Trend CompassAbout This Script
Trend Compass Pro is a multi-layered market analysis tool designed to unify three essential components of price behavior: momentum, trend strength, and directional structure.
It is built to provide traders with a clear and readable visualization of market conditions without relying on external scripts or unnecessary visual clutter.
How It Works
1. Momentum Layer — RSI
The script uses a fast-period Relative Strength Index (RSI) to measure short-term momentum sensitivity.
Its line is dynamically colored based on candle direction (bullish, bearish, neutral), which makes momentum shifts easy to interpret at a glance.
2. Strength Layer — ADX
The next layer applies a standard ADX calculation to measure the strength of the prevailing trend, independent of direction.
A threshold level marks when the trend becomes strong or meaningful.
The ADX line is also color-synchronized with candle direction to highlight moments when trend strength aligns with price momentum.
A visual fill between the RSI and ADX lines appears when both layers agree — green for bullish strength, red for bearish strength.
3. Direction Layer — Trend Compass (Original Logic)
This is the core component of the script and is fully original.
It works by comparing a fast EMA with a slow EMA across three separate internal timeframes, representing:
Short-term trend
Medium-term trend
Long-term trend
Each timeframe outputs a simple directional state based on EMA spread, displayed as three horizontal color-coded bands (levels 25, 50, 75).
These colors show when trend direction is aligned or mixed across different timescales.
Why These Elements Are Combined
The script is not a random combination of indicators.
Each layer solves a distinct analytical need:
RSI → short-term market mood
ADX → strength behind the move
Trend Compass → structural direction across multiple trend horizons
Together, they provide a consolidated and readable picture of how direction, strength, and momentum interact.
How to Use It
When all three layers show bullish agreement → strong and confirmed uptrend
When all three align bearish → strong downtrend
When mixed → transitional or weak environment
When Trend Compass is neutral → market lacks directional structure
This makes the script suitable for trend trading, breakout confirmation, and momentum-aligned entries.
Publishing Notes
A clean chart was used when publishing this script.
No additional indicators or unrelated drawings were included.
All visible elements originate directly from the script and serve the purpose of understanding its function.
Trend Compass combines momentum (RSI), trend strength (ADX), and multi-timeframe direction (EMA-based Trend Compass) into a single clean panel.
The script highlights periods when momentum and strength agree and shows trend direction across three internal time horizons.
It offers a clear way to confirm trend continuation, strength, and reversals without clutter.
Unlock a complete trend-reading system with Trend Compass — a smart fusion of RSI momentum, ADX strength, and a unique triple-layer trend engine.
Identify strong trends instantly, filter noise, and trade only when momentum, strength, and direction align.
חפש סקריפטים עבור "adx"
Scalper Pro Pattern Recognition & Price Action📘 Scalper Pro Pattern Recognition & Price Action
Overview
Scalper Pro is a dynamic multi-layer trend recognition and price action strategy that integrates Supertrend, Smart Money Concepts (SMC), and volatility-based risk control.
It adapts to market volatility in real time to enhance entry precision and optimize risk.
⚠️ This script is for educational and research purposes only.
Past performance does not guarantee future results.
🎯 Strategy Objectives
Detect structural market shifts (BOS / CHoCH) automatically.
Identify Order Blocks (OB), Fair Value Gaps (FVG), and key liquidity zones.
Plot dynamic Take-Profit (TP) and Stop-Loss (SL) levels based on ATR.
Avoid low-volatility (sideways) conditions using ADX filtering.
Combine trend-following signals with structural confirmation.
✨ Key Features
Supertrend Entry Signals — Generates precise buy/sell markers based on price crossovers with the Supertrend line.
Order Block Detection — Automatically plots both Internal and Swing Order Blocks for smart money insights.
Fair Value Gap Visualization — Highlights inefficiency zones in bullish or bearish structures.
Market Structure Labels — Marks Break of Structure (BOS) and Change of Character (CHoCH) points for clear trend shifts.
Dynamic Risk Levels — Automatically generates TP/SL lines and price labels using ATR-based distance.
