RAS.V2 Strength Index OscillatorHeavily modified version of my previous "Relative Aggregate Strength Oscillator" -Added high/low lines, alma curves,, lrc bands, changed candle calculations + other small things. Replaces the standard RSI indicator with something a bit more insightful.
Credits to @wolneyyy - 'Mean Deviation Detector - Throw Out All Other Indicators ' And @algomojo - 'Responsive Coppock Curve'
And the default Relative Strength Index
The candles are the average of the MFI ,CCI ,MOM and RSI candles, they seemed similar enough in style to me so I created candles out of each and the took the sum of all the candle's OHLC values and divided by 4 to get an average, same as v1 but with some tweaks. Previous Peaks and Potholes visible with the blue horizontal lines which adjust when a new boundary is established. Toggle alma waves or smalrc curves or both to your liking. This indicator is great for calling out peaks and troughs in realtime, although is best when combined with other trusted indicators to get a consensus.
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WoAlgo Premium v3.0
WoAlgo Premium v3.0 - Smart Money Analysis
Overview
** WoAlgo Premium v3.0 ** is an advanced technical analysis indicator designed for educational purposes. This tool combines Smart Money Concepts with multi-factor confluence analysis to help traders identify potential market opportunities across multiple timeframes.
The indicator integrates market structure analysis, order flow concepts, and technical momentum indicators into a comprehensive dashboard system. It is designed to assist traders in understanding institutional trading patterns and market dynamics through visual analysis tools.
### What It Does
This indicator provides:
**1. Smart Money Concepts Analysis**
- Market structure identification (Break of Structure and Change of Character patterns)
- Order block detection with volume confirmation
- Fair value gap recognition
- Liquidity zone mapping (equal highs and lows)
- Premium and discount zone calculations
**2. Multi-Factor Confluence Scoring**
The indicator calculates a proprietary confluence score (0-100) based on five key components:
- Price action analysis (30% weight)
- Volume confirmation (20% weight)
- Momentum indicators (25% weight)
- Trend strength measurement (15% weight)
- Money flow analysis (10% weight)
**3. Multi-Timeframe Analysis**
- Scans 5 different timeframes (5M, 15M, 1H, 4H, Daily)
- Calculates alignment percentage across timeframes
- Displays trend and structure status for each period
**4. Visual Dashboard System**
- Comprehensive main dashboard with 13 metrics
- Real-time screener table with 10 data columns
- Multi-timeframe scanner
- Performance tracking panel
### How It Works
**Market Structure Detection**
The indicator identifies key structural changes in price action:
- **BOS (Break of Structure)**: Indicates trend continuation when price breaks previous swing points
- **CHoCH (Change of Character)**: Signals potential trend reversal when market structure shifts
**Order Block Identification**
Order blocks are detected when:
- Significant volume appears at swing points
- Price shows strong directional movement from these levels
- Enhanced detection with extreme volume confirmation (OB++ markers)
**Fair Value Gap Recognition**
Gaps between candles are identified when:
- Price leaves inefficiencies in the market
- Three consecutive candles create a gap pattern
- Gap size exceeds minimum threshold based on ATR
**Confluence Calculation**
The system evaluates multiple technical factors:
1. **Price Position**: Relative to moving averages (EMA 20, 50, 200)
2. **Volume Analysis**: Standard deviation-based volume spikes
3. **Momentum**: RSI, MACD, Stochastic indicators
4. **Trend Strength**: ADX measurements
5. **Money Flow**: MFI indicator readings
Each factor contributes weighted points to create an overall confluence score that helps assess signal strength.
### Signal Types
**Confirmation Signals (▲ / ▼)**
Generated when:
- EMA crossovers occur (20/50 cross)
- Volume confirmation is present
- RSI is in appropriate zone
- Confluence score exceeds 50%
**Strong Signals (▲+ / ▼+)**
Higher-confidence signals requiring:
- Confluence score above 70%
- Extreme volume confirmation
- Alignment with 200 EMA trend
- MACD confirmation
- Bullish or bearish market structure
**Contrarian Signals (⚡)**
Reversal indicators appearing when:
- RSI reaches extreme levels (<30 or >70)
- Stochastic shows oversold/overbought conditions
- Price touches Bollinger Band extremes
- Potential divergence patterns emerge
**Reversal Zones**
Visual boxes highlighting areas where:
- Market structure conflicts with momentum
- High probability of directional change
- Key support/resistance levels interact
**Smart Trail**
Dynamic stop-loss indicator that:
- Adjusts based on ATR (Average True Range)
- Follows trend direction
- Updates automatically as price moves
- Provides risk management reference points
### Dashboard Components
**Main Dashboard (13 Metrics)**
1. **Confluence Score**: Current bull/bear percentage (0-100)
2. **Market Regime**: Trend classification (Strong Up/Down, Range, Squeeze)
3. **Signal Status**: Active buy/sell signal indication
4. **Structure State**: Current market structure (Bullish/Bearish/Neutral)
5. **Trend Strength**: ADX-based measurement
6. **RSI Level**: Momentum indicator with overbought/oversold zones
7. **MACD Direction**: Trend momentum confirmation
8. **Money Flow Index**: Smart money sentiment
9. **Volume Status**: Current volume relative to average
10. **Volatility Rating**: ATR percentage measurement
11. **ATR Value**: Average true range for position sizing
12. **MTF Alignment**: Multi-timeframe agreement percentage
**Screener Table (10 Columns)**
- Current symbol and timeframe
- Real-time price and percentage change
- Quality rating (star system)
- Active signal type
- Smart trail status
- Market structure state
- MACD direction
- Trend strength percentage
- Bollinger Band squeeze detection
**MTF Scanner (5 Timeframes)**
Displays for each timeframe:
- Trend direction indicator
- Market structure classification
- Visual confirmation with color coding
**Performance Metrics**
- Win rate percentage (simplified calculation)
- Total signals generated
- Current confluence score
- MTF alignment status
- Volatility level
### Settings and Customization
**Preset Styles**
Choose from predefined configurations:
- **Conservative**: Fewer, higher-quality signals
- **Moderate**: Balanced approach (recommended)
- **Aggressive**: More frequent signals
- **Scalper**: Short-term focused
- **Swing**: Longer-term oriented
- **Custom**: Full manual control
**Smart Money Concepts Controls**
- Toggle each feature independently
- Adjust swing length (3-50 periods)
- Enable/disable internal structure
- Control order block display
- Manage breaker block visibility
- Show/hide fair value gaps
- Display liquidity zones
- Premium/discount zone visualization
**Signal Configuration**
- Enable/disable confirmation signals
- Toggle strong signal markers
- Control contrarian signal display
- Show/hide reversal zones
- Smart trail activation
- Sensitivity adjustment (5-50)
**Visual Customization**
- Moving average display options
- MA period adjustments (Fast: 20, Slow: 50, Trend: 200)
- Support/resistance line toggle
- Dynamic S/R lookback period
- Candle coloring based on trend
- Color scheme customization
- Dashboard size options (Small/Normal/Large)
- Position placement (4 corners)
### How to Use
**Step 1: Initial Setup**
1. Add indicator to chart
2. Select appropriate preset or use Custom
3. Adjust timeframe to match trading style
4. Configure dashboard visibility preferences
**Step 2: Analysis Workflow**
1. Check MTF Scanner for timeframe alignment
2. Review Main Dashboard confluence score
3. Observe Market Regime classification
4. Identify active signals on chart
5. Confirm with Smart Money Concepts (order blocks, FVG, structure)
**Step 3: Trade Consideration**
Strong signals (▲+ / ▼+) require:
- Confluence score >70%
- MTF alignment >60%
- Confirmation from multiple dashboard metrics
- Support from Smart Money Concepts
- Appropriate volume levels
**Step 4: Risk Management**
- Use Smart Trail as dynamic stop-loss reference
- Consider ATR for position sizing
- Monitor volatility rating
- Respect support/resistance levels
- Combine with personal risk parameters
### Best Practices
**For Scalping (1M-5M timeframes)**
- Use Scalper preset
- Reduce swing length to 5-7
- Focus on strong signals only
- Monitor MTF alignment closely
- Quick entries near order blocks
**For Intraday Trading (15M-1H timeframes)**
- Use Moderate preset (recommended)
- Default swing length (10)
- Combine confirmation and strong signals
- Check MTF scanner before entry
- Use fair value gaps for entries
**For Swing Trading (4H-D timeframes)**
- Use Swing preset
- Increase swing length to 15-20
- Focus on strong signals
- Require high MTF alignment
- Patient approach with major structure levels
### Technical Specifications
**Indicators Used**
- Exponential Moving Averages (20, 50, 200)
- Hull Moving Average
- Relative Strength Index (14)
- MACD (12, 26, 9)
- Money Flow Index (14)
- Stochastic Oscillator (14, 3)
- ADX / DMI (14)
- Bollinger Bands (20, 2)
- ATR (14)
- Volume Analysis (SMA 20 with standard deviation)
**Calculation Methods**
- Swing detection using pivot high/low functions
- Volume confirmation via statistical analysis
- Multi-factor scoring with weighted components
- Dynamic support/resistance using highest/lowest functions
- Real-time MTF data via security() function
### Limitations and Considerations
**Important Notes**
1. This indicator is designed for educational and analytical purposes only
2. Historical performance does not guarantee future results
3. Signals should be confirmed with additional analysis
4. Market conditions vary and affect indicator performance
5. Not all signals will be profitable
6. Risk management is essential for all trading
**Known Limitations**
- Confluence scoring is algorithmic and not predictive
- MTF analysis requires sufficient historical data
- Effectiveness varies across different market conditions
- Sideways markets may produce conflicting signals
- High volatility can affect signal reliability
- Backtesting results shown are simplified calculations
**Not Suitable For**
- Automated trading without human oversight
- Sole basis for trading decisions
- Guaranteed profit expectations
- Inexperienced traders without proper education
- Trading without risk management plans
### Market Applicability
**Effective On**
- Trending markets (any direction)
- Clear structure formation periods
- Liquid instruments with consistent volume
- Multiple asset classes (forex, stocks, crypto, commodities)
- Various timeframes with appropriate settings
**Less Effective During**
- Extended ranging/choppy conditions
- Extremely low volume periods
- Major news events causing gaps
- Early market open with high spread
- Illiquid instruments with erratic price action
### Risk Disclaimer
**⚠️ IMPORTANT NOTICE**
This indicator is provided for **educational and informational purposes only**. It does not constitute financial advice, investment recommendations, or trading signals.
**Key Risk Factors:**
- Trading financial instruments involves substantial risk of loss
- Past performance does not indicate future results
- No indicator can predict market movements with certainty
- Users should conduct independent research and analysis
- Professional financial advice should be sought when appropriate
- Risk management and position sizing are critical to successful trading
- Users are solely responsible for their trading decisions
**Responsible Usage:**
- Combine with comprehensive market analysis
- Use appropriate stop-loss orders
- Never risk more than you can afford to lose
- Maintain realistic expectations
- Continue education on technical analysis principles
- Test thoroughly on demo accounts before live trading
- Understand all indicator features before using
### Educational Resources
**Understanding Smart Money Concepts**
Smart Money Concepts analyze how institutional traders and large market participants operate. Key principles include:
- Institutional order flow patterns
- Market structure changes
- Liquidity manipulation
- Supply and demand imbalances
- Order block formations
**Multi-Timeframe Analysis Theory**
Analyzing multiple timeframes helps:
- Identify overall market direction
- Improve entry timing
- Confirm trend strength
- Recognize consolidation periods
- Reduce conflicting signals
**Confluence Trading Approach**
Using multiple confirming factors:
- Increases signal reliability
- Reduces false signals
- Provides conviction for trades
- Helps with position sizing
- Improves risk-reward ratios
### Version History
**v3.0 (Current)**
- Multi-factor confluence scoring system
- Complete Smart Money Concepts implementation
- Real-time multi-timeframe analysis
- Four professional dashboard panels
- Enhanced order block detection
- Breaker block identification
- Premium/discount zone calculations
- Smart trail stop-loss system
- Customizable preset configurations
- Performance tracking metrics
**Development Philosophy**
This indicator was developed with focus on:
- Educational value for traders
- Transparent methodology
- Comprehensive feature set
- User-friendly interface
- Flexible customization options
### Technical Support
**For Questions About:**
- Indicator functionality
- Parameter optimization
- Signal interpretation
- Dashboard metrics
- Best practice recommendations
Please use TradingView's comment section below. The developer monitors comments and provides assistance to users learning to use the indicator effectively.
### Acknowledgments
This indicator implements concepts from:
- Smart Money Concepts trading methodology
- Multi-timeframe analysis techniques
- Technical indicator theory
- Market structure analysis principles
- Institutional order flow concepts
All implementations are original code and calculations based on established technical analysis principles.
---
## ADDITIONAL INFORMATION SECTION
**Category**: Indicators
**Type**: Market Structure / Multi-Timeframe Analysis
**Complexity**: Intermediate to Advanced
**Open Source**: Code visible for transparency and education
**Pine Script Version**: v6
**Chart Overlay**: Yes
**Maximum Objects**: 500 boxes, 500 lines, 500 labels
Bifurcation Zone - CAEBifurcation Zone — Cognitive Adversarial Engine (BZ-CAE)
Bifurcation Zone — CAE (BZ-CAE) is a next-generation divergence detection system enhanced by a Cognitive Adversarial Engine that evaluates both sides of every potential trade before presenting signals. Unlike traditional divergence indicators that show every price-oscillator disagreement regardless of context, BZ-CAE applies comprehensive market-state intelligence to identify only the divergences that occur in favorable conditions with genuine probability edges.
The system identifies structural bifurcation points — critical junctures where price and momentum disagree, signaling potential reversals or continuations — then validates these opportunities through five interconnected intelligence layers: Trend Conviction Scoring , Directional Momentum Alignment , Multi-Factor Exhaustion Modeling , Adversarial Validation , and Confidence Scoring . The result is a selective, context-aware signal system that filters noise and highlights high-probability setups.
This is not a "buy the arrow" indicator. It's a decision support framework that teaches you how to read market state, evaluate divergence quality, and make informed trading decisions based on quantified intelligence rather than hope.
What Sets BZ-CAE Apart: Technical Architecture
The Problem With Traditional Divergence Indicators
Most divergence indicators operate on a simple rule: if price makes a higher high and RSI makes a lower high, show a bearish signal. If price makes a lower low and RSI makes a higher low, show a bullish signal. This creates several critical problems:
Context Blindness : They show counter-trend signals in powerful trends that rarely reverse, leading to repeated losses as you fade momentum.
Signal Spam : Every minor price-oscillator disagreement generates an alert, overwhelming you with low-quality setups and creating analysis paralysis.
No Quality Ranking : All signals are treated identically. A marginal divergence in choppy conditions receives the same visual treatment as a high-conviction setup at a major exhaustion point.
Single-Sided Evaluation : They ask "Is this a good long?" without checking if the short case is overwhelmingly stronger, leading you into obvious bad trades.
Static Configuration : You manually choose RSI 14 or Stochastic 14 and hope it works, with no systematic way to validate if that's optimal for your instrument.
BZ-CAE's Solution: Cognitive Adversarial Intelligence
BZ-CAE solves these problems through an integrated five-layer intelligence architecture:
1. Trend Conviction Score (TCS) — 0 to 1 Scale
Most indicators check if ADX is above 25 to determine "trending" conditions. This binary approach misses nuance. TCS is a weighted composite metric:
Formula : 0.35 × normalize(ADX, 10, 35) + 0.35 × structural_strength + 0.30 × htf_alignment
Structural Strength : 10-bar SMA of consecutive directional bars. Captures persistence — are bulls or bears consistently winning?
HTF Alignment : Multi-timeframe EMA stacking (20/50/100/200). When all EMAs align in the same direction, you're in institutional trend territory.
Purpose : Quantifies how "locked in" the trend is. When TCS exceeds your threshold (default 0.80), the system knows to avoid counter-trend trades unless other factors override.
Interpretation :
TCS > 0.85: Very strong trend — counter-trading is extremely high risk
TCS 0.70-0.85: Strong trend — favor continuation, require exhaustion for reversals
TCS 0.50-0.70: Moderate trend — context matters, both directions viable
TCS < 0.50: Weak/choppy — reversals more viable, range-bound conditions
2. Directional Momentum Alignment (DMA) — ATR-Normalized
Formula : (EMA21 - EMA55) / ATR14
This isn't just "price above EMA" — it's a regime-aware momentum gauge. The same $100 price movement reads completely differently in high-volatility crypto versus low-volatility forex. By normalizing with ATR, DMA adapts its interpretation to current market conditions.
Purpose : Quantifies the directional "force" behind current price action. Positive = bullish push, negative = bearish push. Magnitude = strength.
Interpretation :
DMA > 0.7: Strong bullish momentum — bearish divergences risky
DMA 0.3 to 0.7: Moderate bullish bias
DMA -0.3 to 0.3: Balanced/choppy conditions
DMA -0.7 to -0.3: Moderate bearish bias
DMA < -0.7: Strong bearish momentum — bullish divergences risky
3. Multi-Factor Exhaustion Modeling — 0 to 1 Probability
Single-metric exhaustion detection (like "RSI > 80") misses complex market states. BZ-CAE aggregates five independent exhaustion signals:
Volume Spikes : Current volume versus 50-bar average
2.5x average: 0.25 weight
2.0x average: 0.15 weight
1.5x average: 0.10 weight
Divergence Present : The fact that a divergence exists contributes 0.30 weight — structural momentum disagreement is itself an exhaustion signal.
RSI Extremes : Captures oscillator climax zones
RSI > 80 or < 20: 0.25 weight
RSI > 75 or < 25: 0.15 weight
Pin Bar Detection : Identifies rejection candles (2:1 wick-to-body ratio, indicating failed breakout attempts): 0.15 weight
Extended Runs : Consecutive bars above/below EMA20 without pullback
30+ bars: 0.15 weight (market hasn't paused to consolidate)
Total exhaustion score is the sum of all applicable weights, capped at 1.0.
Purpose : Detects when strong trends become vulnerable to reversal. High exhaustion can override trend filters, allowing counter-trend trades at genuine turning points that basic indicators would miss.
Interpretation :
Exhaustion > 0.75: High probability of climax — yellow background shading alerts you visually
Exhaustion 0.50-0.75: Moderate overextension — watch for confirmation
Exhaustion < 0.50: Fresh move — trend can continue, counter-trend trades higher risk
4. Adversarial Validation — Game Theory Applied to Trading
This is BZ-CAE's signature innovation. Before approving any signal, the engine quantifies BOTH sides of the trade simultaneously:
For Bullish Divergences , it calculates:
Bull Case Score (0-1+) :
Distance below EMA20 (pullback quality): up to 0.25
Bullish EMA alignment (close > EMA20 > EMA50): 0.25
Oversold RSI (< 40): 0.25
Volume confirmation (> 1.2x average): 0.25
Bear Case Score (0-1+) :
Price below EMA50 (structural weakness): 0.30
Very oversold RSI (< 30, indicating knife-catching): 0.20
Differential = Bull Case - Bear Case
If differential < -0.10 (default threshold), the bear case is dominating — signal is BLOCKED or ANNOTATED.
