Range Percentage Analyzer This indicator is a tool for analyzing the market range and trend. It calculates the extent of price movement between a specified starting point and the current price, displaying it as a percentage.
The calculation can be based on a fixed lookback period (e.g., the last 30 candles) or from a fixed start date. It also provides a clear table that shows the general trend in "Trend" mode, and the relative strength of the base and quote currencies of forex pairs (e.g., EURUSD) in "Forex" mode.
User Guide
Calculation Method
This setting determines how the indicator defines the starting point for the calculation.
Lookback Period: In this mode, the indicator uses the last N candles (the number can be specified in the "Lookback Period (bars)" field, maximum 250).
The starting point is "floating," meaning it shifts with each new candle. For example, with a setting of 30, the 30th candle from the current one will always be the starting point.
Date Based: In this mode, the calculation starts from a fixed date and time you select.
This mode is ideal for measuring performance from a specific event (e.g., news, start of a week/month).
Note: If you select a date in "Date Based" mode for which no data is available on the current timeframe (e.g., switching to a very low timeframe), the indicator will automatically use the earliest available candle as the starting point.
Start Date & Time
This setting is only active in "Date Based" mode.
Here you can specify the fixed starting point for the calculation.
The specified time is in the Exchange timezone.
Important limitation: Due to TradingView platform limits, visual elements (box, line) are only drawn for a maximum of 250 candles back.
If the set date is older than this, the calculation still applies to the entire period (from the set date), but the drawing only covers the last 250 candles.
When switching to a higher timeframe, the range may restart from a slightly later bar due to TradingView's bar alignment. For best accuracy, set your timeframe first, then select the start date.
Table Mode
This setting controls what data the information table displays.
Trend: This is the default mode, which works on any symbol (stock, index, crypto, etc.). It displays information related to the trend.
Forex: This is a special mode used to measure the strength of currency pairs.
It only works on symbols with exactly 6 characters (e.g., "EURUSD", "BTCUSD"). It treats the first 3 characters as the base currency (e.g., EUR) and the last 3 as the quote currency (e.g., USD).
If the symbol does not have 6 characters, the table will automatically display in "Trend" mode.
Extremes Trend Row
If this is enabled, the table displays an additional row that determines the trend based on the formation order of the high and low within the analyzed range.
The logic is as follows:
Bullish: Indicated if the low was formed before the high.
(Or if they formed on the same candle, which was a bullish candle).
Bearish: Indicated if the high was formed before the low.
(Or if they formed on the same candle, which was a bearish candle).
Neutral: Indicated if the high and low formed on the same candle, and it was a "doji" candle (close = open).
Upper & Lower Threshold
These settings control the logic for the "Change Trend" and "Forex Display" rows at the top of the table.
They determine when the total percentage change for the entire period is considered "Bullish/Strong", "Bearish/Weak", or "Neutral".
Upper Threshold (%): The percentage value (default 0.1%) above which the indicator considers the change "Bullish/Strong".
Lower Threshold (%): The percentage value (default -0.1%) below which the indicator considers the change "Bearish/Weak".
If the change is between the two, the signal is Neutral.
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Island Reversal [LuxAlgo]The Island Reversal tool allows traders to identify reversal patterns directly on the chart. These patterns signal a potential change in trend, either from bullish to bearish or vice versa.
The tool enables traders to filter these patterns by trend, volume, and range, making it easy to display pure or less constrained island reversals.
🔶 USAGE
An island reversal pattern may indicate a change in trend. It occurs when prices change direction from an uptrend to a downtrend, or vice versa.
This pattern is a great tool for timing the market. Traders should be aware of when these patterns develop and watch how prices behave after the pattern forms.
Now, let's take a closer look at one of these island reversal patterns to highlight its different components.
The different parts are depicted in the image above.
1. A trend prior to the pattern
2. A gap starts the pattern.
3. A range of prices
4. A final gap, opposite to the first one, closes the pattern.
5. In this case, the pattern leads to a bearish trend, which is opposite to the trend in the first step.
🔹 Trend, Volume and Range Filters
Enabling the trend filter causes the tool to only detect top island reversals during a bullish trend and bottom island reversals during a bearish trend.
Traders can adjust the size of the detected trend in the settings panel. The larger the trend size, the more relevant the reversal patterns can be.
The volume filter only detects reversal patterns if there is more volume within the range of the pattern than in the preceding trend.
The idea is that more people tend to participate at the top and bottom of a trend as it changes direction.
The tool has two range filters that discriminate the range within the island reversal pattern:
Horizontality Filter (R2): Based on the R-squared statistic from linear regression, it detects whether the price is moving sideways within the range.
Volatility Filter: Based on long-term volatility, it detects the size of the range within the pattern.
The smaller the value in the Horizontality Filter, the more horizontal the prices will be within the range. A larger value will detect more reversal patterns.
The larger the value in the Volatility Filter, the larger the ranges will be. A smaller value will detect fewer reversal patterns.
🔶 SETTINGS
🔹 Trend Filter
Trend Filter: Enable or disable the trend filter.
Trend Length: Select the size of the detected trend.
🔹 Volume Filter
Volume Filter: Enable or disable the volume filter.
🔹 Range Filter
Horizontality Filter (R2): Enable or disable the Horizontality filter and select a threshold value.
Volatility Filter: Enable or disable the Volatility filter and select the multiplier value.
🔹 Style
Bullish: Select a color for bullish sessions.
Bearish: Select a color for bearish sessions.
Transparency: Select a transparency level from 100 to 0.
Smart Trend MASmart Trend MA - Adaptive Moving Average with VHF Technology
WHAT IT IS
Smart Trend MA is an adaptive moving average indicator based on Perry Kaufman's KAMA (Kaufman Adaptive Moving Average) algorithm enhanced with VHF (Vertical Horizontal Filter) technology. The indicator automatically adjusts its responsiveness to current market conditions, becoming faster during trending markets and slower during ranging conditions to reduce false signals.
ORIGINALITY AND VALUE
This implementation combines KAMA's efficiency ratio methodology with dynamic VHF period adaptation, creating an intelligent system that self-adjusts without manual intervention. Unlike standard moving averages with fixed periods, Smart Trend MA dynamically calculates optimal sensitivity based on market structure. The gradient color visualization system provides immediate trend strength feedback. This indicator adds value by reducing whipsaw trades in choppy markets while maintaining responsiveness during genuine trends.
HOW IT WORKS
The indicator employs Kaufman's efficiency ratio calculation to measure directional movement relative to volatility. When markets trend strongly, the efficiency ratio increases and the moving average responds quickly to price changes. During sideways or choppy markets, the efficiency ratio decreases and the moving average becomes smoother to filter noise.
The VHF adaptation layer adds a second dimension of intelligence by dynamically adjusting the calculation period based on vertical price movement relative to horizontal price range. This dual-adaptive approach creates a moving average that automatically optimizes itself for current conditions without requiring parameter changes.
The gradient color system uses slope calculation to display trend strength visually. Stronger trends display more saturated colors while weaker or consolidating markets show muted tones.
FEATURES
- KAMA algorithm with efficiency ratio calculation
- VHF adaptive period adjustment for enhanced responsiveness
- Gradient color visualization with 7 color scheme options
- Range detection line showing mid-range support and resistance levels
- Multi-timeframe compatible across all markets
- No repainting - calculations use confirmed bar data
- Native TradingView alert system with 6 alert conditions
SETTINGS AND PARAMETERS
Length: Base calculation period (default 21). Higher values produce smoother lines suitable for position trading. Lower values (9-12) increase sensitivity for shorter timeframes.
Fast Factor: Controls maximum responsiveness during strong trends (default 0.66). Higher values increase reaction speed but may produce more noise.
Slow Factor: Controls minimum responsiveness during ranging markets (default 0.0645). Lower values create more smoothing during consolidation.
Smoothing Method: Optional additional smoothing using Hann Window or T3 methods. Default "None" recommended for most applications.
Enable VHF Adaptiveness: Activates dynamic period adjustment based on market structure. Recommended to keep enabled.
Range Detection: Displays mid-range line calculated from recent highs and lows. Useful for identifying support and resistance zones.
Gradient Colors: Choose from 7 color schemes or disable for simple two-color trend indication.
USAGE INSTRUCTIONS
The indicator plots a single adaptive line on the price chart. When the line slopes upward, market conditions favor bullish positions. When the line slopes downward, market conditions favor bearish positions. The gradient color intensity indicates trend strength - more saturated colors signal stronger directional movement.
The range detection line identifies the midpoint between recent price extremes. Price above the range line suggests bullish bias while price below suggests bearish bias. This line often acts as dynamic support or resistance.
For best results, combine Smart Trend MA with volume analysis and price action confirmation. The indicator works across all timeframes and markets including forex, cryptocurrency, stocks, and indices.
ALERT CONDITIONS
The indicator provides six native alert conditions through TradingView's alert system:
Bullish Trend: Triggers when the moving average direction changes to upward
Bearish Trend: Triggers when the moving average direction changes to downward
Strong Bullish: Triggers when slope exceeds threshold indicating strong upward momentum
Strong Bearish: Triggers when slope exceeds threshold indicating strong downward momentum
Price Cross Above: Triggers when price crosses above the moving average
Price Cross Below: Triggers when price crosses below the moving average
TECHNICAL NOTES
This indicator uses lookahead_off to ensure calculations reflect only confirmed bar data, preventing repainting issues. The default 21-period setting represents a Fibonacci number statistically proven optimal for swing trading across multiple markets.
LIMITATIONS
Past performance does not guarantee future results. This indicator provides trend analysis based on historical price data and does not predict future price movement. Best results occur in markets with clear directional bias. During extreme volatility or news events, all technical indicators including adaptive moving averages may produce less reliable signals.
No indicator should be used as the sole basis for trading decisions. Combine Smart Trend MA with proper risk management, additional analysis methods, and thorough understanding of the markets you trade.
VIX Regime AnalyzerVIX Regime Analyzer
The VIX Regime Analyzer is an analytical tool that examines historical VIX patterns to provide insights into how your asset typically performs under similar volatility conditions.
Key Features:
Historical Pattern Matching: Automatically scans up to 1,000 bars of history to find all periods when VIX was at levels similar to today, using customizable tolerance ranges (absolute or percentage-based).
Forward-Looking Statistics: For each VIX regime match, calculates what actually happened to your asset over the next 1, 5, 10, and 20 trading days, providing both average returns and probability of positive outcomes.
Regime Classification System: Intelligently categorizes the current market environment as bullish or bearish: Visual Historical Context:
Background shading throughout your chart highlights every historical period when VIX matched current levels, color-coded by subsequent performance (green for gains, red for losses).
User Inputs:
VIX Level Tolerance (+/-): How closely VIX must match (default: ±5 points)
Use Relative Tolerance (%): Switch to percentage-based matching for consistency across different VIX levels
Lookback Period: How many bars to analyze
Highlight Historical VIX Matches: Toggle background highlighting of past matching periods
The Data Table
The statistics box appears in the right handside of your chart and contains three main sections:
Section 1: VIX REGIME
Current VIX: The live VIX closing price
Range: The tolerance band being searched (e.g., if VIX is 18 with ±5 tolerance, range is 13-23)
Historical Samples: Number of matching periods found in the lookback window (minimum 10 required for statistical validity)
Section 2: FORWARD RETURN
Shows the average percentage change in your asset over different timeframes following similar VIX levels:
Avg Next Day: What typically happened by the next trading session
Avg Next 5 Days: Average 5-day forward performance
Avg Next 10 Days: Average 10-day forward performance
Avg Next 20 Days: Average 20-day forward performance (approximately 1 month)
Section 3: PROBABILITY UP
Shows the win rate - the percentage of times your asset closed higher after VIX matched current levels:
Next Day: Probability of being up the next session
Next 5 Days: Probability of being up after 5 days
Next 10 Days: Probability of being up after 10 days
Next 20 Days: Probability of being up after 20 days
Colors:
🟢 Green: Bullish regimes (various strengths)
🔴 Red: Bearish regimes (various strengths)
🟡 Yellow: Choppy/uncertain regime
When "Highlight Historical VIX Matches" is enabled:
Scroll back through your chart and you'll see colored backgrounds highlighting every period when VIX matched today's level. The color tells you whether that match led to gains (green) or losses (red). This provides instant visual pattern recognition - you can quickly see if similar VIX levels historically led to bullish or bearish outcomes.
Practical Example:
If you see that most historical periods with similar VIX levels are highlighted in green, it suggests the current VIX level has historically been a bullish signal for your asset.
How The Indicator Makes Decisions
The regime classification uses both magnitude AND probability to avoid false signals:
Example of Strong Classification:
Average 5-day return: +1.5%
Win rate: 65%
Result: STRONG BULLISH (both high return and high probability)
Example of Weak Signal:
Average 5-day return: +2.0%
Win rate: 35%
Result: CHOPPY (high average but low consistency = unreliable)
This dual-factor approach ensures the indicator doesn't mislead you with regimes that had a few huge winners but mostly losers, or vice versa.
Best Practices
Combine with your existing strategy: Use this as a regime filter rather than standalone signals
Check sample size: More historical matches = more reliable statistics
Consider multiple timeframes: If 5-day and 20-day metrics disagree, proceed with caution
Asset-specific tuning: Different assets may require different tolerance settings
VIX spikes: The indicator is particularly useful during VIX spikes to understand if panic is justified
What Makes This Different
Unlike simple VIX indicators that just plot the fear index, this tool:
Quantifies the actual impact of VIX levels on YOUR specific asset
Provides probability-based forecasts rather than subjective interpretation
Shows historical context visually so you can see patterns at a glance
Uses rigorous statistical criteria to avoid false regime classifications
Pinbar MTF - No Repaint# Pinbar MTF - No Repaint Indicator
## Complete Technical Documentation
---
## 📊 Overview
**Pinbar MTF (Multi-Timeframe) - No Repaint** is a professional-grade TradingView Pine Script indicator designed to detect high-probability pinbar reversal patterns with advanced filtering systems. The indicator is specifically engineered to be **100% non-repainting**, making it reliable for both live trading and backtesting.
### Key Features
✅ **Non-Repainting** - Signals only appear AFTER bar closes, never disappear
✅ **Three-Layer Filter System** - ATR, SWING, and RSI filters
✅ **Automatic SL/TP Calculation** - Based on risk:reward ratios
✅ **Real-time Alerts** - TradingView notifications for all signals
✅ **Visual Trade Management** - Lines, labels, and areas for entries, stops, and targets
✅ **Backtesting Ready** - Reliable historical data for strategy testing
---
## 🎯 What is a Pinbar?
A **Pinbar (Pin Bar/Pinocchio Bar)** is a single candlestick pattern that indicates a potential price reversal:
### Bullish Pinbar (BUY Signal)
- **Long lower wick** (rejection of lower prices)
- **Small body at the top** of the candle
- Shows buyers rejected sellers' attempt to push price down
- Forms at support levels or swing lows
- Entry signal for LONG positions
### Bearish Pinbar (SELL Signal)
- **Long upper wick** (rejection of higher prices)
- **Small body at the bottom** of the candle
- Shows sellers rejected buyers' attempt to push price up
- Forms at resistance levels or swing highs
- Entry signal for SHORT positions
---
## 🔧 How the Indicator Works
### 1. **Pinbar Detection Logic**
The indicator analyzes the **previous closed bar ** to identify pinbar patterns:
```
Bullish Pinbar Requirements:
- Lower wick > 72% of total candle range (adjustable)
- Upper wick < 28% of total candle range
- Close > Open (bullish candle body)
Bearish Pinbar Requirements:
- Upper wick > 72% of total candle range (adjustable)
- Lower wick < 28% of total candle range
- Close < Open (bearish candle body)
```
**Why check ?** By analyzing the previous completed bar, we ensure the pattern is fully formed and won't change, preventing repainting.
---
### 2. **Three-Layer Filter System**
#### 🔍 **Filter #1: ATR (Average True Range) Filter**
- **Purpose**: Ensures the pinbar has significant size
- **Function**: Only signals if pinbar range ≥ ATR value
- **Benefit**: Filters out small, insignificant pinbars
- **Settings**:
- Enable/Disable toggle
- ATR Period (default: 7)
**Example**: If ATR = 50 pips, only pinbars with 50+ pip range will signal.
---
#### 🔍 **Filter #2: SWING Filter** (Always Active)
- **Purpose**: Confirms pinbar forms at swing highs/lows
- **Function**: Validates the pinbar is an absolute high/low
- **Benefit**: Identifies true reversal points
- **Settings**:
- Swing Candles (default: 3)
**How it works**:
- For bullish pinbar: Checks if low is lowest of past 3 bars
- For bearish pinbar: Checks if high is highest of past 3 bars
**Example**: With 3 swing candles, a bullish pinbar must have the lowest low among the last 3 bars.
---
#### 🔍 **Filter #3: RSI (Relative Strength Index) Filter**
- **Purpose**: Confirms momentum conditions
- **Function**: Prevents signals in extreme momentum zones
- **Benefit**: Avoids counter-trend trades
- **Settings**:
- Enable/Disable toggle
- RSI Period (default: 7)
- RSI Source (Close, Open, High, Low, HL2, HLC3, OHLC4)
- Overbought Level (default: 70)
- Oversold Level (default: 30)
**Logic**:
- Bullish Pinbar: Only signals if RSI < 70 (not overbought)
- Bearish Pinbar: Only signals if RSI > 30 (not oversold)
---
### 3. **Stop Loss Calculation**
Two methods available:
#### Method A: ATR-Based Stop Loss (Recommended)
```
Bullish Pinbar:
SL = Pinbar Low - (1 × ATR)
Bearish Pinbar:
SL = Pinbar High + (1 × ATR)
```
**Benefit**: Dynamic stops that adapt to market volatility
#### Method B: Fixed Pips Stop Loss
```
Bullish Pinbar:
SL = Pinbar Low - (Fixed Pips)
Bearish Pinbar:
SL = Pinbar High + (Fixed Pips)
```
**Settings**:
- Calculate Stop with ATR (toggle)
- Stop Pips without ATR (default: 5)
---
### 4. **Take Profit Calculation**
Take Profit is calculated based on Risk:Reward ratio:
```
Bullish Trade:
TP = Entry + (Entry - SL) × Risk:Reward Ratio
Bearish Trade:
TP = Entry - (SL - Entry) × Risk:Reward Ratio
```
**Example**:
- Entry: 1.2000
- SL: 1.1950 (50 pip risk)
- RR: 2:1
- TP: 1.2100 (100 pip reward = 50 × 2)
**Settings**:
- Risk:Reward Ratio (default: 1.0, range: 0.1 to 10.0)
---
## 📈 Visual Elements
### On-Chart Displays
1. **Signal Markers**
- 🟢 **Green Triangle Up** = Bullish Pinbar (BUY)
- 🔴 **Red Triangle Down** = Bearish Pinbar (SELL)
- Placed directly on the pinbar candle
2. **Entry Labels**
- Green "BUY" label with entry price
- Red "SELL" label with entry price
- Shows exact entry level
3. **Stop Loss Lines**
- 🔴 Red horizontal line
- "SL" label
- Extends 20 bars forward
4. **Take Profit Lines**
- 🟢 Green horizontal line
- "TP" label
- Extends 20 bars forward
5. **Risk/Reward Areas** (Optional)
- Red shaded box = Risk zone (Entry to SL)
- Green shaded box = Reward zone (Entry to TP)
- Visual risk:reward visualization
6. **Info Table** (Top Right)
- Displays current settings
- Shows filter status (ON/OFF)
- Real-time RSI value
- Quick reference panel
---
## 🔔 Alert System
Three alert types available:
### 1. Combined Alert: "Pinbar Signal (Any Direction)"
- Fires for BOTH bullish and bearish pinbars
- **Best for**: General monitoring
- **Message**: "Pinbar Signal Detected on {TICKER} at {PRICE}"
### 2. Bullish Alert: "Bullish Pinbar Alert"
- Fires ONLY for BUY signals
- **Best for**: Long-only strategies
- **Message**: "BUY Signal on {TICKER} at {PRICE}"
### 3. Bearish Alert: "Bearish Pinbar Alert"
- Fires ONLY for SELL signals
- **Best for**: Short-only strategies
- **Message**: "SELL Signal on {TICKER} at {PRICE}"
---
## ⚙️ Input Parameters Reference
### **Filters Group**
| Parameter | Default | Range | Description |
|-----------|---------|-------|-------------|
| ATR Filter on Pinbar Range? | ✅ ON | Boolean | Enable/disable ATR filter |
| ATR Period | 7 | 1+ | Lookback period for ATR calculation |
| Swing Candles | 3 | 1+ | Bars to check for swing high/low |
| RSI Filter on Pinbar? | ❌ OFF | Boolean | Enable/disable RSI filter |
| RSI Period | 7 | 2+ | Lookback period for RSI calculation |
| RSI Source | Close | Multiple | Price data for RSI (Close/Open/High/Low/etc) |
| RSI Overbought Level | 70 | 50-100 | Upper threshold for RSI filter |
| RSI Oversold Level | 30 | 0-50 | Lower threshold for RSI filter |
### **Pinbar Detection Group**
| Parameter | Default | Range | Description |
|-----------|---------|-------|-------------|
| Shadow % vs Body | 72 | 50-95 | Minimum wick size as % of total range |
### **Visualization Group**
| Parameter | Default | Range | Description |
|-----------|---------|-------|-------------|
| Show SL and TP Lines? | ✅ ON | Boolean | Display stop loss and take profit lines |
| Show SL and TP Area? | ❌ OFF | Boolean | Show shaded risk/reward boxes |
### **Risk Management Group**
| Parameter | Default | Range | Description |
|-----------|---------|-------|-------------|
| Risk:Reward Ratio | 1.0 | 0.1-10.0 | Target profit vs risk (1.0 = 1:1, 2.0 = 1:2) |
| Calculate Stop with ATR? | ✅ ON | Boolean | Use ATR for stop calculation |
| Stop Pips without ATR | 5 | 1+ | Fixed pip stop when ATR disabled |
---
## 🚫 Non-Repainting Architecture
### What is Repainting?
**Repainting** occurs when an indicator's historical signals differ from what appeared in real-time. This makes backtesting unreliable and can lead to false confidence in a strategy.
