging
## Use Cases
### 1. Market Regime Identification
- **Rising Ratio (trending up)** → Bull market / Risk-on environment
- Aggressive sectors leading, investors chasing growth
- Favorable for long positions in tech, growth stocks
- **Falling Ratio (trending down)** → Bear market / Risk-off environment
- Defensive sectors leading, investors seeking safety
- Consider defensive positioning or short opportunities
### 2. Divergence Analysis
- **Bullish Divergence**: Price makes new lows but ratio rises
- Suggests underlying strength returning
- Potential market bottom forming
- **Bearish Divergence**: Price makes new highs but ratio falls
- Suggests weakening momentum
- Potential market top forming
### 3. Trend Confirmation
- **Strong uptrend + Rising ratio** → Confirmed bullish trend
- **Strong downtrend + Falling ratio** → Confirmed bearish trend
- **Uptrend + Falling ratio** → Weakening trend, watch for reversal
- **Downtrend + Rising ratio** → Potential trend exhaustion
## Best Practices
⚠️ **Timeframe Selection**
- Recommended: Daily, 4H, 1H for cleaner signals
- Lower timeframes (15m, 5m) may produce noisy signals
⚠️ **Complementary Analysis**
- Use alongside price action and volume analysis
- Combine with support/resistance levels
- Not designed as a standalone trading system
⚠️ **Market Conditions**
- Most effective in trending markets
- Less reliable during ranging/consolidation periods
- Works best in liquid, well-traded sectors
⚠️ **Customization Tips**
- Can substitute with international sectors (EWU, EWZ, etc.)
- Can use crypto sectors (DeFi vs Layer1, etc.)
- Adjust smoothing based on trading style (day trading = 2-5, swing = 10-20)
## Display Options
### Default View (overlay=false)
- Shows in separate pane below chart
- Dedicated scale for ratio values
### Alternative View
- Can be moved to main chart pane (drag indicator)
I typically overlay this indicator on the SPY daily chart to observe divergences. I don’t focus on specific values but rather on the direction of the trend.
The author is not responsible for any trading losses incurred using this indicator.
## Support & Feedback
For questions, feature requests, or bug reports:
- Comment below
- Send a private message
- Check for updates regularly
If you find this indicator useful, please:
- ⭐ Leave a like/favorite
- 💬 Share your experience in comments
- 📊 Share charts showing interesting patterns
Adaptive Trend Navigator [ATH Filter & Risk Engine]Description:
This strategy implements a systematic Trend Following approach designed to capture major moves while actively protecting capital during severe bear markets. It combines a classic Moving Average "Fan" logic with two advanced risk management layers: a 4-Stage Dynamic Stop Loss and a macro-economic "Circuit Breaker" filter.
Core Concepts:
1. Trend Identification (Entry Logic) The script uses a cascade of Simple Moving Averages (SMA 25, 50, 100, 200) to identify the maturity of a trend.
Entries are triggered by specific crossovers (e.g., SMA 25 crossing SMA 50) or by breaking above the previous trade's high ("High-Water Mark" Re-Entry).
2. The "Circuit Breaker" (Crash Protection) To prevent trading during historical market collapses (like 2000 or 2008), the strategy monitors the Nasdaq 100 (QQQ) as a global benchmark:
Normal Regime: If the market is within 20% of its All-Time High, the strategy operates normally.
Crisis Regime: If the QQQ falls more than 20% from its ATH, the "Circuit Breaker" activates (Visualized by a Red Background).
Recovery Rule: In a Crisis Regime, new long positions are blocked unless the QQQ reclaims its SMA 200. This filters out "bull traps" in secular bear markets.
3. 4-Stage Risk Engine (Exit Logic) Once in a trade, the risk management adapts to the position's performance:
Stage 1: Fixed initial Stop Loss (default 10%) for breathing room.
Stage 2: Moves to Break-Even area once the price rises 12%.
Stage 3: Tightens to a trailing stop (8%) after 25% profit.
Stage 4: Maximizes gains with a tight trailing stop (5%) during parabolic moves (>40% profit).
Visual Guide:
SMAs: 25/50/100/200 period lines for trend visualization.
Red Background: Indicates the "Crisis Regime" where trading is halted due to broad market weakness.
Blue Background: Indicates a "Recovery Phase" (Crisis is active, but market is above SMA 200).
Red Line: Shows the dynamic Stop Loss level for active positions.
