Market Profile Dominance Analyzer# Market Profile Dominance Analyzer
## 📊 OVERVIEW
**Market Profile Dominance Analyzer** is an advanced multi-factor indicator that combines Market Profile methodology with composite dominance scoring to identify buyer and seller strength across higher timeframes. Unlike traditional volume profile indicators that only show volume distribution, or simple buyer/seller indicators that only compare candle colors, this script integrates six distinct analytical components into a unified dominance measurement system.
This indicator helps traders understand **WHO controls the market** by analyzing price position relative to Market Profile key levels (POC, Value Area) combined with volume distribution, momentum, and trend characteristics.
## 🎯 WHAT MAKES THIS ORIGINAL
### **Hybrid Analytical Approach**
This indicator uniquely combines two separate methodologies that are typically analyzed independently:
1. **Market Profile Analysis** - Calculates Point of Control (POC) and Value Area (VA) using volume distribution across price channels on higher timeframes
2. **Multi-Factor Dominance Scoring** - Weights six independent factors to produce a composite dominance index
### **Six-Factor Composite Analysis**
The dominance score integrates:
- Price position relative to POC (equilibrium assessment)
- Price position relative to Value Area boundaries (acceptance/rejection zones)
- Volume imbalance within Value Area (institutional bias detection)
- Price momentum (directional strength)
- Volume trend comparison (participation analysis)
- Normalized Value Area position (precise location within fair value zone)
### **Adaptive Higher Timeframe Integration**
The script features an intelligent auto-selection system that automatically chooses appropriate higher timeframes based on the current chart period, ensuring optimal Market Profile structure regardless of the trading timeframe being analyzed.
## 💡 HOW IT WORKS
### **Market Profile Construction**
The indicator builds a Market Profile structure on a higher timeframe by:
1. **Session Identification** - Detects new higher timeframe sessions using `request.security()` to ensure accurate period boundaries
2. **Data Accumulation** - Stores high, low, and volume data for all bars within the current higher timeframe session
3. **Channel Distribution** - Divides the session's price range into configurable channels (default: 20 rows)
4. **Volume Mapping** - Distributes each bar's volume proportionally across all price channels it touched
### **Key Level Calculation**
**Point of Control (POC)**
- Identifies the price channel with the highest accumulated volume
- Represents the price level where the most trading activity occurred
- Serves as a magnetic level where price often returns
**Value Area (VA)**
- Starts at POC and expands both upward and downward
- Includes channels until reaching the specified percentage of total volume (default: 70%)
- Expansion algorithm compares adjacent volumes and prioritizes the direction with higher activity
- Defines the "fair value" zone where most market participants agreed to trade
### **Dominance Score Formula**
```
Dominance Score = (price_vs_poc × 10) +
(price_vs_va × 5) +
(volume_imbalance × 0.5) +
(price_momentum × 100) +
(volume_trend × 5) +
(va_position × 15)
```
**Component Breakdown:**
- **price_vs_poc**: +1 if above POC, -1 if below (shows which side of equilibrium)
- **price_vs_va**: +2 if above VAH, -2 if below VAL, 0 if inside VA
- **volume_imbalance**: Percentage difference between upper and lower VA volumes
- **price_momentum**: 5-period SMA of price change (directional acceleration)
- **volume_trend**: Compares 5-period vs 20-period volume averages
- **va_position**: Normalized position within Value Area (-1 to +1)
The composite score is then smoothed using EMA with configurable sensitivity to reduce noise while maintaining responsiveness.
### **Market State Determination**
- **BUYERS Dominant**: Smooth dominance > +10 (bullish control)
- **SELLERS Dominant**: Smooth dominance < -10 (bearish control)
- **NEUTRAL**: Between -10 and +10 (balanced market)
## 📈 HOW TO USE THIS INDICATOR
### **Trend Identification**
- **Green background** indicates buyers are in control - look for long opportunities
- **Red background** indicates sellers are in control - look for short opportunities
- **Gray background** indicates neutral market - consider range-bound strategies
### **Signal Interpretation**
**Buy Signals** (green triangle) appear when:
- Dominance crosses above -10 from oversold conditions
- Previous state was not already bullish
- Suggests shift from seller to buyer control
**Sell Signals** (red triangle) appear when:
- Dominance crosses below +10 from overbought conditions
- Previous state was not already bearish
- Suggests shift from buyer to seller control
### **Value Area Context**
Monitor the information table (top-right) to understand market structure:
- **Price vs POC**: Shows if trading above/below equilibrium
- **Volume Imbalance**: Positive values favor buyers, negative favors sellers
- **Market State**: Current dominant force (BUYERS/SELLERS/NEUTRAL)
### **Multi-Timeframe Strategy**
The auto-timeframe feature analyzes higher timeframe structure:
- On 1-minute charts → analyzes 2-hour structure
- On 5-minute charts → analyzes Daily structure
- On 15-minute charts → analyzes Weekly structure
- On Daily charts → analyzes Yearly structure
This higher timeframe context helps avoid counter-trend trades against the dominant force.
### **Confluence Trading**
Strongest signals occur when multiple factors align:
1. Price above VAH + positive volume imbalance + buyers dominant = Strong bullish setup
2. Price below VAL + negative volume imbalance + sellers dominant = Strong bearish setup
3. Price at POC + neutral state = Potential breakout/breakdown pivot
## ⚙️ INPUT PARAMETERS
- **Higher Time Frame**: Select specific HTF or use 'Auto' for intelligent selection
- **Value Area %**: Percentage of volume contained in VA (default: 70%)
- **Show Buy/Sell Signals**: Toggle signal triangles visibility
- **Show Dominance Histogram**: Toggle histogram display
- **Signal Sensitivity**: EMA period for dominance smoothing (1-20, default: 5)
- **Number of Channels**: Market Profile resolution (10-50, default: 20)
- **Color Settings**: Customize buyer, seller, and neutral colors
## 🎨 VISUAL ELEMENTS
- **Histogram**: Shows smoothed dominance score (green = buyers, red = sellers)
- **Zero Line**: Neutral equilibrium reference
- **Overbought/Oversold Lines**: ±50 levels marking extreme dominance
- **Background Color**: Highlights current market state
- **Information Table**: Displays key metrics (state, dominance, POC relationship, volume imbalance, timeframe, bars in session, total volume)
- **Signal Shapes**: Triangle markers for buy/sell signals
## 🔔 ALERTS
The indicator includes three alert conditions:
1. **Buyers Dominate** - Fires on buy signal crossovers
2. **Sellers Dominate** - Fires on sell signal crossovers
3. **Dominance Shift** - Fires when dominance crosses zero line
## 📊 BEST PRACTICES
### **Timeframe Selection**
- **Scalping (1-5min)**: Focus on 2H-4H dominance shifts
- **Day Trading (15-60min)**: Monitor Daily and Weekly structure
- **Swing Trading (4H-Daily)**: Track Weekly and Monthly dominance
### **Confirmation Strategies**
1. **Trend Following**: Enter in direction of dominance above/below ±20
2. **Reversal Trading**: Fade extreme readings beyond ±50 when diverging with price
3. **Breakout Trading**: Look for dominance expansion beyond ±30 with increasing volume
### **Risk Management**
- Avoid trading during NEUTRAL states (dominance between -10 and +10)
- Use POC levels as logical stop-loss placement
- Consider VAH/VAL as profit targets for mean reversion
## ⚠️ LIMITATIONS & WARNINGS
**Data Requirements**
- Requires sufficient historical data on current chart (minimum 100 bars recommended)
- Lower timeframes may show fewer bars per HTF session initially
- More accurate results after several complete HTF sessions have formed
**Not a Standalone System**
- This indicator analyzes market structure and participant control
- Should be combined with price action, support/resistance, and risk management
- Does not guarantee profitable trades - past dominance does not predict future results
**Repainting Characteristics**
- Higher timeframe levels (POC, VAH, VAL) update as new bars form within the session
- Dominance score recalculates with each new bar
- Historical signals remain fixed, but current session data is developing
**Volume Limitations**
- Uses exchange-provided volume data which varies by instrument type
- Forex and some CFDs use tick volume (not actual transaction volume)
- Most accurate on instruments with reliable volume data (stocks, futures, crypto)
## 🔍 TECHNICAL NOTES
**Performance Optimization**
- Uses `max_bars_back=5000` for extended historical analysis
- Efficient array management prevents memory issues
- Automatic cleanup of session data on new period
**Calculation Method**
- Market Profile uses actual volume distribution, not TPO (Time Price Opportunity)
- Value Area expansion follows traditional Market Profile auction theory
- All calculations occur on the chart's current symbol and timeframe
## 📚 EDUCATIONAL VALUE
This indicator helps traders understand:
- How institutional traders use Market Profile to identify fair value
- The relationship between price, volume, and market acceptance
- Multi-factor analysis techniques for assessing market conditions
- The importance of higher timeframe structure in trade planning
## 🎓 RECOMMENDED READING
To better understand the concepts behind this indicator:
- "Mind Over Markets" by James Dalton (Market Profile foundations)
- "Markets in Profile" by James Dalton (Value Area analysis)
- Volume Profile analysis in institutional trading
## 💬 USAGE TERMS
This indicator is provided as an educational and analytical tool. It does not constitute financial advice, investment recommendations, or trading signals. Users are responsible for their own trading decisions and should conduct their own research and due diligence.
Trading involves substantial risk of loss. Past performance does not guarantee future results. Always use proper risk management and never risk more than you can afford to lose.
ค้นหาในสคริปต์สำหรับ "profitable"
RED-E Gamma Range DetectorRED-E Gamma Range Detector
Overview
The RED-E Gamma Range Detector identifies key support and resistance zones based on recent price action and volume distribution, combined with a simple momentum ribbon to help traders visualize trend direction. It's designed to highlight potential areas where price may react, inspired by the concept of gamma exposure levels in options trading.
How It Works
1. Support & Resistance Zones (Green & Red Boxes)
RED-E analyzes the recent price range over a customizable lookback period
It identifies high-probability support levels (green boxes) below current price
It identifies high-probability resistance levels (red boxes) above current price
These zones represent areas where price has historically shown increased activity
2. Gamma Flip Level (Yellow Dashed Line)
The yellow line represents the approximate "gamma flip" - the midpoint of the recent range
Above this line: Price tends to be more stable with range-bound behavior
Below this line: Price tends to be more volatile with trending behavior
This level acts as a key pivot point for market structure
3. Momentum Ribbon (Green/Red Fill)
A simple visual indicator using 9 and 21 period EMAs
Green ribbon: 9 EMA is above 21 EMA (bullish momentum)
Red ribbon: 9 EMA is below 21 EMA (bearish momentum)
Ribbon width shows strength of trend (wider = stronger trend)
How to Use
For Range Trading:
Look for buy signals near green support zones when above gamma flip
Look for sell signals near red resistance zones when above gamma flip
Price tends to bounce between zones in stable conditions
For Trend Trading:
Watch for breakouts above resistance or below support zones
Use the momentum ribbon to confirm trend direction
Wider ribbon gaps indicate stronger directional moves
For Risk Management:
Use support/resistance zones for stop-loss placement
Recognize increased volatility potential below the gamma flip
Adjust position sizing based on your proximity to key zones
Settings
Lookback Period: Number of bars to analyze (default: 20)
Lower values = more responsive to recent price action
Higher values = more stable, longer-term levels
Best Practices
Works best on liquid instruments (major stocks, indices, forex pairs)
Combine with other technical analysis tools for confirmation
Most effective on 1H, 4H, and daily timeframes
Always use proper risk management and stop losses
Why "RED-E"?
RED-E stands for being Ready to identify critical gamma levels, support/resistance zones, and momentum shifts - keeping you prepared for market moves before they happen.
Educational Note
This indicator approximates gamma exposure concepts using price and volume analysis. It does not use actual options data. The term "gamma" refers to the rate of change in options delta and how market makers hedge their positions, which can create support/resistance at certain price levels.
Disclaimer
This indicator is for educational and informational purposes only. It does not guarantee profitable trades. Past performance is not indicative of future results. Always conduct your own analysis and manage risk appropriately. Trading involves substantial risk of loss.
Recommended Categories
Primary Category:
✅ Support and Resistance
Secondary Categories:
✅ Momentum
✅ Trend Analysis
✅ Volatility
Slick Strategy Weekly PCS TesterInspired by the book “The Slick Strategy: A Unique Profitable Options Trading Method.” This indicator tests weekly SPX put-credit spreads set below Monday’s open and judged at Friday’s close.
WHAT IT DOES
• Sets weekly PCS level = Monday (or first trading day) OPEN − your offset; win/loss checked at Friday close.
• Optional core filter at entry: Price ≥ 200-SMA AND 10-SMA ≥ 20-SMA; pause if Price < both 10 & 20 while > 200.
• Reference modes: Strict = Mon OPEN vs Fri SMAs (no repaint); Mid = Mon OPEN vs Mon SMAs
KEY INPUTS
• Date range (Start/End) to limit backtest window.
• Offset mode/value (Points or Percent).
• Entry day (Monday only or first trading day).
• Core filters (On/Off) and Strict/Mid reference.
• SMA settings (source; 10/20/200 lengths).
• Table settings (position, size, padding, border).
VISUALS
• Active week line: Orange = trade taken; Gray = skipped.
• History: Green = win; Red = loss; Purple = skipped.
• Optional week bands highlight active/win/loss/skipped weeks (adjustable opacity).
TABLE
• Shows Date range, Trades, Wins, Losses, Win rate, and Active level (this week’s PCS price).
NOTES
• PCS level freezes at week open and persists through the week.
Force DashboardScalping Dashboard - Complete User Guide
Overview
This scalping system consists of two complementary TradingView indicators designed for intraday trading with no overnight holds:
Force Dashboard - Single-row table showing real-time market bias and entry signals
Large Order Detection - Visual diamonds showing institutional order flow
Together, they provide a complete at-a-glance view of market conditions optimized for quick entries and exits.
Recommended Timeframes
Primary Scalping Timeframes
1-minute chart: Ultra-fast scalps (30 seconds - 3 minutes hold time)
2-minute chart: Quick scalps (2-5 minutes hold time)
5-minute chart: Standard scalps (5-15 minutes hold time)
Best Practices
Use 1-2 minute for highly liquid instruments (ES, NQ, major forex pairs)
Use 5-minute for less liquid markets or if you prefer fewer signals
Never hold past the last hour of trading to avoid overnight risk
Set hard stop times (e.g., exit all positions by 3:45 PM EST)
Dashboard Components Explained
Core Indicators (Circles ●)
MACD (5/13/5)
Green ● = Bullish momentum (MACD histogram positive)
Red ● = Bearish momentum (MACD histogram negative)
Gray ● = No clear momentum
Use: Confirms trend direction and momentum shifts
EMA (9/20/50)
Green ● = Price > EMA9 > EMA20 (uptrend)
Red ● = Price < EMA9 < EMA20 (downtrend)
Gray ● = Choppy/sideways
Use: Identifies the immediate micro-trend
Stoch (5-period Stochastic)
Green ● = Oversold (<20) - potential reversal up
Red ● = Overbought (>80) - potential reversal down
Gray ● = Neutral zone (20-80)
Use: Spots reversal opportunities at extremes
RSI (7-period)
Green ● = Oversold (<30)
Red ● = Overbought (>70)
Gray ● = Neutral
Use: Confirms overbought/oversold conditions
CVD (Cumulative Volume Delta)
Green ● = CVD above its moving average (buying pressure)
Red ● = CVD below its moving average (selling pressure)
Gray ● = Neutral
Use: Shows overall buying vs selling pressure
ΔCVD (Delta CVD - Rate of Change)
Green ● = CVD accelerating upward (buying acceleration)
Red ● = CVD accelerating downward (selling acceleration)
Gray ● = No acceleration
Use: Detects momentum shifts in order flow
Imbal (Order Flow Imbalance)
Green ● = Buy pressure >2x sell pressure
Red ● = Sell pressure >2x buy pressure
Gray ● = Balanced
Use: Identifies extreme one-sided order flow
Vol (Volume Strength)
Green ● = Volume >1.5x average (strong interest)
Red ● = Volume <0.7x average (low interest)
Gray ● = Normal volume
Yellow background = Volume surge (>2x average) - BIG MOVE ALERT
Use: Confirms conviction behind price moves
Tape (Tape Speed)
Green ● = Fast order flow (>1.3x normal)
Red ● = Slow order flow (<0.7x normal)
Gray ● = Normal speed
Yellow background = Very fast tape (>1.5x) - RAPID EXECUTION ALERT
Use: Measures urgency and speed of orders
Key Levels
Support (Supp)
Shows the nearest high-volume support level below current price
Bright Green background = Price is AT support (within 0.3%) - BOUNCE ZONE
Green background = Price above support (healthy)
Red background = Price below support (broken support, now resistance)
Resistance (Res)
Shows the nearest high-volume resistance level above current price
Bright Orange background = Price is AT resistance (within 0.3%) - REJECTION ZONE
Red background = Price below resistance (facing overhead supply)
Green background = Price above resistance (breakout)
These levels update automatically every 3 bars based on volume profile
Entry Signal Components
Score
Displays format: "6L" (6 long indicators) or "4S" (4 short indicators)
Bright Green = 6-7 indicators aligned for long
Light Green = 5 indicators aligned for long
Yellow = 4 indicators aligned (weaker setup)
Gray = No alignment
Red/Orange colors = Same scale for short setups
Score of 5+ indicates high-probability setup
SCALP (Main Entry Signal)
BRIGHT GREEN "LONG" = High-quality long scalp (Score 5+)
Green "LONG" = Decent long scalp (Score 4)
BRIGHT ORANGE "SHORT" = High-quality short scalp (Score 5+)
Red "SHORT" = Decent short scalp (Score 4)
Gray "WAIT" = No clear setup - STAY OUT
Entry Strategies
Strategy 1: High-Probability Scalps (Conservative)
When to Enter:
SCALP column shows BRIGHT GREEN "LONG" or BRIGHT ORANGE "SHORT"
Score is 5 or higher
Vol or Tape has yellow background (volume surge)
Example Long Setup:
SCALP = BRIGHT GREEN "LONG"
Score = 6L
Vol = Yellow background
Price AT Support (bright green Supp cell)
EMA, MACD, CVD, ΔCVD, Imbal all green
Entry: Enter immediately on next candle
Target: 0.5-1% move or resistance level
Stop: Below support or -0.3%
Hold Time: 2-10 minutes
Strategy 2: Momentum Scalps (Aggressive)
When to Enter:
Tape has yellow background (fast tape)
Vol has yellow background (volume surge)
ΔCVD is green (for longs) or red (for shorts)
Imbal shows strong imbalance in your direction
Score is 4+
Example Short Setup:
Tape & Vol = Yellow backgrounds
ΔCVD = Red, Imbal = Red
Price AT Resistance (bright orange)
Score = 5S
Entry: Enter immediately
Target: Quick 0.3-0.7% move
Stop: Tight -0.2%
Hold Time: 1-5 minutes
Strategy 3: Reversal Scalps (Mean Reversion)
When to Enter:
Stoch shows oversold (green) or overbought (red)
RSI confirms the extreme
Price is AT Support (for longs) or AT Resistance (for shorts)
ΔCVD and Imbal start reversing direction
Score is 4+
Example Long Setup:
Stoch = Green (oversold)
RSI = Green (oversold)
Supp = Bright green (at support)
ΔCVD turns green
Imbal turns green
Score = 4L or 5L
Entry: Wait for confirmation candle
Target: Move back to EMA9 or mid-range
Stop: Below the low
Hold Time: 3-8 minutes
Large Order Detection Usage
Diamond Signals
Green diamonds below bar = Large buy orders (institutional buying)
Red diamonds above bar = Large sell orders (institutional selling)
Size matters: Larger diamonds = larger order flow
How to Use with Dashboard
Confirmation Entries
Dashboard shows "LONG" signal
Green diamond appears
Enter immediately - institutions are buying
Divergence Alerts (CAUTION)
Dashboard shows "LONG" signal
RED diamond appears (institutions selling)
DO NOT ENTER - conflicting order flow
Cluster Patterns
Multiple green diamonds in row = Strong accumulation, stay long
Multiple red diamonds in row = Strong distribution, stay short
Alternating colors = Chop, avoid trading
Risk Management Rules
Position Sizing
Risk 0.5-1% of account per scalp
Maximum 3 concurrent positions
Reduce size after 2 consecutive losses
Stop Loss Guidelines
Tight stops: 0.2-0.3% for 1-2 min charts
Standard stops: 0.3-0.5% for 5 min charts
Always use stop loss - no exceptions
Place stops below support (longs) or above resistance (shorts)
Take Profit Targets
Target 1: 0.3-0.5% (take 50% off)
Target 2: 0.7-1% (take remaining 50%)
Move stop to breakeven after Target 1 hit
Trail stop if Score remains high
Time-Based Exits
Exit immediately if:
SCALP changes from LONG/SHORT to WAIT
Score drops below 3
Large diamond appears in opposite direction
Maximum hold time: 15 minutes (even if profitable)
Hard exit time: 30 minutes before market close
Trading Sessions
Best Times to Scalp
High-Liquidity Sessions
9:30-11:00 AM EST (Market open, highest volume)
2:00-3:30 PM EST (Afternoon session, good moves)
Avoid
11:30 AM-1:30 PM EST (Lunch, low volume)
Last 30 minutes (unpredictable, don't initiate new trades)
News releases (wait 5 minutes for volatility to settle)
Common Patterns & Setups
The Perfect Storm (Highest Probability)
Score = 6L or 7L
SCALP = BRIGHT GREEN
Vol + Tape = Yellow backgrounds
Green diamond appears
Price AT Support
Win rate: ~70-80%
The Fade Setup (Counter-Trend)
Price hits resistance (bright orange)
Stoch + RSI overbought (red)
Red diamond appears
CVD starts turning red
SCALP shows "SHORT"
Win rate: ~60-70%
The Breakout Continuation
Price breaks resistance (Res turns green)
EMA, MACD green
Vol surge (yellow)
Multiple green diamonds
SCALP = "LONG"
Win rate: ~65-75%
Warning Signs - DO NOT TRADE
Red Flags
❌ SCALP shows "WAIT"
❌ Score below 3
❌ Vol and Tape both gray (no volume)
❌ Conflicting signals (dashboard says LONG but red diamonds appearing)
❌ Alternating green/red circles (choppy market)
❌ Support and Resistance very close together (tight range)
Market Conditions to Avoid
Low volume periods
Major news releases (first 5 minutes after)
First 2 minutes after market open
Wide spreads
Consecutive losing trades (take a break after 2 losses)
Quick Reference Checklist
Before Taking ANY Trade:
☑ SCALP shows LONG or SHORT (not WAIT)
☑ Score is 4 or higher
☑ Vol or Tape shows activity
☑ No conflicting diamond signals
☑ Stop loss level identified
☑ Target profit level identified
☑ Not in restricted time periods
After Entering:
☑ Set stop loss immediately
☑ Set profit targets
☑ Watch SCALP column - exit if changes to WAIT
☑ Watch for opposite-colored diamonds
☑ Move stop to breakeven after first target
☑ Exit all by market close
Advanced Tips
Scalping Psychology
Be patient: Wait for Score 5+ setups
Be decisive: When signal appears, act immediately
Be disciplined: Follow your stop loss always
Be flexible: Exit quickly if dashboard reverses
Optimization
Backtest on your specific instrument
Adjust RSI/Stoch levels for your market
Fine-tune volume thresholds
Keep a trade journal to track which setups work best
Multi-Timeframe Confirmation
Use 5-min dashboard as "trend filter"
Take 1-min trades only in direction of 5-min SCALP signal
Increases win rate by ~10-15%
Troubleshooting
Q: Dashboard shows WAIT most of the time
Normal - scalping is about patience. Quality > Quantity
3-8 good setups per day is excellent
Q: Too many false signals
Increase minimum Score requirement to 5 or 6
Only trade with volume surge (yellow backgrounds)
Add large order detection confirmation
Q: Signals too slow
You may be on too high a timeframe
Try 1-minute chart for faster signals
Ensure real-time data feed is active
Q: Support/Resistance not updating
Normal - updates every 3 bars
If completely stuck, remove and re-add indicator
Summary
This scalping system works best when:
✅ Multiple indicators align (Score 5+)
✅ Volume and tape speed confirm the move
✅ Order flow (diamonds) confirms direction
✅ Price is at key levels (support/resistance)
✅ You manage risk strictly
✅ You exit before market close
The golden rule: When SCALP says WAIT, you WAIT. Discipline beats frequency.
chart Pattern & Candle sticks Strategy# **XAUUSD Pattern & Candle Strategy - Complete Description**
## **Overview**
This Pine Script indicator is a comprehensive multi-factor trading system specifically designed for **XAUUSD (Gold) scalping and swing trading**. It combines classical technical analysis methods including candlestick patterns, chart patterns, moving averages, and volume analysis to generate high-probability buy/sell signals with automatic stop-loss and take-profit levels.