### How This Indicator Prevents Repainting
1. **Closed Bar Analysis**
- All calculations use ` ` offset (previous bar)
- Only analyzes COMPLETED candles
- Signals appear on the bar AFTER the pinbar closes
2. **Confirmed Swing Points**
- Waits for sufficient bar history before signaling
- Only checks historical bars that cannot change
- Prevents premature swing detection
3. **Static Alert Timing**
- Alerts fire only after bar completion
- No conditional logic that changes historically
- Same results in replay mode and live trading
### Verification Method
To verify non-repainting behavior:
1. Apply indicator to chart
2. Note signal locations and prices
3. Refresh browser / reload chart
4. **Signals remain in exact same locations**
---
## 💼 Trading Strategy Guidelines
### Entry Rules
**For Bullish Pinbar (LONG):**
1. Wait for green triangle to appear
2. Enter at close of pinbar (shown in label)
3. Alternative: Enter on break of pinbar high
4. Place stop loss at red SL line
5. Set target at green TP line
**For Bearish Pinbar (SHORT):**
1. Wait for red triangle to appear
2. Enter at close of pinbar (shown in label)
3. Alternative: Enter on break of pinbar low
4. Place stop loss at red SL line
5. Set target at green TP line
### Risk Management
- **Position Sizing**: Risk only 1-2% of account per trade
- **Stop Loss**: Always use the calculated SL (never move it wider)
- **Take Profit**: Use calculated TP or trail stop after 1:1 RR
- **Multiple Timeframes**: Confirm signals on higher timeframe
### Best Practices
✅ **DO:**
- Wait for bar to close before entering
- Trade in direction of higher timeframe trend
- Use on liquid markets with clear support/resistance
- Combine with price action analysis
- Keep a trading journal
❌ **DON'T:**
- Enter before bar closes (prevents seeing full pattern)
- Trade against strong trends
- Ignore the filters (they improve win rate)
- Risk more than 2% per trade
- Trade every signal (be selective)
---
## 📊 Backtesting & Data Export
### Available Data Points
The indicator exports these values for strategy development:
| Output | Description |
|--------|-------------|
| Bullish Signal | 1 = BUY signal, 0 = No signal |
| Bearish Signal | 1 = SELL signal, 0 = No signal |
| Bull SL | Stop loss level for long trades |
| Bull TP | Take profit level for long trades |
| Bull Entry | Entry price for long trades |
| Bear SL | Stop loss level for short trades |
| Bear TP | Take profit level for short trades |
| Bear Entry | Entry price for short trades |
### How to Use in Strategy
These values can be accessed by Pine Script strategies using:
```pine
indicator_values = request.security(syminfo.tickerid, timeframe.period,
)
```
---
## 🎓 Understanding the Filters
### Why Use Multiple Filters?
Single-indicator systems often generate too many false signals. This indicator uses a **confluence approach**:
1. **Pinbar Pattern** = Price rejection detected
2. **+ SWING Filter** = Rejection at key level
3. **+ ATR Filter** = Significant move
4. **+ RSI Filter** = Favorable momentum
**Result**: Higher probability setups with better risk:reward
### Filter Optimization
**Conservative Settings** (Fewer, Higher Quality Signals):
- ATR Filter: ON
- Swing Candles: 5
- RSI Filter: ON
- Shadow %: 75%
**Aggressive Settings** (More Signals, More Noise):
- ATR Filter: OFF
- Swing Candles: 2
- RSI Filter: OFF
- Shadow %: 65%
**Balanced Settings** (Recommended):
- ATR Filter: ON
- Swing Candles: 3
- RSI Filter: OFF (or ON for trending markets)
- Shadow %: 72%
---
## 🔍 Troubleshooting
### "No Signals Appearing"
**Possible Causes:**
1. Filters are too strict
2. No pinbars forming on chart
3. Insufficient bar history
**Solutions:**
- Reduce Shadow % to 65%
- Reduce Swing Candles to 2
- Disable ATR or RSI filters temporarily
- Check that chart has enough data loaded
### "Too Many Signals"
**Solutions:**
- Enable ATR filter
- Increase Swing Candles to 4-5
- Enable RSI filter
- Increase Shadow % to 75-80%
### "Signals Appearing Late"
**This is normal behavior!** The indicator:
- Analyzes previous closed bar
- Signals appear on the bar AFTER the pinbar
- This is what prevents repainting
- Signal latency is 1 bar (by design)
---
## 📝 Technical Specifications
**Indicator Type:** Overlay (displays on price chart)
**Pine Script Version:** 5
**Max Labels:** 500
**Max Lines:** 500
**Repainting:** None (100% non-repainting)
**Data Window Values:** 8 exported values
**Alert Types:** 3 (Combined, Bullish, Bearish)
**Performance:**
- Lightweight script (fast execution)
- Works on all timeframes
- Compatible with all markets (Forex, Crypto, Stocks, Futures)
- No data snooping bias
---
## 🎯 Use Cases
### 1. **Swing Trading**
- Timeframe: Daily, 4H
- Filter Settings: All enabled
- Best for: Catching major reversals
### 2. **Day Trading**
- Timeframe: 15m, 1H
- Filter Settings: ATR + SWING only
- Best for: Intraday reversals
### 3. **Scalping**
- Timeframe: 5m, 15m
- Filter Settings: SWING only (aggressive)
- Best for: Quick reversals (requires experience)
### 4. **Position Trading**
- Timeframe: Weekly, Daily
- Filter Settings: All enabled + high RR (2:1 or 3:1)
- Best for: Long-term trend reversal catches
---
## 🏆 Advantages Over Other Pinbar Indicators
✅ **Guaranteed Non-Repainting** - Many pinbar indicators repaint; this one never does
✅ **Automatic SL/TP** - No manual calculation needed
✅ **Multi-Layer Filtering** - Reduces false signals significantly
✅ **Visual Trade Management** - Clear entry, stop, and target levels
✅ **Flexible Configuration** - Adaptable to any trading style
✅ **Alert System** - Never miss a setup
✅ **Backtesting Ready** - Reliable historical data
✅ **Professional Grade** - Suitable for live trading
---
## 📚 Educational Resources
### Recommended Reading on Pinbars
- "The Pin Bar Trading Strategy" by Nial Fuller
- "Price Action Trading" by Al Brooks
- TradingView Education: Price Action Patterns
### Practice Recommendations
1. Paper trade signals for 20+ trades before live trading
2. Backtest on different timeframes and markets
3. Keep detailed records of all trades
4. Analyze winning vs losing setups
5. Refine filter settings based on results
---
## ⚖️ Disclaimer
This indicator is a tool for technical analysis and does not guarantee profits. Trading involves substantial risk of loss. Past performance is not indicative of future results.
- Always use proper risk management
- Never risk more than you can afford to lose
- Consider your trading experience and objectives
- Seek independent financial advice if needed
---
## 📧 Version Information
**Current Version:** 1.0
**Last Updated:** 2024
**Compatibility:** TradingView Pine Script v5
**Status:** Production Ready
---
## 🔄 Future Enhancements (Potential)
Possible future additions:
- Multi-timeframe confirmation option
- Volume filter integration
- Customizable color schemes
- Win rate statistics display
- Partial profit taking levels
- Trailing stop functionality
---
## 📖 Quick Start Guide
### 5-Minute Setup
1. **Add to Chart**
- Open TradingView
- Go to Pine Editor
- Paste the code
- Click "Add to Chart"
2. **Configure Settings**
- Open indicator settings (gear icon)
- Start with default settings
- Enable "Show SL and TP Lines"
3. **Set Alert**
- Right-click indicator name
- Click "Add Alert"
- Select "Pinbar Signal (Any Direction)"
- Configure notification method
4. **Test**
- Scroll back on chart
- Verify signals make sense
- Check that signals don't repaint
5. **Trade** (After Practice!)
- Wait for alert
- Verify signal quality
- Enter, place SL/TP
- Manage trade
---
## 🎯 Final Thoughts
The **Pinbar MTF - No Repaint** indicator is designed for serious traders who value:
- **Reliability** over flashy signals
- **Quality** over quantity
- **Honesty** over false promises
This indicator will NOT:
- Make you rich overnight
- Win every trade
- Replace proper trading education
This indicator WILL:
- Identify high-probability reversal setups
- Save you analysis time
- Provide consistent, non-repainting signals
- Help you develop a systematic trading approach
**Success in trading comes from:**
1. Proper education (60%)
2. Risk management (30%)
3. Technical tools like this indicator (10%)
Use this tool as part of a complete trading plan, not as a standalone solution.
Launchpad & SlingshotOverview and Originality:
This indicator combines two complementary trading concepts—Launchpad (LP) and Slingshot (SS)—into a single, cohesive tool designed to identify potential trend continuations and reversals in trending markets. Launchpads provide context on overall trend alignment via stacked moving averages, acting as a filter for higher-probability setups, while Slingshot pinpoints precise entry timing during short-term pullbacks or bounces within those trends. This synergy reduces false signals by requiring both trend confirmation (LP) and momentum shift (SS), making it more robust than using either in isolation. Unlike simple merges, this script adds original enhancements such as a "curling" filter on the shortest Launchpad MA to ensure directional momentum, separate configurable MAs for bullish/bearish Slingshot thresholds, and combined LP/SS alerts for chained patterns (e.g., LP following SS). These improvements aim to enhance usability for trend-following strategies, particularly in volatile stocks or forex pairs, by providing visual labels, alerts, and multi-timeframe support without overcomplicating the core logic.
Underlying Concepts:
Launchpad (LP): Based on the idea of moving average "stacking," where shorter-period MAs align above longer ones in uptrends (bullish stack) or below in downtrends (bearish stack). This detects when price is in a strong, aligned trend phase, similar to how Guppy Multiple Moving Averages identify trend strength through ribbon compression/expansion. The script uses up to four customizable MAs (default: 8/21/50/200 EMAs of close), calculating the highest/lowest among included ones as the key crossover level. A signal triggers when the stack forms from a non-stacked state and price crosses the extreme MA, indicating potential trend acceleration.
Slingshot (SS): Draws from Scot1and's bullish pattern, which looks for price to remain below a 4-period EMA of highs for three consecutive bars (signaling a controlled pullback), then close above it (indicating rebound momentum). This script symmetrizes it for bearish cases using a separate 4-period EMA of lows, allowing detection of breakdowns after temporary bounces in downtrends. The separation of bull/bear sources is an original adaptation to better capture market structure asymmetry—highs for resistance in uptrends, lows for support in downtrends—reducing noise compared to a single-source approach.
The components work together by allowing users to spot "LP after SS" patterns: a Slingshot pullback/rebound followed by a Launchpad stack crossover, which often signals stronger continuations. This chained logic is grounded in momentum trading principles, where short-term mean reversion (SS) aligns with longer-term trend bias (LP) for improved risk-reward entries.
How It Works: The script calculates signals on each bar as follows:
Launchpad Calculations:
Build an array of included MAs (users can exclude any via inputs).
Check for stacking: For bull LP, shorter MAs > longer ones; for bear, shorter < longer.
Require a transition from non-stacked to stacked state.
Price must cross above the highest MA (bull) or below the lowest (bear).
Original filter: The shortest MA must be "curling" up (current > previous for bull) or down (current < previous for bear) to confirm recent momentum, preventing signals in counter-trend flattenings.
Slingshot Calculations:
Use separate MAs: Bull SS uses EMA of highs (default); Bear SS uses EMA of lows.
For bull SS: Close below bull MA for the prior N bars (default 3), then close above it.
For bear SS: Close above bear MA for prior N bars, then close below it.
No additional filters like volume or momentum jumps are applied, staying true to the pattern's simplicity.
Combined and Additional Signals:
"LP after SS": Triggers if LP occurs immediately after an SS, highlighting high-conviction setups.
Stack alerts: Pure stack with price above/below extremes, for trend monitoring.
All MAs can use multi-timeframe data via the timeframe input.
Alerts are set for each condition, and labels appear on the chart (configurable visibility, size, colors). Labels combine (e.g., "Bull LP & SS") if both trigger simultaneously.
How to Use It: Add the script to your chart via TradingView's indicator menu. Default settings suit daily/intraday charts for trending assets like stocks in bull markets (e.g., tech sector during rallies).
Interpretation:
Bull SS: Look for labels during uptrends; enter long on close above the blue Bull SS MA line after a 3-bar pullback. Use as a dip-buy signal.
Bear SS: In downtrends, enter short on close below the purple Bear SS MA after a 3-bar bounce.
Bull LP: Confirms trend strength; enter long on crossover if shortest MA is rising (green label).
Bear LP: Short entry on downside crossover with falling shortest MA (red label).
Prioritize "LP after SS" for layered confirmation—e.g., SS rebound leading into LP acceleration.
Monitor stack alerts for overall bias; avoid trading against the stack.
Customization:
Launchpad Group: Adjust lengths/sources/types; exclude MAs for simpler stacks (e.g., just 50/200 for long-term).
Slingshot Group: Change length (4 default), type (EMA), sources (high/low defaults), or preceding bars (3 default).
Display: Toggle labels, set timeframe (e.g., "D" for daily MAs on hourly chart), adjust offset for label positioning.
Test on historical data: Apply to strong trenders like AAPL or BTC; backtest entries with stops below recent lows.
For best results, combine with volume confirmation or broader market context—e.g., above 200-day MA for longs. This is not financial advice; always use risk management.
Manifold Singularity EngineManifold Singularity Engine: Catastrophe Theory Detection Through Multi-Dimensional Topology Analysis
The Manifold Singularity Engine applies catastrophe theory from mathematical topology to multi-dimensional price space analysis, identifying potential reversal conditions by measuring manifold curvature, topological complexity, and fractal regime states. Unlike traditional reversal indicators that rely on price pattern recognition or momentum oscillators, this system reconstructs the underlying geometric surface (manifold) that price evolves upon and detects points where this topology undergoes catastrophic folding—mathematical singularities that correspond to forced directional changes in price dynamics.
The indicator combines three analytical frameworks: phase space reconstruction that embeds price data into a multi-dimensional coordinate system, catastrophe detection that measures when this embedded manifold reaches critical curvature thresholds indicating topology breaks, and Hurst exponent calculation that classifies the current fractal regime to adaptively weight detection sensitivity. This creates a geometry-based reversal detection system with visual feedback showing topology state, manifold distortion fields, and directional probability projections.
What Makes This Approach Different
Phase Space Embedding Construction
The core analytical method reconstructs price evolution as movement through a three-dimensional coordinate system rather than analyzing price as a one-dimensional time series. The system calculates normalized embedding coordinates: X = normalize(price_velocity, window) , Y = normalize(momentum_acceleration, window) , and Z = normalize(volume_weighted_returns, window) . These coordinates create a trajectory through phase space where price movement traces a path across a geometric surface—the market manifold.
This embedding approach differs fundamentally from traditional technical analysis by treating price not as a sequential data stream but as a dynamical system evolving on a curved surface in multi-dimensional space. The trajectory's geometric properties (curvature, complexity, folding) contain information about impending directional changes that single-dimension analysis cannot capture. When this manifold undergoes rapid topological deformation, price must respond with directional change—this is the mathematical basis for catastrophe detection.
Statistical normalization using z-score transformation (subtracting mean, dividing by standard deviation over a rolling window) ensures the coordinate system remains scale-invariant across different instruments and volatility regimes, allowing identical detection logic to function on forex, crypto, stocks, or indices without recalibration.
Catastrophe Score Calculation
The catastrophe detection formula implements a composite anomaly measurement combining multiple topology metrics: Catastrophe_Score = 0.45×Curvature_Percentile + 0.25×Complexity_Ratio + 0.20×Condition_Percentile + 0.10×Gradient_Percentile . Each component measures a distinct aspect of manifold distortion:
Curvature (κ) is computed using the discrete Laplacian operator: κ = √ , which measures how sharply the manifold surface bends at the current point. High curvature values indicate the surface is folding or developing a sharp corner—geometric precursors to catastrophic topology breaks. The Laplacian measures second derivatives (rate of change of rate of change), capturing acceleration in the trajectory's path through phase space.
Topological Complexity counts sign changes in the curvature field over the embedding window, measuring how chaotically the manifold twists and oscillates. A smooth, stable surface produces low complexity; a highly contorted, unstable surface produces high complexity. This metric detects when the geometric structure becomes informationally dense with multiple local extrema, suggesting an imminent topology simplification event (catastrophe).
Condition Number measures the Jacobian matrix's sensitivity: Condition = |Trace| / |Determinant|, where the Jacobian describes how small changes in price produce changes in the embedding coordinates. High condition numbers indicate numerical instability—points where the coordinate transformation becomes ill-conditioned, suggesting the manifold mapping is approaching a singularity.
Each metric is converted to percentile rank within a rolling window, then combined using weighted sum. The percentile transformation creates adaptive thresholds that automatically adjust to each instrument's characteristic topology without manual recalibration. The resulting 0-100% catastrophe score represents the current bar's position in the distribution of historical manifold distortion—values above the threshold (default 65%) indicate statistically extreme topology states where reversals become geometrically probable.
This multi-metric ensemble approach prevents false signals from isolated anomalies: all four geometric features must simultaneously indicate distortion for a high catastrophe score, ensuring only true manifold breaks trigger detection.
Hurst Exponent Regime Classification
The Hurst exponent calculation implements rescaled range (R/S) analysis to measure the fractal dimension of price returns: H = log(R/S) / log(n) , where R is the range of cumulative deviations from mean and S is the standard deviation. The resulting value classifies market behavior into three fractal regimes:
Trending Regime (H > 0.55) : Persistent price movement where future changes are positively correlated with past changes. The manifold exhibits directional momentum with smooth topology evolution. In this regime, catastrophe signals receive 1.2× confidence multiplier because manifold breaks in trending conditions produce high-magnitude directional changes.
Mean-Reverting Regime (H < 0.45) : Anti-persistent price movement where future changes tend to oppose past changes. The manifold exhibits oscillatory topology with frequent small-scale distortions. Catastrophe signals receive 0.8× confidence multiplier because reversal significance is diminished in choppy conditions where the manifold constantly folds at minor scales.
Random Walk Regime (H ≈ 0.50) : No statistical correlation in returns. The manifold evolution is geometrically neutral with moderate topology stability. Standard 1.0× confidence multiplier applies.
This adaptive weighting system solves a critical problem in reversal detection: the same geometric catastrophe has different trading implications depending on the fractal regime. A manifold fold in a strong trend suggests a significant reversal opportunity; the same fold in mean-reversion suggests a minor oscillation. The Hurst-based regime filter ensures detection sensitivity automatically adjusts to market character without requiring trader intervention.
The implementation uses logarithmic price returns rather than raw prices to ensure
stationarity, and applies the calculation over a configurable window (default 5 bars) to balance responsiveness with statistical validity. The Hurst value is then smoothed using exponential moving average to reduce noise while maintaining regime transition detection.
Multi-Layer Confirmation Architecture
The system implements five independent confirmation filters that must simultaneously validate
before any singularity signal generates:
1. Catastrophe Threshold : The composite anomaly score must exceed the configured threshold (default 0.65 on 0-1 scale), ensuring the manifold distortion is statistically extreme relative to recent history.
2. Pivot Structure Confirmation : Traditional swing high/low patterns (using ta.pivothigh and ta.pivotlow with configurable lookback) must form at the catastrophe bar. This ensures the geometric singularity coincides with observable price structure rather than occurring mid-swing where interpretation is ambiguous.
3. Swing Size Validation : The pivot magnitude must exceed a minimum threshold measured in ATR units (default 1.5× Average True Range). This filter prevents signals on insignificant price jiggles that lack meaningful reversal potential, ensuring only substantial swings with adequate risk/reward ratios generate signals.
4. Volume Confirmation : Current volume must exceed 1.3× the 20-period moving average, confirming genuine market participation rather than low-liquidity price noise. Manifold catastrophes without volume support often represent false topology breaks that don't translate to sustained directional change.
5. Regime Validity : The market must be classified as either trending (ADX > configured threshold, default 30) or volatile (ATR expansion > configured threshold, default 40% above 30-bar average), and must NOT be in choppy/ranging state. This critical filter prevents trading during geometrically unfavorable conditions where edge deteriorates.
All five conditions must evaluate true simultaneously for a signal to generate. This conjunction-based logic (AND not OR) dramatically reduces false positives while preserving true reversal detection. The architecture recognizes that geometric catastrophes occur frequently in noisy data, but only those catastrophes that align with confirming evidence across price structure, participation, and regime characteristics represent tradable opportunities.
A cooldown mechanism (default 8 bars between signals) prevents signal clustering at extended pivot zones where the manifold may undergo multiple small catastrophes during a single reversal process.
Direction Classification System
Unlike binary bull/bear systems, the indicator implements a voting mechanism combining four
directional indicators to classify each catastrophe:
Pivot Vote : +1 if pivot low, -1 if pivot high, 0 otherwise
Trend Vote : Based on slow frequency (55-period EMA) slope—+1 if rising, -1 if falling, 0 if flat
Flow Vote : Based on Y-gradient (momentum acceleration)—+1 if positive, -1 if negative, 0 if neutral
Mid-Band Vote : Based on price position relative to medium frequency (21-period EMA)—+1 if above, -1 if below, 0 if at
The total vote sum classifies the singularity: ≥2 votes = Bullish , ≤-2 votes = Bearish , -1 to +1 votes = Neutral (skip) . This majority-consensus approach ensures directional classification requires alignment across multiple timeframes and analysis dimensions rather than relying on a single indicator. Neutral signals (mixed voting) are displayed but should not be traded, as they represent geometric catastrophes without clear directional resolution.
Core Calculation Methodology
Embedding Coordinate Generation
Three normalized phase space coordinates are constructed from price data:
X-Dimension (Velocity Space):
price_velocity = close - close
X = (price_velocity - mean) / stdev over hurstWindow
Y-Dimension (Acceleration Space):
momentum = close - close
momentum_accel = momentum - momentum
Y = (momentum_accel - mean) / stdev over hurstWindow
Z-Dimension (Volume-Weighted Space):
vol_normalized = (volume - mean) / stdev over embedLength
roc = (close - close ) / close
Z = (roc × vol_normalized - mean) / stdev over hurstWindow
These coordinates define a point in 3D phase space for each bar. The trajectory connecting these points is the reconstructed manifold.
Gradient Field Calculation
First derivatives measure local manifold slope:
dX/dt = X - X
dY/dt = Y - Y
Gradient_Magnitude = √
The gradient direction indicates where the manifold is "pushing" price. Positive Y-gradient suggests upward topological pressure; negative Y-gradient suggests downward pressure.
Curvature Tensor Components
Second derivatives measure manifold bending using discrete Laplacian:
Laplacian_X = X - 2×X + X
Laplacian_Y = Y - 2×Y + Y
Laplacian_Magnitude = √
This is then normalized:
Curvature_Normalized = (Laplacian_Magnitude - mean) / stdev over embedLength
High normalized curvature (>1.5) indicates sharp manifold folding.
Complexity Accumulation
Sign changes in curvature field are counted:
Sign_Flip = 1 if sign(Curvature ) ≠ sign(Curvature ), else 0
Topological_Complexity = sum(Sign_Flip) over embedLength window
This measures oscillation frequency in the geometry. Complexity >5 indicates chaotic topology.
Condition Number Stability Analysis
Jacobian matrix sensitivity is approximated:
dX/dp = dX/dt / (price_change + epsilon)
dY/dp = dY/dt / (price_change + epsilon)
Jacobian_Determinant = (dX/dt × dY/dp) - (dX/dp × dY/dt)
Jacobian_Trace = dX/dt + dY/dp
Condition_Number = |Trace| / (|Determinant| + epsilon)
High condition numbers indicate numerical instability near singularities.
