(QUANTLABS) Fractal God Mode: 25-Timeframe Scanner The indicator aggregates data into three distinct metric columns:
1. STRUCT (Market Structure) This analyzes price action relative to Fractal Pivots (Highs and Lows) to determine market direction.
HH (Breakout): Price has closed above the previous Pivot High. (Bullish Structure)
LL (Breakdown): Price has closed below the previous Pivot Low. (Bearish Structure)
TRAPPED: Price is trading between the last Pivot High and Low. This indicates a ranging market where trend trades should be avoided.
2. VELOCITY (Thrust) This measures the specific strength of the current candle on that timeframe.
The Math: It calculates the ratio of the body (Close - Open) relative to the total candle range (High - Low).
The Signal: High positive numbers (Green) indicate buyers are closing near highs. High negative numbers (Red) indicate sellers are dominating the range.
3. QUALITY (Efficiency Ratio) This acts as a "Noise Filter." It determines if the trend is moving in a straight line or whipping back and forth.
The Math: It divides the Net Price Movement (Distance from 5 bars ago) by the Total Path Traveled (Sum of the ranges of the last 5 bars).
PRISTINE (Values > 0.6): The market is moving efficiently in one direction.
CHOPPY (Values < 0.4): The market is volatile and non-directional (High Noise).
1. The Matrix (Dashboard) Located in the bottom right, this table gives you an instant read on Short-Term (3m-9m), Medium-Term (10m-45m), and Long-Term (1H-Daily) trends.
2. Coherence Flow At the bottom of the table, the script sums up the structural score of all 25 timeframes.
COHERENT BULL: When the Short, Medium, and Long terms align green.
COHERENT BEAR: When the Short, Medium, and Long terms align red.
3. God Mode (Global S/R) The indicator can plot Support and Resistance levels from higher timeframes onto your current chart. For example, while trading the 5m chart, you can see the 4H and Daily pivot levels plotted automatically as dotted lines, ensuring you never trade blindly into a higher-timeframe wall.
Trend Following: Wait for the "Coherent Bull/Bear" signal at the bottom of the dashboard. This confirms that momentum is aligned from the 3m chart up to the Daily.
Scalping: Focus on the Quality column. Only take trades when the Quality is "CLEAN" or "PRISTINE." Avoid entries when the dashboard warns of "High Noise" (Choppy).
Risk Management: If the dashboard shows "TRAPPED" on the Long Term (1H+), reduce position size or wait for a breakout.
Pivot Lookback: Adjusts the sensitivity of the Fractal Structure (Default: 5).
Show Fractal DNA Matrix: Toggles the dashboard table.
Show ALL Timeframe S/R: Enables "God Mode" to see supports/resistances from all 25 timeframes (Heavy visual processing, use carefully).
Search in scripts for "bear"
DeltaBurst Locator ## DeltaBurst Locator
DeltaBurst Locator is a sponsorship detector that divides OBV impulse by price thrust, normalizes the ratio, and cross-checks it against a higher timeframe confirmation stream. The oscillator turns the abstract "is this move real?" question into a precise number, exposing accumulation, distribution, and exhaustion across futures and stocks.
HOW IT WORKS
OBV Impulse vs. Price Change – Smoothed deltas of On-Balance Volume and price are ratioed, then normalized using a hyperbolic tangent function to prevent single prints from dominating.
Signal vs. Confirmation – A short EMA produces the execution signal while a higher-timeframe request.security() feed validates whether broader flows agree.
Spectrum Classification – Expansion/compression metrics grade whether current aggression is intense or fading, while ±0.65 bands define exhaust/vacuum zones.
Slope Divergences – Linear regression slopes on both price and the ratio expose bullish/bearish sponsorship mismatches before candles reverse.
HOW TO USE IT
Breakout Validation : Only chase breakouts when both local and higher-timeframe ratios are on the same side of zero; mixed signals suggest liquidity is fading.
Absorption Trades : When the histogram spikes beyond ±0.65 but the EMA lags, expect absorption; combine with price structure for pinpoint reversals.
News/Event Monitoring : During earnings or macro releases, watch for ratio collapses with price still rising—this flags forced moves driven by hedging rather than real demand.
VISUAL FEATURES
Color logic: Positive sponsorship fills teal, negative fills crimson against the zero line, making intent obvious at a glance.
Optional markers: Burst triangles and divergence dots can be enabled when you need explicit annotations or left off for a minimalist panel.
Compression heatmap: Background shading communicates whether the market is coiling (high compression) or erupting (low compression).
Dashboard: Displays the live ratio, higher-timeframe ratio, and agreement state to speed up scanning across tickers.
PARAMETERS
Fast Pulse Length (default: 5): Controls the smoothing window for price change detection.
Slow Equilibrium Length (default: 34): Window for expansion/compression calculation.
OBV Smooth (default: 8): Smoothing period for OBV impulse calculation.
Ratio Ceiling (default: 3.0): Controls how aggressively values saturate; raise for high-volatility tickers.
Signal EMA (default: 4): EMA period for the signal line.
Confirmation Timeframe (default: 240): Pick a higher anchor (e.g., 4H) to validate intraday moves.
Divergence Window (default: 21): Window for slope-based divergence detection.
Show Burst Markers (default: disabled): Toggle burst triangles on demand.
Show Divergence Markers (default: disabled): Toggle divergence dots on demand.
Show Delta Dashboard (default: enabled): Hide when screen space is limited; leave on for desk broadcasts.
ALERTS
The indicator includes four alert conditions:
DeltaBurst Bull: Spotted a bullish liquidity burst
DeltaBurst Bear: Spotted a bearish liquidity burst
DeltaBurst Bull Div: Detected bullish sponsorship divergence
DeltaBurst Bear Div: Detected bearish sponsorship divergence
Hope you enjoy!
MTC – Multi-Timeframe Trend Confirmator V2MTC – Multi-Timeframe Trend Confirmator V2
A comprehensive trend analysis indicator that systematically combines six technical indicators across three customizable timeframes, using a weighted scoring system to identify high-probability trend conditions.
ORIGINALITY AND CONCEPT
This indicator is original in its approach to multi-timeframe trend confirmation. Rather than relying on a single indicator or timeframe, it creates a composite score by evaluating six different technical conditions simultaneously across three timeframes. The scoring system weighs certain indicators more heavily based on their reliability in trend identification. The visual gauge provides an at-a-glance view of trend alignment across timeframes, making it easier to identify when multiple timeframes agree - a condition that typically produces stronger, more reliable trends.
HOW IT WORKS - DETAILED SCORING METHODOLOGY
The indicator evaluates six technical conditions on each timeframe. Each condition contributes to a composite score:
EMA 200 (Weight: 1 point)
Bullish: Price closes above EMA 200 (+1)
Bearish: Price closes below EMA 200 (-1)
Rationale: Long-term trend direction
SMA 50/200 Crossover (Weight: 1 point)
Bullish: SMA 50 above SMA 200 (+1)
Bearish: SMA 50 below SMA 200 (-1)
Rationale: Golden/Death cross confirmation
RSI 14 (Weight: 1 point)
Bullish: RSI above 55 (+1)
Bearish: RSI below 45 (-1)
Neutral: RSI between 45-55 (0)
Rationale: Momentum filter with buffer zone to avoid chop
MACD (12,26,9) (Weight: 1 point)
Bullish: MACD line above signal line (+1)
Bearish: MACD line below signal line (-1)
Rationale: Trend momentum confirmation
ADX 14 (Weight: 2 points - DOUBLE WEIGHTED)
Requires ADX above 25 to activate
Bullish: DI+ above DI- and ADX > 25 (+2)
Bearish: DI- above DI+ and ADX > 25 (-2)
Neutral: ADX below 25 (0)
Rationale: Trend strength filter - only counts when a strong trend exists. Double weighted because ADX is specifically designed to measure trend strength, making it more reliable than oscillators.
Supertrend (Factor: 3.0, ATR Period: 10) (Weight: 2 points - DOUBLE WEIGHTED)
Bullish: Direction indicator = -1 (+2)
Bearish: Direction indicator = +1 (-2)
Rationale: Dynamic support/resistance that adapts to volatility. Double weighted because Supertrend provides clear, objective trend signals with built-in stop-loss levels.
COMPOSITE SCORE CALCULATION:
Total possible score range: -10 to +10 points
Score interpretation:
Score > 2: UPTREND (majority of indicators bullish, especially weighted ones)
Score < -2: DOWNTREND (majority of indicators bearish, especially weighted ones)
Score between -2 and +2: NEUTRAL/RANGING (mixed signals or weak trend)
The threshold of +/- 2 was chosen because it requires more than just basic agreement - it typically means at least 3-4 indicators align, or that the heavily-weighted indicators (ADX, Supertrend) confirm the direction.
MULTI-TIMEFRAME LOGIC:
The indicator calculates the composite score independently for three timeframes:
Higher Timeframe (default: 4H) - Major trend direction
Mid Timeframe (default: 1H) - Intermediate trend
Lower Timeframe (default: 15min) - Entry timing
Main Trend Confirmation Rule:
The indicator only signals a confirmed trend when BOTH the higher timeframe AND mid timeframe scores agree (both > 2 for uptrend, or both < -2 for downtrend). This dual-timeframe confirmation significantly reduces false signals during choppy or ranging markets.
HOW TO USE IT
Setup:
Add indicator to chart
Customize timeframes based on your trading style:
Scalpers: 15min, 5min, 1min
Day traders: 4H, 1H, 15min (default)
Swing traders: Daily, 4H, 1H
Toggle individual indicators on/off based on your preference
Adjust Supertrend parameters if needed for your instrument's volatility
Reading the Gauge (Top Right Corner):
Each row shows one timeframe
Left column: Timeframe label
Middle column: Visual strength bars (10 bars = maximum score)
Green bars = Bullish score
Red bars = Bearish score
Yellow bars = Neutral/ranging
More filled bars = stronger trend
Right column: Numerical score
Trading Signals:
Entry Signals:
Long Entry: Wait for upward triangle arrow (appears when higher + mid TF both bullish)
Confirm gauge shows green bars on higher and mid timeframes
Lower timeframe should ideally turn green for entry timing
Chart background tints light green
Short Entry: Wait for downward triangle arrow (appears when higher + mid TF both bearish)
Confirm gauge shows red bars on higher and mid timeframes
Lower timeframe should ideally turn red for entry timing
Chart background tints light red
Position Management:
Stay in position while higher and mid timeframes remain aligned
Consider reducing position size when mid timeframe score weakens
Exit when higher timeframe trend reverses (daily label changes)
Avoiding False Signals:
Ignore signals when gauge shows mixed colors across timeframes
Avoid trading when scores are close to threshold (+/- 2 to +/- 4 range)
Best trades occur when all three timeframes align (all green or all red in gauge)
Use the numerical scores: higher absolute values (7-10) indicate stronger, more reliable trends
Practical Examples:
Example 1 - Strong Uptrend Entry:
Higher TF: +8 (strong green bars)
Mid TF: +6 (strong green bars)
Lower TF: +4 (moderate green bars)
Action: Look for long entries on lower timeframe pullbacks
Background is tinted green, upward arrow appears
Example 2 - Ranging Market (Avoid):
Higher TF: +3 (weak green)
Mid TF: -1 (weak red)
Lower TF: +2 (neutral yellow)
Action: Stay out, wait for alignment
Example 3 - Trend Reversal Warning:
Higher TF: +7 (still green)
Mid TF: -3 (turned red)
Lower TF: -5 (strong red)
Action: Consider exiting longs, prepare for potential higher TF reversal
Customization Options:
Timeframes: Adjust all three to match your trading horizon
Indicator Toggles: Disable indicators that don't suit your instrument:
Disable RSI for highly volatile crypto markets
Disable SMA crossover for range-bound instruments
Keep ADX and Supertrend enabled for trending markets
Visual Preferences:
Arrow size: 5 options from Tiny to Huge
Gauge size: Small/Medium/Large for different screen sizes
Toggle arrows on/off if you only want the gauge
Alert Setup:
Right-click chart, "Add Alert"
Condition: MTC v6 - UPTREND or DOWNTREND
Get notified when multi-timeframe confirmation occurs
Best Practices:
Use with Price Action: The indicator works best when combined with support/resistance levels, chart patterns, and volume analysis
Risk Management: Even with multi-timeframe confirmation, always use stop losses
Market Context: Works best in trending markets; less reliable in strong consolidation
Backtesting: Test the default settings on your specific instrument and timeframe before live trading
Patience: Wait for full multi-timeframe alignment rather than taking premature signals
Technical Notes:
All calculations use Pine Script's security function to fetch data from multiple timeframes
Prevents repainting by using confirmed bar data
Gauge updates in real-time on the last bar
Daily labels mark at the open of each new daily candle
Works on all instruments and timeframes
This indicator is ideal for traders who want objective, systematic trend identification without the complexity of analyzing multiple indicators manually across different timeframes.
-NATANTIA
CVD [able0.1]# CVD Overlay iOS Style - Complete User Guide
## 📖 Table of Contents
1. (#what-is-cvd)
2. (#installation-guide)
3. (#understanding-the-display)
4. (#reading-the-info-table)
5. (#settings--customization)
6. (#trading-strategies)
7. (#common-mistakes-to-avoid)
---
## 🎯 What is CVD?
**CVD (Cumulative Volume Delta)** tracks the **difference between buying and selling pressure** over time.
### Simple Explanation:
- **Positive CVD** (Orange) = More buying than selling = Bulls winning
- **Negative CVD** (Gray) = More selling than buying = Bears winning
- **Rising CVD** = Increasing buying pressure = Potential uptrend
- **Falling CVD** = Increasing selling pressure = Potential downtrend
### Why It Matters:
CVD helps you see **who's really in control** of the market - not just price movement, but actual buying/selling volume.
---
## 🚀 Installation Guide
### Step 1: Open Pine Editor
1. Go to TradingView
2. Click the **"Pine Editor"** tab at the bottom of the screen
3. Click **"New"** or open an existing script
### Step 2: Copy & Paste the Code
1. Select all existing code (Ctrl+A / Cmd+A)
2. Delete it
3. Copy the entire CVD iOS Style code
4. Paste it into Pine Editor
### Step 3: Add to Chart
1. Click **"Save"** button (or Ctrl+S / Cmd+S)
2. Click **"Add to Chart"** button
3. The indicator will appear on your chart!
### Step 4: Initial Setup
- The indicator appears as an **overlay** on your price chart
- You'll see an **orange/gray line** following price
- An **info table** appears in the top-right corner
---
## 📊 Understanding the Display
### Main Chart Elements:
#### 1. **CVD Line** (Orange/Gray)
- **Orange Line** = Positive CVD (buying pressure)
- **Gray Line** = Negative CVD (selling pressure)
- This line moves with your price chart but shows volume delta
#### 2. **CVD Zone** (Shaded Area)
- Light shaded box around the CVD line
- Shows the "range" of CVD movement
- Helps visualize CVD boundaries
#### 3. **Center Line** (Dotted)
- Gray dotted line in the middle of the zone
- Represents the "neutral" point
- CVD crossing this = shift in market control
#### 4. **Reference Asset Line** (Light Gray)
- Shows Bitcoin (BTC) price movement for comparison
- Helps you see if your asset moves with or against BTC
- Can be changed to any asset you want
#### 5. **CVD Label**
- Shows current CVD value
- Positioned above/below zone to avoid overlap
- Updates in real-time
#### 6. **Reset Background** (Very Light Gray)
- Appears when CVD resets
- Indicates a new calculation period
---
## 📋 Reading the Info Table
The info table (top-right) shows **8 key metrics**:
### Row 1: **Header**
```
╔═ CVD able ═╗ | 15m | ████████ | able
```
- **CVD able** = Indicator name + creator
- **15m** = Current timeframe
- **████████** = Visual decoration
- **able** = Creator signature
### Row 2: **CVD Value**
```
CVD▲ | 7.39K | ████████ | █
█
█
```
- **CVD▲** = CVD with trend arrow
- ▲ = CVD increasing
- ▼ = CVD decreasing
- ► = CVD unchanged
- **7.39K** = Actual CVD number
- **Progress Bar** = Visual strength (darker = stronger)
- **Vertical Bars** = Height shows intensity
### Row 3: **Delta**
```
◆DELTA | -1.274K | ████░░░░ | ░
░
```
- **Delta** = Volume change THIS BAR ONLY
- **Negative** = More selling this bar
- **Positive** = More buying this bar
- Shows **immediate** pressure (not cumulative)
### Row 4: **UP Volume**
```
UP↑ | -1.263K | ████████ | █
█
█
```
- Total **buying volume** this bar
- Higher = Stronger buying pressure
- Green/Orange vertical bars = Bullish strength
### Row 5: **DOWN Volume**
```
DN↓ | 2.643K | ████████ | ░
░
░
```
- Total **selling volume** this bar
- Higher = Stronger selling pressure
- Gray vertical bars = Bearish strength
### Row 6-7: **Reference Asset** (if enabled)
```
══ REF ══ | ══════ | ████████ | █
█
PRICE▲ | 4130.300 | ████████ | █
█
```
- **REF** = Reference asset header
- **PRICE▲** = Reference price with trend
- Shows if BTC (or chosen asset) is rising/falling
- Compare with your chart to see correlation
### Row 8: **Market Status**
```
◄STATUS► | NEUT | ████░░░░ | ▒
▒
```
- **BULL** = CVD positive + Delta positive = Strong buying
- **BEAR** = CVD negative + Delta negative = Strong selling
- **NEUT** = Mixed signals = Wait for clarity
**Status Colors:**
- **Orange background** = Bullish (good for long)
- **Gray background** = Bearish (good for short)
- **White background** = Neutral (no clear signal)
---
## ⚙️ Settings & Customization
### Main Settings (⚙️)
#### **CVD Reset**
- **None** = CVD never resets (from beginning of data)
- **On Higher Timeframe** = Resets when HTF candle closes
- 15m chart → Resets hourly
- 1h chart → Resets daily
- Recommended for most traders
- **On Session Start** = Resets at market open
- **On Visible Chart** = Resets from leftmost visible bar
#### **Precision**
- **Low (Fast)** = Uses 1m data, faster but less accurate
- **Medium** = Uses 5m data, balanced (recommended)
- **High** = Uses 15m data, most accurate but slower
#### **Cumulative**
- ✅ On = CVD accumulates over time (recommended)
- ❌ Off = Shows only current bar delta
#### **Show Labels**
- ✅ On = Shows CVD value label on chart
- ❌ Off = Cleaner chart, no label
#### **Show Info Table**
- ✅ On = Shows info table (recommended for beginners)
- ❌ Off = Hide table for minimalist view
---
### 🎨 iOS Style Colors
You can customize **every color** to match your chart theme:
#### **Primary Colors**
- **Primary (Orange)** = Main bullish color (#FF9500)
- **Secondary (Gray)** = Main bearish color (#8E8E93)
- **Background** = Table background (#FFFFFF)
- **Text** = Text color (#1C1C1E)
#### **Bullish/Bearish**
- **Bullish (Orange)** = Positive CVD color
- **Bearish (Gray)** = Negative CVD color
- **Opacity** = Zone transparency (0-100%)
- **Show Zone** = Enable/disable shaded area
#### **Table Colors** (📋)
- **Header Background** = Top row background
- **Header Text** = Top row text color
- **Cell Background** = Data cells background
- **Cell Text** = Data cells text color
- **Border** = Table border color
- **Accent Background** = Special rows background
- **Alert Background** = Warning/status background
---
### 📊 Reference Asset Settings
#### **Enable**
- ✅ On = Shows reference asset line
- ❌ Off = Hide reference asset
#### **Symbol**
- Default: `BINANCE:BTCUSDT`
- Can change to any asset:
- `BINANCE:ETHUSDT` (Ethereum)
- `SPX` (S&P 500)
- `DXY` (US Dollar Index)
- Any ticker symbol
#### **Color & Width**
- Customize line appearance
- Width: 1-4 (thickness)
---
## 💡 Trading Strategies
### Strategy 1: CVD Divergence (Beginner-Friendly)
**What to Look For:**
- Price making **higher highs** but CVD making **lower highs** = Bearish divergence
- Price making **lower lows** but CVD making **higher lows** = Bullish divergence
**How to Trade:**
1. Wait for divergence to form
2. Look for confirmation (price reversal, candlestick pattern)
3. Enter trade in divergence direction
4. Stop loss beyond recent high/low
**Example:**
```
Price: /\ /\ /\ (higher highs)
CVD: /\ / \/ (lower highs) = Bearish signal
```
### Strategy 2: CVD Trend Following (Intermediate)
**What to Look For:**
- **Strongly rising CVD** + **rising price** = Strong uptrend
- **Strongly falling CVD** + **falling price** = Strong downtrend
**How to Trade:**
1. Wait for CVD and price moving in same direction
2. Enter on pullbacks to support/resistance
3. Stay in trade while CVD trend continues
4. Exit when CVD trend breaks
**Signals:**
- CVD ▲▲▲ + Price ↑ = Go LONG
- CVD ▼▼▼ + Price ↓ = Go SHORT
### Strategy 3: CVD + Reference Asset (Advanced)
**What to Look For:**
- Your asset **rising** but BTC (reference) **falling** = Relative strength
- Your asset **falling** but BTC (reference) **rising** = Relative weakness
**How to Trade:**
1. Compare CVD movement with BTC
2. If your CVD rises faster than BTC = Buy signal
3. If your CVD falls faster than BTC = Sell signal
4. Use for **pair trading** or **asset selection**
### Strategy 4: Volume Delta Confirmation
**What to Look For:**
- **Large positive Delta** = Strong buying this bar
- **Large negative Delta** = Strong selling this bar
**How to Trade:**
1. Price breaks resistance + Large positive Delta = Confirmed breakout
2. Price breaks support + Large negative Delta = Confirmed breakdown
3. Use Delta to **confirm** price moves, not predict them
**Rules:**
- Delta > 2x average = Very strong pressure
- Delta near zero at key level = Weak move, likely false breakout
---
## 🎓 Reading Real Scenarios
### Scenario 1: Strong Buying Pressure
```
Table Shows:
CVD▲ | 12.5K | ████████ | ████ (CVD rising)
◆DELTA | +2.8K | ████████ | ▲ (Positive delta)
UP↑ | 3.1K | ████████ | ████ (High buy volume)
DN↓ | 0.3K | ██░░░░░░ | ░ (Low sell volume)
◄STATUS► | BULL | ████████ | ████ (Orange background)
```
**Interpretation:** Strong buying, good for LONG trades
### Scenario 2: Distribution (Hidden Selling)
```
Table Shows:
CVD► | 8.2K | ████░░░░ | ▒▒ (CVD flat)
◆DELTA | -1.5K | ████████ | ▼ (Negative delta)
UP↑ | 0.8K | ███░░░░░ | ░ (Low buy volume)
DN↓ | 2.3K | ████████ | ████ (High sell volume)
◄STATUS► | BEAR | ████████ | ░░░░ (Gray background)
```
**Interpretation:** Price may look stable, but selling increasing = Prepare for drop
### Scenario 3: Neutral/Choppy Market
```
Table Shows:
CVD► | 5.1K | ████░░░░ | ▒ (CVD sideways)
◆DELTA | +0.2K | ██░░░░░░ | ─ (Small delta)
UP↑ | 1.2K | ████░░░░ | ▒ (Medium buy)
DN↓ | 1.0K | ████░░░░ | ▒ (Medium sell)
◄STATUS► | NEUT | ████░░░░ | ▒▒ (White background)
```
**Interpretation:** No clear direction = Stay out or reduce position size
---
## ⚠️ Common Mistakes to Avoid
### Mistake 1: Trading on CVD Alone
- ❌ **Wrong:** "CVD is rising, I'll buy immediately"
- ✅ **Right:** "CVD is rising, let me check price structure, support/resistance, and wait for confirmation"
### Mistake 2: Ignoring Delta
- ❌ **Wrong:** Looking only at cumulative CVD
- ✅ **Right:** Watch both CVD (trend) and Delta (momentum)
- Delta shows **immediate** pressure changes
### Mistake 3: Wrong Timeframe
- ❌ **Wrong:** Using 1m chart with High Precision (too slow)
- ✅ **Right:** Match precision to timeframe:
- 1m-5m → Low Precision
- 15m-1h → Medium Precision
- 4h+ → High Precision
### Mistake 4: Not Using Reset
- ❌ **Wrong:** Using "None" reset for intraday trading
- ✅ **Right:** Use "On Higher Timeframe" to see fresh CVD each session
### Mistake 5: Overtrading Neutral Status
- ❌ **Wrong:** Forcing trades when STATUS = NEUT
- ✅ **Right:** Only trade clear BULL or BEAR status
### Mistake 6: Ignoring Reference Asset
- ❌ **Wrong:** Trading altcoin without checking BTC
- ✅ **Right:** Always check if BTC CVD agrees with your asset
---
## 🔥 Pro Tips
### Tip 1: Multi-Timeframe Analysis
- Check CVD on **3 timeframes**:
- Lower TF (15m) = Entry timing
- Current TF (1h) = Trade direction
- Higher TF (4h) = Overall trend
### Tip 2: Volume Confirmation
- Big price move + Small Delta = **Weak move** (likely reversal)
- Small price move + Big Delta = **Strong accumulation** (continuation)
### Tip 3: CVD Reset Zones
- Pay attention to **reset backgrounds** (light gray)
- Often marks **session starts** = High volatility periods
### Tip 4: Divergence + Status
- Bearish divergence + STATUS = BEAR = **Strongest short signal**
- Bullish divergence + STATUS = BULL = **Strongest long signal**
### Tip 5: Color Psychology
- **Orange** (Bullish) is **warm** = Buying energy
- **Gray** (Bearish) is **cool** = Selling pressure
- Train your eye to read colors instantly
### Tip 6: Table as Quick Scan
- Glance at table without reading numbers:
- **All orange** = Bullish
- **All gray** = Bearish
- **Mixed** = Wait
---
## 📱 Quick Reference Card
| Signal | CVD | Delta | Status | Action |
|--------|-----|-------|--------|--------|
| **Strong Buy** | ▲▲ High | ++ Positive | BULL | Long Entry |
| **Strong Sell** | ▼▼ Low | -- Negative | BEAR | Short Entry |
| **Divergence Buy** | ▲ Rising | Price ▼ | → BULL | Long Setup |
| **Divergence Sell** | ▼ Falling | Price ▲ | → BEAR | Short Setup |
| **Neutral** | → Flat | ~0 Near Zero | NEUT | Stay Out |
| **Accumulation** | → Flat | ++ Positive | NEUT→BULL | Watch for Breakout |
| **Distribution** | → Flat | -- Negative | NEUT→BEAR | Watch for Breakdown |
---
## 🆘 Troubleshooting
### Issue: "Indicator not showing"
- **Solution:** Make sure overlay=true in code, re-add to chart
### Issue: "Table overlaps with price"
- **Solution:** Change table position in code or use TradingView's "Move" feature
### Issue: "CVD line too far from price"
- **Solution:** This is normal! CVD is volume-based, not price-based. Focus on CVD direction, not position
### Issue: "Too many lines on chart"
- **Solution:** Disable "Show Zone" and "Show Labels" in settings for cleaner view
### Issue: "Calculations too slow"
- **Solution:** Change Precision to "Low (Fast)" or use higher timeframe
### Issue: "Reference asset not showing"
- **Solution:** Check if "Enable" is ON and symbol is valid (e.g., BINANCE:BTCUSDT)
---
## 🎬 Getting Started Checklist
- Install indicator on TradingView
- Set precision to "Medium"
- Set reset to "On Higher Timeframe"
- Enable info table
- Add reference asset (BTC)
- Practice reading the table on demo account
- Test on different timeframes (15m, 1h, 4h)
- Compare CVD with your current strategy
- Paper trade for 1 week before going live
- Keep a trading journal of CVD signals
---
## 📚 Summary
**CVD shows WHO is winning: Buyers or Sellers**
**Key Points:**
1. **Orange/Rising CVD** = Buying pressure = Bullish
2. **Gray/Falling CVD** = Selling pressure = Bearish
3. **Delta** = Immediate momentum THIS BAR
4. **Status** = Overall market condition
5. **Always confirm** with price action & other indicators
**Remember:**
- CVD is a **tool**, not a crystal ball
- Use with proper risk management
- Practice makes perfect
- Stay disciplined!
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**Created by: able**
**Version:** iOS Style v1.0
**Contact:** For questions, refer to TradingView community
Happy Trading! 🚀📈
Inversion Fair Value Gap Model [PJ Trades]GENERAL OVERVIEW:
The Inversion Fair Value Gap Model indicator is a complete rule-based system designed to identify trade setups using the Inversion Fair Value Gap strategy taught by PJ Trades. It automates the strategy’s workflow by detecting liquidity sweeps, confirming V-shape recoveries, identifying valid Inversion Fair Value Gaps, validating higher-timeframe Fair Value Gap taps, and checking for a clear opposite Draw On Liquidity. These factors are evaluated together to produce a signal rating of A, A+, or A++, based on how many of these criteria the setup satisfies. When a long or short setup is confirmed, the indicator automatically plots an entry, stop-loss, break-even, and two take-profit levels.