***
## **Core Components**
### **1. Moving Average System (Triple MA)**
**Purpose:** Identifies trend direction and momentum
- **Fast MA (20-period)** - Short-term price action
- **Medium MA (50-period)** - Intermediate trend
- **Slow MA (200-period)** - Long-term trend direction
**How it works:**
- **Bullish alignment**: MA20 > MA50 > MA200 (all pointing up)
- **Bearish alignment**: MA20 < MA50 < MA200 (all pointing down)
- **Crossover signals**: When Fast MA crosses Medium MA, it triggers buy/sell signals
- **Choice of SMA or EMA**: Adjustable based on preference
**Visual indicators:**
- Blue line = Fast MA
- Orange line = Medium MA
- Light red line = Slow MA
- Green background tint = Bullish trend
- Red background tint = Bearish trend
---
### **2. Candlestick Pattern Recognition (13 Patterns)**
**Purpose:** Identifies reversal and continuation signals based on price action
#### **Bullish Patterns (Signal potential upward moves):**
1. **Hammer** 🔨
- Long lower wick (2x body size)
- Small body at top
- Indicates rejection of lower prices (buyers stepping in)
- Best at support levels
2. **Inverted Hammer**
- Long upper wick
- Small body at bottom
- Shows buying pressure despite initial selling
3. **Bullish Engulfing** 📈
- Green candle completely engulfs previous red candle
- Strong reversal signal
- Body must be 1.2x larger than previous
4. **Morning Star** ⭐
- 3-candle pattern
- Red candle → Small indecision candle → Large green candle
- Powerful reversal at bottoms
5. **Piercing Line** ⚡
- Green candle closes above 50% of previous red candle
- Indicates strong buying interest
6. **Bullish Marubozu**
- Almost no wicks (95% body)
- Very strong bullish momentum
- Body must be 1.3x average size
#### **Bearish Patterns (Signal potential downward moves):**
7. **Shooting Star** 💫
- Long upper wick
- Small body at bottom
- Indicates rejection of higher prices (sellers in control)
- Best at resistance levels
8. **Hanging Man**
- Similar to hammer but appears at top
- Warning of potential reversal down
9. **Bearish Engulfing** 📉
- Red candle completely engulfs previous green candle
- Strong reversal signal
10. **Evening Star** 🌙
- 3-candle pattern (opposite of Morning Star)
- Green → Small → Large red candle
- Powerful top reversal
11. **Dark Cloud Cover** ☁️
- Red candle closes below 50% of previous green candle
- Indicates strong selling pressure
12. **Bearish Marubozu**
- Almost no wicks, pure red body
- Very strong bearish momentum
#### **Neutral Pattern:**
13. **Doji**
- Open and close nearly equal (tiny body)
- Indicates indecision
- Often precedes major moves
**Detection Logic:**
- Compares body size, wick ratios, and position relative to previous candles
- Uses 14-period average body size as reference
- All patterns validated against volume confirmation
***
### **3. Chart Pattern Recognition**
**Purpose:** Identifies major support/resistance and reversal patterns
#### **Patterns Detected:**
**Double Bottom** 📊 (Bullish)
- Two lows at approximately same level
- Indicates strong support
- Breakout above neckline triggers buy signal
- Most reliable at major support zones
**Double Top** 📊 (Bearish)
- Two highs at approximately same level
- Indicates strong resistance
- Breakdown below neckline triggers sell signal
- Most reliable at major resistance zones
**Support & Resistance Levels**
- Automatically plots recent pivot highs (resistance)
- Automatically plots recent pivot lows (support)
- Uses 3-bar strength for validation
- Levels shown as dashed horizontal lines
**Price Action Patterns**
- **Uptrend detection**: Higher highs + higher lows
- **Downtrend detection**: Lower highs + lower lows
- Confirms overall market structure
***
### **4. Volume Analysis**
**Purpose:** Confirms signal strength and filters false signals
**Metrics tracked:**
- **Volume MA (20-period)**: Baseline average volume
- **High volume threshold**: 1.5x the volume average
- **Volume increase**: Current volume > previous 2 bars
**How it's used:**
- All buy/sell signals **require volume confirmation**
- High volume = institutional participation
- Low volume signals are filtered out
- Prevents whipsaw trades during quiet periods
**Visual indicator:**
- Dashboard shows "High" volume in orange when active
- "Normal" shown in gray during low volume
***
### **5. Signal Generation Logic**
**BUY SIGNALS triggered when ANY of these occur:**
1. **Candlestick + Volume**
- Bullish candle pattern detected
- High volume confirmation
- Price above Fast MA
2. **MA Crossover + Volume**
- Fast MA crosses above Medium MA
- High volume confirmation
3. **Double Bottom Breakout**
- Price breaks above support level
- Volume confirmation present
4. **Trend Continuation**
- Uptrend structure intact (higher highs/lows)
- All MAs in bullish alignment
- Price above Fast MA
- Volume confirmation
**SELL SIGNALS triggered when ANY of these occur:**
1. **Candlestick + Volume**
- Bearish candle pattern detected
- High volume confirmation
- Price below Fast MA
2. **MA Crossunder + Volume**
- Fast MA crosses below Medium MA
- High volume confirmation
3. **Double Top Breakdown**
- Price breaks below resistance level
- Volume confirmation present
4. **Trend Continuation**
- Downtrend structure intact (lower highs/lows)
- All MAs in bearish alignment
- Price below Fast MA
- Volume confirmation
***
### **6. Risk Management System**
**Automatic Stop Loss Calculation:**
- Based on ATR (Average True Range) - 14 periods
- **Formula**: Entry price ± (ATR × SL Multiplier)
- **Default multiplier**: 1.5 (adjustable)
- Adapts to market volatility automatically
**Automatic Take Profit Calculation:**
- **Formula**: Entry price ± (ATR × TP Multiplier)
- **Default multiplier**: 2.5 (adjustable)
- **Default Risk:Reward ratio**: 1:1.67
- Higher TP multiplier = more aggressive targets
**Position Management:**
- Tracks ONE position at a time (no pyramiding)
- Automatically closes position when:
- Stop loss is hit
- Take profit is reached
- Opposite MA crossover occurs
- Prevents revenge trading and over-leveraging
**Visual Representation:**
- **Red horizontal line** = Stop Loss level
- **Green horizontal line** = Take Profit level
- Lines remain on chart while position is active
- Automatically disappear when position closes
***
### **7. Visual Elements**
**On-Chart Displays:**
1. **Moving Average Lines**
- Fast MA (Blue, thick)
- Medium MA (Orange, thick)
- Slow MA (Red, thin)
2. **Support/Resistance**
- Green crosses = Support levels
- Red crosses = Resistance levels
3. **Buy/Sell Arrows**
- Large GREEN "BUY" label below bars
- Large RED "SELL" label above bars
4. **Pattern Labels** (Small markers)
- "Hammer", "Bull Engulf", "Morning Star" (green, below bars)
- "Shooting Star", "Bear Engulf", "Evening Star" (red, above bars)
- "Double Bottom" / "Double Top" (blue/orange)
5. **Signal Detail Labels** (Medium size)
- Shows signal reason (e.g., "Bullish Candle", "MA Cross Up")
- Displays Entry, SL, and TP prices
- Color-coded (green for long, red for short)
6. **Background Coloring**
- Light green tint = Bullish MA alignment
- Light red tint = Bearish MA alignment
***
### **8. Information Dashboard**
**Top-right corner table showing:**
| Metric | Description |
|--------|-------------|
| **Position** | Current trade status (LONG/SHORT/None) |
| **MA Trend** | Overall trend direction (Bullish/Bearish/Neutral) |
| **Volume** | Current volume status (High/Normal) |
| **Pattern** | Last detected candlestick pattern |
| **ATR** | Current volatility measurement |
**Purpose:**
- Quick at-a-glance market assessment
- Real-time position tracking
- No need to check multiple indicators
***
### **9. Alert System**
**Complete alert coverage for:**
✅ **Entry Alerts**
- "Buy Signal" - Triggers when buy conditions met
- "Sell Signal" - Triggers when sell conditions met
✅ **Exit Alerts**
- "Long TP Hit" - Take profit reached on long position
- "Long SL Hit" - Stop loss triggered on long position
- "Short TP Hit" - Take profit reached on short position
- "Short SL Hit" - Stop loss triggered on short position
**How to use:**
1. Click "Create Alert" button
2. Select desired alert from dropdown
3. Set notification method (popup, email, SMS, webhook)
4. Never miss a trade opportunity
***
## **Recommended Settings**
### **For Scalping (Quick trades):**
- **Timeframe**: 5-minute
- **Fast MA**: 9
- **Medium MA**: 21
- **Slow MA**: 50
- **SL Multiplier**: 1.0
- **TP Multiplier**: 2.0
- **Volume Threshold**: 1.5x
### **For Swing Trading (Longer holds):**
- **Timeframe**: 1-hour or 4-hour
- **Fast MA**: 20
- **Medium MA**: 50
- **Slow MA**: 200
- **SL Multiplier**: 2.0
- **TP Multiplier**: 3.0
- **Volume Threshold**: 1.3x
### **Best Trading Hours for XAUUSD:**
- **Asian Session**: 00:00 - 08:00 GMT (lower volatility)
- **London Session**: 08:00 - 16:00 GMT (high volatility) ⭐
- **New York Session**: 13:00 - 21:00 GMT (highest volume) ⭐
- **London-NY Overlap**: 13:00 - 16:00 GMT (BEST for scalping) 🔥
***
## **How to Use This Strategy**
### **Step 1: Setup**
1. Open TradingView
2. Load XAUUSD chart
3. Select timeframe (5m, 15m, 1H, or 4H)
4. Add indicator from Pine Editor
5. Adjust settings based on your trading style
### **Step 2: Wait for Signals**
- Watch for GREEN "BUY" or RED "SELL" labels
- Check the signal reason in the detail label
- Verify dashboard shows favorable conditions
- Confirm volume is "High" (not required but preferred)
### **Step 3: Enter Trade**
- Enter at market or limit order near signal price
- Note the displayed Entry, SL, and TP prices
- Set your broker's SL/TP to match indicator levels
### **Step 4: Manage Position**
- Watch for SL/TP lines on chart
- Monitor dashboard for trend changes
- Exit manually if opposite MA crossover occurs
- Let SL/TP do their job (don't move them!)
### **Step 5: Review & Learn**
- Track win rate over 20+ trades
- Adjust multipliers if needed
- Note which patterns work best for you
- Refine entry timing
***
## **Key Advantages**
✅ **Multi-confirmation approach** - Reduces false signals significantly
✅ **Automatic risk management** - No manual calculation needed
✅ **Adapts to volatility** - ATR-based SL/TP adjusts to market conditions
✅ **Volume filtered** - Ensures institutional participation
✅ **Visual clarity** - Easy to understand at a glance
✅ **Complete alert system** - Never miss opportunities
✅ **Pattern education** - Learn patterns as they appear
✅ **Works on all timeframes** - Scalping to swing trading
***
## **Limitations & Considerations**
⚠️ **Not a holy grail** - No strategy wins 100% of trades
⚠️ **Requires practice** - Demo trade first to understand signals
⚠️ **Market conditions matter** - Works best in trending or volatile markets
⚠️ **News events** - Avoid trading during major economic releases
⚠️ **Slippage on 5m** - Fast markets may have execution delays
⚠️ **Pattern subjectivity** - Some patterns may trigger differently than expected
***
## **Risk Management Rules**
1. **Never risk more than 1-2% per trade**
2. **Maximum 3 positions per day** (avoid overtrading)
3. **Don't trade during major news** (NFP, FOMC, etc.)
4. **Use proper position sizing** (0.01 lot per $100 for micro accounts)
5. **Keep trade journal** (track patterns, win rate, mistakes)
6. **Stop trading after 3 consecutive losses** (psychological reset)
7. **Don't move stop loss further away** (accept losses)
8. **Take partial profits** at 1:1 R:R if desired
***
## **Expected Performance**
**Realistic expectations:**
- **Win rate**: 50-65% (depending on market conditions and timeframe)
- **Risk:Reward**: 1:1.67 default (adjustable to 1:2 or 1:3)
- **Signals per day**: 3-8 on 5m, 1-3 on 1H
- **Best months**: High volatility periods (news events, economic uncertainty)
- **Drawdowns**: Expect 3-5 losing trades in a row occasionally
***
## **Customization Options**
All inputs are adjustable in settings panel:
**Moving Averages:**
- Type (SMA or EMA)
- All three period lengths
**Volume:**
- Volume MA length
- High volume multiplier threshold
**Chart Patterns:**
- Pattern strength (bars for pivot detection)
- Show/hide pattern labels
**Risk Management:**
- ATR period
- Stop loss multiplier
- Take profit multiplier
**Display:**
- Toggle pattern labels
- Customize colors (in code)
***
## **Conclusion**
This is a **professional-grade, multi-factor trading system** that combines the best of classical technical analysis with modern risk management. It's designed to give clear, actionable signals while automatically handling the complex calculations of stop loss and take profit levels.
**Best suited for traders who:**
- Understand basic technical analysis
- Can follow rules consistently
- Prefer systematic approach over gut feeling
- Want visual confirmation before entering trades
- Value proper risk management
**Start with demo trading** for at least 20-30 trades to understand how the signals work in different market conditions. Once comfortable and profitable on demo, transition to live trading with minimal risk per trade.
Happy trading! 📈🎯
LONG/SHORT Signals by YCGH CapitalThis indicator uses volatility as its primary input to help identify potential market
bottoms and tops. By measuring extreme price movements and volatility spikes, it generates
signals for both long (buy) and short (sell) opportunities.
BEST SUITED FOR:
This indicator works best when the market is in a clear trend - either uptrend or downtrend.
It excels at catching reversal points within trending markets and identifying exhaustion
points where trends may reverse.
HOW TO USE THIS INDICATOR:
1. IDENTIFY SIGNAL TYPES:
• Long Filtered (Dark Blue, Tiny): Conservative buy signals with higher probability
• Long Aggressive (Aqua, Small): Early buy signals for catching bottoms faster
• Short Filtered (Dark Red, Tiny): Conservative sell signals with confirmation
• Short Aggressive (Orange, Small): Early sell signals for catching tops
2. TRADING APPROACHES:
Conservative Traders:
- Focus only on Filtered signals (tiny arrows)
- Wait for full confirmation before entering
- Lower risk, fewer trades, higher win rate
Aggressive Traders:
- Use Aggressive signals (small arrows) for earlier entries
- Accept more risk for potentially larger profits
- More trades, catch moves from the beginning
Balanced Approach:
- Use Aggressive signals to spot opportunities early
- Confirm with Filtered signals or use them to add to positions
- Scale in with Aggressive, scale out with opposite signals
3. RISK MANAGEMENT:
- Always use stop losses below recent swing lows (long) or above swing highs (short)
- Risk less per trade on Aggressive signals (they have more false signals)
- Risk more per trade on Filtered signals (higher probability setups)
- Consider the broader trend - signals aligned with trend work better
4. COMBINATION STRATEGIES:
- Use with trend indicators (moving averages) to filter signals
- Combine with support/resistance levels for higher probability entries
- Look for signals near key price levels for best results
- Use volume confirmation to validate signal strength
5. TIMEFRAME RECOMMENDATIONS:
- 15min-1H charts: Day trading with quick reversals
- 4H-Daily charts: Swing trading with multi-day holds (RECOMMENDED)
- Weekly charts: Position trading for long-term trend reversals
IMPORTANT NOTES:
- Not all signals will result in profitable trades
- Best performance in trending markets, may produce false signals in sideways/choppy conditions
- Combine with your own analysis and risk management rules
- Past performance does not guarantee future results
ZynAlgo S&R ProZynAlgo S&R Pro identifies confirmed swing highs and swing lows, marks them on the chart, and draws single horizontal liquidity lines that extend from each confirmed swing until the next swing of the same type occurs. The tool can optionally recolor candles based on whether the current close is above or below the previous close. It also exposes alert conditions for new swing points and for when price reaches the most recent buy-side or sell-side liquidity line.
Important: This is a visual analysis tool. It does not open, manage, or close positions. It is provided for educational and informational purposes only.
How it works (under the hood)
Swing detection (confirmed):
The script uses ta.pivothigh/ta.pivotlow with symmetric left/right bars defined by Left bar & Right bar. A swing is considered only after the bar is confirmed.
Swing markers:
When enabled, confirmed swing highs/lows are marked with small circles above/below bars. The offset equals the left/right length to align with the confirmed pivot location.
Liquidity lines:
On each swing high, the script ends (anchors) the previous buy-side line at the pivot’s bar, then creates a new dotted/dashed/solid horizontal line at that swing price and extends it forward.
On each swing low, it does the same for sell-side lines.
Between swing events, the most recent buy-side and sell-side lines continue extending to the current bar.
Alerts:
Swing High / Swing Low Created — fires on confirmation of a new swing.
Buy Side Liquidity Raid — when price crosses over the most recent swing-high line.
Sell Side Liquidity Raid — when price crosses under the most recent swing-low line.
Optional candle coloring:
If enabled, candles can be recolored by comparing current close to the previous close, with independent toggles for body, borders, and wicks.
Inputs & recommended tooltips (copy-friendly)
Swing High/Low Setting
Left bar & Right bar (len_l)
Tooltip: “Bars to the left/right required to confirm a pivot. Larger values = fewer but stronger swing points (default: 20).”
Show Swing High Swing Low (flg_shsl)
Tooltip: “Plot small circles at confirmed swing highs (red) and swing lows (blue).”
(Note: i_labelcolor_price is present but unused in visible drawings—safe to ignore or reserve for future use.)
Liquidity Pools Settings
Show Liquidity Pools (flg_lq)
Tooltip: “Draw a horizontal line at each confirmed swing. The line extends forward until the next swing of the same type appears.”
Line Width (i_width)
Tooltip: “Thickness of liquidity lines (1–6).”
Line Style (i_linestyle)
Tooltip: “Choose solid, dashed, or dotted style for liquidity lines.”
Buy Side Liquidity Color (i_linecolor_bs)
Tooltip: “Color for swing-high liquidity lines (default: red).”
Sell Side Liquidity Color (i_linecolor_ss)
Tooltip: “Color for swing-low liquidity lines (default: blue).”
Candles
Color bars based on previous close (use_prev_close)
Tooltip: “If enabled, candle colors are based on whether close > previous close (Up) or not (Down).”
Up Color / Down Color
Tooltip: “Colors used for up vs. down determination.”
Body / Borders / Wick (apply toggles)
Tooltip: “Choose which candle parts to recolor.”
Alerts available (names as shown in the Create Alert dialog)
Swing High
Triggers when a new swing high is confirmed. Select this condition to be notified about newly formed swing highs.
Swing Low
Triggers when a new swing low is confirmed.
Buy Side Liquidity Raid
Triggers when price crosses above the most recent swing-high liquidity line (crossover(high, LSH)).
Sell Side Liquidity Raid
Triggers when price crosses below the most recent swing-low liquidity line (crossunder(low, LSL)).
Quick start (suggested workflow)
Add to chart: Apply ZynAlgo S&R Pro to your symbol and timeframe.
Choose sensitivity: Adjust Left bar & Right bar. Higher values focus on more significant swing points; lower values react faster.
Toggle visuals:
Enable Show Swing High Swing Low to see swing markers.
Enable Show Liquidity Pools to draw/extend liquidity lines. Pick the line style, width, and colors you prefer.
(Optional) Candle colors: Turn on Color bars based on previous close and choose which parts to color.
Set alerts:
Open Create Alert → Condition: ZynAlgo S&R Pro → choose Swing High, Swing Low, Buy Side Liquidity Raid, or Sell Side Liquidity Raid as needed.
Practical notes & limitations
Confirmed swings only: Pivots are plotted after confirmation (i.e., once the required left/right bars are complete). This avoids repainting the pivot location.
One active line per side: Only the most recent buy-side and sell-side liquidity lines extend to the right; prior lines are ended when a new swing of the same side appears.
Timeframes & instruments: Parameter sensitivity can vary across markets/timeframes. Consider tuning Left bar & Right bar to match volatility.
No orders are placed: This indicator does not execute trades or manage positions.
Compliance & fair-use guidance
No performance promises: This tool does not guarantee profitable results and should not be described as “signals,” “guaranteed,” “best,” or similar claims. It is an analysis aid that visualizes historical swing points, liquidity levels, and optional candle coloring.
Educational intent: Use it to support your chart review and alerting workflow; combine with your own judgment and risk controls.
Alerts are informational: Alerts reflect the conditions described above and do not constitute financial advice.
Change log (summary of core features)
Swing detection with configurable left/right bars; optional swing markers.
Auto-extending buy-side/sell-side liquidity lines with customizable style/width/colors.
Four alert conditions (new swing highs/lows and liquidity raids).
Optional candle recoloring with separate toggles for body/borders/wicks.
Dynamic Line Management
Unlike static support/resistance tools, ZynAlgo S&R Pro automatically manages the lifecycle of each liquidity line — removing outdated levels the moment new structure forms.
This ensures the chart always reflects the most relevant active zones.
Structure + Liquidity Integration
By combining price structure (swing points) with liquidity visualization, it bridges the gap between classic S&R and modern liquidity-based interpretation — a fusion rarely found in lightweight indicators.
Noise-Free Design
The script plots only the most essential elements: confirmed swings, active liquidity lines, and optional candle color context.
It avoids overlapping labels, text clutter, or unnecessary metrics — ideal for traders who prefer clarity and precision.
Non-Repainting Logic
All pivots are confirmed only after the required right-side bars are closed, ensuring all swing points and lines remain fixed once plotted.
This gives confidence in backtesting and visual analysis without misleading signals.