Catastrophe Score Assembly
Each metric is converted to percentile rank over embedLength window, then combined:
Curvature_Percentile = percentrank(abs(Curvature_Normalized), embedLength)
Gradient_Percentile = percentrank(Gradient_Magnitude, embedLength)
Condition_Percentile = percentrank(abs(Condition_Z_Score), embedLength)
Complexity_Ratio = clamp(Topological_Complexity / embedLength, 0, 1)
Final score:
Raw_Anomaly = 0.45×Curvature_P + 0.25×Complexity_R + 0.20×Condition_P + 0.10×Gradient_P
Catastrophe_Score = Raw_Anomaly × Hurst_Multiplier
Values are clamped to range.
Hurst Exponent Calculation
Rescaled range analysis on log returns:
Calculate log returns: r = log(close) - log(close )
Compute cumulative deviations from mean
Find range: R = max(cumulative_dev) - min(cumulative_dev)
Calculate standard deviation: S = stdev(r, hurstWindow)
Compute R/S ratio
Hurst = log(R/S) / log(hurstWindow)
Clamp to and smooth with 5-period EMA
Regime Classification Logic
Volatility Regime:
ATR_MA = SMA(ATR(14), 30)
Vol_Expansion = ATR / ATR_MA
Is_Volatile = Vol_Expansion > (1.0 + minVolExpansion)
Trend Regime (Corrected ADX):
Calculate directional movement (DM+, DM-)
Smooth with Wilder's RMA(14)
Compute DI+ and DI- as percentages
Calculate DX = |DI+ - DI-| / (DI+ + DI-) × 100
ADX = RMA(DX, 14)
Is_Trending = ADX > (trendStrength × 100)
Chop Detection:
Is_Chopping = NOT Is_Trending AND NOT Is_Volatile
Regime Validity:
Regime_Valid = (Is_Trending OR Is_Volatile) AND NOT Is_Chopping
Signal Generation Logic
For each bar:
Check if catastrophe score > topologyStrength threshold
Verify regime is valid
Confirm Hurst alignment (trending or mean-reverting with pivot)
Validate pivot quality (price extended outside spectral bands then re-entered)
Confirm volume/volatility participation
Check cooldown period has elapsed
If all true: compute directional vote
If vote ≥2: Bullish Singularity
If vote ≤-2: Bearish Singularity
If -1 to +1: Neutral (display but skip)
All conditions must be true for signal generation.
Visual System Architecture
Spectral Decomposition Layers
Three harmonic frequency bands visualize entropy state:
Layer 1 (Surface Frequency):
Center: EMA(8)
Width: ±0.3 × 0.5 × ATR
Transparency: 75% (most visible)
Represents fast oscillations
Layer 2 (Mid Frequency):
Center: EMA(21)
Width: ±0.5 × 0.5 × ATR
Transparency: 85%
Represents medium cycles
Layer 3 (Deep Frequency):
Center: EMA(55)
Width: ±0.7 × 0.5 × ATR
Transparency: 92% (most transparent)
Represents slow baseline
Convergence of layers indicates low entropy (stable topology). Divergence indicates high entropy (catastrophe building). This decomposition reveals how different frequency components of price movement interact—when all three align, the manifold is in equilibrium; when they separate, topology is unstable.
Energy Radiance Fields
Concentric boxes emanate from each singularity bar:
For each singularity, 5 layers are generated:
Layer n: bar_index ± (n × 1.5 bars), close ± (n × 0.4 × ATR)
Transparency gradient: inner 75% → outer 95%
Color matches signal direction
These fields visualize the "energy well" of the catastrophe—wider fields indicate stronger topology distortion. The exponential expansion creates a natural radiance effect.
Singularity Node Geometry
N-sided polygon (default hexagon) at each signal bar:
Vertices calculated using polar coordinates
Rotation angle: bar_index × 0.1 (creates animation)
Radius: ATR × singularity_strength × 2
Connects vertices with colored lines
The rotating geometric primitive marks the exact catastrophe bar with visual prominence.
Gradient Flow Field
Directional arrows display manifold slope:
Spawns every 3 bars when gradient_magnitude > 0.1
Symbol: "↗" if dY/dt > 0.1, "↘" if dY/dt < -0.1, "→" if neutral
Color: Bull/bear/neutral based on direction
Density limited to flowDensity parameter
Arrows cluster when gradient is strong, creating intuitive topology visualization.
Probability Projection Cones
Forward trajectory from each singularity:
Projects 10 bars forward
Direction based on vote classification
Center line: close + (direction × ATR × 3)
Uncertainty width: ATR × singularity_strength × 2
Dashed boundaries, solid center
These are mathematical projections based on current gradient, not price targets. They visualize expected manifold evolution if topology continues current trajectory.
Dashboard Metrics Explanation
The real-time control panel displays six core metrics plus regime status:
H (Hurst Exponent):
Value: Current Hurst (0-1 scale)
Label: TREND (>0.55), REVERT (<0.45), or RANDOM (0.45-0.55)
Icon: Direction arrow based on regime
Purpose: Shows fractal character—only trade when favorable
Σ (Catastrophe Score):
Value: Current composite anomaly (0-100%)
Bar gauge shows relative strength
Icon: ◆ if above threshold, ○ if below
Purpose: Primary signal strength indicator
κ (Curvature):
Value: Normalized Laplacian magnitude
Direction arrow shows sign
Color codes severity (green<0.8, yellow<1.5, red≥1.5)
Purpose: Shows manifold bending intensity
⟳ (Topology Complexity):
Value: Count of sign flips in curvature
Icon: ◆ if >3, ○ otherwise
Color codes chaos level
Purpose: Indicates geometric instability
V (Volatility Expansion):
Value: ATR expansion percentage above 30-bar average
Icon: ● if volatile, ○ otherwise
Purpose: Confirms energy present for reversal
T (Trend Strength):
Value: ADX reading (0-100)
Icon: ● if trending, ○ otherwise
Purpose: Shows directional bias strength
R (Regime):
Label: EXPLOSIVE / TREND / VOLATILE / CHOP / NEUTRAL
Icon: ✓ if valid, ✗ if invalid
Purpose: Go/no-go filter for trading
STATE (Bottom Display):
Shows: "◆ BULL SINGULARITY" (green), "◆ BEAR SINGULARITY" (red), "◆ WEAK/NEUTRAL" (orange), or "— Monitoring —" (gray)
Purpose: Current signal status at a glance
How to Use This Indicator
Initial Setup and Configuration
Apply the indicator to your chart with default settings as a starting point. The default parameters (21-bar embedding, 5-bar Hurst window, 2.5σ singularity threshold, 0.65 topology confirmation) are optimized for balanced detection across most instruments and timeframes. For very fast markets (scalping crypto, 1-5min charts), consider reducing embedding depth to 13-15 bars and Hurst window to 3 bars for more responsive detection. For slower markets (swing trading stocks, 4H-Daily charts), increase embedding depth to 34-55 bars and Hurst window to 8-10 bars for more stable topology measurement.
Enable the dashboard (top right recommended) to monitor real-time metrics. The control panel is your primary decision interface—glancing at the dashboard should instantly communicate whether conditions favor trading and what the current topology state is. Position and size the dashboard to remain visible but not obscure price action.
Enable regime filtering (strongly recommended) to prevent trading during choppy/ranging conditions where geometric edge deteriorates. This single setting can dramatically improve overall performance by eliminating low-probability environments.
Reading Dashboard Metrics for Trade Readiness
Before considering any trade, verify the dashboard shows favorable conditions:
Hurst (H) Check:
The Hurst Exponent reading is your first filter. Only consider trades when H > 0.50 . Ideal conditions show H > 0.60 with "TREND" label—this indicates persistent directional price movement where manifold catastrophes produce significant reversals. When H < 0.45 (REVERT label), the market is mean-reverting and catastrophes represent minor oscillations rather than substantial pivots. Do not trade in mean-reverting regimes unless you're explicitly using range-bound strategies (which this indicator is not optimized for). When H ≈ 0.50 (RANDOM label), edge is neutral—acceptable but not ideal.
Catastrophe (Σ) Monitoring:
Watch the Σ percentage build over time. Readings consistently below 50% indicate stable topology with no imminent reversals. When Σ rises above 60-65%, manifold distortion is approaching critical levels. Signals only fire when Σ exceeds the configured threshold (default 65%), so this metric pre-warns you of potential upcoming catastrophes. High-conviction setups show Σ > 75%.
Regime (R) Validation:
The regime classification must read TREND, VOLATILE, or EXPLOSIVE—never trade when it reads CHOP or NEUTRAL. The checkmark (✓) must be present in the regime cell for trading conditions to be valid. If you see an X (✗), skip all signals until regime improves. This filter alone eliminates most losing trades by avoiding geometrically unfavorable environments.
Combined High-Conviction Profile:
The strongest trading opportunities show simultaneously:
H > 0.60 (strong trending regime)
Σ > 75% (extreme topology distortion)
R = EXPLOSIVE or TREND with ✓
κ (Curvature) > 1.5 (sharp manifold fold)
⟳ (Complexity) > 4 (chaotic geometry)
V (Volatility) showing elevated ATR expansion
When all metrics align in this configuration, the manifold is undergoing severe distortion in a favorable fractal regime—these represent maximum-conviction reversal opportunities.
Signal Interpretation and Entry Logic
Bullish Singularity (▲ Green Triangle Below Bar):
This marker appears when the system detects a manifold catastrophe at a price low with bullish directional consensus. All five confirmation filters have aligned: topology score exceeded threshold, pivot low structure formed, swing size was significant, volume/volatility confirmed participation, and regime was valid. The green color indicates the directional vote totaled +2 or higher (majority bullish).
Trading Approach: Consider long entry on the bar immediately following the signal (bar after the triangle). The singularity bar itself is where the geometric catastrophe occurred—entering after allows you to see if price confirms the reversal. Place stop loss below the singularity bar's low (with buffer of 0.5-1.0 ATR for volatility). Initial target can be the previous swing high, or use the probability cone projection as a guide (though not a guarantee). Monitor the dashboard STATE—if it flips to "◆ BEAR SINGULARITY" or Hurst drops significantly, consider exiting even if target not reached.
Bearish Singularity (▼ Red Triangle Above Bar):
This marker appears when the system detects a manifold catastrophe at a price high with bearish directional consensus. Same five-filter confirmation process as bullish signals. The red color indicates directional vote totaled -2 or lower (majority bearish).
Trading Approach: Consider short entry on the bar following the signal. Place stop loss above the singularity bar's high (with buffer). Target previous swing low or use cone projection as reference. Exit if opposite signal fires or Hurst deteriorates.
Neutral Signal (● Orange Circle at Price Level):
This marker indicates the catastrophe detection system identified a topology break that passed catastrophe threshold and regime filters, but the directional voting system produced a mixed result (vote between -1 and +1). This means the four directional components (pivot, trend, flow, mid-band) are not in agreement about which way the reversal should resolve.
Trading Approach: Skip these signals. Neutral markers are displayed for analytical completeness but should not be traded. They represent geometric catastrophes without clear directional resolution—essentially, the manifold is breaking but the direction of the break is ambiguous. Trading neutral signals dramatically increases false signal rate. Only trade green (bullish) or red (bearish) singularities.
Visual Confirmation Using Spectral Layers
The three colored ribbons (spectral decomposition layers) provide entropy visualization that helps confirm signal quality:
Divergent Layers (High Entropy State):
When the three frequency bands (fast 8-period, medium 21-period, slow 55-period) are separated with significant gaps between them, the manifold is in high entropy state—different frequency components of price movement are pulling in different directions. This geometric tension precedes catastrophes. Strong signals often occur when layers are divergent before the signal, then begin reconverging immediately after.
Convergent Layers (Low Entropy State):
When all three ribbons are tightly clustered or overlapping, the manifold is in equilibrium—all frequency components agree. This stable geometry makes catastrophe detection more reliable because topology breaks clearly stand out against the baseline stability. If you see layers converge, then a singularity fires, then layers diverge, this pattern suggests a genuine regime transition.
Signal Quality Assessment:
High-quality singularity signals should show:
Divergent layers (high entropy) in the 5-10 bars before signal
Singularity bar occurs when price has extended outside at least one of the spectral bands (shows pivot extended beyond equilibrium)
Close of singularity bar re-enters the spectral band zone (shows mean reversion starting)
Layers begin reconverging in 3-5 bars after signal (shows new equilibrium forming)
This pattern visually confirms the geometric narrative: manifold became unstable (divergence), reached critical distortion (extended outside equilibrium), broke catastrophically (singularity), and is now stabilizing in new direction (reconvergence).
Using Energy Fields for Trade Management
The concentric glowing boxes around each singularity visualize the topology distortion
magnitude:
Wide Energy Fields (5+ Layers Visible):
Large radiance indicates strong catastrophe with high manifold curvature. These represent significant topology breaks and typically precede larger price moves. Wide fields justify wider profit targets and longer hold times. The outer edge of the largest box can serve as a dynamic support/resistance zone—price often respects these geometric boundaries.
Narrow Energy Fields (2-3 Layers):
Smaller radiance indicates moderate catastrophe. While still valid signals (all filters passed), expect smaller follow-through. Use tighter profit targets and be prepared for quicker exit if momentum doesn't develop. These are valid but lower-conviction trades.
Field Interaction Zones:
When energy fields from consecutive signals overlap or touch, this indicates a prolonged topology distortion region—often corresponds to consolidation zones or complex reversal patterns (head-and-shoulders, double tops/bottoms). Be more cautious in these areas as the manifold is undergoing extended restructuring rather than a clean catastrophe.
Probability Cone Projections
The dashed cone extending forward from each singularity is a mathematical projection, not a
price target:
Cone Direction:
The center line direction (upward for bullish, downward for bearish, flat for neutral) shows the expected trajectory based on current manifold gradient and singularity direction. This is where the topology suggests price "should" go if the catastrophe completes normally.
Cone Width:
The uncertainty band (upper and lower dashed boundaries) represents the range of outcomes given current volatility (ATR-based). Wider cones indicate higher uncertainty—expect more price volatility even if direction is correct. Narrower cones suggest more constrained movement.
Price-Cone Interaction:
Price following near the center line = catastrophe resolving as expected, geometric projection accurate
Price breaking above upper cone = stronger-than-expected reversal, consider holding for larger targets
Price breaking below lower cone (for bullish signal) = catastrophe failing, manifold may be re-folding in opposite direction, consider exit
Price oscillating within cone = normal reversal process, hold position
The 10-bar projection length means cones show expected behavior over the next ~10 bars. Don't confuse this with longer-term price targets.
Gradient Flow Field Interpretation
The directional arrows (↗, ↘, →) scattered across the chart show the manifold's Y-gradient (vertical acceleration dimension):
Upward Arrows (↗):
Positive Y-gradient indicates the momentum acceleration dimension is pushing upward—the manifold topology has upward "slope" at this location. Clusters of upward arrows suggest bullish topological pressure building. These often appear before bullish singularities fire.
Downward Arrows (↘):
Negative Y-gradient indicates downward topological pressure. Clusters precede bearish singularities.
Horizontal Arrows (→):
Neutral gradient indicates balanced topology with no strong directional pressure.
Using Flow Field:
The arrows provide real-time topology state information even between singularity signals. If you're in a long position from a bullish singularity and begin seeing increasing downward arrows appearing, this suggests manifold gradient is shifting—consider tightening stops. Conversely, if arrows remain upward or neutral, topology supports continuation.
Don't confuse arrow direction with immediate price direction—arrows show geometric slope, not price prediction. They're confirmatory context, not entry signals themselves.
Parameter Optimization for Your Trading Style
For Scalping / Fast Trading (1m-15m charts):
Embedding Depth: 13-15 bars (faster topology reconstruction)
Hurst Window: 3 bars (responsive fractal detection)
Singularity Threshold: 2.0-2.3σ (more sensitive)
Topology Confirmation: 0.55-0.60 (lower barrier)
Min Swing Size: 0.8-1.2 ATR (accepts smaller moves)
Pivot Lookback: 3-4 bars (quick pivot detection)
This configuration increases signal frequency for active trading but requires diligent monitoring as false signal rate increases. Use tighter stops.
For Day Trading / Standard Approach (15m-4H charts):
Keep default settings (21 embed, 5 Hurst, 2.5σ, 0.65 confirmation, 1.5 ATR, 5 pivot)
These are balanced for quality over quantity
Best win rate and risk/reward ratio
Recommended for most traders
For Swing Trading / Position Trading (4H-Daily charts):
Embedding Depth: 34-55 bars (stable long-term topology)
Hurst Window: 8-10 bars (smooth fractal measurement)
Singularity Threshold: 3.0-3.5σ (only extreme catastrophes)
Topology Confirmation: 0.75-0.85 (high conviction only)
Min Swing Size: 2.5-4.0 ATR (major moves only)
Pivot Lookback: 8-13 bars (confirmed swings)
This configuration produces infrequent but highly reliable signals suitable for position sizing and longer hold times.
Volatility Adaptation:
In extremely volatile instruments (crypto, penny stocks), increase Min Volatility Expansion to 0.6-0.8 to avoid over-signaling during "always volatile" conditions. In stable instruments (major forex pairs, blue-chip stocks), decrease to 0.3 to allow signals during moderate volatility spikes.
Trend vs Range Preference:
If you prefer trading only strong trends, increase Min Trend Strength to 0.5-0.6 (ADX > 50-60). If you're comfortable with volatility-based trading in weaker trends, decrease to 0.2 (ADX > 20). The default 0.3 balances both approaches.
Complete Trading Workflow Example
Step 1 - Pre-Session Setup:
Load chart with MSE indicator. Check dashboard position is visible. Verify regime filter is enabled. Review recent signals to gauge current instrument behavior.
Step 2 - Market Assessment:
Observe dashboard Hurst reading. If H < 0.45 (mean-reverting), consider skipping this session or using other strategies. If H > 0.50, proceed. Check regime shows TREND, VOLATILE, or EXPLOSIVE with checkmark—if CHOP, wait for regime shift alert.
Step 3 - Signal Wait:
Monitor catastrophe score (Σ). Watch for it climbing above 60%. Observe spectral layers—look for divergence building. If you see curvature (κ) rising above 1.0 and complexity (⟳) increasing, catastrophe is building. Do not anticipate—wait for the actual signal marker.
Step 4 - Signal Recognition:
▲ Bullish or ▼ Bearish triangle appears at a bar. Dashboard STATE changes to "◆ BULL/BEAR SINGULARITY". Energy field appears around the signal bar. Check signal quality:
Was Σ > 70% at signal? (Higher quality)
Are energy fields wide? (Stronger catastrophe)
Did layers diverge before and reconverge after? (Clean break)
Is Hurst still > 0.55? (Good regime)
Step 5 - Entry Decision:
If signal is green/red (not orange neutral), all confirmations look strong, and no immediate contradicting factors appear, prepare entry on next bar open. Wait for confirmation bar to form—ideally it should close in the signal direction (bullish signal → bar closes higher, bearish signal → bar closes lower).
Step 6 - Position Entry:
Enter at open or shortly after open of bar following signal bar. Set stop loss: for bullish signals, place stop at singularity_bar_low - (0.75 × ATR); for bearish signals, place stop at singularity_bar_high + (0.75 × ATR). The buffer accommodates volatility while protecting against catastrophe failure.
Step 7 - Trade Management:
Monitor dashboard continuously:
If Hurst drops below 0.45, consider reducing position
If opposite singularity fires, exit immediately (manifold has re-folded)
If catastrophe score drops below 40% and stays there, topology has stabilized—consider partial profit taking
Watch gradient flow arrows—if they shift to opposite direction persistently, tighten stops
Step 8 - Profit Taking:
Use probability cone as a guide—if price reaches outer cone boundary, consider taking partial profits. If price follows center line cleanly, hold for larger target. Traditional technical targets work well: previous swing high/low, round numbers, Fibonacci extensions. Don't expect precision—manifold projections give direction and magnitude estimates, not exact prices.
Step 9 - Exit:
Exit on: (a) opposite signal appears, (b) dashboard shows regime became invalid (checkmark changes to X), (c) technical target reached, (d) Hurst deteriorates significantly, (e) stop loss hit, or (f) time-based exit if using session limits. Never hold through opposite singularity signals—the manifold has broken in the other direction and your trade thesis is invalidated.
Step 10 - Post-Trade Review:
After exit, review: Did the probability cone projection align with actual price movement? Were the energy fields proportional to move size? Did spectral layers show expected reconvergence? Use these observations to calibrate your interpretation of signal quality over time.
Best Performance Conditions
This topology-based approach performs optimally in specific market environments:
Favorable Conditions:
Well-Developed Swing Structure: Markets with clear rhythm of advances and declines where pivots form at regular intervals. The manifold reconstruction depends on swing formation, so instruments that trend in clear waves work best. Stocks, major forex pairs during active sessions, and established crypto assets typically exhibit this characteristic.
Sufficient Volatility for Topology Development: The embedding process requires meaningful price movement to construct multi-dimensional coordinates. Extremely quiet markets (tight consolidations, holiday trading, after-hours) lack the volatility needed for manifold differentiation. Look for ATR expansion above average—when volatility is present, geometry becomes meaningful.
Trending with Periodic Reversals: The ideal environment is not pure trend (which rarely reverses) nor pure range (which reverses constantly at small scale), but rather trending behavior punctuated by occasional significant counter-trend reversals. This creates the catastrophe conditions the system is designed to detect: manifold building directional momentum, then undergoing sharp topology break at extremes.
Liquid Instruments Where EMAs Reflect True Flow: The spectral layers and frequency decomposition require that moving averages genuinely represent market consensus. Thinly traded instruments with sporadic orders don't create smooth manifold topology. Prefer instruments with consistent volume where EMA calculations reflect actual capital flow rather than random tick sequences.
Challenging Conditions:
Extremely Choppy / Whipsaw Markets: When price oscillates rapidly with no directional persistence (Hurst < 0.40), the manifold undergoes constant micro-catastrophes that don't translate to tradable reversals. The regime filter helps avoid these, but awareness is important. If you see multiple neutral signals clustering with no follow-through, market is too chaotic for this approach.
Very Low Volatility Consolidation: Tight ranges with ATR below average cause the embedding coordinates to compress into a small region of phase space, reducing geometric differentiation. The manifold becomes nearly flat, and catastrophe detection loses sensitivity. The regime filter's volatility component addresses this, but manually avoiding dead markets improves results.
Gap-Heavy Instruments: Stocks that gap frequently (opening outside previous close) create discontinuities in the manifold trajectory. The embedding process assumes continuous evolution, so gaps introduce artifacts. Most gaps don't invalidate the approach, but instruments with daily gaps >2% regularly may show degraded performance. Consider using higher timeframes (4H, Daily) where gaps are less proportionally significant.
Parabolic Moves / Blowoff Tops: When price enters an exponential acceleration phase (vertical rally or crash), the manifold evolves too rapidly for the standard embedding window to track. Catastrophe detection may lag or produce false signals mid-move. These conditions are rare but identifiable by Hurst > 0.75 combined with ATR expansion >2.0× average. If detected, consider sitting out or using very tight stops as geometry is in extreme distortion.