Settings: All parameters (SMA lengths, Drawdown threshold, Risk Stages) are fully customizable. The QQQ benchmark ticker can also be changed to SPY or other indices depending on the asset class traded.
MA200 Deviation Percentile200-Day MA Deviation with Dynamic Thresholds
OVERVIEW
This indicator measures price deviation from the 200-day moving average as a percentage, with dynamically calculated overbought/oversold thresholds based on historical percentiles.
Best suited for broad market indices (SPY, QQQ, IWM, etc.) where the 200-day MA serves as a reliable long-term trend indicator. Individual stocks may exhibit more erratic behavior around this level.
CALCULATION
Deviation (%) = (Close - 200MA) / 200MA x 100
Dynamic thresholds are derived from actual historical distribution rather than assuming normal distribution:
- Overbought threshold = 97.5th percentile of historical deviations
- Oversold threshold = 2.5th percentile of historical deviations
SETTINGS
MA Length (default: 200)
Moving average period.
Lookback Period (default: 1260)
Historical window for threshold calculation. 1260 bars approximates 5 years of daily data.
Threshold Percentile (default: 5%)
Two-tailed threshold. 5% places overbought/oversold boundaries at the 97.5th and 2.5th percentiles respectively.
INTERPRETATION
Deviation Value
- Positive: Price trading above 200MA
- Negative: Price trading below 200MA
- Magnitude indicates extent of deviation
Percentile Ranking (0-100%)
- Shows where current deviation ranks historically
- Above 90%: Historically elevated
- Below 10%: Historically depressed
Dynamic Threshold Lines
- Red line: Upper boundary based on historical distribution
- Green line: Lower boundary based on historical distribution
- These adapt automatically to each asset's volatility characteristics
APPLICATION
Mean Reversion
Extreme deviations tend to normalize over time. When deviation exceeds dynamic thresholds, probability of mean reversion increases.
Trend Assessment
Sustained positive/negative deviation confirms trend direction. Zero-line crossovers may signal trend changes.
NOTES
- Optimized for daily timeframe on market indices
- Requires sufficient historical data (minimum equal to lookback period)
- Extreme readings do not guarantee immediate reversals
- Use in conjunction with other analysis methods
Mebane Faber GTAA 5In 2007, Mebane Faber published research that challenged the conventional wisdom of buy-and-hold investing. His paper, titled "A Quantitative Approach to Tactical Asset Allocation" and published in the Journal of Wealth Management, demonstrated that a simple timing mechanism could reduce portfolio volatility and drawdowns while maintaining competitive returns (Faber, 2007). This indicator implements his Global Tactical Asset Allocation strategy, known as GTAA5, following the original methodology.
The core insight of Faber's research stems from a century of market data. By analyzing asset class performance from 1901 onwards, Faber found that a ten-month simple moving average served as an effective trend filter across major asset classes. When an asset trades above its ten-month moving average, it tends to continue its upward trajectory; when it falls below, significant drawdowns often follow (Faber, 2007, pp. 12-16). This observation aligns with momentum research by Jegadeesh and Titman (1993), who documented that intermediate-term momentum persists across equity markets.
The GTAA5 strategy allocates capital equally across five diversified asset classes: domestic equities (SPY), international developed markets (EFA), aggregate bonds (AGG), commodities (DBC), and real estate investment trusts (VNQ). Each asset receives a twenty percent allocation when trading above its ten-month moving average. When an asset falls below this threshold, its allocation moves to short-term treasury bills (SHY), creating a dynamic cash position that scales with market risk (Cambria Investment Management, 2013).
The strategy's historical performance during market crises illustrates its function. During the 2008 financial crisis, traditional sixty-forty portfolios experienced drawdowns exceeding forty percent. The GTAA5 strategy limited losses to approximately twelve percent by reducing equity exposure as prices declined below their moving averages (Faber, 2013). This asymmetric return profile represents the strategy's primary characteristic.
This implementation uses monthly closing prices retrieved via request.security() to calculate the ten-month simple moving average. This distinction matters, as approximations using daily data (such as a 200-day moving average) can generate different signals during volatile periods. Monthly data ensures the indicator produces signals consistent with published academic research.
The indicator provides position monitoring, automatic rebalancing detection on either the first or last trading day of each month, and share calculations based on user-defined capital. A dashboard displays current trend status for each asset class, target versus actual weightings, and trade instructions for rebalancing. Performance metrics including annualized volatility and Sharpe ratio provide ongoing risk assessment.