A dashboard that updates in real-time displays the current directional bias, liquidity sweep activity, Inversion Fair Value Gap confirmation state, V Shape Recovery state, higher-timeframe Fair Value Gap context, opposite Draw on Liquidity, SMT divergence, and other key information relevant to the trading model. The indicator also includes optional trade statistics on the dashboard that tracks the recent win rates for A, A+, and A++ setups, as well as separate long and short win rates.
This indicator was developed by Flux Charts, in collaboration with PJ Trades.
What is the theory behind the indicator?:
The Inversion Fair Value Gap model is built on the idea that when the market pushes above a high or below a low, it often does so to sweep liquidity. If that move quickly fails and price reverses, it shows the sweep was a grab for orders and not a continuation. That quick rejection is the V Shape Recovery behavior. An Inversion Fair Value Gap forms when a Fair Value Gap that once supported the original move gets invalidated afterward. That invalidation confirms the shift in direction and becomes the new reference point for trades. The Inversion Fair Value Gap model uses this sequence because it highlights when the market has taken liquidity, rejected continuation, and started delivering in the opposite direction.
INVERSION FAIR VALUE GAP MODEL FEATURES:
The Inversion Fair Value Gap Model indicator includes 15 main features:
Sessions
Key Levels & Swing Levels
Liquidity Levels
Liquidity Sweeps
V Shape Recoveries
Higher-Timeframe Fair Value Gaps
Inversion Fair Value Gaps
Macros
Bias
Signals
New Day Opening Gap
New Week Opening Gap
SMT Divergences
Dashboard
Alerts
SESSIONS:
The Inversion Fair Value Gap Model indicator includes five trading sessions (times in EST):
Asia: 20:00 - 00:00
London: 02:00 - 05:00
NY AM: 09:30 - 12:15
NY Lunch: 12:15 - 13:30
NY PM: 13:30 - 16:00
Session highs and lows are automatically tracked and used within the indicator’s signal logic.
🔹Session Zones:
Each session has a zone that outlines its active time window. These zones can be toggled on or off independently. When active, they visually separate each part of the trading day. Users can adjust the color and opacity of each session box. Users can also enable session labels, which place a label above each session zone showing its corresponding session name.
🔹Session Time:
Users can toggle on ‘Time’ which will display each session’s time window next to its session title.
🔹Session Highs/Lows:
Every session can display its own high and low as horizontal lines. Users can customize the line style for session highs/lows, choosing between solid, dashed, or dotted. The color of the lines will match the same color used for the session box. Users can adjust the color of the labels as well, which is applied to all session high/low labels.
When price has moved above a session high, or below a session low, the label will not be displayed anymore.
🔹Extend Levels:
When enabled, each session’s high and low levels can be extended forward by a set number of bars.
Please Note: Disabling a session under the main Sessions section only hides its visuals (boxes, lines, or labels). It does not impact signal detection or logic.
KEY LEVELS:
The Inversion Fair Value Gap Model indicator includes 11 key market levels that outline important structural price areas across daily, weekly, and monthly timeframes. These levels include the Daily Open, Previous Day High/Low, Weekly Open, Previous Week High/Low, Monthly Open, Previous Month High/Low, Midnight Open, and 08:30 Open. The levels can be enabled or disabled and customized in color and line style. All of the levels except the Midnight Open and 08:30 Open are used for the indicator’s signal logic.
🔹Daily Open
The Daily Open marks where the current trading day began.
🔹Previous Day High/Low
The Previous Day High (PDH) marks the highest price reached during the previous regular trading session. It shows where buyers pushed price to its highest point before the market closed.
The Previous Day Low (PDL) marks the lowest price reached during the previous regular trading session. It shows where selling pressure reached its lowest point before buyers stepped in.
When price pushes above the PDH or below the PDL, the level is removed from the chart.
🔹Weekly Open
The Weekly Open marks the first price of the current trading week.
🔹Previous Week High/Low
The Previous Week High (PWH) marks the highest price reached during the previous trading week. It shows where buying pressure reached its peak before the weekly close.
The Previous Week Low (PWL) marks the lowest price reached during the previous trading week. It shows where sellers pushed price to its lowest point before buyers regained control.
When price pushes above the PWH or below the PWL, the level is removed from the chart.
🔹Monthly Open
The Monthly Open marks the opening price of the current month.
🔹Previous Month High/Low
The Previous Month High (PMH) marks the highest price reached during the previous calendar month. It represents the point at which buyers achieved the strongest push before the monthly close.
The Previous Month Low (PML) marks the lowest price reached during the previous calendar month. It shows where selling pressure was strongest before buyers stepped back in.
When price pushes above the PMH or below the PML, the level is removed from the chart.
🔹Midnight Open
The Midnight Open marks the first price of the trading day at 00:00 EST.
🔹08:30 Open
The 08:30 Open marks the opening price at 08:30 EST.
🔹Customization Options:
Users can fully customize the appearance of all key levels, including the following:
Labels
Label Size
Line Style
Line Colors
Labels:
Users can toggle on ‘Show Labels’ to display labels for each toggled-on level that price hasn’t pushed above/below. Users can also adjust the size of labels, choosing between auto, tiny, small, normal, large, or huge.
Line Style:
Users can select a line style, choosing between solid, dashed, or dotted, which is applied to all toggled-on key levels.
Line Color:
Users can choose different colors for each of the following key levels:
Daily Open, Previous Day High, Previous Day Low
Weekly Open, Previous Week High, Previous Week Low,
Monthly Open, Previous Month High, Previous Month Low
Midnight Open
08:30 Open
🔹Extend Levels:
When enabled, each key level is extended forward by a set number of bars.
Please Note: Disabling a level in the “Key Levels” section only hides its visuals and does not affect the indicator’s signals.
🔹Swing Levels
The indicator automatically plots Swing Highs and Swing Lows which are used in the indicator’s signal generation logic.
A swing high forms when a candle’s high is greater than the highs of the bars immediately before and after it.
A swing low forms when a candle’s low is lower than the lows of the bars immediately before and after it.
🔹Swing Level Colors
Users can customize the color of Active Levels and Swept Levels.
Active Levels are levels that price has not pushed above or below
Swept Levels are levels that price pushed above or below.
🔹Swing Levels – Show Nearest
This setting determines how many swing highs/lows are displayed on the chart. The indicator will display the nearest X highs to price and the nearest X lows to price.
For example, if ‘Show Nearest’ is set to 2, the nearest 2 swing highs and nearest 2 swing lows to price will be plotted on the chart.
LIQUIDITY LEVELS:
The Inversion Fair Value Gap Model indicator automatically identifies and plots liquidity at key structural points in the market. These include swing highs and swing lows, session highs and lows, and major higher timeframe reference points as explained in the SESSIONS and KEY LEVELS sections above. All of these areas are treated as potential pools of resting orders and are used throughout the indicator’s signal logic.
🔹What is Buyside Liquidity?:
Buyside Liquidity (BSL) represents price levels where many buy stop orders are sitting, usually from traders holding short positions. When price moves into these areas, those stop-loss orders get triggered and short sellers are forced to buy back their positions. These zones often form above key highs such as the previous day, week, or month. Understanding BSL is important because when price reaches these levels, the sudden wave of buy orders can create sharp reactions or reversals as liquidity is taken from the market.
🔹What is Sellside Liquidity?:
Sellside Liquidity (SSL) represents price levels where many sell stop orders are waiting, usually from traders holding long positions. When price drops into these areas, those stop-loss orders are triggered and long traders are forced to sell their positions. These zones often form below key lows such as the previous day, week, or month. Understanding SSL is important because when price reaches these levels, the surge of sell orders can cause sharp reactions or reversals as liquidity is taken from the market.
🔹 Which Liquidity Levels Are Used
The indicator tracks liquidity at the following areas:
Asia Session High/Low
London High/Low
NY AM High/Low
NY Lunch High/Low
NY PM High/Low
Previous Day High and Low
Previous Week High and Low
Previous Month High and Low
Daily Open
Weekly Open
Monthly Open
Swing Highs/Lows
🔹 How Liquidity Levels Are Used
All tracked levels across sessions, swing points, and higher timeframes serve as potential liquidity targets. When price trades above one of these highs, the indicator looks for short setups if other confluences align. When price trades below lows, the indicator looks for long setups if other confluences align.
LIQUIDITY SWEEPS:
The indicator automatically detects Buyside Liquidity and Sellside Liquidity sweeps using the liquidity levels mentioned in the previous section.
🔹What is a Liquidity Sweep?
Liquidity sweeps occur when price trades beyond a key high or low and activates resting buy-stop or sell-stop orders in that area. It’s how the market gathers the liquidity needed for larger participants to enter positions.
Traders often place stop-loss orders around obvious highs and lows, such as the previous day’s, week’s, or month’s levels. When price pushes through one of these areas, it triggers the stops placed there and generates a burst of volume. This can lead to quick movements in price as those orders are executed.
🔹Sellside Liquidity Sweep
These occur when price dips below a Sellside Liquidity (SSL) level, taking out the stop-loss orders placed by long traders below that low. When this happens, the indicator records the sweep and begins monitoring for potential long setups as the next step in the IFVG trading strategy. Long trades are only eligible after a SSL sweep.
🔹Buyside Liquidity Sweep
These occur when price dips above a Buyside Liquidity (BSL) level, taking out the stop-loss orders placed by short seller traders above that high. When this happens, the indicator records the sweep and begins monitoring for potential short setups as the next step in the trading strategy. Short trades are only eligible after a BSL sweep.
🔹How to Use Liquidity Sweeps
Liquidity sweeps are not direct trade signals. They are best used as context when forming a directional bias. A sweep shows that the market has removed liquidity from one side, which can hint at where the next move may develop.
For example:
When BSL is swept, it often signals that buy stops have been triggered and the market may be preparing to move lower. Traders may then begin looking for short opportunities.
When SSL is swept, it often signals that sell stops have been triggered and the market may be preparing to move higher. Traders may then begin looking for long opportunities.
V SHAPE RECOVERIES:
🔹 What Is a V Shape Recovery?
A V shape recovery is a sharp, immediate reversal that happens right after price sweeps BSL or SSL. It indicates that price quickly moved back in the opposite direction after trading through the level. This behavior signals a shift in momentum and is a required confirmation in the indicator for signal generation. The indicator will not look for long trades after a SSL sweep unless a V shape recovery occurs. It will not look for short trades after a BSL sweep unless a V shape recovery occurs. Without this behavior, the indicator assumes that price may still be delivering in the direction of the sweep, so no valid setups can form.
🔹 Why V Shape Recoveries Matter
V shape recoveries help confirm that the liquidity the sweep did not immediately continue in the same direction. They separate false breaks from true continuation. A sweep without recovery often means price may keep trending, so the indicator does not generate signals in those cases. A sweep with a V shape recovery confirms rejection and sets the foundation for valid Inversion Fair Value Gap formation. This makes the V shape recovery one of the most important sequence steps in the Inversion Fair Value Gap Model.
🔹 How the Indicator Detects V Shape Recoveries
V shape recoveries can be visually intuitive when looking at a chart, but they are difficult to define consistently programmatically. To ensure reliable and repeatable detection, the indicator uses a rules-based method that evaluates candle size, candle direction, and the strength of the move immediately following the liquidity sweep. This approach removes subjectivity and allows the indicator to confirm V shape behavior the same way every time.
The indicator does not plot any visual elements specifically for V shape recoveries. Instead, the presence of a V shape recovery is implied through the signals themselves. Every valid long or short signal that appears after a liquidity sweep requires a confirmed V shape recovery. This means that if a signal is generated following a sweep, a V shape recovery has occurred.
🔹 V Shape Recovery After a Sellside Sweep (SSL Sweep)
After price trades below a sellside liquidity level, long positions are liquidated. If buyers quickly step in and force price upward with strong momentum, this forms a V shape recovery. This signals that the sweep below the low was rejected and that buyers have reclaimed control. When this occurs, the indicator begins monitoring for long setups.
🔹 V Shape Recovery After a Buyside Sweep (BSL Sweep)
After price pushes above a buyside liquidity level, many short positions are stopped out. If sellers immediately step in and drive price back down with strong movement, this forms a V shape recovery. This behavior reflects a quick change in candle direction immediately following the sweep. When this occurs, the indicator begins monitoring for short setups.
🔹Failed V Shape Recoveries
These examples show failed V shape recoveries, where price did not reverse decisively after the BSL or SSL sweep. The lack of strong response from buyers or sellers indicates that momentum did not shift. Thus, the indicator will not detect valid long/short setups using these liquidity sweeps.
HIGHER-TIMEFRAME FAIR VALUE GAPS:
Higher-timeframe Fair Value Gaps (HTF FVGs) provide important context in the Inversion Fair Value Gap Model because they show where significant imbalance occurred on larger market structures. The indicator automatically detects HTF FVGs and uses them as part of the signal rating system.
🔹 What Is a Fair Value Gap?
A Fair Value Gap (FVG) is an area where the market’s perception of fair value suddenly changes. On your chart, it appears as a three-candle pattern: a large candle in the middle, with smaller candles on each side that don’t fully overlap it.
A bullish FVG forms when a bullish candle is between two smaller bullish/bearish candles, where the first and third candles’ wicks don’t overlap each other at all.
A bearish FVG forms when a bearish candle is between two smaller bullish/bearish candles, where the first and third candles’ wicks don’t overlap each other at all.
This creates an imbalance because price moved so quickly that one side of the auction did not trade.
Examples:
🔹 What Makes an FVG “Higher-Timeframe”?
In this indicator, HTF FVGs are Fair Value Gaps detected on timeframes higher than the chart’s current timeframe. For example, on a 5-minute chart, a 1-hour FVG would be considered a HTF FVG. The indicator automatically plots and checks whether price interacts with these HTF FVGs during a liquidity sweep and incorporates this into the signal rating (A, A+, A++).
🔹 How the Indicator Uses Higher-Timeframe FVGs
The indicator automatically scans up to three user-selected higher timeframes for valid bullish and bearish FVGs and tracks price’s behavior around them in the background. When any of these higher timeframes are enabled, their FVGs are used directly within the signal logic.
During a liquidity sweep, the indicator checks whether price taps into any enabled HTF FVG. A tap occurs when price trades inside the boundaries of a higher-timeframe FVG during or immediately after the sweep.
A bullish HTF FVG tap during a sellside sweep supports a long setup.
A bearish HTF FVG tap during a buyside sweep supports a short setup.
When an HTF FVG tap aligns with the direction of the setup, the signal’s rating is increased. This can increase a setup’s rating from A to A+ or from A+ to A++.
🔹 Higher-Timeframe FVG Customization
Users can select up to three higher timeframes for HTF FVG detection. When a higher timeframe is enabled, its FVGs are used in the model’s signal logic. Users can also choose whether to display these HTF FVGs visually on the chart, by enabling the ‘Plot HTF FVGs’ setting.
Each enabled HTF FVG can be customized with the following options:
Bullish and Bearish Colors: Users can set different fill colors for bullish and bearish HTF FVGs for each selected timeframe.
Midline: When enabled, a midline is drawn through the center of each HTF FVG. Users can customize the midline’s line style, choosing between solid, dashed, or dotted and also customize the midline’s color.
Labels: When enabled, each plotted HTF FVG displays a label that shows its originating timeframe (for example, 1H, 4H).
Plot HTF FVGs: When disabled, the HTF FVG zones are hidden from the chart while the logic remains active in the background for signals.
Show Nearest:
This setting controls how many HTF FVGs are displayed based on proximity to current price. Users can choose to show the nearest X bullish HTF FVGs and the nearest X bearish HTF FVGs. This filter is applied across all enabled higher timeframes and does not limit by timeframe individually.
🔹When are Higher Timeframe Fair Value Gaps mitigated?
A Higher Timeframe Fair Value Gap is considered mitigated when a candle from the chart’s timeframe closes above the gap for a bearish FVG or below the gap for a bullish FVG.
INVERSION FAIR VALUE GAPS:
Inversion Fair Value Gaps (IFVGs) are a core requirement of the Inversion Fair Value Gap Model. Every long and short signal generated by the indicator requires a valid IFVG, just like liquidity sweeps and V shape recoveries. Without a confirmed IFVG, the model will not produce a setup.
🔹 What Is an Inversion Fair Value Gap?
An Inversion Fair Value Gap is a Fair Value Gap that becomes invalidated by a candle close in the opposite direction. This “flip” confirms that the original imbalance failed and that the market has shifted.
A bullish IFVG forms when a bearish FVG is invalidated by a candle closing above it.
A bearish IFVG forms when a bullish FVG is invalidated by a candle closing below it.
In the indicator, IFVGs are not used as retracement areas. Signals are generated immediately when a valid IFVG forms, not after price returns to the gap. The IFVG itself is the confirmation event that finalizes a setup sequence after a liquidity sweep and V shape recovery.
🔹 How the Indicator Plots IFVGs
The indicator only plots IFVGs that are used in long or short setups. Not every possible IFVG is shown on the chart. Only the IFVG involved in a confirmed signal is displayed. Users can disable IFVG plots entirely if they prefer a minimal view. This hides the visual gaps but does not affect the signal logic.
🔹 Customization Options
Users can customize how IFVGs appear on the chart:
Color Settings: Choose separate fill colors for bullish IFVGs and bearish IFVGs.
Midline: Toggle an optional midline inside the IFVG and choose between a solid, dashed, or dotted line.
Midline Color: Adjust the color of the IFVG Midline.
MACROS:
Macros are short, predefined time windows, where price is more likely to seek liquidity or rebalance imbalances. These periods often create sharp movements or shifts in delivery, giving additional context to setups. In the Inversion Fair Value Gap Model, macros are used as a confluence factor. When a long or short signal forms during a macro time window, the setup’s rating can increase from A to A+ or from A+ to A++.
Macros are not required for a signal to form, but they increase the signal’s rating when the setup aligns with macro timing.
🔹 How the Indicator Uses Macros
The indicator allows users to enable up to five macros. Each macro has its own start and end time, which the user can customize. These time windows are used directly in the signal logic. If a valid IFVG setup forms while price is inside any of the enabled macro windows, the indicator increases the signal’s rating.
Users may visually disable macros on the chart without affecting signal logic. Disabling visuals hides the macro zones, labels, and lines, but the underlying macro logic continues to function in the background for signals.
The indicator’s default macros use the following time periods (in EST):
09:50 - 10:10
10:50 - 11:10
11:50 - 12:10
12:50 - 13:10
13:50 - 14:10
🔹 Macro Settings
Each macro displays a shaded zone representing the active time window. This zone can be toggled on or off. Users can customize:
The color of each macro zone
The opacity of each zone
Whether the zones display at all (‘Show Zones’)
These visuals help identify whether price is currently inside a macro window.
🔹 Macro Labels:
Users can enable macro labels, which place a text label showing the macro’s title and its time window. The label color is global (applies to all macros), and the label size can be adjusted. Individual macros cannot have unique label colors.
🔹 Macro Start/End Lines
For additional clarity, the indicator draws two vertical markers for each macro:
One at the start of the macro
One at the end of the macro
A horizontal macro line is then drawn between the highs of these two candles to highlight the full duration of the macro window. Users can customize:
The line styles (solid, dashed, dotted) of the Macro Line and Start/End Lines
BIAS:
Bias determines which direction the indicator is allowed to generate signals. A bullish bias means only long setups can be confirmed. A bearish bias means only short setups can be confirmed. The bias acts as the final directional filter after a liquidity sweep, V shape recovery, and IFVG have all been validated. Even if all model conditions are met, the indicator will only confirm the setup if the direction aligns with the active bias.
Users are able to manually set a bias or use an automatic bias filter, which is explained below.
🔹 Manual Bias
Users can manually choose the directional bias at any time and choose between Bullish, Bearish, or Both.
When set to Bullish, the indicator will only confirm long setups, regardless of market structure.
When set to Bearish, only short setups are allowed.
When set to Both, the indicator can confirm both long and short setups if all requirements are met.
🔹 Automatic Bias
Automatic bias is fully rules-based and determined by how the previous session interacted with major draw-on-liquidity (DOL) levels. These levels include 1-hour highs and lows, 4-hour highs and lows, previous session highs and lows (such as Asia or London), and the previous day’s high and low. The indicator evaluates whether the previous session consolidated, manipulated liquidity, or manipulated and reversed before closing. Based on this behavior, the indicator establishes a directional bias for the current session.
◇ Previous Session Consolidation:
If the previous session did not sweep any major liquidity levels and price remained inside its range, the session is classified as consolidation.
After the current session sweeps a key low, the bias becomes bullish.
After the current session sweeps a key high, the bias becomes bearish.
The bias is determined live based on which side the current session manipulates first.
◇ Previous Session Manipulation (No Reversal):
If the previous session swept a major high-timeframe level but did not reverse before the session closed, the model assigns a reversal-based bias at the start of the current session.
If the previous session swept a low, the current session bias is bullish.
If the previous session swept a high, the current session bias is bearish.
Here, bias is determined immediately because the previous session’s manipulation defines the directional framework for the current session.
◇ Previous Session Manipulation + Reversal:
If the previous session swept a DOL level and also reversed away from it within the same session, the model assigns a continuation-based bias at the start of the current session.
If the previous session swept a low and reversed upward, the bias for the current session is bullish.
If the previous session swept a high and reversed downward, the bias is bearish.
🔹 How the Indicator Uses Bias in Practice
After the indicator validates the liquidity sweep, V shape recovery, and IFVG, it checks the active bias before confirming a signal.
If bias is bullish, only long setups are allowed.
If bias is bearish, only short setups are allowed.
If bias is Both, setups of either direction may form.
The bias does not influence the detection of liquidity sweeps, V shape recoveries, or IFVGs. It only determines whether those validated components are allowed to produce a final signal. Automatic bias updates based on session behavior, while manual bias remains fixed until the user changes it.
SIGNALS:
Signals are the final output of the Inversion Fair Value Gap Model indicator. A signal is only generated when all model conditions are satisfied in a clear, rules-based sequence.
A signal consists of:
An Entry
A Stop-Loss (SL)
A Breakeven (BE) level
Two Take-Profit levels (TP1 and TP2)
These components are plotted immediately once the final requirement (the IFVG confirmation) is met and the directional filter (bias) allows the setup.
Signals can be rated A, A+, or A++, based on whether certain confluences were present during the setup’s formation.
🔹 What All Signals Have in Common
Each signal type (A, A+, A++) requires the same four mandatory conditions. If any of these four are missing, the indicator will not print a signal.
◇ Required Component #1 – Valid Directional Bias
The bias determines whether the indicator can confirm a long or short setup.
Bullish bias → only long setups allowed
Bearish bias → only short setups allowed
Both → long or short setups allowed
Automatic bias → bias determined by session-based liquidity logic explained above
◇ Required Component #2 – Liquidity Sweep
The indicator must detect one of the following:
Sellside Liquidity Sweep (SSL Sweep) for potential long setups
Buyside Liquidity Sweep (BSL Sweep) for potential short setups
◇ Required Component #3 – V Shape Recovery
After a liquidity sweep, the indicator evaluates whether price produced a valid V shape recovery.
◇ Required Component #4 – Inversion Fair Value Gap (IFVG)
An IFVG must form in the direction of the potential setup.
A bullish IFVG forms when a bearish FVG is invalidated by a candle closing above that gap
A bearish IFVG forms when a bullish FVG is invalidated by a candle closing below that gap
The IFVG must occur after the V Shape Recovery and Liquidity Sweep. The IFVG confirmation is the final structural requirement. Once it forms, the setup is considered structurally complete.
🔹 A Signals
An A-rated signal contains exactly the four required components:
Valid Bias
Liquidity Sweep
V Shape Recovery
IFVG
An A signals represent the foundational implementation of the IFVG Model.
🔹 A+ Signals
An A+ signal includes the full A-signal structure plus ONE of the following:
Higher-Timeframe FVG Tap
Multi-Liquidity Sweep
Inside a Macro Window
◇ Higher-Timeframe FVG Tap
During a liquidity sweep, the indicator checks whether price taps into any enabled HTF FVG. A tap occurs when price trades inside the boundaries of a higher-timeframe FVG during or immediately after the sweep.
A bullish HTF FVG tap during a sellside sweep supports a long setup.
A bearish HTF FVG tap during a buyside sweep supports a short setup.
◇ Multi-Liquidity Sweep
A Multi-Liquidity Sweep occurs when price sweeps two liquidity levels of the same type in the same directional push.
Sweeping two lows in one move: Multi-Sellside Liquidity Sweep (long setups).
Sweeping two highs in one move → Multi-Buyside Liquidity Sweep (short setups).
◇ Inside a Macro Window
The final IFVG confirmation must occur inside a macro time window defined by the user.
If exactly one of these additional confluences is present, the signal rating is A+.
🔹 A++ Signals (Two Additional Confluences)
An A++ signal contains the full A signal structure plus TWO of the three confluences listed above.
HTF FVG tap + Multi-Liquidity Sweep
HTF FVG tap + Inside a Macro Window
Multi-Liquidity Sweep + Inside a Macro Window
If two confluences are present, the rating becomes A++. If all three are present, the setup is still rated a A++ (there is no A+++).
🔹 Signal Plots
When a valid long/short setup is detected, a signal with its rating appears with the following:
Entry: At the close of the candle that inverted a FVG
Stop-Loss: At the nearest swing high for short setups or nearest swing low for long setups
Breakeven Level: At the nearest swing high for long setups or the nearest swing low for short setups
Take-Profit 1: At the second nearest swing high for long setups or the second nearest swing low for short setups.
Take-Profit 2: At the third nearest swing high for long setups or the third nearest swing low for short setups.
After a signal reaches either TP2 or SL, the levels for Entry, SL, BE, TP1, and TP2 are removed from the chart. If another signal appears before the prior signal reaches either TP2 or SL, the levels are also removed.
Users can hover over any signal label to view a short summary of the exact criteria that were met for that setup. This includes whether a HTF FVG tap occurred, whether a multi-liquidity sweep was detected, whether the setup formed inside a macro window, and which liquidity level was swept prior to the V shape recovery.
🔹 Long Setup – A Rating
A long A-rated setup forms when all four core requirements of the IFVG Model occur without any additional confluences. First, price must sweep a Sellside Liquidity level. Immediately after the sweep, price must form a valid V shape recovery. Once the recovery completes, a bullish IFVG must form by invalidating a bearish Fair Value Gap with a candle close above it.
For a confirmed long signal, the indicator marks:
Entry: At the candle close that invalidates the bearish FVG and creates the IFVG
Stop Loss: At the nearest swing low
Breakeven: Midpoint between entry and stop-loss
Take Profit 1: At the second nearest swing high
Take Profit 2: At the third nearest swing high
In this example, price sweeps a swing low, has a V Shape recovery, and forms a bullish IFVG:
🔹 Short Setup – A Rating
A short A-rated setup forms when all four core requirements of the IFVG Model occur without any additional confluences. Price must first sweep a Buyside Liquidity level. Immediately after the sweep, price must form a valid V shape recovery. Once the recovery completes, a bearish IFVG must form by invalidating a bullish Fair Value Gap with a candle close below it.
For a confirmed short signal, the indicator marks:
Entry: At the candle close that invalidates the bullish FVG and creates the IFVG
Stop Loss: At the nearest swing high
Breakeven: Midpoint between entry and stop-loss
Take Profit 1: At the second nearest swing low
Take Profit 2: At the third nearest swing low
In this example, price sweeps a swing high, has a V shape recovery, and forms a bearish IFVG:
🔹 Long Setup – A+ Rating
A long A+ setup forms when the four core requirements of the IFVG Model occur and exactly one additional confluence is present. Price must sweep a Sellside Liquidity level, form a valid V shape recovery, and create a bullish IFVG by invalidating a bearish FVG. One of the following must also occur: a bullish HTF FVG tap during the liquidity sweep, a multi-sellside liquidity sweep, or the IFVG confirmation forms inside a macro window.
For a confirmed long A+ signal, the indicator marks:
Entry: At the candle close that creates the bullish IFVG
Stop Loss: At the nearest swing low
Breakeven: Midpoint between entry and stop-loss
Take Profit 1: At the second nearest swing high
Take Profit 2: At the third nearest swing high
In this example, price sweeps the NY AM Session Low, taps a 30-minute HTF FVG during the sweep, has a V shape recovery, and forms a bullish IFVG:
🔹 Short Setup – A+ Rating
A short A+ setup forms when the four core requirements of the IFVG Model occur and exactly one additional confluence is present. Price must sweep a Buyside Liquidity level, form a valid V shape recovery, and create a bearish IFVG by invalidating a bullish FVG. One of the following must also occur: a bearish HTF FVG tap, a multi-buyside liquidity sweep, or the IFVG confirmation forms inside a macro window.