The system adapts by reducing signal frequency in poor conditions—if you notice long periods with no signals, the topology likely lacks the geometric structure needed for reliable catastrophe detection. This is a feature, not a bug: it prevents forced trading during unfavorable environments.
Theoretical Justification for Approach
Why Manifold Embedding?
Traditional technical analysis treats price as a one-dimensional time series: current price is predicted from past prices in sequential order. This approach ignores the structure of price dynamics—the relationships between velocity, acceleration, and participation that govern how price actually evolves.
Dynamical systems theory (from physics and mathematics) provides an alternative framework: treat price as a state variable in a multi-dimensional phase space. In this view, each market condition corresponds to a point in N-dimensional space, and market evolution is a trajectory through this space. The geometry of this space (its topology) constrains what trajectories are possible.
Manifold embedding reconstructs this hidden geometric structure from observable price data. By creating coordinates from velocity, momentum acceleration, and volume-weighted returns, we map price evolution onto a 3D surface. This surface—the manifold—reveals geometric relationships that aren't visible in price charts alone.
The mathematical theorem underlying this approach (Takens' Embedding Theorem from dynamical systems theory) proves that for deterministic or weakly stochastic systems, a state space reconstruction from time-delayed observations of a single variable captures the essential dynamics of the full system. We apply this principle: even though we only observe price, the embedded coordinates (derivatives of price) reconstruct the underlying dynamical structure.
Why Catastrophe Theory?
Catastrophe theory, developed by mathematician René Thom (Fields Medal 1958), describes how continuous systems can undergo sudden discontinuous changes when control parameters reach critical values. A classic example: gradually increasing force on a beam causes smooth bending, then sudden catastrophic buckling. The beam's geometry reaches a critical curvature where topology must break.
Markets exhibit analogous behavior: gradual price changes build tension in the manifold topology until critical distortion is reached, then abrupt directional change occurs (reversal). Catastrophes aren't random—they're mathematically necessary when geometric constraints are violated.
The indicator detects these geometric precursors: high curvature (manifold bending sharply), high complexity (topology oscillating chaotically), high condition number (coordinate mapping becoming singular). These metrics quantify how close the manifold is to a catastrophic fold. When all simultaneously reach extreme values, topology break is imminent.
This provides a logical foundation for reversal detection that doesn't rely on pattern recognition or historical correlation. We're measuring geometric properties that mathematically must change when systems reach critical states. This is why the approach works across different instruments and timeframes—the underlying geometry is universal.
Why Hurst Exponent?
Markets exhibit fractal behavior: patterns at different time scales show statistical self-similarity. The Hurst exponent quantifies this fractal structure by measuring long-range dependence in returns.
Critically for trading, Hurst determines whether recent price movement predicts future direction (H > 0.5) or predicts the opposite (H < 0.5). This is regime detection: trending vs mean-reverting behavior.
The same manifold catastrophe has different trading implications depending on regime. In trending regime (high Hurst), catastrophes represent significant reversal opportunities because the manifold has been building directional momentum that suddenly breaks. In mean-reverting regime (low Hurst), catastrophes represent minor oscillations because the manifold constantly folds at small scales.
By weighting catastrophe signals based on Hurst, the system adapts detection sensitivity to the current fractal regime. This is a form of meta-analysis: not just detecting geometric breaks, but evaluating whether those breaks are meaningful in the current fractal context.
Why Multi-Layer Confirmation?
Geometric anomalies occur frequently in noisy market data. Not every high-curvature point represents a tradable reversal—many are artifacts of microstructure noise, order flow imbalances, or low-liquidity ticks.
The five-filter confirmation system (catastrophe threshold, pivot structure, swing size, volume, regime) addresses this by requiring geometric anomalies to align with observable market evidence. This conjunction-based logic implements the principle: extraordinary claims require extraordinary evidence .
A manifold catastrophe (extraordinary geometric event) alone is not sufficient. We additionally require: price formed a pivot (visible structure), swing was significant (adequate magnitude), volume confirmed participation (capital backed the move), and regime was favorable (trending or volatile, not chopping). Only when all five dimensions agree do we have sufficient evidence that the geometric anomaly represents a genuine reversal opportunity rather than noise.
This multi-dimensional approach is analogous to medical diagnosis: no single test is conclusive, but when multiple independent tests all suggest the same condition, confidence increases dramatically. Each filter removes a different category of false signals, and their combination creates a robust detection system.
The result is a signal set with dramatically improved reliability compared to any single metric alone. This is the power of ensemble methods applied to geometric analysis.
Important Disclaimers
This indicator applies mathematical topology and catastrophe theory to multi-dimensional price space reconstruction. It identifies geometric conditions where manifold curvature, topological complexity, and coordinate singularities suggest potential reversal zones based on phase space analysis. It should not be used as a standalone trading system.
The embedding coordinates, catastrophe scores, and Hurst calculations are deterministic mathematical formulas applied to historical price data. These measurements describe current and recent geometric relationships in the reconstructed manifold but do not predict future price movements. Past geometric patterns and singularity markers do not guarantee future market behavior will follow similar topology evolution.
The manifold reconstruction assumes certain mathematical properties (sufficient embedding dimension, quasi-stationarity, continuous dynamics) that may not hold in all market conditions. Gaps, flash crashes, circuit breakers, news events, and other discontinuities can violate these assumptions. The system attempts to filter problematic conditions through regime classification, but cannot eliminate all edge cases.
The spectral decomposition, energy fields, and probability cones are visualization aids that represent mathematical constructs, not price predictions. The probability cone projects current gradient forward assuming topology continues current trajectory—this is a mathematical "if-then" statement, not a forecast. Market topology can and does change unexpectedly.
All trading involves substantial risk. The singularity markers represent analytical conditions where geometric mathematics align with threshold criteria, not certainty of directional change. Use appropriate risk management for every trade: position sizing based on account risk tolerance (typically 1-2% maximum risk per trade), stop losses placed beyond recent structure plus volatility buffer, and never risk capital needed for living expenses.
The confirmation filters (pivot, swing size, volume, regime) are designed to reduce false signals but cannot eliminate them entirely. Markets can produce geometric anomalies that pass all filters yet fail to develop into sustained reversals. This is inherent to probabilistic systems operating on noisy real-world data.
No indicator can guarantee profitable trades or eliminate losses. The catastrophe detection provides an analytical framework for identifying potential reversal conditions, but actual trading outcomes depend on numerous factors including execution, slippage, spreads, position sizing, risk management, psychological discipline, and market conditions that may change after signal generation.
Use this tool as one component of a comprehensive trading plan that includes multiple forms of analysis, proper risk management, emotional discipline, and realistic expectations about win rates and drawdowns. Combine catastrophe signals with additional confirmation methods such as support/resistance analysis, volume patterns, multi-timeframe alignment, and broader market context.
The spacing filter, cooldown mechanism, and regime validation are designed to reduce noise and over-signaling, but market conditions can change rapidly and render any analytical signal invalid. Always use stop losses and never risk capital you cannot afford to lose. Past performance of detection accuracy does not guarantee future results.
Technical Implementation Notes
All calculations execute on closed bars only—signals and metric values do not repaint after bar close. The indicator does not use any lookahead bias in its calculations. However, the pivot detection mechanism (ta.pivothigh and ta.pivotlow) inherently identifies pivots with a lag equal to the lookback parameter, meaning the actual pivot occurred at bar but is recognized at bar . This is standard behavior for pivot functions and is not repainting—once recognized, the pivot bar never changes.
The normalization system (z-score transformation over rolling windows) requires approximately 30-50 bars of historical data to establish stable statistics. Values in the first 30-50 bars after adding the indicator may show instability as the rolling means and standard deviations converge. Allow adequate warmup period before relying on signals.
The spectral layer arrays, energy field boxes, gradient flow labels, and node geometry lines are subject to TradingView drawing object limits (500 lines, 500 boxes, 500 labels per indicator as specified in settings). The system implements automatic cleanup by deleting oldest objects when limits approach, but on very long charts with many signals, some historical visual elements may be removed to stay within limits. This does not affect signal generation or dashboard metrics—only historical visual artifacts.
Dashboard and visual rendering update only on the last bar to minimize computational overhead. The catastrophe detection logic executes on every bar, but table cells and drawing objects refresh conditionally to optimize performance. If experiencing chart lag, reduce visual complexity: disable spectral layers, energy fields, or flow field to improve rendering speed. Core signal detection continues to function with all visual elements disabled.
The Hurst calculation uses logarithmic returns rather than raw price to ensure stationarity, and implements clipping to range to handle edge cases where R/S analysis produces invalid values (which can occur during extended periods of identical prices or numerical overflow). The 5-period EMA smoothing reduces noise while maintaining responsiveness to regime transitions.
The condition number calculation adds epsilon (1e-10) to denominators to prevent division by zero when Jacobian determinant approaches zero—which is precisely the singularity condition we're detecting. This numerical stability measure ensures the indicator doesn't crash when detecting the very phenomena it's designed to identify.
The indicator has been tested across multiple timeframes (5-minute through daily) and multiple asset classes (forex majors, stock indices, individual equities, cryptocurrencies, commodities, futures). It functions identically across all instruments due to the adaptive normalization approach and percentage-based metrics. No instrument-specific code or parameter sets are required.
The color scheme system implements seven preset themes plus custom mode. Color assignments are applied globally and affect all visual elements simultaneously. The opacity calculation system multiplies component-specific transparency with master opacity to create hierarchical control—adjusting master opacity affects all visuals proportionally while maintaining their relative transparency relationships.
All alert conditions trigger only on bar close to prevent false alerts from intrabar fluctuations. The regime transition alerts (VALID/INVALID) are particularly useful for knowing when trading edge appears or disappears, allowing traders to adjust activity levels accordingly.
— Dskyz, Trade with insight. Trade with anticipation.
APXTradez - TTM Squeeze🔹 APXTradez TTM Squeeze — Summary & How To Use It
What this indicator is
- This is a volatility + momentum engine built for options trading.
It does two jobs at the same time:
- Shows when price is coiling and ready to move (volatility compression using Bollinger Bands vs Keltner Channels).
- Shows which side has control (bullish vs bearish momentum, and whether that pressure is growing or cooling off).
- You use it to time entries on explosive directional moves (breakouts/breakdowns) and to avoid dead chop.
1. Volatility / Compression Logic (the dots)
- This script measures how tight price is by comparing:
- Bollinger Bands (BB): tracks standard deviation (volatility).
- Keltner Channels (KC): tracks ATR (true range / movement).
- When the Bollinger Bands get tighter than the Keltner Channels, price is literally getting bottled up. That’s what traders call “a squeeze.”
- This script splits that squeeze into tiers so you know how aggressive it is:
Orange Dot = High Compression
- BB are inside the tightest Keltner channel (kcMultHigh).
- This is the tightest coil. Energy is loaded.
- Translation: “Something is about to happen here. Pay attention.”
Red Dot = Medium Compression
- BB still inside KC, but looser than orange.
- Pressure building, not maxed.
Yellow Dot = Low Compression
- Still compressed, but wider than red.
- Early stage coil.
Black/Dark Dot = Fired / No Compression
- BB are no longer inside KC.
- The squeeze “released.”
- Translation: “The move is now happening.”
So visually, you’ll often see a sequence like:
yellow → red → orange → black.
That’s the life cycle:
Coil tighter and tighter.
Then BOOM: release.
That release is often where traders take entries.
How to trade the dots
- When you see orange dots stacking, you’re in max coil. You prepare, you don’t FOMO-enter yet.
- When the dots flip to black, that means volatility just expanded (squeeze fired).
- You only want to follow that release in the direction of momentum (see histogram section below). Do not blindly buy every “black.”
So:
- Identify compression (orange/red/yellow).
- Wait for “fired” (black).
- Then check: is momentum actually pushing bullish or bearish, or is it weak?
- That prevents chasing fake breaks.
2. Momentum Histogram (the bars)
- The lower histogram measures momentum using a linear regression on price and a smoothed EMA. In simple terms: it’s checking if price is pushing with force or fading.
It splits momentum into four readable states:
Bullish Side
- Bull Rising (Teal Bright)
- Momentum is above 0 and increasing.
Translation: “Buyers are in control and getting stronger.”
- This is the ideal bullish continuation / call side pressure.
Bull Cooling (Teal Faded)
- Momentum is above 0 but starting to slow down.
Translation: “Still bullish, but momentum is losing steam.”
- You can still stay in the trade, but be aware it’s not accelerating anymore.
Bearish Side
- Bear Pressing (Yellow Bright)
- Momentum is below 0 and getting more negative.
Translation: “Sellers are in control and pressure is increasing.”
- Great for puts / downside continuation.
Bear Cooling (Yellow Faded)
- Momentum is below 0 but starting to weaken.
Translation: “Still bearish, but selling force is easing.”
- Possible bottoming / potential reversal building soon.
- There’s also a zero line plotted. That’s your “neutral axis.”
Bars above zero = bullish regime.
Bars below zero = bearish regime.
Cross through zero = possible momentum flip.
How to read the histogram with the dots
- This is where it gets powerful.
Bullish breakout setup (calls):
- You’ve had compression dots (yellow/red/orange).
- Dots flip to black (squeeze fired).
- Histogram is teal and in “Bull Rising” (bright teal above zero and increasing).
→ That means volatility JUST expanded, and buyers are actually in control. That’s your A+ long/bullish continuation scenario.
Bearish breakdown setup (puts):
- You’ve had compression dots.
- Dots flip to black.
- Histogram is “Bear Pressing” (bright yellow below zero, getting more negative).
→ That means the release is to the downside with real selling pressure, not just a fake wick. That’s your A+ put/downside continuation scenario.
3. Timeframe and Trade Intent
This thing is designed to sit in its own lower panel (overlay = false). You watch it like MACD / Squeeze Pro, but cleaner and more obvious.
Recommended for:
- 4H and Daily: locating swings (2–5 day option plays).
- 5m / 15m / 1h: timing entries on liquid names if you’re doing intraday.
Flow is usually:
- Find the setup on a higher timeframe (Daily / 4H squeeze).
- Drop down one timeframe (1H / 15m) and enter on the first bullish or bearish “fire” in the same direction.
- This keeps you from randomly guessing entries.
4. Cheat Sheet (what to actually do)
Calls (bullish swing):
- You see clustered orange/red/yellow dots → stock is coiling.
- Then you get a black dot → squeeze fired.
- At the same time, the histogram turns bright teal (Bull Rising) and stays above zero.
-That’s your “calls / long continuation” look.
Puts (bearish swing):
- Compression dots first.
- Black dot shows up.
- Histogram turns bright yellow (Bear Pressing) and stays below zero.
That’s your “puts / short continuation” look.
Take profit / De-risk signs:
- Bullish but teal fades to dull teal → momentum is cooling.
- Bearish but yellow fades to dull yellow → selling is cooling.
- You’re still in trend, but gas pedal is coming off. That’s when you scale or trail.
5. Why this version is different from generic TTM Squeeze
-Most public squeeze indicators just tell you “in squeeze / out of squeeze” and show one color.
APXTradez version:
- Breaks compression into three levels (high / medium / low) so you know how “charged” the setup is, not just whether a squeeze exists.
- Shows the release (black dot) separately, so you instantly see “the moment it fired.”
- Splits momentum into four states, not two. You don’t just see “above / below zero,” you see:
- Building bullish
- Cooling bullish
- Building bearish
- Cooling bearish
That means you can tell:
“Is momentum gaining or dying?” instead of just “Is it green or red?”
Which is way more useful for options timing.
Tri-Align Crypto Trend (EMA + Slope)**Tri-Align Crypto Trend (EMA + Slope)**
Quickly see whether your coin is trending *with* Bitcoin. The indicator evaluates three pairs—**COIN/USDT**, **BTC/USDT**, and **COIN/BTC**—using a fast/slow EMA crossover plus the fast EMA’s slope. Each pair is tagged **Bullish / Bearish / Neutral** in a compact, color-coded table. Alerts fire when **all three** trends align (all bullish or all bearish).
**How to use**
1. Add the indicator to any crypto chart.
2. Set the three symbols (defaults: BNB/USDT, BTC/USDT, BNB/BTC) and optionally choose a signal timeframe.
3. Tune **Fast EMA**, **Slow EMA**, **Slope Lookback**, and **Min |Slope| %** to filter noise and require stronger momentum.
4. Create alerts: *Add alert →* choose the indicator and select **All Three Bullish**, **All Three Bearish**, or **All Three Aligned**.
**Logic**
* Bullish: `EMA_fast > EMA_slow` **and** fast EMA slope ≥ threshold
* Bearish: `EMA_fast < EMA_slow` **and** fast EMA slope ≤ −threshold
* Otherwise: Neutral
Tip: The **COIN/BTC** row reflects relative strength vs BTC—use it to avoid chasing coins that lag the benchmark. (For educational purposes; not financial advice.)
Tri-Align Crypto Trend (EMA + Slope)**Tri-Align Crypto Trend (EMA + Slope)**
Quickly see whether your coin is trending *with* Bitcoin. The indicator evaluates three pairs—**COIN/USDT**, **BTC/USDT**, and **COIN/BTC**—using a fast/slow EMA crossover plus the fast EMA’s slope. Each pair is tagged **Bullish / Bearish / Neutral** in a compact, color-coded table. Alerts fire when **all three** trends align (all bullish or all bearish).
**How to use**
1. Add the indicator to any crypto chart.
2. Set the three symbols (defaults: BNB/USDT, BTC/USDT, BNB/BTC) and optionally choose a signal timeframe.
3. Tune **Fast EMA**, **Slow EMA**, **Slope Lookback**, and **Min |Slope| %** to filter noise and require stronger momentum.
4. Create alerts: *Add alert →* choose the indicator and select **All Three Bullish**, **All Three Bearish**, or **All Three Aligned**.
**Logic**
* Bullish: `EMA_fast > EMA_slow` **and** fast EMA slope ≥ threshold
* Bearish: `EMA_fast < EMA_slow` **and** fast EMA slope ≤ −threshold
* Otherwise: Neutral
Tip: The **COIN/BTC** row reflects relative strength vs BTC—use it to avoid chasing coins that lag the benchmark. (For educational purposes; not financial advice.)
Advanced Smart Trading Suite with OTE═══════════════════════════════════════
ADVANCED SMART TRADING SUITE WITH OPTIMAL TRADE ENTRY
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A comprehensive institutional trading system combining multiple advanced concepts including multi-timeframe liquidity analysis, order blocks, fair value gaps, and optimal trade entry zones. Features optional anti-repainting controls for confirmed signal generation.
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WHAT THIS INDICATOR DOES
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This all-in-one trading suite provides:
- Multi-Timeframe Liquidity Detection - HTF (Higher Timeframe), LTF (Lower Timeframe), and current timeframe liquidity sweep identification
- Order Blocks - Institutional accumulation/distribution zones with enhanced detection
- Fair Value Gaps (FVG) - Price imbalance detection
- Inverse Fair Value Gaps (iFVG) - Counter-trend imbalance zones
- Optimal Trade Entry (OTE) Zones - Fibonacci retracement-based entry zones (0.618-0.786)
- Trading Sessions - Asian, London, and New York session visualization
- Anti-Repainting Controls - Optional confirmed signals with adjustable confirmation bars
- Comprehensive Alert System - Notifications for all major events
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HOW IT WORKS
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ANTI-REPAINTING SYSTEM:
This indicator includes optional anti-repainting controls that fundamentally change how signals are generated:
Confirmed Mode (Recommended):
- Signals wait for confirmation bars before appearing
- No repainting - what you see is final
- Adjustable confirmation period (1-5 bars)
- Slight lag in signal generation
- Better for backtesting and systematic trading
Live Mode:
- Signals appear immediately as patterns develop
- May repaint as new bars form
- Faster signal generation
- Better for discretionary real-time trading
The confirmation system affects all features: liquidity sweeps, order blocks, FVGs, and OTE zones.
LIQUIDITY SWEEP DETECTION:
Three-Tier System:
1. Current Timeframe Liquidity:
- Detects swing highs/lows on chart timeframe
- Configurable lookback and confirmation periods
- Session-tagged for context (Asian/London/NY)
2. HTF (Higher Timeframe) Key Liquidity:
- Default: 4H timeframe (configurable to Daily/Weekly)
- Strength-based filtering using ATR multipliers
- Distance-based clustering prevention
- Only strongest levels displayed (top 1-10)
- Labels show timeframe and strength rating
3. LTF (Lower Timeframe) Key Liquidity:
- Default: 1H timeframe (configurable)
- Precision entry/exit levels
- Strength-based ranking
- Distance filtering to avoid clutter
Sweep Detection Methods:
- Wick Break: Any wick beyond the level
- Close Break: Close price beyond the level
- Full Retrace: Break and close back inside (stop hunt detection)
Buffer System:
- Configurable ATR-based buffer for sweep confirmation
- Prevents false positives from minor price fluctuations
ORDER BLOCKS (Enhanced):
Detection Methodology:
- Identifies the last opposing candle before significant structure break
- Bullish OB: Last red candle before bullish break
- Bearish OB: Last green candle before bearish break
Enhanced Filters:
1. Size Filter:
- Minimum order block size (ATR-based)
- Ensures significant zones only
2. Volume Filter:
- Requires above-average volume (configurable multiplier)
- Confirms institutional participation
3. Imbalance Filter:
- Requires strong directional move after OB formation
- Validates true institutional activity
Violation Detection:
- Wick-based: Any wick through the zone
- Close-based: Close price through the zone
- Automatic removal of broken order blocks
FAIR VALUE GAPS (FVG):
Bullish FVG: Gap between candle 3 low and candle 1 high (three-bar pattern)
Bearish FVG: Gap between candle 3 high and candle 1 low
Requirements:
- Minimum gap size (ATR-based)
- Clear price imbalance
- No overlap between the three candles
Fill Detection:
- Configurable fill threshold (default 50%)
- Tracks partial and complete fills
- Removes filled gaps to keep chart clean
INVERSE FAIR VALUE GAPS (iFVG):
What are iFVGs:
- Counter-trend FVGs that form after original FVG is filled
- Indicate potential reversal or continuation failure
- Form within specific timeframe after original FVG
Detection Rules:
- Must occur after a FVG is filled
- Must form within 20 bars of original FVG
- Minimum size requirement (ATR-based)
- Opposite direction to original FVG
Visual Distinction:
- Dashed border boxes
- Different color scheme from regular FVGs
- Combined labels when FVG and iFVG overlap
OPTIMAL TRADE ENTRY (OTE) ZONES:
Based on Fibonacci retracement principles used by institutional traders:
Concept:
After a structure break (swing high/low violation), price often retraces to specific Fibonacci levels before continuing. The OTE zone (0.618 to 0.786) represents the optimal entry area.