For Bearish Divergences , the logic inverts (Bear Case vs Bull Case).
Purpose : Prevents trades where you're fighting obvious strength in the opposite direction. This is institutional-grade risk management — don't just evaluate your trade, evaluate the counter-trade simultaneously.
Why This Matters : You might see a bullish divergence at a local low, but if price is deeply below major support EMAs with strong bearish momentum, you're catching a falling knife. The adversarial check catches this and blocks the signal.
5. Confidence Scoring — 0 to 1 Quality Assessment
Every signal that passes initial filters receives a comprehensive quality score:
Formula :
0.30 × normalize(TCS) // Trend context
+ 0.25 × normalize(|DMA|) // Momentum magnitude
+ 0.20 × pullback_quality // Entry distance from EMA20
+ 0.15 × state_quality // ADX + alignment + structure
+ 0.10 × divergence_strength // Slope separation magnitude
+ adversarial_bonus (0-0.30) // Your side's advantage
Purpose : Ranks setup quality for filtering and position sizing decisions. You can set a minimum confidence threshold (default 0.35) to ensure only quality setups reach your chart.
Interpretation :
Confidence > 0.70: Premium setup — consider increased position size
Confidence 0.50-0.70: Good quality — standard size
Confidence 0.35-0.50: Acceptable — reduced size or skip if conservative
Confidence < 0.35: Marginal — blocked in Filtering mode, annotated in Advisory mode
CAE Operating Modes: Learning vs Enforcement
Off : Disables all CAE logic. Raw divergence pipeline only. Use for baseline comparison.
Advisory : Shows ALL signals regardless of CAE evaluation, but annotates signals that WOULD be blocked with specific warnings (e.g., "Bull: strong downtrend (TCS=0.87)" or "Adversarial bearish"). This is your learning mode — see CAE's decision logic in action without missing educational opportunities.
Filtering : Actively blocks low-quality signals. Only setups that pass all enabled gates (Trend Filter, Adversarial Validation, Confidence Gating) reach your chart. This is your live trading mode — trust the system to enforce discipline.
CAE Filter Gates: Three-Layer Protection
When CAE is enabled, signals must pass through three independent gates (each can be toggled on/off):
Gate 1: Strong Trend Filter
If TCS ≥ tcs_threshold (default 0.80)
And signal is counter-trend (bullish in downtrend or bearish in uptrend)
And exhaustion < exhaustion_required (default 0.50)
Then: BLOCK signal
Logic: Don't fade strong trends unless the move is clearly overextended
Gate 2: Adversarial Validation
Calculate both bull case and bear case scores
If opposing case dominates by more than adv_threshold (default 0.10)
Then: BLOCK signal
Logic: Avoid trades where you're fighting obvious strength in the opposite direction
Gate 3: Confidence Gating
Calculate composite confidence score (0-1)
If confidence < min_confidence (default 0.35)
Then: In Filtering mode, BLOCK signal; in Advisory mode, ANNOTATE with warning
Logic: Only take setups with minimum quality threshold
All three gates work together. A signal must pass ALL enabled gates to fire.
Visual Intelligence System
Bifurcation Zones (Supply/Demand Blocks)
When a divergence signal fires, BZ-CAE draws a semi-transparent box extending 15 bars forward from the signal pivot:
Demand Zones (Bullish) : Theme-colored box (cyan in Cyberpunk, blue in Professional, etc.) labeled "Demand" — marks where smart money likely placed buy orders as price diverged at the low.
Supply Zones (Bearish) : Theme-colored box (magenta in Cyberpunk, orange in Professional) labeled "Supply" — marks where smart money likely placed sell orders as price diverged at the high.
Theory : Divergences represent institutional disagreement with the crowd. The crowd pushed price to an extreme (new high or low), but momentum (oscillator) is waning, indicating smart money is taking the opposite side. These zones mark order placement areas that become future support/resistance.
Use Cases :
Exit targets: Take profit when price returns to opposite-side zone
Re-entry levels: If price returns to your entry zone, consider adding
Stop placement: Place stops just beyond your zone (below demand, above supply)
Auto-Cleanup : System keeps the last 20 zones to prevent chart clutter.
Adversarial Bar Coloring — Real-Time Market Debate Heatmap
Each bar is colored based on the Bull Case vs Bear Case differential:
Strong Bull Advantage (diff > 0.3): Full theme bull color (e.g., cyan)
Moderate Bull Advantage (diff > 0.1): 50% transparency bull
Neutral (diff -0.1 to 0.1): Gray/neutral theme
Moderate Bear Advantage (diff < -0.1): 50% transparency bear
Strong Bear Advantage (diff < -0.3): Full theme bear color (e.g., magenta)
This creates a real-time visual heatmap showing which side is "winning" the market debate. When bars flip from cyan to magenta (or vice versa), you're witnessing a shift in adversarial advantage — a leading indicator of potential momentum changes.
Exhaustion Shading
When exhaustion score exceeds 0.75, the chart background displays a semi-transparent yellow highlight. This immediate visual warning alerts you that the current move is at high risk of reversal, even if trend indicators remain strong.
Visual Themes — Six Aesthetic Options
Cyberpunk : Cyan/Magenta/Yellow — High contrast, neon aesthetic, excellent for dark-themed trading environments
Professional : Blue/Orange/Green — Corporate color palette, suitable for presentations and professional documentation
Ocean : Teal/Red/Cyan — Aquatic palette, calming for extended monitoring sessions
Fire : Orange/Red/Coral — Warm aggressive colors, high energy
Matrix : Green/Red/Lime — Code aesthetic, homage to classic hacker visuals
Monochrome : White/Gray — Minimal distraction, maximum focus on price action
All visual elements (signal markers, zones, bar colors, dashboard) adapt to your selected theme.
Divergence Engine — Core Detection System
What Are Divergences?
Divergences occur when price action and momentum indicators disagree, creating structural tension that often resolves in a change of direction:
Regular Divergence (Reversal Signal) :
Bearish Regular : Price makes higher high, oscillator makes lower high → Potential trend reversal down
Bullish Regular : Price makes lower low, oscillator makes higher low → Potential trend reversal up
Hidden Divergence (Continuation Signal) :
Bearish Hidden : Price makes lower high, oscillator makes higher high → Downtrend continuation
Bullish Hidden : Price makes higher low, oscillator makes lower low → Uptrend continuation
Both types can be enabled/disabled independently in settings.
Pivot Detection Methods
BZ-CAE uses symmetric pivot detection with separate lookback and lookforward periods (default 5/5):
Pivot High : Bar where high > all highs within lookback range AND high > all highs within lookforward range
Pivot Low : Bar where low < all lows within lookback range AND low < all lows within lookforward range
This ensures structural validity — the pivot must be a clear local extreme, not just a minor wiggle.
Divergence Validation Requirements
For a divergence to be confirmed, it must satisfy:
Slope Disagreement : Price slope and oscillator slope must move in opposite directions (for regular divs) or same direction with inverted highs/lows (for hidden divs)
Minimum Slope Change : |osc_slope| > min_slope_change / 100 (default 1.0) — filters weak, marginal divergences
Maximum Lookback Range : Pivots must be within max_lookback bars (default 60) — prevents ancient, irrelevant divergences
ATR-Normalized Strength : Divergence strength = min(|price_slope| × |osc_slope| × 10, 1.0) — quantifies the magnitude of disagreement in volatility context
Regular divergences receive 1.0× weight; hidden divergences receive 0.8× weight (slightly less reliable historically).
Oscillator Options — Five Professional Indicators
RSI (Relative Strength Index) : Classic overbought/oversold momentum indicator. Best for: General purpose divergence detection across all instruments.
Stochastic : Range-bound %K momentum comparing close to high-low range. Best for: Mean reversion strategies and range-bound markets.
CCI (Commodity Channel Index) : Measures deviation from statistical mean, auto-normalized to 0-100 scale. Best for: Cyclical instruments and commodities.
MFI (Money Flow Index) : Volume-weighted RSI incorporating money flow. Best for: Volume-driven markets like stocks and crypto.
Williams %R : Inverse stochastic looking back over period, auto-adjusted to 0-100. Best for: Reversal detection at extremes.
Each oscillator has adjustable length (2-200, default 14) and smoothing (1-20, default 1). You also set overbought (50-100, default 70) and oversold (0-50, default 30) thresholds.
Signal Timing Modes — Understanding Repainting
BZ-CAE offers two timing policies with complete transparency about repainting behavior:
Realtime (1-bar, peak-anchored)
How It Works :
Detects peaks 1 bar ago using pattern: high > high AND high > high
Signal prints on the NEXT bar after peak detection (bar_index)
Visual marker anchors to the actual PEAK bar (bar_index - 1, offset -1)
Signal locks in when bar CONFIRMS (closes)
Repainting Behavior :
On the FORMING bar (before close), the peak condition may change as new prices arrive
Once bar CLOSES (barstate.isconfirmed), signal is locked permanently
This is preview/early warning behavior by design
Best For :
Active monitoring and immediate alerts
Learning the system (seeing signals develop in real-time)
Responsive entry if you're watching the chart live
Confirmed (lookforward)
How It Works :
Uses Pine Script's built-in ta.pivothigh() and ta.pivotlow() functions
Requires full pivot validation period (lookback + lookforward bars)
Signal prints pivot_lookforward bars after the actual peak (default 5-bar delay)
Visual marker anchors to the actual peak bar (offset -pivot_lookforward)
No Repainting Behavior
Best For :
Backtesting and historical analysis
Conservative entries requiring full confirmation
Automated trading systems
Swing trading with larger timeframes
Tradeoff :
Delayed entry by pivot_lookforward bars (typically 5 bars)
On a 5-minute chart, this is a 25-minute delay
On a 4-hour chart, this is a 20-hour delay
Recommendation : Use Confirmed for backtesting to verify system performance honestly. Use Realtime for live monitoring only if you're actively watching the chart and understand pre-confirmation repainting behavior.
Signal Spacing System — Anti-Spam Architecture
Even after CAE filtering, raw divergences can cluster. The spacing system enforces separation:
Three Independent Filters
1. Min Bars Between ANY Signals (default 12):
Prevents rapid-fire clustering across both directions
If last signal (bull or bear) was within N bars, block new signal
Ensures breathing room between all setups
2. Min Bars Between SAME-SIDE Signals (default 24, optional enforcement):
Prevents bull-bull or bear-bear spam
Separate tracking for bullish and bearish signal timelines
Toggle enforcement on/off
3. Min ATR Distance From Last Signal (default 0, optional):
Requires price to move N × ATR from last signal location
Ensures meaningful price movement between setups
0 = disabled, 0.5-2.0 = typical range for enabled
All three filters work independently. A signal must pass ALL enabled filters to proceed.
Practical Guidance :
Scalping (1-5m) : Any 6-10, Same-side 12-20, ATR 0-0.5
Day Trading (15m-1H) : Any 12, Same-side 24, ATR 0-1.0
Swing Trading (4H-D) : Any 20-30, Same-side 40-60, ATR 1.0-2.0
Dashboard — Real-Time Control Center
The dashboard (toggleable, four corner positions, three sizes) provides comprehensive system intelligence:
Oscillator Section
Current oscillator type and value
State: OVERBOUGHT / OVERSOLD / NEUTRAL (color-coded)
Length parameter
Cognitive Engine Section
TCS (Trend Conviction Score) :
Current value with emoji state indicator
🔥 = Strong trend (>0.75)
📊 = Moderate trend (0.50-0.75)
〰️ = Weak/choppy (<0.50)
Color: Red if above threshold (trend filter active), yellow if moderate, green if weak
DMA (Directional Momentum Alignment) :
Current value with emoji direction indicator
🐂 = Bullish momentum (>0.5)
⚖️ = Balanced (-0.5 to 0.5)
🐻 = Bearish momentum (<-0.5)
Color: Green if bullish, red if bearish
Exhaustion :
Current value with emoji warning indicator
⚠️ = High exhaustion (>0.75)
🟡 = Moderate (0.50-0.75)
✓ = Low (<0.50)
Color: Red if high, yellow if moderate, green if low
Pullback :
Quality of current distance from EMA20
Values >0.6 are ideal entry zones (not too close, not too far)
Bull Case / Bear Case (if Adversarial enabled):
Current scores for both sides of the market debate
Differential with emoji indicator:
📈 = Bull advantage (>0.2)
➡️ = Balanced (-0.2 to 0.2)
📉 = Bear advantage (<-0.2)
Last Signal Metrics Section (New Feature)
When a signal fires, this section captures and displays:
Signal type (BULL or BEAR)
Bars elapsed since signal
Confidence % at time of signal
TCS value at signal time
DMA value at signal time
Purpose : Provides a historical reference for learning. You can see what the market state looked like when the last signal fired, helping you correlate outcomes with conditions.
Statistics Section
Total Signals : Lifetime count across session
Blocked Signals : Count and percentage (filter effectiveness metric)
Bull Signals : Total bullish divergences
Bear Signals : Total bearish divergences
Purpose : System health monitoring. If blocked % is very high (>60%), filters may be too strict. If very low (<10%), filters may be too loose.
Advisory Annotations
When CAE Mode = Advisory, this section displays warnings for signals that would be blocked in Filtering mode:
Examples:
"Bull spacing: wait 8 bars"
"Bear: strong uptrend (TCS=0.87)"
"Adversarial bearish"
"Low confidence 32%"
Multiple warnings can stack, separated by " | ". This teaches you CAE's decision logic transparently.
How to Use BZ-CAE — Complete Workflow
Phase 1: Initial Setup (First Session)
Apply BZ-CAE to your chart
Select your preferred Visual Theme (Cyberpunk recommended for visibility)
Set Signal Timing to "Confirmed (lookforward)" for learning
Choose your Oscillator Type (RSI recommended for general use, length 14)
Set Overbought/Oversold to 70/30 (standard)
Enable both Regular Divergence and Hidden Divergence
Set Pivot Lookback/Lookforward to 5/5 (balanced structure)
Enable CAE Intelligence
Set CAE Mode to "Advisory" (learning mode)
Enable all three CAE filters: Strong Trend Filter , Adversarial Validation , Confidence Gating
Enable Show Dashboard , position Top Right, size Normal
Enable Draw Bifurcation Zones and Adversarial Bar Coloring
Phase 2: Learning Period (Weeks 1-2)
Goal : Understand how CAE evaluates market state and filters signals.
Activities :
Watch the dashboard during signals :
Note TCS values when counter-trend signals fail — this teaches you the trend strength threshold for your instrument
Observe exhaustion patterns at actual turning points — learn when overextension truly matters
Study adversarial differential at signal times — see when opposing cases dominate
Review blocked signals (orange X-crosses):
In Advisory mode, you see everything — signals that would pass AND signals that would be blocked
Check the advisory annotations to understand why CAE would block
Track outcomes: Were the blocks correct? Did those signals fail?
Use Last Signal Metrics :
After each signal, check the dashboard capture of confidence, TCS, and DMA
Journal these values alongside trade outcomes
Identify patterns: Do confidence >0.70 signals work better? Does your instrument respect TCS >0.85?
Understand your instrument's "personality" :
Trending instruments (indices, major forex) may need TCS threshold 0.85-0.90
Choppy instruments (low-cap stocks, exotic pairs) may work best with TCS 0.70-0.75
High-volatility instruments (crypto) may need wider spacing
Low-volatility instruments may need tighter spacing
Phase 3: Calibration (Weeks 3-4)
Goal : Optimize settings for your specific instrument, timeframe, and style.
Calibration Checklist :
Min Confidence Threshold :
Review confidence distribution in your signal journal
Identify the confidence level below which signals consistently fail
Set min_confidence slightly above that level
Day trading : 0.35-0.45
Swing trading : 0.40-0.55
Scalping : 0.30-0.40
TCS Threshold :
Find the TCS level where counter-trend signals consistently get stopped out
Set tcs_threshold at or slightly below that level
Trending instruments : 0.85-0.90
Mixed instruments : 0.80-0.85
Choppy instruments : 0.75-0.80
Exhaustion Override Level :
Identify exhaustion readings that marked genuine reversals
Set exhaustion_required just below the average
Typical range : 0.45-0.55
Adversarial Threshold :
Default 0.10 works for most instruments
If you find CAE is too conservative (blocking good trades), raise to 0.15-0.20
If signals are still getting caught in opposing momentum, lower to 0.07-0.09
Spacing Parameters :
Count bars between quality signals in your journal
Set min bars ANY to ~60% of that average
Set min bars SAME-SIDE to ~120% of that average
Scalping : Any 6-10, Same 12-20
Day trading : Any 12, Same 24
Swing : Any 20-30, Same 40-60
Oscillator Selection :
Try different oscillators for 1-2 weeks each
Track win rate and average winner/loser by oscillator type
RSI : Best for general use, clear OB/OS
Stochastic : Best for range-bound, mean reversion
MFI : Best for volume-driven markets
CCI : Best for cyclical instruments
Williams %R : Best for reversal detection
Phase 4: Live Deployment
Goal : Disciplined execution with proven, calibrated system.
Settings Changes :
Switch CAE Mode from Advisory to Filtering
System now actively blocks low-quality signals
Only setups passing all gates reach your chart
Keep Signal Timing on Confirmed for conservative entries
OR switch to Realtime if you're actively monitoring and want faster entries (accept pre-confirmation repaint risk)
Use your calibrated thresholds from Phase 3
Enable high-confidence alerts: "⭐ High Confidence Bullish/Bearish" (>0.70)
Trading Discipline Rules :
Respect Blocked Signals :
If CAE blocks a trade you wanted to take, TRUST THE SYSTEM
Don't manually override — if you consistently disagree, return to Phase 2/3 calibration
The block exists because market state failed intelligence checks
Confidence-Based Position Sizing :
Confidence >0.70: Standard or increased size (e.g., 1.5-2.0% risk)
Confidence 0.50-0.70: Standard size (e.g., 1.0% risk)
Confidence 0.35-0.50: Reduced size (e.g., 0.5% risk) or skip if conservative
TCS-Based Management :
High TCS + counter-trend signal: Use tight stops, quick exits (you're fading momentum)
Low TCS + reversal signal: Use wider stops, trail aggressively (genuine reversal potential)
Exhaustion Awareness :
Exhaustion >0.75 (yellow shading): Market is overextended, reversal risk is elevated — consider early exit or tighter trailing stops even on winning trades
Exhaustion <0.30: Continuation bias — hold for larger move, wide trailing stops
Adversarial Context :
Strong differential against you (e.g., bullish signal with bear diff <-0.2): Use very tight stops, consider skipping
Strong differential with you (e.g., bullish signal with bull diff >0.2): Trail aggressively, this is your tailwind
Practical Settings by Timeframe & Style
Scalping (1-5 Minute Charts)
Objective : High frequency, tight stops, quick reversals in fast-moving markets.