For a confirmed short A+ signal, the indicator marks:
Entry: At the candle close that creates the bearish IFVG
Stop Loss: At the nearest swing high
Breakeven: Midpoint between entry and stop-loss
Take Profit 1: At the second nearest swing low
Take Profit 2: At the third nearest swing low
In this example, price sweeps a swing high, has a V shape recovery, and forms a bearish IFVG inside of the 13:50-14:10 macro:
🔹 Long Setup – A++ Rating
A long A++ setup forms when the four core requirements of the IFVG Model occur and at least two additional confluences are present. Price must sweep a Sellside Liquidity level, form a valid V shape recovery, and create a bullish IFVG. The setup must also include any two or three of the following: a bullish HTF FVG tap, a multi-sellside liquidity sweep, or the IFVG confirmation forming inside a macro window.
For a confirmed long A++ signal, the indicator marks:
Entry: At the candle close that creates the bullish IFVG
Stop Loss: At the nearest swing low
Breakeven: Midpoint between entry and stop-loss
Take Profit 1: At the second nearest swing high
Take Profit 2: At the third nearest swing high
In this example, price sweeps two swing lows, has a V shape recovery, taps a bullish 30-minute HTF FVG during the liquidity sweep, and forms a bullish IFVG inside of the 10:50-11:10 macro:
🔹 Short Setup – A++ Rating
A short A++ setup forms when the four core requirements of the IFVG Model occur and at least two additional confluences are present. Price must sweep a Buyside Liquidity level, form a valid V shape recovery, and create a bearish IFVG. The setup must also include any two or three of the following: a bearish HTF FVG tap, a multi-buyside liquidity sweep, or the IFVG confirmation forming inside a macro window.
For a confirmed short A++ signal, the indicator marks:
Entry: At the candle close that creates the bearish IFVG
Stop Loss: At the nearest swing high
Breakeven: Midpoint between entry and stop-loss
Take Profit 1: At the second nearest swing low
Take Profit 2: At the third nearest swing low
In this example, price sweeps a swing high, has a V shape recovery, taps a bearish 30-minute HTF FVG during the liquidity sweep, and forms a bearish IFVG inside of the 09:50-10:10 macro:
🔹Signal Settings
◇ Liquidity Levels Used:
Users can select which type of liquidity levels the indicator uses for identifying liquidity sweeps:
Swing Points: Only uses Swing Highs/Lows
Session Highs/Lows: Only uses Session Highs/Lows
Both: Uses both Swing Highs/Lows and Session Highs/Lows
◇ Bias:
This setting determines which signal directions are allowed.
Manual Bias: Users can manually choose the directional bias, picking between Bullish, Bearish, or Both.
Automatic Bias: The indicator automatically determines a directional bias based on the criteria mentioned in the previous Bias section.
◇ IFVG Sensitivity:
This setting determines the minimum gap size required for an FVG to qualify as an Inversion FVG.
Higher values: only larger FVGs become IFVGs
Lower values: smaller gaps are allowed
◇ Use First Presented IFVG:
This setting determines whether the indicator limits signals to only the first IFVG created within the manipulation leg.
What Is the First Presented IFVG?
It is the earliest FVG formed inside the displacement that causes the liquidity sweep.
For a bearish manipulation leg (price moving downward into the sweep), the first presented IFVG is the first FVG created at the start of that downward move:
For a bullish manipulation leg (price moving upward into the sweep), the first presented IFVG is the first FVG created at the start of that upward move:
When this setting is enabled, the indicator will only confirm signals when the IFVG used is derived from this first presented FVG. IFVGs that form later in the manipulation leg are not used for signal generation.
◇ Only Take Trades:
This setting allows users to restrict signals to a defined time window.
If a complete setup occurs inside the time window, it is allowed and plotted
If it occurs outside the window, the signal will not appear
For example, if you only wanted to see long/short signals between 9:30 AM and 12:00 PM, you would enable this setting and set the time window from 09:30 - 12:00.
◇ Minimum R:R
This setting allows users to require a minimum risk-to-reward ratio before a signal is confirmed and plotted on the chart. The risk-to-reward ratio is calculated using the distance from the Entry to the Stop-Loss (risk) and the distance from the Entry to TP2 (reward). The indicator compares these distances and determines whether the setup meets or exceeds the minimum R:R value selected by the user.
If the calculated R:R is equal to or greater than the chosen threshold, the signal will be displayed.
If the calculated R:R is lower than the threshold, the signal will not appear on the chart.
🔹 Signal Rating Minimum
Users can restrict which signal ratings appear:
A: shows all signals
A+: shows only A+ and A++
A++: shows only A++ setups
🔹 Signal Styling and Customization
The indicator provides full control over how signal labels and levels appear on your chart. Users can customize long signals, short signals, all plotted lines, and the visibility of every individual element.
◇ Long Signal Styling
Users can customize:
Long Signal Label Color
Long Signal Text Color
Long Signal Label Size
◇ Short Signal Styling
Users can customize:
Short Signal Label Color
Short Signal Text Color
Short Signal Label Size
◇ Entry, Stop Loss, Breakeven, and Take Profit Lines
Each line type can be enabled or disabled individually:
Entry Line
Stop Loss Line
Breakeven Line
Take Profit 1 & 2 Lines
Users can also set custom colors for each line so every level is easy to track during live price movement.
◇ Show Price Labels
Price labels can be toggled on or off individually for each level. Users can choose whether to show or hide the price for:
Entry
Stop loss
Breakeven
Take Profit 1 & 2
NEW DAY OPENING GAP:
The New Day Opening Gap (NDOG) highlights the price difference between the previous day’s closing candle and the first candle of the new trading day. The indicator tracks this gap automatically each day and makes it available as optional context for users.
🔹 What Is the New Day Opening Gap?
A New Day Opening Gap forms when the trading day opens at a price different from the previous day’s final closing price.
If the new day opens above the prior day’s close → Bullish NDOG
If the new day opens below the prior day’s close → Bearish NDOG
This gap acts as a short-term draw on liquidity because the market may revisit the gap to rebalance price delivery. While the NDOG is not a required component for IFVG signals.
🔹 How the Indicator Uses the New Day Opening Gap
When enabled, the indicator plots the gap as a rectangular zone spanning from the previous day’s close to the new day’s open. The zone remains active until it is fully filled by price or until the next day’s opening gap forms. Once price trades through the entire gap, or once a new NDOG replaces it the following day, the zone becomes inactive and is removed from the chart. The indicator does not use the NDOG for signal generation. It is strictly a visual tool that helps traders identify areas where price may retrace or seek liquidity during the session.
🔹 Customization Options
Users have full control over how the New Day Opening Gap displays on the chart:
Show New Day Opening Gap: Toggle the NDOG zone on or off
Bullish NDOG Color: Customize the fill color for gaps formed above the prior close
Bearish NDOG Color: Customize the fill color for gaps formed below the prior close
NEW WEEK OPENING GAP:
The New Week Opening Gap (NWOG) highlights the price difference between the previous week’s final closing candle and the first candle of the new trading week. The indicator tracks this gap automatically each week and provides it as optional context for users.
🔹 What Is the New Week Opening Gap?
A New Week Opening Gap forms when the new trading week opens at a price different from the previous week’s closing price.
If the new week opens above the prior week’s close → Bullish NWOG
If the new week opens below the prior week’s close → Bearish NWOG
This gap often serves as a medium-term draw on liquidity because price may return to rebalance the weekly displacement. The NWOG is not a required component for IFVG signals.
🔹 How the Indicator Uses the New Week Opening Gap
When enabled, the indicator plots the gap as a rectangular zone spanning from the previous week’s close to the new week’s open. The zone remains active until it is fully filled by price or until the next week’s opening gap forms. Once price trades through the entire gap, or once a new NWOG replaces it the following week, the zone becomes inactive and is removed from the chart. The indicator does not use the NWOG for signal generation. It is purely a visual reference to help traders identify areas where price may rebalance or seek liquidity during the week.
🔹 Customization Options
Users have full control over how the New Week Opening Gap displays on the chart:
Show New Week Opening Gap: Toggle the NWOG zone on or off
Bullish NWOG Color: Set the fill color for gaps formed above the prior weekly close
Bearish NWOG Color: Set the fill color for gaps formed below the prior weekly close
SMT DIVERGENCES:
The indicator automatically marks SMT Divergences that occur between the current selected chart ticker and a second user-selected ticker.
A SMT Divergence forms when the prices of the currently selected chart ticker and the user-selected ticker don’t follow each other. For example, if the current chart’s ticker symbol is SEED_ALEXDRAYM_SHORTINTEREST2:NQ and the user-selected ticker is $ES. If SEED_ALEXDRAYM_SHORTINTEREST2:NQ does not sweep the low of the NY AM Session, but NYSE:ES sweeps that same exact session’s low during the same candle, then a SMT Divergence is detected.
In the images below, SEED_ALEXDRAYM_SHORTINTEREST2:NQ and NYSE:ES form a low at 12:20 AM on November 12th. At 12:35 AM, the 12:20 AM low is taken out on $NQ. However, on NYSE:ES , price failed to take out this exact low at 12:35 AM. Thus, an SMT Divergence is detected, and a line is drawn between the two lows on $NQ.
NYSE:ES Chart:
SEED_ALEXDRAYM_SHORTINTEREST2:NQ Chart:
🔹 SMT Divergence Settings
The indicator includes settings that allow users to control how SMT Divergences are detected and displayed.
◇ Length
Length controls how sensitive the pivot detection is when finding highs and lows for SMT.
Lower Length: confirms swings with fewer bars, so more swings qualify.
Higher Length: requires more bars to confirm a swing, so fewer swings qualify.
◇ Divergence Length
The Divergence Length setting defines how many bars apart the two swing points may be for them to count as part of the same SMT Divergence.
Higher Values: The two instruments can form their swing highs or lows farther apart in time. As long as both swings occur within this wider bar window, the indicator compares them for divergence.
Lower Values: The two swing points must occur very close to each other.
◇ Show Last
This setting limits how many recent SMT Divergences are displayed on the chart. For example, setting Show Last to 1 will only show the most recent SMT Divergence, while higher values allow more historical SMT Divergences to remain visible on the chart.
◇ Divergence Ticker
Users can change the ticker used for detections. Since SMT Divergences occur by comparing two tickers, the inputted ticker within the settings will always be compared to the current selected ticker on your chart.
DASHBOARD:
The dashboard provides a live summary of all major components of the Inversion Fair Value Gap Model. It updates every candle and displays the current state of each requirement used in the setup logic.
🔹 Real-Time Model Components
The state of each component is displayed with the following:
✔️ = condition is satisfied
❌ = condition is not satisfied
🐂 / 🐻 = current directional bias (bullish or bearish)
The dashboard actively tracks the following:
◇ Bias (🐂 Bullish, 🐻 Bearish, or Both)
Shows the current bias with a bull or bear emoji. If using automatic bias, the dashboard updates as soon as the session logic determines a direction.
◇ Liquidity Sweep
Displays ✔️ once a valid BSL Sweep (for shorts) or SSL Sweep (for longs) is detected.
Shows ❌ when no sweep is present.
◇ V Shape Recovery
Displays ✔️ when a confirmed V shape recovery forms after the sweep.
Shows ❌ until a valid V shape appears.
◇ Inversion Fair Value Gap (IFVG)
Shows ✔️ once a bullish or bearish IFVG forms in the correct direction.
Shows ❌ when no IFVG has yet confirmed.
◇ Higher-Timeframe FVG Interaction
Displays ✔️ when price is currently inside any enabled HTF FVG or taps a HTF FVG during a liquidity sweep.
Displays ❌ when price is not inside a HTF imbalance.
◇ Clear Opposite Draw on Liquidity (DOL)
Shows ✔️ when a clear opposite-side draw is present in the model logic.
Shows ❌ if no clear opposite draw is detected.
◇ SMT Divergence
Shows ✔️ for 20 candles immediately after an SMT Divergence forms.
After 20 candles, it returns to ❌ unless a new SMT Divergence is detected.
🔹 Signal Information Display
When a valid long or short signal appears, the dashboard expands to show the full details of the setup, including:
Signal Rating
Entry Price
Stop-Loss Price
Breakeven Price
Take Profit 1 Price
Take Profit 2 Price
🔹 Trade Statistics Module
Users can enable a built-in statistics panel to view historical performance of signals across all ratings. The trade stats include:
A Signal Win Rate
A+ Signal Win Rate
A++ Signal Win Rate
Long Signal Win Rate
Short Signal Win Rate
Total Number of Trades Used in the Calculations
A trade is counted as a win if price reaches breakeven before stop-loss. A trade is counted as a loss if price hits stop-loss before breakeven.
🔹 Dashboard Customization
The dashboard includes several options to control its appearance and position:
Show Dashboard: Toggle the entire dashboard on or off
Dashboard Size: Choose the size of the dashboard
Dashboard Position: Choose the location of the dashboard on the chart
Trade Stats Text Color: Customize the color of the 2nd column outputs under the Trade Stats section in the dashboard
◇ Component Toggles
Users can enable or disable the display of any model component based on preference. Each of these items can be shown or hidden independently:
Setup Rating
Entry
Stop-Loss
Breakeven
Take Profit 1
Take Profit 2
Bias
Liquidity Sweep
Higher-Timeframe FVG Interaction
V Shape Recovery
Inversion FVG
Clear Opposite Draw on Liquidity
Trade Stats
These toggles only affect visual display. Disabling any of them does not affect the underlying indicator’s logic.
ALERTS:
The Inversion Fair Value Gap Model includes full alert functionality using AnyAlert(), allowing users to receive notifications in real time for all major model components and signal events.
Users can enable or disable each alert type in the “Alerts” section of the settings. After selecting which alerts they want active, they can create a single TradingView alert using the AnyAlert() condition. This will automatically trigger alerts for all enabled events as soon as they occur on the chart.
Available Alerts:
Long Signal
Short Signal
Breakeven Hit (BE)
Take Profit 1 Hit (TP1)
Take Profit 2 Hit (TP2)
Stop-Loss Hit (SL)
Liquidity Sweep Detected
SMT Divergence Detected
How to Receive Alerts:
Open the TradingView alert creation window.
Select the IFVG Model indicator as the alert condition.
Choose AnyAlert() from the condition dropdown.
Create the alert.
IMPORTANT NOTES:
TradingView has limitations when running features on multiple timeframes such as the HTF FVGs, which can result in the following restriction:
Computation Error:
The computation of using MTF features is very intensive on TradingView. This can sometimes cause calculation timeouts. When this occurs, simply force the recalculation by modifying one indicator’s settings or by removing the indicator and adding it to your chart again.
UNIQUENESS:
This indicator is unique because it organizes every part of the Inversion Fair Value Gap Model into one structured, rules based system. It detects liquidity sweeps, confirms V shape recoveries, identifies valid IFVGs, checks higher timeframe FVG taps, reads macro timing, and applies a session based directional bias. All of these components are evaluated in a fixed sequence so users always know exactly why a signal appears. Every part of the logic is customizable, including which liquidity types are used, which IFVGs qualify for signals, which time windows allow trades, the minimum risk to reward for a setup, and all visual elements on the chart. The tool also includes optional SMT Divergence detection, daily and weekly opening gaps, a live dashboard that shows the state of each model requirement, and optional signal performance statistics.
XAUUSD Multi-Timeframe Bias Scanner🎯 Purpose & Overview
This is a sophisticated trading indicator that analyzes XAUUSD (Gold) across 5 different timeframes simultaneously to determine market bias and trend direction.
⚙️ Core Components
2. Bias Calculation Engine
The heart of the indicator uses 5 technical factors to score each timeframe:
Technical Factors (Weighted):
Moving Average Alignment (30 points)
Bullish: EMA(9) > EMA(21) > EMA(50)
Bearish: EMA(9) < EMA(21) < EMA(50)
Price vs MA Position (20 points)
Score increases when price above MAs
Score decreases when price below MAs
RSI Momentum (20 points)
Bullish: RSI > 60 or > 50
Bearish: RSI < 40 or < 50
MACD Signals (15 points)
Bullish: MACD line > Signal line AND > 0
Bearish: MACD line < Signal line AND < 0
Volume Confirmation (15 points)
Volume spikes with price movement add confirmation
📊 Timeframe Analysis
Five Timeframes Monitored:
5-minute - Short-term noise (10% weight)
15-minute - Intraday direction (15% weight)
1-hour - Key intraday bias (25% weight)
4-hour - Primary directional bias (30% weight)
1-day - Overall trend context (20% weight)
Bias Scoring System:
0-100 Scale (50 = Neutral)
STRONG BULLISH: ≥70 (Green)
BULLISH: 55-69 (Lime)
NEUTRAL: 46-54 (Gray)
BEARISH: 31-45 (Orange)
STRONG BEARISH: ≤30 (Red)
🎨 Visual Features
1. Comprehensive Table Display
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var table biasTable = table.new(position.top_right, 3, 7, ...)
Shows a color-coded table with:
Timeframe name
Numerical bias score (0-100)
Strength description with color coding
2. Chart Visual Indicators
Background coloring based on overall bias
Label markers for strong bullish/bearish conditions
Real-time label showing all timeframe scores
3. Alert System
Triggers when overall bias crosses 70 (bullish) or 30 (bearish)
Configurable with sound options
🔄 How It Processes Data
Data Flow:
Requests security data for each timeframe using request.security()
Calculates technical indicators for each TF separately
Scores each TF based on 5 technical factors
Computes weighted overall bias
Updates visual displays and checks alert conditions
💡 Trading Applications
Bullish Scenarios:
Multiple timeframes show bullish alignment
Higher timeframe bias supports lower timeframe direction
Overall score > 70 indicates strong bullish conviction
Bearish Scenarios:
Multiple timeframes show bearish alignment
Higher timeframe bias confirms lower timeframe moves
Overall score < 30 indicates strong bearish conviction
Conflict Detection:
When timeframes show conflicting biases
Caution required - market may be consolidating
Wait for alignment before taking trades
🎚️ Customization Options
Users can modify:
Timeframe weights
Technical indicator parameters
Alert thresholds
Visual display preferences
Scoring sensitivity
📈 XAUUSD Specific Optimizations
The indicator considers Gold's unique characteristics:
High volatility periods
ATR-based volatility adjustments
Volume confirmation for breakouts
Multiple timeframe confirmation for trend reliability
This creates a powerful tool for identifying high-probability trade setups in XAUUSD by ensuring traders have a complete multi-timeframe perspective before entering positions.
Kalman Trend Sniper# KALMAN TREND SNIPER
## ORIGINALITY STATEMENT
The Kalman Trend Sniper combines adaptive trend detection with precision entry validation to identify high-probability trading opportunities. Unlike static moving averages that use fixed parameters, this indicator adapts to changing market volatility through ATR-based gain adjustment and distinguishes trending from ranging markets using ADX regime detection.
The indicator's unique contribution is its three-phase entry validation system: signals must hold for three bars, undergo a pullback test to the signal level, and receive confirmation through price action before generating an entry. This structured approach helps traders enter established trends at favorable retracement levels rather than chasing momentum.
---
## TECHNICAL METHODOLOGY
### Kalman Filter Implementation
This indicator implements an Alpha-Beta variant of the Kalman filter, a recursive algorithm that estimates trend from noisy price data:
1. Prediction: kf = kf + velocity
2. Error calculation: error = price - kf
3. Correction: kf = kf + gain * error
4. Velocity update: velocity = velocity + (gain * error) / 2
The gain parameter determines filter responsiveness. Higher gain values track price more closely but increase noise sensitivity, while lower values provide smoother output but lag price changes.
### Adaptive Gain Mechanism
The indicator adjusts gain dynamically based on volatility:
Volatility Factor = Current ATR / Long-term ATR
Adaptive Gain = Base Gain * (0.7 + 0.6 * Volatility Factor)
This ATR ratio increases responsiveness during high-volatility periods and reduces sensitivity during consolidations, addressing the fixed-parameter limitation of traditional moving averages. The volatility factor is bounded between configurable minimum and maximum values to prevent extreme adjustments.
### Regime Detection
The indicator uses the Average Directional Index (ADX) to distinguish market conditions:
- Trending markets (ADX above threshold): Full gain applied, signals generated
- Ranging markets (ADX below threshold): Gain reduced 25%, fewer signals
This regime awareness helps reduce whipsaw signals during sideways consolidation periods.
### Signal Line Validation System
When the Kalman line changes direction in trending conditions, the indicator draws a horizontal signal line at the low (for long signals) or high (for short signals) of the signal candle. This line represents a potential support or resistance level.
The validation system then monitors three phases:
Phase 1 - Hold Period: Price must remain above (long) or below (short) the signal line for three consecutive bars. This requirement filters weak signals where price immediately violates the signal level.
Phase 2 - Test: After the hold period, the system waits for price to pull back and touch the signal line, with configurable tolerance for volatile instruments.
Phase 3 - Confirmation: Within eight bars of the test, a confirmation candle must close above (long) or below (short) the test candle's body, demonstrating renewed momentum. If confirmation does not occur within eight bars, the validation attempt expires.
Successful validation generates an R label at the entry point. This three-phase structure helps identify entries where trend direction and support/resistance validation align.
---
## USAGE INSTRUCTIONS
### Signal Interpretation
Triangle Signals:
- Upward triangle (teal): Kalman line turns bullish in trending market (ADX above threshold)
- Downward triangle (red): Kalman line turns bearish in trending market
Signal Lines (horizontal):
- Teal line: Potential long support level at signal candle low
- Red line: Potential short resistance level at signal candle high
- Gray line: First opposite-color candle after signal (initial reversal pressure)
R Labels (optional, disabled by default):
- Green R below price: Validation complete for long entry
- Red R above price: Validation complete for short entry
Stop Levels:
- Red dots: Long stop level (Kalman line minus ATR multiplier)
- Teal dots: Short stop level (Kalman line plus ATR multiplier)
### Dashboard Information
The dashboard displays real-time indicator state:
- Trend: Current Kalman direction (BULL/BEAR)
- Regime: Market classification (Trending when ADX exceeds threshold, Ranging otherwise)
- Gain: Current adaptive gain value
- Vol Factor: Volatility ratio (current ATR / long-term ATR)
- ADX: Trend strength (higher values indicate stronger trends)
- Z-Score: Standard deviation distance from Kalman line (when enabled)
- Stop Dist: Current ATR-based stop distance
- Lines: Number of active signal lines displayed
- R-Status: Validation system state (Idle / Waiting / Testing)
### Trading Applications
Trend Following Approach:
1. Wait for triangle signal in trending market (ADX above threshold)
2. Enter immediately at signal candle close or wait for pullback
3. Place stop at displayed stop level
4. Trail stop using Kalman line as dynamic support/resistance
Validation Entry Approach (conservative):
1. After triangle signal, observe three-bar hold period
2. Wait for pullback to signal line (test phase)
3. Enter on R label confirmation
4. Place stop below/above signal line
5. Provides higher probability entries but reduces trade frequency
Z-Score Mean Reversion (when enabled):
1. Watch for Z-Score exceeding entry threshold (default +/-2.0)
2. Consider counter-trend entries when price touches Kalman line
3. Target return to Kalman line (Z-Score near zero)
4. Use Z-Score threshold as stop level for extreme continuation
### Optimal Conditions
The indicator performs optimally in clearly trending markets where ADX consistently exceeds the threshold. Performance degrades in sideways, choppy conditions.
Recommended timeframes:
- 1-5 minute charts: Use Crypto_1M preset (faster adaptation)
- 15-60 minute charts: Use Crypto_15M preset (balanced)
- Hourly charts: Use Forex preset (smoother)
- Daily charts: Use Stocks_Daily preset (long-term trends)
Market conditions:
- High volatility (Vol Factor above 1.5): Expect faster adaptation, wider stops needed
- Normal volatility (Vol Factor 0.7-1.5): Standard behavior
- Low volatility (Vol Factor below 0.7): Expect slower adaptation, tighter stops possible
---
## PARAMETER DOCUMENTATION
### Kalman Filter Settings
Preset Mode: Select optimized configuration for specific markets
- Custom: Manual parameter control
- Crypto_1M: Base Gain 0.05, ATR 7 (fast response for 1-5 minute crypto charts)
- Crypto_15M: Base Gain 0.03, ATR 14 (balanced for 15-60 minute crypto charts)
- Forex: Base Gain 0.02, ATR 14 (standard for forex pairs)
- Stocks_Daily: Base Gain 0.01, ATR 20 (smooth for daily stock charts)
Base Gain (0.001-0.2): Core Kalman filter responsiveness parameter. Higher values increase sensitivity to price changes. Low values (0.01-0.02) provide smooth output with fewer whipsaws but slower trend changes. High values (0.06-0.08) offer fast response with more signals but increased whipsaw risk.
Adaptive (checkbox): When enabled, automatically adjusts gain based on ATR ratio. Recommended to keep enabled for dynamic volatility adaptation.
ATR (5-50): Short-term Average True Range period for current volatility measurement. Default 14 is industry standard. Lower values respond faster to volatility changes.
Long ATR (20-200): Long-term ATR period for baseline volatility comparison. Default 50 provides stable reference. The ratio between ATR and Long ATR determines adaptive adjustment magnitude.
Regime Filter (checkbox): Enables ADX-based trending/ranging detection. When enabled, reduces gain by 25 percent during ranging markets to minimize false signals.
ADX Period (7-30): Period for ADX calculation. Default 14 is standard. Lower values respond faster to trend strength changes.
Threshold (15-40): ADX level distinguishing trending from ranging markets. Default 25. Above threshold: trending (generate signals normally). Below threshold: ranging (reduce sensitivity).
Min Vol / Max Vol (0.3-3.0): Bounds for volatility factor adjustment. Prevents extreme gain changes during unusual volatility spikes or quiet periods. Default minimum 0.5, maximum 2.0.
Stop ATR x (1.0-3.0): Multiplier for ATR-based stop loss distance. Default 2.0 places stops two ATRs from Kalman line. Use 1.5 for tight stops (intraday), 2.5-3.0 for wide stops (swing trading).
Show Signals (checkbox): Displays triangle signals when Kalman changes direction in trending markets. Disable to use indicator purely as dynamic support/resistance without signals.
Z-Score (checkbox): Enables mean-reversion signal generation based on statistical deviation from Kalman line.
Period (10-100): Lookback period for Z-Score standard deviation calculation. Default 20 bars. Longer periods produce smoother, less sensitive readings.
Entry (1.5-3.5): Standard deviation threshold for Z-Score signals. Default 2.0 generates signals at plus/minus two standard deviations (approximately 95th percentile moves).
Bull / Bear Colors: Customize Kalman line colors for uptrend (default teal) and downtrend (default red).
Fill (checkbox): Shows semi-transparent fill between price and Kalman line for visual trend emphasis.
### Signal Line System Settings
Signal Lines (checkbox): Displays horizontal signal lines at low (long) or high (short) of signal candles. These function as dynamic support/resistance levels.
Reverse Lines (checkbox): Shows gray horizontal lines at first opposite-colored candle after signal. Helps identify initial resistance points in new trends.
Max Lines (0-20): Maximum number of signal lines to display simultaneously. Older lines are removed as new signals appear. Use 1-2 for clean charts, 3-5 for recent support/resistance history.
Style (Solid/Dotted/Dashed): Visual style for signal and reverse lines. Dotted provides subtle appearance, solid is most prominent.
Line % / Label % (0-100): Transparency percentage for lines and labels. Zero is fully opaque, 100 is invisible.
R Labels (checkbox): Shows R labels when validation confirmation occurs. Default disabled. Enable if you want visual confirmation of successful pullback entries.
Tolerance % (0-1.0): Price deviation tolerance for test candle detection. Zero requires exact touch. 0.5 allows 0.5 percent deviation for volatile instruments.
### Dashboard Settings
Show Dashboard (checkbox): Toggles visibility of information panel. Disable for clean chart presentation.
Position: Choose dashboard location from nine positions (Top/Middle/Bottom combined with Left/Center/Right).
---
## LIMITATIONS AND WARNINGS
This indicator is a technical analysis tool that processes historical price data. It does not predict future price movements.
Inherent limitations:
1. Lagging nature: Like all trend indicators, the Kalman filter lags price. Signals occur after trend changes begin, not before.
2. Ranging markets: Generates fewer signals and reduced performance when ADX falls below threshold. Not optimized for sideways consolidation.