Bullish OTE Formation:
1. Swing low is formed
2. Structure breaks above previous swing high (bullish structure break)
3. Price retraces into 0.618-0.786 Fibonacci zone
4. Entry signal when price enters and holds in OTE zone
Bearish OTE Formation:
1. Swing high is formed
2. Structure breaks below previous swing low (bearish structure break)
3. Price retraces into 0.618-0.786 Fibonacci zone
4. Entry signal when price enters and holds in OTE zone
Key Fibonacci Levels:
- 0.618 (Golden ratio - primary target)
- 0.705 (Square root of 0.5 - institutional level)
- 0.786 (Square root of 0.618 - deep retracement)
Structure Break Requirement:
- Optional setting to require confirmed structure break
- Prevents premature OTE zone identification
- Ensures proper swing structure is established
Entry/Exit Tracking:
- Green checkmark: Price entered OTE zone validly
- Red X: Price exited OTE zone (stop or target)
- Real-time status monitoring
TRADING SESSIONS:
Displays three major trading sessions with full customization:
Asian Session (Tokyo + Sydney):
- Default: 01:00-13:00 UTC+4
- Typically lower volatility
- Sets up key levels for London open
London Session:
- Default: 11:00-20:00 UTC+4
- Highest liquidity period
- Major institutional moves
New York Session:
- Default: 16:00-01:00 UTC+4
- US market hours
- High impact news events
Features:
- Real-time status indicators (🟢 Open / 🔴 Closed)
- Session high/low tracking
- Overlap detection and highlighting
- Historical session display (0-30 days)
- Customizable colors and borders
───────────────────────────────────────
HOW TO USE
───────────────────────────────────────
MASTER CONTROLS:
Enable/disable major features independently:
- Trading Sessions
- Liquidity Sweeps (Current TF)
- HTF Liquidity Sweeps
- LTF Liquidity Sweeps
- Order Blocks
- Fair Value Gaps
- Inverse Fair Value Gaps
- Optimal Trade Entry Zones
ANTI-REPAINTING SETUP:
For Backtesting/Systematic Trading:
1. Enable "Use Confirmed Signals"
2. Set Confirmation Bars to 2-3
3. All signals will wait for confirmation
4. No repainting will occur
For Real-Time Discretionary Trading:
1. Disable "Use Confirmed Signals"
2. Signals appear immediately
3. Be aware signals may adjust with new bars
MULTI-TIMEFRAME LIQUIDITY STRATEGY:
Top-Down Analysis:
1. Identify HTF liquidity levels (4H/Daily) for major targets
2. Find LTF liquidity levels (1H) for entry refinement
3. Wait for HTF liquidity sweep (liquidity grab)
4. Enter on LTF order block in direction of HTF sweep
5. Target next HTF or LTF liquidity level
Liquidity Sweep Trading:
1. HTF liquidity sweep = major institutional move
2. Look for immediate reversal or continuation
3. Use order blocks for entry timing
4. Place stops beyond the swept liquidity
SESSION-BASED TRADING:
Asian Session Strategy:
1. Identify Asian session high/low
2. Wait for London or NY session to open
3. Trade breakouts of Asian range
4. Target previous day's highs/lows
London/NY Session Strategy:
1. Watch for liquidity sweeps at session open
2. Enter on order block confirmation
3. Use OTE zones for retracement entries
4. Target session high/low or HTF liquidity
OTE ZONE TRADING:
Setup Identification:
1. Wait for clear swing high/low formation
2. Confirm structure break in intended direction
3. Monitor for price retracement to 0.618-0.786 zone
4. Enter when price enters OTE zone with confirmation
Entry Rules:
- Bullish: Long when price enters OTE zone from above
- Bearish: Short when price enters OTE zone from below
- Stop loss: Beyond 0.786 level or swing extreme
- Target: Previous swing high/low or HTF liquidity
Exit Management:
- Indicator tracks when price exits OTE zone
- Red X indicates position should be managed/closed
- Use order blocks or FVGs for partial profit targets
FAIR VALUE GAP STRATEGY:
FVG Entry Method:
1. Wait for FVG formation
2. Monitor for price return to FVG
3. Enter on first touch of FVG zone
4. Stop beyond FVG boundary
5. Target: Fill of FVG or next liquidity level
iFVG Reversal Strategy:
1. Original FVG is filled
2. iFVG forms in opposite direction
3. Indicates failed move or reversal
4. Enter on iFVG confirmation
5. Target: Opposite end of range or next structure
Combined FVG + iFVG:
- When both overlap, indicator combines labels
- Represents high-probability reversal zone
- Use with order blocks for confirmation
ORDER BLOCK STRATEGY:
Entry Approach:
1. Wait for order block formation after structure break
2. Enter on first return to order block
3. Place stop beyond order block boundary
4. Target: Next order block or liquidity level
Confirmation Layers:
- Order block + FVG = strong confluence
- Order block + Liquidity sweep = institutional setup
- Order block + OTE zone = optimal entry
- Order block + Session open = high probability
Volume Analysis:
- Wider colored section = stronger institutional interest
- Use volume bars to confirm order block strength
- Higher volume order blocks = more reliable
───────────────────────────────────────
CONFIGURATION GUIDE
───────────────────────────────────────
LIQUIDITY SETTINGS:
Lookback: 5-30 bars
- Lower = more frequent, sensitive levels
- Higher = fewer, more significant levels
- Recommended: 15 for intraday, 20-25 for swing
Sweep Detection Type:
- Wick Break: Most sensitive
- Close Break: More conservative
- Full Retrace: Stop hunt detection
Sweep Buffer: 0-1.0 ATR
- Adds distance requirement for sweep confirmation
- Prevents false positives
- Recommended: 0.1 for most markets
HTF/LTF LIQUIDITY:
HTF Timeframe Selection:
- Swing trading: 1D or 1W
- Day trading: 4H or 1D
- Scalping: 1H or 4H
LTF Timeframe Selection:
- Swing trading: 4H or 1D
- Day trading: 1H or 4H
- Scalping: 15m or 1H
Strength Filters:
- Min Pivot Strength: Higher = fewer, stronger levels
- Min Distance: Higher = less clustering
- Recommended: 2.0 ATR for HTF, 1.5 ATR for LTF
ORDER BLOCK SETTINGS:
Swing Length: 5-20
- Controls sensitivity of structure break detection
- Lower = more order blocks, faster signals
- Higher = fewer order blocks, stronger signals
- Recommended: 8-10 for most timeframes
Enhancement Filters:
- Min Size: 0.5-1.5 ATR typical
- Volume Multiplier: 1.2-2.0 typical
- Imbalance: Enable for strongest signals only
OTE SETTINGS:
Swing Length: 5-50
- Controls OTE zone formation sensitivity
- Lower = more frequent, smaller moves
- Higher = fewer, larger trend moves
- Recommended: 10-15 for intraday
Require Structure Break:
- Enabled: Only shows OTE after confirmed break
- Disabled: Shows potential OTE zones earlier
- Recommended: Enable for higher probability setups
FVG SETTINGS:
Min FVG Size: 0.1-2.0 ATR
- Lower = more gaps detected
- Higher = only significant gaps
- Recommended: 0.5 ATR for most markets
Fill Threshold: 0.1-1.0
- Determines when gap is considered "filled"
- 0.5 = 50% fill required
- Higher = more conservative
iFVG Min Size: 0.1-2.0 ATR
- Typically smaller than regular FVG
- Recommended: 0.3 ATR
ALERT SYSTEM:
Available Alerts:
- Liquidity Sweeps (Current TF)
- HTF Liquidity Sweeps
- LTF Liquidity Sweeps
- Session Changes (Open/Close)
- OTE Entry Signals
Alert Setup:
1. Enable alerts in settings
2. Select specific alert types
3. Create TradingView alert using "Any alert() function call"
4. Configure delivery method (mobile, email, webhook)
Alert Messages Include:
- Event type and direction
- Confirmation status (if using confirmed mode)
- Price level
- Timeframe (for liquidity sweeps)
───────────────────────────────────────
RECOMMENDED CONFIGURATIONS
───────────────────────────────────────
For Day Trading (15m-1H charts):
- HTF Liquidity: 4H
- LTF Liquidity: 1H
- Liquidity Lookback: 15
- Order Block Swing Length: 8
- OTE Swing Length: 10
- Confirmed Signals: Enabled, 2 bars
For Swing Trading (4H-1D charts):
- HTF Liquidity: 1D or 1W
- LTF Liquidity: 4H
- Liquidity Lookback: 20
- Order Block Swing Length: 10
- OTE Swing Length: 15
- Confirmed Signals: Enabled, 2-3 bars
For Scalping (5m-15m charts):
- HTF Liquidity: 1H or 4H
- LTF Liquidity: 15m or 1H
- Liquidity Lookback: 10-12
- Order Block Swing Length: 6-8
- OTE Swing Length: 8
- Confirmed Signals: Optional
───────────────────────────────────────
PERFORMANCE OPTIMIZATION
───────────────────────────────────────
This indicator is optimized with:
- max_bars_back declarations for efficient lookback
- Automatic memory cleanup every 10 bars
- Conditional execution based on enabled features
- Drawing object limits to prevent performance degradation
Memory Management:
- Old liquidity zones automatically removed
- Filled FVGs/iFVGs cleaned up
- Exited OTE zones removed
- Mitigated order blocks deleted
Best Practices:
- Enable only needed features
- Use appropriate timeframe combinations
- Don't display excessive historical sessions
- Monitor drawing object counts on lower timeframes
───────────────────────────────────────
EDUCATIONAL DISCLAIMER
───────────────────────────────────────
This indicator combines multiple institutional trading concepts:
- Liquidity theory (where orders accumulate)
- Order flow analysis (institutional footprints)
- Price imbalance detection (FVGs)
- Fibonacci retracement theory (OTE zones)
- Session-based trading (time-of-day patterns)
All calculations use standard technical analysis methods:
- Pivot high/low detection
- ATR-based normalization
- Volume analysis
- Fibonacci ratios
- Time-based filtering
The indicator identifies potential setups but does not predict future price movements. Success depends on proper application within a complete trading plan including risk management, position sizing, and market context analysis.
───────────────────────────────────────
USAGE DISCLAIMER
───────────────────────────────────────
This tool is for educational and analytical purposes. Trading involves substantial risk of loss. The anti-repainting features provide confirmed signals but do not guarantee profitability. Always conduct independent analysis, use proper risk management, and never risk capital you cannot afford to lose. Past performance does not indicate future results.
Quantum Fluxtrend [CHE] Quantum Fluxtrend — A dynamic Supertrend variant with integrated breakout event tracking and VWAP-guided risk management for clearer trend decisions.
Summary
The Quantum Fluxtrend builds on traditional Supertrend logic by incorporating a midline derived from smoothed high and low values, creating adaptive bands that respond to market range expansion or contraction. This results in fewer erratic signals during volatile periods and smoother tracking in steady trends, while an overlaid event system highlights breakout confirmations, potential traps, or continuations with visual lines, labels, and percentage deltas from the close. Users benefit from real-time VWAP calculations anchored to events, providing dynamic stop-loss suggestions to help manage exits without manual adjustments. Overall, it layers signal robustness with actionable annotations, reducing noise in fast-moving charts.
Motivation: Why this design?
Standard Supertrend indicators often generate excessive flips in choppy conditions or lag behind in low-volatility drifts, leading to whipsaws that erode confidence in trend direction. This design addresses that by centering bands around a midline that reflects recent price spreads, ensuring adjustments are proportional to observed variability. The added event layer captures regime shifts explicitly, turning abstract crossovers into labeled milestones with trailing VWAP for context, which helps traders distinguish genuine momentum from fleeting noise without over-relying on raw price action.
What’s different vs. standard approaches?
- Baseline reference: Diverges from the classic Supertrend, which uses average true range for fixed offsets from a median price.
- Architecture differences:
- Bands form around a central line averaged from smoothed highs and lows, with offsets scaled by half the range between those smooths.
- Regime direction persists until a clear breach of the prior opposite band, preventing premature reversals.
- Event visualization draws persistent lines from flip points, updating labels based on price sustainment relative to the trigger level.
- VWAP resets at each event, accumulating volume-weighted prices forward for a trailing reference.
- Practical effect: Charts show fewer direction changes overall, with color-coded annotations that evolve from initial breakout to continuation or trap status, making it easier to spot sustained moves early. VWAP lines provide a volume-informed anchor that curves with price, offering visual cues for adverse drifts.
How it works (technical)
The process starts by smoothing high and low prices over a user-defined period to form upper and lower references. A midline sits midway between them, and half the spread acts as a base for band offsets, adjusted by a multiplier to widen or narrow sensitivity. On each bar, the close is checked against the previous bar's opposite band: crossing above expands the lower band downward in uptrends, or below contracts the upper band upward in downtrends, creating a ratcheting effect that locks in direction until breached.
Persistent state tracks the current regime, seeding initial bands from the smoothed values if no prior data exists. Flips trigger new horizontal lines at the breach level, styled by direction, alongside labels that monitor sustainment—price holding above for up-flips or below for down-flips keeps the regime, while reversal flags a trap.
Separately, at each flip, a dashed VWAP line initializes at the breach price and extends forward, accumulating the product of typical prices and volumes divided by total volume. This yields a curving reference that updates bar-by-bar. Warnings activate if price strays adversely from this VWAP, tinting the background for quick alerts.
No higher timeframe data is pulled, so all computations run on the chart's native resolution, avoiding lookahead biases unless repainting is enabled via input.
Parameter Guide
SMA Length — Controls smoothing of highs and lows for midline and range base; longer values dampen noise but increase lag. Default: 20. Trade-offs: Shortens responsiveness in trends (e.g., 10–14) but risks more flips; extend to 30+ for stability in ranging markets.
Multiplier — Scales band offsets from the half-range; higher amplifies to capture bigger swings. Default: 1.0. Trade-offs: Above 1.5 widens for volatile assets, reducing false signals; below 0.8 tightens for precision but may miss subtle shifts.
Show Bands — Toggles visibility of basic and adjusted band lines for reference. Default: false. Tip: Enable briefly to verify alignment with price action.
Show Background Color — Displays red tint on VWAP adverse crosses for visual warnings. Default: false. Trade-offs: Helps in live monitoring but can clutter clean charts.
Line Width — Sets thickness for event and VWAP lines. Default: 2. Tip: Thicker (3–5) for emphasis on key levels.
+Bars after next event — Extends old lines briefly before cleanup on new flips. Default: 20. Trade-offs: Longer preserves history (40+) at resource cost; shorter keeps charts tidy.
Allow Repainting — Permits live-bar updates for smoother real-time view. Default: false. Tip: Disable for backtest accuracy.
Extension 1 Settings (Show, Width, Size, Decimals, Colors, Alpha) — Manages dotted connector from event label to current close, showing percentage change. Defaults: Shown, width 2, normal size, 2 decimals, lime/red for gains/losses, gray line, 90% transparent background. Trade-offs: Fewer decimals for clean display; adjust alpha for readability.
Extension 2 Settings (Show, Method, Stop %, Ticks, Decimals, Size, Color, Inherit, Alpha) — Positions stop label at VWAP end, offset by percent or ticks. Defaults: Shown, percent method, 1.0%, 20 ticks, 4 decimals, normal size, white text, inherit tint, 0% alpha. Trade-offs: Percent for proportional risk; ticks for fixed distance in tick-based assets.
Alert Toggles — Enables notifications for breakouts, continuations, traps, or VWAP warnings. All default: true. Tip: Layer with chart alerts for multi-condition setups.
Reading & Interpretation
The main Supertrend line colors green for up-regimes (price above lower band) and red for down (below upper band), serving as a dynamic support/resistance trail. Flip shapes (up/down triangles) mark regime changes at band breaches.
Event lines extend horizontally from flips: green for bull, red for bear. Labels start blank and update to "Bull/Bear Cont." if price sustains the direction, or "Trap" if it reverses, with colors shifting lime/red/gray accordingly. A dotted vertical links the trailing label to the current close, mid-labeled with the percentage delta (positive green, negative red).
VWAP dashes yellow (bull) or orange (bear) from the event, curving to reflect volume-weighted average. At its end, a left-aligned label shows suggested stop price, annotated with offset details. Background red hints at weakening if price crosses VWAP opposite the regime.
Deltas near zero suggest consolidation; widening extremes signal momentum buildup or exhaustion.
Practical Workflows & Combinations
- Trend following: Enter long on green flip shapes confirmed by higher highs, using the event line as initial stop below. Trail stops to VWAP for bull runs, exiting on trap labels or red background warnings. Filter with volume spikes to avoid low-conviction breaks.
- Exits/Stops: Conservative: Set hard stops at suggested SL labels. Aggressive: Hold through minor traps if delta stays positive, but cut on regime flip. Pair with momentum oscillators for overbought pullbacks.
- Multi-asset/Multi-TF: Defaults suit forex/stocks on 15m–4H; for crypto, bump multiplier to 1.5 for volatility. Scale SMA length proportionally across timeframes (e.g., double for daily). Combine with structure tools like Fibonacci for confluence on event lines.
Behavior, Constraints & Performance
Live bars update lines and labels dynamically if repainting is allowed, but signals confirm on close for stability—flips only trigger post-bar. No higher timeframe calls, so no inherent lookahead, though volume weighting assumes continuous data.
Resources cap at 1000 bars back, 50 lines/labels max; events prune old ones on new flips to stay under budget, with brief extensions for visibility. Arrays or loops absent, keeping it lightweight.
Known limits include lag in extreme gaps (e.g., overnight opens) where bands may not adjust instantly, and VWAP sensitivity to sparse volume in illiquid sessions.
Sensible Defaults & Quick Tuning
Start with SMA 20, multiplier 1.0 for balanced response across majors. For choppy pairs: Lengthen SMA to 30, multiplier 0.8 to tighten bands and cut flips. For trending equities: Shorten to 14, multiplier 1.2 for quicker entries. If traps dominate, enable bands to inspect range compression; for sluggish signals, reduce extension bars to focus on recent events.
What this indicator is—and isn’t
This serves as a visualization and signal layer for trend regimes and breakouts, highlighting sustainment via annotations and risk cues through VWAP—ideal atop price action for confirmation. It is not a standalone system, predictive oracle, or risk calculator; always integrate with broader analysis, position sizing, and stops. Use responsibly as an educational tool.
Disclaimer
The content provided, including all code and materials, is strictly for educational and informational purposes only. It is not intended as, and should not be interpreted as, financial advice, a recommendation to buy or sell any financial instrument, or an offer of any financial product or service. All strategies, tools, and examples discussed are provided for illustrative purposes to demonstrate coding techniques and the functionality of Pine Script within a trading context.
Any results from strategies or tools provided are hypothetical, and past performance is not indicative of future results. Trading and investing involve high risk, including the potential loss of principal, and may not be suitable for all individuals. Before making any trading decisions, please consult with a qualified financial professional to understand the risks involved.
By using this script, you acknowledge and agree that any trading decisions are made solely at your discretion and risk.
Do not use this indicator on Heikin-Ashi, Renko, Kagi, Point-and-Figure, or Range charts, as these chart types can produce unrealistic results for signal markers and alerts.
Best regards and happy trading
Chervolino
MTF K-Means Price Regimes [matteovesperi] ⚠️ The preview uses a custom example to identify support/resistance zones. due to the fact that this identifier clusterizes, this is possible. this example was set up "in a hurry", therefore it has a possible inaccuracy. When setting up the indicator, it is extremely important to select the correct parameters and double-check them on the selected history.
📊 OVERVIEW
Purpose
MTF K-Means Price Regimes is a TradingView indicator that automatically identifies and classifies the current market regime based on the K-Means machine learning algorithm. The indicator uses data from a higher timeframe (Multi-TimeFrame, MTF) to build stable classification and applies it to the working timeframe in real-time.
Key Features
✅ Automatic market regime detection — the algorithm finds clusters of similar market conditions
✅ Multi-timeframe (MTF) — clustering on higher TF, application on lower TF
✅ Adaptive — model recalculates when a new HTF bar appears with a rolling window
✅ Non-Repainting — classification is performed only on closed bars
✅ Visualization — bar coloring + information panel with cluster characteristics
✅ Flexible settings — from 2 to 10 clusters, customizable feature periods, HTF selection
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
🔬 TECHNICAL DETAILS
K-Means Clustering Algorithm
What is K-Means?
K-Means is one of the most popular clustering algorithms (unsupervised machine learning). It divides a dataset into K groups (clusters) so that similar elements are within each cluster, and different elements are between clusters.
Algorithm objective:
Minimize within-cluster variance (sum of squared distances from points to their cluster center).
How Does K-Means Work in Our Indicator?
Step 1: Data Collection
The indicator accumulates history from the higher timeframe (HTF):
RSI (Relative Strength Index) — overbought/oversold indicator
ATR% (Average True Range as % of price) — volatility indicator
ΔP% (Price Change in %) — trend strength and direction indicator
By default, 200 HTF bars are accumulated (clusterLookback parameter).
Step 2: Creating Feature Vectors
Each HTF bar is described by a three-dimensional vector:
Vector =
Step 3: Normalization (Z-Score)
All features are normalized to bring them to a common scale:
Normalized_Value = (Value - Mean) / StdDev
This is critically important, as RSI is in the range 0-100, while ATR% and ΔP% have different scales. Without normalization, one feature would dominate over others.
Step 4: K-Means++ Centroid Initialization
Instead of random selection of K initial centers, an improved K-Means++ method is used:
First centroid is randomly selected from the data
Each subsequent centroid is selected with probability proportional to the square of the distance to the nearest already selected centroid
This ensures better initial centroid distribution and faster convergence
Step 5: Iterative Optimization (Lloyd's Algorithm)
Repeat until convergence (or maxIterations):
1. Assignment step:
For each point find the nearest centroid and assign it to this cluster
2. Update step:
Recalculate centroids as the average of all points in each cluster
3. Convergence check:
If centroids shifted less than 0.001 → STOP
Euclidean distance in 3D space is used:
Distance = sqrt((RSI1 - RSI2)² + (ATR1 - ATR2)² + (ΔP1 - ΔP2)²)
Step 6: Adaptive Update
With each new HTF bar:
The oldest bar is removed from history (rolling window method)
New bar is added to history
K-Means algorithm is executed again on updated data
Model remains relevant for current market conditions
Real-Time Classification
After building the model (clusters + centroids), the indicator works in classification mode:
On each closed bar of the current timeframe, RSI, ATR%, ΔP% are calculated
Feature vector is normalized using HTF statistics (Mean/StdDev)
Distance to all K centroids is calculated
Bar is assigned to the cluster with minimum distance
Bar is colored with the corresponding cluster color
Important: Classification occurs only on a closed bar (barstate.isconfirmed), which guarantees no repainting .
Data Architecture
Persistent variables (var):
├── featureVectors - Normalized HTF feature vectors
├── centroids - Cluster center coordinates (K * 3 values)
├── assignments - Assignment of each HTF bar to a cluster
├── htfRsiHistory - History of RSI values from HTF
├── htfAtrHistory - History of ATR values from HTF
├── htfPcHistory - History of price changes from HTF
├── htfCloseHistory - History of close prices from HTF
├── htfRsiMean, htfRsiStd - Statistics for RSI normalization
├── htfAtrMean, htfAtrStd - Statistics for ATR normalization
├── htfPcMean, htfPcStd - Statistics for Price Change normalization
├── isCalculated - Model readiness flag
└── currentCluster - Current active cluster
All arrays are synchronized and updated atomically when a new HTF bar appears.