Several limitations warrant acknowledgment. First, the strategy rebalances monthly, meaning it cannot respond to intra-month market crashes. Second, transaction costs and taxes from monthly rebalancing may reduce net returns for taxable accounts. Third, the ten-month lookback period, while historically robust, offers no guarantee of future effectiveness. As Ilmanen (2011) notes in "Expected Returns", all timing strategies face the risk of regime change, where historical relationships break down.
This indicator serves educational purposes and portfolio monitoring. It does not constitute financial advice.
References:
Cambria Investment Management (2013). Global Tactical Asset Allocation: An Introduction to the Approach. Research Report, Los Angeles.
Faber, M.T. (2007). A Quantitative Approach to Tactical Asset Allocation. Journal of Wealth Management, Spring 2007, pp. 9-79.
Faber, M.T. (2013). Global Asset Allocation: A Survey of the World's Top Asset Allocation Strategies. Cambria Investment Management, Los Angeles.
Ilmanen, A. (2011). Expected Returns: An Investor's Guide to Harvesting Market Rewards. John Wiley and Sons, Chichester.
Jegadeesh, N. and Titman, S. (1993). Returns to Buying Winners and Selling Losers: Implications for Stock Market Efficiency. Journal of Finance, 48(1), pp. 65-91.
Classic Wave: The Easy WayClassic Wave is a simple strategy with few rules and no over-optimization. Despite its simplicity, it is backed by a nearly century-long historical track record, delivering excellent returns on the weekly chart of the SPX (TVC).
I also recommend observing its strong performance on the SPY (weekly), which is the perfect instrument for executing this strategy with futures in the future.
Strategy Rules and Parameters
When a bullish candle closes above the 20-period EMA, we place the stop-loss below the low of that candle and target a risk-reward ratio of 1:1.
A second, more profitable variant is to change the risk-reward ratio in the code to 2:1.
-Total capital: $10,000
-We use 10% of the total capital per trade.
-Commissions: 0.1% per trade.
The code construction is simple and very well detailed within the script itself.
Risk-Reward Ratio 2:1
Using a 2:1 risk-reward ratio reduces the win rate but significantly increases profitability.
Across the full historical data of the SPX index (weekly), the system would have generated 236 trades, with a win rate of 51.27% and a profit factor of 2.53.
From January 1, 2023, to November 28, 2025, the system would have generated 5 trades, with an 80% win rate and a profit factor of 9.244.
What makes this system so good?
-It takes advantage of the long-term bullish bias of U.S. stock indices and traditional markets.
-It filters out a lot of noise thanks to the weekly timeframe.
-It uses simple parameters with no over-optimization.
Final Notes:
This strategy has consistently outperformed the returns offered by most traditional funds over time, with fewer drawdowns and significantly less stress. I hope you like it.
Elite Correlation Matrix AIThe Elite Correlation Matrix AI indicator provides comprehensive real-time correlation analysis across multiple asset classes, displaying the interrelationships between equities, bonds, commodities, currencies, and volatility instruments.
The indicator calculates and displays correlation coefficients between a predefined set of major market indices and instruments, including:
• Major equity indices (SPY, QQQ, IWM)
• Long-term Treasury bonds (TLT)
• Gold (GLD)
• Crude oil (USO)
• Volatility (VIX)
• US Dollar Index (DXY)
• Bitcoin (BTCUSD)
Key features include:
• Rolling correlation calculations across user-defined periods to identify both short-term and longer-term relationships
• Visual correlation heat map showing the strength and direction of relationships between all tracked instruments
• Detection of correlation breakdowns, which often precede significant market regime shifts
• Dashboard display providing summary metrics of prevailing correlation patterns
The indicator enables users to monitor the current state of market relationships and identify when traditional correlations begin to break down, which frequently serves as an early warning of impending changes in market behavior. By tracking the degree of connectedness between different asset classes, the indicator provides insight into the current risk environment and the potential for diversification effectiveness.
This analysis is particularly valuable for understanding periods of market stress when asset relationships deviate from their normal patterns, as well as identifying environments where traditional correlations hold and where they are undergoing structural changes.
Trend Breakout & Ratchet Stop System [Market Filter]Description:
This strategy implements a robust trend-following system designed to capture momentum moves while strictly managing downside risk through a multi-stage "Ratchet" exit mechanism and broad market filters.