3. Whipsaw risk: In choppy, indecisive markets near ADX threshold, signals may reverse quickly despite regime filtering.
4. Parameter sensitivity: Inappropriate Base Gain settings can cause over-trading (too high) or missed trends (too low).
5. Validation requirement: The three-phase confirmation system provides higher accuracy but significantly reduces trade frequency. Not all trends produce valid pullback entries.
Not suitable for:
- Scalping strategies requiring instant signals (Kalman filter has intentional smoothing)
- Ultra-high frequency trading (indicator updates once per bar close)
- Markets with extreme overnight gaps (stops may be exceeded)
- Strategies requiring signals on Heikin Ashi, Renko, Kagi, Point and Figure, or Range charts
Risk management requirements:
This indicator provides trend direction and signal levels but does not incorporate position sizing, risk management, or account balance considerations. Users must implement appropriate position sizing, maximum daily loss limits, and portfolio diversification. Past performance does not indicate future results.
Optimal usage:
- Works optimally in clearly trending markets where ADX consistently exceeds threshold
- Performance degrades in sideways, choppy conditions
- Designed for swing trading and position trading timeframes (15-minute and above)
- Requires confirmation from price action or additional technical analysis
---
## NO REPAINT GUARANTEE
This indicator operates on bar close confirmation only. All signals, signal lines, and validation labels appear exclusively when candles close. Historical signals remain exactly where they appeared. This makes the indicator suitable for automated trading and reliable backtesting. What you see in historical data matches what appeared in real-time.
---
## ALERTS
The indicator provides eight alert conditions:
1. Kalman Buy Signal: Fires when upward triangle appears (bullish trend change in trending market)
2. Kalman Sell Signal: Fires when downward triangle appears (bearish trend change in trending market)
3. Trend Change to Bullish: Fires whenever Kalman line changes to bullish (regardless of ADX)
4. Trend Change to Bearish: Fires whenever Kalman line changes to bearish (regardless of ADX)
5. SCT-R Long Retest Confirmed: Fires when green R label appears for long validation
6. SCT-R Short Retest Confirmed: Fires when red R label appears for short validation
7. SCT Test Long Detected: Fires when test candle appears for long signal (before confirmation)
8. SCT Test Short Detected: Fires when test candle appears for short signal (before confirmation)
Alert messages include context about bar close confirmation and current price levels.
---
## CALCULATION TRANSPARENCY
While complete proprietary optimization methodology is not disclosed, the core technical approach is fully explained: Alpha-Beta Kalman filter with ATR-based adaptive gain adjustment and ADX regime detection. The signal line validation system uses a three-phase structure (hold, test, confirmation) with configurable parameters. Users can understand indicator functionality and make informed decisions about application.
---
## DISCLAIMER
This indicator is provided as a technical analysis tool. It does not constitute financial advice, trading recommendations, or performance guarantees. All trading decisions carry risk. Users are responsible for their own trading decisions and risk management. Past results do not indicate future performance.
Scout Regiment - OBV# Scout Regiment - OBV Indicator
## English Documentation
### Overview
Scout Regiment - OBV (On-Balance Volume) is an advanced momentum indicator that combines volume and price movement to identify the strength of buying and selling pressure. This indicator features an oscillator-based approach with divergence detection to help traders spot potential trend reversals and confirm price movements.
### What is OBV?
On-Balance Volume (OBV) is a cumulative volume indicator that adds volume on up days and subtracts volume on down days:
- **Rising OBV**: Accumulation (buying pressure)
- **Falling OBV**: Distribution (selling pressure)
- **OBV Oscillator**: The difference between OBV and its smoothed moving average, making divergences easier to spot
### Key Features
#### 1. **OBV Oscillator Display**
Instead of displaying raw OBV values, this indicator shows the oscillator (difference between OBV and its smoothed line):
**Benefits:**
- Easier to identify divergences
- Clearer trend changes
- More sensitive to momentum shifts
- Zero line as reference point
**Visual Elements:**
- **Step Line**: Main OBV oscillator line
- Green: Positive oscillator (accumulation)
- Red: Negative oscillator (distribution)
- **Histogram**: Visual representation of oscillator strength
- Green bars: Above zero line
- Red bars: Below zero line
- **Zero Line**: White dotted horizontal line as reference
#### 2. **Smoothing Options**
Choose from multiple moving average types to smooth the OBV:
- **None**: Raw OBV (most sensitive)
- **SMA**: Simple Moving Average (equal weight)
- **EMA**: Exponential Moving Average (recent price emphasis) - Default
- **SMMA (RMA)**: Smoothed Moving Average (very smooth)
- **WMA**: Weighted Moving Average (linear weight)
- **VWMA**: Volume Weighted Moving Average (volume emphasis)
**Default Settings:**
- Type: EMA
- Length: 21 periods
- Best for: Most market conditions
#### 3. **Multi-Timeframe Analysis**
- Calculate OBV on any timeframe
- View higher timeframe momentum on lower timeframe charts
- Align trades with larger timeframe volume trends
- Empty field = Current chart timeframe
#### 4. **Visual Enhancements**
**Background Color**
- Light green: Positive oscillator (bullish volume pressure)
- Light red: Negative oscillator (bearish volume pressure)
- Optional display for cleaner charts
**Crossover Labels**
- "突破" (Breakout): When oscillator crosses above zero
- "跌破" (Breakdown): When oscillator crosses below zero
- Indicates potential trend changes
- Can be toggled on/off
#### 5. **Comprehensive Divergence Detection**
The indicator automatically detects four types of divergences:
**Regular Bullish Divergence (Yellow)**
- **Price**: Makes lower lows
- **OBV**: Makes higher lows
- **Signal**: Potential upward reversal
- **Label**: "看涨" (Bullish)
- **Use**: Enter long positions
**Regular Bearish Divergence (Blue)**
- **Price**: Makes higher highs
- **OBV**: Makes lower highs
- **Signal**: Potential downward reversal
- **Label**: "看跌" (Bearish)
- **Use**: Enter short positions or exit longs
**Hidden Bullish Divergence (Light Yellow)**
- **Price**: Makes higher lows
- **OBV**: Makes lower lows
- **Signal**: Trend continuation (uptrend)
- **Label**: "隐藏看涨" (Hidden Bullish)
- **Use**: Add to long positions
**Hidden Bearish Divergence (Light Blue)**
- **Price**: Makes lower highs
- **OBV**: Makes higher highs
- **Signal**: Trend continuation (downtrend)
- **Label**: "隐藏看跌" (Hidden Bearish)
- **Use**: Add to short positions
#### 6. **Customizable Divergence Detection**
**Pivot Lookback Settings:**
- **Left Lookback**: Bars to the left of pivot (default: 5)
- **Right Lookback**: Bars to the right of pivot (default: 5)
- Determines how "extreme" a point must be to qualify as a pivot
**Range Settings:**
- **Maximum Range**: Maximum bars between pivots (default: 60)
- **Minimum Range**: Minimum bars between pivots (default: 5)
- Filters out too-close or too-distant divergences
**Display Options:**
- Toggle regular divergences on/off
- Toggle hidden divergences on/off
- Toggle divergence labels on/off
- Show only the divergences you need
### Configuration Settings
#### Smoothing Settings
- **Smoothing Type**: Choose MA type (None/SMA/EMA/SMMA/WMA/VWMA)
- **Smoothing Length**: Number of periods for smoothing (default: 21)
#### Calculation Settings
- **Timeframe**: Select calculation timeframe (empty = current chart)
#### Display Settings
- **Show OBV Line**: Toggle step line display
- **Show OBV Histogram**: Toggle histogram display
- **Show Background Color**: Toggle background coloring
- **Show Crossover Labels**: Toggle breakout/breakdown labels
#### Divergence Settings
- **Pivot Right Lookback**: Right bars for pivot detection (default: 5)
- **Pivot Left Lookback**: Left bars for pivot detection (default: 5)
- **Range Maximum**: Max bars between divergences (default: 60)
- **Range Minimum**: Min bars between divergences (default: 5)
- **Show Regular Divergences**: Enable/disable regular divergences
- **Show Regular Labels**: Enable/disable regular divergence labels
- **Show Hidden Divergences**: Enable/disable hidden divergences
- **Show Hidden Labels**: Enable/disable hidden divergence labels
### How to Use
#### For Trend Confirmation
1. **Identify Trend with Price**
- Uptrend: Higher highs and higher lows
- Downtrend: Lower highs and lower lows
2. **Confirm with OBV Oscillator**
- Strong uptrend: OBV oscillator staying positive
- Strong downtrend: OBV oscillator staying negative
- Weak trend: OBV oscillator frequently crossing zero
3. **Volume Confirmation**
- Trend with increasing OBV = Strong trend
- Trend with decreasing OBV = Weak trend (watch for reversal)
#### For Divergence Trading
1. **Enable Divergence Detection**
- Start with regular divergences only
- Add hidden divergences for trend continuation
2. **Wait for Divergence Signal**
- Yellow label = Potential bullish reversal
- Blue label = Potential bearish reversal
3. **Confirm with Price Action**
- Wait for support/resistance break
- Look for candlestick confirmation
- Check higher timeframe alignment
4. **Enter Trade**
- Enter after confirmation
- Set stop loss beyond recent swing
- Target based on previous swing or support/resistance
#### For Breakout Trading
1. **Enable Crossover Labels**
- Identify when oscillator crosses zero line
2. **Confirm Volume Strength**
- Strong breakouts have large oscillator moves
- Weak breakouts barely cross zero
3. **Trade Direction**
- "突破" label = Enter long
- "跌破" label = Enter short
4. **Manage Position**
- Exit when oscillator crosses back
- Use price structure for stops
#### For Multi-Timeframe Analysis
1. **Set Higher Timeframe**
- Example: On 15min chart, set timeframe to 1H or 4H
2. **Identify Higher Timeframe Trend**
- Positive oscillator = Uptrend bias
- Negative oscillator = Downtrend bias
3. **Trade with the Trend**
- Only take long signals in uptrend
- Only take short signals in downtrend
4. **Time Entries**
- Use current timeframe for precise entry
- Confirm with higher timeframe direction
### Trading Strategies
#### Strategy 1: Regular Divergence Reversal
**Setup:**
1. Price in strong trend (up or down)
2. Regular divergence appears
3. Price reaches support/resistance level
**Entry:**
- Bullish: After "看涨" label, when price breaks above recent high
- Bearish: After "看跌" label, when price breaks below recent low
**Stop Loss:**
- Bullish: Below divergence low
- Bearish: Above divergence high
**Exit:**
- Take profit at next major support/resistance
- Or when opposite divergence appears
**Best For:** Swing trading, reversal trading
#### Strategy 2: Hidden Divergence Continuation
**Setup:**
1. Clear trend established
2. Price pulls back (retracement)
3. Hidden divergence appears
**Entry:**
- Bullish: After "隐藏看涨" label, when price resumes uptrend
- Bearish: After "隐藏看跌" label, when price resumes downtrend
**Stop Loss:**
- Behind the pullback swing point
**Exit:**
- Trail stop as trend continues
- Exit on regular divergence (reversal signal)
**Best For:** Trend following, adding to positions
#### Strategy 3: Zero Line Crossover
**Setup:**
1. Enable crossover labels
2. Oscillator crosses zero line
3. Confirm with price structure break
**Entry:**
- "突破" label = Buy signal
- "跌破" label = Sell signal
**Stop Loss:**
- Below/above recent swing
**Exit:**
- When oscillator crosses back over zero
- Or at predetermined target
**Best For:** Momentum trading, quick trades
#### Strategy 4: Multi-Timeframe Confluence
**Setup:**
1. Set indicator to higher timeframe (e.g., 4H on 1H chart)
2. Wait for higher TF oscillator to be positive (uptrend) or negative (downtrend)
3. Look for entries on current timeframe aligned with higher TF
**Entry:**
- Long: When both timeframes show positive oscillator or bullish divergence
- Short: When both timeframes show negative oscillator or bearish divergence
**Stop Loss:**
- Based on current timeframe structure
**Exit:**
- When higher timeframe oscillator turns negative (for longs) or positive (for shorts)
**Best For:** Swing trading, high-probability setups
### Best Practices
#### Volume Analysis
1. **Strong Moves Need Volume**
- Price increase + Rising OBV = Healthy uptrend
- Price increase + Falling OBV = Weak uptrend (warning)
2. **Watch for Confirmation**
- New highs with new OBV highs = Confirmed
- New highs without new OBV highs = Potential divergence
3. **Consider Context**
- Low volume periods (Asian session, holidays) = Less reliable
- High volume periods (News, London/NY overlap) = More reliable
#### Divergence Trading Tips
1. **Not All Divergences Work**
- Wait for price confirmation
- Stronger in oversold/overbought areas
- Better at support/resistance levels
2. **Multiple Divergences**
- Multiple divergences on same trend = Stronger signal
- Quick divergence failures = Ignore and wait for next
3. **Timeframe Matters**
- Higher timeframe divergences = More reliable
- Lower timeframe divergences = More frequent, less reliable
#### Smoothing Selection
1. **No Smoothing (None)**
- Most sensitive, more signals
- More noise, more false signals
- Best for: Scalping, very active trading
2. **EMA (Default)**
- Balanced approach
- Good for most strategies
- Best for: Swing trading, day trading
3. **SMMA (RMA)**
- Very smooth, fewer signals
- Less responsive to sudden changes
- Best for: Position trading, longer timeframes
### Indicator Combinations
**With Moving Averages:**
- Use EMAs for trend direction
- OBV for volume confirmation
- Enter when both align
**With RSI:**
- RSI for overbought/oversold
- OBV for volume confirmation
- Divergences on both = Stronger signal
**With Price Action:**
- Support/resistance for levels
- OBV for strength confirmation
- Breakouts with positive OBV = More likely to succeed
**With Bias Indicator:**
- Bias for price deviation
- OBV for volume confirmation
- Both showing divergence = High probability reversal
### Common Patterns
1. **Accumulation**: OBV rising while price consolidates (breakout likely)
2. **Distribution**: OBV falling while price consolidates (breakdown likely)
3. **Confirmation**: OBV and price both making new highs/lows (trend strong)
4. **Divergence**: OBV and price moving opposite directions (reversal warning)
5. **False Breakout**: Price breaks but OBV doesn't confirm (likely to fail)
### Performance Tips
- Disable unused display features for faster loading
- Start with regular divergences only, add hidden later
- Use histogram for quick visual reference
- Enable crossover labels for clear entry signals
- Test different smoothing lengths for your market
### Alert Conditions
The indicator includes alerts for:
- Regular bullish divergence detected
- Regular bearish divergence detected
- Hidden bullish divergence detected
- Hidden bearish divergence detected
**How to Set Alerts:**
1. Click on the indicator name
2. Select "Add Alert"
3. Choose condition
4. Configure notification method
---
## 中文说明文档
### 概述
Scout Regiment - OBV（能量潮）是一个高级动量指标，结合成交量和价格变动来识别买卖压力的强度。该指标采用振荡器方法并具有背离检测功能，帮助交易者发现潜在的趋势反转并确认价格走势。
### 什么是OBV？
能量潮（OBV）是一个累积成交量指标，在上涨日累加成交量，在下跌日减去成交量：
- **上升的OBV**：积累（买入压力）
- **下降的OBV**：派发（卖出压力）
- **OBV振荡器**：OBV与其平滑移动平均线之间的差值，使背离更容易识别
### 核心功能
#### 1. **OBV振荡器显示**
该指标不显示原始OBV值，而是显示振荡器（OBV与其平滑线之间的差值）：
**优势：**
- 更容易识别背离
- 趋势变化更清晰
- 对动量变化更敏感
- 零线作为参考点
**视觉元素：**
- **阶梯线**：主OBV振荡器线
- 绿色：正振荡器（积累）
- 红色：负振荡器（派发）
- **柱状图**：振荡器强度的可视化表示
- 绿色柱：零线以上
- 红色柱：零线以下
- **零线**：白色虚线作为参考
#### 2. **平滑选项**
选择多种移动平均类型来平滑OBV：
- **None**：原始OBV（最敏感）
- **SMA**：简单移动平均（等权重）
- **EMA**：指数移动平均（强调近期价格）- 默认
- **SMMA (RMA)**：平滑移动平均（非常平滑）
- **WMA**：加权移动平均（线性权重）
- **VWMA**：成交量加权移动平均（强调成交量）
**默认设置：**
- 类型：EMA
- 长度：21周期
- 适合：大多数市场状况
#### 3. **多时间框架分析**
- 在任何时间框架上计算OBV
- 在低时间框架图表上查看高时间框架动量
- 使交易与更大时间框架的成交量趋势保持一致
- 空字段 = 当前图表时间框架
#### 4. **视觉增强**
**背景颜色**
- 浅绿色：正振荡器（看涨成交量压力）
- 浅红色：负振荡器（看跌成交量压力）
- 可选显示，图表更清爽
**穿越标签**
- "突破"：振荡器向上穿越零线
- "跌破"：振荡器向下穿越零线
- 指示潜在趋势变化
- 可开关
#### 5. **全面的背离检测**
指标自动检测四种类型的背离：
**常规看涨背离（黄色）**
- **价格**：创新低
- **OBV**：创更高的低点
- **信号**：潜在向上反转
- **标签**："看涨"
- **用途**：进入多头仓位
**常规看跌背离（蓝色）**
- **价格**：创新高
- **OBV**：创更低的高点
- **信号**：潜在向下反转
- **标签**："看跌"
- **用途**：进入空头仓位或退出多头
**隐藏看涨背离（浅黄色）**
- **价格**：创更高的低点
- **OBV**：创更低的低点
- **信号**：趋势延续（上升趋势）
- **标签**："隐藏看涨"
- **用途**：加仓多头
**隐藏看跌背离（浅蓝色）**
- **价格**：创更低的高点
- **OBV**：创更高的高点
- **信号**：趋势延续（下降趋势）
- **标签**："隐藏看跌"
- **用途**：加仓空头
#### 6. **可自定义的背离检测**
**枢轴回溯设置：**
- **左侧回溯**：枢轴点左侧K线数（默认：5）
- **右侧回溯**：枢轴点右侧K线数（默认：5）
- 决定一个点要多"极端"才能成为枢轴点
**范围设置：**
- **最大范围**：枢轴点之间最大K线数（默认：60）
- **最小范围**：枢轴点之间最小K线数（默认：5）
- 过滤太近或太远的背离
**显示选项：**
- 开关常规背离
- 开关隐藏背离
- 开关背离标签
- 只显示需要的背离
### 配置设置
#### 平滑设置
- **平滑类型**：选择MA类型（None/SMA/EMA/SMMA/WMA/VWMA）
- **平滑长度**：平滑周期数（默认：21）
#### 计算设置
- **时间周期**：选择计算时间框架（空 = 当前图表）
#### 显示设置
- **显示OBV点线**：切换阶梯线显示
- **显示OBV柱状图**：切换柱状图显示
- **显示背景颜色**：切换背景着色
- **显示突破标签**：切换突破/跌破标签
#### 背离设置
- **枢轴右侧回溯**：枢轴检测右侧K线数（默认：5）
- **枢轴左侧回溯**：枢轴检测左侧K线数（默认：5）
- **回看范围最大值**：背离之间最大K线数（默认：60）
- **回看范围最小值**：背离之间最小K线数（默认：5）
- **显示常规背离**：启用/禁用常规背离
- **显示常规背离标签**：启用/禁用常规背离标签
- **显示隐藏背离**：启用/禁用隐藏背离
- **显示隐藏背离标签**：启用/禁用隐藏背离标签
### 使用方法
#### 趋势确认
1. **用价格识别趋势**
- 上升趋势：更高的高点和更高的低点
- 下降趋势：更低的高点和更低的低点
2. **用OBV振荡器确认**
- 强劲上升趋势：OBV振荡器保持正值
- 强劲下降趋势：OBV振荡器保持负值
- 弱势趋势：OBV振荡器频繁穿越零线
3. **成交量确认**
- 趋势伴随上升的OBV = 强趋势
- 趋势伴随下降的OBV = 弱趋势（注意反转）
#### 背离交易
1. **启用背离检测**
- 先从常规背离开始
- 添加隐藏背离用于趋势延续
2. **等待背离信号**
- 黄色标签 = 潜在看涨反转
- 蓝色标签 = 潜在看跌反转
3. **用价格行为确认**
- 等待支撑/阻力突破
- 寻找K线确认
- 检查更高时间框架对齐
4. **进入交易**
- 确认后进入
- 在近期波动之外设置止损
- 基于前一波动或支撑/阻力设定目标
#### 突破交易
1. **启用穿越标签**
- 识别振荡器何时穿越零线
2. **确认成交量强度**
- 强突破有大振荡器移动
- 弱突破勉强穿越零线
3. **交易方向**
- "突破"标签 = 进入多头
- "跌破"标签 = 进入空头
4. **管理仓位**
- 振荡器反向穿越时退出
- 使用价格结构设置止损
#### 多时间框架分析
1. **设置更高时间框架**
- 例如：在15分钟图上，设置时间框架为1H或4H
2. **识别更高时间框架趋势**
- 正振荡器 = 上升趋势偏向
- 负振荡器 = 下降趋势偏向
3. **顺趋势交易**
- 仅在上升趋势中接受多头信号
- 仅在下降趋势中接受空头信号
4. **把握入场时机**
- 使用当前时间框架进行精确进入
- 用更高时间框架方向确认
### 交易策略
#### 策略1：常规背离反转
**设置：**
1. 价格处于强趋势（上涨或下跌）
2. 出现常规背离
3. 价格到达支撑/阻力水平
**入场：**
- 看涨：在"看涨"标签后，价格突破近期高点时
- 看跌：在"看跌"标签后，价格跌破近期低点时
**止损：**
- 看涨：背离低点之下
- 看跌：背离高点之上
**退出：**
- 在下一个主要支撑/阻力获利
- 或出现相反背离时
**适合：**波段交易、反转交易
#### 策略2：隐藏背离延续
**设置：**
1. 建立明确趋势
2. 价格回调（回撤）
3. 出现隐藏背离
**入场：**
- 看涨：在"隐藏看涨"标签后，价格恢复上升趋势时
- 看跌：在"隐藏看跌"标签后，价格恢复下降趋势时
**止损：**
- 在回调波动点之后
**退出：**
- 随着趋势延续移动止损
- 出现常规背离（反转信号）时退出
**适合：**趋势跟随、加仓
#### 策略3：零线穿越
**设置：**
1. 启用穿越标签
2. 振荡器穿越零线
3. 用价格结构突破确认
**入场：**
- "突破"标签 = 买入信号
- "跌破"标签 = 卖出信号
**止损：**
- 近期波动之下/之上
**退出：**
- 振荡器反向穿越零线时
- 或在预定目标
**适合：**动量交易、快速交易
#### 策略4：多时间框架汇合
**设置：**
1. 设置指标到更高时间框架（例如，在1H图上设置4H）
2. 等待更高TF振荡器为正（上升趋势）或负（下降趋势）
3. 在当前时间框架上寻找与更高TF一致的入场机会
**入场：**
- 多头：两个时间框架都显示正振荡器或看涨背离时
- 空头：两个时间框架都显示负振荡器或看跌背离时
**止损：**
- 基于当前时间框架结构
**退出：**
- 更高时间框架振荡器变为负（多头）或正（空头）时
**适合：**波段交易、高概率设置
### 最佳实践
#### 成交量分析
1. **强势波动需要成交量**
- 价格上涨 + 上升的OBV = 健康上升趋势
- 价格上涨 + 下降的OBV = 弱上升趋势（警告）
2. **注意确认**
- 新高伴随新OBV高点 = 已确认
- 新高没有新OBV高点 = 潜在背离
3. **考虑背景**
- 低成交量期（亚洲时段、假期）= 可靠性较低
- 高成交量期（新闻、伦敦/纽约重叠）= 更可靠
#### 背离交易技巧
1. **不是所有背离都有效**
- 等待价格确认
- 在超卖/超买区域更强
- 在支撑/阻力水平更好
2. **多重背离**
- 同一趋势上多个背离 = 更强信号
- 背离快速失败 = 忽略并等待下一个
3. **时间框架重要**
- 更高时间框架背离 = 更可靠
- 更低时间框架背离 = 更频繁，可靠性较低
#### 平滑选择
1. **无平滑（None）**
- 最敏感，更多信号
- 更多噪音，更多假信号
- 适合：剥头皮、非常活跃的交易
2. **EMA（默认）**
- 平衡方法
- 适合大多数策略
- 适合：波段交易、日内交易
3. **SMMA (RMA)**
- 非常平滑，更少信号
- 对突然变化响应较慢
- 适合：仓位交易、更长时间框架
### 指标组合
**与移动平均线配合：**
- 使用EMA确定趋势方向
- OBV确认成交量
- 两者一致时进入
**与RSI配合：**
- RSI用于超买超卖
- OBV用于成交量确认
- 两者都背离 = 更强信号
**与价格行为配合：**
- 支撑/阻力确定水平
- OBV确认强度
- 正OBV的突破 = 更可能成功
**与Bias指标配合：**
- Bias用于价格偏离
- OBV用于成交量确认
- 两者都显示背离 = 高概率反转
### 常见形态
1. **积累**：OBV上升而价格盘整（突破可能）
2. **派发**：OBV下降而价格盘整（跌破可能）
3. **确认**：OBV和价格都创新高/新低（趋势强劲）
4. **背离**：OBV和价格反向移动（反转警告）
5. **假突破**：价格突破但OBV不确认（可能失败）
### 性能提示
- 禁用未使用的显示功能以加快加载
- 先从常规背离开始，稍后添加隐藏背离
- 使用柱状图快速视觉参考
- 启用穿越标签以获得清晰的入场信号
- 为您的市场测试不同的平滑长度
### 警报条件
指标包含以下警报：
- 检测到常规看涨背离
- 检测到常规看跌背离
- 检测到隐藏看涨背离
- 检测到隐藏看跌背离
**如何设置警报：**
1. 点击指标名称
2. 选择"添加警报"
3. 选择条件
4. 配置通知方法
---
## Technical Support
For questions or issues, please refer to the TradingView community or contact the indicator creator.
## 技术支持
如有问题，请参考TradingView社区或联系指标创建者。
ICT/SMC DOL Detector PRO (Final)This indicator is designed to operate only on the 1-hour timeframe.
The ICT/SMC DOL Detector PRO is an educational indicator designed to identify and visualize Draw on Liquidity (DOL) levels across multiple time-frames. It tracks unmitigated daily highs and lows, clusters them into zones, and calculates confidence scores based on multiple factors including time decay, cluster size, and time-frame alignment.
This indicator is based on ICT (Inner Circle Trader) concepts and liquidity theory, which suggests that price tends to seek out areas of concentrated unfilled orders before reversing or continuing its trend.
What is a DOL (Draw on Liquidity)?
A Draw on Liquidity represents a daily high or low that has not been revisited (mitigated) by price. These levels act as "magnets" that draw price toward them because:
1. They represent untapped liquidity pools where unfilled orders exist
2. Market makers and institutions often target these levels to fill large orders
3. Price is drawn to these zones to clear pending orders
4. They can serve as potential reversal or continuation zones once liquidity is taken
Methodology
1. Level Tracking
The indicator monitors daily session highs and lows on the 1-hour time-frame, tracking:
- Session high price and time of formation
- Session low price and time of formation
- Whether each level has been breached (mitigated)
- Time elapsed since level formation
2. Clustering Algorithm
Unmitigated levels within a defined tolerance (default 0.5% of price) are grouped together to identify zones where multiple DOLs cluster. Larger clusters indicate stronger liquidity pools.
3. Confidence Scoring (The "AI" Logic)
Each DOL receives a confidence score (0-100%) based on three weighted factors. This is the core "AI" intelligence of the indicator:
**Factor 1: Cluster Size (50% weight)**
- Counts how many unmitigated levels exist within 0.5% of the price zone
- Formula: (levels_in_cluster / total_unmitigated_levels) × 50
- Logic: More unfilled orders clustered together = stronger liquidity pool = higher confidence
- Example: If 5 out of 10 total unmitigated levels cluster at 27,500, cluster score = (5/10) × 50 = 25%
**Factor 2: Time Decay (25% weight)**
- Calculates age of the level since formation
- Fresh levels (< 1 week old): Full 25% score
- Aging penalty: Loses 5% per week of age
- Maximum penalty: 25% (very old levels = 0% time score)
- Formula: max(0, 25 - (weeks_old × 5))
- Logic: Recent liquidity is more relevant than old liquidity that price has ignored for months
**Factor 3: Timeframe Alignment (25% weight)**
- Checks how many timeframes (1H, 4H, D1, W1) point in the same direction
- If multiple timeframes identify DOLs on the same side (all bullish or all bearish): Higher score
- If mixed signals: Lower score
- Formula: (aligned_timeframes / total_timeframes) × 25
- Logic: When multiple timeframes agree, the liquidity zone is validated across different time perspectives
**Total Confidence Score:**
```
Confidence = Cluster_Score + Time_Score + Alignment_Score
= (0-50%) + (0-25%) + (0-25%)
= 0-100%
```
**Example Calculation:**
```
DOL at 27,500:
- 6 out of 12 unmitigated levels cluster here → (6/12) × 50 = 25%
- Level is 2 weeks old → 25 - (2 × 5) = 15%
- 3 out of 4 timeframes bullish toward this level → (3/4) × 25 = 18.75%
- Total Confidence = 25% + 15% + 18.75% = 58.75% ≈ 59%
```
This mathematical approach removes subjectivity and provides objective, data-driven confidence scoring.