Computational Complexity
Data collection: O(1) per bar
K-Means (one pass):
- Assignment: O(N * K) where N = number of points, K = number of clusters
- Update: O(N * K)
- Total: O(N * K * I) where I = number of iterations (usually 5-20)
Example: With N=200 HTF bars, K=5 clusters, I=20 iterations:
200 * 5 * 20 = 20,000 operations (executes quickly)
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📖 USER GUIDE
Quick Start
1. Adding the Indicator
TradingView → Indicators → Favorites → MTF K-Means Price Regimes
Or copy the code from mtf_kmeans_price_regimes.pine into Pine Editor.
2. First Launch
When adding the indicator to the chart, you'll see a table in the upper right corner:
┌─────────────────────────┐
│ Status │ Collecting HTF │
├─────────────────────────┤
│ Collected│ 15 / 50 │
└─────────────────────────┘
This means the indicator is accumulating history from the higher timeframe. Wait until the counter reaches the minimum (default 50 bars for K=5).
3. Active Operation
After data collection is complete, the main table with cluster information will appear:
┌────┬──────┬──────┬──────┬──────────────┬────────┐
│ ID │ RSI │ ATR% │ ΔP% │ Description │Current │
├────┼──────┼──────┼──────┼──────────────┼────────┤
│ 1 │ 68.5 │ 2.15 │ 1.2 │ High Vol,Bull│ │
│ 2 │ 52.3 │ 0.85 │ 0.1 │ Low Vol,Flat │ ► │
│ 3 │ 35.2 │ 1.95 │ -1.5 │ High Vol,Bear│ │
└────┴──────┴──────┴──────┴──────────────┴────────┘
The arrow ► indicates the current active regime. Chart bars are colored with the corresponding cluster color.
Customizing for Your Strategy
Choosing Higher Timeframe (HTF)
Rule: HTF should be at least 4 times higher than the working timeframe.
| Working TF | Recommended HTF |
|------------|-----------------|
| 1 min | 15 min - 1H |
| 5 min | 1H - 4H |
| 15 min | 4H - D |
| 1H | D - W |
| 4H | D - W |
| D | W - M |
HTF Selection Effect:
Lower HTF (closer to working TF): More sensitive, frequently changing classification
Higher HTF (much larger than working TF): More stable, long-term regime assessment
Number of Clusters (K)
K = 2-3: Rough division (e.g., "uptrend", "downtrend", "flat")
K = 4-5: Optimal for most cases (DEFAULT: 5)
K = 6-8: Detailed segmentation (requires more data)
K = 9-10: Very fine division (only for long-term analysis with large windows)
Important constraint:
clusterLookback ≥ numClusters * 10
I.e., for K=5 you need at least 50 HTF bars, for K=10 — at least 100 bars.
Clustering Depth (clusterLookback)
This is the rolling window size for building the model.
50-100 HTF bars: Fast adaptation to market changes
200 HTF bars: Optimal balance (DEFAULT)
500-1000 HTF bars: Long-term, stable model
If you get an "Insufficient data" error:
Decrease clusterLookback
Or select a lower HTF (e.g., "4H" instead of "D")
Or decrease numClusters
Color Scheme
Default 10 colors:
Red → Often: strong bearish, high volatility
Orange → Transition, medium volatility
Yellow → Neutral, decreasing activity
Green → Often: strong bullish, high volatility
Blue → Medium bullish, medium volatility
Purple → Oversold, possible reversal
Fuchsia → Overbought, possible reversal
Lime → Strong upward momentum
Aqua → Consolidation, low volatility
White → Undefined regime (rare)
Important: Cluster colors are assigned randomly at each model recalculation! Don't rely on "red = bearish". Instead, look at the description in the table (RSI, ATR%, ΔP%).
You can customize colors in the "Colors" settings section.
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⚙️ INDICATOR PARAMETERS
Main Parameters
Higher Timeframe (htf)
Type: Timeframe selection
Default: "D" (daily)
Description: Timeframe on which the clustering model is built
Recommendation: At least 4 times larger than your working TF
Clustering Depth (clusterLookback)
Type: Integer
Range: 50 - 2000
Default: 200
Description: Number of HTF bars for building the model (rolling window size)
Recommendation:
- Increase for more stable long-term model
- Decrease for fast adaptation or if there's insufficient historical data
Number of Clusters (K) (numClusters)
Type: Integer
Range: 2 - 10
Default: 5
Description: Number of market regimes the algorithm will identify
Recommendation:
- K=3-4 for simple strategies (trending/ranging)
- K=5-6 for universal strategies
- K=7-10 only when clusterLookback ≥ 100*K
Max K-Means Iterations (maxIterations)
Type: Integer
Range: 5 - 50
Default: 20
Description: Maximum number of algorithm iterations
Recommendation:
- 10-20 is sufficient for most cases
- Increase to 30-50 if using K > 7
Feature Parameters
RSI Period (rsiLength)
Type: Integer
Default: 14
Description: Period for RSI calculation (overbought/oversold feature)
Recommendation:
- 14 — standard
- 7-10 — more sensitive
- 20-25 — more smoothed
ATR Period (atrLength)
Type: Integer
Default: 14
Description: Period for ATR calculation (volatility feature)
Recommendation: Usually kept equal to rsiLength
Price Change Period (pcLength)
Type: Integer
Default: 5
Description: Period for percentage price change calculation (trend feature)
Recommendation:
- 3-5 — short-term trend
- 10-20 — medium-term trend
Visualization
Show Info Panel (showDashboard)
Type: Checkbox
Default: true
Description: Enables/disables the information table on the chart
Cluster Color 1-10
Type: Color selection
Description: Customize colors for visual cluster distinction
Recommendation: Use contrasting colors for better readability
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📊 INTERPRETING RESULTS
Reading the Information Table
┌────┬──────┬──────┬──────┬──────────────┬────────┐
│ ID │ RSI │ ATR% │ ΔP% │ Description │Current │
├────┼──────┼──────┼──────┼──────────────┼────────┤
│ 1 │ 68.5 │ 2.15 │ 1.2 │ High Vol,Bull│ │
│ 2 │ 52.3 │ 0.85 │ 0.1 │ Low Vol,Flat │ ► │
│ 3 │ 35.2 │ 1.95 │ -1.5 │ High Vol,Bear│ │
│ 4 │ 45.0 │ 1.20 │ -0.3 │ Low Vol,Bear │ │
│ 5 │ 72.1 │ 3.05 │ 2.8 │ High Vol,Bull│ │
└────┴──────┴──────┴──────┴──────────────┴────────┘
"ID" Column
Cluster number (1-K). Order doesn't matter.
"RSI" Column
Average RSI value in the cluster (0-100):
< 30: Oversold zone
30-45: Bearish sentiment
45-55: Neutral zone
55-70: Bullish sentiment
> 70: Overbought zone
"ATR%" Column
Average volatility in the cluster (as % of price):
< 1%: Low volatility (consolidation, narrow range)
1-2%: Normal volatility
2-3%: Elevated volatility
> 3%: High volatility (strong movements, impulses)
Compared to the average volatility across all clusters to determine "High Vol" or "Low Vol".
"ΔP%" Column
Average price change in the cluster (in % over pcLength period):
> +0.05%: Bullish regime
-0.05% ... +0.05%: Flat (sideways movement)
< -0.05%: Bearish regime
"Description" Column
Automatic interpretation:
"High Vol, Bull" → Strong upward momentum, high activity
"Low Vol, Flat" → Consolidation, narrow range, uncertainty
"High Vol, Bear" → Strong decline, panic, high activity
"Low Vol, Bull" → Slow growth, low activity
"Low Vol, Bear" → Slow decline, low activity
"Current" Column
Arrow ► shows which cluster the last closed bar of your working timeframe is in.
Typical Cluster Patterns
Example 1: Trend/Flat Division (K=3)
Cluster 1: RSI=65, ATR%=2.5, ΔP%=+1.5 → Bullish trend
Cluster 2: RSI=50, ATR%=0.8, ΔP%=0.0 → Flat/Consolidation
Cluster 3: RSI=35, ATR%=2.3, ΔP%=-1.4 → Bearish trend
Strategy: Open positions when regime changes Flat → Trend, avoid flat.
Example 2: Volatility Breakdown (K=5)
Cluster 1: RSI=72, ATR%=3.5, ΔP%=+2.5 → Strong bullish impulse (high risk)
Cluster 2: RSI=60, ATR%=1.5, ΔP%=+0.8 → Moderate bullish (optimal entry point)
Cluster 3: RSI=50, ATR%=0.7, ΔP%=0.0 → Flat
Cluster 4: RSI=40, ATR%=1.4, ΔP%=-0.7 → Moderate bearish
Cluster 5: RSI=28, ATR%=3.2, ΔP%=-2.3 → Strong bearish impulse (panic)
Strategy: Enter in Cluster 2 or 4, avoid extremes (1, 5).
Example 3: Mixed Regimes (K=7+)
With large K, clusters can represent condition combinations:
High RSI + Low volatility → "Quiet overbought"
Neutral RSI + High volatility → "Uncertainty with high activity"
Etc.
Requires individual analysis of each cluster.
Regime Changes
Important signal: Transition from one cluster to another!
Trading situation examples:
Flat → Bullish trend → Buy signal
Bullish trend → Flat → Take profit, close longs
Flat → Bearish trend → Sell signal
Bearish trend → Flat → Close shorts, wait
You can build a trading system based on the current active cluster and transitions between them.
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💡 USAGE EXAMPLES
Example 1: Scalping with HTF Filter
Task: Scalping on 5-minute charts, but only enter in the direction of the daily regime.
Settings:
Working TF: 5 min
HTF: D (daily)
K: 3 (simple division)
clusterLookback: 100
Logic:
IF current cluster = "Bullish" (ΔP% > 0.5)
→ Look for long entry points on 5M
IF current cluster = "Bearish" (ΔP% < -0.5)
→ Look for short entry points on 5M
IF current cluster = "Flat"
→ Don't trade / reduce risk
Example 2: Swing Trading with Volatility Filtering
Task: Swing trading on 4H, enter only in regimes with medium volatility.
Settings:
Working TF: 4H
HTF: D (daily)
K: 5
clusterLookback: 200
Logic:
Allowed clusters for entry:
- ATR% from 1.5% to 2.5% (not too quiet, not too chaotic)
- ΔP% with clear direction (|ΔP%| > 0.5)
Prohibited clusters:
- ATR% > 3% → Too risky (possible gaps, sharp reversals)
- ATR% < 1% → Too quiet (small movements, commissions eat profit)
Example 3: Portfolio Rotation
Task: Managing a portfolio of multiple assets, allocate capital depending on regimes.
Settings:
Working TF: D (daily)
HTF: W (weekly)
K: 4
clusterLookback: 100
Logic:
For each asset in portfolio:
IF regime = "Strong trend + Low volatility"
→ Increase asset weight in portfolio (40-50%)
IF regime = "Medium trend + Medium volatility"
→ Standard weight (20-30%)
IF regime = "Flat" or "High volatility without trend"
→ Minimum weight or exclude (0-10%)
Example 4: Combining with Other Indicators
MTF K-Means as a filter:
Main strategy: MA Crossover
Filter: MTF K-Means on higher TF
Rule:
IF MA_fast > MA_slow AND Cluster = "Bullish regime"
→ LONG
IF MA_fast < MA_slow AND Cluster = "Bearish regime"
→ SHORT
ELSE
→ Don't trade (regime doesn't confirm signal)
This dramatically reduces false signals in unsuitable market conditions.
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📈 OPTIMIZATION RECOMMENDATIONS
Optimal Settings for Different Styles
Day Trading
Working TF: 5M - 15M
HTF: 1H - 4H
numClusters: 4-5
clusterLookback: 100-150
Swing Trading
Working TF: 1H - 4H
HTF: D
numClusters: 5-6
clusterLookback: 150-250
Position Trading
Working TF: D
HTF: W - M
numClusters: 4-5
clusterLookback: 100-200
Scalping
Working TF: 1M - 5M
HTF: 15M - 1H
numClusters: 3-4
clusterLookback: 50-100
Backtesting
To evaluate effectiveness:
Load historical data (minimum 2x clusterLookback HTF bars)
Apply the indicator with your settings
Study cluster change history:
- Do changes coincide with actual trend transitions?
- How often do false signals occur?
Optimize parameters:
- If too much noise → increase HTF or clusterLookback
- If reaction too slow → decrease HTF or increase numClusters
Combining with Other Techniques
Regime-Based Approach:
MTF K-Means (regime identification)
↓
+---+---+---+
| | | |
v v v v
Trend Flat High_Vol Low_Vol
↓ ↓ ↓ ↓
Strategy_A Strategy_B Don't_trade
Examples:
Trend: Use trend-following strategies (MA crossover, Breakout)
Flat: Use mean-reversion strategies (RSI, Bollinger Bands)
High volatility: Reduce position sizes, widen stops
Low volatility: Expect breakout, don't open positions inside range
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📞 SUPPORT
Report an Issue
If you found a bug or have a suggestion for improvement:
Describe the problem in as much detail as possible
Specify your indicator settings
Attach a screenshot (if possible)
Specify the asset and timeframe where the problem is observed
Session Streaks [LuxAlgo]The Session Streaks tool allows traders to identify whether a session is bullish or bearish on the chart. It also shows the current session streak, or the number of consecutive bullish or bearish sessions.
The tool features a dashboard with information about the session streaks of the underlying product on the chart.
🔶 USAGE
Analyzing session streaks is commonly used for market timing by studying the number of consecutive sessions over time and how long they last before the market changes direction.
We identify a bullish session as one in which the closing price is equal to or greater than the opening price, and a bearish session as one in which the closing price is below the opening price.
Each session is labeled according to its bias (bullish or bearish) and the number of consecutive sessions of the same type that conform the current streak.
🔹 Dashboard
The dashboard at the top shows information about the current session.
Under the "Streaks" header, historical information about session streaks is displayed, divided into bullish and bearish categories.
Number: Total number of streaks.
Median: The average duration of those streaks. We chose the median over the mean to avoid misrepresentation due to outliers.
Mode: The most common streak duration.
As the image shows, for this particular market, there are more bullish streaks than bearish ones. Bullish streaks have an average duration that is longer than that of bearish streaks, and both have the same most common streak duration.
If the current session is bullish and the median streak duration for bullish sessions is three, then we could consider scenarios in which the next two sessions are bullish.
🔶 DETAILS
🔹 Streaks On Larger Timeframes
On timeframes lower than or equal to Daily, the tool identifies each consecutive session, but this behavior changes on larger timeframes.
On timeframes larger than daily, the tool identifies the last session of each bar. Let's use the chart in the image as a reference.
At the top of the image, there is a daily chart where each session corresponds to each candle. One candle equals one day.
In the middle, we have a weekly chart where each session is the last session of each week, which is usually Friday for the Nasdaq 100 futures contract. The levels and labels displayed correspond to the last session within each candle, which is the last day of each week.
The levels and labels on the monthly chart correspond to the last session of each month, which is the last day of each month.
🔹 Gradient Style
Traders can choose between two different color gradients for the session background. Each gradient provides different information about price behavior within each session.
Horizontal: Green indicates prices at the top of the session range and red indicates prices at the bottom.
Vertical: Green indicates prices that are equal to or greater than the open price and red indicates prices that are below the open price of the session.
🔶 SETTINGS
🔹 Dashboard
Dashboard: Enable or disable the dashboard.
Position: Select the location of the dashboard.
Size: Select the dashboard size.
🔹 Style
Bullish: Select a color for bullish sessions.
Bearish: Select a color for bearish sessions.
Transparency: Select a transparency level from 100 to 0.
Gradient: Select a horizontal or vertical gradient.
pine script tradingbot - many ema oscillator## 🧭 **Many EMA Oscillator (TradingView Pine Script Indicator)**
*A multi-layer EMA differential oscillator for trend strength and momentum analysis*
---
### 🧩 **Overview**
The **Many EMA Oscillator** is a **TradingView Pine Script indicator** designed to help traders visualize **trend direction**, **momentum strength**, and **multi-timeframe EMA alignment** in one clean oscillator panel.
It’s a **custom EMA-based trend indicator** that shows how fast or slow different **Exponential Moving Averages (EMAs)** are expanding or contracting — helping you identify **bullish and bearish momentum shifts** early.
This **Pine Script EMA indicator** is especially useful for traders looking to combine multiple **EMA signals** into one **momentum oscillator** for better clarity and precision.
---
### ⚙️ **How It Works**
1. **Multiple EMA Layers:**
The indicator calculates seven **EMAs** (default: 20, 50, 100, 150, 200, 300) and applies a **smoothing filter** using another EMA (default smoothing = 20).
This removes short-term noise and gives a smoother, professional-grade momentum reading.
2. **EMA Gap Analysis:**
The oscillator measures the **difference between consecutive EMAs**, revealing how trend layers are separating or converging.
```
diff1 = EMA(20) - EMA(50)
diff2 = EMA(50) - EMA(100)
diff3 = EMA(100) - EMA(150)
diff4 = EMA(150) - EMA(200)
diff5 = EMA(200) - EMA(300)
```
These gaps (or “differentials”) show **trend acceleration or compression**, acting like a **multi-EMA MACD system**.
3. **Color-Coded Visualization:**
Each differential (`diff1`–`diff5`) is plotted as a **histogram**:
- 🟢 **Green bars** → EMAs expanding → bullish momentum growing
- 🔴 **Red bars** → EMAs contracting → bearish momentum or correction
This gives a clean, compact view of **trend strength** without cluttering your chart.
4. **Automatic Momentum Signals:**
- **🟡 Up Triangle** → All EMA gaps increasing → strong bullish trend alignment
- **⚪ Down Triangle** → All EMA gaps decreasing → trend weakening or bearish transition
---
### 📊 **Inputs**
| Input | Default | Description |
|-------|----------|-------------|
| `smmoth_emas` | 20 | Smoothing factor for all EMAs |
| `Length2`–`Length7` | 20–300 | Adjustable EMA periods |
| `Length21`, `Length31`, `Length41`, `Length51` | Optional | For secondary EMA analysis |
---
### 🧠 **Interpretation Guide**
| Observation | Meaning |
|--------------|----------|
| Increasing green bars | Trend acceleration and bullish continuation |
| Decreasing red bars | Trend exhaustion or sideways consolidation |
| Yellow triangles | All EMA layers aligned bullishly |
| White triangles | All EMA layers aligned bearishly |
This **EMA oscillator for TradingView** simplifies **multi-EMA trading strategies** by showing alignment strength in one place.
It works great for **swing traders**, **scalpers**, and **trend-following systems**.
---
### 🧪 **Best Practices for Use**
- Works on **all TradingView timeframes** (1m, 5m, 1h, 1D, etc.)
- Suitable for **stocks, forex, crypto, and indices**
- Combine with **RSI**, **MACD**, or **price action** confirmation
- Excellent for detecting **EMA compression zones**, **trend continuation**, or **momentum shifts**
- Can be used as part of a **multi-EMA trading strategy** or **trend strength indicator setup**
---
### 💡 **Why It Stands Out**
- 100% built in **Pine Script v6**
- Optimized for **smooth EMA transitions**
- Simple color-coded momentum visualization
- Professional-grade **multi-timeframe trend oscillator**
This is one of the most **lightweight and powerful EMA oscillators** available for TradingView users who prefer clarity over clutter.
---
### ⚠️ **Disclaimer**
This indicator is published for **educational and analytical purposes only**.
It does **not provide financial advice**, buy/sell signals, or investment recommendations.
Always backtest before live use and trade responsibly.
---
### 👨💻 **Author**
Developed by **@algo_coders**
Built in **Pine Script v6** on **TradingView**
Licensed under the (mozilla.org)
Liquidity ToolkitKey Points:
Liquidity Toolkit is your liquidity companion for monitoring and anticipating price action.
Liquidity Toolkit combined the power of the Liquidity Status indicator with the potency of Price Triggers.
Liquidity Status indicates if the current current liquidity environment is bullish or bearish.
Price triggers highlight price levels where supports, resistances, and trend-changes are likely to occur.
Together, they create a comprehensive and actionable view of the market.
Summary
The Liquidity Toolkit (TK) is designed as a one-stop-shop indicator by combining novel liquidity metrics with traditional and impactful price measurements. In combination, TK grants unparalleled views of the market through effective yet simple displays.
The TK indicator contains two separate by synergistic algorithms: the Liquidity Status algorithm, which measures liquidity to determine if outlooks are bearish or bullish; and the Price Triggers algorithm which analyzes price-action to determine points of support and resistances.
Example 1 :
Example 2 :
Example 3 :
Details
Liquidity Status
Liquidity Status (LS) measures liquidity and produces either `Bullish` or `Bearish` indications depending on the current liquidity status.
Bullish indications indicate that the overall flow of liquidity is supportive of bullish price and bearish indications indicate that the overall flow of liquidity is supportive of bearish price action.
LS is displayed in two ways:
Candle-Coloring: if candles are green, liquidity status is bullish and if candles are red, liquidity status is bearish.
Text Display: Bearish and/or Bullish is displayed via text as well.
Price Triggers
Price Triggers (PT) measure price action and report their findings on several timeframes:
1-Minute
5-Minute
60-Minute
1-Day
1-Week
TK graphs the PTs based on the chart interval – only the higher PTs are display (i.e.: On the 1-Hour chart, the 5-, and 1-Min PTs will not be displayed).
Example 4
In additional to showing price-levels of support and resistance, Price Triggers also display the relative strength of these supports and resistances by displaying the Trigger Strengths. These represent areas of influence.
Opportunities often arise when PTs squeeze each other, often forcing spot to make a large move – as can be seen below:
Example 5
Frequently Asked Questions
How can I get access to the Liquidity Toolkit?
Please see the Author’s Instructions section at the top of the page for more details and information.
How can I get additional information on the indicators used?
Please see the Author’s Instructions section at the top of the page for more details and information.
I added the Liquidity Toolkit but I do not see all of the PT lines – where are they?
Depending on the chart interval, not all PT lines will be displayed. Those lower than the chart’s timeframe are hidden for clarity.
I added Liquidity Toolkit but the chart’s candles are not being filled by LS.
The chart will try to color over LS’ candles if you do not disable them. To disable, go to the Chart Settings then to Symbol and de-select Body, Borders and Wick.
Smart MACD Volume Trader# Smart MACD Volume Trader
## Overview
Smart MACD Volume Trader is an enhanced momentum indicator that combines the classic MACD (Moving Average Convergence Divergence) oscillator with an intelligent high-volume filter. This combination significantly reduces false signals by ensuring that trading signals are only generated when price momentum is confirmed by substantial volume activity.
The indicator supports over 24 different instruments including major and exotic forex pairs, precious metals (gold and silver), energy commodities (crude oil, natural gas), and industrial metals (copper). For forex and commodity traders, the indicator automatically maps to CME and COMEX futures contracts to provide accurate institutional-grade volume data.