📊 Trading Rules
Long Entry:
• Price crosses above the Supertrend (ta.crossover(close, supertrend))
• ADX above sideways threshold (trend condition confirmed)
• Optional confirmation from a bullish BOS or CHoCH
Short Entry:
• Price crosses below the Supertrend (ta.crossunder(close, supertrend))
• ADX above threshold
• Optional confirmation from a bearish BOS or CHoCH
Exit (or Reverse):
• Opposite Supertrend crossover
• Price hits TP/SL lines
• Trend shift confirmed by internal BOS/CHoCH
💰 Risk Management Parameters
Stop Loss & Take Profit based on ATR × risk multiplier
ATR Length: 14 (default)
Risk %: 3% per trade
Sideways Filter: ADX < 15 → no trade zone
TP1–TP3 = Entry ± (ATR × 1~3)
⚙️ Indicator Settings
Supertrend Module:
ATR Length: 10
Factor: nsensitivity × 7
ADX Module:
ADX Length: 15
Sideways Threshold: 15
EMA Set:
EMA (5, 9, 13, 34, 50) × Volatility Factor (3)
SMA Filter:
SMA(8) & SMA(9) for short-term trend confirmation
Smart Money Concepts Module:
Displays BOS/CHoCH, Order Blocks, FVGs, Equal Highs/Lows, and Premium/Discount zones
🔧 Improvements & Uniqueness
Integrates Supertrend momentum with Smart Money Concepts (SMC) structural analysis.
Dual detection layers: Internal (micro) and Swing (macro) structures.
ATR-driven auto labeling for entry, stop, and profit targets.
Premium/Discount and Equilibrium zones visualized on the chart.
Built-in ADX filter to skip low-trend market conditions.
✅ Summary
Scalper Pro Pattern Recognition & Price Action merges classical trend-following with modern market structure analytics.
It combines momentum detection, volatility control, and smart money mapping into one cohesive framework.
Unified trend, structure, and risk visualization.
Auto-marked BOS/CHoCH, OB, FVG, and liquidity zones.
Usable for scalping, intraday, or swing trading setups.
⚠️ This strategy is based on historical data and designed for educational use only.
Always apply sound risk management and forward testing before live trading.
Chronos Reversal Labs - SPChronos Reversal Labs - Shadow Portfolio
Chronos Reversal Labs - Shadow Portfolio: combines reinforcement learning optimization with adaptive confluence detection through a shadow portfolio system. Unlike traditional indicator mashups that force traders to manually interpret conflicting signals, this system deploys 4 multi-armed bandit algorithms to automatically discover which of 5 specialized confluence strategies performs best in current market conditions, then validates those discoveries through parallel shadow portfolios that track virtual P&L for each strategy independently.
Core Innovation: Rather than relying on static indicator combinations, this system implements Thompson Sampling (Bayesian multi-armed bandits), contextual bandits (regime-specific learning), advanced chop zone detection (geometric pattern analysis), and historical pre-training to build a self-improving confluence detection engine. The shadow portfolio system runs 5 parallel virtual trading accounts—one per strategy—allowing the system to learn which confluence approach works best through actual position tracking with realistic exits.
Target Users: Intermediate to advanced traders seeking systematic reversal signals with mathematical rigor. Suitable for swing trading and day trading across stocks, forex, crypto, and futures on liquid instruments. Requires understanding of basic technical analysis and willingness to allow 50-100 bars for initial learning.
Why These Components Are Combined
The Fundamental Problem
No single confluence method works consistently across all market regimes. Kernel-based methods (entropy, DFA) excel during predictable phases but fail in chaos. Structure-based methods (harmonics, BOS) work during clear swings but fail in ranging conditions. Technical methods (RSI, MACD, divergence) provide reliable signals in trends but generate false signals during consolidation.
Traditional solutions force traders to either manually switch between methods (slow, error-prone) or interpret all signals simultaneously (cognitive overload). Both fail because they assume the trader knows which regime the market is in and which method works best.
The Solution: Meta-Learning Through Reinforcement Learning
This system solves the problem through automated strategy selection : Deploy 5 specialized confluence strategies designed for different market conditions, track their real-world performance through shadow portfolios, then use multi-armed bandit algorithms to automatically select the optimal strategy for the next trade.
Why Shadow Portfolios? Traditional bandit implementations use abstract "rewards." Shadow portfolios provide realistic performance measurement : Each strategy gets a virtual trading account with actual position tracking, stop-loss management, take-profit targets, and maximum holding periods. This creates risk-adjusted learning where strategies are evaluated on P&L, win rate, and drawdown—not arbitrary scores.