4. Multi-Timeframe Analysis
The indicator analyzes DOLs across four timeframes:
- **1H:** Intraday levels (fastest reaction)
- **4H:** Short-term swing levels
- **Daily:** Intermediate-term levels
- **Weekly:** Long-term structural levels
For each timeframe, it identifies:
- Highest confidence unmitigated high
- Highest confidence unmitigated low
- Directional bias (bullish if high > low confidence, bearish if low > high confidence)
5. Primary DOL Selection (AI Auto-Selection Logic)
When "Show AI DOL" is enabled, the indicator uses an automated selection algorithm to identify the most important targets:
**Step 1: Collect All Candidates**
The algorithm gathers all identified DOLs from all timeframes (1H, 4H, D1, W1) that meet minimum criteria:
- Must be unmitigated (not yet swept)
- Must have confidence score > 0%
- Must have at least 1 level in cluster
**Step 2: Calculate Confidence for Each**
Each candidate DOL receives its confidence score using the three-factor formula described above (Cluster + Time + Alignment).
**Step 3: Sort by Confidence**
All candidates are ranked from highest to lowest confidence score.
**Step 4: Select Primary and Secondary**
- **P1 (Primary DOL):** The DOL with the absolute highest confidence score
- **P2 (Secondary DOL):** The DOL with the second highest confidence score
**Why This Matters:**
Instead of manually scanning multiple timeframes and guessing which level is most important, the AI objectively identifies the two highest-probability liquidity targets based on quantifiable data.
**Example AI Selection:**
```
Available DOLs:
- 1H High: 27,400
- 4H High: 27,500
- D1 High: 27,500 ← P1 (Highest)
- W1 High: 27,650 ← P2 (Second Highest)
- 1H Low: 26,800
- D1 Low: 26,500
AI Selection:
P1 = 27,500 (Daily High with 92% confidence)
P2 = 27,650 (Weekly High with 88% confidence)
```
This provides a data-driven target selection rather than subjective manual interpretation. The AI removes emotion and bias, selecting targets based purely on mathematical probability.
Features
Why "AI" DOL?
The term "AI" in this indicator refers to the automated algorithmic selection process, not machine learning or neural networks. Specifically:
**What the AI Does:**
- Automatically evaluates all available DOLs across all timeframes
- Applies a weighted scoring algorithm (Cluster 50%, Time 25%, Alignment 25%)
- Objectively ranks DOLs by probability
- Selects the top 2 highest-confidence targets (P1 and P2)
- Removes human bias and emotion from target selection
**What the AI Does NOT Do:**
- It does not use machine learning or train on historical data
- It does not predict future price movements
- It does not adapt or "learn" over time
- It does not guarantee accuracy
The "AI" is simply an automated decision-making algorithm that applies consistent mathematical rules to identify the most statistically significant liquidity zones. Think of it as a "smart filter" rather than artificial intelligence in the traditional sense.
Visual Components
**Daily Level Lines:**
- Green lines: Unmitigated (not yet breached) levels
- Red lines: Mitigated (already breached) levels
- Dots at origin point showing where level was formed
- X marker when level gets breached
- Lines extend forward to show projection
**DOL Labels:**
- Display timeframe (1H, 4H, D1, W1) or "DOL" for AI selection
- Show confidence percentage in brackets
- Color-coded by timeframe:
- Lime: AI DOL (Smart selection)
- Aqua: 1-hour timeframe
- Blue: 4-hour timeframe
- Purple: Daily timeframe
- Orange: Weekly timeframe
**Info Box (Top Right):**
Displays comprehensive liquidity metrics:
- Total levels tracked
- Active (unmitigated) levels count
- Cleared (mitigated) levels count
- Flow direction (BID PRESSURE / OFFER PRESSURE)
- Most recent sweep
- Primary and Secondary DOL targets
- Multi-timeframe bias analysis
- Overall directional bias
Settings Explained
**Daily Levels Group:**
- Show Daily Highs/Lows: Toggle visibility of all daily level tracking
- Unbreached Color: Color for levels not yet hit
- Breached Color: Color for levels that have been swept
- Show X on Breach: Display marker when level is breached
- Show Dot at Origin: Display marker at level formation point
- Line Width: Thickness of level lines (1-5)
- Line Extension: How many bars forward to project (1-24)
- Max Days to Track: Historical lookback period (5-200 days)
**DOL Settings Group:**
- Cluster Tolerance %: Price range to group DOLs (0.1-2.0%)
- Show Price on Labels: Display actual price value on labels
- Backtest Mode: Only show recent labels for clean historical analysis
- Labels Lookback: Number of bars to show labels when backtesting (10-500)
**Info Box Group:**
- Show Info Box: Toggle info panel visibility
**DOL Toggles Group:**
- Show AI DOL: Display smart auto-selected primary target
- Show 1HR DOL: Display 1-hour timeframe DOLs
- Show 4HR DOL: Display 4-hour timeframe DOLs
- Show Daily DOL: Display daily timeframe DOLs
- Show Weekly DOL: Display weekly timeframe DOLs
**Advanced Group:**
- Manual Mode: Simplified display showing only daily high/low clusters
How to Use This Indicator
Educational Application
This indicator is intended for educational purposes to help traders:
1. **Understand Liquidity Concepts:** Visualize where unfilled orders may exist
2. **Identify Key Levels:** See where price may be drawn to
3. **Analyze Market Structure:** Understand how price interacts with liquidity
4. **Study Multi-Timeframe Alignment:** Observe when multiple timeframes agree
5. **Learn ICT Concepts:** Apply liquidity theory in practice
Interpretation Guidelines
**BID PRESSURE (Flow):**
When lows are being swept more than highs, it suggests:
- Sell-side liquidity being taken
- Potential for upward move to unfilled buy-side liquidity
- Market may be clearing the way for a bullish move
**OFFER PRESSURE (Flow):**
When highs are being swept more than lows, it suggests:
- Buy-side liquidity being taken
- Potential for downward move to unfilled sell-side liquidity
- Market may be clearing the way for a bearish move
**Confidence Scores:**
- 90-100%: Very high probability zone (strong cluster, recent, aligned)
- 80-89%: High probability zone (good cluster, relatively recent)
- 70-79%: Moderate probability zone (decent cluster or older)
- 60-69%: Lower probability zone (small cluster or very old)
- Below 60%: Weak zone (minimal confluence)
**Timeframe Analysis:**
- All timeframes LONG: Strong bullish alignment
- All timeframes SHORT: Strong bearish alignment
- Mixed: Conflicting signals, exercise caution
- Higher timeframes (D1, W1) carry more weight than lower (1H, 4H)
**DIRECTIONAL Indicator:**
- BULLISH: Overall bias suggests upward movement toward buy-side DOLs
- BEARISH: Overall bias suggests downward movement toward sell-side DOLs
- NEUTRAL: No clear directional bias, conflicting signals
Practical Application Examples
**Example 1: Bullish Setup**
```
Flow: BID PRESSURE (lows being swept)
P1: 27,500 (price above current market)
D1: LONG 27,500
W1: LONG 27,650
DIRECTIONAL: BULLISH
```
Interpretation: Price has cleared sell-side liquidity. High confidence buy-side DOL at 27,500. Daily and Weekly timeframes aligned bullish. Watch for move toward 27,500 target.
**Example 2: Bearish Setup**
```
Flow: OFFER PRESSURE (highs being swept)
P1: 26,200 (price below current market)
D1: SHORT 26,200
W1: SHORT 26,100
DIRECTIONAL: BEARISH
```
Interpretation: Price has cleared buy-side liquidity. High confidence sell-side DOL at 26,200. Daily and Weekly timeframes aligned bearish. Watch for move toward 26,200 target.
**Example 3: Mixed Signals - Wait**
```
Flow: BID PRESSURE
P1: 26,800
D1: LONG 27,000
W1: SHORT 26,200
DIRECTIONAL: NEUTRAL
```
Interpretation: Conflicting signals. Flow suggests up, but Weekly bias is down. Confidence scores moderate. Better to wait for clarity.
Important Considerations
This Indicator Does NOT:
- Predict the future
- Guarantee profitable trades
- Provide buy/sell signals
- Replace proper risk management
- Work in isolation without other analysis
This Indicator DOES:
- Visualize liquidity concepts
- Identify potential target zones
- Show timeframe alignment
- Calculate objective confidence scores
- Help understand market structure
Proper Usage:
1. Use as one component of a complete trading strategy
2. Combine with price action analysis
3. Confirm with other technical indicators
4. Consider fundamental factors
5. Always use proper risk management
6. Backtest any strategy before live trading
Risk Disclaimer
**FOR EDUCATIONAL PURPOSES ONLY**
This indicator is for educational purposes only. Trading financial markets involves substantial risk of loss. Past performance does not guarantee future results. Always conduct your own research and consult with a financial advisor before making trading decisions.
**Important Limitations:**
- No indicator is 100% accurate, including the AI selection
- The "AI" is an automated algorithm, not predictive artificial intelligence
- DOL levels can be swept and price can continue in the same direction
- Confidence scores are mathematical calculations, not predictions or probabilities of success
- High confidence does not mean guaranteed profit
- Markets can remain irrational longer than you can remain solvent
- Always use stop losses and proper position sizing
**Understanding the AI Component:**
The AI auto-selection feature uses a fixed mathematical formula to rank DOLs. It does not:
- Predict where price will go
- Learn from past performance
- Adapt to market conditions
- Guarantee any level of accuracy
The confidence score represents the mathematical strength of a liquidity cluster based on objective factors (cluster size, recency, timeframe alignment), NOT a probability of the trade succeeding.
**Risk Warning:**
Trading is risky. Most traders lose money. This indicator cannot change that fundamental reality. Use it as an educational tool to understand market structure, not as a trading signal or system.
Technical Requirements
- **Timeframe:** Best used on 1-hour charts (required for accurate daily level tracking)
- **Markets:** Works on any market (forex, crypto, stocks, futures, indices)
- **Updates:** Real-time calculation on each bar close
- **Resources:** Uses max 500 lines and 500 labels (TradingView limits)
Backtesting Features
The indicator includes "Backtest Mode" to keep historical charts clean:
- When enabled, only shows labels from recent bars
- Adjustable lookback period (10-500 bars)
- All lines remain visible
- Helps review past setups without clutter
To use:
1. Enable "Backtest Mode" in settings
2. Adjust "Labels Lookback" to desired period
3. Review historical price action
4. Disable for live trading
Credits and Methodology
This indicator implements concepts from:
- ICT (Inner Circle Trader) liquidity theory
- Smart Money Concepts (SMC)
- Order flow analysis
- Multi-timeframe analysis principles
The clustering algorithm, confidence scoring, and timeframe synthesis are original implementations designed to quantify and visualize these concepts.
Version History
**v1.0 - Initial Release**
- Multi-timeframe DOL detection
- Confidence scoring system
- Info box with liquidity metrics
- Backtest mode for clean charts
- Black/white professional theme
Support and Updates
For questions, feedback, or suggestions, please use the TradingView comments section. Updates and improvements will be released as needed based on user feedback and market evolution.
**Remember:** This is an educational tool. Successful trading requires knowledge, discipline, risk management, and continuous learning. Use this indicator to enhance your understanding of market structure and liquidity, not as a standalone trading system.
掘金社区趋势系统Of course. Here is the English translation of the provided trading system rules:
### Trading System Core Elements Explained
#### 1. Core Indicators and Definitions
* **Bull-Bear Line (Purple Line):** The primary basis for measuring the strength of long and short forces.
* *Example: If the 5-minute chart candlestick is below the Bull-Bear Line, the bears have the advantage. If the candlestick is above it, the bulls have the advantage.*
* **Trading Line (Yellow Line):** The operational line.
* **Opening/Closing Positions:** The Bull-Bear Line and Trading Line are the levels for both opening trades and taking profits.
* *Clarification: We only open or close positions when the price is at or very close to the Trading Line or Bull-Bear Line. If the price is not near these lines, it is not an opportunity for us to open or close a position. Note that the above rules for the Trading Line and Bull-Bear Line apply to all timeframes. Profit targets are scaled up through higher timeframes.*
#### 2. How to Identify a One-Sided Trend
* **Uptrend:** When the ribbon is **green** and positioned **above the Trading Line** and **above the Bull-Bear Line**, it indicates an uptrend on that timeframe.
* **Multi-Timeframe Confirmation (Resonance):** If **three timeframes simultaneously** show this state (green ribbon above both lines), it is a multi-timeframe resonance. The trading strategy then is to **buy on dips to support**, with entry positions being the Trading Line and Bull-Bear Line on the various timeframes.
* **General Rule:** When the price is **above the Bull-Bear Line**, place more trust in emerging **long signals** (e.g., green ribbon) to enter long positions.
* **Downtrend (Conversely):** When the candlestick is **below the Bull-Bear Line**, place more trust in emerging **short signals** (e.g., red ribbon) to enter short positions.
#### 3. Gauging Long/Short Strength
* The primary references for measuring the strength of bulls and bears are:
1. The positional relationship between the **Candlestick**, the **Bull-Bear Line**, and the **Trading Line**.
2. The **color of the ribbon**.
* **During Bearish Advantage:** Place more trust in emerging bearish signals for shorting. Be cautious with long operations.
* **During Bullish Trend:** Place more trust in emerging bullish signals. Focus on long positions and be cautious with shorting.
#### 4. Strong Trending Markets
* **Strong Bullish Market:** A pullback **does not break the lower ribbon**. In a strong, one-sided rally, the pullback **does not break the 5-15 minute Trading Line**.
* **Strong Bearish Market:** A rebound **does not surpass the upper ribbon**. In the strongest one-sided decline, the rebound **does not surpass the 5-15 minute Trading Line**.
True Trend OscillatorCore Concept: The Range Filter
The main purpose of this indicator is not just to show the trend, but to actively filter out "noise" or sideways (ranging) markets.
It doesn't give you a buy or sell signal simply because a fast line crosses a slow one. Instead, it tells you if the market has sufficient strength to sustain a trend. If it doesn't, it signals this by painting the line gray, suggesting it's better to stay out.
How It Works: The 3 Key Components
Your indicator works by fusing three concepts: Price Momentum, Volatility Momentum, and a Threshold Filter.
1. Price Momentum Component (RSI)
What it does: It uses a standard RSI (14-period) to measure the internal strength of the price.
How it's used:
If the RSI is high (e.g., > 50), the "Bulls" have the momentum.
If the RSI is low (e.g., < 50), the "Bears" have the momentum.
2. "Energy" Component (Stochastic ATR)
What it does: This is the most advanced part of the indicator. It doesn't measure price; it measures volatility.
How it's used:
It calculates the ATR (Average True Range) to measure volatility.
It then calculates a Stochastic of the ATR. This measures where the current volatility is relative to its recent range (highs and lows of volatility).
The result is the value k, which represents the market's "energy" or "conviction".
3. The Fusion: Creating the Bull and Bear Lines
This is where the magic happens. The indicator combines price momentum (RSI) with energy (k) using a geometric mean (math.sqrt):
bull = math.sqrt(RSI * k)
bear = math.sqrt((100 - RSI) * k)
This means a strong "Bull" line needs not only a high RSI but also high "energy" (k).
The Visual Logic: How to Read the Oscillator
You have modified the indicator to display a single line (trendStrength) whose value is the strength of the dominant trend (math.max(bull, bear)).
The color of this line is the most important signal and is based on the Threshold Filter:
🟩 Green Color (Strong Bullish Trend)
The line is painted green (lime) only if TWO conditions are met:
Bullish strength is greater than bearish strength (bull > bear).
AND the bearish strength (the weaker side) is still above the threshold (math.min(bull, bear) > threshold).
Meaning: The bulls are winning, but the bears are still putting up a fight. This is a "true trend," not just a weak, random move.
🟥 Red Color (Strong Bearish Trend)
The line is painted red only if TWO conditions are met:
Bearish strength is greater than bullish strength (bear > bull).
AND the bullish strength (the weaker side) is still above the threshold (math.min(bull, bear) > threshold).
Meaning: The bears are winning in a real, strong trend.
⬜ Gray Color (Range-Bound or "Chop" Market)
The line is painted gray if either of the two forces (bullish or bearish) drops below the threshold.
Meaning: This is the filter signal. The indicator is telling you that the market has lost its directional energy. The trend has either exhausted itself, or the market is in a sideways chop. It's a "do not trade" or "take profits" signal.
Visual Summary
Main Line (and Area Fill): Shows the strength of the dominant trend. Its color (green, red, or gray) tells you the state of that trend.
Bar Coloring: You have the option (showBarColors) to have your main price chart candles painted the same color as the oscillator, allowing you to see the trend without looking at the panel below.
Background Lines (threshold, 80, 0): These are fixed reference levels. The threshold line (green by default) is the most important, as it's the filter that decides if you are in a trend or a range.
VWAP Diario + VWAP 08:00-12:00 ventanas NYWhat it plots
Daily VWAP (main line)
Anchored to the current trading day and only visible between 19:00 and 16:50 New York (UTC-5) to prevent any “ghost” segments.
Dynamic color: turns green when price closes above (bullish bias) and red when price closes below (bearish bias).
Optional standard-deviation/percentage bands (off by default).
08:00–12:00 VWAP (morning line)
Resets at 08:00 NY and shows until 12:00 NY only.
Acts as a morning value guide for early direction and pullbacks.
Clean rendering: Both lines use strict time masks and line breaks, so nothing is drawn outside their windows. You can toggle either line on/off.
How to Read It
Daily VWAP ≈ “fair value” of the whole session; use it for directional bias and confluence.
08:00–12:00 VWAP ≈ “fair value” of the morning; helps refine entries during the open.
Alignment:
Bullish environment: price and 08–12 VWAP sit above the Daily VWAP.
Rotation/mixed: price oscillates between the two lines.
Bearish: price and 08–12 VWAP sit below the Daily VWAP.
Two Mechanical Playbooks
Recommended charts: 1-minute for entries, 5-minute for context on NQ/Nasdaq100.
Primary execution window: 09:30–12:00 NY.
A) Trend Play (Break → Pullback to VWAP)
Goal: Join the day’s impulse with value confirmation.
Rules
Bias filter before 09:30
Bullish: 08–12 VWAP ≥ Daily VWAP; Bearish: 08–12 ≤ Daily.
First push 09:30–09:45 breaks the initial range high (bull) or low (bear).
Entry (pullback into confluence)
Wait for a pullback that tags/wicks the 08–12 VWAP or the Daily VWAP in the direction of bias.
Go long on bullish rejection (close back above); short on bearish rejection.
Stop-loss
Beyond the rejection wick or the touched VWAP (e.g., 1–1.5× ATR(1m/5m)).
Take-profit
TP1 = 1R (scale 50%); TP2 = 2–3R or day extremes (HOD/LOD).
If bands are on, consider exiting on a clean tag of the opposite band.
Management
Move to breakeven at 1R; exit early if price reclaims the opposite side of Daily VWAP.
Avoid when the morning is choppy and price sits glued between the two VWAPs.
B) Mean-Reversion Play (Controlled Reversal at Daily VWAP)
Goal: Capture a return to value after an overstretch and a clean rejection.
Rules
Stretch condition
Fast move away from Daily VWAP (3–5 bars) or beyond Band #1/#2 if enabled.
Rejection signal at Daily VWAP
A bar that touches Daily VWAP and closes back on the opposite side (pin/engulfing/strong close).
Entry
Long if a selloff rejects above Daily VWAP.
Short if a rally rejects below Daily VWAP.
Stop-loss
Just beyond the rejection wick or ~1× ATR(1m).
Take-profit
TP1 = 1R or the 08–12 VWAP; TP2 = 2–3R or a prior consolidation.
Management
If price crosses and holds on the other side of Daily VWAP (2 closes), cut the idea.
Avoid during high-impact news or when the session is strongly trending (prefer Play A).
Quality Filters
Volatility: Ensure ATR(14, 1m) or the 09:30–09:45 range exceeds your minimum.
Spread/liquidity: Skip abnormal spreads at the open.
News: If a red-level release is imminent, wait 2–3 bars after the print.
Coherence: Prefer trades when 08–12 and Daily VWAP don’t conflict.
Risk & Trade Management
Risk per trade: 0.25%–0.5% account risk.
Daily cap: 2–3 trades; stop for the day at –1R to –1.5R.
No over-reentry: Don’t chase if price is sitting exactly on a VWAP; wait for separation.
Log your metrics: setup type (A/B), confluences, distance to VWAP at trigger, time, R multiple.
Quick Pre-Trade Checklist
Bias aligned? (price vs Daily and 08–12 VWAP)
Choose Trend or Mean-Reversion play
Clear confluence at the VWAP line?
Realistic stop (≤ ~1.5× ATR 1m)?
Any imminent news?
TP plan: TP1 = 1R → BE, TP2 = 2–3R.
EPS Estimate Profile [SS]This is the EPS Estimate Profile indicator.
What it does
This indicator
Collects all EPS estimates over the course of a lookback and BINS them (sorts them into 10 equal sized categories).
Analyzes the returns from earnings releases based on the EPS estimate and the reaction.
Calculates the number of bullish vs bearish responses that transpired based on the EPS estimate profile.
Calculates the expected Open to High and Open to Low ATR based on the EPS estimate using regression.
Toggle to actual EPS release to compare once earnings results are released.
How to Use it
This indicator can be used to gain insight into whether an earnings release will be received bullishly or bearishly based on the company's EPS estimate.
The indicator allows you to see all historic estimates and how the market generally responded to those estimates, as well as a breakdown of how many times estimates in those ranges produced a bullish response or a bearish response to earnings.
Examples
Let's look at some examples:
Here is MSFT. MSFT's last EPS estimate was 3.672.
If we consult the table, we can see the average return associated with this estimate range is -4%.
Now let's flip to the Daily timeframe and take a look:
MSFT ended the day red and continued to sell into the coming days.
Let's look at another example:
MCDs. Last earnings estimate was 3.327, putting it at the top of the range with an average positive return of 4%.
Let's look on the daily:
We can see that the earnings had a huge, bullish effect on MCD, despite them coming in below their estimates.
If we toggle the indicator to "Actual" EPS release, to see the profile of Actual earnings releases vs response, we get this:
Since MCD under-performed, they were still at the top of the profile; but, we can see that the expected returns are more muted now, though still positive. And indeed, the reaction was still positive.
Distinguishing % Bullish/Bearish to Avg Returns
You will see the profile table displays both the average returns and the percent of bullish/bearish responses. In some cases, you will see that, despite a negative return, the profile reveals more bullish reactions than bearish.
What does this mean?
It means, despite there being more bullish responses, when bearish responses happen they tend to be more severe and profound, vs bullish responses likely are muted.
This can alert you to potential downside risk and help you manage risk accordingly should you elect to trade the earnings release.
ATR Prediction
You will notice in the bottom right corner of the screen a secondary table that lists the predicted open to high ATR and open to low ATR.
This is done using RAW EPS estimates (or raw ACTUAL estimates depending on which you select) and performing a regression to determine the expected ATR.
This is only for reference, the analysis should focus around the historic profile of return estimates and actual return values.
IMPORTANT NOTE: You MUST be on the Monthly timeframe to use this. Otherwise, you will get an error. If, on certain tickers with a huge history, such as MSFT and XOM or OXY, you get an error, you can simply reduce the lookback length to 80 and this will resolve the issue.
Conclusion
And that's the indicator!
A blend of some light math and fundamentals! A real joy honestly.
Hope you enjoy it!
Dynamic FVG & Trap Zones📘 Dynamic FVG & Trap Zones (DFTZ)
A Hybrid Model Combining Imbalance Mapping, Volume Behavior, and Trap Detection
Concept Overview
“Dynamic FVG & Trap Zones” is built to visualize real-time Fair Value Gaps (FVGs) and identify liquidity trap events inside those gaps using adaptive volume filters and wick-based logic.
Traditional FVG indicators merely mark imbalance zones between consecutive candles, but this model goes further — it measures how volume reaction and price penetration inside those zones reveal potential f alse moves or trap formations by smart money.
⚙️ How It Works
1. FVG Detection
• A Bullish FVG is detected when low > high , showing a price void left by aggressive buying.
• A Bearish FVG forms when high < low , implying a selling imbalance.
• These zones are automatically drawn as semi-transparent boxes that extend forward for 10 bars and decay once they exceed the configurable lookback window.
2. Volume Normalization & Grading
• Every bar’s volume is compared against a dynamic SMA( volLookback ) average to calculate a Volume Grade = current vol / avg vol.
• Only bars exceeding the Min Volume Grade threshold are eligible to generate valid FVG zones, ensuring that low-participation moves are ignored.
• The Trap Volume Threshold sets how quiet the reaction bar must be (relative to average volume) to qualify as a trap event.
3. Trap Detection Logic
• Each active FVG zone monitors incoming candles.
• A potential trap is triggered when price re-enters the zone (body or wick depending on settings) but fails to expand with confirming volume.
• If the event occurs inside a Bullish FVG, it marks a Bear Trap (green zone turned red).
If it happens inside a Bearish FVG, it flags a Bull Trap (red zone turned green).
• This reversal in zone color visually conveys trapped liquidity and potential directional fade.
4. Exclusivity and Cooldown Control
• To avoid signal clustering, you can choose exclusivity modes:
Allow Both, Bear over Bull, or Bull over Bear.
• A built-in per-signal cooldown timer prevents back-to-back plots of the same type, enhancing signal clarity during rapid price action.
5. Adaptive Visualization
• Wick-based vs body-based trap detection (toggleable).
• Optional cooldown filtering on shapes ensures the chart only displays validated events.
• Old FVG boxes are pruned automatically beyond the chosen lookback horizon.
🧠 Why It’s Different
Unlike static FVG detectors or simple liquidity sweep tools, DFTZ blends:
• Volume context (Smart Volume Grade filtering)
• Behavioral trap detection within imbalance zones
• Dynamic cooldown mechanics that control over-signaling
• Forward-propagating zones that self-expire gracefully
This synergy makes it a compact yet powerful tool for visualizing imbalances + liquidity traps in one framework — ideal for discretionary traders combining SMC concepts with volume analytics.
📈 How to Use
• Primary Context: Use on 15 min to 1 h charts to spot active FVG zones forming after impulsive moves.
• Trap Signal Interpretation:
• 🔴 “Trap” below bar → Bullish reversal (Bear Trap).
• 🟢 “Trap” above bar → Bearish reversal (Bull Trap).
• Combine With: Market structure breaks, VWAP, or delta volume tools to confirm true reversal intent.
• Alerts: All major events (FVG creation & trap confirmation) trigger ready-to-use alerts for automation or back-testing.
🧩 Customization
Setting Function
Max FVG Lookback Controls how long old zones remain active.
Volume SMA Period Defines the baseline for volume grading.
Min Volume Grade & Trap Volume Threshold Tune the sensitivity of trap confirmation.
Wick-Based Trap Detection Enable to capture wick rejections inside zones.
Signal Cooldown Prevents rapid multiple plots on successive bars.
⚠️ Disclaimer
This tool is designed for educational and analytical purposes only. It does not constitute financial advice or guarantee trading performance. Always conduct your own analysis and risk management before entering a position.
ZynAlgo Trend MiniZynAlgo Trend Mini — Multi-Timeframe Trend Scanner & Compact Table UI
What this indicator does
ZynAlgo Trend Dashboard Mini scans up to five user-selected timeframes and summarizes the trend state for each, using one of three signal modes: MA Cross, Price vs MA, or RSI. It then aggregates these per-timeframe signals into an Overall Trend line and optionally shows a score count (bull/bear/neutral). A compact table dashboard renders in the corner you choose, with multiple themes or fully custom colors.
How it works (conceptual)
1) Per-timeframe signal
Choose a Signal Mode for classification:
MA Cross — compares fast vs. slow MA. If % distance exceeds Neutral Zone %, it’s Bullish/Bearish; otherwise Neutral.
Price vs MA — compares price to a single MA; % deviation beyond Neutral Zone is Bullish/Bearish; within it is Neutral.
RSI — RSI above Bullish Level ⇒ Bullish; below Bearish Level ⇒ Bearish; between the two ⇒ Neutral.