Oscillator :
Type: RSI or Stochastic (fast response to quick moves)
Length: 9-11 (more responsive than standard 14)
Smoothing: 1 (no lag)
OB/OS: 65/35 (looser thresholds ensure frequent crossings in fast conditions)
Divergence :
Pivot Lookback/Lookforward: 3/3 (tight structure, catch small swings)
Max Lookback: 40-50 bars (recent structure only)
Min Slope Change: 0.8-1.0 (don't be overly strict)
CAE :
Mode: Advisory first (learn), then Filtering
Min Confidence: 0.30-0.35 (lower bar for speed, accept more signals)
TCS Threshold: 0.70-0.75 (allow more counter-trend opportunities)
Exhaustion Required: 0.45-0.50 (moderate override)
Strong Trend Filter: ON (still respect major intraday trends)
Adversarial: ON (critical for scalping protection — catches bad entries quickly)
Spacing :
Min Bars ANY: 6-10 (fast pace, many setups)
Min Bars SAME-SIDE: 12-20 (prevent clustering)
Min ATR Distance: 0 or 0.5 (loose)
Timing : Realtime (speed over precision, but understand repaint risk)
Visuals :
Signal Size: Tiny (chart clarity in busy conditions)
Show Zones: Optional (can clutter on low timeframes)
Bar Coloring: ON (helps read momentum shifts quickly)
Dashboard: Small size (corner reference, not main focus)
Key Consideration : Scalping generates noise. Even with CAE, expect lower win rate (45-55%) but aim for favorable R:R (2:1 or better). Size conservatively.
Day Trading (15-Minute to 1-Hour Charts)
Objective : Balance quality and frequency. Standard divergence trading approach.
Oscillator :
Type: RSI or MFI (proven reliability, volume confirmation with MFI)
Length: 14 (industry standard, well-studied)
Smoothing: 1-2
OB/OS: 70/30 (classic levels)
Divergence :
Pivot Lookback/Lookforward: 5/5 (balanced structure)
Max Lookback: 60 bars
Min Slope Change: 1.0 (standard strictness)
CAE :
Mode: Filtering (enforce discipline from the start after brief Advisory learning)
Min Confidence: 0.35-0.45 (quality filter without being too restrictive)
TCS Threshold: 0.80-0.85 (respect strong trends)
Exhaustion Required: 0.50 (balanced override threshold)
Strong Trend Filter: ON
Adversarial: ON
Confidence Gating: ON (all three filters active)
Spacing :
Min Bars ANY: 12 (breathing room between all setups)
Min Bars SAME-SIDE: 24 (prevent bull/bear clusters)
Min ATR Distance: 0-1.0 (optional refinement, typically 0.5-1.0)
Timing : Confirmed (1-bar delay for reliability, no repainting)
Visuals :
Signal Size: Tiny or Small
Show Zones: ON (useful reference for exits/re-entries)
Bar Coloring: ON (context awareness)
Dashboard: Normal size (full visibility)
Key Consideration : This is the "sweet spot" timeframe for BZ-CAE. Market structure is clear, CAE has sufficient data, and signal frequency is manageable. Expect 55-65% win rate with proper execution.
Swing Trading (4-Hour to Daily Charts)
Objective : Quality over quantity. High conviction only. Larger stops and targets.
Oscillator :
Type: RSI or CCI (robust on higher timeframes, smooth longer waves)
Length: 14-21 (capture larger momentum swings)
Smoothing: 1-3
OB/OS: 70/30 or 75/25 (strict extremes)
Divergence :
Pivot Lookback/Lookforward: 5/5 or 7/7 (structural purity, major swings only)
Max Lookback: 80-100 bars (broader historical context)
Min Slope Change: 1.2-1.5 (require strong, undeniable divergence)
CAE :
Mode: Filtering (strict enforcement, premium setups only)
Min Confidence: 0.40-0.55 (high bar for entry)
TCS Threshold: 0.85-0.95 (very strong trend protection — don't fade established HTF trends)
Exhaustion Required: 0.50-0.60 (higher bar for override — only extreme exhaustion justifies counter-trend)
Strong Trend Filter: ON (critical on HTF)
Adversarial: ON (avoid obvious bad trades)
Confidence Gating: ON (quality gate essential)
Spacing :
Min Bars ANY: 20-30 (substantial separation)
Min Bars SAME-SIDE: 40-60 (significant breathing room)
Min ATR Distance: 1.0-2.0 (require meaningful price movement)
Timing : Confirmed (purity over speed, zero repaint for swing accuracy)
Visuals :
Signal Size: Small or Normal (clear markers on zoomed-out view)
Show Zones: ON (important HTF levels)
Bar Coloring: ON (long-term trend awareness)
Dashboard: Normal or Large (comprehensive analysis)
Key Consideration : Swing signals are rare but powerful. Expect 2-5 signals per month per instrument. Win rate should be 60-70%+ due to stringent filtering. Position size can be larger given confidence.
Dashboard Interpretation Reference
TCS (Trend Conviction Score) States
0.00-0.50: Weak/Choppy
Emoji: 〰️
Color: Green/cyan
Meaning: No established trend. Range-bound or consolidating. Both reversal and continuation signals viable.
Action: Reversals (regular divs) are safer. Use wider profit targets (market has room to move). Consider mean reversion strategies.
0.50-0.75: Moderate Trend
Emoji: 📊
Color: Yellow/neutral
Meaning: Developing trend but not locked in. Context matters significantly.
Action: Check DMA and exhaustion. If DMA confirms trend and exhaustion is low, favor continuation (hidden divs). If exhaustion is high, reversals are viable.
0.75-0.85: Strong Trend
Emoji: 🔥
Color: Orange/warning
Meaning: Well-established trend with persistence. Counter-trend is high risk.
Action: Require exhaustion >0.50 for counter-trend entries. Favor continuation signals. Use tight stops on counter-trend attempts.
0.85-1.00: Very Strong Trend
Emoji: 🔥🔥
Color: Red/danger (if counter-trading)
Meaning: Locked-in institutional trend. Extremely high risk to fade.
Action: Avoid counter-trend unless exhaustion >0.75 (yellow shading). Focus exclusively on continuation opportunities. Momentum is king here.
DMA (Directional Momentum Alignment) Zones
-2.0 to -1.0: Strong Bearish Momentum
Emoji: 🐻🐻
Color: Dark red
Meaning: Powerful downside force. Sellers are in control.
Action: Bullish divergences are counter-momentum (high risk). Bearish divergences are with-momentum (lower risk). Size down on longs.
-0.5 to 0.5: Neutral/Balanced
Emoji: ⚖️
Color: Gray/neutral
Meaning: No strong directional bias. Choppy or consolidating.
Action: Both directions have similar probability. Focus on confidence score and adversarial differential for edge.
1.0 to 2.0: Strong Bullish Momentum
Emoji: 🐂🐂
Color: Bright green/cyan
Meaning: Powerful upside force. Buyers are in control.
Action: Bearish divergences are counter-momentum (high risk). Bullish divergences are with-momentum (lower risk). Size down on shorts.
Exhaustion States
0.00-0.50: Fresh Move
Emoji: ✓
Color: Green
Meaning: Trend is healthy, not overextended. Room to run.
Action: Counter-trend trades are premature. Favor continuation. Hold winners for larger moves. Avoid early exits.
0.50-0.75: Mature Move
Emoji: 🟡
Color: Yellow
Meaning: Move is aging. Watch for signs of climax.
Action: Tighten trailing stops on winning trades. Be ready for reversals. Don't add to positions aggressively.
0.75-0.85: High Exhaustion
Emoji: ⚠️
Color: Orange
Background: Yellow shading appears
Meaning: Move is overextended. Reversal risk elevated significantly.
Action: Counter-trend reversals are higher probability. Consider early exits on with-trend positions. Size up on reversal divergences (if CAE allows).
0.85-1.00: Critical Exhaustion
Emoji: ⚠️⚠️
Color: Red
Background: Yellow shading intensifies
Meaning: Climax conditions. Reversal imminent or underway.
Action: Aggressive reversal trades justified. Exit all with-trend positions. This is where major turns occur.
Confidence Score Tiers
0.00-0.30: Low Quality
Color: Red
Status: Blocked in Filtering mode
Action: Skip entirely. Setup lacks fundamental quality across multiple factors.
0.30-0.50: Moderate Quality
Color: Yellow/orange
Status: Marginal — passes in Filtering only if >min_confidence
Action: Reduced position size (0.5-0.75% risk). Tight stops. Conservative profit targets. Skip if you're selective.
0.50-0.70: High Quality
Color: Green/cyan
Status: Good setup across most quality factors
Action: Standard position size (1.0-1.5% risk). Normal stops and targets. This is your bread-and-butter trade.
0.70-1.00: Premium Quality
Color: Bright green/gold
Status: Exceptional setup — all factors aligned
Visual: Double confidence ring appears
Action: Consider increased position size (1.5-2.0% risk, maximum). Wider stops. Larger targets. High probability of success. These are rare — capitalize when they appear.
Adversarial Differential Interpretation
Bull Differential > 0.3 :
Visual: Strong cyan/green bar colors
Meaning: Bull case strongly dominates. Buyers have clear advantage.
Action: Bullish divergences favored (with-advantage). Bearish divergences face headwind (reduce size or skip). Momentum is bullish.
Bull Differential 0.1 to 0.3 :
Visual: Moderate cyan/green transparency
Meaning: Moderate bull advantage. Buyers have edge but not overwhelming.
Action: Both directions viable. Slight bias toward longs.
Differential -0.1 to 0.1 :
Visual: Gray/neutral bars
Meaning: Balanced debate. No clear advantage either side.
Action: Rely on other factors (confidence, TCS, exhaustion) for direction. Adversarial is neutral.
Bear Differential -0.3 to -0.1 :
Visual: Moderate red/magenta transparency
Meaning: Moderate bear advantage. Sellers have edge but not overwhelming.
Action: Both directions viable. Slight bias toward shorts.
Bear Differential < -0.3 :
Visual: Strong red/magenta bar colors
Meaning: Bear case strongly dominates. Sellers have clear advantage.
Action: Bearish divergences favored (with-advantage). Bullish divergences face headwind (reduce size or skip). Momentum is bearish.
Last Signal Metrics — Post-Trade Analysis
After a signal fires, dashboard captures:
Type : BULL or BEAR
Bars Ago : How long since signal (updates every bar)
Confidence : What was the quality score at signal time
TCS : What was trend conviction at signal time
DMA : What was momentum alignment at signal time
Use Case : Post-trade journaling and learning.
Example: "BULL signal 12 bars ago. Confidence: 68%, TCS: 0.42, DMA: -0.85"
Analysis : This was a bullish reversal (regular div) with good confidence, weak trend (TCS), but strong bearish momentum (DMA). The bet was that momentum would reverse — a counter-momentum play requiring exhaustion confirmation. Check if exhaustion was high at that time to justify the entry.
Track patterns:
Do your best trades have confidence >0.65?
Do low-TCS signals (<0.50) work better for you?
Are you more successful with-momentum (DMA aligned with signal) or counter-momentum?
Troubleshooting Guide
Problem: No Signals Appearing
Symptoms : Chart loads, dashboard shows metrics, but no divergence signals fire.
Diagnosis Checklist :
Check dashboard oscillator value : Is it crossing OB/OS levels (70/30)? If oscillator stays in 40-60 range constantly, it can't reach extremes needed for divergence detection.
Are pivots forming? : Look for local swing highs/lows on your chart. If price is in tight consolidation, pivots may not meet lookback/lookforward requirements.
Is spacing too tight? : Check "Last Signal" metrics — how many bars since last signal? If <12 and your min_bars_ANY is 12, spacing filter is blocking.
Is CAE blocking everything? : Check dashboard Statistics section — what's the blocked signal count? High blocks indicate overly strict filters.
Solutions :
Loosen OB/OS Temporarily :
Try 65/35 to verify divergence detection works
If signals appear, the issue was threshold strictness
Gradually tighten back to 67/33, then 70/30 as appropriate
Lower Min Confidence :
Try 0.25-0.30 (diagnostic level)
If signals appear, filter was too strict
Raise gradually to find sweet spot (0.35-0.45 typical)
Disable Strong Trend Filter Temporarily :
Turn off in CAE settings
If signals appear, TCS threshold was blocking everything
Re-enable and lower TCS_threshold to 0.70-0.75
Reduce Min Slope Change :
Try 0.7-0.8 (from default 1.0)
Allows weaker divergences through
Helpful on low-volatility instruments
Widen Spacing :
Set min_bars_ANY to 6-8
Set min_bars_SAME_SIDE to 12-16
Reduces time between allowed signals
Check Timing Mode :
If using Confirmed, remember there's a pivot_lookforward delay (5+ bars)
Switch to Realtime temporarily to verify system is working
Realtime has no delay but repaints
Verify Oscillator Settings :
Length 14 is standard but might not fit all instruments
Try length 9-11 for faster response
Try length 18-21 for slower, smoother response
Problem: Too Many Signals (Signal Spam)
Symptoms : Dashboard shows 50+ signals in Statistics, confidence scores mostly <0.40, signals clustering close together.
Solutions :
Raise Min Confidence :
Try 0.40-0.50 (quality filter)
Blocks bottom-tier setups
Targets top 50-60% of divergences only
Tighten OB/OS :
Use 70/30 or 75/25
Requires more extreme oscillator readings
Reduces false divergences in mid-range
Increase Min Slope Change :
Try 1.2-1.5 (from default 1.0)
Requires stronger, more obvious divergences
Filters marginal slope disagreements
Raise TCS Threshold :
Try 0.85-0.90 (from default 0.80)
Stricter trend filter blocks more counter-trend attempts
Favors only strongest trend alignment
Enable ALL CAE Gates :
Turn on Trend Filter + Adversarial + Confidence
Triple-layer protection
Blocks aggressively — expect 20-40% reduction in signals
Widen Spacing :
min_bars_ANY: 15-20 (from 12)
min_bars_SAME_SIDE: 30-40 (from 24)
Creates substantial breathing room
Switch to Confirmed Timing :
Removes realtime preview noise
Ensures full pivot validation
5-bar delay filters many false starts
Problem: Signals in Strong Trends Get Stopped Out
Symptoms : You take a bullish divergence in a downtrend (or bearish in uptrend), and it immediately fails. Dashboard showed high TCS at the time.
Analysis : This is INTENDED behavior — CAE is protecting you from low-probability counter-trend trades.
Understanding :
Check Last Signal Metrics in dashboard — what was TCS when signal fired?
If TCS was >0.85 and signal was counter-trend, CAE correctly identified it as high risk
Strong trends rarely reverse cleanly without major exhaustion
Your losses here are the system working as designed (blocking bad odds)
If You Want to Override (Not Recommended) :
Lower TCS_threshold to 0.70-0.75 (allows more counter-trend)
Lower exhaustion_required to 0.40 (easier override)
Disable Strong Trend Filter entirely (very risky)
Better Approach :
TRUST THE FILTER — it's preventing costly mistakes
Wait for exhaustion >0.75 (yellow shading) before counter-trending strong TCS
Focus on continuation signals (hidden divs) in high-TCS environments
Use Advisory mode to see what CAE is blocking and learn from outcomes
Problem: Adversarial Blocking Seems Wrong
Symptoms : You see a divergence that "looks good" visually, but CAE blocks with "Adversarial bearish/bullish" warning.
Diagnosis :
Check dashboard Bull Case and Bear Case scores at that moment
Look at Differential value
Check adversarial bar colors — was there strong coloring against your intended direction?
Understanding :
Adversarial catches "obvious" opposing momentum that's easy to miss
Example: Bullish divergence at a local low, BUT price is deeply below EMA50, bearish momentum is strong, and RSI shows knife-catching conditions
Bull Case might be 0.20 while Bear Case is 0.55
Differential = -0.35, far beyond threshold
Block is CORRECT — you'd be fighting overwhelming opposing flow
If You Disagree Consistently
Review blocked signals on chart — scroll back and check outcomes
Did those blocked signals actually work, or did they fail as adversarial predicted?
Raise adv_threshold to 0.15-0.20 (more permissive, allows closer battles)
Disable Adversarial Validation temporarily (diagnostic) to isolate its effect
Use Advisory mode to learn adversarial patterns over 50-100 signals
Remember : Adversarial is conservative BY DESIGN. It prevents "obvious" bad trades where you're fighting strong strength the other way.
Problem: Dashboard Not Showing or Incomplete
Solutions :
Toggle "Show Dashboard" to ON in settings
Try different dashboard sizes (Small/Normal/Large)
Try different positions (Top Left/Right, Bottom Left/Right) — might be off-screen
Some sections require CAE Enable = ON (Cognitive Engine section won't appear if CAE is disabled)
Statistics section requires at least 1 lifetime signal to populate
Check that visual theme is set (dashboard colors adapt to theme)
Problem: Performance Lag, Chart Freezing
Symptoms : Chart loading is slow, indicator calculations cause delays, pinch-to-zoom lags.
Diagnosis : Visual features are computationally expensive, especially adversarial bar coloring (recalculates every bar).
Solutions (In Order of Impact) :
Disable Adversarial Bar Coloring (MOST EXPENSIVE):
Turn OFF "Adversarial Bar Coloring" in settings
This is the single biggest performance drain
Immediate improvement
Reduce Vertical Lines :
Lower "Keep last N vertical lines" to 20-30
Or set to 0 to disable entirely
Moderate improvement
Disable Bifurcation Zones :
Turn OFF "Draw Bifurcation Zones"
Reduces box drawing calculations
Moderate improvement
Set Dashboard Size to Small :
Smaller dashboard = fewer cells = less rendering
Minor improvement
Use Shorter Max Lookback :
Reduce max_lookback to 40-50 (from 60+)
Fewer bars to scan for divergences
Minor improvement
Disable Exhaustion Shading :
Turn OFF "Show Market State"
Removes background coloring calculations
Minor improvement
Extreme Performance Mode :
Disable ALL visual enhancements
Keep only triangle markers
Dashboard Small or OFF
Use Minimal theme if available
Problem: Realtime Signals Repainting
Symptoms : You see a signal appear, but on next bar it disappears or moves.
Explanation :
Realtime mode detects peaks 1 bar ago: high > high AND high > high
On the FORMING bar (before close), this condition can change as new prices arrive
Example: At 10:05, high (10:04 bar) was 100, current high is 99 → peak detected
At 10:05:30, new high of 101 arrives → peak condition breaks → signal disappears
At 10:06 (bar close), final high is 101 → no peak at 10:04 anymore → signal gone permanently
This is expected behavior for realtime responsiveness. You get preview/early warning, but it's not locked until bar confirms.
Solutions :
Use Confirmed Timing :
Switch to "Confirmed (lookforward)" mode
ZERO repainting — pivot must be fully validated
5-bar delay (pivot_lookforward)
What you see in history is exactly what would have appeared live
Accept Realtime Repaint as Tradeoff :
Keep Realtime mode for speed and alerts
Understand that pre-confirmation signals may vanish
Only trade signals that CONFIRM at bar close (check barstate.isconfirmed)
Use for live monitoring, NOT for backtesting
Trade Only After Confirmation :
In Realtime mode, wait 1 full bar after signal appears before entering
If signal survives that bar close, it's locked
This adds 1-bar delay but removes repaint risk
Recommendation : Use Confirmed for backtesting and conservative trading. Use Realtime only for active monitoring with full understanding of preview behavior.