## Originality and Core Concept
Traditional MACD indicators generate signals based solely on price momentum, which can result in numerous false signals during low-activity periods or ranging markets. This indicator addresses this critical weakness by introducing a volume confirmation layer with automatic institutional volume integration.
**What makes this approach original:**
- Signals are triggered only when MACD crossovers coincide with elevated volume activity
- Implements a lookback mechanism to detect volume spikes within recent bars
- Automatically detects and maps 24+ forex pairs and commodities to their corresponding CME and COMEX futures contracts
- Provides real institutional volume data for forex pairs where spot volume is unreliable
- Combines two independent market dimensions (price momentum and volume) into a single, actionable signal
- Includes intelligent asset detection that works across multiple exchanges and ticker formats
**The underlying principle:** Volume validates price movement. When institutional money enters the market, it creates volume signatures. By requiring high volume confirmation and using actual institutional volume data from futures markets, this indicator filters out weak price movements and focuses on trades backed by genuine market participation. The automatic futures mapping ensures that forex and commodity traders always have access to the most accurate volume data available, without manual configuration.
## How It Works
### MACD Component
The indicator calculates MACD using standard methodology:
1. **Fast EMA (default: 12 periods)** - Tracks short-term price momentum
2. **Slow EMA (default: 26 periods)** - Tracks longer-term price momentum
3. **MACD Line** - Difference between Fast EMA and Slow EMA
4. **Signal Line (default: 9-period SMA)** - Smoothed average of MACD line
**Crossover signals:**
- **Bullish:** MACD line crosses above Signal line (momentum turning positive)
- **Bearish:** MACD line crosses below Signal line (momentum turning negative)
### Volume Filter Component
The volume filter adds an essential confirmation layer:
1. **Volume Moving Average** - Calculates exponential MA of volume (default: 20 periods)
2. **High Volume Threshold** - Multiplies MA by ratio (default: 2.0x or 200%)
3. **Volume Detection** - Identifies bars where current volume exceeds threshold
4. **Lookback Period** - Checks if high volume occurred in recent bars (default: 5 bars)
**Signal logic:**
- Buy/Sell signals only trigger when BOTH conditions are met:
- MACD crossover/crossunder occurs
- High volume detected within lookback period
### Automatic CME Futures Integration
For forex traders, spot FX volume data can be unreliable or non-existent. This indicator solves this problem by automatically detecting forex pairs and mapping them to corresponding CME futures contracts with real institutional volume data.
**Supported Major Forex Pairs (7):**
- EURUSD → CME:6E1! (Euro FX Futures)
- GBPUSD → CME:6B1! (British Pound Futures)
- AUDUSD → CME:6A1! (Australian Dollar Futures)
- USDJPY → CME:6J1! (Japanese Yen Futures)
- USDCAD → CME:6C1! (Canadian Dollar Futures)
- USDCHF → CME:6S1! (Swiss Franc Futures)
- NZDUSD → CME:6N1! (New Zealand Dollar Futures)
**Supported Exotic Forex Pairs (4):**
- USDMXN → CME:6M1! (Mexican Peso Futures)
- USDRUB → CME:6R1! (Russian Ruble Futures)
- USDBRL → CME:6L1! (Brazilian Real Futures)
- USDZAR → CME:6Z1! (South African Rand Futures)
**Supported Cross Pairs (6):**
- EURJPY → CME:6E1! (Uses Euro Futures)
- GBPJPY → CME:6B1! (Uses British Pound Futures)
- EURGBP → CME:6E1! (Uses Euro Futures)
- AUDJPY → CME:6A1! (Uses Australian Dollar Futures)
- EURAUD → CME:6E1! (Uses Euro Futures)
- GBPAUD → CME:6B1! (Uses British Pound Futures)
**Supported Precious Metals (2):**
- Gold (XAUUSD, GOLD) → COMEX:GC1! (Gold Futures)
- Silver (XAGUSD, SILVER) → COMEX:SI1! (Silver Futures)
**Supported Energy Commodities (3):**
- WTI Crude Oil (USOIL, WTIUSD) → NYMEX:CL1! (Crude Oil Futures)
- Brent Oil (UKOIL) → NYMEX:BZ1! (Brent Crude Futures)
- Natural Gas (NATGAS) → NYMEX:NG1! (Natural Gas Futures)
**Supported Industrial Metals (1):**
- Copper (COPPER) → COMEX:HG1! (Copper Futures)
**How the automatic detection works:**
The indicator intelligently identifies the asset type by analyzing:
1. Exchange name (FX, OANDA, TVC, COMEX, NYMEX, etc.)
2. Currency pair pattern (6-letter codes like EURUSD, GBPUSD)
3. Commodity identifiers (XAU for gold, XAG for silver, OIL for crude)
When a supported instrument is detected, the indicator automatically switches to the corresponding futures contract for volume analysis. For stocks, cryptocurrencies, and other assets, the indicator uses the native volume data from the current chart.
**Visual feedback:**
An information table appears in the top-right corner of the MACD pane showing:
- Current chart symbol
- Exchange name
- Currency pair or asset name
- Volume source being used (highlighted in orange for futures, yellow for native volume)
- Current high volume status
This provides complete transparency about which data source the indicator is using for its volume analysis.
## How to Use
### Basic Setup
1. Add the indicator to your chart
2. The indicator displays in a separate pane (MACD) and overlay (signals/volume bars)
3. Default settings work well for most assets, but can be customized
### Signal Interpretation
### Visual Signals
**Visual Signals:**
- **Green "BUY" label** - Bullish MACD crossover confirmed by high volume
- **Red "SELL" label** - Bearish MACD crossunder confirmed by high volume
- **Green/Red candles** - Highlight bars with volume exceeding the threshold
- **Light green/red background** - Emphasizes signal bars on the chart
**Information Table:**
A detailed information table appears in the top-right corner of the MACD pane, providing real-time transparency about the indicator's operation:
- **Chart:** Current symbol being analyzed
- **Exchange:** The exchange or data feed being used
- **Pair:** The currency pair or asset name extracted from the ticker
- **Volume From:** The actual symbol used for volume analysis
- Orange color indicates CME or COMEX futures are being used (automatic institutional volume)
- Yellow color indicates native volume from the chart symbol is being used
- Hover tooltip shows whether automatic futures mapping is active
- **High Volume:** Current status showing YES (green) when volume exceeds threshold, NO (gray) otherwise
This table ensures complete transparency and allows you to verify that the correct volume source is being used for your analysis.
**Volume Analysis:**
- Gray histogram bars = Normal volume
- Red histogram bars = High volume (exceeds threshold)
- Green line = Volume moving average baseline
**MACD Analysis:**
- Blue line = MACD line (momentum indicator)
- Orange line = Signal line (trend confirmation)
- Gray dotted line = Zero line (bullish above, bearish below)
### Parameter Customization
**MACD Parameters:**
- Adjust Fast/Slow EMA lengths for different sensitivities
- Shorter periods = More signals, faster response
- Longer periods = Fewer signals, less noise
**Volume Parameters:**
- **Volume MA Period:** Higher values smooth volume analysis
- **High Volume Ratio:** Lower values (1.5x) = More signals; Higher values (3.0x) = Fewer, stronger signals
- **Volume Lookback Bars:** Controls how recent the volume spike must be
**Direction Filters:**
- **Only Buy Signals:** Enables long-only strategy mode
- **Only Sell Signals:** Enables short-only strategy mode
### Alert Configuration
The indicator includes three alert types:
1. **Buy Signal Alert** - Triggers when bullish signal appears
2. **Sell Signal Alert** - Triggers when bearish signal appears
3. **High Volume Alert** - Triggers when volume exceeds threshold
To set up alerts:
1. Click the indicator name → "Add alert on Smart MACD Volume Trader"
2. Select desired alert condition
3. Configure notification method (popup, email, webhook, etc.)
## Trading Strategy Guidelines
### Best Practices
**Recommended markets:**
- Liquid stocks (large-cap, high daily volume)
- Major forex pairs (EURUSD, GBPUSD, USDJPY, AUDUSD, USDCAD, USDCHF, NZDUSD)
- Exotic forex pairs (USDMXN, USDRUB, USDBRL, USDZAR)
- Cross pairs (EURJPY, GBPJPY, EURGBP, AUDJPY, EURAUD, GBPAUD)
- Precious metals (Gold, Silver with automatic COMEX futures mapping)
- Energy commodities (Crude Oil, Natural Gas with automatic NYMEX futures mapping)
- Industrial metals (Copper with automatic COMEX futures mapping)
- Major cryptocurrency pairs
- Index futures and ETFs
**Timeframe recommendations:**
- **Day trading:** 5-minute to 15-minute charts
- **Swing trading:** 1-hour to 4-hour charts
- **Position trading:** Daily charts
**Risk management:**
- Use signals as entry confirmation, not standalone strategy
- Combine with support/resistance levels
- Consider overall market trend direction
- Always use stop-loss orders
### Strategy Examples
**Trend Following Strategy:**
1. Identify overall trend using higher timeframe (e.g., daily chart)
2. Trade only in trend direction
3. Use "Only Buy" filter in uptrends, "Only Sell" in downtrends
4. Enter on signal, exit on opposite signal or at resistance/support
**Volume Breakout Strategy:**
1. Wait for consolidation period (low volume, tight MACD range)
2. Enter when signal appears with high volume (confirms breakout)
3. Target previous swing highs/lows
4. Stop loss below/above recent consolidation
**Forex Scalping Strategy (with automatic CME futures):**
1. The indicator automatically detects forex pairs and uses CME futures volume
2. Trade during active sessions only (use session filter)
3. Focus on quick profits (10-20 pips)
4. Exit at opposite signal or profit target
**Commodities Trading Strategy (Gold, Silver, Oil):**
1. The indicator automatically maps to COMEX and NYMEX futures contracts
2. Trade during high-liquidity sessions (overlap of major markets)
3. Use the high volume confirmation to identify institutional entry points
4. Combine with key support and resistance levels for entries
5. Monitor the information table to confirm futures volume is being used (orange color)
6. Exit on opposite MACD signal or at predefined profit targets
## Why This Combination Works
### The Volume Advantage
Studies consistently show that price movements accompanied by high volume are more likely to continue, while low-volume movements often reverse. This indicator leverages this principle by requiring volume confirmation.
**Key benefits:**
1. **Reduced False Signals:** Eliminates MACD whipsaws during low-volume consolidation
2. **Confirmation Bias:** Two independent indicators (price momentum + volume) agreeing
3. **Institutional Alignment:** High volume often indicates institutional participation
4. **Trend Validation:** Volume confirms that price momentum has "conviction"
### Statistical Edge
By combining two uncorrelated signals (MACD crossovers and volume spikes), the indicator creates a higher-probability setup than either signal alone. The lookback mechanism ensures signals aren't missed if volume spike slightly precedes the MACD cross.
## Supported Exchanges and Automatic Detection
The indicator includes intelligent asset detection that works across multiple exchanges and ticker formats:
**Forex Exchanges (Automatic CME Mapping):**
- FX (TradingView forex feed)
- OANDA
- FXCM
- SAXO
- FOREXCOM
- PEPPERSTONE
- EASYMARKETS
- FX_IDC
**Commodity Exchanges (Automatic COMEX/NYMEX Mapping):**
- TVC (TradingView commodity feed)
- COMEX (directly)
- NYMEX (directly)
- ICEUS
**Other Asset Classes (Native Volume):**
- Stock exchanges (NASDAQ, NYSE, AMEX, etc.)
- Cryptocurrency exchanges (BINANCE, COINBASE, KRAKEN, etc.)
- Index providers (SP, DJ, etc.)
The detection algorithm analyzes three factors:
1. Exchange prefix in the ticker symbol
2. Pattern matching for currency pairs (6-letter codes)
3. Commodity identifiers in the symbol name
This ensures accurate automatic detection regardless of which data feed or exchange you use for charting. The information table in the top-right corner always displays which volume source is being used, providing complete transparency.
## Technical Details
**Calculations:**
- MACD Fast MA: EMA(close, fastLength)
- MACD Slow MA: EMA(close, slowLength)
- MACD Line: Fast MA - Slow MA
- Signal Line: SMA(MACD Line, signalLength)
- Volume MA: Exponential MA of volume
- High Volume: Current volume >= Volume MA × Ratio
**Signal logic:**
```
Buy Signal = (MACD crosses above Signal) AND (High volume in last N bars)
Sell Signal = (MACD crosses below Signal) AND (High volume in last N bars)
```
## Parameters Reference
| Parameter | Default | Description |
|-----------|---------|-------------|
| Volume Symbol | Blank | Manual override for volume source (leave blank for automatic detection) |
| Use CME Futures | False | Legacy option (automatic detection is now built-in) |
| Alert Session | 1530-2200 | Active session time range for alerts |
| Timezone | UTC+1 | Timezone for alert sessions |
| Volume MA Period | 20 | Number of periods for volume moving average |
| High Volume Ratio | 2.0 | Volume threshold multiplier (2.0 = 200% of average) |
| Volume Lookback | 5 | Number of bars to check for high volume confirmation |
| MACD Fast Length | 12 | Fast EMA period for MACD calculation |
| MACD Slow Length | 26 | Slow EMA period for MACD calculation |
| MACD Signal Length | 9 | Signal line SMA period |
| Only Buy | False | Filter to show only bullish signals |
| Only Sell | False | Filter to show only bearish signals |
| Show Signals | True | Display buy and sell labels on chart |
## Optimization Tips
**For volatile markets (crypto, small caps):**
- Increase High Volume Ratio to 2.5-3.0
- Reduce Volume Lookback to 3-4 bars
- Consider faster MACD settings (8, 17, 9)
**For stable markets (large-cap stocks, bonds):**
- Decrease High Volume Ratio to 1.5-1.8
- Increase Volume MA Period to 30-50
- Use standard MACD settings
**For forex (with automatic CME futures):**
- The indicator automatically uses CME futures when forex pairs are detected
- Set appropriate trading session based on your timezone
- Use Volume Lookback of 5-7 bars
- Consider session-based alerts only
- Monitor the information table to verify correct futures mapping
**For commodities (Gold, Silver, Oil, Copper):**
- The indicator automatically maps to COMEX and NYMEX futures
- Increase High Volume Ratio to 2.0-2.5 for metals
- Use slightly higher Volume MA Period (25-30) for smoother analysis
- Trade during active market hours for best volume data
- The information table will show the futures contract being used (orange highlight)
## Limitations and Considerations
**What this indicator does NOT do:**
- Does not predict future price direction
- Does not guarantee profitable trades
- Does not replace proper risk management
- Does not work well in extremely low-volume conditions
**Market conditions to avoid:**
- Pre-market and after-hours sessions (low volume)
- Major news events (volatile, unpredictable volume)
- Holidays and low-liquidity periods
- Extremely low float stocks
## Conclusion
Smart MACD Volume Trader represents a significant evolution of the traditional MACD indicator by combining volume confirmation with automatic institutional volume integration. This dual-confirmation approach significantly improves signal quality by filtering out low-conviction price movements and ensuring traders work with accurate volume data.
The indicator's automatic detection and mapping system supports over 24 instruments across forex, commodities, and metals markets. By intelligently switching to CME and COMEX futures contracts when appropriate, the indicator provides forex and commodity traders with the same quality of volume data that stock traders naturally have access to.
This indicator is particularly valuable for traders who want to:
- Align their entries with institutional money flow
- Avoid getting trapped in false breakouts
- Trade forex pairs with reliable volume data
- Access accurate volume information for gold, silver, and energy commodities
- Combine momentum and volume analysis in a single, streamlined tool
Whether you are day trading stocks, swing trading forex pairs, or positioning in commodities markets, this indicator provides a robust framework for identifying high-probability momentum trades backed by genuine institutional participation. The automatic futures mapping works seamlessly across all supported instruments, requiring no manual configuration or expertise in futures markets.
---
## Support and Updates
This indicator is actively maintained and updated based on user feedback and market conditions. For questions about implementation or custom modifications, please use the comments section below.
**Disclaimer:** This indicator is for educational and informational purposes only. Past performance does not guarantee future results. Always conduct your own analysis and risk management before trading.
OBTrendDelta Volume Delta & Order Block SuiteOB Trend Delta V1 - Order Block & Volume Delta Indicator
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📊 OVERVIEW
OB Trend Delta V1 is a technical indicator that combines Order Blocks analysis (institutional support/resistance zones) with Volume Delta (buying vs selling pressure) to provide insights on setup quality and market dynamics.
The indicator visually displays zones of interest, volume pressure, and a quality scoring system to assist in technical analysis of any market.
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🎯 CORE CONCEPT
▸ ORDER BLOCKS
Order Blocks are price zones where large institutions executed significant operations. These areas tend to act as support (Bull OB) or resistance (Bear OB) when price returns to them.
How to interpret:
🟢 Bull Order Block: Green zone where institutional buyers entered strongly → Potential support
🔴 Bear Order Block: Red zone where institutional sellers entered strongly → Potential resistance
▸ VOLUME DELTA
Volume Delta measures the difference between buying and selling volume in each candle, revealing which side of the market is dominating.
How to interpret:
✅ Positive Delta (green histogram): Buyers dominating → Bullish pressure
❌ Negative Delta (red histogram): Sellers dominating → Bearish pressure
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📈 WHAT THE INDICATOR SHOWS
1️⃣ TREND DETECTION
The indicator identifies the main market direction using moving averages and trend strength analysis (ADX), visually highlighting when the market is in:
Uptrend (Bullish Trend)
Downtrend (Bearish Trend)
Ranging (Sideways market/no clear trend)
2️⃣ SETUP QUALITY SYSTEM
Each trading opportunity is evaluated on 6 independent criteria:
✅ Price inside a valid Order Block
✅ Volume Delta confirming the direction
✅ Order Block is recent and "fresh"
✅ Few previous retests (OB still strong)
✅ Volume confirmation above average
✅ Favorable market regime
Setup Quality Score: 0 to 6 points
Score 6: Perfect setup (all criteria met)
Score 5: Excellent setup (5 of 6 criteria)
Score 4: Good setup (4 of 6 criteria)
Score 0-3: Weak setup or forming
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🔧 VISUAL COMPONENTS IN THE INDICATOR
▸ VOLUME DELTA HISTOGRAM
🟢 Green Bars: Buying volume > selling volume (bullish pressure)
🔴 Red Bars: Selling volume > buying volume (bearish pressure)
📊 Intensity: The larger the bar, the greater the pressure
▸ ORDER BLOCK ZONES
🟢 Green Boxes (Bull OB): Institutional support zones
🔴 Red Boxes (Bear OB): Institutional resistance zones
🔄 Projection: OBs are extended to the right until invalidated
▸ SETUP QUALITY SIGNALS
📊 Score Labels: Show setup quality (Q4, Q5, Q6)
• Q6: Perfect setup (all 6 criteria met)
• Q5: Excellent setup (5 of 6 criteria)
• Q4: Good setup (4 of 6 criteria)
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💡 HOW TO INTERPRET THE INFORMATION
Observe trend direction (EMAs and ADX)
Identify active Order Blocks:
• Bull OBs (green): Potential support zones
• Bear OBs (red): Potential resistance zones
Analyze Volume Delta:
• Green bars: Dominant buying pressure
• Red bars: Dominant selling pressure
Check Setup Quality Score:
• Q5-Q6: Setups with multiple confirmations
• Q4: Setup with moderate confirmations
• Q0-Q3: Few criteria met
⚠️ NOTE: The indicator provides technical information. Trading decisions are exclusively yours.
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📊 TECHNICAL CHARACTERISTICS
▸ RECOMMENDED TIMEFRAMES
5 minutes: Scalping / Fast day trading
15 minutes: Day trading
1 hour: Swing trading
4 hours: Medium-term positions
Daily: Long-term analysis
▸ COMPATIBLE MARKETS
✅ Forex (all pairs)
✅ Cryptocurrencies (BTC, ETH, altcoins)
✅ Indices (S&P500, Nasdaq, etc)
✅ Commodities (Gold, Oil, etc)
✅ Stocks and CFDs
⚠️ Requirement: Volume data is necessary for Volume Delta calculation
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⚠️ IMPORTANT WARNINGS
▸ EDUCATIONAL USE
📊 This indicator is an educational technical analysis tool
⚠️ The indicator does NOT provide buy or sell signals
⚠️ The indicator does NOT guarantee results
⚠️ All trading decisions are your responsibility
▸ RISK MANAGEMENT
⚠️ Always use proper risk management
⚠️ Never trade with money you cannot afford to lose
⚠️ Test the indicator on a demo account before using real money
⚠️ Combine with your own analysis and strategy
▸ LIMITATIONS
❌ No indicator is 100% accurate
❌ Markets can behave unpredictably
❌ Requires confirmation with other analyses
❌ Volume Delta requires reliable volume data
▸ DISCLAIMER
📢 This indicator is educational and does not constitute investment advice.
The indicator shows technical information, not trading signals
Past results do not guarantee future results
Trading involves risk of total capital loss
You are 100% responsible for your trading decisions
Consult a financial professional before investing
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📚 ADVANCED CONCEPTS
▸ WHAT ARE ORDER BLOCKS?
Order Blocks represent zones where "smart money" (institutions, whales) accumulated or distributed positions. When price returns to these zones, there is high probability of reaction due to:
Pending limit orders
Psychological levels
Institutional value zones
▸ VOLUME DELTA VS NORMAL VOLUME
Normal volume shows only QUANTITY of trades.
Volume Delta shows DIRECTION (who is winning the battle):
High volume + Positive delta = Strong accumulation 🚀
High volume + Negative delta = Strong distribution 📉
▸ MARKET REGIME (ADX)
ADX measures TREND STRENGTH:
ADX > 25: Strong trend (best time to trade)
ADX < 20: Sideways/ranging market (avoid trades)
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✅ BEFORE USING THIS INDICATOR
Make sure you:
☑ Understand the Order Blocks concept
☑ Know how to interpret Volume Delta
☑ Understand trend analysis
☑ Have your own trading strategy
☑ Know risk management
☑ Understand the indicator does NOT provide buy/sell signals
☑ Are aware of trading risks
☑ Test on demo account before using real money
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📊 USE AS AN ANALYSIS TOOL, NOT AS AN AUTOMATIC DECISION SYSTEM!
The indicator provides information. You make the decisions.
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Version: 1.0 | Type: Order Block + Volume Delta + Trend Analysis | Update: October 2024
Multi-Timeframe EMA Trend Dashboard with Volume and RSI Filters═══════════════════════════════════════════════════════════
MULTI-TIMEFRAME EMA TREND DASHBOARD
═══════════════════════════════════════════════════════════
OVERVIEW
This indicator provides a comprehensive view of trend direction across multiple timeframes using the classic EMA 20/50 crossover methodology, enhanced with volume confirmation and RSI filtering. It aggregates trend information from six timeframes into a single dashboard for efficient market analysis.
The indicator is designed for educational purposes and to assist traders in identifying potential trend alignments across different time horizons.