Lightweight & Efficient
Despite tracking multiple dynamic lines, the algorithm is optimized for performance (using arrays and efficient bar updates), making it suitable for both high- and low-timeframe analysis.
Adaptable Across Market Types
Equally applicable to forex, crypto, indices, and commodities, the algorithm’s sensitivity parameter lets users adjust to volatility differences between instruments.
Purely Analytical
The tool does not provide trade signals or predictions.
Its design supports price-action interpretation, liquidity mapping, and structure confirmation — helping traders read context rather than react to noise.
🔶 RISK DISCLAIMER
Trading is risky & most day traders lose money. All content, tools, scripts, articles, & education provided by ZynAlgo are purely for informational & educational purposes only. Past performance does not guarantee future results.
Ultimate MACD Suite [BigBeluga]🔵 OVERVIEW
The Ultimate MACD Suite is an advanced momentum-based system that enhances the classic MACD with modern features tailored for professional traders.
It transforms MACD into a full market-decision engine — offering multi-timeframe confluence, adaptive histogram behavior, divergence detection, heatmap trend visualization, and actionable reversal signals.
This toolkit goes far beyond standard MACD, helping traders identify trend momentum shifts, exhaustion zones, high-probability reversal areas, and breakout confirmation signals across multiple timeframes simultaneously. It's to be used as part of a major trading system and to simplify usage of the MACD.
⚠️ Note:
This is not a traditional MACD — it uses normalized values , enhanced visual feedback, and a multi-timeframe dashboard engine for superior signal quality and clarity.
🔵 CONCEPTS
Combines MACD momentum, signal-line crossovers, and histogram reversals into one system
Uses normalized scaling to detect extreme momentum levels and exhaustion zones
Multi-timeframe dashboard displays consensus signal alignment across several timeframes
Divergence engine identifies bullish & bearish trend weakening early
Heatmap mode visually distinguishes strong trend phases from neutral or fading momentum
Reversal arrows & crosses highlight actionable turning points on chart
🔵 FEATURES
Normalized MACD Engine — improves signal clarity across all assets/timeframes
MACD Heatmap Mode — color-coded slope intensity for trend strength monitoring
MACD Rising and Falling Mode — color-coded rising and falling MACD regimes
Histogram Reversal Detection — early momentum fade signal before price turns
Signal-Line Momentum Shifts — bullish ▲ & bearish ▼ alerts on cross-confirmation
Overbought/Oversold Bands — enhanced visual thresholds at ±80 levels
Smart Divergence Detection (Non-Lag) — confirms regular bullish & bearish divergences
Multi-Timeframe Dashboard — MACD, signal, histogram & divergence signals across 5+ TFs
Reversal Push-Filter — ensures only clean signals after confirmed momentum inflection
On-Chart Reversal Labels — optional compact signal markers for clean visual execution
Histogram Color Logic — rising/falling or heatmap mode for deeper momentum reading
🔵 HOW TO USE
Look for MACD crossing above signal + green histogram to confirm bullish momentum
Use ▼ and ▲ arrows to catch confirmed momentum reversals
Monitor the dashboard — the more timeframes align, the stronger the setup
Watch divergences for trend exhaustion or reversal setups
Treat histogram trend shifts as early momentum clues before price reacts
Use ±80 levels to identify overheated conditions & fade opportunities
Combine with structure, volume, or BigBeluga liquidity tools for higher accuracy
🔵 ALERTS
The indicator includes a full alert suite for automation and real-time trade readiness:
MACD crossovers (Bullish / Bearish)
Histogram reversals & zero-line shifts
Bullish / Bearish divergence detection
Overbought / Oversold MACD alerts
Bullish ▲ and bearish ▼ reversal triggers
Use these alerts to automate signal monitoring or feed algorithmic systems.
🔵 CONCLUSION
The Ultimate MACD Suite transforms a classic indicator into a powerful trading engine.
With multi-timeframe alignment, heatmapping, divergence logic, normalized scaling and automated signals, it becomes an elite momentum-confirmation and reversal-timing system built for serious traders.
Whether scalping intraday or managing swing positions, this MACD engine helps identify the most profitable phases of trend movement — while warning early when a trend is weakening.
สคริปต์แบบชำระเงิน
Binary Options Gold Scalping [TradingFinder] 1 & 5 Min Strategy🔵 Introduction
In binary options trading, price movements are often driven by the market’s tendency to reach key liquidity zones. These areas include Liquidity, Fair Value Gaps (FVGs), and Order Blocks (OBs), zones where a large number of pending orders are concentrated.
When price reaches one of these zones, it typically enters a Liquidity Sweep phase to collect available liquidity. After this process, the market often reacts sharply, either reversing direction or continuing its move with renewed momentum. Understanding this cycle forms the foundation of most smart money-based binary options strategies.
In this analytical approach, a Liquidity Sweep is usually seen as a False Breakout, often recognized through a distinctive candle confirmation pattern. The pattern appears when price briefly breaks a level to trigger stops, then quickly returns within range. This formation is one of the most reliable reversal signals for short-term trades and plays a central role in many binary options strategies.
After a liquidity sweep, price often returns to Fair Value Gap (FVG) or Order Block (OB) areas to restore balance in the market. These are zones where institutional orders are typically placed, and reactions around them can create high-probability trade setups. In binary options trading, this quick reaction following a sweep and retrace into an FVG or OB provides one of the best entry opportunities for short-term trades.
By combining the concepts of Liquidity Sweep, Fair Value Gap, and Order Block, traders can build a precise binary options strategy based on smart money behavior, allowing them to identify market reversals with greater confidence and enter at the optimal moment.
Bullish Setup :
Bearish Setup :
🔵 How to Use
This indicator is built on the Smart Money Concept (SMC) framework and serves as a core tool for accurately detecting Liquidity Sweeps, Order Blocks, and Fair Value Gaps in binary options trading.
Its logic is simple yet powerful : when price reaches high-interest liquidity zones and shows reversal signs, the indicator issues an entry signal immediately after a Candle Confirmation is complete.
Signals only activate when both the market structure and the candle confirmation pattern align, ensuring high accuracy in spotting genuine reversals.
🟣 Long Position
A bullish signal appears when the market, after a downward move, reaches sell-side liquidity zones where liquidity has built up below previous lows. In such conditions, a bullish Order Block or Fair Value Gap often exists in the same region, acting as a potential reversal point.
When the indicator detects the presence of liquidity, an imbalance zone (FVG), and a valid candle confirmation simultaneously, it triggers a green Call signal.
In a binary options strategy, the best entry moment is immediately after the candle confirmation closes, as this is when the probability of reversal is highest and the market tends to react strongly within the next few candles.
In the example below, after the liquidity sweep and candle confirmation, price quickly rallied, resulting in a Binary Win setup.
🟣 Short Position
A bearish signal occurs when price, after an upward move, reaches an area of buy-side liquidity and collects liquidity above recent highs. At this stage, the market is typically overbought and ready to reverse. If a bearish Order Block or Fair Value Gap exists in the same area and a candle confirmation pattern forms, the indicator displays a red Put signal.
This setup is highly accurate because multiple structural confirmations occur simultaneously : liquidity has been absorbed, price is rebalancing, and the confirmation candle has closed.
In binary options trading, this is the ideal moment to enter a Put (Sell) position, as the price reaction to the downside is usually quick and decisive.
In the example chart, the indicator generated a bearish signal right after the candle confirmation and completion of the liquidity sweep, price then dropped within minutes, resulting in another Binary Win.
🔵 Settings
Time Frame : Select the desired timeframe for analysis. If left blank, the indicator uses the chart’s current timeframe.
Swing Period : Defines how many candles are used to detect structural pivots (swing highs and lows). A higher value increases accuracy but reduces the number of signals.
Candle Pattern : Enables candle-based confirmation logic. When turned on, the indicator issues signals only if a valid reversal pattern is detected. You can also choose the confirmation filter strength, tighter filters show fewer but more precise signals.
🔵 Conclusion
A deep understanding of Liquidity Sweeps, Order Blocks, and Fair Value Gaps can make a decisive difference between ordinary and professional traders in the binary options market.
This indicator, combining smart money logic with candle confirmation, is one of the most precise tools for detecting true market reversals. When liquidity is collected and structural reversal signs emerge, the indicator automatically recognizes the price reaction and generates a reliable Call or Put signal.
Using this tool alongside market structure analysis and FVG detection allows traders to enter high-probability setups while filtering out false breakouts. For that reason, this binary options strategy is not only suitable for short-term trading but also valuable for understanding deeper smart-money behavior across timeframes.
Ultimately, success with this system comes down to two key principles: understanding the logic of the liquidity sweep and waiting for the candle confirmation to close. When these two conditions align, the indicator can pinpoint the best entry points with remarkable precision, helping you build a structured, intelligent, and profitable binary options strategy.
CipherThis indicator identifies potential reversal points through volume exhaustion analysis combined with multi-factor confirmation, volume distribution patterns at price extremes, market state classification based on volatility characteristics, and time-weighted probability calculations. Each component reduces false signals that single-factor indicators typically produce.
METHODOLOGY:
The system continuously monitors market conditions across multiple dimensions. When volume patterns indicate potential exhaustion at significant price levels, it checks for alignment with favorable market conditions and statistical probabilities. Signals only generate when multiple factors confirm, with entry triggered on momentum continuation beyond the exhaustion point.
COMPLETE USAGE GUIDE:
Signal Identification:
- "EXH L+2" = Long exhaustion with 2 confirmations
- "EXH S+3" = Short exhaustion with 3 confirmations
- Higher confirmation numbers indicate stronger setups
Entry Execution:
- Dashed lines mark entry trigger levels
- Entry activates when price breaks trigger within specified bar window
- Buffer setting controls distance from exhaustion bar (ticks)
Position Management:
- Automatic stop loss and target levels display on entry
- Green lines = profit targets
- Red lines = stop loss levels
- Info panel shows real-time position status
CONFIGURABLE PARAMETERS:
Timing Controls:
- Entry Buffer: 0-5 ticks (momentum confirmation distance)
- Max Bars to Wait: 3-10 bars (entry window duration)
- Session Times: Separate London/New York parameters
Sensitivity Settings:
- Volume Multiplier: 1.5-3.0 (vs 20-bar average)
- Lambda Values: Setup frequency expectations per session
- Stop Distances: Session-specific risk parameters
Risk Controls:
- Daily Win Limit: Stops after profitable day
- Daily Loss Limit: Prevents excessive drawdown
- Maximum Daily Trades: Controls overtrading
PERFORMANCE OPTIMIZATION:
Best Trading Windows:
- 10:00 AM EST: Primary reversal window
- 9:30-9:45 AM EST: Opening range exhaustion
- 3:00-4:00 AM EST: European session setups
- 2:30 PM EST: Afternoon reversal potential
Session Characteristics:
- London (2-9 AM EST): Lower frequency, cleaner setups
- New York (9 AM-4 PM EST): Higher frequency, requires filtering
- Background colors indicate active sessions
RISK PARAMETERS:
- Default Stops: 30-40 ticks (session-dependent)
- Risk:Reward Ratios: 1:1.5 to 1:3 (configurable)
- Trade Frequency: 2-4 quality setups weekly
VISUAL REFERENCE:
- Orange Background: London session active
- Blue Background: New York session active
- Yellow Markers: Exhaustion points identified
- Dashed Lines: Pending entry levels
- Solid Lines: Active trade levels
- Info Table: Statistics and system status
IMPORTANT CONSIDERATIONS:
This tool identifies potential setups based on rule-based analysis. Traders should understand that no system guarantees profits and should use appropriate risk management. The indicator works best on 3-minute and 5-minute timeframes in liquid markets. Combine with market context and price action understanding for optimal results.
TECHNICAL REQUIREMENTS:
- Best suited for index and commodites
- Optimized for 3M and 5M
- Requires volume data for proper function
- Best results with consistent market participation
Lot Size Calculator for FX(JPY Base)-By Jason v1.1 ロッド自動計算ツール🧭概要
このインジケーターは、日本円口座で取引するFXトレーダー専用に設計されたロットサイズ自動計算ツールです。
クロス円だけでなく、ドルストレート通貨ペア（EURUSD・GBPUSD・など）も自動換算に対応。
リアルなJPY換算ベースで、リスクとロットを正確に可視化します。
🎯 主な特徴
✅ JPY自動換算対応
ドルストレート・クロス円ペアを問わず、リアルタイムでJPYベースに換算。
✅ リスク/リワード自動計算
口座残高・ストップロス・リスク割合・固定損失額からロットサイズを即時算出。
✅ 証拠金維持率 / 実効レバレッジ表示
過剰エントリーを防ぎ、リスクを数値で管理。
✅ パネル表示を自由カスタマイズ
* 表示項目を個別にON/OFF可能
* 項目名（ラベル）を自分の言葉に変更可能
* パネル位置・文字サイズ・色・背景も自由設定
✅ 日本口座仕様に最適化
DMM、GMO、外為どっとコムなどJPY建て口座での取引計算に完全対応。
💡 推奨リスク管理ルール（プロトレーダー実践例）
プロ仕様のトレードは、「勝つこと」より「失わないこと」を最優先に行われます。
安定して利益を積み上げるトレーダーは、常に明確なリスク基準をもって行動します。
以下は、その代表的なリスク管理ルールです。
📉 連敗時のリスクコントロール（防御モード）
* 1トレードあたり口座残高の1%以下に抑える
* 連続2～3敗でリスクを半分（例：1%→0.5%）に下げる
* 1日の最大損失率を 3〜5%以内に制限（到達したらその日は終了）
* 「メンタルドローダウン」を避けるために連敗日翌日は休むことも多い
📘 目的：生き残ること。資金を守ることが最大の攻撃。
📈 連勝時のリスクコントロール（拡張モード）
* 2連勝以上の場合、**リスクを段階的に拡大（例：1%→1.5%）**
* ただし、最大でも3%以内
* リワードが積み上がっている時にのみ増加させる（利益分をリスクに再投資）
📘 目的：勝っている時にリスクを“複利的”に活かすが、ルール内にとどめる。
🧠 デイリーマネジメントルール（プロ基準）
1トレードリスク ： 1〜2%以内
1日最大損失 ：3〜5%以内
1週間最大損失 ： 10%以内
リスクリワード比 ：最低 1 : 2（理想は 1 : 3 以上）
勝率の目安 ： 40〜50%でもRR管理で黒字維持可能
⚙️ このツールを使う理由
このロット計算機を使えば、
「感覚的なロット設定」から「数値的なリスク管理」へ進化できます。
✅ 過剰ロット防止
✅ 損失率の明確化
✅ 勝ち負けのバランス最適化
✅ 冷静なトレード継続が可能に
🧩 使い方
1️⃣ チャートにインジケーターを追加
2️⃣ 「口座残高」「リスク割合」「ストップロス(pips)」を設定
3️⃣ 「ロットサイズ」欄の数値が、**最適ロットサイズ**
4️⃣ リスク指標（証拠金維持率・実効レバレッジ）をチェック
⚠️ 免責事項
このインジケーターは教育目的の補助ツールです。
最終的な売買判断はご自身の責任で行ってください。
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🧾 クレジット
Developed for Japanese Traders 🇯🇵
Optimized for FX Based Risk Control
Created by
💬 まとめ
資金を守ることは「守り」ではなく、次のチャンスに立ち続けるための最強の戦略です。
リスクを管理できる者だけが、長期的に勝ち続けることができます。
🧩 今後について
このインジケーターは、今後も使いやすさと精度を追求しながら改善を続けていきます。
もちろんです。以下は、あなたの日本語説明文を**自然でプロフェッショナルな英語**に翻訳したものです。
TradingViewのインジケーター説明欄にそのまま使えるトーン（ややフォーマル＋分かりやすい）で整えています👇
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🧭 Overview
This indicator is a **lot size auto-calculator** designed specifically for **FX traders using Japanese Yen (JPY) accounts**.
It automatically converts values not only for JPY crosses but also for **USD-based pairs (e.g., EURUSD, GBPUSD, etc.)**,
providing precise **risk and lot visualization in real JPY terms**.
🎯 Key Features
✅ **Automatic JPY Conversion**
Real-time JPY-based conversion for both USD and JPY pairs.
✅ **Risk / Reward Auto Calculation**
Instantly calculates the optimal lot size based on account balance, stop loss, and defined risk percentage or fixed loss.
✅ **Margin Maintenance Rate / Effective Leverage Display**
Prevents over-leveraging and allows you to monitor your risk numerically.
✅ **Fully Customizable Panel Display**
* Enable or disable each display item individually
* Rename labels freely to your preferred wording
* Adjust panel position, font size, colors, and background
✅ **Optimized for Japanese Brokerage Accounts**
Fully compatible with major JPY-based brokers such as **DMM, GMO, and Gaitame.com**.
💡 Recommended Risk Management Rules (Professional Trader Practices)
Professional trading prioritizes **“not losing” over “winning.”**
Consistent traders operate with a clear and disciplined risk framework.
Here are the most common examples of professional risk management rules:
📉 Loss Streak Risk Control (Defensive Mode)
* Keep risk per trade below **1% of account balance**
* After **2–3 consecutive losses**, reduce risk by half (e.g., 1% → 0.5%)
* Limit daily loss to **3–5%** — stop trading once reached
* Take a break after a losing streak to avoid **mental drawdown**
📘 **Objective:** Survival first. Protecting capital is the strongest form of offense.
📈 Win Streak Risk Control (Expansion Mode)
* After 2 consecutive wins, **gradually increase risk (e.g., 1% → 1.5%)**
* Never exceed **3% total risk per trade**
* Only scale up when trading with accumulated profit — reinvest from gains, not from capital
📘 **Objective:** Use profits to grow risk *compoundedly*, but always within defined limits.
🧠 Daily Risk Management (Professional Standards)
Risk per trade : 1–2% of account balance
Max daily loss : 3–5%
Max weekly loss :10%
Minimum R:R ratio : 1 : 2 (Ideal: 1 : 3 or higher)
Profitability baseline : 40–50% win rate can still stay profitable with proper R:R control
⚙️ Why Use This Tool?
This calculator helps you shift from **“emotional lot sizing” to “numerical risk control.”**
✅ Prevents over-lotting
✅ Clarifies risk exposure
✅ Balances wins and losses
✅ Enables calm, consistent execution
🧩 How to Use
1️⃣ Add the indicator to your chart
2️⃣ Set your **account balance**, **risk percentage**, and **stop loss (pips)**
3️⃣ The **“Lot Size”** value automatically displays the optimal lot size
4️⃣ Check risk indicators such as **Margin Maintenance** and **Effective Leverage**
⚠️ Disclaimer
This indicator is a **support tool for educational purposes only**.
All final trading decisions are the sole responsibility of the user.
🧾 Credits
Developed for **Japanese Traders 🇯🇵**
Optimized for **FX-Based Risk Control**
Created by ** **
💬 Summary
Protecting your capital isn’t a defensive move —
it’s the **strongest strategy to stay in the game and seize the next opportunity**.
Only those who manage risk properly can sustain consistent long-term success.
🧩 Future Updates
This indicator will continue to evolve with improvements in usability and accuracy.
Stay tuned for upcoming updates and refinements.
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.
Volumetric Spectrogram [by Oberlunar]Volumetric Spectrogram
A two-pole, price-relative volume profiler that turns regional buy/sell pressure into clean oscillators and actionable regimes in a multi-broker setup.
What it measures
The indicator divides the recent price span into bins and accumulates buy vs. sell volume in each bin, then summarises two regions with respect to the current price:
Upper (↑) — volume that traded above the current price (overhead supply/demand).
Lower (↓) — volume that traded below the current price (underfoot bid/pressure).
Per region, it computes BUY% and SELL%, then forms two normalised oscillators in :
Upper Osc = Upper(BUY%) − Upper(SELL%) → positive when overhead offers are being lifted (breakout acceptance), negative when overhead sell pressure dominates (resistance).
Lower Osc = Lower(BUY%) − Lower(SELL%) → positive when sub-price bids strengthen (support/absorption), negative when selling persists beneath price (weak underbelly).
Both oscillators are optionally smoothed with EMA and can be filled to zero or between curves for quick polarity/strength reading.
Candle-fill modes across brokers
The indicator supports multiple candle-fill policies tied to cross-broker volumetric agreement (e.g., spectral/range-only fills when ≥N brokers align above 70% bullish or below 20% bearish Buy%). This makes regime and pressure shifts visually explicit while filtering out unconfirmed noise.
How it works (core algorithm)
Over a lookback window, find the high/low and split the range into N bins .
For each historical bar, approximate “buy” vs “sell” volume using candle direction and the close relative to each bin’s midprice; update left/right profiles per bin.
Aggregate bins above the current price into the Upper region and bins below into the Lower region; compute regional totals and percentages.
Convert to signed oscillators and smooth (EMA length per input).
Scenario engine (table, every bar)
A compact table reports, for Upper/Lower: BUY Vol, SELL Vol, BUY%, SELL%, and Net%. A classifier labels 8 regimes based on oscillator sign and recent expansion/decay: Sync Long/Short (Expanding/Decaying), Opposite Signs (Widening/Converging), and Tilts (Upper/Lower). This helps distinguish trend continuation, fade risk, compression before break, and asymmetric pressure (e.g., “Tilt Lower — bid/support strengthening”).
# Example strategies and annotated cases:
There are different operational strategies:
1) Bottle-neck Strategy with multi-broker confirmation
When both oscillators are red and they compress toward the zero line (a bottle-neck [/i>), if the squeeze does not flip into the opposite trend but instead resolves in the same direction, you have a continuation setup that can be exploited:
• Pattern: both oscillators red → short, visible contraction (narrow, low-variance cluster) → break of the cluster lows → background shadow bars align bearish (multi-broker agreement).
Example:
This sequence often supports a 1.5–2.5 R/R trade, as in:
Bullish mirror
If both oscillators are teal and compress, then expand upward with multi-broker agreement, the scenario becomes bullish after several bars; the position can be profitable with a reasonable risk setup:
Example:
Follow-through:
Here are the additional, English “playbook” examples you can append to the previous description.
2) Dual-confirmation on volume spikes + multi-broker checks
When pronounced volumetric spikes appear (up or down), trend often reverses sharply. In the figure, the circles highlight the spikes; once the spike subsides (reversion toward baseline), the oscillator turns bullish. The double confirmation of two consecutive minimum spikes acts as support for an ensuing up-move, with fill colors confirming direction.
Chart:
Even with a single spike confirmation, the reversion from an extreme often provides actionable long setups.
3) Volume-pressure + regime-change (multi-broker)
A prospective long configuration emerges when bullish volumetric pressure dominates and bearish pressure fades, especially if this occurs after a lateral phase, followed by a bullish volume spike and multi-broker confirmation .
Chart:
Shadow bars subsequently confirm continuation in a bullish regime; however, a possible regime change is flagged by the scenario classifier and by a color flip in the volumetric borders ( “Possible regime change, but without multi-broker confirmation.” is an appropriate label when applicable).
Chart:
After a verified mean-reversion, price transitions into a bearish configuration: both oscillators turn red. One can wait for a pullback and seek short entries.
Chart:
As shown here, the regime change is anticipated well in advance by the oscillators and multi-broker pressure:
Chart:
4) Contrastive regime-shift with multi-broker validation
In a contrastive trading phase, the lower volumetric oscillator flips color first—buyers start attacking. The first set of background shadow bars does not agree with the regime flip; the second set does. This sequence (oscillator flip → later multi-broker agreement) is a robust early sign of a potential long setup.