Risk Management Integration
BZ-CAE is a signal generation system, not a complete trading strategy. You must integrate proper risk management:
Position Sizing by Confidence
Confidence 0.70-1.00 (Premium) :
Risk: 1.5-2.0% of account (MAXIMUM)
Reasoning: High-quality setup across all factors
Still cap at 2% — even premium setups can fail
Confidence 0.50-0.70 (High Quality) :
Risk: 1.0-1.5% of account
Reasoning: Standard good setup
Your bread-and-butter risk level
Confidence 0.35-0.50 (Moderate Quality) :
Risk: 0.5-1.0% of account
Reasoning: Marginal setup, passes minimum threshold
Reduce size or skip if you're selective
Confidence <0.35 (Low Quality) :
Risk: 0% (blocked in Filtering mode)
Reasoning: Insufficient quality factors
System protects you by not showing these
Stop Placement Strategies
For Reversal Signals (Regular Divergences) :
Place stop beyond the divergence pivot plus buffer
Bullish : Stop below the divergence low - 1.0-1.5 × ATR
Bearish : Stop above the divergence high + 1.0-1.5 × ATR
Reasoning: If price breaks the pivot, divergence structure is invalidated
For Continuation Signals (Hidden Divergences) :
Place stop beyond recent swing in opposite direction
Bullish continuation : Stop below recent swing low (not the divergence pivot itself)
Bearish continuation : Stop above recent swing high
Reasoning: You're trading with trend, allow more breathing room
ATR-Based Stops :
1.5-2.0 × ATR is standard
Scale by timeframe:
Scalping (1-5m): 1.0-1.5 × ATR (tight)
Day trading (15m-1H): 1.5-2.0 × ATR (balanced)
Swing (4H-D): 2.0-3.0 × ATR (wide)
Never Use Fixed Dollar/Pip Stops :
Markets have different volatility
50-pip stop on EUR/USD ≠ 50-pip stop on GBP/JPY
Always normalize by ATR or pivot structure
Profit Targets and Scaling
Primary Target :
2-3 × ATR from entry (minimum 2:1 reward-risk)
Example : Entry at 100, ATR = 2, stop at 97 (1.5 × ATR) → target at 106 (3 × ATR) = 2:1 R:R
Scaling Out Strategy :
Take 50% off at 1.5 × ATR (secure partial profit)
Move stop to breakeven
Trail remaining 50% with 1.0 × ATR trailing stop
Let winners run if trend persists
Targets by Confidence :
High Confidence (>0.70) : Aggressive targets (3-4 × ATR), trail wider (1.5 × ATR)
Standard Confidence (0.50-0.70) : Normal targets (2-3 × ATR), standard trail (1.0 × ATR)
Low Confidence (0.35-0.50) : Conservative targets (1.5-2 × ATR), tight trail (0.75 × ATR)
Use Bifurcation Zones :
If opposite-side zone is visible on chart (from previous signal), use it as target
Example : Bullish signal at 100, prior supply zone at 110 → use 110 as target
Zones mark institutional resistance/support
Exhaustion-Based Exits :
If you're in a trade and exhaustion >0.75 develops (yellow shading), consider early exit
Market is overextended — reversal risk is high
Take profit even if target not reached
Trade Management by TCS
High TCS + Counter-Trend Trade (Risky) :
Use very tight stops (1.0-1.5 × ATR)
Conservative targets (1.5-2 × ATR)
Quick exit if trade doesn't work immediately
You're fading momentum — respect it
Low TCS + Reversal Trade (Safer) :
Use wider stops (2.0-2.5 × ATR)
Aggressive targets (3-4 × ATR)
Trail with patience
Genuine reversal potential in weak trend
High TCS + Continuation Trade (Safest) :
Standard stops (1.5-2.0 × ATR)
Very aggressive targets (4-5 × ATR)
Trail wide (1.5-2.0 × ATR)
You're with institutional momentum — let it run
Educational Value — Learning Machine Intelligence
BZ-CAE is designed as a learning platform, not just a tool:
Advisory Mode as Teacher
Most indicators are binary: signal or no signal. You don't learn WHY certain setups are better.
BZ-CAE's Advisory mode shows you EVERY potential divergence, then annotates the ones that would be blocked in Filtering mode with specific reasons:
"Bull: strong downtrend (TCS=0.87)" teaches you that TCS >0.85 makes counter-trend very risky
"Adversarial bearish" teaches you that the opposing case was dominating
"Low confidence 32%" teaches you that the setup lacked quality across multiple factors
"Bull spacing: wait 8 bars" teaches you that signals need breathing room
After 50-100 signals in Advisory mode, you internalize the CAE's decision logic. You start seeing these factors yourself BEFORE the indicator does.
Dashboard Transparency
Most "intelligent" indicators are black boxes — you don't know how they make decisions.
BZ-CAE shows you ALL metrics in real-time:
TCS tells you trend strength
DMA tells you momentum alignment
Exhaustion tells you overextension
Adversarial shows both sides of the debate
Confidence shows composite quality
You learn to interpret market state holistically, a skill applicable to ANY trading system beyond this indicator.
Divergence Quality Education
Not all divergences are equal. BZ-CAE teaches you which conditions produce high-probability setups:
Quality divergence : Regular bullish div at a low, TCS <0.50 (weak trend), exhaustion >0.75 (overextended), positive adversarial differential, confidence >0.70
Low-quality divergence : Regular bearish div at a high, TCS >0.85 (strong uptrend), exhaustion <0.30 (not overextended), negative adversarial differential, confidence <0.40
After using the system, you can evaluate divergences manually with similar intelligence.
Risk Management Discipline
Confidence-based position sizing teaches you to adjust risk based on setup quality, not emotions:
Beginners often size all trades identically
Or worse, size UP on marginal setups to "make up" for losses
BZ-CAE forces systematic sizing: premium setups get larger size, marginal setups get smaller size
This creates a probabilistic approach where your edge compounds over time.
What This Indicator Is NOT
Complete transparency about limitations and positioning:
Not a Prediction System
BZ-CAE does not predict future prices. It identifies structural divergences (price-momentum disagreements) and assesses current market state (trend, exhaustion, adversarial conditions). It tells you WHEN conditions favor a potential reversal or continuation, not WHAT WILL HAPPEN.
Markets are probabilistic. Even premium-confidence setups fail ~30-40% of the time. The system improves your probability distribution over many trades — it doesn't eliminate risk.
Not Fully Automated
This is a decision support tool, not a trading robot. You must:
Execute trades manually based on signals
Manage positions (stops, targets, trailing)
Apply discretionary judgment (news events, liquidity, context)
Integrate with your broader strategy and risk rules
The confidence scores guide position sizing, but YOU determine final risk allocation based on your account size, risk tolerance, and portfolio context.
Not Beginner-Friendly
BZ-CAE requires understanding of:
Divergence trading concepts (regular vs hidden, reversal vs continuation)
Market state interpretation (trend vs range, momentum, exhaustion)
Basic technical analysis (pivots, support/resistance, EMAs)
Risk management fundamentals (position sizing, stops, R:R)
This is designed for intermediate to advanced traders willing to invest time learning the system. If you want "buy the arrow" simplicity, this isn't the tool.
Not a Holy Grail
There is no perfect indicator. BZ-CAE filters noise and improves signal quality significantly, but:
Losing trades are inevitable (even at 70% win rate, 30% still fail)
Market conditions change rapidly (yesterday's strong trend becomes today's chop)
Black swan events occur (fundamentals override technicals)
Execution matters (slippage, fees, emotional discipline)
The system provides an EDGE, not a guarantee. Your job is to execute that edge consistently with proper risk management over hundreds of trades.
Not Financial Advice
BZ-CAE is an educational and analytical tool. All trading decisions are your responsibility. Past performance (backtested or live) does not guarantee future results. Only risk capital you can afford to lose. Consult a licensed financial advisor for investment advice specific to your situation.
Ideal Market Conditions
Best Performance Characteristics
Liquid Instruments :
Major forex pairs (EUR/USD, GBP/USD, USD/JPY)
Large-cap stocks and index ETFs (SPY, QQQ, AAPL, MSFT)
High-volume crypto (BTC, ETH)
Major commodities (Gold, Oil, Natural Gas)
Reasoning: Clean price structure, clear pivots, meaningful oscillator behavior
Trending with Consolidations :
Markets that trend for 20-40 bars, then consolidate 10-20 bars, repeat
Creates divergences at consolidation boundaries (reversals) and within trends (continuations)
Both regular and hidden divs find opportunities
5-Minute to Daily Timeframes :
Below 5m: too much noise, false pivots, CAE metrics unstable
Above daily: too few signals, edge diminishes (fundamentals dominate)
Sweet spot: 15m to 4H for most traders
Consistent Volume and Participation :
Regular trading sessions (not holidays or thin markets)
Predictable volatility patterns
Avoid instruments with sudden gaps or circuit breakers
Challenging Conditions
Extremely Low Liquidity :
Penny stocks, exotic forex pairs, low-volume crypto
Erratic pivots, unreliable oscillator readings
CAE metrics can't assess market state properly
Very Low Timeframes (1-Minute or Below) :
Dominated by market microstructure noise
Divergences are everywhere but meaningless
CAE filtering helps but still unreliable
Extended Sideways Consolidation :
100+ bars of tight range with no clear pivots
Oscillator hugs midpoint (45-55 range)
No divergences to detect
Fundamentally-Driven Gap Markets :
Earnings releases, economic data, geopolitical events
Price gaps over stops and targets
Technical structure breaks down
Recommendation: Disable trading around known events
Calculation Methodology — Technical Depth
For users who want to understand the math:
Oscillator Computation
Each oscillator type calculates differently, but all normalize to 0-100:
RSI : ta.rsi(close, length) — Standard Relative Strength Index
Stochastic : ta.stoch(high, low, close, length) — %K calculation
CCI : (ta.cci(hlc3, length) + 100) / 2 — Normalized from -100/+100 to 0-100
MFI : ta.mfi(hlc3, length) — Volume-weighted RSI equivalent
Williams %R : ta.wpr(length) + 100 — Inverted stochastic adjusted to 0-100
Smoothing: If smoothing > 1, apply ta.sma(oscillator, smoothing)
Divergence Detection Algorithm
Identify Pivots :
Price high pivot: ta.pivothigh(high, lookback, lookforward)
Price low pivot: ta.pivotlow(low, lookback, lookforward)
Oscillator high pivot: ta.pivothigh(osc, lookback, lookforward)
Oscillator low pivot: ta.pivotlow(osc, lookback, lookforward)
Store Recent Pivots :
Maintain arrays of last 10 pivots with bar indices
When new pivot confirmed, unshift to array, pop oldest if >10
Scan for Slope Disagreements :
Loop through last 5 pivots
For each pair (current pivot, historical pivot):
Check if within max_lookback bars
Calculate slopes: (current - historical) / bars_between
Regular bearish: price_slope > 0, osc_slope < 0, |osc_slope| > min_threshold
Regular bullish: price_slope < 0, osc_slope > 0, |osc_slope| > min_threshold
Hidden bearish: price_slope < 0, osc_slope > 0, osc_slope > min_threshold
Hidden bullish: price_slope > 0, osc_slope < 0, |osc_slope| > min_threshold
Important Disclaimers and Terms
Performance Disclosure
Past performance, whether backtested or live-traded, does not guarantee future results. Markets change. What works today may not work tomorrow. Hypothetical or simulated performance results have inherent limitations and do not represent actual trading.
Risk of Loss
Trading involves substantial risk of loss. Only trade with risk capital you can afford to lose entirely. The high degree of leverage often available in trading can work against you as well as for you. Leveraged trading may result in losses exceeding your initial deposit.
Not Financial Advice
BZ-CAE is an educational and analytical tool for technical analysis. It is not financial advice, investment advice, or a recommendation to buy or sell any security or instrument. All trading decisions are your sole responsibility. Consult a licensed financial advisor for advice specific to your circumstances.
Technical Indicator Limitations
BZ-CAE is a technical analysis tool based on price and volume data. It does not account for:
Fundamental analysis (earnings, economic data, financial health)
Market sentiment and positioning
Geopolitical events and news
Liquidity conditions and market microstructure changes
Regulatory changes or exchange rules
Integrate with broader analysis and strategy. Do not rely solely on technical indicators for trading decisions.
Repainting Acknowledgment
As disclosed throughout this documentation:
Realtime mode may repaint on forming bars before confirmation (by design for preview functionality)
Confirmed mode has zero repainting (fully validated pivots only)
Choose timing mode appropriate for your use case. Understand the tradeoffs.
Testing Recommendation
ALWAYS test on demo/paper accounts before committing real capital. Validate the indicator's behavior on your specific instruments and timeframes. Learn the system thoroughly in Advisory mode before using Filtering mode.
Learning Resources :
In-indicator tooltips (hover over setting names for detailed explanations)
This comprehensive publishing statement (save for reference)
User guide in script comments (top of code)
Final Word — Philosophy of BZ-CAE
BZ-CAE is not designed to replace your judgment — it's designed to enhance it.
The indicator identifies structural inflection points (bifurcations) where price and momentum disagree. The Cognitive Engine evaluates market state to determine if this disagreement is meaningful or noise. The Adversarial model debates both sides of the trade to catch obvious bad setups. The Confidence system ranks quality so you can choose your risk appetite.
But YOU still execute. YOU still manage risk. YOU still learn from outcomes.
This is intelligence amplification, not intelligence replacement.
Use Advisory mode to learn how expert traders evaluate market state. Use Filtering mode to enforce discipline when emotions run high. Use the dashboard to develop a systematic approach to reading markets. Use confidence scores to size positions probabilistically.
The system provides an edge. Your job is to execute that edge with discipline, patience, and proper risk management over hundreds of trades.
Markets are probabilistic. No system wins every trade. But a systematic edge + disciplined execution + proper risk management compounds over time. That's the path to consistent profitability. BZ-CAE gives you the edge. The discipline and risk management are on you.
Taking you to school. — Dskyz, Trade with insight. Trade with anticipation.
Smart RSI Money Flow - Core Bands V1.01SMART RSI – Money Flow Bands (Technical Overview)
1. Background: RSI and Its Behavior on Lower Timeframes
The Relative Strength Index (RSI) originally is a momentum oscillator calculated from average gains and losses over a selected period. In its standard form, RSI is derived solely from price changes; it does not incorporate volume data or order-flow information in its formula.
Because RSI is price-based, its interpretation depends strongly on the timeframe:
• On higher timeframes, each bar aggregates more trading activity, and RSI tends to behave more smoothly.
• On lower timeframes (1-hour down to intraday scalping intervals), price fluctuations are quicker, and RSI becomes more sensitive to short-term noise.
This does not imply that RSI becomes invalid, but that its signals on fast charts can be more reactive and may benefit from additional context such as volume behavior or structural information.
2. Purpose of This Indicator
This indicator extends the classical RSI by adding information that RSI does not include:
• Mapping RSI values into price-based bands instead of the 0–100 oscillator space.
• Retrieving lower timeframe volume data and separating it into buy and sell components.
• Comparing the slope (angle) of price movement with the slope of buy and sell volume.
The goal is to provide a structural interpretation of where price sits relative to RSI conditions and how volume is behaving on a lower timeframe.
3. Technical Differences Compared to Classical RSI
A) Classical RSI
• Input: price only (usually close).
• Output: normalized oscillator between 0 and 100.
• Does not incorporate intra-bar volume distribution.
• Does not separate buy/sell volume.
B) SMART RSI – Money Flow Bands
1) RSI-to-Price Mapping
Converts RSI values into upper/lower price bands using recent price extremes.
2) Lower Timeframe Volume Decomposition
Retrieves LTF data and splits each bar’s volume into buy (close>open) and sell (close
Hyper Strength Index | QuantLapse🧠 Hyper Strength Index (HSI) | QuantLapse
Overview:
The Hyper Strength Index (HSI) is a composite momentum oscillator designed to unify multiple strength measures into a single, adaptive framework. It combines the Relative Strength Index (RSI), Chande Momentum Oscillator (CMO), Money Flow Index (MFI), and Stochastic RSI to deliver a refined, multidimensional view of market momentum and overbought/oversold conditions.
Unlike traditional oscillators that rely on a single formula, the HSI averages four distinct momentum perspectives — price velocity, directional conviction, volume participation, and stochastic behavior — offering traders a more balanced and noise-resistant reading of market strength.
⚙️ Calculation Logic:
The Hyper Strength Index is computed as the normalized average of:
📈 RSI — classic measure of relative momentum.
💪 CMO — captures directional bias and intensity of moves.
💵 MFI — integrates volume and money flow pressure.
🔄 Stochastic RSI (K-line) — identifies momentum extremes and short-term turning points.
This fusion creates a smoother, more comprehensive signal, mitigating the weaknesses of any single oscillator.
🎯 Interpretation:
Overbought Zone (Default: > 75):
Indicates potential exhaustion of bullish momentum — a cooling phase or reversal may follow.
Oversold Zone (Default: < 7):
Suggests bearish exhaustion — a rebound or accumulation phase may emerge.
Neutral Zone (Between 7 and 75):
Represents balanced market conditions or trend continuation phases.
Visual cues highlight key conditions:
🔺 Red Highlights — Overbought regions or downward inflection points.
🔻 Green Highlights — Oversold regions or upward inflection points.
Neutral zones are shaded with subtle gray backgrounds for clarity.
💡 Key Features:
🔹 Multi-factor strength analysis (RSI + CMO + MFI + StochRSI).
🔹 Adaptive overbought/oversold detection.
🔹 Visual alerts via colored backgrounds and bar markers.
🔹 Customizable smoothing and length parameters for fine-tuning sensitivity.
🔹 Intuitive visualization ideal for both short-term scalping and swing trading setups.
🧭 Usage Notes:
Works best as a momentum confirmation tool — pair with trend filters like EMA, SuperTrend, or ADX.
In trending markets, use crossovers from extreme zones as potential continuation or exhaustion signals.
In ranging markets, exploit overbought/oversold reversals for high-probability mean reversion trades.
📘 Summary:
The Hyper Strength Index | QuantLapse distills multiple dimensions of market strength into a single, cohesive oscillator. By merging price, volume, and directional momentum, it provides traders with a more robust, responsive, and context-aware perspective on market dynamics — a next-generation evolution beyond the limitations of RSI or CMO alone.
Enhanced Holt-Winters RSI [BOSWaves]Enhanced Holt-Winters RSI – Next-Level Momentum Smoothing & Signal Precision
Overview
The Enhanced Holt-Winters RSI transforms the classic Relative Strength Index into a robust, lag-minimized momentum oscillator through Holt-Winters triple exponential smoothing. By modeling the level, trend, and cyclical behavior of the RSI series, this indicator delivers smoother, more responsive signals that highlight overbought/oversold conditions, momentum shifts, and high-conviction trading setups without cluttering the chart with noise.
Unlike traditional RSI, which reacts to historical data and produces frequent whipsaws, the Enhanced Holt-Winters RSI filters transient price fluctuations, enabling traders to detect emerging momentum and potential reversal zones earlier.