The Five Confluence Strategies
The system deploys 5 orthogonal strategies with different weighting schemes optimized for specific market conditions:
Strategy 1: Kernel-Dominant (Entropy/DFA focused, optimal in predictable markets)
Shannon Entropy weight × 2.5, DFA weight × 2.5
Detects low-entropy predictable patterns and DFA persistence/mean-reversion signals
Failure mode: High-entropy chaos (hedged by Technical-Dominant)
Strategy 2: Structure-Dominant (Harmonic/BOS focused, optimal in clear swing structures)
Harmonics weight × 2.5, Liquidity (S/R) weight × 2.0
Uses swing detection, break-of-structure, and support/resistance clustering
Failure mode: Range-bound markets (hedged by Balanced)
Strategy 3: Technical-Dominant (RSI/MACD/Divergence focused, optimal in established trends)
RSI weight × 2.0, MACD weight × 2.0, Trend weight × 2.0
Zero-lag RSI suite with 4 calculation methods, MACD analysis, divergence detection
Failure mode: Choppy/ranging markets (hedged by chop filter)
Strategy 4: Balanced (Equal weighting, optimal in unknown/transitional regimes)
All components weighted 1.2×
Baseline performance during regime uncertainty
Strategy 5: Regime-Adaptive (Dynamic weighting by detected market state)
Chop zones: Kernel × 2.0, Technical × 0.3
Bull/Bear trends: Trend × 1.5, DFA × 2.0
Ranging: Mean reversion × 1.5
Adapts explicitly to detected regime
Multi-Armed Bandit System: 4 Core Algorithms
What Is a Multi-Armed Bandit Problem?
Formal Definition: K arms (strategies), each with unknown reward distribution. Goal: Maximize cumulative reward while learning which arms are best. Challenge: Balance exploration (trying uncertain strategies) vs. exploitation (using known-best strategy).
Trading Application: Each confluence strategy is an "arm." After each trade, receive reward (P&L percentage). Bandits decide which strategy to trust for next signal.
The 4 Implemented Algorithms
1. Thompson Sampling (DEFAULT)
Category: Bayesian approach with probability distributions
How It Works: Model each strategy as Beta(α, β) where α = wins, β = losses. Sample from distributions, select highest sample.
Properties: Optimal regret O(K log T), automatic exploration-exploitation balance
When To Use: Best all-around choice, adaptive markets, long-term optimization
2. UCB1 (Upper Confidence Bound)
Category: Frequentist approach with confidence intervals
Formula: UCB_i = reward_mean_i + sqrt(2 × ln(total_pulls) / pulls_i)
Properties: Deterministic, interpretable, same optimal regret as Thompson
When To Use: Prefer deterministic behavior, stable markets
3. Epsilon-Greedy
Category: Simple baseline with random exploration
How It Works: With probability ε (0.15): random strategy. Else: best average reward.
Properties: Simple, fast initial learning
When To Use: Baseline comparison, short-term testing
4. Contextual Bandit
Category: Context-aware Thompson Sampling
Enhancement: Maintains separate alpha/beta for Bull/Bear/Ranging regimes
Learning: "Strategy 2: 60% win rate in Bull, 40% in Bear"
When To Use: After 100+ bars, clear regime shifts
Shadow Portfolio System
Why Shadow Portfolios?
Traditional bandits use abstract scores. Shadow portfolios provide realistic performance measurement through actual position simulation.
How It Works
Position Opening:
When strategy generates validated signal:
Opens virtual position for selected strategy
Records: entry price, direction, entry bar, RSI method
Optional: Open positions for ALL strategies simultaneously (faster learning)
Position Management (Every Bar):
Current P&L: pnl_pct = (close - entry) / entry × direction × 100
Exit if: pnl_pct <= -2.0% (stop-loss) OR pnl_pct >= +4.0% (take-profit) OR held ≥ 100 bars (time)
Position Closing:
Calculate final P&L percentage
Update strategy equity, track win rate, gross profit/loss, max drawdown
Calculate risk-adjusted reward:
text
base_reward = pnl_pct / 10.0
win_rate_bonus = (win_rate - 0.5) × 0.3
drawdown_penalty = -max_drawdown × 0.05
total_reward = sigmoid(base + bonus + penalty)
Update bandit algorithms with reward
Update RSI method bandit
Statistics Tracked Per Strategy:
Equity curve (starts at $10,000)
Win rate percentage
Max drawdown
Gross profit/loss
Current open position
This creates closed-loop learning : Strategies compete → Best performers selected → Bandits learn quality → System adapts automatically.
Historical Pre-Training System
The Problem with Live-Only Learning
Standard bandits start with zero knowledge and need 50-100 signals to stabilize. For weekly timeframe traders, this could take years.
The Solution: Historical Training
During Chart Load: System processes last 300-1000 bars (configurable) in "training mode":
Detect signals using Balanced strategy (consistent baseline)
For each signal, open virtual training positions for all 5 strategies
Track positions through historical bars using same exit logic (SL/TP/time)
Update bandit algorithms with historical outcomes
CRITICAL TRANSPARENCY: Signal detection does NOT look ahead—signals use only data available at entry bar. Exit tracking DOES look ahead (uses future bars for SL/TP), which is acceptable because:
✅ Entry decisions remain valid (no forward bias)
✅ Learning phase only (not affecting shown signals)
✅ Real-time mirrors training (identical exit logic)
Training Completion: Once chart reaches current bar, system transitions to live mode. Dashboard displays training vs. live statistics for comparison.