It is designed for swing traders who want to align individual stock entries with the overall market direction.
How it works:
1. Market Regime Filters (The "Safety Check") Before taking any position, the strategy checks the health of the broader market to avoid "catching falling knives."
Broad Market Filter: By default, it checks NASDAQ:QQQ (adjustable). If the benchmark is trading below its SMA 200, the strategy assumes a Bear Market and suppresses all new long entries.
Volatility Filter (VIX): Uses CBOE:VIX to gauge fear. If the VIX is above a specific threshold (Default: 32), entries are paused, and existing positions can optionally be closed to preserve capital.
2. Entry Logic Entries are based on Momentum and Trend confirmation. A position is opened if filters are clear AND one of the following occurs:
Golden Cross: SMA 25 crosses over SMA 50.
SMA Breakouts: A "Three-Bar-Break" logic confirms a breakout above the SMA 50, 100, or 200 (price must establish itself above the moving average).
3. The "Ratchet" Exit System The exit logic evolves as the trade progresses, tightening risk like a ratchet:
Stage 0 (Initial Risk): Starts with a standard percentage Stop Loss from the entry price.
Stage 1 (Breakeven/Lock): Once the price rises by Profit Step 1 (e.g., +10%), the Stop Loss jumps to a tighter level and locks there. This secures the initial move.
Stage 2 (Trailing Mode): If the price continues to rise to Profit Step 2 (e.g., +15%), the Stop Loss converts into a dynamic Trailing Stop relative to the Highest High. This allows the trade to run as long as the trend persists.
Additional Exits:
Dead Cross: Closes position if SMA 25 crosses under SMA 50.
VIX Panic: Emergency exit if volatility spikes above the threshold.
Settings & Customization:
SMAs: Adjustable lengths for all Moving Averages.
Filters: Toggle Market/VIX filters on/off and choose your benchmark ticker (e.g., SPY or QQQ).
Risk Management: Fully customizable percentages for the Ratchet steps (Initial SL, Stage 1 Trigger, Trailing distance).
Best Entry Swing MASTER v3 PUBLIC (S.S)Strategy Description (English)
Best Entry Swing MASTER v3 – Quality Mode
The Best Entry Swing MASTER v3 is a structured swing trading and trend-following strategy designed to identify high-probability long and short entries during directional markets.
It combines three core setup types commonly used by momentum and breakout traders:
Breakout (BO)
Pullback Reversal (PB)
Volatility Contraction Pattern (VCP)
The strategy applies multiple layers of confirmation, including multi-EMA trend structure, volatility contraction, volume filters, and an optional market regime filter.
It is suitable for swing trading on higher timeframes (4H, Daily), as well as medium-term trend continuation setups.
Core Concepts
1. Trend Structure
A trend is considered valid when:
Uptrend: Price > EMA20 > EMA50 > EMA100
Downtrend: Price < EMA20 < EMA50 < EMA100
In addition, a simple but effective trend-strength metric is calculated using the percentage spread between EMA20 and EMA100.
This helps avoid signals during sideways or low-volatility environments.
2. Market Regime Filter
The market environment is determined using a higher timeframe benchmark (default: SPY on Daily).
Only long trades are allowed in bullish market conditions
Only short trades in bearish conditions
This significantly reduces false signals in counter-trend conditions.
Entry Logic
Breakout (BO)
A long breakout triggers when:
Price closes above the highest high of the lookback period
Volume exceeds its 20-period average
Trend and market regime confirm
(Optional A+ mode): true volatility contraction is required
Similar logic applies for short breakdowns.
Pullback (PB)
A pullback entry triggers after:
At least two corrective candles
A strong reversal candle (close above previous high for long)
Volume confirmation
Price interacts with EMA20
This structure models classical trend-reentry conditions.
Volatility Contraction Pattern (VCP)
A VCP entry triggers when:
True range contracts over multiple bars
Price holds near the breakout zone
Volume contracts
Trend and market regime are aligned
This setup aims to capture explosive continuation moves.
Quality Modes
The strategy offers two modes:
Balanced Mode
Moderate signal frequency
Broader trend-strength allowance
Suitable for more active traders
A+ Only Mode
Strict confirmation requirements
Only high-quality setups with multiple confluences
Designed to avoid low-probability trades entirely
Risk Management
Risk is managed using an ATR-based stop and target:
Long SL = Close − ATR × 1.5
Long TP = Close + ATR × 3
(Equivalent logic for short positions)
This provides a balanced reward-to-risk profile and avoids overly tight stops.