Theoretical Foundation
The traditional RSI measures relative strength by comparing average gains and losses, but suffers from:
Lag in trend recognition : Signals often arrive after momentum has shifted.
Noise sensitivity : High-frequency price movements generate unreliable crossovers.
Limited insight into structural market shifts : Standard RSI cannot contextualize cyclical or momentum patterns.
The Enhanced Holt-Winters RSI addresses these limitations by applying triple exponential smoothing directly to the RSI series. This decomposes the series into:
Level (Lₜ) : Represents the smoothed central tendency of RSI.
Trend (Tₜ) : Captures rate-of-change in smoothed momentum.
Seasonal Component (Sₜ) : Models short-term cyclical deviations in momentum.
By incorporating these elements, the oscillator produces smoothed RSI values that react faster to emerging trends while suppressing erratic noise. Its internal forecast is mathematical, influencing the smoothed RSI output and signals, rather than being directly plotted.
How It Works
The Enhanced Holt-Winters RSI builds its signal framework through several layers:
1. Base RSI Calculation
Computes standard RSI over the selected period as the primary momentum input.
2. Triple Exponential Smoothing (Holt-Winters)
The RSI is smoothed recursively to extract underlying momentum structure:
Level, trend, and seasonal components are combined to produce a smoothed RSI.
This internal smoothing reduces lag and enhances signal reliability.
3. Momentum Analysis
Short-term momentum shifts are tracked via a moving average of the smoothed RSI, highlighting acceleration or deceleration in directional strength.
4. Volume Confirmation (Optional)
Buy/sell signals can be filtered through a configurable volume threshold, ensuring only high-conviction moves trigger alerts.
5. Visual Output
Colored Candles : Represent overbought (red), oversold (green), or neutral (yellow) conditions.
Oscillator Panel : Plots the smoothed RSI with dynamic color coding for immediate trend context.
Signals : Triangular markers indicate bullish or bearish setups, with stronger signals flagged in extreme zones.
Interpretation
The Enhanced Holt-Winters RSI provides a multi-dimensional perspective on price action:
Trend Strength : Smoothed RSI slope and color coding reflect the direction and momentum intensity.
Momentum Shifts : Rapid changes in the smoothed RSI indicate emerging strength or weakness.
Overbought/Oversold Zones : Highlight areas where price is stretched relative to recent momentum.
High-Conviction Signals : Combined with volume filtering, markers indicate optimal entries/exits.
Cycle Awareness : Smoothing reveals structural patterns, helping traders avoid reacting to noise.
By combining these elements, traders gain early insight into market structure and momentum without relying on raw, lag-prone RSI data.
Strategy Integration
The Enhanced Holt-Winters RSI can be applied across trading styles:
Trend Following
Enter when RSI is aligned with price momentum and color-coded signals confirm trend direction.
Strong slope in the smoothed RSI signals trend continuation.
Reversal Trading
Look for RSI extremes with momentum shifts and strong signal markers.
Compression in oscillator values often precedes reversal setups.
Breakout Detection
Oscillator flattening in neutral zones followed by directional expansion indicates potential breakout conditions.
Multi-Timeframe Confluence
Higher timeframes provide directional bias; lower timeframes refine entry timing using smoothed RSI dynamics.
Technical Implementation Details
Input Source : Close, open, high, low, or price.
Smoothing : Holt-Winters triple exponential smoothing applied to RSI.
Parameters :
Level (α) : Controls smoothing of RSI.
Trend (β) : Adjusts responsiveness to momentum changes.
Seasonal Length : Defines cycles for short-term adjustments.
Delta Smoothing : Reduces choppiness in smoothed RSI difference.
Outputs :
Smoothed RSI
Colored candles and oscillator panel
Buy/Sell signal markers (with optional strength filtering)
Volume Filtering : Optional threshold to confirm signals.
Optimal Application Parameters
Asset-Specific Guidance:
Forex : Use moderate smoothing (α, β) to capture medium-term momentum swings while filtering minor price noise. Works best when combined with volume or volatility filters.
Equities : Balance responsiveness and smoothness to identify sustained sector momentum or rotational shifts; ideal for capturing clean directional transitions.
Cryptocurrency : Increase smoothing parameters slightly to stabilize RSI during extreme volatility; optional volume confirmation can help filter false signals.
Futures/Indices : Lower smoothing sensitivity emphasizes macro momentum and structural trend durability over short-term fluctuations.
Timeframe Optimization:
Scalping (1-5m) : Use higher sensitivity (lower smoothing factors) to react quickly to micro-momentum reversals.
Intraday (15m-1h) : Balance smoothing and responsiveness for detecting short-term acceleration and exhaustion zones.
Swing (4h-Daily) : Apply moderate smoothing to reveal underlying directional persistence and cyclical reversals.
Position (Daily-Weekly) : Use stronger smoothing to isolate dominant momentum trends and filter temporary pullbacks.
Integration Guidelines
Combine with trend filters (EMAs, SuperSmoother MA, ATR-based tools) for confirmation.
Use volume and signal strength markers to filter low-conviction trades.
Slope, color, and signal alignment can guide entry, stop placement, and scaling.
Disclaimer
The Enhanced Holt-Winters RSI is a technical analysis tool, not a guaranteed profit system. Effectiveness depends on proper settings, market structure, and disciplined risk management. Always backtest before live trading.
TradeScope: MA Reversion • RVOL • Trendlines • GAPs • TableTradeScope is an all-in-one technical analysis suite that brings together price action, momentum, volume dynamics, and trend structure into one cohesive and fully customizable indicator.
An advanced, modular trading suite that combines moving averages, reversion signals, RSI/CCI momentum, relative volume, gap detection, trendline analysis, and dynamic tables — all within one powerful dashboard.
Perfect for swing traders, intraday traders, and analysts who want to read price strength, volume context, and market structure in real time.
⚙️ Core Components & Inputs
🧮 Moving Average Settings
Moving Average Type & Length:
Choose between SMA or EMA and set your preferred period for smoother or more reactive trend tracking.
Multi-MA Plotting:
Up to 8 customizable moving averages (each with independent type, color, and length).
Includes a “window filter” to show only the last X bars, reducing chart clutter.
MA Reversion Engine:
Detects when price has extended too far from its moving average.
Reversion Lookback: Number of bars analyzed to determine historical extremes.
Reversion Threshold: Sensitivity multiplier—lower = more frequent signals, higher = stricter triggers.
🔄 Trend Settings
Short-Term & Long-Term Trend Lookbacks:
Uses linear regression to detect the slope and direction of the short- and long-term trend.
Results are displayed in the live table with color-coded bias:
🟩 Bullish | 🟥 Bearish
📈 Momentum Indicators
RSI (Relative Strength Index):
Adjustable period; displays the current RSI value, overbought (>70) / oversold (<30) zones, and trending direction.
CCI (Commodity Channel Index):
Customizable length with color-coded bias:
🟩 Oversold (< -100), 🟥 Overbought (> 100).
Tooltip shows whether the CCI is trending up or down.
📊 Volume Analysis
Relative Volume (RVOL):
Estimates end-of-day projected volume using intraday progress and compares it against the 20-day average.
Displays whether today’s volume is expected to exceed yesterday’s, and highlights color by strength.
Volume Trend (Short & Long Lookbacks):
Visual cues for whether current volume is above or below short-term and long-term averages.
Estimated Full-Day Volume & Multiplier:
Converts raw volume into “X” multiples (e.g., 2.3X average) for quick interpretation.
🕳️ Gap Detection
Automatically identifies and plots bullish and bearish price gaps within a defined lookback period.
Gap Lookback: Defines how far back to search for gaps.
Gap Line Width / Visibility: Controls the thickness and display of gap lines on chart.
Displays the closest open gap in the live table, including its distance from current price (%).
🔍 ATR & Volatility
14-day ATR (% of price):
Automatically converts the Average True Range into a percent, providing quick volatility context:
🟩 Low (<3%) | 🟨 Moderate (3–5%) | 🟥 High (>5%)
💬 Candlestick Pattern Recognition
Auto-detects popular reversal and continuation patterns such as:
Bullish/Bearish Engulfing
Hammer / Hanging Man
Shooting Star / Inverted Hammer
Doji / Harami / Kicking / Marubozu / Morning Star
Each pattern is shown with contextual color coding in the table.
🧱 Pivot Points & Support/Resistance
Optional Pivot High / Pivot Low Labels
Adjustable left/right bar lengths for pivot detection
Theme-aware text and label color options
Automatically drawn diagonal trendlines for both support and resistance
Adjustable line style, color, and thickness
Detects and tracks touches for reliability
Includes breakout alerts (with optional volume confirmation)
🚨 Alerts
MA Cross Alerts:
Triggers when price crosses the fast or slow moving average within a tolerance band (default ±0.3%).
Diagonal Breakout Alerts:
Detects and alerts when price breaks diagonal trendlines.
Volume-Confirmed Alerts:
Filters breakouts where volume exceeds 1.5× the 20-bar average.
🧾 Live Market Table
A fully dynamic table displayed on-chart, customizable via input toggles:
Choose which rows to show (e.g., RSI, ATR, RVOL, Gaps, CCI, Trend, MA info, Diff, Low→Close%).
Choose table position (top-right, bottom-left, etc.) and text size.
Theme selection: Light or Dark
Conditional background colors for instant visual interpretation:
🟩 Bullish or Oversold
🟥 Bearish or Overbought
🟨 Neutral / Moderate
🎯 Practical Uses
✅ Identify confluence setups combining MA reversion, volume expansion, and RSI/CCI extremes.
✅ Track trend bias and gap proximity directly in your dashboard.
✅ Monitor relative volume behavior for intraday strength confirmation.
✅ Automate MA cross or breakout alerts to stay ahead of key price action.
🧠 Ideal For
Swing traders seeking confluence-based setups
Intraday traders monitoring multi-factor bias
Analysts looking for compact market health dashboards
💡 Summary
TradeScope is designed as a single-pane-of-glass market view — combining momentum, trend, volume, structure, and reversion into one clear visual system.
Fully customizable. Fully dynamic.
Use it to see what others miss — clarity, confluence, and confidence in every trade.
Currency Strength v3.0Currency Strength v3.0
Summary
The Currency Strength indicator is a powerful tool designed to gauge the relative strength of major and emerging market currencies. By plotting the True Strength Index (TSI) of various currency indices, it provides a clear visual representation of which currencies are gaining momentum and which are losing it. This indicator automatically detects the currency pair on your chart and highlights the corresponding strength lines, simplifying analysis and helping you quickly identify potential trading opportunities based on currency dynamics.
Key Features
Comprehensive Currency Analysis: Tracks the strength of 19 currencies, including major pairs and several emerging market currencies.
Automatic Pair Detection: Intelligently identifies the base and quote currency of the active chart, automatically highlighting the relevant strength lines.
Dynamic Coloring: The base currency is consistently colored blue, and the quote currency is colored gold, making it easy to distinguish between the two at a glance.
Non-Repainting TSI Calculation: Uses the True Strength Index (TSI) for smooth and reliable momentum readings that do not repaint.
Customizable Settings: Allows for adjustment of the fast and slow periods for the TSI calculation to fit your specific trading style.
Clean Interface: Features a minimalist legend table that only displays the currencies relevant to your current chart, keeping your workspace uncluttered.
How It Works
The indicator pulls data from major currency indices (like DXY for the US Dollar and EXY for the Euro). For currencies that don't have a dedicated index, it uses their USD pair (e.g., USDCNY) and inverts the calculation to derive the currency's strength relative to the dollar. It then applies the True Strength Index (TSI) to this data. The TSI is a momentum oscillator that is less volatile than other oscillators, providing a more reliable measure of strength. The resulting values are plotted on the chart, allowing you to see how different currencies are performing against each other in real-time.
How to Use
Trend Confirmation: When the base currency's line is rising and above the zero line, and the quote currency's line is falling, it can confirm a bullish trend for the pair. The opposite would suggest a bearish trend.
Identifying Divergences: Look for divergences between the currency strength lines and the price action of the pair. For example, if the price is making higher highs but the base currency's strength is making lower highs, it could signal a potential reversal.
Crossovers: A crossover of the base and quote currency lines can signal a shift in momentum. A bullish signal occurs when the base currency line crosses above the quote currency line. A bearish signal occurs when it crosses below.
Overbought/Oversold Levels: The horizontal dashed lines at 0.5 and -0.5 can be used as general guides for overbought and oversold conditions, respectively. Strength moving beyond these levels may indicate an unsustainable move that is due for a correction.
Settings
Fast Period: The short-term period for the TSI calculation. Default is 7.
Slow Period: The long-term period for the TSI calculation. Default is 15.
Index Source: The price source used for the calculations (e.g., Close, Open). Default is Close.
Base Currency Color: The color for the base currency line. Default is Royal Blue.
Quote Currency Color: The color for the quote currency line. Default is Goldenrod.
Disclaimer
This indicator is intended for educational and analytical purposes only. It is not financial advice. Trading involves substantial risk, and past performance is not indicative of future results. Always conduct your own research and risk management before making any trading decisions.
Range Breakout [sgbpulse]Range Breakout
1. Overview
The "Range Breakout " indicator is a powerful tool designed to identify and visually display price ranges on your chart using pivot points. It dynamically draws two distinct boxes – an External Range and an Internal Range – helping traders pinpoint potential support and resistance zones. Beyond its visual representation, the indicator offers a comprehensive set of 12 unique breakout alerts, providing real-time notifications for significant price movements outside these defined ranges. Additionally, it integrates RSI and MFI metrics for momentum confirmation.
2. How It Works
The indicator operates by identifying pivot points based on user-defined "left" and "right" bar lengths. A high pivot is a bar with a specified number of lower highs both to its left and right, and similarly for a low pivot.
External Range: Calculated using longer pivot lengths (default: 15 bars left, 6 bars right). This range represents broader, more significant price consolidation areas.
Internal Range: Calculated using shorter pivot lengths (default: 4 bars left, 3 bars right). This range captures tighter, more immediate price consolidations within the broader trend.
The External Range will always be greater than or equal to the Internal Range, as it's based on a wider historical context. Both ranges are displayed as transparent boxes on your chart, dynamically adjusting as new pivots are formed.
3. Key Features and Settings
Customizable Pivot Lengths:
External Range (Left/Right Bars): Adjust sensitivity for identifying the broader price range. Longer lengths lead to more stable, but less frequent, range updates.
Internal Range (Left/Right Bars): Adjust sensitivity for the tighter, more immediate price range.
Tool Tips: Minimum 6 bars for the External Range, and minimum 2 bars for the Internal Range.
Customizable Range Colors: Easily change the background colors of the External and Internal Range boxes to match your chart's aesthetic.
Dynamic Range Display: The indicator automatically updates the range boxes as new pivot highs and lows are formed, always presenting the most current valid ranges.
RSI / MFI Settings:
Timeframe Source: Select the timeframe for RSI and MFI calculation.
- Chart: Calculation based on the current chart timeframe.
- Daily: Always calculated based on the daily ("D") timeframe, even if the chart is on a lower timeframe.
RSI Length: Period length for RSI calculation (default: 14).
RSI Overbought Level: Overbought level for RSI (default: 70.0).
RSI Oversold Level: Oversold level for RSI (default: 30.0).
MFI Length: Period length for MFI calculation (default: 14).
MFI Overbought Level: Overbought level for MFI (default: 80.0).
MFI Oversold Level: Oversold level for MFI (default: 20.0).
4. Synergy of Ranges & Breakout Strength
The interaction between the External and Internal Ranges provides deep insights into price movement and breakout strength:
Immediate Direction: The movement of the Internal Range (up or down) indicates the short-term directional bias within the broader framework of the External Range.
Strength Confirmation: A breakout of the External Range, followed by a breakout of the Internal Range, confirms the strength of the move and increases confidence in the breakout.
Strong Momentum ("Leaving" Ranges Behind): When price breaks out with exceptionally strong momentum, it continues to move aggressively and does not immediately form new pivots. In such situations, the existing ranges (External and Internal) remain in place while the candles "leave them behind." A "Full Candle" breakout, where the entire candle moves past both ranges, indicates a particularly powerful and decisive move.
Momentum (RSI / MFI) as Confirmation:
- RSI (Relative Strength Index): Measures the speed and change of price movements. Extreme values (above 70 or below 30) indicate overbought/oversold conditions respectively, confirming strong momentum in a breakout.
- MFI (Money Flow Index): Similar to RSI but incorporates volume. Extreme values (above 80 or below 20) indicate strong money flow in/out, reinforcing breakout confirmation.
- Importance of Confirmation: If a breakout occurs but momentum indicators do not confirm it (for example, an upside breakout while RSI is declining), this could signal weakness in the move and the risk of a false breakout (Fakeout).
5. Visuals
The indicator provides clear visual representations on the chart:
Range Boxes:
Two dynamic boxes are drawn on the chart: one for the External Range and one for the Internal Range.
These boxes update continuously, displaying the current range boundaries based on the latest pivots. They provide an immediate visual indication of support and resistance levels.
RSI/MFI Status Labels:
Small text labels appear to the right of the current bar, vertically centered.
They display the status of RSI and MFI: RSI OB (Overbought), RSI OS (Oversold), MFI OB, MFI OS, along with the exact value.
Important: The labels remain on the chart as long as the condition holds (indicator is above/below the level), unlike alerts which mark a singular crossover event.
Plotting of Key Values:
The indicator plots six invisible series on the chart, primarily to allow the user to view the exact numerical values of:
- The upper and lower bounds of the External Range (External High, External Low).
- The upper and lower bounds of the Internal Range (Internal High, Internal Low).
- The calculated RSI and MFI values (RSI, MFI).
These values are accessible for viewing through TradingView's Data Window and also via the Status Line when hovering over the relevant candle. This enables more precise quantitative analysis of range levels and momentum.
6. Comprehensive Breakout Alerts
The "Range Breakout " indicator provides 12 distinct alert conditions for breakouts, allowing you to select the required level of confirmation for each alert. All alerts are triggered only upon a fully confirmed bar close (barstate.isconfirmed) to minimize false signals and ensure reliability.
All breakout alerts are configured to detect a Crossover/Crossunder of the levels, meaning a specific event where the price moves from one side of the range to the other.
External Range Breakout UP
- Close: Price closes above the External Range.
- Real Body: The entire "real body" of the candle (min of open/close prices) closes above the External Range.
- Full Candle: The entire candle (the lowest point of the candle) closes above the External Range.
External Range Breakout DOWN
- Close: Price closes below the External Range.
- Real Body: The entire "real body" of the candle (max of open/close prices) closes below the External Range.
- Full Candle: The entire candle (the highest point of the candle) closes below the External Range.
Internal Range Breakout UP
- Close: Price closes above the Internal Range.
- Real Body: The "real body" of the candle closes above the Internal Range.
- Full Candle: The entire candle closes above the Internal Range.
Internal Range Breakout DOWN
- Close: Price closes below the Internal Range.
- Real Body: The "real body" of the candle closes below the Internal Range.
- Full Candle: The entire candle closes below the Internal Range.
7. Ideal Use Cases
This indicator is ideal for traders who:
Want to clearly identify and monitor price consolidation zones.
Seek confirmation for breakout strategies across various timeframes.