Benefit: System begins live trading with 100-500 historical trades worth of learning, enabling immediate intelligent strategy selection.
Advanced Chop Zone Detection Engine
The Innovation: Multi-Layer Geometric Chop Analysis
Traditional chop filters use simple volatility metrics (ATR thresholds) that can't distinguish between trending volatility (good for signals) and choppy volatility (bad for signals). This system implements three-layer geometric pattern analysis to precisely identify consolidation zones where reversal signals fail.
Layer 1: Micro-Structure Chop Detection
Method: Analyzes micro pivot points (5-bar left, 2-bar right) to detect geometric compression patterns.
Slope Analysis:
Calculates slope of pivot high trendline and pivot low trendline
Compression ratio: compression = slope_high - slope_low
Pattern Classification:
Converging slopes (compression < -0.05) → "Rising Wedge" or "Falling Wedge"
Flat slopes (|slope| < 0.05) → "Rectangle"
Parallel slopes (|compression| < 0.1) → "Channel"
Expanding slopes → "Expanding Range"
Chop Scoring:
Rectangle pattern: +15 points (highest chop)
Low average slope (<0.05): +15 points
Wedge patterns: +12 points
Flat structures: +10 points
Why This Works: Geometric patterns reveal market indecision. Rectangles and wedges create false breakouts that trap technical traders. By quantifying geometric compression, system detects these zones before signals fire.
Layer 2: Macro-Structure Chop Detection
Method: Tracks major swing highs/lows using ATR-based deviation threshold (default 2.0× ATR), projects channel boundaries forward.
Channel Position Calculation:
proj_high = last_swing_high + (swing_high_slope × bars_since)
proj_low = last_swing_low + (swing_low_slope × bars_since)
channel_width = proj_high - proj_low
position = (close - proj_low) / channel_width
Dead Zone Detection:
Middle 50% of channel (position 0.25-0.75) = low-conviction zone
Score increases as price approaches center (0.5)
Chop Scoring:
Price in dead zone: +15 points (scaled by centrality)
Narrow channel width (<3× ATR): +15 points
Channel width 3-5× ATR: +10 points
Why This Works: Price in middle of range has equal probability of moving either direction. Institutional traders avoid mid-range entries. By detecting "dead zones," system avoids low-probability setups.
Layer 3: Volume Chop Scoring
Method: Low volume indicates weak conviction—precursor to ranging behavior.
Scoring:
Volume < 0.5× average: +20 points
Volume 0.5-0.8× average: +15 points
Volume 0.8-1.0× average: +10 points
Overall Chop Intensity & Signal Filtering
Total Chop Calculation:
chop_intensity = micro_score + macro_score + (volume_score × volume_weight)
is_chop = chop_intensity >= 40
Signal Filtering (Three-Tier Approach):
1. Signal Blocking (Intensity > 70):
Extreme chop detected (e.g., tight rectangle + dead zone + low volume)
ALL signals blocked regardless of confluence
Chart displays red/orange background shading
2. Threshold Adjustment (Intensity 40-70):
Moderate chop detected
Confluence threshold increased: threshold += (chop_intensity / 50)
Only highest-quality signals pass
3. Strategy Weight Adjustment:
During Chop: Kernel-Dominant weight × 2.0 (entropy detects breakout precursors), Technical-Dominant weight × 0.3 (reduces false signals)
After Chop Exit: Weights revert to normal
Why This Three-Tier Approach Is Original: Most chop filters simply block all signals (loses breakout entries). This system adapts strategy selection during chop—allowing Kernel-Dominant (which excels at detecting low-entropy breakout precursors) to operate while suppressing Technical-Dominant (which generates false signals in consolidation). Result: System remains functional across full market regime spectrum.