Chart:
At the multi-broker level, all shadow bars turn fully green and the setup becomes unambiguously bullish.
Chart:
Note that bearish pressure can still be non-trivial on the volumetric scale—even if it does not reach prior extreme minima—so risk controls should reflect the residual supply.
Delta-bar coloring (optional)
Bars (or candle overlays) can be tinted by a multi-venue weighted bias:
Choose venues (OKX, Coinbase, Bybit, Binance, BlackBull…).
Weight by Equal / Last Volume / SMA Volume.
Apply deadband to suppress flicker around neutrality and a gamma curve to modulate opacity with |bias|.
This layer is independent of the spectrogram core but provides immediate market-wide flow context, consistent with the table and fills.
Inputs (essentials)
Calculation Period and Bins — resolution and depth of the price-range histogram.
EMA length — smoothing per oscillator (optional)
Fill options — to zero / between curves, gradual opacity by |osc|, min/max alpha.
Delta Bar — enable tinting, gamma, neutral band; venue list and weighting mode.
Reading guide
Upper > 0 & expanding : overhead supply is being lifted → breakout acceptance risk rises.
Lower > 0 & expanding : sub-price bids strengthen → pullbacks more likely to absorb.
Opposite signs widening : tug-of-war; avoid late entries.
Converging : compression → prepare for break.
Use the table’s regime label to keep the narrative honest bar-by-bar.
Notes & limits
Buy/Sell attribution uses candle direction and range partitioning (no L2/tick tape).
Venue aggregation relies on per-exchange volume and your chosen weighting; symbols must align (e.g., BTCUSDT pairs).
Oscillators are relative to the current price (regional) by design; they complement, not replace, classical volume profile.
— Oberlunar 👁 ★
XT Buy Sell v1.0 Lite: Non-Repainting Signal Indicator🚀 XT Buy Sell v1.0 Lite: Non-Repainting Signal Indicator
The XT Buy Sell v1.0 Lite indicator is a streamlined version of our flagship tool, designed for traders who need a reliable, ready-to-use source of signals for market entry and exit.
✨ Key Advantages
Non-Repainting Signals: BUY/SELL signals remain permanently on the chart, providing reliability and easy verification on historical data.
High Accuracy: Developed as one of the most accurate tools for identifying entry points.
Ready "Out of the Box": The indicator comes with optimal default settings. All additional and advanced settings are available in the PRO version.
Versatility: Suitable for both Spot and Futures/Leveraged trading.
🔔 Convenience Features
Alerts: Set up alerts for BUY/SELL signals so you don't have to constantly monitor the chart.
Optimization: Configure alerts on the specific coins (tickers) where the indicator shows the best setups (most accurate and profitable).
🧠 Recommendations for Professional Trading (Risk Management)
To achieve maximum results and safety, follow these guidelines:
Historical Backtesting: Always verify the indicator's performance on the history of the selected trading pair before deployment.
Multi-Timeframe Analysis: Utilize the principle of "Signal on Lower TF, Confirmation on Higher TF" to increase your trading confidence.
Entry Confirmation: For maximum entry precision, it is recommended to use it in conjunction with our additional tool "X Trend Dashboard (Lite)".
Sequential Signals: The consecutive appearance of signals in the same direction (e.g., two or more consecutive BUYS) can be interpreted as a signal for re-entry/averaging down the position.
Risk Management:
Always set Stop-Losses.
Move the trade to Break-Even as soon as possible.
Carefully consider the risks and the leverage being used.
Happy trading and profits to all! 📈💰
Squeeze Momentum ProSQUEEZE MOMENTUM PRO - Enhanced Visual Dashboard
A modernized version of the TTM Squeeze Momentum indicator, designed for cleaner visual interpretation and faster decision-making.
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📊 WHAT IS THE SQUEEZE?
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The "squeeze" occurs when Bollinger Bands contract inside Keltner Channels, indicating extremely low volatility. This compression typically precedes explosive directional moves - the tighter the squeeze, the bigger the potential breakout.
John Carter's TTM Squeeze concept (from "Mastering the Trade") combines this volatility compression with momentum direction to identify high-probability setups.
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✨ WHAT'S NEW IN THIS VERSION
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🎯 VISUAL STATUS BAR
- Real-time squeeze state with clear labels
- Color-coded backgrounds (Red = Building, Green = Fired Bullish, Orange = Fired Bearish)
- Squeeze duration counter to gauge compression time
📊 ENHANCED HISTOGRAM
- 4-color momentum gradient (Strong Bull/Weak Bull/Weak Bear/Strong Bear)
- Instantly shows both direction AND strength
- Background shading for current market state
🔥 SQUEEZE INTENSITY GAUGE
- 5-dot pressure indicator showing compression tightness
- Percentage display of squeeze strength
- Only appears during active squeezes
📈 REAL-TIME METRICS PANEL
- Current momentum value
- Direction indicator (increasing/decreasing)
- Strength assessment (strong/weak)
🔔 COMPREHENSIVE ALERTS
- Squeeze started
- Squeeze fired (bullish/bearish)
- Momentum crossovers
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🎮 HOW TO USE
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1. WAIT FOR SQUEEZE
• Red status bar appears
• Intensity dots show compression level
• Longer duration = potentially bigger move
2. WATCH FOR RELEASE
• Status changes to "FIRED - BULLISH" or "FIRED - BEARISH"
• Histogram color confirms momentum direction
• Background highlights the event
3. MANAGE POSITION
• Monitor momentum strength in metrics panel
• Exit when histogram changes color (momentum reversal)
• Use with trend/volume confirmation
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⚙️ CUSTOMIZATION
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- Toggle status bar, metrics, intensity dots independently
- Adjustable BB/KC parameters
- Custom color schemes
- Show/hide squeeze duration
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🙏 CREDITS
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Original TTM Squeeze concept: John F. Carter
Original indicator code: LazyBear (@LazyBear)
This builds on LazyBear's excellent implementation of the TTM Squeeze Momentum indicator, adding modern visual elements and real-time dashboards for improved usability.
Original indicator: "Squeeze Momentum Indicator "
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⚠️ DISCLAIMER
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This indicator is for educational purposes. Always use proper risk management and combine with other forms of analysis. No indicator guarantees profitable trades.
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Best used on: Day trading timeframes (1m-15m) for momentum plays
Combine with: Volume analysis, trend filters, support/resistance levels
Wave Conflict DetectorWave Conflict Detector
Wave Conflict Detector: Identifying Pivot Conditions Through Wave Interference Analysis
Wave Conflict Detector applies wave interference principles from physics to dual-EMA analysis, identifying potential pivot conditions by measuring phase relationships and amplitude states between two moving average waves. Unlike traditional EMA crossover systems that signal on wave intersection, this indicator measures the directional alignment (phase) and interaction strength (interference amplitude) between wave states to identify conditions where wave mechanics suggest potential reversal zones.
The indicator combines two analytical components: velocity-based phase difference calculation that measures whether waves are moving in the same or opposite directions, and normalized interference amplitude that quantifies the degree of wave reinforcement or cancellation. This creates a regime-classification system with visual feedback showing when waves are aligned (constructive state) versus opposed (destructive state).
What Makes This Approach Different
Phase Relationship Measurement
The core analytical method is extracting phase alignment from wave velocities rather than simply measuring EMA separation. The system calculates the first derivative (bar-to-bar change) of each EMA, creating velocity measurements: v₁ = ψ₁ - ψ₁ and v₂ = ψ₂ - ψ₂ . These velocities are combined through normalized correlation: Φ = (v₁ × v₂) / |v|², producing an alignment value ranging from -1 (perfect opposition) to +1 (perfect alignment).
This alignment value is smoothed using EMA and converted to angular degrees: Δφ = (1 - Φ) × 90°, creating a phase difference measurement from 0° to 180°. This quantifies how much the waves are "fighting" each other directionally, independent of their separation distance. Two EMAs can be far apart yet moving in harmony (low phase difference), or close together yet moving in opposition (high phase difference).
This directional correlation approach differs from standard dual-EMA analysis by focusing on velocity alignment rather than positional crossovers.
Interference Amplitude Calculation
The interference formula implements wave superposition principles: I = (|ψ₁ + ψ₂|² - |ψ₁ - ψ₂|²) × Gain, which mathematically simplifies to I = 4 × ψ₁ × ψ₂ × Gain. This measures the product of both waves—when both are positive and large, interference is maximally constructive; when they have opposite signs or differing magnitudes, interference weakens.
The raw interference value is then normalized using adaptive statistical bounds calculated over a rolling window (default 100 bars). The system computes mean (μ) and standard deviation (σ) of raw interference, then applies bounds of μ ± 2σ, and normalizes to a 0-1 range. This creates a scale-invariant measurement that adapts automatically to different instruments and volatility regimes without requiring manual recalibration.
The combination of phase measurement and normalized amplitude creates a two-dimensional state space for classifying market conditions.
Dual-Mode Detection Architecture
The system offers two detection approaches that can be selected based on market conditions:
Interference Mode: Detects pivot conditions when normalized interference amplitude forms local peaks or troughs (current bar is higher/lower than both adjacent bars) AND exceeds the configured threshold. This identifies extremes in wave interaction strength.
Phase Mode: Detects pivot conditions when phase alignment reverses (crosses from positive to negative or vice versa) AND absolute phase difference exceeds the threshold. This identifies directional relationship changes between waves.
Both modes require price structure confirmation (traditional pivot high/low patterns) and minimum bar spacing to prevent over-signaling. This architecture allows traders to match detection sensitivity to market character—interference mode for amplitude-driven markets, phase mode for directional trend shifts.
Multi-Layer Visual System
The visualization approach uses hierarchical layers to display wave state information:
Foundation Layer: The two EMA waves (ψ₁ and ψ₂) plotted directly on the price chart, showing the underlying wave states being analyzed.
Background Layer: Color-coded zones showing regime state—green tint when phase alignment is positive (constructive interference), red tint when phase alignment is negative below -0.3 (destructive interference).
Dynamic Ribbon: A band centered on the wave average with width proportional to |ψ₁ - ψ₂| × (0.5 + interference_norm). This creates an adaptive channel that expands with interference strength and contracts during low-energy states.
Phase Field: Multi-frequency harmonic oscillations generated using three phase accumulators driven by interference amplitude, phase alignment, and accumulated phase rotation. Multiple sine-wave layers create visual texture that becomes erratic during wave conflict conditions and smooth during aligned states.
Particle System: Floating symbols whose density is proportional to interference amplitude, creating a visual intensity indicator.
Each visual component displays non-redundant information about the wave state system.
Core Calculation Methodology
Wave State Generation
Two exponential moving averages are calculated using configurable lengths (default 8 and 21 bars):
- ψ₁ = EMA(close, fastLen) — fast wave component
- ψ₂ = EMA(close, slowLen) — slow wave component
These serve as the base wave functions for all subsequent analysis.
Velocity Extraction
First derivatives are computed as simple bar-to-bar differences:
- psi1_velocity = ψ₁ - ψ₁
- psi2_velocity = ψ₂ - ψ₂
These represent the "motion" of each wave through price-time space.
Phase Alignment Calculation
The velocity product and magnitude are calculated:
- velocity_product = v₁ × v₂
- velocity_magnitude = √(v₁² + v₂²)
Phase alignment is computed as:
- phase_alignment = velocity_product / (velocity_magnitude²)
This is smoothed using EMA of configurable length (default 5) and converted to degrees:
- phase_degrees = (1 - phase_alignment_smooth) × 90
Interference Amplitude Processing
Raw interference is calculated:
- interference_raw = (constructive_amplitude - destructive_amplitude) × gain
- where constructive_amplitude = (ψ₁ + ψ₂)²
- and destructive_amplitude = (ψ₁ - ψ₂)²
Statistical normalization is applied:
- interference_mean = SMA(interference_raw, normalizationLen)
- interference_std = StdDev(interference_raw, normalizationLen)
- upper_bound = mean + 2 × std
- lower_bound = mean - 2 × std
- interference_norm = (interference_raw - lower_bound) / (upper_bound - lower_bound), clamped to
State Classification
Three regime states are identified:
- Constructive: phase_alignment_smooth > 0 (waves moving in same direction)
- Destructive: phase_alignment_smooth < -0.3 (waves moving in opposite directions)
- Neutral: phase_alignment between -0.3 and 0 (weak directional correlation)
Pivot Detection Logic
In Interference Mode:
- High pivots: interference_norm > interference_norm AND interference_norm > interference_norm AND interference_norm > threshold AND price forms pivot high AND spacing requirement met
- Low pivots: interference_norm shows local trough using opposite conditions
In Phase Mode:
- Pivots: phase alignment reverses sign AND absolute phase_degrees > threshold AND price forms pivot high/low AND spacing requirement met
All conditions must be true for a signal to generate.
Dashboard Metrics System
The dashboard displays real-time calculations:
- I (Interference): Normalized amplitude shown as bar gauge and percentage
- Δφ (Phase): Phase difference shown as bar gauge and degrees
- ψ₁ and ψ₂: Current wave values in price units
- Wave Separation: |ψ₁ - ψ₂| with directional indicator
- STATE: Current regime classification (CONSTRUCTIVE/DESTRUCTIVE/NEUTRAL)
- PIVOT Probability: Composite score calculated as interference_norm × (phase_degrees/180) × 100
The interference matrix shows historical heatmap data across four metrics (interference amplitude, phase difference, constructive flags, destructive flags) over the configurable number of bars.
How to Use This Indicator
Initial Configuration
Apply the indicator to your chart with default settings. The fast wave length (default 8) should be adjusted to match short-term price swings for your instrument and timeframe. The slow wave length (default 21) should be 2-4 times the fast length to create adequate wave separation. Enable the dashboard (recommended position: top right) to monitor regime state and metrics in real-time.
Signal Interpretation
High Pivot Marker (▼ Red Triangle): Appears above price bars when a bearish pivot condition is detected. This indicates that price formed a swing high, the selected detection criteria were met (interference peak or phase reversal depending on mode), threshold requirements were satisfied, and the minimum spacing filter passed. This represents a potential reversal zone where wave mechanics suggest downward directional change conditions.
Low Pivot Marker (▲ Green Triangle): Appears below price bars when a bullish pivot condition is detected. This indicates that price formed a swing low and all detection criteria aligned. This represents a potential reversal zone where wave mechanics suggest upward directional change conditions.
Dashboard STATE Reading
The STATE field shows current wave relationship:
- "🟢 CONSTRUCTIVE": Waves are moving in the same direction (phase alignment positive). This suggests trend continuation conditions where waves are reinforcing each other.
- "🔴 DESTRUCTIVE": Waves are moving in opposite directions (phase alignment below -0.3). This suggests reversal-prone conditions where waves are conflicting.
- "🟡 NEUTRAL": Weak directional correlation between waves. This suggests ranging or transitional conditions.
Use STATE for regime awareness rather than specific entry signals.
Interference and Phase Metrics
Monitor the I (Interference) percentage:
- Above 70%: High amplitude state, significant wave interaction
- 40-70%: Moderate amplitude state
- Below 40%: Low amplitude state, weak interaction
Monitor the Δφ (Phase) degrees:
- Above 120°: Significant wave opposition (destructive conditions)
- 60-120°: Transitional phase relationship
- Below 60°: Wave alignment (constructive conditions)
The PIVOT probability metric combines both: high values (>70%) indicate conditions where both amplitude and phase suggest elevated pivot formation potential.
Trading Workflow Example
Step 1 - Regime Check: Observe dashboard STATE to understand current wave relationship. CONSTRUCTIVE states favor trend-following approaches, DESTRUCTIVE states suggest reversal-prone conditions.
Step 2 - Metric Monitoring: Watch I% and Δφ values. Rising interference with high phase difference indicates building wave conflict.
Step 3 - Visual Confirmation: Observe amplitude ribbon width (expanding = active state) and phase field texture (chaotic = conflict conditions, smooth = aligned conditions).
Step 4 - Signal Wait: Wait for confirmed pivot marker (▼ or ▲) rather than anticipating based on metrics alone. The marker indicates all detection criteria have aligned.
Step 5 - Entry Decision: Use pivot markers as potential reversal zones. Combine with other analysis methods such as support/resistance levels, volume confirmation, and higher timeframe bias for entry decisions.
Step 6 - Risk Management: Place stops beyond recent swing structure or ribbon edges. Monitor dashboard STATE—if it flips to CONSTRUCTIVE in trade direction, the reversal may be confirmed; if PIVOT% drops significantly, conditions may be weakening.
Step 7 - Exit Criteria: Consider exits when opposite pivot marker appears, STATE changes unfavorably, or standard technical targets are reached.
Parameter Optimization Guidelines
Fast Wave Length: Adjust to match short-term swing frequency. Shorter values (5-8) for active trading on lower timeframes, longer values (13-20) for swing trading on higher timeframes.
Slow Wave Length: Should maintain 2-4x ratio with fast length. Shorter values create more interference cycles, longer values create more stable baseline.
Phase Detection Length: Smoothing for phase alignment. Lower values (3-5) for responsive detection, higher values (8-12) for stable readings with less sensitivity.
Interference Gain: Amplification multiplier. Lower values (0.5-1.0) for conservative detection, higher values (1.5-2.5) for more sensitive detection.
Normalization Period: Rolling window for statistical bounds. Shorter periods (50-100) adapt quickly to volatility changes, longer periods (150-300) provide more stable normalization.
Interference Threshold: Minimum amplitude to trigger signals. Lower values (0.50-0.60) generate more signals, higher values (0.70-0.85) are more selective.
Phase Threshold: Minimum phase difference in degrees. Lower values (90-110) are more permissive, higher values (140-170) require stronger opposition.
Min Pivot Spacing: Bars between signals. Match to average swing duration on your timeframe—tighter spacing (3-8 bars) for scalping, wider spacing (15-30 bars) for swing trading.
Best Performance Conditions
This approach works better in markets with:
- Clear swing structure where EMA-based wave analysis is meaningful
- Sufficient volatility for wave separation to develop
- Periodic oscillation between trending and ranging states
- Liquid instruments where EMAs reflect true price flow
This approach may be less effective in:
- Extremely choppy conditions with no directional persistence
- Very low volatility environments where wave separation is minimal
- Gap-heavy instruments where price discontinuities disrupt wave continuity
- Parabolic moves where waves cannot keep pace with price velocity
The system adapts by reducing signal frequency in poor conditions—when interference stays below threshold or phase alignment remains neutral, pivot markers will not appear.
Visual Performance Optimization
The phase field and particle systems are computationally intensive. If experiencing chart lag:
- Reduce Phase Field Layers from 5 to 2-3 (significant performance improvement)
- Lower Particle Density from 3 to 1 (reduces label creation overhead)
- Disable Phase Field entirely (removes most intensive calculations)
- Decrease Matrix History Bars to 15-20 (reduces table computation load)
The core wave analysis and pivot detection continue to function with all visual elements disabled.
Important Disclaimers
This indicator is an analytical tool that measures phase relationships and interference amplitude between two exponential moving averages. It identifies conditions where these wave mechanics suggest potential pivot zones based on historical price data analysis. It should not be used as a standalone trading system.
The phase and interference calculations are deterministic mathematical formulas applied to EMA values. These measurements describe current and historical wave relationships but do not predict future price movements. Past wave patterns and pivot markers do not guarantee future market behavior will follow similar patterns.
All trading involves risk. The pivot markers represent analytical conditions where wave mechanics align with specific thresholds, not certainty of directional change. Use appropriate risk management, position sizing, and combine with additional confirmation methods such as support/resistance analysis, volume patterns, and multi-timeframe alignment. No indicator can eliminate false signals or guarantee profitable trades.
The spacing filter and threshold requirements 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.
Technical Implementation Notes
All calculations execute on closed bars only—there is no repainting of signals or values. The normalization system requires approximately 100 bars of historical data to establish stable statistical bounds; values in the first 50-100 bars may be unstable as the rolling statistics converge.
Phase field arrays are fixed-size based on the complexity setting. Particle labels are capped at 80 total to prevent excessive memory usage. Dashboard and matrix tables update only on the last bar to minimize computational overhead. Particle generation is throttled to every 2 bars for performance. Phase accumulators use modulo arithmetic (% 2π) to prevent numerical overflow during extended operation.
The indicator has been tested across multiple timeframes (5-minute through daily) and multiple asset classes (forex, stocks, crypto, indices). It functions identically across all instruments due to the adaptive normalization approach.
Quantum Rotational Field MappingQuantum Rotational Field Mapping (QRFM):
Phase Coherence Detection Through Complex-Plane Oscillator Analysis
Quantum Rotational Field Mapping applies complex-plane mathematics and phase-space analysis to oscillator ensembles, identifying high-probability trend ignition points by measuring when multiple independent oscillators achieve phase coherence. Unlike traditional multi-oscillator approaches that simply stack indicators or use boolean AND/OR logic, this system converts each oscillator into a rotating phasor (vector) in the complex plane and calculates the Coherence Index (CI) —a mathematical measure of how tightly aligned the ensemble has become—then generates signals only when alignment, phase direction, and pairwise entanglement all converge.
The indicator combines three mathematical frameworks: phasor representation using analytic signal theory to extract phase and amplitude from each oscillator, coherence measurement using vector summation in the complex plane to quantify group alignment, and entanglement analysis that calculates pairwise phase agreement across all oscillator combinations. This creates a multi-dimensional confirmation system that distinguishes between random oscillator noise and genuine regime transitions.
What Makes This Original
Complex-Plane Phasor Framework
This indicator implements classical signal processing mathematics adapted for market oscillators. Each oscillator—whether RSI, MACD, Stochastic, CCI, Williams %R, MFI, ROC, or TSI—is first normalized to a common scale, then converted into a complex-plane representation using an in-phase (I) and quadrature (Q) component. The in-phase component is the oscillator value itself, while the quadrature component is calculated as the first difference (derivative proxy), creating a velocity-aware representation.
From these components, the system extracts:
Phase (φ) : Calculated as φ = atan2(Q, I), representing the oscillator's position in its cycle (mapped to -180° to +180°)
Amplitude (A) : Calculated as A = √(I² + Q²), representing the oscillator's strength or conviction
This mathematical approach is fundamentally different from simply reading oscillator values. A phasor captures both where an oscillator is in its cycle (phase angle) and how strongly it's expressing that position (amplitude). Two oscillators can have the same value but be in opposite phases of their cycles—traditional analysis would see them as identical, while QRFM sees them as 180° out of phase (contradictory).
Coherence Index Calculation
The core innovation is the Coherence Index (CI) , borrowed from physics and signal processing. When you have N oscillators, each with phase φₙ, you can represent each as a unit vector in the complex plane: e^(iφₙ) = cos(φₙ) + i·sin(φₙ).
The CI measures what happens when you sum all these vectors:
Resultant Vector : R = Σ e^(iφₙ) = Σ cos(φₙ) + i·Σ sin(φₙ)
Coherence Index : CI = |R| / N
Where |R| is the magnitude of the resultant vector and N is the number of active oscillators.
The CI ranges from 0 to 1:
CI = 1.0 : Perfect coherence—all oscillators have identical phase angles, vectors point in the same direction, creating maximum constructive interference
CI = 0.0 : Complete decoherence—oscillators are randomly distributed around the circle, vectors cancel out through destructive interference
0 < CI < 1 : Partial alignment—some clustering with some scatter
This is not a simple average or correlation. The CI captures phase synchronization across the entire ensemble simultaneously. When oscillators phase-lock (align their cycles), the CI spikes regardless of their individual values. This makes it sensitive to regime transitions that traditional indicators miss.