Supported MA types: EMA/SMA/HMA/WMA; lengths and thresholds are user-defined.
2) Multi-timeframe aggregation
The script counts Bullish/Bearish/Neutral outcomes across enabled TFs, then sets Overall Trend by majority (ties → Neutral). Optional score text shows the counts.
3) Dashboard rendering
Three display modes: Detailed, Compact, Minimal. You can position the panel in common corners/center and toggle title, overall row, and score.
Inputs (with tooltip-style guidance)
⏰ Timeframes
Enable Timeframe 1–5 / Timeframe 1–5 — turn on specific TFs (e.g., 5 / 15 / 60 / 240 / D). Tip: “Only enabled TFs are counted in the overall trend.”
📊 Signal Settings
Signal Mode (MA Cross / Price vs MA / RSI) — “Pick how each TF is classified.”
MA Type / Fast MA Length / Slow MA Length — “Used by MA Cross and Price vs MA; shorter fast MA reacts quicker; longer slow MA smooths noise.”
RSI Length / Bullish Level / Bearish Level — “Used by RSI mode; levels define bullish/bearish thresholds.”
Neutral Zone % — “Dead-band around 0% for MA-based modes; inside the band = Neutral.”
🎨 Display
Display Mode (Detailed / Compact / Minimal) — “Switch between full rows, condensed line, or icon-only view.”
Position — “Choose a chart corner/center for the panel.”
Show Overall Trend / Show Score Count / Show Dashboard Title — “Toggle the overall line, counts, and title.”
📝 Text & Size
Dashboard Title / Text Size / Timeframe Text Size — “Set panel title and font sizes independently.”
🎨 Theme & Colors
Color Theme — presets: Dark Neon / Dark Professional / Light Modern / Light Classic / Cyberpunk / Matrix / Custom. Tip: “Pick a preset; choose Custom to define every color.”
Custom Colors (active when Theme=Custom) — border/background/header/row/text/title/TF label and bull/bear/neutral colors.
🧱 Border & Background
Border Width — “0 hides the frame; higher values increase panel emphasis.”
Alternate Row — “Subtle row striping for readability.” (enabled in code)
🔔 Alerts
Enable Alerts — “Master on/off for the four prebuilt alerts.”
Using the indicator (suggested workflow)
Choose timeframes (e.g., M5/M15/H1/H4/D1). Disable any you don’t want counted.
Select a signal model that fits your playbook (MA Cross, Price vs MA, or RSI), then set MA/RSI lengths and the Neutral Zone %.
Pick a display mode & position. Toggle Overall Trend, Score Count, and Title as needed.
Style with a theme (or Custom colors) for readability on your chart background.
(Optional) Alerts: enable and then create alerts for unanimous or majority trends (see list below).
Reading the dashboard
Per-TF cells/icons: color and text show the state (BULLISH / BEARISH / NEUTRAL).
Overall Trend row: majority summary with ▲ / ▼ / ● icon; optional score shows counts (Bull/Bear/Neutral).
Built-in alert conditions
All Timeframes Bullish — every enabled TF is Bullish (requires ≥3 enabled).
All Timeframes Bearish — every enabled TF is Bearish (requires ≥3 enabled).
Majority Bullish — majority Bullish and Overall Trend = Bullish.
Majority Bearish — majority Bearish and Overall Trend = Bearish.
Hidden plots for Overall/Bull/Bear counts are available for alert logic/custom uses.
Three interchangeable models in one panel (MA Cross, Price-Deviation, RSI) → one UI, multiple perspectives.
Flexible aggregation that adapts to enabled TFs only (disabled TFs are excluded cleanly).
Compact, themeable UI with Detailed/Compact/Minimal layouts and corner/center anchoring — designed for clarity on busy charts.
Bar-confirmed calculations via request.security (no forward-looking values used in the logic described).
Lightweight implementation (table rendering and per-bar updates gated on barstate.islast) to minimize overhead in common workflows.
🔶 RISK DISCLAIMER
Trading is risky & most day traders lose money. All content, tools, scripts, articles, & education provided by ZynAlgo are purely for informational & educational purposes only. Past performance does not guarantee future results.
GTI BGTI: RSI Suite (Standard • Stochastic • Smoothed)
A three-layer momentum and trend toolkit that combines Standard RSI, Stochastic RSI, and a Smoothed/“Macro” RSI to help you read intraday swings, trend transitions, and high-probability reversal/continuation spots.
All in one pane with intuitive coloring and optional divergence markers and alerts.
Why this works
* Stochastic RSI (K/D) visualizes fast momentum swings and timing.
* Standard RSI moves more gradually, helping confirm trend transitions that may span several Stochastic cycles.
* Smoothed RSI (Average → Macro) adds a second-pass filter and slope persistence to reveal the macro direction while suppressing noise.
Used together, Stochastic guides entries/exits around local highs/lows, while the RSI layers improve confidence when a small swing is likely part of a larger turn.
What you’ll see
* Standard RSI (yellow; pink above Bull line, aqua below Bear line).
* Stochastic RSI (K/D) with contextual colors:
* Greens when RSI is weak/oversold (bearish conditions → watch for bullish reversals/continuations).
* Reds when RSI is strong/overbought (bullish conditions → watch for bearish reversals/continuations).
* Smoothed (Macro) RSI with trend color:
* Red when macro is ascending (bullish),
* Aqua when macro is descending (bearish).
* Divergences (optional markers):
* Bearish: RSI Lower High + Price Higher High (red ⬇).
* Bullish: RSI Higher Low + Price Lower Low (green ⬆).
* No repaint: pivots confirm after the chosen right-bars window.
How to use it
* Bullish Reversal
* Macro RSI is reversing at a higher low after price has been in a overall downtrend
* Stochastic RSI is switching from green to red in an overall downtrend
* Bullish Oversold
* Macro RSI is reversing from a significantly low level after price has a short but strong dip during an overall uptrend
* Stochastic RSI is switching from green to red in an overall uptrend
* Bullish Continuation
* Macro RSI is ascending with a strong slope or forming a higher low above the 50 line
* Stochastic RSI is reaching a bottom but still painted red
* Bearish Reversal
* Macro RSI is reversing at a lower high after price has been in a overall uptrend
* Stochastic RSI is switching from red to green in an overall uptrend
* Bearish Overbought
* Macro RSI is reversing from a significantly high level after price has a short but strong jump during an overall downtrend
* Stochastic RSI is switching from red to green in an overall downtrend
* Bearish Continuation
* Macro RSI is descending with a strong slope or forming a lower high below the 50 line
* Stochastic RSI is reaching a top but still painted green
* Divergences: Use as signals of exhaustion—best when aligned with Macro RSI color/slope and key levels (e.g., Bull/Bear lines, 50 midline).
*** IMPORTANT ***
* Stack confluence, don’t single-signal trade. Look for:
* 1) Macro RSI color & slope (red = ascending/bullish, aqua = descending/bearish)
* 2) Standard RSI location (above/below Bull/Bear lines or 50)
* 3) Stoch flip + direction
* 4) Price structure (HH/HL vs LH/LL)
* 5) Divergence type (regular vs hidden) at meaningful levels
* Trade with the macro
* Prioritize longs when Macro RSI is red or just flipped up
* Prioritize shorts when Macro RSI is aqua or just flipped down
* Counter-trend setups = smaller size and faster management.
* Location > signal
* The same crossover/divergence is higher quality near Bull (~60)/Bear(~40) or extremes than in the mid-range chop around 50.
* Early vs confirmed
* Use the early pivot heads-up for anticipation, but scale in only after the confirmed pivot (right-bars complete). If early signal fails to confirm, stand down.
* Define invalidation upfront
* For divergence entries, place stops beyond the pivot extreme (LL/HH). If Macro RSI flips against your trade or RSI breaks back through 50 with slope, exit or tighten.
* Multi-timeframe alignment
* Best results come when entry timeframe (e.g., 1H) aligns with higher-TF macro (e.g., 4H/D). If they disagree, treat it as mean-reversion only.
* Avoid common traps
* Skip: isolated Stochastic flips without RSI support, divergences without price HH/LL confirmation, and serial divergences when Macro RSI slope is strong against the idea.
* Parameter guidance
* Start with defaults; then tune: confirmBars 3–7, minSlope 0.05–0.15 RSI pts/bar, pivot left/right tighter for faster but noisier signals, wider for cleaner but fewer.
* Alerts = workflow, not auto-trades
* Use Macro Flip + Divergence alerts as a checklist trigger; enter only when your confluence rules are met and risk is defined.
Key inputs (tweak to your market/timeframe)
* RSI / Stochastic lengths and K/D smoothing.
* Bull / Bear Lines (default 61.1 / 43.6).
* Average RSI Method/Length (SMA/EMA/RMA/WMA) + Macro Smooth Length.
* Trend confirmation: bars of persistence and minimum slope to reduce flip noise.
* Pivot look-back (left/right) for divergence confirmation strictness.
Alerts included
* Macro Flip Up / Down (Smoothed RSI regime change).
* RSI Bullish/Bearish Divergence (confirmed at pivot).
* Stochastic RSI continuation/divergence (optional).
Tips
* Level + Slope matter. High/low RSI level flags conditions; slope confirms impulse/continuation.
* Let Stochastic time the swing; let Macro RSI filter the trend.
* Tighten or loosen pivot windows to trade fewer/cleaner vs. more/faster signals.
OBV with Divergence (SMA Smoother)Title: OBV Divergence with SMA Smoothing
Description:
This indicator is a powerful tool designed to identify regular (reversal) and hidden (continuation) On-Balance Volume (OBV) divergences against price action. It uses a modified OBV calculation (an OBV Oscillator) and integrates pivot analysis to automatically highlight potential turning points or trend continuations directly on your chart.
Key Features
Advanced Divergence Detection: Automatically detects and labels four types of divergences:
Regular Bullish/Bearish: Signals potential trend reversals.
Regular Bullish: Price makes a Lower Low (LL) but the OBV Oscillator makes a Higher Low (HL).
Regular Bearish: Price makes a Higher High (HH) but the OBV Oscillator makes a Lower High (LH).
Hidden Bullish/Bearish: Signals potential trend continuations.
Hidden Bullish: Price makes a Higher Low (HL) but the OBV Oscillator makes a Lower Low (LL).
Hidden Bearish: Price makes a Lower High (LH) but the OBV Oscillator makes a Higher High (HH).
OBV Oscillator: Instead of plotting the raw OBV, this script uses the difference between the OBV and its Exponential Moving Average (EMA). This technique centers the indicator around zero, making it easier to visualize volume momentum shifts and clearly identify peaks and troughs for divergence analysis.
Optional SMA Smoothing Line (New Feature): An added Simple Moving Average (SMA) line can be toggled on to further smooth the OBV Oscillator. Traders can use this line for crossover signals or to confirm the underlying trend of the volume momentum, reducing whipsaws.
Customizable Lookback: The indicator allows you to define the lookback periods (Pivot Lookback Left/Right) for price and oscillator pivots, giving you precise control over sensitivity. The Max/Min of Lookback Range helps filter out divergences that are too close or too far apart.
ZS Master Vision Pro - Advanced Multi-Timeframe Trading SystemZS MASTER VISION PRO - PROFESSIONAL TRADING SUITE
Created by Zakaria Safri
A comprehensive, all-in-one trading system combining multiple proven technical analysis methods into a single, powerful indicator. Designed for traders who demand precision, clarity, and actionable signals across all timeframes.
KEY FEATURES
CORE TREND ALGORITHM
Adaptive ATR-based trend detection with dynamic support and resistance zones. Features Type A and Type B signal modes for different trading styles, strong signal detection in key reversal zones, and optional EMA source smoothing for noise reduction.
MULTI-LAYER EMA CLOUD SYSTEM
Five customizable EMA cloud layers for multi-timeframe analysis with theme-adaptive color coding across five professional themes. Optional line display for detailed MA tracking with configurable periods from scalping to position trading.
WAVE TREND OSCILLATOR
Advanced momentum oscillator with channel-based calculations featuring smart reversal detection at extreme overbought and oversold levels. Includes directional strength confirmation and customizable sensitivity with adjustable reaction periods.
DIVERGENCE SCANNER
Detects four types of divergence automatically:
- Regular Bullish: Price making lower lows while oscillator making higher lows
- Regular Bearish: Price making higher highs while oscillator making lower highs
- Hidden Bullish: Trend continuation signals in uptrends
- Hidden Bearish: Trend continuation signals in downtrends
Automatic fractal-based detection with clear visual labels on chart.
MARKET BIAS INDICATOR
Heikin Ashi-based trend strength analysis with real-time bias calculation showing Bullish or Bearish combined with Strong or Weak conditions. Smoothed for cleaner signals and perfect for trend confirmation.
MOMENTUM SYSTEM
Proprietary momentum calculation using adaptive smoothing with growing and falling state detection. Normalized values for consistent interpretation and responsive to rapid market changes.
DYNAMIC SUPPORT AND RESISTANCE
Automatic pivot-based support and resistance level detection with adjustable left and right bar lookback. Non-repainting levels with visual clarity through color-coded lines.
LIVE INFORMATION DASHBOARD
Real-time market analysis panel displaying current trend direction, market bias based on Heikin Ashi, Wave Trend status and value, and momentum trend with state. Customizable display options with theme-adaptive colors.
VISUAL CUSTOMIZATION
FIVE PROFESSIONAL COLOR THEMES:
Pro - Modern green and red color scheme (default)
Classic - Traditional teal and red combination
Cyberpunk - Neon cyan and magenta contrast
Ocean - Blue and orange contrast
Sunset - Gold and red warmth
SIGNAL STYLES:
Labels with emoji indicators (BUY with rocket, SELL with bear, STRONG with lightning)
Arrows for clean minimal appearance
Triangles for classic approach
DISPLAY OPTIONS:
Color-coded candles following trend direction
Trend background highlighting for instant trend recognition
Optional EMA line display for detailed analysis
Adjustable transparency levels for personal preference
SMART ALERTS
Pre-configured alert conditions for all major signals:
Buy signals for standard entry opportunities
Sell signals for standard exit or short opportunities
Strong buy signals for high-confidence long entries
Strong sell signals for high-confidence short entries
Bullish divergence detection alerts
Bearish divergence detection alerts
Alert messages automatically include ticker symbol, current price, and specific signal type for quick decision making.
HOW TO USE
FOR TREND TRADERS:
Enable EMA Clouds with focus on Cloud 5 featuring 50 and 200 period moving averages. Wait for trend background color change to confirm direction. Enter on STRONG signals aligned with higher timeframe trend direction. Use support and resistance levels for strategic exits.
FOR SWING TRADERS:
Enable Wave Trend Oscillator information display. Look for oversold and overbought reversal setups. Confirm potential reversals with divergence scanner. Enter on smart reversal signals with proper risk management.
FOR SCALPERS:
Use Type B signal mode for more frequent trading signals. Enable Cloud 1 with 5 and 13 periods for quick trend confirmation. Focus on momentum growing and falling states for entry timing. Take quick entries on regular buy and sell signals.
FOR POSITION TRADERS:
Use Type A mode with higher ATR multiplier set to 3.0 or above. Enable only Cloud 5 with 50 and 200 periods for major trend confirmation. Only take STRONG signals for highest probability setups. Hold positions through minor pullbacks and noise.
RECOMMENDED SETTINGS
STOCKS ON DAILY TIMEFRAME:
Trend Period: 180
ATR Period: 155
ATR Multiplier: 2.1
Signal Mode: Type A
FOREX ON HOURLY AND 4-HOUR TIMEFRAMES:
Trend Period: 150
ATR Period: 120
ATR Multiplier: 2.5
Signal Mode: Type A
CRYPTOCURRENCY ON 15-MINUTE AND 1-HOUR TIMEFRAMES:
Trend Period: 100
ATR Period: 80
ATR Multiplier: 3.0
Signal Mode: Type B
SCALPING ON 1-MINUTE AND 5-MINUTE TIMEFRAMES:
Trend Period: 50
ATR Period: 40
ATR Multiplier: 2.0
Signal Mode: Type B
WHAT IS INCLUDED
Trend Analysis using ATR-based adaptive algorithm
Five EMA Cloud Layers for multi-timeframe confluence
Wave Trend Oscillator for momentum and reversal detection
Divergence Scanner detecting four types of divergence
Market Bias using Heikin Ashi-based trend strength
Momentum System with advanced momentum tracking
Support and Resistance Levels with automatic pivot detection
Live Dashboard showing real-time market analysis
Smart Alerts featuring six pre-configured alert types
Five Color Themes offering professional visual options
TECHNICAL DETAILS
CALCULATION METHODS:
Average True Range (ATR) for volatility adaptation
Exponential Moving Average (EMA) and Simple Moving Average (SMA) for trend smoothing
Wave Trend channel oscillator for momentum analysis
Fractal-based divergence detection algorithm
Heikin Ashi transformation for bias calculation
Logarithmic momentum calculation for precision
PERFORMANCE CHARACTERISTICS:
Optimized for maximum speed and efficiency
No repainting signals ensuring reliability
Works on all timeframes from 1 minute to monthly
Compatible with all instruments including stocks, forex, crypto, and futures
RISK DISCLAIMER
This indicator is a technical analysis tool and should not be used as the sole basis for trading decisions. Always use proper risk management and never risk more than you can afford to lose. Combine with other analysis methods and practice on demo accounts first. Past performance does not guarantee future results. Trading carries substantial risk and is not suitable for all investors.
SUPPORT AND UPDATES
Regular updates and continuous improvements
Based on proven technical analysis principles
Developed following Pine Coders best practices and standards
Clean, well-documented, and optimized code structure
WHY CHOOSE ZS MASTER VISION PRO
All-in-one solution eliminating the need for multiple indicators
Highly customizable to adapt to your specific trading style
Professional grade analysis with institutional-quality standards
Clean interface that is not cluttered or confusing
Works everywhere across all markets and all timeframes
Smart signals filtered for quality over quantity
Beautiful design featuring five professional color themes
Active development with regular improvements and updates
Transform your trading with ZS Master Vision Pro today.
Version 2.0 | Created by Zakaria Safri | Pine Script Version 5
Mythical EMAs + Dynamic VWAP BandThis indicator titled "Mythical EMAs + Dynamic VWAP Band." It overlays several volatility-adjusted Exponential Moving Averages (EMAs) on the chart, along with a Volume Weighted Average Price (VWAP) line and a dynamic band around it.
Additionally, it uses background coloring (clouds) to visualize bullish or bearish trends, with intensity modulated by the price's position relative to the VWAP.
The EMAs are themed with mythical names (e.g., Hermes for the 9-period EMA), but this is just stylistic flavoring and doesn't affect functionality.
I'll break it down section by section, explaining what each part does, how it works, and its purpose in the context of technical analysis. This indicator is designed for traders to identify trends, momentum, and price fairness relative to volume-weighted averages, with volatility adjustments to make the EMAs more responsive in volatile markets.
### 1. **Volatility Calculation (ATR)**
```pine
atrLength = 14
volatility = ta.atr(atrLength)
```
- **What it does**: Calculates the Average True Range (ATR) over 14 periods (a common default). ATR measures market volatility by averaging the true range (the greatest of: high-low, |high-previous close|, |low-previous close|).
- **Purpose**: This volatility value is used later to dynamically adjust the EMAs, making them more sensitive in high-volatility conditions (e.g., during market swings) and smoother in low-volatility periods. It helps the indicator adapt to changing market environments rather than using static EMAs.
### 2. **Custom Mythical EMA Function**
```pine
mythical_ema(src, length, base_alpha, vol_factor) =>
alpha = (2 / (length + 1)) * base_alpha * (1 + vol_factor * (volatility / src))
ema = 0.0
ema := na(ema ) ? src : alpha * src + (1 - alpha) * ema
ema
```
- **What it does**: Defines a custom function to compute a modified EMA.
- It starts with the standard EMA smoothing factor formula: `2 / (length + 1)`.
- Multiplies it by a `base_alpha` (a user-defined multiplier to tweak responsiveness).
- Adjusts further for volatility: Adds a term `(1 + vol_factor * (volatility / src))`, where `vol_factor` scales the impact, and `volatility / src` normalizes ATR relative to the source price (making it scale-invariant).
- The EMA is then calculated recursively: If the previous EMA is NA (e.g., at the start), it uses the current source value; otherwise, it weights the current source by `alpha` and the prior EMA by `(1 - alpha)`.
- **Purpose**: This creates "adaptive" EMAs that react faster in volatile markets (higher alpha when volatility is high relative to price) without overreacting in calm periods. It's an enhancement over standard EMAs, which use fixed alphas and can lag in choppy conditions. The mythical theme is just naming—functionally, it's a volatility-weighted EMA.
### 3. **Calculating the EMAs**
```pine
ema9 = mythical_ema(close, 9, 1.2, 0.5) // Hermes - quick & nimble
ema20 = mythical_ema(close, 20, 1.0, 0.3) // Apollo - short-term foresight
ema50 = mythical_ema(close, 50, 0.9, 0.2) // Athena - wise strategist
ema100 = mythical_ema(close, 100, 0.8, 0.1) // Zeus - powerful oversight
ema200 = mythical_ema(close, 200, 0.7, 0.05) // Kronos - long-term patience
```
- **What it does**: Applies the custom EMA function to the close price with varying lengths (9, 20, 50, 100, 200 periods), base alphas (decreasing from 1.2 to 0.7 for longer periods to make shorter ones more responsive), and volatility factors (decreasing from 0.5 to 0.05 to reduce volatility influence on longer-term EMAs).
- **Purpose**: These form a multi-timeframe EMA ribbon:
- Shorter EMAs (e.g., 9 and 20) capture short-term momentum.
- Longer ones (e.g., 200) show long-term trends.
- Crossovers (e.g., short EMA crossing above long EMA) can signal buy/sell opportunities. The volatility adjustment makes them "mythical" by adding dynamism, potentially improving signal quality in real markets.
### 4. **VWAP Calculation**
```pine
vwap_val = ta.vwap(close) // VWAP based on close price
```
- **What it does**: Computes the Volume Weighted Average Price (VWAP) using the built-in `ta.vwap` function, anchored to the close price. VWAP is the average price weighted by volume over the session (resets daily by default in Pine Script).
- **Purpose**: VWAP acts as a benchmark for "fair value." Prices above VWAP suggest bullishness (buyers in control), below indicate bearishness (sellers dominant). It's commonly used by institutional traders to assess entry/exit points.
### 5. **Plotting EMAs and VWAP**
```pine
plot(ema9, color=color.fuchsia, title='EMA 9 (Hermes)')
plot(ema20, color=color.red, title='EMA 20 (Apollo)')
plot(ema50, color=color.orange, title='EMA 50 (Athena)')
plot(ema100, color=color.aqua, title='EMA 100 (Zeus)')
plot(ema200, color=color.blue, title='EMA 200 (Kronos)')
plot(vwap_val, color=color.yellow, linewidth=2, title='VWAP')
```
- **What it does**: Overlays the EMAs and VWAP on the chart with distinct colors and titles for easy identification in TradingView's legend.
- **Purpose**: Visualizes the EMA ribbon and VWAP line. Traders can watch for EMA alignments (e.g., all sloping up for uptrend) or price interactions with VWAP.
### 6. **Dynamic VWAP Band**
```pine
band_pct = 0.005
vwap_upper = vwap_val * (1 + band_pct)
vwap_lower = vwap_val * (1 - band_pct)
p1 = plot(vwap_upper, color=color.new(color.yellow, 0), title="VWAP Upper Band")
p2 = plot(vwap_lower, color=color.new(color.yellow, 0), title="VWAP Lower Band")
fill_color = close >= vwap_val ? color.new(color.green, 80) : color.new(color.red, 80)
fill(p1, p2, color=fill_color, title="Dynamic VWAP Band")
```
- **What it does**: Creates a band ±0.5% around the VWAP.
- Plots the upper/lower bands with full transparency (color opacity 0, so lines are invisible).
- Fills the area between them dynamically: Semi-transparent green (opacity 80) if close ≥ VWAP (bullish bias), red if below (bearish bias).
- **Purpose**: Highlights deviations from VWAP visually. The color change provides an at-a-glance sentiment indicator—green for "above fair value" (potential strength), red for "below" (potential weakness). The narrow band (0.5%) focuses on short-term fairness, and the fill makes it easier to spot than just the line.
### 7. **Trend Clouds with VWAP Interaction**
```pine
bullish = ema9 > ema20 and ema20 > ema50
bearish = ema9 < ema20 and ema20 < ema50
bullish_above_vwap = bullish and close > vwap_val
bullish_below_vwap = bullish and close <= vwap_val
bearish_below_vwap = bearish and close < vwap_val
bearish_above_vwap = bearish and close >= vwap_val
bgcolor(bullish_above_vwap ? color.new(color.green, 50) : na, title="Bullish Above VWAP")
bgcolor(bullish_below_vwap ? color.new(color.green, 80) : na, title="Bullish Below VWAP")
bgcolor(bearish_below_vwap ? color.new(color.red, 50) : na, title="Bearish Below VWAP")
bgcolor(bearish_above_vwap ? color.new(color.red, 80) : na, title="Bearish Above VWAP")
```
- **What it does**: Defines trend conditions based on EMA alignments:
- Bullish: Shorter EMAs stacked above longer ones (9 > 20 > 50, indicating upward momentum).
- Bearish: The opposite (downward momentum).
- Sub-conditions combine with VWAP: E.g., bullish_above_vwap is true only if bullish and price > VWAP.
- Applies background colors (bgcolor) to the entire chart pane:
- Strong bullish (above VWAP): Green with opacity 50 (less transparent, more intense).
- Weak bullish (below VWAP): Green with opacity 80 (more transparent, less intense).
- Strong bearish (below VWAP): Red with opacity 50.
- Weak bearish (above VWAP): Red with opacity 80.
- If no condition matches, no color (na).
- **Purpose**: Creates "clouds" for trend visualization, enhanced by VWAP context. This helps traders confirm trends—e.g., a strong bullish cloud (darker green) suggests a high-conviction uptrend when price is above VWAP. The varying opacity differentiates signal strength: Darker for aligned conditions (trend + VWAP agreement), lighter for misaligned (potential weakening or reversal).
### Overall Indicator Usage and Limitations
- **How to use it**: Add this to a TradingView chart (e.g., stocks, crypto, forex). Look for EMA crossovers, price bouncing off EMAs/VWAP, or cloud color changes as signals. Bullish clouds with price above VWAP might signal buys; bearish below for sells.
- **Strengths**: Combines momentum (EMAs), volume (VWAP), and volatility adaptation for a multi-layered view. Dynamic colors make it intuitive.
- **Limitations**:
- EMAs lag in ranging markets; volatility adjustment helps but doesn't eliminate whipsaws.
- VWAP resets daily (standard behavior), so it's best for intraday/session trading.
- No alerts or inputs for customization (e.g., changeable lengths)—it's hardcoded.
- Performance depends on the asset/timeframe; backtest before using.
- **License**: Mozilla Public License 2.0, so it's open-source and modifiable.
ICT PDA - Gold & BTC (QuickScalp Bias/FVG/OB/OTE + Alerts)What this script does
This indicator implements a complete ICT Price Delivery Algorithm (PDA) workflow tailored for XAUUSD and BTCUSD. It combines HTF bias, OTE zones, Fair Value Gaps, Order Blocks, micro-BOS confirmation, and liquidity references into a single, cohesive tool with early and final alerts. The script is not a mashup for cosmetic plotting; each component feeds the next decision step.
Why this is original/useful
Symbol-aware impulse filter: A dynamic displacement threshold kTune adapts to Gold/BTC volatility (body/ATR vs. per-symbol factor), reducing noise on fast markets without hiding signals.
Scalping preset: “Quick Clean” mode limits drawings to the most recent bars and keeps only the latest FVG/OB zones for a clear chart.
Three display modes: Full, Clean, and Signals-Only to match analysis vs. execution.
Actionable alerts: Early heads-up when price enters OTE in the HTF bias direction, and Final alerts once mitigation + micro-break confirm the setup.
How it works (high-level logic)
HTF Bias: Uses request.security() on a user-selected timeframe (e.g., 240m) and EMA filter. Bias = close above/below HTF EMA.
Dealing Range & OTE: Recent swing high/low (pivot length configurable) define the range; OTE (62–79%) boxes are drawn contextually for up/down ranges.
Displacement: A candle’s body/ATR must exceed kTune and break short-term structure (displacement up/down).
FVG: 3-bar imbalance (bull: low > high ; bear: high < low ). Latest gaps are tracked and extended.
Order Blocks: Last opposite candle prior to a qualifying displacement that breaks recent highs/lows; zones are drawn and extended.
Entry & Alerts:
Long: Bullish bias + price inside buy-OTE + mitigation of a bullish FVG or OB + micro BOS up → “PDA Long (Final)”.