Early Entry Signals (Optional)
The script offers optional “Early Entry” markers that highlight when a setup is forming but not yet confirmed.
These are not entry signals and are disabled by default for public use.
Intended Use
This strategy is designed for:
Swing trading
Momentum continuation
Trend-following
Multi-day to multi-week trades
It performs best on:
4H
Daily
High-liquidity equities, indices, and futures
Disclaimer
This script is intended for educational and research purposes.
Past performance does not guarantee future results.
Always backtest thoroughly and use appropriate risk management.
stock-vs-industry using NQUSB benchmark idexesOriginal idea from Stock versus Industry by Tr33man .
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
═══ PRIMARY IMPROVEMENT: NQUSB Hierarchical Index Benchmarks ═══
The KEY improvement: Multi-Level Industry Granularity with Drill-Down/Drill-Up Navigation
From: Simple ETF Comparison (1 Level) Stock → Industry ETF (e.g., "SOXX" for all semiconductors)
To: NQUSB Hierarchical Comparison (4 Levels)
Level 4 (Primary): NQUSB10102010 → Semiconductors (most specific)
Level 3 (Secondary): NQUSB101020 → Technology Hardware and Equipment
Level 2 (Tertiary): NQUSB101010 → Software and Computer Services
Level 1 (Quaternary): NQUSB10 → Technology (broadest sector)
Users can now drill up and down the industry hierarchy to see how their stock performs against different levels of industry classification!
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
═══ WHY THIS MATTERS ═══
Original Limitations:
Single comparison level - ETF only
No drill-down capability - Can't zoom in to more specific industries
No drill-up capability - Can't zoom out to broader sectors
ETF limitations - Not all industries have dedicated ETFs
Arbitrary mappings - Manual ETF selection may not represent true industry
Improved Capabilities:
4-level hierarchical navigation - Drill-down and drill-up through industry classifications
361 NQUSB official indices - NASDAQ US Benchmark Index structure
Official NASDAQ classification - Industry-standard taxonomy
Large Mid Cap (LM) option - Focus on larger companies when needed
Enhanced UI - Clear level indicators and full index descriptions
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
═══ EXAMPLE: ANALYZING NVDA (Semiconductors) ═══
Level 4 - Primary (Most Specific):
NQUSB10102010 - Semiconductors
→ NVDA vs. AMD, AVGO, QCOM, TXN, etc. (direct competitors)
Level 3 - Secondary (Broader):
NQUSB101020 - Tech Hardware & Equipment
→ NVDA vs. AAPL, CSCO + semiconductors
Level 2 - Tertiary (Even Broader):
NQUSB101010 - Software and Computer Services
→ NVDA vs. all tech hardware
Level 1 - Quaternary (Broadest):
NQUSB10 - Technology Sector
→ NVDA vs. entire technology sector
You can now zoom in to see direct competitors or zoom out to understand macro sector trends - all in one indicator!
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
═══ COMPARISON SUMMARY ═══
Original Version:
Comparison System: Industry ETFs
Industry Levels: 1 (flat ETF mapping)
Total Classifications: ~140 industries
Hierarchy Navigation: ❌ No
Data Source: Manual ETF curation
Improved Version:
Comparison System: NQUSB Official Indices
Industry Levels: 4 (hierarchical drill-down/up)
Total Classifications: 361 NQUSB indices
Hierarchy Navigation: ✅ 4-level drill navigation
Data Source: NASDAQ official taxonomy
Large/Mid Cap Option: ✅ LM variant toggle
Level Indicator: ✅ to labels
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
═══ ADDITIONAL FEATURES ═══
Dual Comparison System - Toggle between ETF mode (original) and Index Benchmark mode (NQUSB hierarchy)
Better Fallback Logic - Manual Override > NQUSB Index > ETF > SPY default
Enhanced Display - 4-row information table with full NQUSB index description
Backward Compatible - All original ETF mappings still work, existing charts won't break
Large Mid Cap Toggle - Optional "LM" suffix for focusing on larger companies only
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For complete documentation, data files, technical details, and the full NQUSB hierarchy structure, visit the GitHub repository.
The result: More accurate, more flexible, and more comprehensive industry strength analysis - enabling traders to understand exactly where their stock's performance comes from by drilling through multiple levels of industry classification.