Dominant Phase and Direction Detection
Beyond measuring alignment strength, the system calculates the dominant phase of the ensemble—the direction the resultant vector points:
Dominant Phase : φ_dom = atan2(Σ sin(φₙ), Σ cos(φₙ))
This gives the "average direction" of all oscillator phases, mapped to -180° to +180°:
+90° to -90° (right half-plane): Bullish phase dominance
+90° to +180° or -90° to -180° (left half-plane): Bearish phase dominance
The combination of CI magnitude (coherence strength) and dominant phase angle (directional bias) creates a two-dimensional signal space. High CI alone is insufficient—you need high CI plus dominant phase pointing in a tradeable direction. This dual requirement is what separates QRFM from simple oscillator averaging.
Entanglement Matrix and Pairwise Coherence
While the CI measures global alignment, the entanglement matrix measures local pairwise relationships. For every pair of oscillators (i, j), the system calculates:
E(i,j) = |cos(φᵢ - φⱼ)|
This represents the phase agreement between oscillators i and j:
E = 1.0 : Oscillators are in-phase (0° or 360° apart)
E = 0.0 : Oscillators are in quadrature (90° apart, orthogonal)
E between 0 and 1 : Varying degrees of alignment
The system counts how many oscillator pairs exceed a user-defined entanglement threshold (e.g., 0.7). This entangled pairs count serves as a confirmation filter: signals require not just high global CI, but also a minimum number of strong pairwise agreements. This prevents false ignitions where CI is high but driven by only two oscillators while the rest remain scattered.
The entanglement matrix creates an N×N symmetric matrix that can be visualized as a web—when many cells are bright (high E values), the ensemble is highly interconnected. When cells are dark, oscillators are moving independently.
Phase-Lock Tolerance Mechanism
A complementary confirmation layer is the phase-lock detector . This calculates the maximum phase spread across all oscillators:
For all pairs (i,j), compute angular distance: Δφ = |φᵢ - φⱼ|, wrapping at 180°
Max Spread = maximum Δφ across all pairs
If max spread < user threshold (e.g., 35°), the ensemble is considered phase-locked —all oscillators are within a narrow angular band.
This differs from entanglement: entanglement measures pairwise cosine similarity (magnitude of alignment), while phase-lock measures maximum angular deviation (tightness of clustering). Both must be satisfied for the highest-conviction signals.
Multi-Layer Visual Architecture
QRFM includes six visual components that represent the same underlying mathematics from different perspectives:
Circular Orbit Plot : A polar coordinate grid showing each oscillator as a vector from origin to perimeter. Angle = phase, radius = amplitude. This is a real-time snapshot of the complex plane. When vectors converge (point in similar directions), coherence is high. When scattered randomly, coherence is low. Users can see phase alignment forming before CI numerically confirms it.
Phase-Time Heat Map : A 2D matrix with rows = oscillators and columns = time bins. Each cell is colored by the oscillator's phase at that time (using a gradient where color hue maps to angle). Horizontal color bands indicate sustained phase alignment over time. Vertical color bands show moments when all oscillators shared the same phase (ignition points). This provides historical pattern recognition.
Entanglement Web Matrix : An N×N grid showing E(i,j) for all pairs. Cells are colored by entanglement strength—bright yellow/gold for high E, dark gray for low E. This reveals which oscillators are driving coherence and which are lagging. For example, if RSI and MACD show high E but Stochastic shows low E with everything, Stochastic is the outlier.
Quantum Field Cloud : A background color overlay on the price chart. Color (green = bullish, red = bearish) is determined by dominant phase. Opacity is determined by CI—high CI creates dense, opaque cloud; low CI creates faint, nearly invisible cloud. This gives an atmospheric "feel" for regime strength without looking at numbers.
Phase Spiral : A smoothed plot of dominant phase over recent history, displayed as a curve that wraps around price. When the spiral is tight and rotating steadily, the ensemble is in coherent rotation (trending). When the spiral is loose or erratic, coherence is breaking down.
Dashboard : A table showing real-time metrics: CI (as percentage), dominant phase (in degrees with directional arrow), field strength (CI × average amplitude), entangled pairs count, phase-lock status (locked/unlocked), quantum state classification ("Ignition", "Coherent", "Collapse", "Chaos"), and collapse risk (recent CI change normalized to 0-100%).
Each component is independently toggleable, allowing users to customize their workspace. The orbit plot is the most essential—it provides intuitive, visual feedback on phase alignment that no numerical dashboard can match.
Core Components and How They Work Together
1. Oscillator Normalization Engine
The foundation is creating a common measurement scale. QRFM supports eight oscillators:
RSI : Normalized from to using overbought/oversold levels (70, 30) as anchors
MACD Histogram : Normalized by dividing by rolling standard deviation, then clamped to
Stochastic %K : Normalized from using (80, 20) anchors
CCI : Divided by 200 (typical extreme level), clamped to
Williams %R : Normalized from using (-20, -80) anchors
MFI : Normalized from using (80, 20) anchors
ROC : Divided by 10, clamped to
TSI : Divided by 50, clamped to
Each oscillator can be individually enabled/disabled. Only active oscillators contribute to phase calculations. The normalization removes scale differences—a reading of +0.8 means "strongly bullish" regardless of whether it came from RSI or TSI.
2. Analytic Signal Construction
For each active oscillator at each bar, the system constructs the analytic signal:
In-Phase (I) : The normalized oscillator value itself
Quadrature (Q) : The bar-to-bar change in the normalized value (first derivative approximation)
This creates a 2D representation: (I, Q). The phase is extracted as:
φ = atan2(Q, I) × (180 / π)
This maps the oscillator to a point on the unit circle. An oscillator at the same value but rising (positive Q) will have a different phase than one that is falling (negative Q). This velocity-awareness is critical—it distinguishes between "at resistance and stalling" versus "at resistance and breaking through."
The amplitude is extracted as:
A = √(I² + Q²)
This represents the distance from origin in the (I, Q) plane. High amplitude means the oscillator is far from neutral (strong conviction). Low amplitude means it's near zero (weak/transitional state).
3. Coherence Calculation Pipeline
For each bar (or every Nth bar if phase sample rate > 1 for performance):
Step 1 : Extract phase φₙ for each of the N active oscillators
Step 2 : Compute complex exponentials: Zₙ = e^(i·φₙ·π/180) = cos(φₙ·π/180) + i·sin(φₙ·π/180)
Step 3 : Sum the complex exponentials: R = Σ Zₙ = (Σ cos φₙ) + i·(Σ sin φₙ)
Step 4 : Calculate magnitude: |R| = √
Step 5 : Normalize by count: CI_raw = |R| / N
Step 6 : Smooth the CI: CI = SMA(CI_raw, smoothing_window)
The smoothing step (default 2 bars) removes single-bar noise spikes while preserving structural coherence changes. Users can adjust this to control reactivity versus stability.
The dominant phase is calculated as:
φ_dom = atan2(Σ sin φₙ, Σ cos φₙ) × (180 / π)
This is the angle of the resultant vector R in the complex plane.
4. Entanglement Matrix Construction
For all unique pairs of oscillators (i, j) where i < j:
Step 1 : Get phases φᵢ and φⱼ
Step 2 : Compute phase difference: Δφ = φᵢ - φⱼ (in radians)
Step 3 : Calculate entanglement: E(i,j) = |cos(Δφ)|
Step 4 : Store in symmetric matrix: matrix = matrix = E(i,j)
The matrix is then scanned: count how many E(i,j) values exceed the user-defined threshold (default 0.7). This count is the entangled pairs metric.
For visualization, the matrix is rendered as an N×N table where cell brightness maps to E(i,j) intensity.
5. Phase-Lock Detection
Step 1 : For all unique pairs (i, j), compute angular distance: Δφ = |φᵢ - φⱼ|
Step 2 : Wrap angles: if Δφ > 180°, set Δφ = 360° - Δφ
Step 3 : Find maximum: max_spread = max(Δφ) across all pairs
Step 4 : Compare to tolerance: phase_locked = (max_spread < tolerance)
If phase_locked is true, all oscillators are within the specified angular cone (e.g., 35°). This is a boolean confirmation filter.
6. Signal Generation Logic
Signals are generated through multi-layer confirmation:
Long Ignition Signal :
CI crosses above ignition threshold (e.g., 0.80)
AND dominant phase is in bullish range (-90° < φ_dom < +90°)
AND phase_locked = true
AND entangled_pairs >= minimum threshold (e.g., 4)
Short Ignition Signal :
CI crosses above ignition threshold
AND dominant phase is in bearish range (φ_dom < -90° OR φ_dom > +90°)
AND phase_locked = true
AND entangled_pairs >= minimum threshold
Collapse Signal :
CI at bar minus CI at current bar > collapse threshold (e.g., 0.55)
AND CI at bar was above 0.6 (must collapse from coherent state, not from already-low state)
These are strict conditions. A high CI alone does not generate a signal—dominant phase must align with direction, oscillators must be phase-locked, and sufficient pairwise entanglement must exist. This multi-factor gating dramatically reduces false signals compared to single-condition triggers.
Calculation Methodology
Phase 1: Oscillator Computation and Normalization
On each bar, the system calculates the raw values for all enabled oscillators using standard Pine Script functions:
RSI: ta.rsi(close, length)
MACD: ta.macd() returning histogram component
Stochastic: ta.stoch() smoothed with ta.sma()
CCI: ta.cci(close, length)
Williams %R: ta.wpr(length)
MFI: ta.mfi(hlc3, length)
ROC: ta.roc(close, length)
TSI: ta.tsi(close, short, long)
Each raw value is then passed through a normalization function:
normalize(value, overbought_level, oversold_level) = 2 × (value - oversold) / (overbought - oversold) - 1
This maps the oscillator's typical range to , where -1 represents extreme bearish, 0 represents neutral, and +1 represents extreme bullish.
For oscillators without fixed ranges (MACD, ROC, TSI), statistical normalization is used: divide by a rolling standard deviation or fixed divisor, then clamp to .
Phase 2: Phasor Extraction
For each normalized oscillator value val:
I = val (in-phase component)
Q = val - val (quadrature component, first difference)
Phase calculation:
phi_rad = atan2(Q, I)
phi_deg = phi_rad × (180 / π)
Amplitude calculation:
A = √(I² + Q²)
These values are stored in arrays: osc_phases and osc_amps for each oscillator n.
Phase 3: Complex Summation and Coherence
Initialize accumulators:
sum_cos = 0
sum_sin = 0
For each oscillator n = 0 to N-1:
phi_rad = osc_phases × (π / 180)
sum_cos += cos(phi_rad)
sum_sin += sin(phi_rad)
Resultant magnitude:
resultant_mag = √(sum_cos² + sum_sin²)
Coherence Index (raw):
CI_raw = resultant_mag / N
Smoothed CI:
CI = SMA(CI_raw, smoothing_window)
Dominant phase:
phi_dom_rad = atan2(sum_sin, sum_cos)
phi_dom_deg = phi_dom_rad × (180 / π)
Phase 4: Entanglement Matrix Population
For i = 0 to N-2:
For j = i+1 to N-1:
phi_i = osc_phases × (π / 180)
phi_j = osc_phases × (π / 180)
delta_phi = phi_i - phi_j
E = |cos(delta_phi)|
matrix_index_ij = i × N + j
matrix_index_ji = j × N + i
entangle_matrix = E
entangle_matrix = E
if E >= threshold:
entangled_pairs += 1
The matrix uses flat array storage with index mapping: index(row, col) = row × N + col.
Phase 5: Phase-Lock Check
max_spread = 0
For i = 0 to N-2:
For j = i+1 to N-1:
delta = |osc_phases - osc_phases |
if delta > 180:
delta = 360 - delta
max_spread = max(max_spread, delta)
phase_locked = (max_spread < tolerance)
Phase 6: Signal Evaluation
Ignition Long :
ignition_long = (CI crosses above threshold) AND
(phi_dom > -90 AND phi_dom < 90) AND
phase_locked AND
(entangled_pairs >= minimum)
Ignition Short :
ignition_short = (CI crosses above threshold) AND
(phi_dom < -90 OR phi_dom > 90) AND
phase_locked AND
(entangled_pairs >= minimum)
Collapse :
CI_prev = CI
collapse = (CI_prev - CI > collapse_threshold) AND (CI_prev > 0.6)
All signals are evaluated on bar close. The crossover and crossunder functions ensure signals fire only once when conditions transition from false to true.
Phase 7: Field Strength and Visualization Metrics
Average Amplitude :
avg_amp = (Σ osc_amps ) / N
Field Strength :
field_strength = CI × avg_amp
Collapse Risk (for dashboard):
collapse_risk = (CI - CI) / max(CI , 0.1)
collapse_risk_pct = clamp(collapse_risk × 100, 0, 100)
Quantum State Classification :
if (CI > threshold AND phase_locked):
state = "Ignition"
else if (CI > 0.6):
state = "Coherent"
else if (collapse):
state = "Collapse"
else:
state = "Chaos"
Phase 8: Visual Rendering
Orbit Plot : For each oscillator, convert polar (phase, amplitude) to Cartesian (x, y) for grid placement:
radius = amplitude × grid_center × 0.8
x = radius × cos(phase × π/180)
y = radius × sin(phase × π/180)
col = center + x (mapped to grid coordinates)
row = center - y
Heat Map : For each oscillator row and time column, retrieve historical phase value at lookback = (columns - col) × sample_rate, then map phase to color using a hue gradient.
Entanglement Web : Render matrix as table cell with background color opacity = E(i,j).
Field Cloud : Background color = (phi_dom > -90 AND phi_dom < 90) ? green : red, with opacity = mix(min_opacity, max_opacity, CI).
All visual components render only on the last bar (barstate.islast) to minimize computational overhead.
How to Use This Indicator
Step 1 : Apply QRFM to your chart. It works on all timeframes and asset classes, though 15-minute to 4-hour timeframes provide the best balance of responsiveness and noise reduction.
Step 2 : Enable the dashboard (default: top right) and the circular orbit plot (default: middle left). These are your primary visual feedback tools.
Step 3 : Optionally enable the heat map, entanglement web, and field cloud based on your preference. New users may find all visuals overwhelming; start with dashboard + orbit plot.
Step 4 : Observe for 50-100 bars to let the indicator establish baseline coherence patterns. Markets have different "normal" CI ranges—some instruments naturally run higher or lower coherence.
Understanding the Circular Orbit Plot
The orbit plot is a polar grid showing oscillator vectors in real-time:
Center point : Neutral (zero phase and amplitude)
Each vector : A line from center to a point on the grid
Vector angle : The oscillator's phase (0° = right/east, 90° = up/north, 180° = left/west, -90° = down/south)
Vector length : The oscillator's amplitude (short = weak signal, long = strong signal)
Vector label : First letter of oscillator name (R = RSI, M = MACD, etc.)
What to watch :
Convergence : When all vectors cluster in one quadrant or sector, CI is rising and coherence is forming. This is your pre-signal warning.
Scatter : When vectors point in random directions (360° spread), CI is low and the market is in a non-trending or transitional regime.
Rotation : When the cluster rotates smoothly around the circle, the ensemble is in coherent oscillation—typically seen during steady trends.
Sudden flips : When the cluster rapidly jumps from one side to the opposite (e.g., +90° to -90°), a phase reversal has occurred—often coinciding with trend reversals.
Example: If you see RSI, MACD, and Stochastic all pointing toward 45° (northeast) with long vectors, while CCI, TSI, and ROC point toward 40-50° as well, coherence is high and dominant phase is bullish. Expect an ignition signal if CI crosses threshold.
Reading Dashboard Metrics
The dashboard provides numerical confirmation of what the orbit plot shows visually:
CI : Displays as 0-100%. Above 70% = high coherence (strong regime), 40-70% = moderate, below 40% = low (poor conditions for trend entries).
Dom Phase : Angle in degrees with directional arrow. ⬆ = bullish bias, ⬇ = bearish bias, ⬌ = neutral.
Field Strength : CI weighted by amplitude. High values (> 0.6) indicate not just alignment but strong alignment.
Entangled Pairs : Count of oscillator pairs with E > threshold. Higher = more confirmation. If minimum is set to 4, you need at least 4 pairs entangled for signals.
Phase Lock : 🔒 YES (all oscillators within tolerance) or 🔓 NO (spread too wide).
State : Real-time classification:
🚀 IGNITION: CI just crossed threshold with phase-lock
⚡ COHERENT: CI is high and stable
💥 COLLAPSE: CI has dropped sharply
🌀 CHAOS: Low CI, scattered phases
Collapse Risk : 0-100% scale based on recent CI change. Above 50% warns of imminent breakdown.
Interpreting Signals
Long Ignition (Blue Triangle Below Price) :
Occurs when CI crosses above threshold (e.g., 0.80)
Dominant phase is in bullish range (-90° to +90°)
All oscillators are phase-locked (within tolerance)
Minimum entangled pairs requirement met
Interpretation : The oscillator ensemble has transitioned from disorder to coherent bullish alignment. This is a high-probability long entry point. The multi-layer confirmation (CI + phase direction + lock + entanglement) ensures this is not a single-oscillator whipsaw.
Short Ignition (Red Triangle Above Price) :
Same conditions as long, but dominant phase is in bearish range (< -90° or > +90°)
Interpretation : Coherent bearish alignment has formed. High-probability short entry.
Collapse (Circles Above and Below Price) :
CI has dropped by more than the collapse threshold (e.g., 0.55) over a 5-bar window
CI was previously above 0.6 (collapsing from coherent state)
Interpretation : Phase coherence has broken down. If you are in a position, this is an exit warning. If looking to enter, stand aside—regime is transitioning.
Phase-Time Heat Map Patterns
Enable the heat map and position it at bottom right. The rows represent individual oscillators, columns represent time bins (most recent on left).
Pattern: Horizontal Color Bands
If a row (e.g., RSI) shows consistent color across columns (say, green for several bins), that oscillator has maintained stable phase over time. If all rows show horizontal bands of similar color, the entire ensemble has been phase-locked for an extended period—this is a strong trending regime.
Pattern: Vertical Color Bands
If a column (single time bin) shows all cells with the same or very similar color, that moment in time had high coherence. These vertical bands often align with ignition signals or major price pivots.
Pattern: Rainbow Chaos
If cells are random colors (red, green, yellow mixed with no pattern), coherence is low. The ensemble is scattered. Avoid trading during these periods unless you have external confirmation.
Pattern: Color Transition
If you see a row transition from red to green (or vice versa) sharply, that oscillator has phase-flipped. If multiple rows do this simultaneously, a regime change is underway.
Entanglement Web Analysis
Enable the web matrix (default: opposite corner from heat map). It shows an N×N grid where N = number of active oscillators.
Bright Yellow/Gold Cells : High pairwise entanglement. For example, if the RSI-MACD cell is bright gold, those two oscillators are moving in phase. If the RSI-Stochastic cell is bright, they are entangled as well.
Dark Gray Cells : Low entanglement. Oscillators are decorrelated or in quadrature.
Diagonal : Always marked with "—" because an oscillator is always perfectly entangled with itself.
How to use :
Scan for clustering: If most cells are bright, coherence is high across the board. If only a few cells are bright, coherence is driven by a subset (e.g., RSI and MACD are aligned, but nothing else is—weak signal).
Identify laggards: If one row/column is entirely dark, that oscillator is the outlier. You may choose to disable it or monitor for when it joins the group (late confirmation).
Watch for web formation: During low-coherence periods, the matrix is mostly dark. As coherence builds, cells begin lighting up. A sudden "web" of connections forming visually precedes ignition signals.
Trading Workflow
Step 1: Monitor Coherence Level
Check the dashboard CI metric or observe the orbit plot. If CI is below 40% and vectors are scattered, conditions are poor for trend entries. Wait.
Step 2: Detect Coherence Building
When CI begins rising (say, from 30% to 50-60%) and you notice vectors on the orbit plot starting to cluster, coherence is forming. This is your alert phase—do not enter yet, but prepare.
Step 3: Confirm Phase Direction
Check the dominant phase angle and the orbit plot quadrant where clustering is occurring:
Clustering in right half (0° to ±90°): Bullish bias forming
Clustering in left half (±90° to 180°): Bearish bias forming
Verify the dashboard shows the corresponding directional arrow (⬆ or ⬇).
Step 4: Wait for Signal Confirmation
Do not enter based on rising CI alone. Wait for the full ignition signal:
CI crosses above threshold
Phase-lock indicator shows 🔒 YES
Entangled pairs count >= minimum
Directional triangle appears on chart
This ensures all layers have aligned.
Step 5: Execute Entry
Long : Blue triangle below price appears → enter long
Short : Red triangle above price appears → enter short
Step 6: Position Management
Initial Stop : Place stop loss based on your risk management rules (e.g., recent swing low/high, ATR-based buffer).
Monitoring :
Watch the field cloud density. If it remains opaque and colored in your direction, the regime is intact.
Check dashboard collapse risk. If it rises above 50%, prepare for exit.
Monitor the orbit plot. If vectors begin scattering or the cluster flips to the opposite side, coherence is breaking.
Exit Triggers :
Collapse signal fires (circles appear)
Dominant phase flips to opposite half-plane
CI drops below 40% (coherence lost)
Price hits your profit target or trailing stop
Step 7: Post-Exit Analysis
After exiting, observe whether a new ignition forms in the opposite direction (reversal) or if CI remains low (transition to range). Use this to decide whether to re-enter, reverse, or stand aside.
Best Practices
Use Price Structure as Context
QRFM identifies when coherence forms but does not specify where price will go. Combine ignition signals with support/resistance levels, trendlines, or chart patterns. For example:
Long ignition near a major support level after a pullback: high-probability bounce
Long ignition in the middle of a range with no structure: lower probability
Multi-Timeframe Confirmation
Open QRFM on two timeframes simultaneously:
Higher timeframe (e.g., 4-hour): Use CI level to determine regime bias. If 4H CI is above 60% and dominant phase is bullish, the market is in a bullish regime.
Lower timeframe (e.g., 15-minute): Execute entries on ignition signals that align with the higher timeframe bias.
This prevents counter-trend trades and increases win rate.
Distinguish Between Regime Types
High CI, stable dominant phase (State: Coherent) : Trending market. Ignitions are continuation signals; collapses are profit-taking or reversal warnings.
Low CI, erratic dominant phase (State: Chaos) : Ranging or choppy market. Avoid ignition signals or reduce position size. Wait for coherence to establish.
Moderate CI with frequent collapses : Whipsaw environment. Use wider stops or stand aside.
Adjust Parameters to Instrument and Timeframe
Crypto/Forex (high volatility) : Lower ignition threshold (0.65-0.75), lower CI smoothing (2-3), shorter oscillator lengths (7-10).
Stocks/Indices (moderate volatility) : Standard settings (threshold 0.75-0.85, smoothing 5-7, oscillator lengths 14).
Lower timeframes (5-15 min) : Reduce phase sample rate to 1-2 for responsiveness.
Higher timeframes (daily+) : Increase CI smoothing and oscillator lengths for noise reduction.