Short: Bearish bias + price inside sell-OTE + mitigation of a bearish FVG or OB + micro BOS down → “PDA Short (Final)”.
Early Alerts: Trigger as soon as price enters OTE in the direction of the active bias.
Inputs & controls (key ones)
Bias (HTF): timeframe minutes, EMA length.
Structure: ATR length, Impulse Threshold (Body/ATR), swing pivot length, OB look-back.
OTE/FVG/OB/LP toggles: show/hide components.
Auto-Tune: per-symbol factors for Gold/BTC + manual tweak.
Display/Performance: View Mode, keep-N latest FVG/OB, limit drawings to last N bars.
Recommended usage (scalping)
Timeframes: Execute on M1–M5 with HTF bias from 120–240m.
Defaults (starting point): ATR=14, Impulse Threshold≈1.6; Gold factor≈1.05, BTC factor≈0.90; Keep FVG/OB=2; last 200–300 bars; View Mode=Clean.
Workflow: Wait for OTE in bias direction → see mitigation (FVG/OB) → confirm with micro BOS → manage risk to nearest liquidity (prev-day H/L or recent swing).
Alerts available
“PDA Early Long/Short”
“PDA Long (Final)” / “PDA Short (Final)”
Attach alerts on “Any alert() function call” or the listed conditions.
Chart & screenshots
Please include symbol and timeframe on screenshots. The on-chart HUD shows the script name and state to help reviewers understand context.
Limitations / notes
This is a discretionary framework. Signals can cluster during news or extreme volatility; use your own risk management. No guarantee of profitability.
Changelog (brief)
v1.2 QuickScalp: added Quick Clean preset, safer array handling, symbol-aware impulse tuning, display modes.
------------------------------
ملخص عربي:
المؤشر يطبق تسلسل PDA عملي للذهب والبتكوين: تحيز من فريم أعلى، مناطق OTE، فجوات FVG، بلوكات أوامر OB، وتأكيد micro-BOS، مع تنبيهات مبكرة ونهائية. تمت إضافة وضع “Quick Clean” لتقليل العناصر على الشارت وحساسية إزاحة تتكيّف مع الأصل. للاستخدام كسكالب: نفّذ على M1–M5 مع تحيز 120–240 دقيقة، وابدأ من الإعدادات المقترحة بالأعلى. هذا إطار سلوكي وليس توصية مالية.
Reversal Probability Meter PRO [optimized for Xau/Usd m5]🎯 Reversal Probability Meter PRO
A powerful multi-factor reversal probability detector that calculates the likelihood of bullish or bearish reversals using RSI, EMA bias, ATR spikes, candle patterns, volume spikes, and higher timeframe (HTF) trend alignment.
🧩 MAIN FEATURES
1. Reversal Probability (Bullish & Bearish)
Displays two key metrics:
Bull % — probability of bullish reversal
Bear % — probability of bearish reversal
These are computed using RSI, EMAs, ATR, demand/supply zones, candle confirmations, and volume spikes.
📊 Interpretation:
Bull % > 70% → Buying pressure building up
Bull % > 85% → Strong bullish reversal confirmed
Bear % > 70% → Selling pressure building up
Bear % > 85% → Strong bearish reversal confirmed
2. Alert Probability Threshold
Adjustable via alertThreshold (default = 85%).
Alerts trigger only when probability ≥ threshold, and confirmed by zone + volume spike + candle pattern.
🔔 Alerts Available:
✅ Bullish Smart Reversal
🔻 Bearish Smart Reversal
To activate: Right-click chart → “Add alert” → choose the alert condition from the indicator.
3. Demand / Supply Zone Detection
The script determines the price position within the last zoneLook (default 30) bars:
🟢 DEMAND → Lower 35% of range (potential bounce zone)
🔴 SUPPLY → Upper 35% of range (potential rejection zone)
⚪ MID → Neutral area
📘 Purpose: Validates reversals based on context:
Bullish only valid in Demand zones
Bearish only valid in Supply zones
4. Higher Timeframe (HTF) Trend Alignment
Reads EMA bias from a higher timeframe (default = 15m) for trend confirmation.
Reversals against HTF trend are automatically weighted down prevents false countertrend signals.
📈 Example:
M5 chart under M15 downtrend → Bullish probability is reduced.
5. Candle Confirmation Patterns
Two key price action confirmations:
Bullish: Engulfing or Pin Bar
Bearish: Engulfing or Pin Bar
A valid reversal requires both a candle confirmation and a volume spike.
6. Volume & ATR Spike Filters
Volume Spike: volume > SMA(20) × 1.3
ATR Spike: ATR > SMA(ATR, 50) × volMult
🎯 Ensures that only strong market moves with real energy are considered valid reversals.
7. Reversal Momentum Histogram
A color-gradient oscillator showing the momentum difference:
Green = bullish dominance
Red = bearish dominance
Flat near 0 = neutral
Controlled by showOscillator toggle.
8. Smart Info Panel
A compact dashboard displayed on the top-right with 4 rows:
Row Info Description
1 Bull % Bullish reversal probability
2 Bear % Bearish reversal probability
3 Zone Market context (DEMAND / SUPPLY / MID)
4 Signal Strength Current signal intensity (probability %)
Dynamic Colors:
90% → Bright (strong signal)
75–90% → Yellow/Orange (medium)
<75% → Gray (weak)
9. Sensitivity Mode
Fine-tunes indicator reactivity:
🟥 Aggressive: Detects reversals early (more signals, less accurate)
🟨 Normal: Balanced, default mode
🟩 Conservative: Filters only strongest reversals (fewer but more reliable)
10. Custom Color Options
Customize bullish and bearish colors via bullBaseColor and bearBaseColor inputs for your preferred chart theme.
⚙️ HOW TO USE
Add to Chart
→ Paste the script into Pine Editor → “Add to chart”.
Select Timeframe
→ Best for M5–M30 (scalping/intraday).
→ H1–H4 for swing trading.
Monitor the Info Panel:
Bull % ≥ 85% + Zone = Demand → Strong bullish reversal signal
Bear % ≥ 85% + Zone = Supply → Strong bearish reversal signal
Watch the Histogram:
Rising green bars = bullish momentum gaining
Deep red bars = bearish momentum gaining
Enable Alerts:
Right-click chart → “Add alert”
Choose Bullish Smart Reversal or Bearish Smart Reversal
🧠 TRADING TIPS
Use Conservative mode for noisy lower timeframes (M5–M15).
Use Aggressive mode for higher timeframes (H1–H4).
Combine with manual support/resistance or zone boxes for precision entries. Personally i use Order Block.
Best reversal setups occur when all align:
Bull % > 85%
Zone = DEMAND
Volume spike present
Candle = Bullish engulfing
HTF trend supportive
Dynamic Equity Allocation Model"Cash is Trash"? Not Always. Here's Why Science Beats Guesswork.
Every retail trader knows the frustration: you draw support and resistance lines, you spot patterns, you follow market gurus on social media—and still, when the next bear market hits, your portfolio bleeds red. Meanwhile, institutional investors seem to navigate market turbulence with ease, preserving capital when markets crash and participating when they rally. What's their secret?
The answer isn't insider information or access to exotic derivatives. It's systematic, scientifically validated decision-making. While most retail traders rely on subjective chart analysis and emotional reactions, professional portfolio managers use quantitative models that remove emotion from the equation and process multiple streams of market information simultaneously.
This document presents exactly such a system—not a proprietary black box available only to hedge funds, but a fully transparent, academically grounded framework that any serious investor can understand and apply. The Dynamic Equity Allocation Model (DEAM) synthesizes decades of financial research from Nobel laureates and leading academics into a practical tool for tactical asset allocation.
Stop drawing colorful lines on your chart and start thinking like a quant. This isn't about predicting where the market goes next week—it's about systematically adjusting your risk exposure based on what the data actually tells you. When valuations scream danger, when volatility spikes, when credit markets freeze, when multiple warning signals align—that's when cash isn't trash. That's when cash saves your portfolio.
The irony of "cash is trash" rhetoric is that it ignores timing. Yes, being 100% cash for decades would be disastrous. But being 100% equities through every crisis is equally foolish. The sophisticated approach is dynamic: aggressive when conditions favor risk-taking, defensive when they don't. This model shows you how to make that decision systematically, not emotionally.
Whether you're managing your own retirement portfolio or seeking to understand how institutional allocation strategies work, this comprehensive analysis provides the theoretical foundation, mathematical implementation, and practical guidance to elevate your investment approach from amateur to professional.
The choice is yours: keep hoping your chart patterns work out, or start using the same quantitative methods that professionals rely on. The tools are here. The research is cited. The methodology is explained. All you need to do is read, understand, and apply.
The Dynamic Equity Allocation Model (DEAM) is a quantitative framework for systematic allocation between equities and cash, grounded in modern portfolio theory and empirical market research. The model integrates five scientifically validated dimensions of market analysis—market regime, risk metrics, valuation, sentiment, and macroeconomic conditions—to generate dynamic allocation recommendations ranging from 0% to 100% equity exposure. This work documents the theoretical foundations, mathematical implementation, and practical application of this multi-factor approach.
1. Introduction and Theoretical Background
1.1 The Limitations of Static Portfolio Allocation
Traditional portfolio theory, as formulated by Markowitz (1952) in his seminal work "Portfolio Selection," assumes an optimal static allocation where investors distribute their wealth across asset classes according to their risk aversion. This approach rests on the assumption that returns and risks remain constant over time. However, empirical research demonstrates that this assumption does not hold in reality. Fama and French (1989) showed that expected returns vary over time and correlate with macroeconomic variables such as the spread between long-term and short-term interest rates. Campbell and Shiller (1988) demonstrated that the price-earnings ratio possesses predictive power for future stock returns, providing a foundation for dynamic allocation strategies.
The academic literature on tactical asset allocation has evolved considerably over recent decades. Ilmanen (2011) argues in "Expected Returns" that investors can improve their risk-adjusted returns by considering valuation levels, business cycles, and market sentiment. The Dynamic Equity Allocation Model presented here builds on this research tradition and operationalizes these insights into a practically applicable allocation framework.
1.2 Multi-Factor Approaches in Asset Allocation
Modern financial research has shown that different factors capture distinct aspects of market dynamics and together provide a more robust picture of market conditions than individual indicators. Ross (1976) developed the Arbitrage Pricing Theory, a model that employs multiple factors to explain security returns. Following this multi-factor philosophy, DEAM integrates five complementary analytical dimensions, each tapping different information sources and collectively enabling comprehensive market understanding.
2. Data Foundation and Data Quality
2.1 Data Sources Used
The model draws its data exclusively from publicly available market data via the TradingView platform. This transparency and accessibility is a significant advantage over proprietary models that rely on non-public data. The data foundation encompasses several categories of market information, each capturing specific aspects of market dynamics.
First, price data for the S&P 500 Index is obtained through the SPDR S&P 500 ETF (ticker: SPY). The use of a highly liquid ETF instead of the index itself has practical reasons, as ETF data is available in real-time and reflects actual tradability. In addition to closing prices, high, low, and volume data are captured, which are required for calculating advanced volatility measures.
Fundamental corporate metrics are retrieved via TradingView's Financial Data API. These include earnings per share, price-to-earnings ratio, return on equity, debt-to-equity ratio, dividend yield, and share buyback yield. Cochrane (2011) emphasizes in "Presidential Address: Discount Rates" the central importance of valuation metrics for forecasting future returns, making these fundamental data a cornerstone of the model.
Volatility indicators are represented by the CBOE Volatility Index (VIX) and related metrics. The VIX, often referred to as the market's "fear gauge," measures the implied volatility of S&P 500 index options and serves as a proxy for market participants' risk perception. Whaley (2000) describes in "The Investor Fear Gauge" the construction and interpretation of the VIX and its use as a sentiment indicator.
Macroeconomic data includes yield curve information through US Treasury bonds of various maturities and credit risk premiums through the spread between high-yield bonds and risk-free government bonds. These variables capture the macroeconomic conditions and financing conditions relevant for equity valuation. Estrella and Hardouvelis (1991) showed that the shape of the yield curve has predictive power for future economic activity, justifying the inclusion of these data.
2.2 Handling Missing Data
A practical problem when working with financial data is dealing with missing or unavailable values. The model implements a fallback system where a plausible historical average value is stored for each fundamental metric. When current data is unavailable for a specific point in time, this fallback value is used. This approach ensures that the model remains functional even during temporary data outages and avoids systematic biases from missing data. The use of average values as fallback is conservative, as it generates neither overly optimistic nor pessimistic signals.
3. Component 1: Market Regime Detection
3.1 The Concept of Market Regimes
The idea that financial markets exist in different "regimes" or states that differ in their statistical properties has a long tradition in financial science. Hamilton (1989) developed regime-switching models that allow distinguishing between different market states with different return and volatility characteristics. The practical application of this theory consists of identifying the current market state and adjusting portfolio allocation accordingly.
DEAM classifies market regimes using a scoring system that considers three main dimensions: trend strength, volatility level, and drawdown depth. This multidimensional view is more robust than focusing on individual indicators, as it captures various facets of market dynamics. Classification occurs into six distinct regimes: Strong Bull, Bull Market, Neutral, Correction, Bear Market, and Crisis.
3.2 Trend Analysis Through Moving Averages
Moving averages are among the oldest and most widely used technical indicators and have also received attention in academic literature. Brock, Lakonishok, and LeBaron (1992) examined in "Simple Technical Trading Rules and the Stochastic Properties of Stock Returns" the profitability of trading rules based on moving averages and found evidence for their predictive power, although later studies questioned the robustness of these results when considering transaction costs.
The model calculates three moving averages with different time windows: a 20-day average (approximately one trading month), a 50-day average (approximately one quarter), and a 200-day average (approximately one trading year). The relationship of the current price to these averages and the relationship of the averages to each other provide information about trend strength and direction. When the price trades above all three averages and the short-term average is above the long-term, this indicates an established uptrend. The model assigns points based on these constellations, with longer-term trends weighted more heavily as they are considered more persistent.
3.3 Volatility Regimes
Volatility, understood as the standard deviation of returns, is a central concept of financial theory and serves as the primary risk measure. However, research has shown that volatility is not constant but changes over time and occurs in clusters—a phenomenon first documented by Mandelbrot (1963) and later formalized through ARCH and GARCH models (Engle, 1982; Bollerslev, 1986).
DEAM calculates volatility not only through the classic method of return standard deviation but also uses more advanced estimators such as the Parkinson estimator and the Garman-Klass estimator. These methods utilize intraday information (high and low prices) and are more efficient than simple close-to-close volatility estimators. The Parkinson estimator (Parkinson, 1980) uses the range between high and low of a trading day and is based on the recognition that this information reveals more about true volatility than just the closing price difference. The Garman-Klass estimator (Garman and Klass, 1980) extends this approach by additionally considering opening and closing prices.
The calculated volatility is annualized by multiplying it by the square root of 252 (the average number of trading days per year), enabling standardized comparability. The model compares current volatility with the VIX, the implied volatility from option prices. A low VIX (below 15) signals market comfort and increases the regime score, while a high VIX (above 35) indicates market stress and reduces the score. This interpretation follows the empirical observation that elevated volatility is typically associated with falling markets (Schwert, 1989).
3.4 Drawdown Analysis
A drawdown refers to the percentage decline from the highest point (peak) to the lowest point (trough) during a specific period. This metric is psychologically significant for investors as it represents the maximum loss experienced. Calmar (1991) developed the Calmar Ratio, which relates return to maximum drawdown, underscoring the practical relevance of this metric.
The model calculates current drawdown as the percentage distance from the highest price of the last 252 trading days (one year). A drawdown below 3% is considered negligible and maximally increases the regime score. As drawdown increases, the score decreases progressively, with drawdowns above 20% classified as severe and indicating a crisis or bear market regime. These thresholds are empirically motivated by historical market cycles, in which corrections typically encompassed 5-10% drawdowns, bear markets 20-30%, and crises over 30%.
3.5 Regime Classification
Final regime classification occurs through aggregation of scores from trend (40% weight), volatility (30%), and drawdown (30%). The higher weighting of trend reflects the empirical observation that trend-following strategies have historically delivered robust results (Moskowitz, Ooi, and Pedersen, 2012). A total score above 80 signals a strong bull market with established uptrend, low volatility, and minimal losses. At a score below 10, a crisis situation exists requiring defensive positioning. The six regime categories enable a differentiated allocation strategy that not only distinguishes binarily between bullish and bearish but allows gradual gradations.
4. Component 2: Risk-Based Allocation
4.1 Volatility Targeting as Risk Management Approach
The concept of volatility targeting is based on the idea that investors should maximize not returns but risk-adjusted returns. Sharpe (1966, 1994) defined with the Sharpe Ratio the fundamental concept of return per unit of risk, measured as volatility. Volatility targeting goes a step further and adjusts portfolio allocation to achieve constant target volatility. This means that in times of low market volatility, equity allocation is increased, and in times of high volatility, it is reduced.
Moreira and Muir (2017) showed in "Volatility-Managed Portfolios" that strategies that adjust their exposure based on volatility forecasts achieve higher Sharpe Ratios than passive buy-and-hold strategies. DEAM implements this principle by defining a target portfolio volatility (default 12% annualized) and adjusting equity allocation to achieve it. The mathematical foundation is simple: if market volatility is 20% and target volatility is 12%, equity allocation should be 60% (12/20 = 0.6), with the remaining 40% held in cash with zero volatility.
4.2 Market Volatility Calculation
Estimating current market volatility is central to the risk-based allocation approach. The model uses several volatility estimators in parallel and selects the higher value between traditional close-to-close volatility and the Parkinson estimator. This conservative choice ensures the model does not underestimate true volatility, which could lead to excessive risk exposure.
Traditional volatility calculation uses logarithmic returns, as these have mathematically advantageous properties (additive linkage over multiple periods). The logarithmic return is calculated as ln(P_t / P_{t-1}), where P_t is the price at time t. The standard deviation of these returns over a rolling 20-trading-day window is then multiplied by √252 to obtain annualized volatility. This annualization is based on the assumption of independently identically distributed returns, which is an idealization but widely accepted in practice.
The Parkinson estimator uses additional information from the trading range (High minus Low) of each day. The formula is: σ_P = (1/√(4ln2)) × √(1/n × Σln²(H_i/L_i)) × √252, where H_i and L_i are high and low prices. Under ideal conditions, this estimator is approximately five times more efficient than the close-to-close estimator (Parkinson, 1980), as it uses more information per observation.
4.3 Drawdown-Based Position Size Adjustment
In addition to volatility targeting, the model implements drawdown-based risk control. The logic is that deep market declines often signal further losses and therefore justify exposure reduction. This behavior corresponds with the concept of path-dependent risk tolerance: investors who have already suffered losses are typically less willing to take additional risk (Kahneman and Tversky, 1979).
The model defines a maximum portfolio drawdown as a target parameter (default 15%). Since portfolio volatility and portfolio drawdown are proportional to equity allocation (assuming cash has neither volatility nor drawdown), allocation-based control is possible. For example, if the market exhibits a 25% drawdown and target portfolio drawdown is 15%, equity allocation should be at most 60% (15/25).
4.4 Dynamic Risk Adjustment
An advanced feature of DEAM is dynamic adjustment of risk-based allocation through a feedback mechanism. The model continuously estimates what actual portfolio volatility and portfolio drawdown would result at the current allocation. If risk utilization (ratio of actual to target risk) exceeds 1.0, allocation is reduced by an adjustment factor that grows exponentially with overutilization. This implements a form of dynamic feedback that avoids overexposure.
Mathematically, a risk adjustment factor r_adjust is calculated: if risk utilization u > 1, then r_adjust = exp(-0.5 × (u - 1)). This exponential function ensures that moderate overutilization is gently corrected, while strong overutilization triggers drastic reductions. The factor 0.5 in the exponent was empirically calibrated to achieve a balanced ratio between sensitivity and stability.
5. Component 3: Valuation Analysis
5.1 Theoretical Foundations of Fundamental Valuation
DEAM's valuation component is based on the fundamental premise that the intrinsic value of a security is determined by its future cash flows and that deviations between market price and intrinsic value are eventually corrected. Graham and Dodd (1934) established in "Security Analysis" the basic principles of fundamental analysis that remain relevant today. Translated into modern portfolio context, this means that markets with high valuation metrics (high price-earnings ratios) should have lower expected returns than cheaply valued markets.
Campbell and Shiller (1988) developed the Cyclically Adjusted P/E Ratio (CAPE), which smooths earnings over a full business cycle. Their empirical analysis showed that this ratio has significant predictive power for 10-year returns. Asness, Moskowitz, and Pedersen (2013) demonstrated in "Value and Momentum Everywhere" that value effects exist not only in individual stocks but also in asset classes and markets.
5.2 Equity Risk Premium as Central Valuation Metric
The Equity Risk Premium (ERP) is defined as the expected excess return of stocks over risk-free government bonds. It is the theoretical heart of valuation analysis, as it represents the compensation investors demand for bearing equity risk. Damodaran (2012) discusses in "Equity Risk Premiums: Determinants, Estimation and Implications" various methods for ERP estimation.
DEAM calculates ERP not through a single method but combines four complementary approaches with different weights. This multi-method strategy increases estimation robustness and avoids dependence on single, potentially erroneous inputs.
The first method (35% weight) uses earnings yield, calculated as 1/P/E or directly from operating earnings data, and subtracts the 10-year Treasury yield. This method follows Fed Model logic (Yardeni, 2003), although this model has theoretical weaknesses as it does not consistently treat inflation (Asness, 2003).
The second method (30% weight) extends earnings yield by share buyback yield. Share buybacks are a form of capital return to shareholders and increase value per share. Boudoukh et al. (2007) showed in "The Total Shareholder Yield" that the sum of dividend yield and buyback yield is a better predictor of future returns than dividend yield alone.
The third method (20% weight) implements the Gordon Growth Model (Gordon, 1962), which models stock value as the sum of discounted future dividends. Under constant growth g assumption: Expected Return = Dividend Yield + g. The model estimates sustainable growth as g = ROE × (1 - Payout Ratio), where ROE is return on equity and payout ratio is the ratio of dividends to earnings. This formula follows from equity theory: unretained earnings are reinvested at ROE and generate additional earnings growth.
The fourth method (15% weight) combines total shareholder yield (Dividend + Buybacks) with implied growth derived from revenue growth. This method considers that companies with strong revenue growth should generate higher future earnings, even if current valuations do not yet fully reflect this.
The final ERP is the weighted average of these four methods. A high ERP (above 4%) signals attractive valuations and increases the valuation score to 95 out of 100 possible points. A negative ERP, where stocks have lower expected returns than bonds, results in a minimal score of 10.
5.3 Quality Adjustments to Valuation
Valuation metrics alone can be misleading if not interpreted in the context of company quality. A company with a low P/E may be cheap or fundamentally problematic. The model therefore implements quality adjustments based on growth, profitability, and capital structure.
Revenue growth above 10% annually adds 10 points to the valuation score, moderate growth above 5% adds 5 points. This adjustment reflects that growth has independent value (Modigliani and Miller, 1961, extended by later growth theory). Net margin above 15% signals pricing power and operational efficiency and increases the score by 5 points, while low margins below 8% indicate competitive pressure and subtract 5 points.
Return on equity (ROE) above 20% characterizes outstanding capital efficiency and increases the score by 5 points. Piotroski (2000) showed in "Value Investing: The Use of Historical Financial Statement Information" that fundamental quality signals such as high ROE can improve the performance of value strategies.
Capital structure is evaluated through the debt-to-equity ratio. A conservative ratio below 1.0 multiplies the valuation score by 1.2, while high leverage above 2.0 applies a multiplier of 0.8. This adjustment reflects that high debt constrains financial flexibility and can become problematic in crisis times (Korteweg, 2010).
6. Component 4: Sentiment Analysis
6.1 The Role of Sentiment in Financial Markets
Investor sentiment, defined as the collective psychological attitude of market participants, influences asset prices independently of fundamental data. Baker and Wurgler (2006, 2007) developed a sentiment index and showed that periods of high sentiment are followed by overvaluations that later correct. This insight justifies integrating a sentiment component into allocation decisions.
Sentiment is difficult to measure directly but can be proxied through market indicators. The VIX is the most widely used sentiment indicator, as it aggregates implied volatility from option prices. High VIX values reflect elevated uncertainty and risk aversion, while low values signal market comfort. Whaley (2009) refers to the VIX as the "Investor Fear Gauge" and documents its role as a contrarian indicator: extremely high values typically occur at market bottoms, while low values occur at tops.
6.2 VIX-Based Sentiment Assessment
DEAM uses statistical normalization of the VIX by calculating the Z-score: z = (VIX_current - VIX_average) / VIX_standard_deviation. The Z-score indicates how many standard deviations the current VIX is from the historical average. This approach is more robust than absolute thresholds, as it adapts to the average volatility level, which can vary over longer periods.
A Z-score below -1.5 (VIX is 1.5 standard deviations below average) signals exceptionally low risk perception and adds 40 points to the sentiment score. This may seem counterintuitive—shouldn't low fear be bullish? However, the logic follows the contrarian principle: when no one is afraid, everyone is already invested, and there is limited further upside potential (Zweig, 1973). Conversely, a Z-score above 1.5 (extreme fear) adds -40 points, reflecting market panic but simultaneously suggesting potential buying opportunities.
6.3 VIX Term Structure as Sentiment Signal
The VIX term structure provides additional sentiment information. Normally, the VIX trades in contango, meaning longer-term VIX futures have higher prices than short-term. This reflects that short-term volatility is currently known, while long-term volatility is more uncertain and carries a risk premium. The model compares the VIX with VIX9D (9-day volatility) and identifies backwardation (VIX > 1.05 × VIX9D) and steep backwardation (VIX > 1.15 × VIX9D).
Backwardation occurs when short-term implied volatility is higher than longer-term, which typically happens during market stress. Investors anticipate immediate turbulence but expect calming. Psychologically, this reflects acute fear. The model subtracts 15 points for backwardation and 30 for steep backwardation, as these constellations signal elevated risk. Simon and Wiggins (2001) analyzed the VIX futures curve and showed that backwardation is associated with market declines.
6.4 Safe-Haven Flows
During crisis times, investors flee from risky assets into safe havens: gold, US dollar, and Japanese yen. This "flight to quality" is a sentiment signal. The model calculates the performance of these assets relative to stocks over the last 20 trading days. When gold or the dollar strongly rise while stocks fall, this indicates elevated risk aversion.
The safe-haven component is calculated as the difference between safe-haven performance and stock performance. Positive values (safe havens outperform) subtract up to 20 points from the sentiment score, negative values (stocks outperform) add up to 10 points. The asymmetric treatment (larger deduction for risk-off than bonus for risk-on) reflects that risk-off movements are typically sharper and more informative than risk-on phases.
Baur and Lucey (2010) examined safe-haven properties of gold and showed that gold indeed exhibits negative correlation with stocks during extreme market movements, confirming its role as crisis protection.
7. Component 5: Macroeconomic Analysis
7.1 The Yield Curve as Economic Indicator
The yield curve, represented as yields of government bonds of various maturities, contains aggregated expectations about future interest rates, inflation, and economic growth. The slope of the yield curve has remarkable predictive power for recessions. Estrella and Mishkin (1998) showed that an inverted yield curve (short-term rates higher than long-term) predicts recessions with high reliability. This is because inverted curves reflect restrictive monetary policy: the central bank raises short-term rates to combat inflation, dampening economic activity.
DEAM calculates two spread measures: the 2-year-minus-10-year spread and the 3-month-minus-10-year spread. A steep, positive curve (spreads above 1.5% and 2% respectively) signals healthy growth expectations and generates the maximum yield curve score of 40 points. A flat curve (spreads near zero) reduces the score to 20 points. An inverted curve (negative spreads) is particularly alarming and results in only 10 points.
The choice of two different spreads increases analysis robustness. The 2-10 spread is most established in academic literature, while the 3M-10Y spread is often considered more sensitive, as the 3-month rate directly reflects current monetary policy (Ang, Piazzesi, and Wei, 2006).
7.2 Credit Conditions and Spreads
Credit spreads—the yield difference between risky corporate bonds and safe government bonds—reflect risk perception in the credit market. Gilchrist and Zakrajšek (2012) constructed an "Excess Bond Premium" that measures the component of credit spreads not explained by fundamentals and showed this is a predictor of future economic activity and stock returns.
The model approximates credit spread by comparing the yield of high-yield bond ETFs (HYG) with investment-grade bond ETFs (LQD). A narrow spread below 200 basis points signals healthy credit conditions and risk appetite, contributing 30 points to the macro score. Very wide spreads above 1000 basis points (as during the 2008 financial crisis) signal credit crunch and generate zero points.