Require reliable and automated alerts for potential entry or exit points based on range expansion.
8. Complementary Indicator
For even more comprehensive market analysis, we highly recommend using this indicator in conjunction with Market Structure Support & Resistance External/Internal & BoS .
This powerful complementary indicator automatically and accurately identifies significant support and resistance levels by locating high and low pivot points, as well as key Pre-Market High/Low levels. Its strength lies in its dynamic adaptability to any timeframe and asset, providing precise and relevant real-time levels while maintaining a clean chart. It also identifies Break of Structure (BoS) to signal potential trend changes or continuations.
Using both indicators together provides a robust framework for identifying defined ranges and potential trend shifts, enabling more informed trading decisions.
View Market Structure Support & Resistance External/Internal & BoS Indicator
9. Important Note: Trading Risk
This indicator is intended for educational and informational purposes only and does not constitute investment advice or a recommendation for trading in any form whatsoever.
Trading in financial markets involves significant risk of capital loss. It is important to remember that past performance is not indicative of future results. All trading decisions are your sole responsibility. Never trade with money you cannot afford to lose.
Crypto Risk-Weighted Allocation SuiteCrypto Risk-Weighted Allocation Suite
This indicator is designed to help users explore dynamic portfolio allocation frameworks for the crypto market. It calculates risk-adjusted allocation weights across major crypto sectors and cash based on multi-factor momentum and volatility signals. Best viewed on INDEX:BTCUSD 1D chart. Other charts and timeframes may give mixed signals and incoherent allocations.
🎯 How It Works
This model systematically evaluates the relative strength of:
BTC Dominance (CRYPTOCAP:BTC.D)
Represents Bitcoin’s share of the total crypto market. Rising dominance typically indicates defensive market phases or BTC-led trends.
ETH/BTC Ratio (BINANCE:ETHBTC)
Gauges Ethereum’s relative performance versus Bitcoin. This provides insight into whether ETH is leading risk appetite.
SOL/BTC Ratio (BINANCE:SOLBTC)
Measures Solana’s performance relative to Bitcoin, capturing mid-cap layer-1 strength.
Total Market Cap excluding BTC and ETH (CRYPTOCAP:TOTAL3ES)
Represents Altcoins as a broad category, reflecting appetite for higher-risk assets.
Each of these series is:
✅ Converted to a momentum slope over a configurable lookback period.
✅ Standardized into Z-scores to normalize changes relative to recent behavior.
✅ Smoothed optionally using a Hull Moving Average for cleaner signals.
✅ Divided by ATR-based volatility to create a risk-weighted score.
✅ Scaled to proportionally allocate exposure, applying user-configured minimum and maximum constraints.
🪙 Dynamic Allocation Logic
All signals are normalized to sum to 100% if fully confident.
An overall confidence factor (based on total signal strength) scales the allocation up or down.
Any residual is allocated to cash (unallocated capital) for conservative exposure.
The script automatically avoids “all-in” bias and prevents negative allocations.
📊 Outputs
The indicator displays:
Market Phase Detection (which asset class is currently leading)
Risk Mode (Risk On, Neutral, Risk Off)
Dynamic Allocations for BTC, ETH, SOL, Alts, and Cash
Optional momentum plots for transparency
🧠 Why This Is Unique
Unlike simple dominance indicators or crossovers, this model:
Integrates multiple cross-asset signals (BTC, ETH, SOL, Alts)
Adjusts exposure proportionally to signal strength
Normalizes by volatility, dynamically scaling risk
Includes configurable constraints to reflect your own risk tolerance
Provides a cash fallback allocation when conviction is low
Is entirely non-repainting and based on daily closing data
⚠️ Disclaimer
This script is provided for educational and informational purposes only.
It is not financial advice and should not be relied upon to make investment decisions.
Past performance does not guarantee future results.
Always consult a qualified financial advisor before acting on any information derived from this tool.
🛠 Recommended Use
As a framework to visualize relative momentum and risk-adjusted allocations
For research and backtesting ideas on portfolio allocation across crypto sectors
To help build your own risk management process
This script is not a turnkey strategy and should be customized to fit your goals.
✅ Enjoy exploring dynamic crypto allocations responsibly!
Bear Market Probability Model# Bear Market Probability Model: A Multi-Factor Risk Assessment Framework
The Bear Market Probability Model represents a comprehensive quantitative framework for assessing systemic market risk through the integration of 13 distinct risk factors across four analytical categories: macroeconomic indicators, technical analysis factors, market sentiment measures, and market breadth metrics. This indicator synthesizes established financial research methodologies to provide real-time probabilistic assessments of impending bear market conditions, offering institutional-grade risk management capabilities to retail and professional traders alike.
## Theoretical Foundation
### Historical Context of Bear Market Prediction
Bear market prediction has been a central focus of financial research since the seminal work of Dow (1901) and the subsequent development of technical analysis theory. The challenge of predicting market downturns gained renewed academic attention following the market crashes of 1929, 1987, 2000, and 2008, leading to the development of sophisticated multi-factor models.
Fama and French (1989) demonstrated that certain financial variables possess predictive power for stock returns, particularly during market stress periods. Their three-factor model laid the groundwork for multi-dimensional risk assessment, which this indicator extends through the incorporation of real-time market microstructure data.
### Methodological Framework
The model employs a weighted composite scoring methodology based on the theoretical framework established by Campbell and Shiller (1998) for market valuation assessment, extended through the incorporation of high-frequency sentiment and technical indicators as proposed by Baker and Wurgler (2006) in their seminal work on investor sentiment.
The mathematical foundation follows the general form:
Bear Market Probability = Σ(Wi × Ci) / ΣWi × 100
Where:
- Wi = Category weight (i = 1,2,3,4)
- Ci = Normalized category score
- Categories: Macroeconomic, Technical, Sentiment, Breadth
## Component Analysis
### 1. Macroeconomic Risk Factors
#### Yield Curve Analysis
The inclusion of yield curve inversion as a primary predictor follows extensive research by Estrella and Mishkin (1998), who demonstrated that the term spread between 3-month and 10-year Treasury securities has historically preceded all major recessions since 1969. The model incorporates both the 2Y-10Y and 3M-10Y spreads to capture different aspects of monetary policy expectations.
Implementation:
- 2Y-10Y Spread: Captures market expectations of monetary policy trajectory
- 3M-10Y Spread: Traditional recession predictor with 12-18 month lead time
Scientific Basis: Harvey (1988) and subsequent research by Ang, Piazzesi, and Wei (2006) established the theoretical foundation linking yield curve inversions to economic contractions through the expectations hypothesis of the term structure.
#### Credit Risk Premium Assessment
High-yield credit spreads serve as a real-time gauge of systemic risk, following the methodology established by Gilchrist and Zakrajšek (2012) in their excess bond premium research. The model incorporates the ICE BofA High Yield Master II Option-Adjusted Spread as a proxy for credit market stress.
Threshold Calibration:
- Normal conditions: < 350 basis points
- Elevated risk: 350-500 basis points
- Severe stress: > 500 basis points
#### Currency and Commodity Stress Indicators
The US Dollar Index (DXY) momentum serves as a risk-off indicator, while the Gold-to-Oil ratio captures commodity market stress dynamics. This approach follows the methodology of Akram (2009) and Beckmann, Berger, and Czudaj (2015) in analyzing commodity-currency relationships during market stress.
### 2. Technical Analysis Factors
#### Multi-Timeframe Moving Average Analysis
The technical component incorporates the well-established moving average convergence methodology, drawing from the work of Brock, Lakonishok, and LeBaron (1992), who provided empirical evidence for the profitability of technical trading rules.
Implementation:
- Price relative to 50-day and 200-day simple moving averages
- Moving average convergence/divergence analysis
- Multi-timeframe MACD assessment (daily and weekly)
#### Momentum and Volatility Analysis
The model integrates Relative Strength Index (RSI) analysis following Wilder's (1978) original methodology, combined with maximum drawdown analysis based on the work of Magdon-Ismail and Atiya (2004) on optimal drawdown measurement.
### 3. Market Sentiment Factors
#### Volatility Index Analysis
The VIX component follows the established research of Whaley (2009) and subsequent work by Bekaert and Hoerova (2014) on VIX as a predictor of market stress. The model incorporates both absolute VIX levels and relative VIX spikes compared to the 20-day moving average.
Calibration:
- Low volatility: VIX < 20
- Elevated concern: VIX 20-25
- High fear: VIX > 25
- Panic conditions: VIX > 30
#### Put-Call Ratio Analysis
Options flow analysis through put-call ratios provides insight into sophisticated investor positioning, following the methodology established by Pan and Poteshman (2006) in their analysis of informed trading in options markets.
### 4. Market Breadth Factors
#### Advance-Decline Analysis
Market breadth assessment follows the classic work of Fosback (1976) and subsequent research by Brown and Cliff (2004) on market breadth as a predictor of future returns.
Components:
- Daily advance-decline ratio
- Advance-decline line momentum
- McClellan Oscillator (Ema19 - Ema39 of A-D difference)
#### New Highs-New Lows Analysis
The new highs-new lows ratio serves as a market leadership indicator, based on the research of Zweig (1986) and validated in academic literature by Zarowin (1990).
## Dynamic Threshold Methodology
The model incorporates adaptive thresholds based on rolling volatility and trend analysis, following the methodology established by Pagan and Sossounov (2003) for business cycle dating. This approach allows the model to adjust sensitivity based on prevailing market conditions.
Dynamic Threshold Calculation:
- Warning Level: Base threshold ± (Volatility × 1.0)
- Danger Level: Base threshold ± (Volatility × 1.5)
- Bounds: ±10-20 points from base threshold
## Professional Implementation
### Institutional Usage Patterns
Professional risk managers typically employ multi-factor bear market models in several contexts:
#### 1. Portfolio Risk Management
- Tactical Asset Allocation: Reducing equity exposure when probability exceeds 60-70%
- Hedging Strategies: Implementing protective puts or VIX calls when warning thresholds are breached
- Sector Rotation: Shifting from growth to defensive sectors during elevated risk periods
#### 2. Risk Budgeting
- Value-at-Risk Adjustment: Incorporating bear market probability into VaR calculations
- Stress Testing: Using probability levels to calibrate stress test scenarios
- Capital Requirements: Adjusting regulatory capital based on systemic risk assessment
#### 3. Client Communication
- Risk Reporting: Quantifying market risk for client presentations
- Investment Committee Decisions: Providing objective risk metrics for strategic decisions
- Performance Attribution: Explaining defensive positioning during market stress
### Implementation Framework
Professional traders typically implement such models through:
#### Signal Hierarchy:
1. Probability < 30%: Normal risk positioning
2. Probability 30-50%: Increased hedging, reduced leverage
3. Probability 50-70%: Defensive positioning, cash building
4. Probability > 70%: Maximum defensive posture, short exposure consideration
#### Risk Management Integration:
- Position Sizing: Inverse relationship between probability and position size
- Stop-Loss Adjustment: Tighter stops during elevated risk periods
- Correlation Monitoring: Increased attention to cross-asset correlations
## Strengths and Advantages
### 1. Comprehensive Coverage
The model's primary strength lies in its multi-dimensional approach, avoiding the single-factor bias that has historically plagued market timing models. By incorporating macroeconomic, technical, sentiment, and breadth factors, the model provides robust risk assessment across different market regimes.
### 2. Dynamic Adaptability
The adaptive threshold mechanism allows the model to adjust sensitivity based on prevailing volatility conditions, reducing false signals during low-volatility periods and maintaining sensitivity during high-volatility regimes.
### 3. Real-Time Processing
Unlike traditional academic models that rely on monthly or quarterly data, this indicator processes daily market data, providing timely risk assessment for active portfolio management.
### 4. Transparency and Interpretability
The component-based structure allows users to understand which factors are driving risk assessment, enabling informed decision-making about model signals.
### 5. Historical Validation
Each component has been validated in academic literature, providing theoretical foundation for the model's predictive power.
## Limitations and Weaknesses
### 1. Data Dependencies
The model's effectiveness depends heavily on the availability and quality of real-time economic data. Federal Reserve Economic Data (FRED) updates may have lags that could impact model responsiveness during rapidly evolving market conditions.
### 2. Regime Change Sensitivity
Like most quantitative models, the indicator may struggle during unprecedented market conditions or structural regime changes where historical relationships break down (Taleb, 2007).
### 3. False Signal Risk
Multi-factor models inherently face the challenge of balancing sensitivity with specificity. The model may generate false positive signals during normal market volatility periods.
### 4. Currency and Geographic Bias
The model focuses primarily on US market indicators, potentially limiting its effectiveness for global portfolio management or non-USD denominated assets.
### 5. Correlation Breakdown
During extreme market stress, correlations between risk factors may increase dramatically, reducing the model's diversification benefits (Forbes and Rigobon, 2002).
## References
Akram, Q. F. (2009). Commodity prices, interest rates and the dollar. Energy Economics, 31(6), 838-851.
Ang, A., Piazzesi, M., & Wei, M. (2006). What does the yield curve tell us about GDP growth? Journal of Econometrics, 131(1-2), 359-403.
Baker, M., & Wurgler, J. (2006). Investor sentiment and the cross‐section of stock returns. The Journal of Finance, 61(4), 1645-1680.
Baker, S. R., Bloom, N., & Davis, S. J. (2016). Measuring economic policy uncertainty. The Quarterly Journal of Economics, 131(4), 1593-1636.
Barber, B. M., & Odean, T. (2001). Boys will be boys: Gender, overconfidence, and common stock investment. The Quarterly Journal of Economics, 116(1), 261-292.
Beckmann, J., Berger, T., & Czudaj, R. (2015). Does gold act as a hedge or a safe haven for stocks? A smooth transition approach. Economic Modelling, 48, 16-24.
Bekaert, G., & Hoerova, M. (2014). The VIX, the variance premium and stock market volatility. Journal of Econometrics, 183(2), 181-192.
Brock, W., Lakonishok, J., & LeBaron, B. (1992). Simple technical trading rules and the stochastic properties of stock returns. The Journal of Finance, 47(5), 1731-1764.
Brown, G. W., & Cliff, M. T. (2004). Investor sentiment and the near-term stock market. Journal of Empirical Finance, 11(1), 1-27.
Campbell, J. Y., & Shiller, R. J. (1998). Valuation ratios and the long-run stock market outlook. The Journal of Portfolio Management, 24(2), 11-26.
Dow, C. H. (1901). Scientific stock speculation. The Magazine of Wall Street.
Estrella, A., & Mishkin, F. S. (1998). Predicting US recessions: Financial variables as leading indicators. Review of Economics and Statistics, 80(1), 45-61.
Fama, E. F., & French, K. R. (1989). Business conditions and expected returns on stocks and bonds. Journal of Financial Economics, 25(1), 23-49.
Forbes, K. J., & Rigobon, R. (2002). No contagion, only interdependence: measuring stock market comovements. The Journal of Finance, 57(5), 2223-2261.
Fosback, N. G. (1976). Stock market logic: A sophisticated approach to profits on Wall Street. The Institute for Econometric Research.
Gilchrist, S., & Zakrajšek, E. (2012). Credit spreads and business cycle fluctuations. American Economic Review, 102(4), 1692-1720.
Harvey, C. R. (1988). The real term structure and consumption growth. Journal of Financial Economics, 22(2), 305-333.
Kahneman, D., & Tversky, A. (1979). Prospect theory: An analysis of decision under risk. Econometrica, 47(2), 263-291.
Magdon-Ismail, M., & Atiya, A. F. (2004). Maximum drawdown. Risk, 17(10), 99-102.
Nickerson, R. S. (1998). Confirmation bias: A ubiquitous phenomenon in many guises. Review of General Psychology, 2(2), 175-220.
Pagan, A. R., & Sossounov, K. A. (2003). A simple framework for analysing bull and bear markets. Journal of Applied Econometrics, 18(1), 23-46.
Pan, J., & Poteshman, A. M. (2006). The information in option volume for future stock prices. The Review of Financial Studies, 19(3), 871-908.
Taleb, N. N. (2007). The black swan: The impact of the highly improbable. Random House.
Whaley, R. E. (2009). Understanding the VIX. The Journal of Portfolio Management, 35(3), 98-105.
Wilder, J. W. (1978). New concepts in technical trading systems. Trend Research.
Zarowin, P. (1990). Size, seasonality, and stock market overreaction. Journal of Financial and Quantitative Analysis, 25(1), 113-125.
Zweig, M. E. (1986). Winning on Wall Street. Warner Books.
Uptrick: Dynamic Z-Score DeviationOverview
Uptrick: Dynamic Z‑Score Deviation is a trading indicator built in Pine Script that combines statistical filters and adaptive smoothing to highlight potential reversal points in price action. It combines a hybrid moving average, dual Z‑Score analysis on both price and RSI, and visual enhancements like slope‑based coloring, ATR‑based shadow bands, and dynamically scaled reversal signals.
Introduction
Statistical indicators like Z‑Scores measure how far a value deviates from its average relative to the typical variation (standard deviation). Standard deviation quantifies how dispersed a set of values is around its mean. A Z‑Score of +2 indicates a value two standard deviations above the mean, while -2 is two below. Traders use Z‑Scores to spot unusually high or low readings that may signal overbought or oversold conditions.
Moving averages smooth out price data to reveal trends. The Arnaud Legoux Moving Average (ALMA) reduces lag and noise through weighted averaging. A Zero‑Lag EMA (approximated here using a time‑shifted EMA) seeks to further minimize delay in following price. The RSI (Relative Strength Index) is a momentum oscillator that measures recent gains against losses over a set period.
ATR (Average True Range) gauges market volatility by averaging the range between high and low over a lookback period. Shadow bands built using ATR give a visual mood of volatility around a central trend line. Together, these tools inform a dynamic but statistically grounded view of market extremes.
Purpose
The main goal of this indicator is to help traders spot short‑term reversal opportunities on lower timeframes. By requiring both price and momentum (RSI) to exhibit statistically significant deviations from their norms, it filters out weak setups and focuses on higher‑probability mean‑reversion zones. Reversal signals appear when price deviates far enough from its hybrid moving average and RSI deviates similarly in the same direction. This makes it suitable for discretionary traders seeking clean entry cues in volatile environments.
Originality and Uniqueness
Uptrick: Dynamic Z‑Score Deviation distinguishes itself from standard reversal or mean‑reversion tools by combining several elements into a single framework:
A composite moving average (ALMA + Zero‑Lag EMA) for a smooth yet responsive baseline
Dual Z‑Score filters on price and RSI rather than relying on a single measure
Adaptive visual elements, including slope‑aware coloring, multi‑layer ATR shadows, and signal sizing based on combined Z‑Score magnitude
Most indicators focus on one aspect—price envelopes or RSI thresholds—whereas Uptrick: Dynamic Z‑Score Deviation requires both layers to align before signaling. Its visual design aids quick interpretation without overwhelming the chart.
Why these indicators were merged
Every component in Uptrick: Dynamic Z‑Score Deviation has a purpose:
• ALMA: provides a smooth moving average with reduced lag and fewer false crossovers than a simple SMA or EMA.