Use Entanglement Count as Conviction Filter
The minimum entangled pairs setting controls signal strictness:
Low (1-2) : More signals, lower quality (acceptable if you have other confirmation)
Medium (3-5) : Balanced (recommended for most traders)
High (6+) : Very strict, fewer signals, highest quality
Adjust based on your trade frequency preference and risk tolerance.
Monitor Oscillator Contribution
Use the entanglement web to see which oscillators are driving coherence. If certain oscillators are consistently dark (low E with all others), they may be adding noise. Consider disabling them. For example:
On low-volume instruments, MFI may be unreliable → disable MFI
On strongly trending instruments, mean-reversion oscillators (Stochastic, RSI) may lag → reduce weight or disable
Respect the Collapse Signal
Collapse events are early warnings. Price may continue in the original direction for several bars after collapse fires, but the underlying regime has weakened. Best practice:
If in profit: Take partial or full profit on collapse
If at breakeven/small loss: Exit immediately
If collapse occurs shortly after entry: Likely a false ignition; exit to avoid drawdown
Collapses do not guarantee immediate reversals—they signal uncertainty .
Combine with Volume Analysis
If your instrument has reliable volume:
Ignitions with expanding volume: Higher conviction
Ignitions with declining volume: Weaker, possibly false
Collapses with volume spikes: Strong reversal signal
Collapses with low volume: May just be consolidation
Volume is not built into QRFM (except via MFI), so add it as external confirmation.
Observe the Phase Spiral
The spiral provides a quick visual cue for rotation consistency:
Tight, smooth spiral : Ensemble is rotating coherently (trending)
Loose, erratic spiral : Phase is jumping around (ranging or transitional)
If the spiral tightens, coherence is building. If it loosens, coherence is dissolving.
Do Not Overtrade Low-Coherence Periods
When CI is persistently below 40% and the state is "Chaos," the market is not in a regime where phase analysis is predictive. During these times:
Reduce position size
Widen stops
Wait for coherence to return
QRFM's strength is regime detection. If there is no regime, the tool correctly signals "stand aside."
Use Alerts Strategically
Set alerts for:
Long Ignition
Short Ignition
Collapse
Phase Lock (optional)
Configure alerts to "Once per bar close" to avoid intrabar repainting and noise. When an alert fires, manually verify:
Orbit plot shows clustering
Dashboard confirms all conditions
Price structure supports the trade
Do not blindly trade alerts—use them as prompts for analysis.
Ideal Market Conditions
Best Performance
Instruments :
Liquid, actively traded markets (major forex pairs, large-cap stocks, major indices, top-tier crypto)
Instruments with clear cyclical oscillator behavior (avoid extremely illiquid or manipulated markets)
Timeframes :
15-minute to 4-hour: Optimal balance of noise reduction and responsiveness
1-hour to daily: Slower, higher-conviction signals; good for swing trading
5-minute: Acceptable for scalping if parameters are tightened and you accept more noise
Market Regimes :
Trending markets with periodic retracements (where oscillators cycle through phases predictably)
Breakout environments (coherence forms before/during breakout; collapse occurs at exhaustion)
Rotational markets with clear swings (oscillators phase-lock at turning points)
Volatility :
Moderate to high volatility (oscillators have room to move through their ranges)
Stable volatility regimes (sudden VIX spikes or flash crashes may create false collapses)
Challenging Conditions
Instruments :
Very low liquidity markets (erratic price action creates unstable oscillator phases)
Heavily news-driven instruments (fundamentals may override technical coherence)
Highly correlated instruments (oscillators may all reflect the same underlying factor, reducing independence)
Market Regimes :
Deep, prolonged consolidation (oscillators remain near neutral, CI is chronically low, few signals fire)
Extreme chop with no directional bias (oscillators whipsaw, coherence never establishes)
Gap-driven markets (large overnight gaps create phase discontinuities)
Timeframes :
Sub-5-minute charts: Noise dominates; oscillators flip rapidly; coherence is fleeting and unreliable
Weekly/monthly: Oscillators move extremely slowly; signals are rare; better suited for long-term positioning than active trading
Special Cases :
During major economic releases or earnings: Oscillators may lag price or become decorrelated as fundamentals overwhelm technicals. Reduce position size or stand aside.
In extremely low-volatility environments (e.g., holiday periods): Oscillators compress to neutral, CI may be artificially high due to lack of movement, but signals lack follow-through.
Adaptive Behavior
QRFM is designed to self-adapt to poor conditions:
When coherence is genuinely absent, CI remains low and signals do not fire
When only a subset of oscillators aligns, entangled pairs count stays below threshold and signals are filtered out
When phase-lock cannot be achieved (oscillators too scattered), the lock filter prevents signals
This means the indicator will naturally produce fewer (or zero) signals during unfavorable conditions, rather than generating false signals. This is a feature —it keeps you out of low-probability trades.
Parameter Optimization by Trading Style
Scalping (5-15 Minute Charts)
Goal : Maximum responsiveness, accept higher noise
Oscillator Lengths :
RSI: 7-10
MACD: 8/17/6
Stochastic: 8-10, smooth 2-3
CCI: 14-16
Others: 8-12
Coherence Settings :
CI Smoothing Window: 2-3 bars (fast reaction)
Phase Sample Rate: 1 (every bar)
Ignition Threshold: 0.65-0.75 (lower for more signals)
Collapse Threshold: 0.40-0.50 (earlier exit warnings)
Confirmation :
Phase Lock Tolerance: 40-50° (looser, easier to achieve)
Min Entangled Pairs: 2-3 (fewer oscillators required)
Visuals :
Orbit Plot + Dashboard only (reduce screen clutter for fast decisions)
Disable heavy visuals (heat map, web) for performance
Alerts :
Enable all ignition and collapse alerts
Set to "Once per bar close"
Day Trading (15-Minute to 1-Hour Charts)
Goal : Balance between responsiveness and reliability
Oscillator Lengths :
RSI: 14 (standard)
MACD: 12/26/9 (standard)
Stochastic: 14, smooth 3
CCI: 20
Others: 10-14
Coherence Settings :
CI Smoothing Window: 3-5 bars (balanced)
Phase Sample Rate: 2-3
Ignition Threshold: 0.75-0.85 (moderate selectivity)
Collapse Threshold: 0.50-0.55 (balanced exit timing)
Confirmation :
Phase Lock Tolerance: 30-40° (moderate tightness)
Min Entangled Pairs: 4-5 (reasonable confirmation)
Visuals :
Orbit Plot + Dashboard + Heat Map or Web (choose one)
Field Cloud for regime backdrop
Alerts :
Ignition and collapse alerts
Optional phase-lock alert for advance warning
Swing Trading (4-Hour to Daily Charts)
Goal : High-conviction signals, minimal noise, fewer trades
Oscillator Lengths :
RSI: 14-21
MACD: 12/26/9 or 19/39/9 (longer variant)
Stochastic: 14-21, smooth 3-5
CCI: 20-30
Others: 14-20
Coherence Settings :
CI Smoothing Window: 5-10 bars (very smooth)
Phase Sample Rate: 3-5
Ignition Threshold: 0.80-0.90 (high bar for entry)
Collapse Threshold: 0.55-0.65 (only significant breakdowns)
Confirmation :
Phase Lock Tolerance: 20-30° (tight clustering required)
Min Entangled Pairs: 5-7 (strong confirmation)
Visuals :
All modules enabled (you have time to analyze)
Heat Map for multi-bar pattern recognition
Web for deep confirmation analysis
Alerts :
Ignition and collapse
Review manually before entering (no rush)
Position/Long-Term Trading (Daily to Weekly Charts)
Goal : Rare, very high-conviction regime shifts
Oscillator Lengths :
RSI: 21-30
MACD: 19/39/9 or 26/52/12
Stochastic: 21, smooth 5
CCI: 30-50
Others: 20-30
Coherence Settings :
CI Smoothing Window: 10-14 bars
Phase Sample Rate: 5 (every 5th bar to reduce computation)
Ignition Threshold: 0.85-0.95 (only extreme alignment)
Collapse Threshold: 0.60-0.70 (major regime breaks only)
Confirmation :
Phase Lock Tolerance: 15-25° (very tight)
Min Entangled Pairs: 6+ (broad consensus required)
Visuals :
Dashboard + Orbit Plot for quick checks
Heat Map to study historical coherence patterns
Web to verify deep entanglement
Alerts :
Ignition only (collapses are less critical on long timeframes)
Manual review with fundamental analysis overlay
Performance Optimization (Low-End Systems)
If you experience lag or slow rendering:
Reduce Visual Load :
Orbit Grid Size: 8-10 (instead of 12+)
Heat Map Time Bins: 5-8 (instead of 10+)
Disable Web Matrix entirely if not needed
Disable Field Cloud and Phase Spiral
Reduce Calculation Frequency :
Phase Sample Rate: 5-10 (calculate every 5-10 bars)
Max History Depth: 100-200 (instead of 500+)
Disable Unused Oscillators :
If you only want RSI, MACD, and Stochastic, disable the other five. Fewer oscillators = smaller matrices, faster loops.
Simplify Dashboard :
Choose "Small" dashboard size
Reduce number of metrics displayed
These settings will not significantly degrade signal quality (signals are based on bar-close calculations, which remain accurate), but will improve chart responsiveness.
Important Disclaimers
This indicator is a technical analysis tool designed to identify periods of phase coherence across an ensemble of oscillators. It is not a standalone trading system and does not guarantee profitable trades. The Coherence Index, dominant phase, and entanglement metrics are mathematical calculations applied to historical price data—they measure past oscillator behavior and do not predict future price movements with certainty.
No Predictive Guarantee : High coherence indicates that oscillators are currently aligned, which historically has coincided with trending or directional price movement. However, past alignment does not guarantee future trends. Markets can remain coherent while prices consolidate, or lose coherence suddenly due to news, liquidity changes, or other factors not captured by oscillator mathematics.
Signal Confirmation is Probabilistic : The multi-layer confirmation system (CI threshold + dominant phase + phase-lock + entanglement) is designed to filter out low-probability setups. This increases the proportion of valid signals relative to false signals, but does not eliminate false signals entirely. Users should combine QRFM with additional analysis—support and resistance levels, volume confirmation, multi-timeframe alignment, and fundamental context—before executing trades.
Collapse Signals are Warnings, Not Reversals : A coherence collapse indicates that the oscillator ensemble has lost alignment. This often precedes trend exhaustion or reversals, but can also occur during healthy pullbacks or consolidations. Price may continue in the original direction after a collapse. Use collapses as risk management cues (tighten stops, take partial profits) rather than automatic reversal entries.
Market Regime Dependency : QRFM performs best in markets where oscillators exhibit cyclical, mean-reverting behavior and where trends are punctuated by retracements. In markets dominated by fundamental shocks, gap openings, or extreme low-liquidity conditions, oscillator coherence may be less reliable. During such periods, reduce position size or stand aside.
Risk Management is Essential : All trading involves risk of loss. Use appropriate stop losses, position sizing, and risk-per-trade limits. The indicator does not specify stop loss or take profit levels—these must be determined by the user based on their risk tolerance and account size. Never risk more than you can afford to lose.
Parameter Sensitivity : The indicator's behavior changes with input parameters. Aggressive settings (low thresholds, loose tolerances) produce more signals with lower average quality. Conservative settings (high thresholds, tight tolerances) produce fewer signals with higher average quality. Users should backtest and forward-test parameter sets on their specific instruments and timeframes before committing real capital.
No Repainting by Design : All signal conditions are evaluated on bar close using bar-close values. However, the visual components (orbit plot, heat map, dashboard) update in real-time during bar formation for monitoring purposes. For trade execution, rely on the confirmed signals (triangles and circles) that appear only after the bar closes.
Computational Load : QRFM performs extensive calculations, including nested loops for entanglement matrices and real-time table rendering. On lower-powered devices or when running multiple indicators simultaneously, users may experience lag. Use the performance optimization settings (reduce visual complexity, increase phase sample rate, disable unused oscillators) to improve responsiveness.
This system is most effective when used as one component within a broader trading methodology that includes sound risk management, multi-timeframe analysis, market context awareness, and disciplined execution. It is a tool for regime detection and signal confirmation, not a substitute for comprehensive trade planning.
Technical Notes
Calculation Timing : All signal logic (ignition, collapse) is evaluated using bar-close values. The barstate.isconfirmed or implicit bar-close behavior ensures signals do not repaint. Visual components (tables, plots) render on every tick for real-time feedback but do not affect signal generation.
Phase Wrapping : Phase angles are calculated in the range -180° to +180° using atan2. Angular distance calculations account for wrapping (e.g., the distance between +170° and -170° is 20°, not 340°). This ensures phase-lock detection works correctly across the ±180° boundary.
Array Management : The indicator uses fixed-size arrays for oscillator phases, amplitudes, and the entanglement matrix. The maximum number of oscillators is 8. If fewer oscillators are enabled, array sizes shrink accordingly (only active oscillators are processed).
Matrix Indexing : The entanglement matrix is stored as a flat array with size N×N, where N is the number of active oscillators. Index mapping: index(row, col) = row × N + col. Symmetric pairs (i,j) and (j,i) are stored identically.
Normalization Stability : Oscillators are normalized to using fixed reference levels (e.g., RSI overbought/oversold at 70/30). For unbounded oscillators (MACD, ROC, TSI), statistical normalization (division by rolling standard deviation) is used, with clamping to prevent extreme outliers from distorting phase calculations.
Smoothing and Lag : The CI smoothing window (SMA) introduces lag proportional to the window size. This is intentional—it filters out single-bar noise spikes in coherence. Users requiring faster reaction can reduce the smoothing window to 1-2 bars, at the cost of increased sensitivity to noise.
Complex Number Representation : Pine Script does not have native complex number types. Complex arithmetic is implemented using separate real and imaginary accumulators (sum_cos, sum_sin) and manual calculation of magnitude (sqrt(real² + imag²)) and argument (atan2(imag, real)).
Lookback Limits : The indicator respects Pine Script's maximum lookback constraints. Historical phase and amplitude values are accessed using the operator, with lookback limited to the chart's available bar history (max_bars_back=5000 declared).
Visual Rendering Performance : Tables (orbit plot, heat map, web, dashboard) are conditionally deleted and recreated on each update using table.delete() and table.new(). This prevents memory leaks but incurs redraw overhead. Rendering is restricted to barstate.islast (last bar) to minimize computational load—historical bars do not render visuals.
Alert Condition Triggers : alertcondition() functions evaluate on bar close when their boolean conditions transition from false to true. Alerts do not fire repeatedly while a condition remains true (e.g., CI stays above threshold for 10 bars fires only once on the initial cross).
Color Gradient Functions : The phaseColor() function maps phase angles to RGB hues using sine waves offset by 120° (red, green, blue channels). This creates a continuous spectrum where -180° to +180° spans the full color wheel. The amplitudeColor() function maps amplitude to grayscale intensity. The coherenceColor() function uses cos(phase) to map contribution to CI (positive = green, negative = red).
No External Data Requests : QRFM operates entirely on the chart's symbol and timeframe. It does not use request.security() or access external data sources. All calculations are self-contained, avoiding lookahead bias from higher-timeframe requests.
Deterministic Behavior : Given identical input parameters and price data, QRFM produces identical outputs. There are no random elements, probabilistic sampling, or time-of-day dependencies.
— Dskyz, Engineering precision. Trading coherence.
EV/FCFThis script in the 6 version of Pine brings you the most accurate multiple of "fundamental valuation" in my opinion. EV/FCF gives you a real metric of how profitable is the company in this exact moment and also if the company is overvaluated or undervaluated.
Luxy BIG beautiful Dynamic ORBThis is an advanced Opening Range Breakout (ORB) indicator that tracks price breakouts from the first 5, 15, 30, and 60 minutes of the trading session. It provides complete trade management including entry signals, stop-loss placement, take-profit targets, and position sizing calculations.
The ORB strategy is based on the concept that the opening range of a trading session often acts as support/resistance, and breakouts from this range tend to lead to significant moves.
What Makes This Different?
Most ORB indicators simply draw horizontal lines and leave you to figure out the rest. This indicator goes several steps further:
Multi-Stage Tracking
Instead of just one ORB timeframe, this tracks FOUR simultaneously (5min, 15min, 30min, 60min). Each stage builds on the previous one, giving you multiple trading opportunities throughout the session.
Active Trade Management
When a breakout occurs, the indicator automatically calculates and displays entry price, stop-loss, and multiple take-profit targets. These lines extend forward and update in real-time until the trade completes.
Cycle Detection
Unlike indicators that only show the first breakout, this tracks the complete cycle: Breakout → Retest → Re-breakout. You can see when price returns to test the ORB level after breaking out (potential re-entry).
Failed Breakout Warning
If price breaks out but quickly returns inside the range (within a few bars), the label changes to "FAILED BREAK" - warning you to exit or avoid the trade.
Position Sizing Calculator
Built-in risk management that tells you exactly how many shares to buy based on your account size and risk tolerance. No more guessing or manual calculations.
Advanced Filtering
Optional filters for volume confirmation, trend alignment, and Fair Value Gaps (FVG) to reduce false signals and improve win rate.
Core Features Explained
### 1. Multi-Stage ORB Levels
The indicator builds four separate Opening Range levels:
ORB 5 - First 5 minutes (fastest signals, most volatile)
ORB 15 - First 15 minutes (balanced, most popular)
ORB 30 - First 30 minutes (slower, more reliable)
ORB 60 - First 60 minutes (slowest, most confirmed)
Each level is drawn as a horizontal range on your chart. As time progresses, the ranges expand to include more price action. You can enable or disable any stage and assign custom colors to each.
How it works: During the opening minutes, the indicator tracks the highest high and lowest low. Once the time period completes, those levels become your ORB high and low for that stage.
### 2. Breakout Detection
When price closes outside the ORB range, a label appears:
BREAK UP (green label above price) - Price closed above ORB High
BREAK DOWN (red label below price) - Price closed below ORB Low
The label shows which ORB stage triggered (ORB5, ORB15, etc.) and the cycle number if tracking multiple breakouts.
Important: Signals appear on bar close only - no repainting. What you see is what you get.
### 3. Retest Detection
After price breaks out and moves away, if it returns to test the ORB level, a "RETEST" label appears (orange). This indicates:
The original breakout level is now acting as support/resistance
Potential re-entry opportunity if you missed the first breakout
Confirmation that the level is significant
The indicator requires price to move a minimum distance away before considering it a valid retest (configurable in settings).
### 4. Failed Breakout Detection
If price breaks out but returns inside the ORB range within a few bars (before the breakout is "committed"), the original label changes to "FAILED BREAK" in orange.
This warns you:
The breakout lacked conviction
Consider exiting if already in the trade
Wait for better setup
Committed Breakout: The indicator tracks how many bars price stays outside the range. Only after staying outside for the minimum number of bars does it become a committed breakout that can be retested.
### 5. TP/SL Lines (Trade Management)
When a breakout occurs, colored horizontal lines appear showing:
Entry Line (cyan for long, orange for short) - Your entry price (the ORB level)
Stop Loss Line (red) - Where to exit if trade goes against you
TP1, TP2, TP3 Lines (same color as entry) - Profit targets at 1R, 2R, 3R
These lines extend forward as new bars form, making it easy to track your trade. When a target is hit, the line turns green and the label shows a checkmark.
Lines freeze (stop updating) when:
Stop loss is hit
The final enabled take-profit is hit
End of trading session (optional setting)
### 6. Position Sizing Dashboard
The dashboard (bottom-left corner by default) shows real-time information:
Current ORB stage and range size
Breakout status (Inside Range / Break Up / Break Down)
Volume confirmation (if filter enabled)
Trend alignment (if filter enabled)
Entry and Stop Loss prices
All enabled Take Profit levels with percentages
Risk/Reward ratio
Position sizing: Max shares to buy and total risk amount
Position Sizing Example:
If your account is $25,000 and you risk 1% per trade ($250), and the distance from entry to stop loss is $0.50, the calculator shows you can buy 500 shares (250 / 0.50 = 500).
### 7. FVG Filter (Fair Value Gap)
Fair Value Gaps are price inefficiencies - gaps left by strong momentum where one candle's high doesn't overlap with a previous candle's low (or vice versa).
When enabled, this filter:
Detects bullish and bearish FVGs
Draws semi-transparent boxes around these gaps
Only allows breakout signals if there's an FVG near the breakout level
Why this helps: FVGs indicate institutional activity. Breakouts through FVGs tend to be stronger and more reliable.
Proximity setting: Controls how close the FVG must be to the ORB level. 2.0x means the breakout can be within 2 times the FVG size - a reasonable default.
### 8. Volume & Trend Filters
Volume Filter:
Requires current volume to be above average (customizable multiplier). High volume breakouts are more likely to sustain.
Set minimum multiplier (e.g., 1.5x = 50% above average)
Set "strong volume" multiplier (e.g., 2.5x) that bypasses other filters
Dashboard shows current volume ratio
Trend Filter:
Only shows breakouts aligned with a higher timeframe trend. Choose from:
VWAP - Price above/below volume-weighted average
EMA - Price above/below exponential moving average
SuperTrend - ATR-based trend indicator
Combined modes (VWAP+EMA, VWAP+SuperTrend) for stricter filtering
### 9. Pullback Filter (Advanced)
Purpose:
Waits for price to pull back slightly after initial breakout before confirming the signal.
This reduces false breakouts from immediate reversals.
How it works:
- After breakout is detected, indicator waits for a small pullback (default 2%)
- Once pullback occurs AND price breaks out again, signal is confirmed
- If no pullback within timeout period (5 bars), signal is issued anyway
Settings:
Enable Pullback Filter: Turn this filter on/off
Pullback %: How much price must pull back (2% is balanced)
Timeout (bars): Max bars to wait for pullback (5 is standard)
When to use:
- Choppy markets with many fake breakouts
- When you want higher quality signals
- Combine with Volume filter for maximum confirmation
Trade-off:
- Better signal quality
- May miss some valid fast moves
- Slight entry delay
How to Use This Indicator
### For Beginners - Simple Setup
Add the indicator to your chart (5-minute or 15-minute timeframe recommended)
Leave all default settings - they work well for most stocks
Watch for BREAK UP or BREAK DOWN labels to appear
Check the dashboard for entry, stop loss, and targets
Use the position sizing to determine how many shares to buy
Basic Trading Plan:
Wait for a clear breakout label
Enter at the ORB level (or next candle open if you're late)
Place stop loss where the red line indicates
Take profit at TP1 (50% of position) and TP2 (remaining 50%)
### For Advanced Traders - Customized Setup
Choose which ORB stages to track (you might only want ORB15 and ORB30)
Enable filters: Volume (stocks) or Trend (trending markets)
Enable FVG filter for institutional confirmation
Set "Track Cycles" mode to catch retests and re-breakouts
Customize stop loss method (ATR for volatile stocks, ORB% for stable ones)
Adjust risk per trade and account size for accurate position sizing
Advanced Strategy Example:
Enable ORB15 only (disable others for cleaner chart)
Turn on Volume filter at 1.5x with Strong at 2.5x
Enable Trend filter using VWAP
Set Signal Mode to "Track Cycles" with Max 3 cycles
Wait for aligned breakouts (Volume + Trend + Direction)
Enter on retest if you missed the initial break
### Timeframe Recommendations
5-minute chart: Scalping, very active trading, crypto
15-minute chart: Day trading, balanced approach (most popular)
30-minute chart: Swing entries, less screen time
60-minute chart: Position trading, longer holds
The indicator works on any intraday timeframe, but ORB is fundamentally a day trading strategy. Daily charts don't make sense for ORB.