Additionally, the model evaluates whether "flight to quality" is occurring, identified through strong performance of Treasury bonds (TLT) with simultaneous weakness in high-yield bonds. This constellation indicates elevated risk aversion and reduces the credit conditions score.
7.3 Financial Stability at Corporate Level
While the yield curve and credit spreads reflect macroeconomic conditions, financial stability evaluates the health of companies themselves. The model uses the aggregated debt-to-equity ratio and return on equity of the S&P 500 as proxies for corporate health.
A low leverage level below 0.5 combined with high ROE above 15% signals robust corporate balance sheets and generates 20 points. This combination is particularly valuable as it represents both defensive strength (low debt means crisis resistance) and offensive strength (high ROE means earnings power). High leverage above 1.5 generates only 5 points, as it implies vulnerability to interest rate increases and recessions.
Korteweg (2010) showed in "The Net Benefits to Leverage" that optimal debt maximizes firm value, but excessive debt increases distress costs. At the aggregated market level, high debt indicates fragilities that can become problematic during stress phases.
8. Component 6: Crisis Detection
8.1 The Need for Systematic Crisis Detection
Financial crises are rare but extremely impactful events that suspend normal statistical relationships. During normal market volatility, diversified portfolios and traditional risk management approaches function, but during systemic crises, seemingly independent assets suddenly correlate strongly, and losses exceed historical expectations (Longin and Solnik, 2001). This justifies a separate crisis detection mechanism that operates independently of regular allocation components.
Reinhart and Rogoff (2009) documented in "This Time Is Different: Eight Centuries of Financial Folly" recurring patterns in financial crises: extreme volatility, massive drawdowns, credit market dysfunction, and asset price collapse. DEAM operationalizes these patterns into quantifiable crisis indicators.
8.2 Multi-Signal Crisis Identification
The model uses a counter-based approach where various stress signals are identified and aggregated. This methodology is more robust than relying on a single indicator, as true crises typically occur simultaneously across multiple dimensions. A single signal may be a false alarm, but the simultaneous presence of multiple signals increases confidence.
The first indicator is a VIX above the crisis threshold (default 40), adding one point. A VIX above 60 (as in 2008 and March 2020) adds two additional points, as such extreme values are historically very rare. This tiered approach captures the intensity of volatility.
The second indicator is market drawdown. A drawdown above 15% adds one point, as corrections of this magnitude can be potential harbingers of larger crises. A drawdown above 25% adds another point, as historical bear markets typically encompass 25-40% drawdowns.
The third indicator is credit market spreads above 500 basis points, adding one point. Such wide spreads occur only during significant credit market disruptions, as in 2008 during the Lehman crisis.
The fourth indicator identifies simultaneous losses in stocks and bonds. Normally, Treasury bonds act as a hedge against equity risk (negative correlation), but when both fall simultaneously, this indicates systemic liquidity problems or inflation/stagflation fears. The model checks whether both SPY and TLT have fallen more than 10% and 5% respectively over 5 trading days, adding two points.
The fifth indicator is a volume spike combined with negative returns. Extreme trading volumes (above twice the 20-day average) with falling prices signal panic selling. This adds one point.
A crisis situation is diagnosed when at least 3 indicators trigger, a severe crisis at 5 or more indicators. These thresholds were calibrated through historical backtesting to identify true crises (2008, 2020) without generating excessive false alarms.
8.3 Crisis-Based Allocation Override
When a crisis is detected, the system overrides the normal allocation recommendation and caps equity allocation at maximum 25%. In a severe crisis, the cap is set at 10%. This drastic defensive posture follows the empirical observation that crises typically require time to develop and that early reduction can avoid substantial losses (Faber, 2007).
This override logic implements a "safety first" principle: in situations of existential danger to the portfolio, capital preservation becomes the top priority. Roy (1952) formalized this approach in "Safety First and the Holding of Assets," arguing that investors should primarily minimize ruin probability.
9. Integration and Final Allocation Calculation
9.1 Component Weighting
The final allocation recommendation emerges through weighted aggregation of the five components. The standard weighting is: Market Regime 35%, Risk Management 25%, Valuation 20%, Sentiment 15%, Macro 5%. These weights reflect both theoretical considerations and empirical backtesting results.
The highest weighting of market regime is based on evidence that trend-following and momentum strategies have delivered robust results across various asset classes and time periods (Moskowitz, Ooi, and Pedersen, 2012). Current market momentum is highly informative for the near future, although it provides no information about long-term expectations.
The substantial weighting of risk management (25%) follows from the central importance of risk control. Wealth preservation is the foundation of long-term wealth creation, and systematic risk management is demonstrably value-creating (Moreira and Muir, 2017).
The valuation component receives 20% weight, based on the long-term mean reversion of valuation metrics. While valuation has limited short-term predictive power (bull and bear markets can begin at any valuation), the long-term relationship between valuation and returns is robustly documented (Campbell and Shiller, 1988).
Sentiment (15%) and Macro (5%) receive lower weights, as these factors are subtler and harder to measure. Sentiment is valuable as a contrarian indicator at extremes but less informative in normal ranges. Macro variables such as the yield curve have strong predictive power for recessions, but the transmission from recessions to stock market performance is complex and temporally variable.
9.2 Model Type Adjustments
DEAM allows users to choose between four model types: Conservative, Balanced, Aggressive, and Adaptive. This choice modifies the final allocation through additive adjustments.
Conservative mode subtracts 10 percentage points from allocation, resulting in consistently more cautious positioning. This is suitable for risk-averse investors or those with limited investment horizons. Aggressive mode adds 10 percentage points, suitable for risk-tolerant investors with long horizons.
Adaptive mode implements procyclical adjustment based on short-term momentum: if the market has risen more than 5% in the last 20 days, 5 percentage points are added; if it has declined more than 5%, 5 points are subtracted. This logic follows the observation that short-term momentum persists (Jegadeesh and Titman, 1993), but the moderate size of adjustment avoids excessive timing bets.
Balanced mode makes no adjustment and uses raw model output. This neutral setting is suitable for investors who wish to trust model recommendations unchanged.
9.3 Smoothing and Stability
The allocation resulting from aggregation undergoes final smoothing through a simple moving average over 3 periods. This smoothing is crucial for model practicality, as it reduces frequent trading and thus transaction costs. Without smoothing, the model could fluctuate between adjacent allocations with every small input change.
The choice of 3 periods as smoothing window is a compromise between responsiveness and stability. Longer smoothing would excessively delay signals and impede response to true regime changes. Shorter or no smoothing would allow too much noise. Empirical tests showed that 3-period smoothing offers an optimal ratio between these goals.
10. Visualization and Interpretation
10.1 Main Output: Equity Allocation
DEAM's primary output is a time series from 0 to 100 representing the recommended percentage allocation to equities. This representation is intuitive: 100% means full investment in stocks (specifically: an S&P 500 ETF), 0% means complete cash position, and intermediate values correspond to mixed portfolios. A value of 60% means, for example: invest 60% of wealth in SPY, hold 40% in money market instruments or cash.
The time series is color-coded to enable quick visual interpretation. Green shades represent high allocations (above 80%, bullish), red shades low allocations (below 20%, bearish), and neutral colors middle allocations. The chart background is dynamically colored based on the signal, enhancing readability in different market phases.
10.2 Dashboard Metrics
A tabular dashboard presents key metrics compactly. This includes current allocation, cash allocation (complement), an aggregated signal (BULLISH/NEUTRAL/BEARISH), current market regime, VIX level, market drawdown, and crisis status.
Additionally, fundamental metrics are displayed: P/E Ratio, Equity Risk Premium, Return on Equity, Debt-to-Equity Ratio, and Total Shareholder Yield. This transparency allows users to understand model decisions and form their own assessments.
Component scores (Regime, Risk, Valuation, Sentiment, Macro) are also displayed, each normalized on a 0-100 scale. This shows which factors primarily drive the current recommendation. If, for example, the Risk score is very low (20) while other scores are moderate (50-60), this indicates that risk management considerations are pulling allocation down.
10.3 Component Breakdown (Optional)
Advanced users can display individual components as separate lines in the chart. This enables analysis of component dynamics: do all components move synchronously, or are there divergences? Divergences can be particularly informative. If, for example, the market regime is bullish (high score) but the valuation component is very negative, this signals an overbought market not fundamentally supported—a classic "bubble warning."
This feature is disabled by default to keep the chart clean but can be activated for deeper analysis.
10.4 Confidence Bands
The model optionally displays uncertainty bands around the main allocation line. These are calculated as ±1 standard deviation of allocation over a rolling 20-period window. Wide bands indicate high volatility of model recommendations, suggesting uncertain market conditions. Narrow bands indicate stable recommendations.
This visualization implements a concept of epistemic uncertainty—uncertainty about the model estimate itself, not just market volatility. In phases where various indicators send conflicting signals, the allocation recommendation becomes more volatile, manifesting in wider bands. Users can understand this as a warning to act more cautiously or consult alternative information sources.
11. Alert System
11.1 Allocation Alerts
DEAM implements an alert system that notifies users of significant events. Allocation alerts trigger when smoothed allocation crosses certain thresholds. An alert is generated when allocation reaches 80% (from below), signaling strong bullish conditions. Another alert triggers when allocation falls to 20%, indicating defensive positioning.
These thresholds are not arbitrary but correspond with boundaries between model regimes. An allocation of 80% roughly corresponds to a clear bull market regime, while 20% corresponds to a bear market regime. Alerts at these points are therefore informative about fundamental regime shifts.
11.2 Crisis Alerts
Separate alerts trigger upon detection of crisis and severe crisis. These alerts have highest priority as they signal large risks. A crisis alert should prompt investors to review their portfolio and potentially take defensive measures beyond the automatic model recommendation (e.g., hedging through put options, rebalancing to more defensive sectors).
11.3 Regime Change Alerts
An alert triggers upon change of market regime (e.g., from Neutral to Correction, or from Bull Market to Strong Bull). Regime changes are highly informative events that typically entail substantial allocation changes. These alerts enable investors to proactively respond to changes in market dynamics.
11.4 Risk Breach Alerts
A specialized alert triggers when actual portfolio risk utilization exceeds target parameters by 20%. This is a warning signal that the risk management system is reaching its limits, possibly because market volatility is rising faster than allocation can be reduced. In such situations, investors should consider manual interventions.
12. Practical Application and Limitations
12.1 Portfolio Implementation
DEAM generates a recommendation for allocation between equities (S&P 500) and cash. Implementation by an investor can take various forms. The most direct method is using an S&P 500 ETF (e.g., SPY, VOO) for equity allocation and a money market fund or savings account for cash allocation.
A rebalancing strategy is required to synchronize actual allocation with model recommendation. Two approaches are possible: (1) rule-based rebalancing at every 10% deviation between actual and target, or (2) time-based monthly rebalancing. Both have trade-offs between responsiveness and transaction costs. Empirical evidence (Jaconetti, Kinniry, and Zilbering, 2010) suggests rebalancing frequency has moderate impact on performance, and investors should optimize based on their transaction costs.
12.2 Adaptation to Individual Preferences
The model offers numerous adjustment parameters. Component weights can be modified if investors place more or less belief in certain factors. A fundamentally-oriented investor might increase valuation weight, while a technical trader might increase regime weight.
Risk target parameters (target volatility, max drawdown) should be adapted to individual risk tolerance. Younger investors with long investment horizons can choose higher target volatility (15-18%), while retirees may prefer lower volatility (8-10%). This adjustment systematically shifts average equity allocation.
Crisis thresholds can be adjusted based on preference for sensitivity versus specificity of crisis detection. Lower thresholds (e.g., VIX > 35 instead of 40) increase sensitivity (more crises are detected) but reduce specificity (more false alarms). Higher thresholds have the reverse effect.
12.3 Limitations and Disclaimers
DEAM is based on historical relationships between indicators and market performance. There is no guarantee these relationships will persist in the future. Structural changes in markets (e.g., through regulation, technology, or central bank policy) can break established patterns. This is the fundamental problem of induction in financial science (Taleb, 2007).
The model is optimized for US equities (S&P 500). Application to other markets (international stocks, bonds, commodities) would require recalibration. The indicators and thresholds are specific to the statistical properties of the US equity market.
The model cannot eliminate losses. Even with perfect crisis prediction, an investor following the model would lose money in bear markets—just less than a buy-and-hold investor. The goal is risk-adjusted performance improvement, not risk elimination.
Transaction costs are not modeled. In practice, spreads, commissions, and taxes reduce net returns. Frequent trading can cause substantial costs. Model smoothing helps minimize this, but users should consider their specific cost situation.
The model reacts to information; it does not anticipate it. During sudden shocks (e.g., 9/11, COVID-19 lockdowns), the model can only react after price movements, not before. This limitation is inherent to all reactive systems.
12.4 Relationship to Other Strategies
DEAM is a tactical asset allocation approach and should be viewed as a complement, not replacement, for strategic asset allocation. Brinson, Hood, and Beebower (1986) showed in their influential study "Determinants of Portfolio Performance" that strategic asset allocation (long-term policy allocation) explains the majority of portfolio performance, but this leaves room for tactical adjustments based on market timing.
The model can be combined with value and momentum strategies at the individual stock level. While DEAM controls overall market exposure, within-equity decisions can be optimized through stock-picking models. This separation between strategic (market exposure) and tactical (stock selection) levels follows classical portfolio theory.
The model does not replace diversification across asset classes. A complete portfolio should also include bonds, international stocks, real estate, and alternative investments. DEAM addresses only the US equity allocation decision within a broader portfolio.
13. Scientific Foundation and Evaluation
13.1 Theoretical Consistency
DEAM's components are based on established financial theory and empirical evidence. The market regime component follows from regime-switching models (Hamilton, 1989) and trend-following literature. The risk management component implements volatility targeting (Moreira and Muir, 2017) and modern portfolio theory (Markowitz, 1952). The valuation component is based on discounted cash flow theory and empirical value research (Campbell and Shiller, 1988; Fama and French, 1992). The sentiment component integrates behavioral finance (Baker and Wurgler, 2006). The macro component uses established business cycle indicators (Estrella and Mishkin, 1998).
This theoretical grounding distinguishes DEAM from purely data-mining-based approaches that identify patterns without causal theory. Theory-guided models have greater probability of functioning out-of-sample, as they are based on fundamental mechanisms, not random correlations (Lo and MacKinlay, 1990).
13.2 Empirical Validation
While this document does not present detailed backtest analysis, it should be noted that rigorous validation of a tactical asset allocation model should include several elements:
In-sample testing establishes whether the model functions at all in the data on which it was calibrated. Out-of-sample testing is crucial: the model should be tested in time periods not used for development. Walk-forward analysis, where the model is successively trained on rolling windows and tested in the next window, approximates real implementation.
Performance metrics should be risk-adjusted. Pure return consideration is misleading, as higher returns often only compensate for higher risk. Sharpe Ratio, Sortino Ratio, Calmar Ratio, and Maximum Drawdown are relevant metrics. Comparison with benchmarks (Buy-and-Hold S&P 500, 60/40 Stock/Bond portfolio) contextualizes performance.
Robustness checks test sensitivity to parameter variation. If the model only functions at specific parameter settings, this indicates overfitting. Robust models show consistent performance over a range of plausible parameters.
13.3 Comparison with Existing Literature
DEAM fits into the broader literature on tactical asset allocation. Faber (2007) presented a simple momentum-based timing system that goes long when the market is above its 10-month average, otherwise cash. This simple system avoided large drawdowns in bear markets. DEAM can be understood as a sophistication of this approach that integrates multiple information sources.
Ilmanen (2011) discusses various timing factors in "Expected Returns" and argues for multi-factor approaches. DEAM operationalizes this philosophy. Asness, Moskowitz, and Pedersen (2013) showed that value and momentum effects work across asset classes, justifying cross-asset application of regime and valuation signals.
Ang (2014) emphasizes in "Asset Management: A Systematic Approach to Factor Investing" the importance of systematic, rule-based approaches over discretionary decisions. DEAM is fully systematic and eliminates emotional biases that plague individual investors (overconfidence, hindsight bias, loss aversion).
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Extreme Pressure Zones Indicator (EPZ) [BullByte]Extreme Pressure Zones Indicator(EPZ)
The Extreme Pressure Zones (EPZ) Indicator is a proprietary market analysis tool designed to highlight potential overbought and oversold "pressure zones" in any financial chart. It does this by combining several unique measurements of price action and volume into a single, bounded oscillator (0–100). Unlike simple momentum or volatility indicators, EPZ captures multiple facets of market pressure: price rejection, trend momentum, supply/demand imbalance, and institutional (smart money) flow. This is not a random mashup of generic indicators; each component was chosen and weighted to reveal extreme market conditions that often precede reversals or strong continuations.
What it is?
EPZ estimates buying/selling pressure and highlights potential extreme zones with a single, bounded 0–100 oscillator built from four normalized components. Context-aware weighting adapts to volatility, trendiness, and relative volume. Visual tools include adaptive thresholds, confirmed-on-close extremes, divergence, an MTF dashboard, and optional gradient candles.
Purpose and originality (not a mashup)
Purpose: Identify when pressure is building or reaching potential extremes while filtering noise across regimes and symbols.
Originality: EPZ integrates price rejection, momentum cascade, pressure distribution, and smart money flow into one bounded scale with context-aware weighting. It is not a cosmetic mashup of public indicators.
Why a trader might use EPZ
EPZ provides a multi-dimensional gauge of market extremes that standalone indicators may miss. Traders might use it to:
Spot Reversals: When EPZ enters an "Extreme High" zone (high red), it implies selling pressure might soon dominate. This can hint at a topside reversal or at least a pause in rallies. Conversely, "Extreme Low" (green) can highlight bottom-fish opportunities. The indicator's divergence module (optional) also finds hidden bullish/bearish divergences between price and EPZ, a clue that price momentum is weakening.
Measure Momentum Shifts: Because EPZ blends momentum and volume, it reacts faster than many single metrics. A rising MPO indicates building bullish pressure, while a falling MPO shows increasing bearish pressure. Traders can use this like a refined RSI: above 50 means bullish bias, below 50 means bearish bias, but with context provided by the thresholds.
Filter Trades: In trend-following systems, one could require EPZ to be in the bullish (green) zone before taking longs, or avoid new trades when EPZ is extreme. In mean-reversion systems, one might specifically look to fade extremes flagged by EPZ.
Multi-Timeframe Confirmation: The dashboard can fetch a higher timeframe EPZ value. For example, you might trade a 15-minute chart only when the 60-minute EPZ agrees on pressure direction.
Components and how they're combined
Rejection (PRV) – Captures price rejection based on candle wicks and volume (see Price Rejection Volume).
Momentum Cascade (MCD) – Blends multiple momentum periods (3,5,8,13) into a normalized momentum score.
Pressure Distribution (PDI) – Measures net buy/sell pressure by comparing volume on up vs down candles.
Smart Money Flow (SMF) – An adaptation of money flow index that emphasizes unusual volume spikes.
Each of these components produces a 0–100 value (higher means more bullish pressure). They are then weighted and averaged into the final Market Pressure Oscillator (MPO), which is smoothed and scaled. By combining these four views, EPZ stands out as a comprehensive pressure gauge – the whole is greater than the sum of parts
Context-aware weighting:
Higher volatility → more PRV weight
Trendiness up (RSI of ATR > 25) → more MCD weight
Relative volume > 1.2x → more PDI weight
SMF holds a stable weight
The weighted average is smoothed and scaled into MPO ∈ with 50 as the neutral midline.
What makes EPZ stand out
Four orthogonal inputs (price action, momentum, pressure, flow) unified in a single bounded oscillator with consistent thresholds.
Adaptive thresholds (optional) plus robust extreme detection that also triggers on crossovers, so static thresholds work reliably too.
Confirm Extremes on Bar Close (default ON): dots/arrows/labels/alerts print on closed bars to avoid repaint confusion.
Clean dashboard, divergence tools, pre-alerts, and optional on-price gradients. Visual 3D layering uses offsets for depth only,no lookahead.
Recommended markets and timeframes
Best: liquid symbols (index futures, large-cap equities, major FX, BTC/ETH).
Timeframes: 5–15m (more signals; consider higher thresholds), 1H–4H (balanced), 1D (clear regimes).
Use caution on illiquid or very low TFs where wick/volume geometry is erratic.
Logic and thresholds
MPO ∈ ; 50 = neutral. Above 50 = bullish pressure; below 50 = bearish.
Static thresholds (defaults): thrHigh = 70, thrLow = 30; warning bands 5 pts inside extremes (65/35).
Adaptive thresholds (optional):
thrHigh = min(BaseHigh + 5, mean(MPO,100) + stdev(MPO,100) × ExtremeSensitivity)
thrLow = max(BaseLow − 5, mean(MPO,100) − stdev(MPO,100) × ExtremeSensitivity)
Extreme detection
High: MPO ≥ thrHigh with peak/slope or crossover filter.
Low: MPO ≤ thrLow with trough/slope or crossover filter.
Cooldown: 5 bars (default). A new extreme will not print until the cooldown elapses, even if MPO re-enters the zone.
Confirmation
"Confirm Extremes on Bar Close" (default ON) gates extreme markers, pre-alerts, and alerts to closed bars (non-repainting).
Divergences
Pivot-based bullish/bearish divergence; tags appear only after left/right bars elapse (lookbackPivot).
MTF
HTF MPO retrieved with lookahead_off; values can update intrabar and finalize at HTF close. This is disclosed and expected.
Inputs and defaults (key ones)
Core: Sensitivity=1.0; Analysis Period=14; Smoothing=3; Adaptive Thresholds=OFF.
Extremes: Base High=70, Base Low=30; Extreme Sensitivity=1.5; Confirm Extremes on Bar Close=ON; Cooldown=5; Dot size Small/Tiny.
Visuals: Heatmap ON; 3D depth optional; Strength bars ON; Pre-alerts OFF; Divergences ON with tags ON; Gradient candles OFF; Glow ON.
Dashboard: ON; Position=Top Right; Size=Normal; MTF ON; HTF=60m; compact overlay table on price chart.
Advanced caps: Max Oscillator Labels=80; Max Extreme Guide Lines=80; Divergence objects=60.
Dashboard: what each element means
Header: EPZ ANALYSIS.
Large readout: Current MPO; color reflects state (extreme, approaching, or neutral).
Status badge: "Extreme High/Low", "Approaching High/Low", "Bullish/Neutral/Bearish".
HTF cell (when MTF ON): Higher-timeframe MPO, color-coded vs extremes; updates intrabar, settles at HTF close.
Predicted (when MTF OFF): Simple MPO extrapolation using momentum/acceleration—illustrative only.
Thresholds: Current thrHigh/thrLow (static or adaptive).
Components: ASCII bars + values for PRV, MCD, PDI, SMF.
Market metrics: Volume Ratio (x) and ATR% of price.
Strength: Bar indicator of |MPO − 50| × 2.
Confidence: Heuristic gauge (100 in extremes, 70 in warnings, 50 with divergence, else |MPO − 50|). Convenience only, not probability.
How to read the oscillator
MPO Value (0–100): A reading of 50 is neutral. Values above ~55 are increasingly bullish (green), while below ~45 are increasingly bearish (red). Think of these as "market pressure".
Extreme Zones: When MPO climbs into the bright orange/red area (above the base-high line, default 70), the chart will display a dot and downward arrow marking that extreme. Traders often treat this as a sign to tighten stops or look for shorts. Similarly, a bright green dot/up-arrow appears when MPO falls below the base-low (30), hinting at a bullish setup.
Heatmap/Candles: If "Pressure Heatmap" is enabled, the background of the oscillator pane will fade green or red depending on MPO. Users can optionally color the price candles by MPO value (gradient candles) to see these extremes on the main chart.
Prediction Zone(optional): A dashed projection line extends the MPO forward by a small number of bars (prediction_bars) using current MPO momentum and acceleration. This is a heuristic extrapolation best used for short horizons (1–5 bars) to anticipate whether MPO may touch a warning or extreme zone. It is provisional and becomes less reliable with longer projection lengths — always confirm predicted moves with bar-close MPO and HTF context before acting.
Divergences: When price makes a higher high but EPZ makes a lower high (bearish divergence), the indicator can draw dotted lines and a "Bear Div" tag. The opposite (lower low price, higher EPZ) gives "Bull Div". These signals confirm waning momentum at extremes.
Zones: Warning bands near extremes; Extreme zones beyond thresholds.
Crossovers: MPO rising through 35 suggests easing downside pressure; falling through 65 suggests waning upside pressure.
Dots/arrows: Extreme markers appear on closed bars when confirmation is ON and respect the 5-bar cooldown.
Pre-alert dots (optional): Proximity cues in warning zones; also gated to bar close when confirmation is ON.
Histogram: Distance from neutral (50); highlights strengthening or weakening pressure.
Divergence tags: "Bear Div" = higher price high with lower MPO high; "Bull Div" = lower price low with higher MPO low.
Pressure Heatmap : Layered gradient background that visually highlights pressure strength across the MPO scale; adjustable intensity and optional zone overlays (warning / extreme) for quick visual scanning.
A typical reading: If the oscillator is rising from neutral towards the high zone (green→orange→red), the chart may see strong buying culminating in a stall. If it then turns down from the extreme, that peak EPZ dot signals sell pressure.
Alerts
EPZ: Extreme Context — fires on confirmed extremes (respects cooldown).
EPZ: Approaching Threshold — fires in warning zones if no extreme.
EPZ: Divergence — fires on confirmed pivot divergences.
Tip: Set alerts to "Once per bar close" to align with confirmation and avoid intrabar repaint.
Practical usage ideas
Trend continuation: In positive regimes (MPO > 50 and rising), pullbacks holding above 50 often precede continuation; mirror for bearish regimes.
Exhaustion caution: E High/E Low can mark exhaustion risk; many wait for MPO rollover or divergence to time fades or partial exits.
Adaptive thresholds: Useful on assets with shifting volatility regimes to maintain meaningful "extreme" levels.
MTF alignment: Prefer setups that agree with the HTF MPO to reduce countertrend noise.
Examples
Screenshots captured in TradingView Replay to freeze the bar at close so values don't fluctuate intrabar. These examples use default settings and are reproducible on the same bars; they are for illustration, not cherry-picking or performance claims.
Example 1 — BTCUSDT, 1h — E Low
MPO closed at 26.6 (below the 30 extreme), printing a confirmed E Low. HTF MPO is 26.6, so higher-timeframe pressure remains bearish. Components are subdued (Momentum/Pressure/Smart$ ≈ 29–37), with Vol Ratio ≈ 1.19x and ATR% ≈ 0.37%. A prior Bear Div flagged weakening impulse into the drop. With cooldown set to 5 bars, new extremes are rate-limited. Many traders wait for MPO to curl up and reclaim 35 or for a fresh Bull Div before considering countertrend ideas; if MPO cannot reclaim 35 and HTF stays weak, treat bounces cautiously. Educational illustration only.
Example 2 — ETHUSD, 30m — E High
A strong impulse pushed MPO into the extreme zone (≥ 70), printing a confirmed E High on close. Shortly after, MPO cooled to ~61.5 while a Bear Div appeared, showing momentum lag as price pushed a higher high. Volume and volatility were elevated (≈ 1.79x / 1.25%). With a 5-bar cooldown, additional extremes won't print immediately. Some treat E High as exhaustion risk—either waiting for MPO rollover under 65/50 to fade, or for a pullback that holds above 50 to re-join the trend if higher-timeframe pressure remains constructive. Educational illustration only.
Known limitations and caveats
The MPO line itself can change intrabar; extreme markers/alerts do not repaint when "Confirm Extremes on Bar Close" is ON.
HTF values settle at the close of the HTF bar.
Illiquid symbols or very low TFs can be noisy; consider higher thresholds or longer smoothing.
Prediction line (when enabled) is a visual extrapolation only.
For coders
Pine v6. MTF via request.security with lookahead_off.
Extremes include crossover triggers so static thresholds also yield E High/E Low.
Extreme markers and pre-alerts are gated by barstate.isconfirmed when confirmation is ON.
Arrays prune oldest objects to respect resource limits; defaults (80/80/60) are conservative for low TFs.
3D layering uses negative offsets purely for drawing depth (no lookahead).
Screenshot methodology:
To make labels legible and to demonstrate non-repainting behavior, the examples were captured in TradingView Replay with "Confirm Extremes on Bar Close" enabled. Replay is used only to freeze the bar at close so plots don't change intrabar. The examples use default settings, include both Extreme Low and Extreme High cases, and can be reproduced by scrolling to the same bars outside Replay. This is an educational illustration, not a performance claim.
Disclaimer
This script is for educational purposes only and does not constitute financial advice. Markets involve risk; past behavior does not guarantee future results. You are responsible for your own testing, risk management, and decisions.