• Zero‑Lag EMA (ZLMA approximation): further reduces the delay relative to price by applying a time shift to EMA inputs. This keeps the composite MA closer to current price action.
• RSI and its EMA filter: RSI measures momentum. Applying an EMA filter on RSI smooths out false spikes and confirms genuine overbought or oversold momentum.
• Dual Z‑Scores: computing Z‑Scores on both the distance between price and the composite MA, and on smoothed RSI, ensures that signals only fire when both price and momentum are unusually stretched.
• ATR bands: using ATR‑based shadow layers visualizes volatility around the MA, guiding traders on potential support and resistance zones.
At the end, these pieces merge into a single indicator that detects statistically significant mean reversions while staying adaptive to real‑time volatility and momentum.
Calculations
1. Compute ALMA over the chosen MA length, offset, and sigma.
2. Approximate ZLMA by applying EMA to twice the price minus the price shifted by the MA length.
3. Calculate the composite moving average as the average of ALMA and ZLMA.
4. Compute raw RSI and smooth it with ALMA. Apply an EMA filter to raw RSI to reduce noise.
5. For both price and smoothed RSI, calculate the mean and standard deviation over the Z‑Score lookback period.
6. Compute Z‑Scores:
• z_price = (current price − composite MA mean) / standard deviation of price deviations
• z_rsi = (smoothed RSI − mean RSI) / standard deviation of RSI
7. Determine reversal conditions: both Z‑Scores exceed their thresholds in the same direction, RSI EMA is in oversold/overbought zones (below 40 or above 60), and price movement confirms directionality.
8. Compute signal strength as the sum of the absolute Z‑Scores, then classify into weak, medium, or strong.
9. Calculate ATR over the chosen period and multiply by layer multipliers to form shadow widths.
10.Derive slope over the chosen slope length and color the MA line and bars based on direction, optionally smoothing color transitions via EMA on RGB channels.
How this indicator actually works
1. The script begins by smoothing price data with ALMA and approximating a zero‑lag EMA, then averaging them for the main MA.
2. RSI is calculated, then smoothed and filtered.
3. Using a rolling window, the script computes statistical measures for both price deviations and RSI.
4. Z‑Scores tell how far current values lie from their recent norms.
5. When both Z‑Scores cross configured thresholds and momentum conditions align, reversal signals are flagged.
6. Signals are drawn with size and color reflecting strength.
7. The MA is plotted with dynamic coloring; ATR shadows are layered beneath to show volatility envelopes.
8. Bars can be colored to match MA slope, reinforcing trend context.
9. Alert conditions allow automated notifications when signals occur.
Inputs
Main Length: Main MA Length. Sets the period for ALMA and ZLMA.
RSI Length: RSI Length. Determines the lookback for momentum calculations.
Z-Score Lookback: Z‑Score Lookback. Window for mean and standard deviation computations.
Price Z-Score Threshold: Price Z‑Score Threshold. Minimum deviation required for price.
RSI Z-Score threshold: RSI Z‑Score Threshold. Minimum deviation required for momentum.
RSI EMA Filter Length: RSI EMA Filter Length. Smooths raw RSI readings.
ALMA Offset: Controls ALMA’s focal point in the window.
ALMA Sigma: Adjusts ALMA’s smoothing strength.
Show Reversal Signals : Toggle to display reversal signal markers.
Slope Sensitivity: Length for slope calculation. Higher values smooth slope changes.
Use Bar Coloring: Enables coloring of price bars based on MA slope.
Show MA Shadow: Toggle for ATR‑based shadow bands.
Shadow Layer Count: Number of shadow layers (1–4).
Base Shadow ATR Multiplier: Multiplier for ATR when sizing the first band.
Smooth Color Transitions (boolean): Smooths RGB transitions for line and shadows, if enabled.
ATR Length for Shadow: ATR Period for computing volatility bands.
Use Dynamic Signal Size: Toggles dynamic scaling of reversal symbols.
Features
Moving average smoothing: a hybrid of ALMA and Zero‑Lag EMA that balances responsiveness and noise reduction.
Slope coloring: MA line and optionally price bars change color based on trend direction; color transitions can be smoothed for visual continuity.
ATR shadow layers: translucent bands around the MA show volatility envelopes; up to four concentric layers help gauge distance from normal price swings.
Dual Z‑Score filters: price and momentum must both deviate beyond thresholds to trigger signals, reducing false positives.
Dynamic signal sizing: reversal markers scale in size based on the combined Z‑Score magnitude, making stronger signals more prominent.
Adaptive visuals: optional smoothing of color channels creates gradient effects on lines and fills for a polished look.
Alert conditions: built‑in buy and sell alerts notify traders when reversal setups emerge.
Conclusion
Uptrick: Dynamic Z‑Score Deviation delivers a structured way to identify short‑term reversal opportunities by fusing statistical rigor with adaptive smoothing and clear visual cues. It guides traders through multiple confirmation layers—hybrid moving average, dual Z‑Score analysis, momentum filtering, and volatility envelopes—while keeping the chart clean and informative.
Disclaimer
This indicator is provided for informational and educational purposes only and does not constitute financial advice. Trading carries risk and may not be suitable for all participants. Past performance is not indicative of future results. Always do your own analysis and risk management before making trading decisions.
Compare Strength with SLOPE Description
This indicator compares the relative strength between the current asset and a benchmark (e.g., BTC vs. ETH or AAPL vs. SPY) using a linear regression slope of their ratio over time.
The ratio is calculated as: close / benchmark
A linear regression slope is computed over a user-defined window
The slope represents trend strength: if it’s rising, the current asset is outperforming the benchmark
Plots
Gray Line: The raw ratio between the asset and benchmark
Orange Line: The slope of the ratio (shows momentum)
Background Color :
Green: The asset is significantly stronger than the benchmark
Red: The asset is significantly weaker than the benchmark
No color: No clear trend
Settings
Slope Window Length: Number of candles used in the regression (default = 10)
Slope Threshold: Sensitivity of trend detection. Smaller values detect weaker trends.
Example Use Cases
Style Rotation Strategy: Use the slope to determine whether "Growth" or "Value" style is leading.
Pair Trading / Relative Performance: Track which asset is leading in a pair (e.g., BTC vs ETH).
Factor Timing: Serve as a timing model to allocate between different sectors or factors.
Happy trading!
[blackcat] L3 Dark Horse OscillatorOVERVIEW
The L3 Dark Horse Oscillator is a sophisticated technical indicator meticulously crafted to offer traders deep insights into market momentum. By leveraging advanced calculations involving Relative Strength Value (RSV) and proprietary oscillatory techniques, this script provides clear and actionable signals for identifying potential buying and selling opportunities. Its distinctive feature—a vibrant gradient color scheme—enhances readability and makes it easier to visualize trends and reversals on the chart 📈↗️.
FEATURES
Advanced Calculation Methods: Utilizes complex algorithms to compute the Relative Strength Value (RSV) over specific periods, providing a nuanced view of price movements.
Default Period: 27 bars for initial RSV calculation.
Additional Period: 36 bars for extended RSV analysis.
Dual-Oscillator Components:
Component A: Derived using multiple layers of Simple Moving Averages (SMAs) applied to the RSV, offering a smoothed representation of short-term momentum.
Component B: Employs a unique averaging method tailored to capture medium-term trends effectively.
Dynamic Gradient Color Scheme: Enhances visualization through a spectrum of colors that change dynamically based on the calculated values, making trend identification intuitive and engaging 🌈.
Customizable Horizontal Reference Lines: Key levels are marked at 0, 10, 50, and 90 to serve as benchmarks for assessing the oscillator's readings, helping traders make informed decisions quickly.
Comprehensive Visual Representation: Combines the strengths of both components into a single, gradient-colored candlestick plot, providing a holistic view of market sentiment and momentum shifts 📊.
HOW TO USE
Adding the Indicator: Start by adding the L3 Dark Horse Oscillator to your TradingView chart via the indicators menu. This will overlay the necessary plots directly onto your price chart.
Interpreting the Components: Familiarize yourself with the two primary components represented by yellow and fuchsia lines. These lines indicate the underlying momentum derived from the RSV calculations.
Monitoring Momentum Shifts: Pay close attention to the gradient-colored candlesticks, which reflect the combined strength of both components. Notice how these candles transition through various shades, signaling changes in market dynamics.
Utilizing Reference Levels: Leverage the horizontal lines at 0, 10, 50, and 90 as critical thresholds. For instance, values above 50 might suggest bullish conditions, while those below could hint at bearish tendencies.
Combining with Other Tools: To enhance reliability, integrate this indicator with complementary technical analyses such as moving averages, volume profiles, or other oscillators like RSI or MACD.
LIMITATIONS
Market Volatility: In extremely volatile or sideways-trending markets, the indicator might produce false signals due to erratic price movements. Always cross-reference with broader market contexts.
Testing Required: Before deploying the indicator in real-time trading, conduct thorough backtesting across diverse assets and timeframes to understand its performance characteristics fully.
Asset-Specific Performance: The efficacy of the L3 Dark Horse Oscillator can differ significantly across various financial instruments and market conditions. Tailor your strategies accordingly.
NOTES
Historical Data: Ensure ample historical data availability to facilitate precise calculations and avoid inaccuracies stemming from insufficient data points.
Parameter Adjustments: Experiment with adjusting the default periods (27 and 36 bars) if you find them unsuitable for your specific trading style or market conditions.
Visual Customization: Modify the appearance settings, including line styles and gradient colors, to better suit personal preferences without compromising functionality.
Risk Management: While the indicator offers valuable insights, always adhere to robust risk management practices to safeguard against unexpected market fluctuations.
EXAMPLE STRATEGIES
Trend Following: Use the oscillator to confirm existing trends. When Component A crosses above Component B, consider entering long positions; conversely, look for short entries during downward crossovers.
Mean Reversion: Identify extreme readings near the upper (90) or lower (10) bands where prices might revert to mean levels, presenting potential reversal opportunities.
Divergence Analysis: Compare the oscillator's behavior with price action to spot divergences, which often precede trend reversals. Bullish divergence occurs when prices make lower lows but the oscillator shows higher lows, suggesting upward momentum.
RSI and CCICombined RSI and CCI Indicator for MetaTrader
The Combined RSI and CCI Indicator is a powerful hybrid momentum oscillator designed to merge the strengths of two popular indicators—the Relative Strength Index (RSI) and the Commodity Channel Index (CCI)—into a single, visually intuitive chart window. This tool enhances traders’ ability to identify overbought and oversold conditions, divergences, trend strength, and potential reversal zones with improved precision.
Purpose
By integrating RSI and CCI, this indicator helps filter out false signals that often occur when using each tool independently. It is especially useful for swing trading, trend confirmation, and spotting high-probability entry/exit zones. This dual-oscillator approach combines RSI’s relative momentum insights with CCI’s deviation-based analysis to produce a more reliable signal structure.
Key Features
Dual Oscillator Display: Plots both RSI and CCI on the same subwindow for easy comparison and correlation analysis.
Customizable Parameters:
RSI Period and Level (default: 14)
CCI Period and Typical Price Type (default: 20, TP)
Overbought/Oversold Levels for both indicators
Color-Coded Zones:
Background highlights when both RSI and CCI enter overbought/oversold territory, signaling high potential reversal zones.
Combined Signal Logic (Optional Feature):
Buy Signal: RSI < 30 and CCI < -100
Sell Signal: RSI > 70 and CCI > 100
These can be visualized as arrows or plotted as signal markers.
Trend Filter Overlay (Optional):
Can be combined with a moving average or price action filter to confirm trend direction before accepting signals.
Divergence Detection (Advanced Option):
Optional plotting of bullish or bearish divergence where both indicators diverge from price action.
Multi-Timeframe Compatibility:
Allows the use of higher timeframe RSI/CCI values to confirm signals on lower timeframes.
Benefits
Improved Signal Accuracy: Using both RSI and CCI together helps avoid false breakouts and whipsaws.
More Informed Decision-Making: Correlating momentum (RSI) with deviation (CCI) provides a well-rounded picture of market behavior.
Efficient Charting: Saves screen space and cognitive load by combining two indicators into one clean panel.
Scalable Strategy Integration: Can be used in discretionary trading or coded into automated strategies/alerts.
Use Case Example
In a ranging market, the indicator highlights zones where both RSI and CCI are oversold, alerting traders to potential bounce opportunities.
In trending markets, it confirms trend strength when RSI and CCI are both aligned with trend direction.
When RSI is diverging from price but CCI isn’t, it can be a clue of weakening momentum, helping traders scale out or avoid traps.
This combined indicator offers a versatile, high-performance toolset for traders looking to elevate their technical analysis by leveraging multiple momentum perspectives simultaneously.
Trend Strength MeterThe Trend Strength Meter (TSM) is a powerful and versatile indicator designed to help traders identify market trends, measure their strength, and detect potential reversals with ease. This indicator combines the power of moving averages, divergence detection, and a clean, customizable dashboard to provide actionable insights for traders of all levels.
How It Works
Trend Strength Calculation:
1. The TSM calculates the trend strength using the difference between two Exponential Moving Averages (EMAs): a fast EMA (default: 20) and a slow EMA (default: 50).
2. The difference is expressed as a percentage of the slow EMA, providing a clear measure of the trend's strength and direction.
Histogram Visualization:
1. A color-coded histogram visually represents the trend strength:
Green: Bullish trend
Red: Bearish trend
Gray: Neutral or no significant trend
2. A smoothed trend strength line (SMA of the trend strength) is also plotted for better clarity.
Divergence Detection:
1. The indicator detects bullish and bearish divergences using the RSI (Relative Strength Index) and price action.
2. Bullish Divergence: Price makes a lower low, but RSI makes a higher low, signaling potential upward momentum.
3. Bearish Divergence: Price makes a higher high, but RSI makes a lower high, signaling potential downward momentum.
=> Divergences are marked with arrows on the chart:
Green Arrow: Bullish divergence
Red Arrow: Bearish divergence
Dashboard:
1. A clean and informative dashboard displays key information:
Trend Strength Value: The current strength of the trend
Trend Direction: Bullish, Bearish, or Neutral
Last Signal: Buy, Sell, or None (based on divergence signals)
The dashboard is fully customizable and can be positioned anywhere on the chart (e.g., top-right, bottom-left, center, etc.).
Key Features
1. Trend Strength Measurement: Quickly identify the strength and direction of the trend.
2. Divergence Detection: Spot potential reversals before they occur with bullish and bearish divergence signals.
3. Customizable Dashboard: Move the dashboard to your preferred location on the chart for better visibility.
4. User-Friendly Design: Clean visuals and intuitive color coding make it easy to interpret market conditions.
5. Actionable Signals: Provides clear Buy/Sell signals based on divergence, helping traders make informed decisions.
How to Use
1. Trend Confirmation:
Use the histogram and trend strength value to confirm the current market trend.
Green bars indicate a bullish trend, while red bars indicate a bearish trend.
2. Divergence Signals:
Look for divergence arrows (green for bullish, red for bearish) to anticipate potential reversals.
Combine divergence signals with other technical analysis tools for higher accuracy.
3. Dashboard Insights:
Monitor the dashboard for real-time updates on trend strength, direction, and the latest signal.
Use the "Last Signal" (Buy/Sell) to validate your trading decisions.
4. Custom Settings:
Adjust the EMA lengths and divergence lookback period to suit your trading style and timeframe.
Position the dashboard anywhere on the chart for convenience.
Best Practices
1. Use the TSM in conjunction with other indicators or price action analysis for confirmation.
2. Test the indicator on different timeframes to find the one that works best for your strategy.
3. Always practice proper risk management when trading.
Disclaimer
This indicator is a tool to assist in technical analysis and should not be used as a standalone trading strategy. Past performance is not indicative of future results. Always conduct your own research and consult with a financial advisor before making trading decisions.
alphaJohnny Dynamic RSI IndicatorAlphaJohnny Dynamic RSI Indicator (Dyn RSI)
The Dynamic RSI Indicator (Dyn RSI) is a custom Pine Script tool designed for TradingView that aggregates Relative Strength Index (RSI) signals from multiple timeframes to provide a comprehensive view of market momentum. It combines RSI data from Weekly, Daily, 4-hour, 1-hour, and 30-minute intervals, offering traders a flexible and customizable way to analyze trends across different periods.
Key Features:
Multi-Timeframe RSI Aggregation: Combines RSI signals from user-selected timeframes for a holistic momentum assessment.
Dynamic or Equal Weighting: Choose between correlation-based dynamic weights (adjusting based on each timeframe’s correlation with price changes) or equal weights for simplicity.
Smoothed Momentum Line: A visually intuitive line that reflects the strength of the aggregate signal, smoothed for clarity.
Color-Coded Signal Strength:
Dark Green: Strong buy signal
Light Green: Weak buy signal
Yellow: Neutral
Light Red: Weak sell signal
Dark Red: Strong sell signal
Visual Markers: Large green triangles at the bottom for strong buy signals and red triangles at the top for strong sell signals.
How to Use:
Apply to Chart: Add the indicator to your TradingView chart (it will appear in a separate pane).
Customize Settings: Adjust inputs like RSI period, signal thresholds, included timeframes, weighting method, and smoothing period to fit your trading style.
Interpret Signals:
Momentum Line: Watch for color changes to gauge market conditions.
Triangles: Green at the bottom for strong buy opportunities, red at the top for strong sell opportunities.
Notes:
The indicator is designed for a separate pane (overlay=false), with triangles positioned relative to the pane’s range.
Fine-tune thresholds and weights based on your strategy and the asset being analyzed.
The source code is open for modification to suit your needs.
This indicator is ideal for traders seeking a multi-timeframe perspective on RSI to identify potential trend reversals and momentum shifts.
Dynamic Currency Strength IndexDescription:
This indicator calculates the relative strength of the base currency and quote currency of the currently selected forex pair. Instead of just using a single pair comparison (e.g., GBPUSD - AUDUSD), it determines currency strength using a basket of related pairs, making it more accurate and useful for trading decisions.
How It Works:
Extracts the base and quote currencies from the selected forex pair.
Calculates their individual strengths using multiple related forex pairs.
Displays the strength difference between the base and quote currencies.
How to Use:
✔️ If the strength difference is positive, the base currency is stronger → Bullish signal.
✔️ If the strength difference is negative, the quote currency is stronger → Bearish signal.
✔️ Use it to confirm trends, filter trades, and improve entry timing in forex trading.
💡 Ideal for traders using trend-based strategies (Dow Theory, HH-HL patterns, breakouts, etc.).
Bollinger Bands + RSI [Uncle Sam Trading]The Bollinger Bands + RSI indicator combines two popular technical analysis tools, Bollinger Bands (BB) and the Relative Strength Index (RSI), into a unified framework designed to assess both market volatility and momentum. This indicator provides both visual signals on the chart, and allows you to set alerts. It is intended to help traders identify potential overbought/oversold conditions, trend reversals, and to refine trade entry and exit points.
Key Features:
Bollinger Bands: The indicator plots Bollinger Bands, which consist of a basis line (typically a 20-period Simple Moving Average), an upper band (basis + 2 standard deviations), and a lower band (basis - 2 standard deviations). The bands dynamically adjust to market volatility, widening during periods of increased volatility and contracting during periods of decreased volatility.