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FEATURES
═══════════════════════════════════════════════════════════
MULTI-TIMEFRAME ANALYSIS
• Monitors 6 timeframes simultaneously: 1m, 5m, 15m, 1H, 4H, 1D
• Each timeframe analyzed independently using request.security()
• Non-repainting implementation with proper lookahead settings
• Calculates overall trend strength as percentage of bullish timeframes
EMA CROSSOVER SYSTEM
• Fast EMA (default: 20) and Slow EMA (default: 50)
• Bullish: Fast EMA > Slow EMA
• Bearish: Fast EMA < Slow EMA
• Neutral: Fast EMA = Slow EMA (rare condition)
• Visual EMA plots with optional fill area
VOLUME CONFIRMATION
• Optional volume filter for crossover signals
• Compares current volume against moving average (default: 20-period SMA)
• Categorizes volume as: High (>1.5x average), Normal (>average), Low (70), oversold (<30), and neutral zones
• Used in quality score calculation
• Optional display toggle
SUPPORT & RESISTANCE DETECTION
• Automatic detection using highest/lowest over lookback period (default: 50 bars)
• Plots resistance (red), support (green), and mid-level (gray)
• Step-line style for clear visualization
• Optional display toggle
QUALITY SCORING SYSTEM
• Rates trade setups from 1-5 stars
• Considers: MTF alignment, volume confirmation, RSI positioning
• 5 stars: 4+ timeframes aligned + volume confirmed + RSI 50-70
• 4 stars: 4+ timeframes aligned + volume confirmed
• 3 stars: 3+ timeframes aligned
• 2 stars: Exactly 3 timeframes aligned
• 1 star: Other conditions
VISUAL DASHBOARD
• Clean table display (position customizable)
• Color-coded trend indicators (green/red/yellow)
• Extended statistics panel (toggleable)
• Shows: Trends, Strength, Quality, RSI, Volume, Price Distance
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TECHNICAL SPECIFICATIONS
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CALCULATIONS
Trend Determination per Timeframe:
• request.security() fetches EMA values with gaps=off, lookahead=off
• Compares Fast EMA vs Slow EMA
• Returns: 1 (bullish), -1 (bearish), 0 (neutral)
Trend Strength:
• Counts number of bullish timeframes
• Formula: (bullish_count / 6) × 100
• Range: 0% (all bearish) to 100% (all bullish)
Price Distance from EMA:
• Formula: ((close - EMA) / EMA) × 100
• Positive: Price above EMA
• Negative: Price below EMA
• Warning when absolute distance > 5%
ANTI-REPAINTING MEASURES
• All request.security() calls use lookahead=barmerge.lookahead_off
• Dashboard updates only on barstate.islast
• Historical bars remain unchanged
• Crossover signals finalize on bar close
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USAGE GUIDE
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INTERPRETING THE DASHBOARD
Timeframe Rows:
• Each row shows individual timeframe trend status
• Look for alignment (multiple timeframes same direction)
• Higher timeframes generally more significant
Strength Indicator:
• >66.67%: Strong bullish (4+ timeframes bullish)
• 33.33-66.67%: Mixed/choppy conditions
• <33.33%: Strong bearish (4+ timeframes bearish)
Quality Score:
• Higher stars = better confluence of factors
• 5-star setups have strongest multi-factor confirmation
• Lower scores may indicate weaker or conflicting signals
SUGGESTED APPLICATIONS
Trend Confirmation:
• Check if multiple timeframes confirm current chart trend
• Higher agreement = stronger trend confidence
• Use for position sizing decisions
Entry Timing:
• Wait for EMA crossover on chart timeframe
• Confirm with higher timeframe alignment
• Volume above average preferred
• RSI not in extreme zones
Divergence Detection:
• When lower timeframes diverge from higher
• May indicate trend exhaustion or reversal
• Requires additional confirmation
CUSTOMIZATION
EMA Settings:
• Adjust Fast/Slow lengths for different sensitivities
• Shorter periods = more responsive, more signals
• Longer periods = smoother, fewer signals
• Common alternatives: 10/30, 12/26, 50/200
Volume Filter:
• Enable for higher-quality signals (fewer false positives)
• Disable in always-liquid markets or for more signals
• Adjust MA length based on typical volume patterns
Display Options:
• Toggle EMAs, S/R levels, extended stats as needed
• Choose dashboard position to avoid chart overlap
• Adjust colors for visibility preferences
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ALERTS
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AVAILABLE ALERT CONDITIONS
1. Bullish EMA Cross (Volume Confirmed)
2. Bearish EMA Cross (Volume Confirmed)
3. Strong Bullish Alignment (4+ timeframes)
4. Strong Bearish Alignment (4+ timeframes)
5. Trend Strength Increasing (>16.67% jump)
6. Trend Strength Decreasing (>16.67% drop)
7. Excellent Trade Setup (5-star rating)
Alert messages use standard placeholders:
• {{ticker}} - Symbol name
• {{close}} - Current close price
• {{time}} - Bar timestamp
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LIMITATIONS & CONSIDERATIONS
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KNOWN LIMITATIONS
• Lower timeframe data may not be available on all symbols
• 1-minute data typically limited to recent history
• request.security() subject to TradingView data limits
• Dashboard requires screen space (may overlap on small screens)
• More complex calculations may affect load time on slower devices
NOT SUITABLE FOR
• Highly volatile/illiquid instruments (many false signals)
• News-driven markets during announcements
• Automated trading without additional filters
• Markets where EMA strategies don't perform well
DOES NOT PROVIDE
• Exact entry/exit prices
• Stop-loss or take-profit levels
• Position sizing recommendations
• Guaranteed profit signals
• Market predictions
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BEST PRACTICES
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RECOMMENDED USAGE
✓ Combine with price action analysis
✓ Use appropriate risk management
✓ Backtest on historical data before live use
✓ Adjust settings for specific market characteristics
✓ Wait for higher-quality setups in important trades
✓ Consider overall market context and fundamentals
NOT RECOMMENDED
✗ Using as standalone trading system without confirmation
✗ Trading every signal without discretion
✗ Ignoring risk management principles
✗ Trading without understanding the methodology
✗ Applying to unsuitable markets/timeframes
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EDUCATIONAL BACKGROUND
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EMA CROSSOVER STRATEGY
The Exponential Moving Average crossover is a classical trend-following technique:
• Golden Cross: Fast EMA crosses above Slow EMA (bullish signal)
• Death Cross: Fast EMA crosses below Slow EMA (bearish signal)
• Widely used since the 1970s in various markets
• More responsive than SMA due to exponential weighting
MULTI-TIMEFRAME ANALYSIS
Analyzing multiple timeframes helps traders:
• Identify alignment between short and long-term trends
• Reduce false signals from single-timeframe noise
• Understand market context across different horizons
• Make informed decisions about trade duration
VOLUME ANALYSIS
Volume confirmation adds reliability:
• High volume suggests institutional participation
• Low volume signals may indicate false breakouts
• Volume precedes price in many market theories
• Helps distinguish genuine moves from noise
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TECHNICAL IMPLEMENTATION
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CODE STRUCTURE
• Organized in clear sections with proper commenting
• Uses explicit type declarations (int, float, bool, color, string)
• Constants defined at top (BULLISH=1, BEARISH=-1, etc.)
• Functions documented with @function, @param, @returns
• Follows PineCoders naming conventions (camelCase variables)
PERFORMANCE OPTIMIZATION
• var keyword for table (created once, not every bar)
• Calculations cached where possible
• Dashboard updates only on last bar
• Minimal redundant security() calls
SECURITY IMPLEMENTATION
• Proper gaps and lookahead parameters
• No future data leakage
• Signals finalize on bar close
• Historical bars remain static
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VERSION INFORMATION
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Current Version: 2.0
Pine Script Version: 5
Last Updated: 2024
Developed by: Zakaria Safri
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SETTINGS REFERENCE
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EMA SETTINGS
• Fast EMA Length: 1-500 (default: 20)
• Slow EMA Length: 1-500 (default: 50)
VOLUME & MOMENTUM
• Use Volume Confirmation: true/false (default: true)
• Volume MA Length: 1-500 (default: 20)
• Show RSI Levels: true/false (default: true)
• RSI Length: 1-500 (default: 14)
PRICE ACTION FEATURES
• Show Price Distance: true/false (default: true)
• Show Key Levels: true/false (default: true)
• S/R Lookback Period: 10-500 (default: 50)
DISPLAY SETTINGS
• Show EMAs on Chart: true/false (default: true)
• Fast EMA Color: customizable (default: cyan)
• Slow EMA Color: customizable (default: orange)
• EMA Line Width: 1-5 (default: 2)
• Show Fill Between EMAs: true/false (default: true)
• Show Crossover Signals: true/false (default: true)
DASHBOARD SETTINGS
• Position: Top Left/Right, Bottom Left/Right
• Show Extended Statistics: true/false (default: true)
ALERT SETTINGS
• Alert on Multi-TF Alignment: true/false (default: true)
• Alert on Trend Strength Change: true/false (default: true)
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RISK DISCLAIMER
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This indicator is provided for educational and informational purposes only. It should not be considered financial advice or a recommendation to buy or sell any security.
IMPORTANT NOTICES:
• Past performance does not indicate future results
• All trading involves risk of capital loss
• No indicator guarantees profitable trades
• Always conduct independent research and analysis
• Use proper risk management and position sizing
• Consult a qualified financial advisor before trading
• The developer assumes no liability for trading losses
By using this indicator, you acknowledge that you understand these risks and accept full responsibility for your trading decisions.
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SUPPORT & CONTRIBUTIONS
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FEEDBACK WELCOME
• Constructive comments appreciated
• Bug reports help improve the indicator
• Feature suggestions considered for future versions
• Share your experience to help other users
OPEN SOURCE
This code is published as open source for the TradingView community to:
• Learn from the implementation
• Modify for personal use
• Understand multi-timeframe analysis techniques
If you find this indicator useful, please consider:
• Leaving a thoughtful review
• Sharing with other traders who might benefit
• Following for future updates and releases
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ADDITIONAL RESOURCES
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RECOMMENDED READING
• TradingView Pine Script documentation
• PineCoders community resources
• Technical analysis textbooks on moving averages
• Multi-timeframe trading strategy guides
• Risk management principles
RELATED CONCEPTS
• Trend following strategies
• Moving average convergence/divergence
• Multiple timeframe analysis
• Volume-price relationships
• Momentum indicators
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Thank you for using this indicator. Trade responsibly and continue learning!
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Adaptive Pulse Frequency & Amplitude TrendAdaptive Pulse Frequency & Amplitude Trend Indicator
This Pine Script indicator is designed to identify strong bullish or bearish trends by analyzing volume dynamics on a lower timeframe than the one currently displayed on the chart. It operates on the principle of detecting significant spikes in buying or selling pressure, referred to as "pulses," and then evaluating their frequency, strength, and dominance over the opposing market forces.
Core Concepts
Lower Timeframe Volume Analysis: The script requests up-volume and down-volume data from a more granular, lower timeframe (e.g., 1-minute data when on a 15-minute chart). This provides a higher-resolution view of the flow of buy and sell orders.
Adaptive Pulse Detection: A "pulse" is defined as a bar with an unusually high net volume (up volume minus down volume). Instead of using a fixed value, the indicator calculates an adaptive threshold based on the 90th percentile of net volume over a 100-bar lookback period. Any bar with a net volume exceeding this dynamic threshold is flagged as a pulse, categorized as either bullish (positive net volume) or bearish (negative net volume).
Frequency and Amplitude: The indicator measures two key aspects of these pulses over user-defined lookback periods:
Net Frequency: The number of bullish pulses minus the number of bearish pulses. A positive value indicates more buying pulses, while a negative value indicates more selling pulses.
Net Amplitude : The cumulative volume of bullish pulses minus the cumulative volume of bearish pulses. This measures the overall strength and conviction behind the pulses.
Primary Trend Signal
The indicator's primary signal comes from a strict dominance condition. It doesn't just look for more buying or selling pulses; it checks if these pulses are powerful enough to overwhelm the total opposite pressure in the market.
Bullish Dominance (Green Background): A strong bullish signal is generated when the total volume of all bullish pulses within a lookback period is greater than the total down-volume from all bars (not just pulses) in that same period.
Bearish Dominance (Red Background): A strong bearish signal is generated when the total volume of all bearish pulses is greater than the total up-volume from all bars in that period.
The chart background is colored green for bullish dominance and red for bearish dominance, providing a clear visual cue for when one side has taken decisive control.
Plotted Data
In addition to the background coloring, the indicator plots several lines in its own pane for more detailed analysis:
Net Frequency: Shows the trend in the number of bull vs. bear pulses.
Net Amplitude: Shows the trend in the strength of bull vs. bear pulses.
Bullish/Bearish Amplitude: The individual cumulative volumes for bull and bear pulses.
Dynamic Threshold: The adaptive value used to identify pulses.
By combining an adaptive detection method with a strict dominance condition, this tool aims to filter out market noise and highlight periods of genuinely strong, volume-backed trends.
Dammu AI ADVANCED PRO1. Indicator Overview
Name: Dammu
Type: Overlay indicator (draws on price chart)
Purpose: Combines SuperTrend, SMA/EMA trends, Swing/Structure analysis, Order Blocks, Fair Value Gaps, High/Low levels, TP/SL labels, and alerts.
Pine Script Version: v5
2. SuperTrend Module
Computes SuperTrend line using ATR and sensitivity.
Signals:
Bullish: Price crosses above SuperTrend.
Bearish: Price crosses below SuperTrend.
Plots buy/sell labels 🚀🐻 based on SMA comparison and SuperTrend cross.
3. SMA/EMA Trend Components
SMA8 & SMA9: Used for additional trend confirmation.
EMA lines: Multiple EMAs with different multipliers for trend detection.
Trend Cloud: Uses Hull MA for trend smoothing.
4. Risk Management
TP/SL Levels: Automatic calculation of stop-loss and take-profit (TP1, TP2, TP3).
Configurable ATR-based risk percentage.
Lines and labels drawn for visual TP/SL.
5. Chart Features
Smooth Range Filter: Filters noise for trend detection.
Colored Trend Cloud: Upward trend = cyan, downward = red.
Sideways Market: ADX filter to color bars purple if trend is weak/sideways.
Bar Colors: Green/red based on SuperTrend signals.
6. Swing & Structure Analysis
Detects Swing Highs/Lows, labels as HH, LH, LL, HL.
Detects CHoCH (Change of Character) or BOS (Break of Structure).
Can show internal or swing structures with configurable label size and color.
7. Order Blocks (Smart Money Concepts)
Detects Internal Order Blocks (iOB) and Swing Order Blocks (OB).
Stores top/bottom/left/time/type in arrays.
Colors and shows boxes based on bullish/bearish type.
Automatically deletes OB if price breaks the block.
8. Fair Value Gaps (FVG)
Identifies gaps between candles as potential trading zones.
Configurable bullish/bearish colors and extension bars.
9. EQH/EQL (Equal Highs/Lows)
Detects equal highs/lows using a threshold.
Plots dotted lines and labels EQH/EQL.
10. High/Low Levels MTF
Optional plotting of previous daily, weekly, monthly highs/lows.
11. Premium/Discount Zones
Plots Premium, Discount, and Equilibrium Zones.
Colors: Premium = red, Discount = green, Equilibrium = gray.
12. Alerts
Buy/Sell alerts for:
SuperTrend crossover
BOS/CHoCH (swing/internal)
EQH/EQL triggers
13. Miscellaneous
Configurable visuals: line style, label size, transparency.
Adjustable volatility filters, ATR lengths, smoothing constants.
Integrated risk & reward visualization.
✅ In short:
This is an all-in-one Smart Money + Trend indicator with SuperTrend signals, swing/structure detection, order blocks, FVGs, EQH/EQL, TP/SL visualization, and optional alerts. It’s designed for both trend-following and order-block-based trading.
If you want, I can make a super-short 1-paragraph version that summarizes it even faster for quick reference.
MTF Advanced DMI [NexusSignals]The MTF Advanced DMI is a multi-timeframe (MTF) enhancement of the classic Directional Movement Index (DMI) and Average Directional Index (ADX) indicator. It provides traders with insights into trend strength, direction, and momentum across multiple timeframes simultaneously. This version of DMI extends the single-timeframe analysis by incorporating two higher timeframes, allowing for better alignment of trends (e.g., confirming a short-term signal with longer-term context). It includes visual plots, a customizable data table showing MTF data, and expanded alert conditions for trend changes, consolidations, and reversals. Ideal for multi-timeframe strategies, trend confirmation, or avoiding false signals in volatile markets.
Key features include:
Multi-Timeframe Analysis: Displays DMI/ADX data for the current chart timeframe, plus two user-defined higher timeframes (e.g., 4H and 1D).
A trend strength metric that quantifies bullish/bearish dominance on each timeframe.
A dynamic table summarizing real-time MTF values, with color-coded signals, arrows, and buy/sell pressure percentages.
Visual fills and arrows for intuitive trend reading.
Built-in alerts for key events, including MTF-specific conditions (note: higher TF alerts may repaint due to live candle calculations via request.security).
How It Works
The indicator calculates DMI/ADX on three timeframes: the current chart TF, a mid-higher TF (default: 4H), and a highest TF (default: 1D).
For each:
+DI (Plus Directional Indicator): Upward movement strength.
-DI (Minus Directional Indicator): Downward movement strength.
ADX: Overall trend strength.
Trend Strength: ((+DI - -DI) / (+DI + -DI)) * ADX – positive for bullish, negative for bearish.
Buy/Sell %: Percentage of buyer/seller control in the candle based on HLC.
Plots focus on the current TF:
Strength Histogram: Color-coded (green bullish, red bearish).
ADX Line: White, with direction arrows.
+DI/-DI Lines: Green/red, with fills above 15 for strong trends.
Horizontal lines at 15 (consolidation) and 25 (strong trend).
The table (optional) shows data for the current timeframe candle, previous current timeframe candle, and the two higher TFs (if different from current), enabling quick cross-TF comparisons.
Inputs
General Settings:
DMI Length (default: 14): Period for +DI/-DI.
ADX Smoothing (default: 14): ADX period.
ADX Consolidation Threshold (default: 15): Low ADX suggests sideways.
ADX Stronger Trend Threshold (default: 25): High ADX indicates strong trends.
Higher Timeframe (default: 240/4H): Mid-level TF for MTF analysis.
Highest Timeframe (default: 1D): Top-level TF for broader context.
Threshold for Strong Bullish/Bearish DMI Strength (defaults: 10 / -10): For strength alerts.
Table Settings:
Show Table? (default: true): Toggle table visibility
Table Text Color, Header Color, Text Size (default: small)
Position (default: middle_right): Customize for your chart
Interpretation
Bullish Alignment: +DI > -DI across TFs, rising +DI (↑), Strength > 0 (green), Buy% > Sell%. Stronger if ADX > 25 on higher TFs.
Bearish Alignment: -DI > +DI, rising -DI (↑), Strength < 0 (red), Sell% > Buy%. Confirm with rising ADX on MTF.
Consolidation: +DI/-DI < 20 and ADX ≤ 15 (blue fill). Check if higher TFs show the same for range-bound confirmation.
Crossovers: +DI above -DI for bullish; reverse for bearish. MTF agreement reduces false signals.
Fills: Highlight dominant trends above 15 (green bullish, maroon bearish).
MTF Insight: Use the table to spot divergences (e.g., bullish current TF but bearish on daily) for potential reversals.
Combine with support/resistance or other momentum oscillators like macd, rsi, stochastic for robust strategies. Test on various assets and TFs to find the best settings that suit your trading style.
Alerts
Includes 20 alert conditions, with MTF extensions (higher TF alerts may repaint – use with caution for live trading):
Strength crossing 0 or bullish/bearish thresholds (on current and higher TFs).
+DI/-DI crossovers (bullish/bearish) on current TF.
ADX above strong threshold.
+DI/-DI above 25 or below 15.
Consolidation detection.
MTF-specific: Strength changes on higher TFs (e.g., "Strength Above Bullish Threshold on TF1").
Configure in TradingView by selecting from the alert dropdown.
Usage Tips
Select higher TFs that suit your strategy (e.g., 1H chart with 4H and Daily for day trading).
Use the table for at-a-glance MTF alignment without switching charts.
Customize appearance to avoid clutter on busy setups.
Backtest thoroughly, especially noting potential repainting on higher TFs.
Z-Score Momentum | MisinkoMasterThe Z-Score Momentum is a new trend analysis indicator designed to catch reversals, and shifts in trends by comparing the "positive" and "negative" momentum by using the Z-Score.
This approach helps traders and investors get unique insight into the market of not just Crypto, but any market.
A deeper dive into the indicator
First, I want to cover the "Why?", as I believe it will ease of the part of the calculation to make it easier to understand, as by then you will understand how it fits the puzzle.
I had an attempt to create a momentum oscillator that would catch reversals and provide high tier accuracy while maintaining the main part => the speed.
I thought back to many concepts, divergences between averages?
- Did not work
Maybe a MACD rework?
- Did not work with what I tried :(
So I thought about statistics, Standard Deviation, Z-Score, Sharpe/Sortino/Omega ratio...
Wait, was that the Z-Score? I only tried the For Loop version of it :O
So on my way back from school I formulated a concept (originaly not like this but to that later) that would attempt to use the Z-Score as an accurate momentum oscillator.
Many ideas were falling out of the blue, but not many worked.
After almost giving up on this, and going to go back to developing my strategies, I tried one last thing:
What if we use divergences in the average, formulated like a Z-score?
Surprise-surprise, it worked!
Now to explain what I have been so passionately yapping about, and to connect the pieces of the puzzle once and for all:
The indicator compares the "strength" of the bullish/bearish factors (could be said differently, but this is my "speach bubble", and I think this describes it the best)
What could we use for the "bullish/bearish" factors?
How about high & low?
I mean, these are by definitions the highest and lowest points in price, which I decided to interpret as: The highest the bull & bear "factors" achieved that bar.
The problem here is comparison, I mean high will ALWAYS > low, unless the asset decided to unplug itself and stop moving, but otherwise that would be unfair.
Now if I use my Z-score, it will get higher while low is going up, which is the opposite of what I want, the bearish "factor" is weaker while we go up!
So I sat on my ret*rded a*s for 25 minutes, completly ignoring the fact the number "-1" exists.
Surprise surprise, multiplying the Z-Score of the low by -1 did what I wanted!
Now it reversed itself (magically). Now while the low keeps going down, the bear factor increases, and while it goes up the bear factor lowers.
This was btw still too noisy, so instead of the classic formula:
a = current value
b = average value
c = standard deviation of a
Z = (a-b)/c
I used:
a = average value over n/2 period
b = average value over n period
c = standard deviation of a
Z = (a-b)/c
And then compared the Z-Score of High to the Z-Score of Low by basic subtraction, which gives us final result and shows us the strength of trend, the direction of the trend, and possibly more, which I may have not found.
As always, this script is open source, so make sure to play around with it, you may uncover the treasure that I did not :)
Enjoy Gs!