DEFAULT CONFIGURATION
ON by Default:
• All 4 ORB stages (5/15/30/60)
• Breakout Detection
• Retest Labels
• All TP levels (1/1.5/2/3)
• TP/SL Lines (Detailed mode)
• Dashboard (Bottom Left, Dark theme)
• Position Size Calculator
OFF by Default (Optional Filters):
• FVG Filter
• Pullback Filter
• Volume Filter
• Trend Filter
• HTF Bias Check
• Alerts
Recommended for Beginners:
• Leave all defaults
• Session Mode: Auto-Detect
• Signal Mode: Track Cycles
• Stop Method: ATR
• Add Volume Filter if trading stocks
Recommended for Advanced:
• Enable ORB15 + ORB30 only (disable 5 & 60)
• Enable: Volume + Trend + FVG
• Signal Mode: Track Cycles, Max 3
• Stop Method: ATR or Safer
• Enable HTF Daily bias check
## Settings Guide
The settings are organized into logical groups. Here's what each section controls:
### ORB COLORS Section
Show Edge Labels: Display "ORB 5", "ORB 15" labels at the right edge of the levels
Background: Fill the area between ORB high/low with color
Transparency: How see-through the background is (95% is nearly invisible)
Enable ORB 5/15/30/60: Turn each stage on or off individually
Colors: Assign colors to each ORB stage for easy identification
### SESSION SETTINGS Section
Session Mode: Choose trading session (Auto-Detect works for most instruments)
Custom Session Hours: Define your own hours if needed (format: HHMM-HHMM)
Auto-Detect uses the instrument's natural hours (stocks use exchange hours, crypto uses 24/7).
### BREAKOUT DETECTION Section
Enable Breakout Detection: Master switch for signals
Show Retest Labels: Display retest signals
Label Size: Visual size for all labels (Small recommended)
Enable FVG Filter: Require Fair Value Gap confirmation
Show FVG Boxes: Display the gap boxes on chart
Signal Mode: "First Only" = one signal per direction per day, "Track Cycles" = multiple signals
Max Cycles: How many breakout-retest cycles to track (6 is balanced)
Breakout Buffer: Extra distance required beyond ORB level (0.1-0.2% recommended)
Min Distance for Retest: How far price must move away before retest is valid (2% recommended)
Min Bars Outside ORB: Bars price must stay outside for committed breakout (2 is balanced)
### TARGETS & RISK Section
Enable Targets & Stop-Loss: Calculate and show trade management
TP1/TP2/TP3 checkboxes: Select which profit targets to display
Stop Method: How to calculate stop loss placement
- ATR: Based on volatility (best for most cases)
- ORB %: Fixed % of ORB range
- Swing: Recent swing high/low
- Safer: Widest of all methods
ATR Length & Multiplier: Controls ATR stop distance (14 period, 1.5x is standard)
ORB Stop %: Percentage beyond ORB for stop (20% is balanced)
Swing Bars: Lookback period for swing high/low (3 is recent)
### TP/SL LINES Section
Show TP/SL Lines: Display horizontal lines on chart
Label Format: "Short" = minimal text, "Detailed" = shows prices
Freeze Lines at EOD: Stop extending lines at session close
### DASHBOARD Section
Show Info Panel: Display the metrics dashboard
Theme: Dark or Light colors
Position: Where to place dashboard on chart
Toggle rows: Show/hide specific information rows
Calculate Position Size: Enable the position sizing calculator
Risk Mode: Risk fixed $ amount or % of account
Account Size: Your total trading capital
Risk %: Percentage to risk per trade (0.5-1% recommended)
### VOLUME FILTER Section
Enable Volume Filter: Require volume confirmation
MA Length: Average period (20 is standard)
Min Volume: Required multiplier (1.5x = 50% above average)
Strong Volume: Multiplier that bypasses other filters (2.5x)
### TREND FILTER Section
Enable Trend Filter: Require trend alignment
Trend Mode: Method to determine trend (VWAP is simple and effective)
Custom EMA Length: If using EMA mode (50 for swing, 20 for day trading)
SuperTrend settings: Period and Multiplier if using SuperTrend mode
### HIGHER TIMEFRAME Section
Check Daily Trend: Display higher timeframe bias in dashboard
Timeframe: What TF to check (D = daily, recommended)
Method: Price vs MA (stable) or Candle Direction (reactive)
MA Period: EMA length for Price vs MA method (20 is balanced)
Min Strength %: Minimum strength threshold for HTF bias to be considered
- For "Price vs MA": Minimum distance (%) from moving average
- For "Candle Direction": Minimum candle body size (%)
- 0.5% is balanced - increase for stricter filtering
- Lower values = more signals, higher values = only strong trends
### ALERTS Section
Enable Alerts: Master switch (must be ON to use any alerts)
Breakout Alerts: Notify on ORB breakouts
Retest Alerts: Notify when price retests after breakout
Failed Break Alerts: Notify on failed breakouts
Stage Complete Alerts: Notify when each ORB stage finishes forming
After enabling desired alert types, click "Create Alert" button, select this indicator, choose "Any alert() function call".
## Tips & Best Practices
### General Trading Tips
ORB works best on liquid instruments (stocks with good volume, major crypto pairs)
First hour of the session is most important - that's when ORB is forming
Breakouts WITH the trend have higher success rates - use the trend filter
Failed breakouts are common - use the "Min Bars Outside" setting to filter weak moves
Not every day produces good ORB setups - be patient and selective
### Position Sizing Best Practices
Never risk more than 1-2% of your account on a single trade
Use the built-in calculator - don't guess your position size
Update your account size monthly as it grows
Smaller accounts: use $ Amount mode for simplicity
Larger accounts: use % of Account mode for scaling
### Take Profit Strategy
Most traders use: 50% at TP1, 50% at TP2
Aggressive: Hold through TP1 for TP2 or TP3
Conservative: Full exit at TP1 (1:1 risk/reward)
After TP1 hits, consider moving stop to breakeven
TP3 rarely hits - only on strong trending days
### Filter Combinations
Maximum Quality: Volume + Trend + FVG (fewest signals, highest quality)
Balanced: Volume + Trend (good quality, reasonable frequency)
Active Trading: No filters or Volume only (many signals, lower quality)
Trending Markets: Trend filter essential (indices, crypto)
Range-Bound: Volume + FVG (avoid trend filter)
### Common Mistakes to Avoid
Chasing breakouts - wait for the bar to close, don't FOMO into wicks
Ignoring the stop loss - always use it, move it manually if needed
Over-leveraging - the calculator shows MAX shares, you can buy less
Trading every signal - quality > quantity, use filters
Not tracking results - keep a journal to see what works for YOU
## Pros and Cons
### Advantages
Complete all-in-one solution - from signal to position sizing
Multiple timeframes tracked simultaneously
Visual clarity - easy to see what's happening
Cycle tracking catches opportunities others miss
Built-in risk management eliminates guesswork
Customizable filters for different trading styles
No repainting - what you see is locked in
Works across multiple markets (stocks, forex, crypto)
### Limitations
Intraday strategy only - doesn't work on daily charts
Requires active monitoring during first 1-2 hours of session
Not suitable for after-hours or extended sessions by default
Can produce many signals in choppy markets (use filters)
Dashboard can be overwhelming for complete beginners
Performance depends on market conditions (trends vs ranges)
Requires understanding of risk management concepts
### Best For
Day traders who can watch the first 1-2 hours of market open
Traders who want systematic entry/exit rules
Those learning proper position sizing and risk management
Active traders comfortable with multiple signals per day
Anyone trading liquid instruments with clear sessions
### Not Ideal For
Swing traders holding multi-day positions
Set-and-forget / passive investors
Traders who can't watch market open
Complete beginners unfamiliar with trading concepts
Low volume / illiquid instruments
## Frequently Asked Questions
Q: Why are no signals appearing?
A: Check that you're on an intraday timeframe (5min, 15min, etc.) and that the current time is within your session hours. Also verify that "Enable Breakout Detection" is ON and at least one ORB stage is enabled. If using filters, they might be blocking signals - try disabling them temporarily.
Q: What's the best ORB stage to use?
A: ORB15 (15 minutes) is most popular and balanced. ORB5 gives faster signals but more noise. ORB30 and ORB60 are slower but more reliable. Many traders use ORB15 + ORB30 together.
Q: Should I enable all the filters?
A: Start with no filters to see all signals. If too many false signals, add Volume filter first (stocks) or Trend filter (trending markets). FVG filter is most restrictive - use for maximum quality but fewer signals.
Q: How do I know which stop loss method to use?
A: ATR works for most cases - it adapts to volatility. Use ORB% if you want predictable stop placement. Swing is for respecting chart structure. Safer gives you the most room but largest risk.
Q: Can I use this for swing trading?
A: Not really - ORB is fundamentally an intraday strategy. The ranges reset each day. For swing trading, look at weekly support/resistance or moving averages instead.
Q: Why do TP/SL lines disappear sometimes?
A: Lines freeze (stop extending) when: stop loss is hit, the last enabled take-profit is hit, or end of session arrives (if "Freeze at EOD" is enabled). This is intentional - the trade is complete.
Q: What's the difference between "First Only" and "Track Cycles"?
A: "First Only" shows one breakout UP and one DOWN per day maximum - clean but might miss opportunities. "Track Cycles" shows breakout-retest-rebreak sequences - more signals but busier chart.
Q: Is position sizing accurate for options/forex?
A: The calculator is designed for shares (stocks). For options, ignore the share count and use the risk amount. For forex, you'll need to adapt the lot size calculation manually.
Q: How much capital do I need to use this?
A: The indicator works for any account size, but practical day trading typically requires $25,000 in the US due to Pattern Day Trader rules. Adjust the "Account Size" setting to match your capital.
Q: Can I backtest this strategy?
A: This is an indicator, not a strategy script, so it doesn't have built-in backtesting. You can visually review historical signals or code a strategy script using similar logic.
Q: Why does the dashboard show different entry price than the breakout label?
A: If you're looking at an old breakout, the ORB levels may have changed when the next stage completed. The dashboard always shows the CURRENT active range and trade setup.
Q: What's a good win rate to expect?
A: ORB strategies typically see 40-60% win rate depending on market conditions and filters used. The strategy relies on positive risk/reward ratios (2:1 or better) to be profitable even with moderate win rates.
Q: Does this work on crypto?
A: Yes, but crypto trades 24/7 so you need to define what "session start" means. Use Session Mode = Custom and set your preferred daily reset time (e.g., 0000-2359 UTC).
## Credits & Transparency
### Development
This indicator was developed with the assistance of AI technology to implement complex ORB trading logic.
The strategy concept, feature specifications, and trading logic were designed by the publisher. The implementation leverages modern development tools to ensure:
Clean, efficient, and maintainable code
Comprehensive error handling and input validation
Detailed documentation and user guidance
Performance optimization
### Trading Concepts
This indicator implements several public domain trading concepts:
Opening Range Breakout (ORB): Trading strategy popularized by Toby Crabel, Mark Fisher and many more talanted traders.
Fair Value Gap (FVG): Price imbalance concept from ICT methodology
SuperTrend: ATR-based trend indicator using public formula
Risk/Reward Ratio: Standard risk management principle
All mathematical formulas and technical concepts used are in the public domain.
### Pine Script
Uses standard TradingView built-in functions:
ta.ema(), ta.atr(), ta.vwap(), ta.highest(), ta.lowest(), request.security()
No external libraries or proprietary code from other authors.
## Disclaimer
This indicator is provided for educational and informational purposes only. It is not financial advice.
Trading involves substantial risk of loss and is not suitable for every investor. Past performance shown in examples is not indicative of future results.
The indicator provides signals and calculations, but trading decisions are solely your responsibility. Always:
Test strategies on paper before using real money
Never risk more than you can afford to lose
Understand that all trading involves risk
Consider seeking advice from a licensed financial advisor
The publisher makes no guarantees regarding accuracy, profitability, or performance. Use at your own risk.
---
Version: 3.0
Pine Script Version: v6
Last Updated: October 2024
For support, questions, or suggestions, please comment below or send a private message.
---
Happy trading, and remember: consistent risk management beats perfect entry timing every time.
Adaptive Trend SelectorThe Adaptive Trend Selector is a comprehensive trend-following tool designed to automatically identify the optimal moving average crossover strategy. It features adjustable parameters and an integrated backtester that delivers institutional-grade insights into the recommended strategy. The model continuously adapts to new data in real time by evaluating multiple moving average combinations, determining the best performing lengths, and presenting the backtest results in a clear, color-coded table that benchmarks performance against the buy-and-hold strategy.
At its core, the model systematically backtests a wide range of moving average combinations to identify the configuration that maximizes the selected optimization metric. Users can choose to optimize for absolute returns or risk-adjusted returns using the Sharpe, Sortino, or Calmar ratios. Alternatively, users can enable manual optimization to test custom fast and slow moving average lengths and view the corresponding backtest results. The label displays the Compounded Annual Growth Rate (CAGR) of the strategy, with the buy-and-hold CAGR in parentheses for comparison. The table presents the backtest results based on the fast and slow lengths displayed at the top:
Sharpe = CAGR per unit of standard deviation.
Sortino = CAGR per unit of downside deviation.
Calmar = CAGR relative to maximum drawdown.
Max DD = Largest peak-to-trough decline in value.
Beta (β) = Return sensitivity relative to buy-and-hold.
Alpha (α) = Excess annualized risk-adjusted returns.
Win Rate = Ratio of profitable trades to total trades.
Profit Factor = Total gross profit per unit of losses.
Expectancy = Average expected return per trade.
Trades/Year = Average number of trades per year.
This indicator is designed with flexibility in mind, enabling users to specify the start date of the backtesting period and the preferred moving average strategy. Supported strategies include the Exponential Moving Average (EMA), Simple Moving Average (SMA), Wilder’s Moving Average (RMA), Weighted Moving Average (WMA), and Volume-Weighted Moving Average (VWMA). To minimize overfitting, users can define constraints such as a minimum and maximum number of trades per year, as well as an optional optimization margin that prioritizes longer, more robust combinations by requiring shorter-length strategies to exceed this threshold. The table follows an intuitive color logic that enables quick performance comparison against buy-and-hold (B&H):
Sharpe = Green indicates better than B&H, while red indicates worse.
Sortino = Green indicates better than B&H, while red indicates worse.
Calmar = Green indicates better than B&H, while red indicates worse.
Max DD = Green indicates better than B&H, while red indicates worse.
Beta (β) = Green indicates better than B&H, while red indicates worse.
Alpha (α) = Green indicates above 0%, while red indicates below 0%.
Win Rate = Green indicates above 50%, while red indicates below 50%.
Profit Factor = Green indicates above 2, while red indicates below 1.
Expectancy = Green indicates above 0%, while red indicates below 0%.
In summary, the Adaptive Trend Selector is a powerful tool designed to help investors make data-driven decisions when selecting moving average crossover strategies. By optimizing for risk-adjusted returns, investors can confidently identify the best lengths using institutional-grade metrics. While results are based on the selected historical period, users should be mindful of potential overfitting, as past results may not persist under future market conditions. Since the model recalibrates to incorporate new data, the recommended lengths may evolve over time.
Multi-Timeframe Granville Signal──────────────────────────────────────────
OVERVIEW
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MTF Granville Signal is an invite-only Pine Script indicator that assists traders in identifying high-probability entry points based on Granville's Law principles, enhanced with Multi-Timeframe (MTF) structural analysis and dynamic Moving Average Deviation Rate (MADR) filtering.
This indicator is NOT investment advice. It is a technical analysis tool. All trading decisions and outcomes are the sole responsibility of the user.
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WHAT MAKES THIS INDICATOR ORIGINAL
──────────────────────────────────────────
While many indicators implement basic Granville's Law or simple moving average crosses, this indicator distinguishes itself through two mathematically rigorous enhancements:
1. Dynamic MADR Filtering with Statistical Foundation
Unlike fixed percentage bands used in conventional overbought/oversold indicators, this system employs adaptive threshold calculation based on rolling standard deviation :
Mathematical Approach:
Calculates price deviation from the reference Simple Moving Average(SMA) as a percentage
Computes standard deviation (σ) over an extended lookback period
Default: 1σ threshold = 68.26% probability zone under normal distribution
User-configurable sigma multiplier (1σ, 2σ, 3σ)
Operational Logic:
Trend-following signals (Granville Rules 1, 2, 3, 5, 6, 7) : Fire only when MADR is within normal range (< threshold), indicating healthy trend conditions
Counter-trend signals (Granville Rules 4, 8) : Fire only when MADR exceeds threshold, indicating statistical over-extension and mean-reversion probability
Why This Matters:
Traditional indicators use arbitrary fixed thresholds (e.g., "overbought above +3%"). Market volatility varies dramatically across assets and time periods. A 3% deviation in EUR/USD may be extreme, while in Bitcoin it's noise. Dynamic MADR automatically adapts to each market's volatility characteristics, maintaining consistent statistical validity across diverse trading instruments.
2. MTF Structural Verification for Cycle-Phase Filtering
This is not merely displaying multiple timeframe SMAs on a chart. The indicator performs structural analysis to determine trend cycle phase :
Verification Mechanism:
Checks if price has recently touched/crossed the higher timeframe SMA within a configurable lookback period
Confirms SMA hierarchy alignment (short-term > mid-term > long-term for uptrends)
Distinguishes between early-cycle trend initiation and late-cycle exhaustion
Why This Matters:
Granville's Law signals can appear throughout a trend cycle, but probability varies significantly:
Early cycle (price recently interacted with higher TF SMA): High probability - catching trend initiation or deep retracements
Late cycle (price extended far from higher TF SMA): Low probability - entering during exhaustion phase
By requiring recent structural interaction with higher timeframe SMAs, the indicator filters out low-probability late-cycle entries, dramatically improving signal quality.
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GRANVILLE'S LAW IMPLEMENTATION
──────────────────────────────────────────
This indicator implements all eight of Joseph Granville's classic rules, with a focus on Rules 1, 2, 3,4, 5, 6, 7, and 8 for primary signal generation. Rules 3 and 7 are operationalized through touch-based approximation (see explanation below):
Trend-Following Signals (Rules 1, 2, 3, 5, 6, 7)
Buy Signals:
Short-term SMA crosses above (or touches and bounces off) mid/long-term SMAs
SMA hierarchy confirms uptrend structure
MADR indicates price is NOT over-extended
Price recently interacted with higher timeframe SMA (MTF verification)
Sell Signals:
Mirror logic for downtrends
Counter-Trend Mean-Reversion Signals (Rules 4, 8)
Sell Signals:
Price shows extreme deviation from reference SMA (MADR exceeds threshold)
Price begins reverting toward SMA
Short-term SMA crosses below (or touches and bounces off) mid/long-term SMAs
Recent structural interaction with higher timeframe SMA confirms reversal setup
Buy Signals:
Mirror logic for oversold reversals
How Rules 3 and 7 Are Handled:
Rules 3 and 7 describe "price approaches the SMA." Rather than excluding these rules, this indicator approximates "approaches" as "touches the SMA" to eliminate ambiguity. In practice, defining "approaches" is subjective and adds complexity. By operationalizing "approaches" as "touches/crosses," the indicator maintains mechanical objectivity while still capturing the intent of Rules 3 and 7.
──────────────────────────────────────────
WHY GRANVILLE'S LAW?
──────────────────────────────────────────
Universality: Functions across all markets (forex, stocks, crypto, commodities) and timeframes
Simplicity: Based solely on price-to-moving-average relationships—no complex calculations
Reproducibility: Mechanical rules eliminate emotional bias
60+ Year Track Record: Proven principle since Joseph Granville's 1960 publication
──────────────────────────────────────────
TECHNICAL ARCHITECTURE
──────────────────────────────────────────
Signal Generation Process
Calculate SMAs across multiple timeframes (short/mid/long-term periods)
Compute MADR : Measure price deviation from reference SMA and its statistical significance
Verify MTF Structure : Check recent price interaction with higher timeframe SMA
Evaluate SMA Hierarchy : Confirm trend direction via SMA alignment
Apply Granville Logic : Detect specific Rule patterns (crosses, touches, bounces)
Determining deviation from SMA :
• Trend-following: MADR < threshold (healthy trend)
• Counter-trend: MADR > threshold (over-extension)
Signal Interval Control : Cooldown period prevents alert spam during noise
Why This Combination Works
The synthesis of these three components creates a robust filtering system:
Granville's Law provides the fundamental signal logic (proven over decades)
Dynamic MADR prevents entries at dangerous price extremes (volatility-adaptive risk management)
MTF Structural Verification ensures signals occur at optimal cycle phases (timing optimization)
No single element alone produces high-quality signals. Their integration may generate edge in trending market conditions.
──────────────────────────────────────────
WHAT THIS INDICATOR DOES NOT DO
──────────────────────────────────────────
To set realistic expectations:
❌ Does not predict future price direction with certainty
❌ Does not guarantee profitable trades
❌ Does not work equally well in all market conditions (see below for limitations)
❌ Does not replace risk management, position sizing, or trading discipline
❌ Does not provide trade exit signals (focus is on entry timing)
──────────────────────────────────────────
PARAMETER CONFIGURATION
──────────────────────────────────────────
Mid Term Trend Check Enabled (Default: true)
Activates SMA hierarchy verification for mid-term trend confirmation.
When enabled: Signals require short-term SMA > mid-term SMA (uptrend) or vice versa (downtrend)
When disabled: Only short-term SMA behavior is evaluated
Recommendation : Keep enabled for most use cases to filter weak trends
Long Term Trend Check Enabled (Default: true)
Adds long-term SMA to hierarchy verification for additional trend strength confirmation.
Requires Mid Term Trend Check to be enabled
When enabled: Signals require short-term SMA > mid-term SMA > long-term SMA alignment
Recommendation : Enable on lower timeframes (15m or below) for stronger filtering. Disable on higher timeframes (1h or above) as the additional filter becomes redundant and overly restrictive
Require Touch Higher Timeframe SMA Enabled (Default: true)
Enforces recent price interaction with higher timeframe SMA to filter late-cycle entries.
When enabled: Signals fire only if price touched/crossed mid-term or long-term SMA within lookback period
When disabled: Signals can fire regardless of recent SMA interaction (more signals, lower quality)
Recommendation : Keep enabled. This is a core filter for cycle-phase discrimination
Touch Higher Timeframe SMA Lookback Period (Default: 24 bars)
Defines how far back to search for price-SMA interaction.
Lower values (12-18): Stricter filtering, fewer signals, earlier cycle detection
Higher values (24-36): More lenient filtering, more signals, includes some mid-cycle entries
Recommendation : Adjust based on market volatility. Trending markets: use lower values. Choppy markets: use higher values to capture valid retracements
SMA Short Term Period (Default: 20)
Primary SMA for Granville's Law pattern detection.
Lower values (10-15): More responsive, more signals, higher noise
Higher values (25-40): Smoother, fewer signals, delayed entries
Recommendation : 20 is standard across most markets. Adjust ±5 based on your timeframe preference
SMA Mid Term Period (Default: 80)
Reference SMA for trend hierarchy and MTF verification.