Relative Strength Index (RSI): The RSI, a momentum oscillator, is plotted in a separate pane below the price chart. It measures the magnitude of recent price changes to evaluate overbought or oversold conditions in the price of a stock or other asset. Traditional interpretation uses 70 and 30 as overbought and oversold levels, respectively.
Overbought/Oversold Zones Highlighting: This indicator uniquely highlights overbought and oversold zones directly on the price chart based on the RSI values. When the RSI is above the overbought level (default 70), a red-shaded area is displayed. When the RSI is below the oversold level (default 30), a green-shaded area is displayed. These visual cues enhance the identification of potential trend reversals.
Buy and Sell Signals: The indicator generates buy signals when the price crosses above the lower Bollinger Band and the RSI is below the oversold level (if the RSI filter is enabled). Sell signals are generated when the price crosses below the upper Bollinger Band and the RSI is above the overbought level (if the RSI filter is enabled). These signals are plotted as green upward-pointing triangles (buy) and red downward-pointing triangles (sell) on the chart.
Customizable Parameters: Users can adjust various settings, including:
Bollinger Bands Length: The number of periods used to calculate the moving average and standard deviation.
Bollinger Bands Standard Deviation: The multiplier used to determine the distance of the upper and lower bands from the basis.
RSI Length: The number of periods used to calculate the RSI.
RSI Overbought/Oversold Levels: The threshold values that define overbought and oversold conditions for the RSI.
Use RSI Filter for Signals: Enable/disable the RSI filter for buy and sell signals.
Colors: The colors of the Bollinger Bands, RSI, overbought/oversold levels, and zone highlights can be customized to suit user preferences.
Alerts: The indicator supports customizable alerts for various conditions, including:
Buy Signal: Triggered when a buy signal is generated.
Sell Signal: Triggered when a sell signal is generated.
Price Crossed Upper BB: Triggered when the price crosses above the upper Bollinger Band.
Price Crossed Lower BB: Triggered when the price crosses below the lower Bollinger Band.
RSI Overbought: Triggered when the RSI crosses above the overbought level.
RSI Oversold: Triggered when the RSI crosses below the oversold level.
How to Use:
The Bollinger Bands + RSI indicator can be used in various ways, including:
Identifying Potential Trend Reversals: Price crosses above the lower band coupled with an oversold RSI (and highlighted zone) may signal a bullish reversal. Conversely, a price cross below the upper band with an overbought RSI (and highlighted zone) may indicate a bearish reversal.
Confirming Trend Strength: In an uptrend, the price may "ride" the upper band, while in a downtrend, it may "ride" the lower band.
Exit Signals: Crossing the opposite band while in a trade, particularly with confirming RSI signals, is often used to identify potential exit points.
Combined with Other Analysis: This indicator works well in conjunction with other technical analysis tools, such as trend lines, support/resistance levels, chart patterns, and moving average-based strategies.
Disclaimer:
This indicator is for educational and informational purposes only and should not be considered as financial advice. Trading involves risk, and past performance is not indicative of future results. Always conduct thorough research and consider your risk tolerance before making any trading decisions.
Custom RSI & MACD Momentum Entry SignalsIndicator Explanation: Custom RSI & MACD Momentum Entry Signals
Introduction
The "Custom RSI & MACD Momentum Entry Signals" indicator combines the Relative Strength Index (RSI) and the Moving Average Convergence Divergence (MACD) to generate precise long and short entry signals. This indicator offers a powerful combination of overbought/oversold zones, momentum analysis, and RSI-EMA crossovers to assist traders in making better decisions.
How the Indicator Works
1. RSI Calculation and EMA
The RSI is calculated based on the closing price with an adjustable period (default: 14).
An Exponential Moving Average (EMA) of the RSI (default: 9) is plotted to identify RSI trend changes.
When the RSI crosses its EMA upwards, it signals a bullish impulse. Conversely, a downward cross indicates a bearish impulse.
2. MACD Calculation and Momentum Shifts
The MACD line is derived from the difference between a fast EMA (default: 12) and a slow EMA (default: 26).
The Signal line is the EMA of the MACD line (default: 9).
The MACD histogram represents the difference between the MACD line and the Signal line.
Momentum shifts are detected as follows:
Weakening Bearish: Histogram is negative but increasing (less bearish pressure).
Strengthening Bullish: Histogram is positive and rising.
Weakening Bullish: Histogram is positive but decreasing.
Strengthening Bearish: Histogram is negative and falling.
Signal Generation
Long Signals
A Long signal is triggered when all of the following conditions are met:
The RSI was previously below 30 (oversold condition).
MACD momentum shifts from "strengthening bearish" to "weakening bearish" or turns bullish.
The RSI crosses its EMA upwards.
A green upward arrow is displayed below the bar, and the background is lightly shaded green for additional visualization.
Short Signals
A Short signal is triggered when all of the following conditions are met:
The RSI was previously above 70 (overbought condition).
MACD momentum shifts from "strengthening bullish" to "weakening bullish" or turns bearish.
The RSI crosses its EMA downwards.
A red downward arrow is displayed above the bar, and the background is lightly shaded red for additional visualization.
Visual Elements
RSI and EMA:
The RSI is shown in purple.
The RSI EMA is shown in blue.
Horizontal lines at 30 (oversold) and 70 (overbought) provide additional context.
MACD:
The MACD line is displayed in blue.
The Signal line is displayed in orange.
The zero line is added for easier interpretation.
Signals:
Green arrows: Long signals.
Red arrows: Short signals.
Background color: Light green for long conditions, light red for short conditions.
Use Cases
This indicator is ideal for:
Trend Followers: Combining RSI and MACD allows traders to identify entry points during impulsive trend shifts.
Swing Traders: Long and short signals can be used at reversal points to capture short-term price movements.
Momentum Traders: By considering MACD momentum, the indicator provides additional confidence in signal generation.
Customizable Settings
The indicator provides flexible input options:
RSI Period (default: 14)
RSI EMA Period (default: 9)
MACD Parameters: Fast, slow, and signal EMAs can be adjusted.
Conclusion
The Custom RSI & MACD Momentum Entry Signals indicator is a powerful tool for traders looking to combine RSI and MACD to identify high-probability entry signals. With clear visualization and precise signal generation, traders can make decisions more efficiently and capitalize on market movements.
XAUUSD Multi-Timeframe Trend AnalyzerOverview
The "XAUUSD Multi-Timeframe Trend Analyzer" is an advanced script designed to provide a comprehensive analysis of the XAUUSD (Gold/US Dollar) trend across multiple timeframes simultaneously. By combining several key technical indicators, this tool helps traders quickly assess the market direction and trend strength for M15, M30, H1, H4, and D1 timeframes.
Multi-Timeframe Analysis: Displays the trend direction and strength across M15, M30, H1, H4, and D1 timeframes, allowing for a complete overview in a single glance.
Comprehensive Indicator Blend: Utilizes six popular technical indicators to determine the trend—Moving Averages, RSI, MACD, Bollinger Bands, DMI, and Parabolic SAR.
Trend Strength Scoring: Provides a numerical trend strength score (from -6 to 6) based on the alignment of the indicators, with positive values indicating uptrends and negative values for downtrends.
Visual Table Display: Displays results in a color-coded table (green for uptrend, red for downtrend, yellow for neutral) with a strength score for each timeframe, helping traders quickly assess market conditions.
How It Works
This script calculates the overall trend and its strength for each selected timeframe by analyzing six widely-used technical indicators:
Moving Averages (MA): The script uses a Fast and a Slow Moving Average. When the Fast MA crosses above the Slow MA, it indicates an uptrend. When the Fast MA crosses below, it signals a downtrend.
Relative Strength Index (RSI): The RSI is used to assess momentum. An RSI value above 50 suggests bullish momentum, while a value below 50 suggests bearish momentum.
Moving Average Convergence Divergence (MACD): MACD measures momentum and trend direction. When the MACD line crosses above the signal line, it signals bullish momentum; when it crosses below, it signals bearish momentum.
Bollinger Bands: These measure price volatility. When the price is above the middle Bollinger Band, the script considers the trend to be bullish, and when it's below, bearish.
Directional Movement Index (DMI): The DMI compares positive directional movement (DI+) and negative directional movement (DI-). A stronger DI+ over DI- signals an uptrend and vice versa.
Parabolic SAR: This indicator is used for determining potential trend reversals and setting stop-loss levels. If the price is above the Parabolic SAR, it indicates an uptrend, and if below, a downtrend.
Trend Strength Calculation
The script calculates a trend strength score for each timeframe:
Each indicator adds or subtracts 1 to the score based on whether it aligns with an uptrend or a downtrend.
A score of 6 indicates a Strong Uptrend, with all indicators aligned bullishly.
A score of -6 indicates a Strong Downtrend, with all indicators aligned bearishly.
Intermediate scores (e.g., 2 or -2) indicate Weak Uptrend or Weak Downtrend, suggesting that not all indicators are in agreement.
A score between 1 and -1 indicates a Neutral trend, suggesting uncertainty in the market.
How to Use
Assess Trend Direction and Strength: The table provides an easy-to-read summary of the trend and its strength on different timeframes. Look for timeframes where the strength is high (either 6 for a strong uptrend or -6 for a strong downtrend) to confirm the market’s overall direction.
Use in Conjunction with Other Strategies: This indicator is designed to provide a comprehensive view of the market. Traders should combine it with other strategies, such as price action analysis or candlestick patterns, to further confirm their trades.
Trend Reversal or Continuation: A weak trend (e.g., a strength of 2 or -2) could signal a possible reversal or a trend that has lost momentum. Strong trends (with a strength of 6 or -6) indicate higher confidence in trend continuation.
Multiple Timeframe Confirmation: Look for alignment across multiple timeframes to confirm the strength and direction of the trend before entering trades. For example, if M15, M30, and H1 are all showing a strong uptrend, it suggests a higher probability of the trend continuing.
Customization Options
- Adjustable Indicators: Users can modify the length and parameters of the Moving Averages, RSI, MACD, Bollinger Bands, DMI, and Parabolic SAR to suit their trading style.
- Flexible Timeframes: You can toggle between different timeframes (M15, M30, H1, H4, D1) to focus on the intervals most relevant to your strategy.
Ideal For
- Traders looking for a detailed, multi-timeframe trend analysis tool for XAUUSD.
- Traders who rely on trend-following strategies and need confirmation across multiple timeframes.
- Those who prefer a multi-indicator approach to avoid false signals and improve the accuracy of their trades.
Disclaimer
This indicator is for informational and educational purposes only. It is recommended to combine this with proper risk management strategies and your own analysis. Past performance does not guarantee future results. Always perform your own due diligence before making trading decisions.
TASC 2024.11 Ultimate Strength Index█ OVERVIEW
This script implements the Ultimate Strength Index (USI) indicator, introduced by John Ehlers in his article titled "Ultimate Strength Index (USI)" from the November 2024 edition of TASC's Traders' Tips . The USI is a modified version of Wilder's original Relative Strength Index (RSI) that incorporates Ehlers' UltimateSmoother lowpass filter to produce an output with significantly reduced lag.
█ CONCEPTS
Many technical indicators, including the RSI, lag due to their heavy reliance on historical data. John Ehlers reformulated the RSI to substantially reduce lag by applying his UltimateSmoother filter to upward movements ( strength up - SU ) and downward movements ( strength down - SD ) in the time series, replacing the standard process of smoothing changes with rolling moving averages (RMAs). Ehlers' recent works, covered in our recent script publications, have shown that the UltimateSmoother is an effective alternative to other classic averages, offering notably less lag in its response.
Ehlers also modified the RSI formula to produce an index that ranges from -1 to +1 instead of 0 to 100. As a result, the USI indicates bullish conditions when its value moves above 0 and bearish conditions when it falls below 0.
The USI retains many of the strengths of the traditional RSI while offering the advantage of reduced lag. It generally uses a larger lookback window than the conventional RSI to achieve similar behavior, making it suitable for trend trading with longer data lengths. When applied with shorter lengths, the USI's peaks and valleys tend to align closely with significant turning points in the time series, making it a potentially helpful tool for timing swing trades.
█ CALCULATIONS
The first step in the USI's calculation is determining each bar's strength up (SU) and strength down (SD) values. If the current bar's close exceeds the previous bar's, the calculation assigns the difference to SU. Otherwise, SU is zero. Likewise, if the current bar's close is below the previous bar's, it assigns the difference to SD. Otherwise, SD is zero.
Next, instead of the RSI's typical smoothing process, the USI's calculation applies the UltimateSmoother to the short-term average SU and SD values, reducing high-frequency chop in the series with low lag.
Finally, this formula determines the USI value:
USI = ( Ult (SU) − Ult (SD)) / ( Ult (SU) + Ult (SD)),
where Ult (SU) and Ult (SD) are the smoothed average strength up and strength down values.
Post-Open Long Strategy with ATR-based Stop Loss and Take ProfitThe "Post-Open Long Strategy with ATR-Based Stop Loss and Take Profit" is designed to identify buying opportunities after the German and US markets open. It combines various technical indicators to filter entry signals, focusing on breakout moments following price lateralization periods.
Key Components and Their Interaction:
Bollinger Bands (BB):
Description: Uses BB with a 14-period length and standard deviation multiplier of 1.5, creating narrower bands for lower timeframes.
Role in the Strategy: Identifies low volatility phases (lateralization). The lateralization condition is met when the price is near the simple moving average of the BB, suggesting an imminent increase in volatility.
Exponential Moving Averages (EMA):
10-period EMA: Quickly detects short-term trend direction.
200-period EMA: Filters long-term trends, ensuring entries occur in a bullish market.
Interaction: Positions are entered only if the price is above both EMAs, indicating a consolidated positive trend.
Relative Strength Index (RSI):
Description: 7-period RSI with a threshold above 30.
Role in the Strategy: Confirms the market is not oversold, supporting the validity of the buy signal.
Average Directional Index (ADX):
Description: 7-period ADX with 7-period smoothing and a threshold above 10.
Role in the Strategy: Assesses trend strength. An ADX above 10 indicates sufficient momentum to justify entry.
Average True Range (ATR) for Dynamic Stop Loss and Take Profit:
Description: 14-period ATR with multipliers of 2.0 for Stop Loss and 4.0 for Take Profit.
Role in the Strategy: Adjusts exit levels based on current volatility, enhancing risk management.
Resistance Identification and Breakout:
Description: Analyzes the highs of the last 20 candles to identify resistance levels with at least two touches.
Role in the Strategy: A breakout above this level signals a potential continuation of the bullish trend.
Time Filters and Market Conditions:
Trading Hours: Operates only during the opening of the German market (8:00 - 12:00) and US market (15:30 - 19:00).
Panic Candle: The current candle must close negative, leveraging potential emotional reactions in the market.
Avoiding Entry During Pullbacks:
Description: Checks that the two previous candles are not both bearish.
Role in the Strategy: Avoids entering during a potential pullback, improving trade success probability.
Post-Open Long Strategy with ATR-Based Stop Loss and Take Profit
The "Post-Open Long Strategy with ATR-Based Stop Loss and Take Profit" is designed to identify buying opportunities after the German and US markets open. It combines various technical indicators to filter entry signals, focusing on breakout moments following price lateralization periods.
Key Components and Their Interaction:
Bollinger Bands (BB):
Description: Uses BB with a 14-period length and standard deviation multiplier of 1.5, creating narrower bands for lower timeframes.
Role in the Strategy: Identifies low volatility phases (lateralization). The lateralization condition is met when the price is near the simple moving average of the BB, suggesting an imminent increase in volatility.
Exponential Moving Averages (EMA):
10-period EMA: Quickly detects short-term trend direction.
200-period EMA: Filters long-term trends, ensuring entries occur in a bullish market.
Interaction: Positions are entered only if the price is above both EMAs, indicating a consolidated positive trend.
Relative Strength Index (RSI):
Description: 7-period RSI with a threshold above 30.
Role in the Strategy: Confirms the market is not oversold, supporting the validity of the buy signal.
Average Directional Index (ADX):
Description: 7-period ADX with 7-period smoothing and a threshold above 10.
Role in the Strategy: Assesses trend strength. An ADX above 10 indicates sufficient momentum to justify entry.
Average True Range (ATR) for Dynamic Stop Loss and Take Profit:
Description: 14-period ATR with multipliers of 2.0 for Stop Loss and 4.0 for Take Profit.
Role in the Strategy: Adjusts exit levels based on current volatility, enhancing risk management.
Resistance Identification and Breakout:
Description: Analyzes the highs of the last 20 candles to identify resistance levels with at least two touches.
Role in the Strategy: A breakout above this level signals a potential continuation of the bullish trend.
Time Filters and Market Conditions:
Trading Hours: Operates only during the opening of the German market (8:00 - 12:00) and US market (15:30 - 19:00).
Panic Candle: The current candle must close negative, leveraging potential emotional reactions in the market.
Avoiding Entry During Pullbacks:
Description: Checks that the two previous candles are not both bearish.
Role in the Strategy: Avoids entering during a potential pullback, improving trade success probability.
Entry and Exit Conditions:
Long Entry:
The price breaks above the identified resistance.
The market is in a lateralization phase with low volatility.
The price is above the 10 and 200-period EMAs.
RSI is above 30, and ADX is above 10.
No short-term downtrend is detected.
The last two candles are not both bearish.
The current candle is a "panic candle" (negative close).
Order Execution: The order is executed at the close of the candle that meets all conditions.
Exit from Position:
Dynamic Stop Loss: Set at 2 times the ATR below the entry price.
Dynamic Take Profit: Set at 4 times the ATR above the entry price.
The position is automatically closed upon reaching the Stop Loss or Take Profit.
How to Use the Strategy:
Application on Volatile Instruments:
Ideal for financial instruments that show significant volatility during the target market opening hours, such as indices or major forex pairs.
Recommended Timeframes:
Intraday timeframes, such as 5 or 15 minutes, to capture significant post-open moves.
Parameter Customization:
The default parameters are optimized but can be adjusted based on individual preferences and the instrument analyzed.
Backtesting and Optimization:
Backtesting is recommended to evaluate performance and make adjustments if necessary.
Risk Management:
Ensure position sizing respects risk management rules, avoiding risking more than 1-2% of capital per trade.
Originality and Benefits of the Strategy:
Unique Combination of Indicators: Integrates various technical metrics to filter signals, reducing false positives.
Volatility Adaptability: The use of ATR for Stop Loss and Take Profit allows the strategy to adapt to real-time market conditions.
Focus on Post-Lateralization Breakout: Aims to capitalize on significant moves following consolidation periods, often associated with strong directional trends.
Important Notes:
Commissions and Slippage: Include commissions and slippage in settings for more realistic simulations.
Capital Size: Use a realistic trading capital for the average user.
Number of Trades: Ensure backtesting covers a sufficient number of trades to validate the strategy (ideally more than 100 trades).
Warning: Past results do not guarantee future performance. The strategy should be used as part of a comprehensive trading approach.
With this strategy, traders can identify and exploit specific market opportunities supported by a robust set of technical indicators and filters, potentially enhancing their trading decisions during key times of the day.