Typically 3-5x the short-term period
Recommendation : 80 works well for intraday (15m, 1h) and swing trading (4h, daily). Maintain ratio relationship with short-term SMA
SMA Long Term Period (Default: 320)
Optional trend strength filter (requires Long Term Trend Check enabled).
Typically 4x the mid-term period
Recommendation : 320 is appropriate for multi-day trend analysis. Not critical for intraday scalping
SMA Period for Divergence (Default: 1920)
Lookback period for calculating MADR standard deviation. Two approaches:
Approach 1: Chart Timeframe SMA (Simple)
Use 20 periods matching your chart timeframe for straightforward deviation measurement.
Example: 20 periods on any timeframe
Approach 2: Higher Timeframe SMA (MTF Analysis)
Use period equivalent to higher timeframe's 20-period SMA for multi-timeframe structural analysis.
Recommendation for day trading :
• 15m chart: 1920 periods (≈ daily 20-SMA: 20 days × 96 bars/day)
• 1h chart: 480 periods (≈ daily 20-SMA: 20 days × 24 bars/day)
• 4h chart: 120 periods (≈ daily 20-SMA: 20 days × 6 bars/day)
Both approaches are valid. Approach 2 incorporates higher timeframe context into MADR filtering.
MADR Standard Deviation Band (Sigma) (Default: 1.00)
Statistical threshold for determining trend overheating vs. healthy conditions.
1.0σ = 68.26% probability zone (default, balanced)
2.0σ = 95.44% probability zone (stricter, fewer counter-trend signals)
3.0σ = 99.74% probability zone (very strict, rare extreme reversals only)
Recommendation : Start with 1.0σ. Increase to 2.0σ if you want to trade only extreme mean-reversion opportunities. Decrease to 0.5σ-0.8σ for more aggressive trend-following
Signal Minimum Interval (Default: 4 hours)
Cooldown period between signals to prevent alert spam during consolidation.
Measured in hours regardless of chart timeframe
0 = no cooldown (all valid signals fire)
2-4 = typical for day trading
8-12 = typical for swing trading
Recommendation : Match to your trading frequency. Day traders: 2-4 hours. Swing traders: 8-12 hours
Buy/Sell Signal Text Color (Default: Blue)
Reversal Buy/Sell Signal Text Color (Default: Purple)
Customize label colors for visual distinction between trend-following and counter-trend signals.
Alert Display Prefix (Default: Auto-detected from chart timeframe)
Prefix for alert messages (e.g., "1h", "15m"). Auto-filled if left blank.
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RECOMMENDED CONFIGURATIONS
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Configuration 1: Aggressive Day Trading (15m Chart)
SMA Short: 20
SMA Mid: 80
SMA Long: 320
MADR SMA Period: 1920
MADR Sigma: 1.0
Signal Interval: 4 hours
Touch Lookback: 24 bars
Long Term Trend Check: Enabled
Use case: Active day trading, multiple signals per session
Configuration 2: Balanced Day Trading (1h Chart)
SMA Short: 20
SMA Mid: 80
MADR SMA Period: 480
MADR Sigma: 1.0
Signal Interval: 4 hours
Touch Lookback: 24 bars
Long Term Trend Check: Disabled
Use case: Standard day trading, moderate signal frequency
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TECHNICAL LIMITATIONS AND UNSUITABLE CONDITIONS
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This indicator has known limitations:
1. Range/Choppy Markets
Extended consolidation generates false signals and whipsaw entries. Wait for clear breakout or use higher timeframe trend filters.
2. Low Liquidity Instruments
In exotic pairs, microcap stocks, or illiquid assets, wide spreads and slippage erode edge. Stick to major high-volume instruments.
3. News-Driven Volatility
Fundamental shocks invalidate technical patterns. Avoid trading around scheduled high-impact news events.
4. Algorithmic Regime Changes
Market microstructure evolves over time. Review performance periodically and adjust parameters if edge deteriorates.
5. Extreme Market Regimes
Black swan events and unprecedented volatility cause all technical systems to fail simultaneously. Use circuit breakers and position size limits.
6. Gap Openings
Price gaps over weekends or between sessions invalidate some signals. Reduce position sizing accordingly.
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OPEN-SOURCE CODE TRANSPARENCY
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While the source code is proprietary and protected, the fundamentals are fully explainable:
SMA calculation : Standard Pine Script ta.sma() function
MADR calculation : (close - sma) / sma * 100 and ta.stdev() for threshold
MTF data retrieval : request.security() for higher timeframe values
Granville pattern detection : Logical comparison of price/SMA positions and crosses
No "black box" algorithms. No hidden magic. Only rigorous application of proven technical principles.
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OPEN-SOURCE CODE REUSE
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This indicator does NOT reuse code from other TradingView scripts. All logic is proprietary.
Standard Pine Script functions (ta.sma, ta.stdev, request.security, etc.) used per documented API
No third-party libraries or external dependencies
No license conflicts
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VERSION INFORMATION
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Current Version : 6 (Pine Script v6)
Author : © 2025 mmntmr369. All rights reserved.
Publication Type : Invite-only (Proprietary source code)
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DISCLAIMER : This indicator is provided for educational and informational purposes only. It does not constitute investment advice, financial advice, trading advice, or any other type of advice. You should not make any investment decisions based solely on this indicator. Always conduct your own research and consult with a licensed financial professional before making investment decisions. Past performance does not indicate future results. Trading carries substantial risk of loss and is not suitable for all investors.
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日本語版 / JAPANESE VERSION
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概要
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MTF Granville Signalは、グランビルの法則の原則に基づいた高確率エントリーポイントの特定を支援する招待制Pine Scriptインジケーターです。マルチタイムフレーム（MTF）構造分析と動的移動平均線乖離率（MADR）フィルタリングにより強化されています。
本インジケーターは投資助言ではありません。 これはテクニカル分析ツールです。すべての取引判断と結果は、ユーザーの単独責任となります。
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本インジケーターの独自性
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多くのインジケーターが基本的なグランビルの法則または単純な移動平均クロスを実装していますが、本インジケーターは2つの数学的に厳密な拡張機能によって差別化されます：
1. 統計的基盤を持つ動的MADRフィルタリング
従来の買われ過ぎ/売られ過ぎインジケーターで使用される固定パーセンテージバンドとは異なり、本システムは ローリング標準偏差に基づく適応的閾値計算 を採用しています：
数学的アプローチ:
参照SMAからの価格偏差をパーセンテージとして計算
拡張ルックバック期間にわたって標準偏差（σ）を計算
デフォルト：1σ閾値 = 正規分布下の68.26%確率ゾーン
ユーザー設定可能なシグマ乗数（1σ、2σ、3σ）
操作ロジック:
順張りシグナル（グランビル法則1、2、3、5、6、7） ：MADRが正常範囲内（<閾値）にある場合のみ発火し、健全なトレンド状態を示します
逆張りシグナル（グランビル法則4、8） ：MADRが閾値を超える場合のみ発火し、統計的過度の拡張と平均回帰確率を示します
重要な理由:
従来のインジケーターは任意の固定閾値（例：「+3%以上で買われ過ぎ」）を使用します。市場のボラティリティは資産と期間によって劇的に変化します。EUR/USDでの3%偏差は極端かもしれませんが、ビットコインではノイズです。動的MADRは各市場のボラティリティ特性に自動的に適応し、多様な取引商品全体で一貫した統計的妥当性を維持します。
2. サイクルフェーズフィルタリングのためのMTF構造検証
これは単にチャート上に複数の時間足SMAを表示するだけではありません。インジケーターは トレンドサイクルフェーズを決定するための構造分析 を実行します：
検証メカニズム:
設定可能なルックバック期間内に価格が上位時間足SMAに最近タッチ/クロスしたかどうかを確認
SMA階層の整列を確認（上昇トレンドでは短期>中期>長期）
初期サイクルトレンド開始と後期サイクル疲弊を区別
重要な理由:
グランビルの法則シグナルはトレンドサイクル全体で出現できますが、確率は大きく異なります：
初期サイクル （価格が最近上位TF SMAと相互作用）：高確率 - トレンド開始または深い調整を捕捉
後期サイクル （価格が上位TF SMAから遠く離れている）：低確率 - 疲弊フェーズ中のエントリー
上位時間足SMAとの最近の構造的相互作用を要求することで、インジケーターは低確率の後期サイクルエントリーを除外し、シグナル品質を劇的に向上させます。
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グランビルの法則実装
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本インジケーターはジョセフ・グランビルの古典的な8つの法則すべてを実装しており、 法則1、2、3、4、5、6、7、8 に焦点を当てた主要シグナル生成を行います。法則3と7はタッチベースの近似で運用されます（以下の説明を参照）：
順張りシグナル（法則1、2、3、5、6、7）
買いシグナル:
短期SMAが中期/長期SMAを上回って交差する（またはタッチしてバウンス）
SMA階層が上昇トレンド構造を確認
MADRが価格が過度に拡張されていないことを示す
価格が最近上位時間足SMAと相互作用した（MTF検証）
売りシグナル:
下降トレンドの場合は反対のロジック
逆張り平均回帰シグナル（法則4、8）
売りシグナル:
価格が参照SMAから極端に乖離（MADRが閾値を超える）
価格がSMAに向かって反転を開始
短期SMAが中期/長期SMAを下回って交差する（またはタッチしてバウンス）
上位時間足SMAとの最近の構造的相互作用が反転セットアップを確認
買いシグナル:
売られ過ぎ反転の場合は反対のロジック
法則3と7の取り扱い:
法則3と7は「価格がSMAに接近する」と説明しています。これらの法則を除外するのではなく、本インジケーターは曖昧さを排除するために「接近」を「SMAにタッチ」として近似します。実際には、「接近」の定義は主観的で複雑さを追加します。「接近」を「タッチ/クロス」として運用することで、インジケーターは法則3と7の意図を捕捉しながら機械的客観性を維持します。
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なぜグランビルの法則？
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普遍性: すべての市場（外国為替、株式、暗号、商品）および時間足で機能
シンプルさ: 価格対移動平均の関係のみに基づく - 複雑な計算なし
再現性: 機械的ルールが感情的バイアスを排除
60年以上の実績: ジョセフ・グランビルの1960年の出版以来実証された原則
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技術アーキテクチャ
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シグナル生成プロセス
SMAを計算 複数の時間足にわたって（短期/中期/長期期間）
MADRを計算 ：参照SMAからの価格偏差とその統計的有意性を測定
MTF構造を検証 ：上位時間足SMAとの最近の価格相互作用を確認
SMA階層を評価 ：SMA整列によってトレンド方向を確認
グランビルロジックを適用 ：特定の法則パターンを検出（クロス、タッチ、バウンス）
SMAからの乖離を判定 ：
• 順張り：MADR < 閾値（健全なトレンド）
• 逆張り：MADR > 閾値（過度の拡張）
シグナル間隔制御 ：クールダウン期間がノイズ中のアラートスパムを防止
なぜこの組み合わせが機能するか
これら3つのコンポーネントの統合が堅牢なフィルタリングシステムを生成します：
グランビルの法則 が基本的なシグナルロジックを提供（数十年にわたって実証）
動的MADR が危険な価格極値でのエントリーを防止（ボラティリティ適応的リスク管理）
MTF構造検証 がシグナルを最適なサイクルフェーズで発生させる（タイミング最適化）
単一の要素だけでは高品質のシグナルは生成されません。それらの統合はトレンド相場環境においてエッジを生み出す可能性があります。
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本インジケーターが行わないこと
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現実的な期待を設定するために：
❌ 将来の価格方向を確実に予測しない
❌ 収益性のある取引を保証しない
❌ すべての市場環境で等しく機能しない（限界については下記参照）
❌ リスク管理、ポジションサイジング、または取引規律を置き換えない
❌ 取引の手仕舞いシグナルを提供しない（焦点はエントリータイミング）
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パラメータ設定
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Mid Term Trend Check Enabled（中期トレンドチェック有効） (デフォルト: true)
中期トレンド確認のためのSMA階層検証を有効化。
有効時：シグナルは短期SMA > 中期SMA（上昇トレンド）またはその逆（下降トレンド）を要求
無効時：短期SMAの動作のみを評価
推奨 ：弱いトレンドをフィルタリングするため、ほとんどの用途で有効を維持
Long Term Trend Check Enabled（長期トレンドチェック有効） (デフォルト: true)
追加のトレンド強度確認のため、長期SMAをSMA階層検証に追加。
中期トレンドチェックの有効化が必要
有効時：シグナルは短期SMA > 中期SMA > 長期SMAの整列を要求
推奨 ：低時間足（15分足以下）でより強力なフィルタリングのため有効化。高時間足（1時間足以上）では追加フィルターが冗長かつ過度に制限的になるため無効化
Require Touch Higher Timeframe SMA Enabled（上位足SMAタッチ要求有効） (デフォルト: true)
後期サイクルエントリーをフィルタリングするため、上位時間足SMAとの最近の価格相互作用を強制。
有効時：シグナルはルックバック期間内に価格が中期または長期SMAにタッチ/クロスした場合のみ発火
無効時：最近のSMA相互作用に関係なくシグナル発火（多くのシグナル、低品質）
推奨 ：有効を維持。これはサイクルフェーズ識別のコアフィルター
Touch Higher Timeframe SMA Lookback Period（上位足SMAタッチルックバック期間） (デフォルト: 24バー)
価格-SMA相互作用を検索する遡及期間を定義。
低い値（12-18）：厳格なフィルタリング、少ないシグナル、初期サイクル検出
高い値（24-36）：寛容なフィルタリング、多くのシグナル、中期サイクルエントリーを含む
推奨 ：市場ボラティリティに基づいて調整。トレンド市場：低い値を使用。荒れた市場：有効な調整を捉えるため高い値を使用
SMA Short Term Period（SMA短期期間） (デフォルト: 20)
グランビルの法則パターン検出のための主要SMA。
低い値（10-15）：反応的、多くのシグナル、高いノイズ
高い値（25-40）：滑らか、少ないシグナル、遅延エントリー
推奨 ：20はほとんどの市場で標準。時間足の好みに基づいて±5調整
SMA Mid Term Period（SMA中期期間） (デフォルト: 80)
トレンド階層とMTF検証のための基準SMA。
通常、短期期間の3-5倍
推奨 ：80はデイトレ（15m、1h）とスイングトレード（4h、日足）に適している。短期SMAとの比率関係を維持
SMA Long Term Period（SMA長期期間） (デフォルト: 320)
オプションのトレンド強度フィルター（長期トレンドチェック有効時必要）。
通常、中期期間の4倍
推奨 ：320は数日間のトレンド分析に適している。デイトレ、スイングには重要でない
SMA Period for Divergence（乖離のためのSMA期間） (デフォルト: 1920)
MADR標準偏差計算のためのルックバック期間。2つのアプローチがあります：
アプローチ1：チャート時間足SMA（シンプル）
チャート時間足と同じ20期間を使用し、シンプルに乖離を測定。
例：どの時間足でも20期間
アプローチ2：上位時間足SMA（MTF分析）
上位時間足の20期間SMA相当の期間を設定し、マルチタイムフレーム構造分析として利用。
デイトレーディング推奨設定 :
• 15分足チャート：1920期間（≈ 日足20-SMA：20日 × 96本/日）
• 1時間足チャート：480期間（≈ 日足20-SMA：20日 × 24本/日）
• 4時間足チャート：120期間（≈ 日足20-SMA：20日 × 6本/日）
両アプローチとも有効。アプローチ2は上位時間足のコンテクストをMADRフィルタリングに組み込む。
MADR Standard Deviation Band (Sigma)（MADR標準偏差バンド（シグマ）） (デフォルト: 1.00)
トレンド過熱と健全状態を判定するための統計的閾値。
1.0σ = 68.26%確率ゾーン（デフォルト、バランス型）
2.0σ = 95.44%確率ゾーン（厳格、少ない逆張りシグナル）
3.0σ = 99.74%確率ゾーン（非常に厳格、稀な極端反転のみ）
推奨 ：1.0σから開始。極端な平均回帰機会のみを取引したい場合は2.0σに増加。より積極的な順張りのため0.5σ-0.8σに減少
Signal Minimum Interval（シグナル最小間隔） (デフォルト: 4時間)
保ち合い中のアラートスパムを防ぐためのシグナル間のクールダウン期間。
チャート時間足に関係なく時間で測定
0 = クールダウンなし（すべての有効なシグナルが発火）
2-4 = デイトレード取引の典型
8-12 = スイング取引の典型
推奨 ：取引頻度に合わせる。デイトレーダー：2-4時間。スイングトレーダー：8-12時間
Buy/Sell Signal Text Color（買い/売りシグナルテキスト色） (デフォルト: 青)
Reversal Buy/Sell Signal Text Color（反転買い/売りシグナルテキスト色） (デフォルト: 紫)
順張りシグナルと逆張りシグナルの視覚的区別のためのラベル色をカスタマイズ。
Alert Display Prefix（アラート表示プレフィックス） (デフォルト: チャート時間足から自動検出)
アラートメッセージのプレフィックス（例：「1h」、「15m」）。空白の場合自動入力。
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推奨設定例
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設定1：積極的デイトレ（15分足チャート）
SMA Short: 20
SMA Mid: 80
SMA Long: 320
MADR SMA Period: 1920
MADR Sigma: 1.0
Signal Interval: 4時間
Touch Lookback: 24バー
Long Term Trend Check: 有効
用途: アクティブなデイトレード、セッションあたり複数のシグナル
設定2：バランス型デイトレ（1時間足チャート）
SMA Short: 20
SMA Mid: 80
MADR SMA Period: 480
MADR Sigma: 1.0
Signal Interval: 4時間
Touch Lookback: 24バー
Long Term Trend Check: 無効
用途: 標準的デイトレード、適度なシグナル頻度
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技術的限界と不適切な条件
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本インジケーターには既知の限界があります：
1. レンジ/荒れた市場
長期の保ち合いが偽シグナルとウィップソーエントリーを生成。明確なブレイクアウトまで待つか、高時間足トレンドフィルターを使用。
2. 流動性の低い銘柄
エキゾチックペア、マイクロキャップ株、流動性の低い資産では、広いスプレッドとスリッページがエッジを侵食。主要な高出来高銘柄に固執。
3. ニュース主導のボラティリティ
ファンダメンタルショックがテクニカルパターンを無効化。予定されている高インパクトニュースイベント前後の取引を避ける。
4. アルゴリズム的レジーム変化
市場マイクロ構造は時間とともに進化。定期的にパフォーマンスをレビューし、エッジが劣化した場合はパラメータを調整。
5. 極端な市場レジーム
ブラックスワンイベントと前例のないボラティリティは、すべてのテクニカルシステムを同時に失敗させる。サーキットブレーカーとポジションサイズ制限を使用。
6. ギャップオープニング
週末またはセッション間の価格ギャップが一部のシグナルを無効化。それに応じてポジションサイジングを削減。
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オープンソースコードの透明性
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ソースコードはプロプライエタリで保護されていますが、基本は以下で完全に説明できます：
SMA計算 ：標準Pine Script ta.sma()関数
MADR計算 ：(close - sma) / sma * 100と閾値のためのta.stdev()
MTFデータ取得 ：上位時間足値のためのrequest.security()
グランビルパターン検出 ：価格/SMAポジションとクロスの論理比較
「ブラックボックス」アルゴリズムなし。隠された魔法なし。実証された技術原則の厳密な適用のみ。
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オープンソースコードの再利用
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本インジケーターは他のTradingViewスクリプトのコードを 再利用していません 。すべてのロジックは独自です。
標準Pine Script関数（ta.sma、ta.stdev、request.securityなど）は文書化されたAPIに従って使用
サードパーティライブラリや外部依存関係なし
ライセンス競合なし
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バージョン情報
現在のバージョン ：6（Pine Script v6）
作成者 ：© 2025 mmntmr369. 無断転載禁止。
公開タイプ ：招待制（プロプライエタリソースコード）
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免責事項 ：本インジケーターは教育および情報提供目的のみで提供されています。投資助言、金融助言、取引助言、その他いかなる種類の助言も構成しません。本インジケーターのみに基づいて投資判断を行うべきではありません。投資判断を行う前に、必ずご自身で調査を行い、認可された金融専門家に相談してください。過去のパフォーマンスは将来の結果を示すものではありません。取引には多大な損失リスクがあり、すべての投資家に適しているわけではありません。
The Slick Strategy ReadinessThe Slick Strategy Readiness
Purpose
This is a readiness checklist, not an auto-trader. It supports the method from “The Slick Strategy: A Unique Profitable Options Trading Method.” The idea: each Monday, if conditions are READY, sell a 10-point wide SPX put credit spread with the short strike ~30 points below Monday’s open and hold to Friday’s close.
How the decision works
• Timing mode (choose one):
– Strict: Monday OPEN vs Friday SMAs (non-repainting on daily)
– Mid: Monday OPEN vs Monday SMAs (uses same day; repaints on daily)
• Core rules (always applied):
1) Price ≥ 200-SMA
2) 10-SMA ≥ 20-SMA
3) Core pause: if price is below both 10 & 20 while still above 200 → PAUSE
• Optional context pauses (only if “Apply context pauses” = ON):
– September: Price > 200 and (10 or 20 above price) → PAUSE
– Short week: Price > 200 and Price > 20 and (10 above price) → PAUSE
– Short week + Mon/Fri holiday + late-week major event and price above both 10 & 20 → PAUSE
If “Apply context pauses” is OFF, context rows are informational only and do not change the decision.
What you see on the chart
• Background tint: green = READY, red = PAUSED (by default, only on Mondays).
• Status bubble (last bar): shows “GOOD TO GO” or “PAUSED” on Mondays.
• PCS weekly reference line (strike helper):
– Level = Monday open − offset (default 30 pts; adjustable; optional rounding).
– Current week: orange = GOOD TO GO, gray = PAUSED; appears at start of Monday’s bar and extends through the week.
– Past weeks: green = win (Friday close ≥ that week’s level), red = loss, purple = skipped by core rules.
• SMA plots: optional 10/20/200 with fill between 10 & 20.
Readiness table (top-right by default)
Two columns: Check / Now (✓ or ✗). Rows: Price ≥ 200-SMA; 10-SMA ≥ 20-SMA; Price ≥ 10-SMA; Price ≥ 20-SMA; any enabled context rows; Core READY; Core PAUSE (price < 10 & 20 while >200); Final decision; optional Weekly PCS level.
Inputs (what to tweak)
• Source, SMA 10/20/200 lengths
• Plot SMAs, Fill between 10 & 20
• Only evaluate/tint on Mondays (on by default)
• Decision timing (Strict or Mid)
• Apply context pauses (and individual context flags)
• Table position/size/padding/border
• PCS helper: show current week’s line, show previous weeks’ lines, offset (pts), rounding increment & method, start only on Mondays, show Weekly PCS level in table
How to use (quick steps)
1) Add to SPX on Daily.
2) Pick timing: Strict (no repaint) or Mid (uses Monday SMAs).
3) Optionally enable Apply context pauses and relevant context flags.
4) On Monday’s open:
– If bubble says GOOD TO GO, consider selling a 10-wide SPX PCS with short strike ~30 pts below Monday’s open (adjust offset/rounding as desired).
– If PAUSED, skip this week.
5) Hold to Friday’s close; past weeks color green/red by result; purple indicates skipped.
Notes
This indicator does not place orders. Results depend on fills, fees, slippage, and risk management. Options trading involves risk; trade responsibly.