Zero-Lag Filter Suite with Dynamic Volatility Scaling
Zero-Lag ADX (Trend Regime Detection)
Implementation: Applies ZLEMA to ADX components:
lag = (length - 1) / 2
zl_source = source + (source - source ) × strength
Dynamic Volatility Scaling (DVS):
Calculates volatility ratio: current_ATR / ATR_100period_avg
Adjusts ADX length dynamically: High vol → shorter length (faster), Low vol → longer length (smoother)
Regime Classification:
ADX > 25 with +DI > -DI = Bull Trend
ADX > 25 with -DI > +DI = Bear Trend
ADX < 25 = Ranging
Zero-Lag RSI Suite (4 Methods with Bandit Selection)
Method 1: Standard RSI - Traditional Wilder's RSI
Method 2: Ehlers Zero-Lag RSI
ema1 = ema(close, length)
ema2 = ema(ema1, length)
zl_close = close + (ema1 - ema2)
Method 3: ZLEMA RSI
lag = (length - 1) / 2
zl_close = close + (close - close )
Method 4: Kalman-Filtered RSI - Adaptive smoothing with process/measurement noise
RSI Method Bandit: Separate 4-arm bandit learns which calculation method produces best results. Updates independently after each trade.
Kalman Adaptive Filters
Fast Kalman: Low process noise → Responsive to genuine moves
Slow Kalman: Higher measurement noise → Filters noise
Application: Crossover logic for trend detection, acceleration analysis for momentum inflection
What Makes This Original
Innovation 1: Shadow Portfolio Validation
First TradingView script to implement parallel virtual portfolios for multi-armed bandit reward calculation. Instead of abstract scoring metrics, each strategy's performance is measured through realistic position tracking with stop-loss, take-profit, time-based exits, and risk-adjusted reward functions (P&L + win rate + drawdown). This provides orders-of-magnitude better reward signal quality for bandit learning than traditional score-based approaches.
Innovation 2: Three-Layer Geometric Chop Detection
Novel multi-scale geometric pattern analysis combining: (1) Micro-structure slope analysis with pattern classification (wedges, rectangles, channels), (2) Macro-structure channel projection with dead zone detection, (3) Volume confirmation. Unlike simple volatility filters, this system adapts strategy weights during chop —boosting Kernel-Dominant (breakout detection) while suppressing Technical-Dominant (false signal reduction)—allowing operation across full market regime spectrum without blind signal blocking.
Innovation 3: Historical Pre-Training System
Implements two-phase learning : Training phase (processes 300-1000 historical bars on chart load with proper state isolation) followed by live phase (real-time learning). Training positions tracked separately from live positions. System begins live trading with 100-500 trades worth of learned experience. Dashboard displays training vs. live performance for transparency.
Innovation 4: Contextual Multi-Armed Bandits with Regime-Specific Learning
Beyond standard bandits (global strategy quality), implements regime-specific alpha/beta parameters for Bull/Bear/Ranging contexts. System learns: "Strategy 2: 60% win rate in ranging markets, 45% in bull trends." Uses current regime's learned parameters for strategy selection, enabling regime-aware optimization.
Innovation 5: RSI Method Meta-Learning
Deploys 4 different RSI calculation methods (Standard, Ehlers ZL, ZLEMA, Kalman) with separate 4-arm bandit that learns which calculation works best. Updates RSI method bandit independently based on trade outcomes, allowing automatic adaptation to instrument characteristics.
Innovation 6: Dynamic Volatility Scaling (DVS)
Adjusts ALL lookback periods based on current ATR ratio vs. 100-period average. High volatility → shorter lengths (faster response). Low volatility → longer lengths (smoother signals). Applied system-wide to entropy, DFA, RSI, ADX, and Kalman filters for adaptive responsiveness.
How to Use: Practical Guide
Initial Setup (5 Minutes)
Theory Mode: Start with "BALANCED" (APEX for aggressive, CONSERVATIVE for defensive)
Enable RL: Toggle "Enable RL Auto-Optimization" to TRUE, select "Thompson Sampling"
Enable Confluence Modules: Divergence, Volume Analysis, Liquidity Mapping, RSI OB/OS, Trend Analysis, MACD (all recommended)
Enable Chop Filter: Toggle "Enable Chop Filter" to TRUE, sensitivity 1.0 (default)
Historical Training: Enable "Enable Historical Pre-Training", set 300-500 bars
Dashboard: Enable "Show Dashboard", position Top Right, size Large
Learning Phase (First 50-100 Bars)
Monitor Thompson Sampling Section:
Alpha/beta values should diverge from initial 1.0 after 20-30 trades
Expected win% should stabilize around 55-60% (excellent), >50% (acceptable)
"Pulls" column should show balanced exploration (not 100% one strategy)
Monitor Shadow Portfolios:
Equity curves should diverge (different strategies performing differently)
Win rate > 55% is strong
Max drawdown < 15% is healthy
Monitor Training vs Live (if enabled):
Delta difference < 10% indicates good generalization
Large negative delta suggests overfitting
Large positive delta suggests system adapting well
Optimization:
Too few signals: Lower "Base Confluence Threshold" to 2.5-3.0
Too many signals: Raise threshold to 4.0-4.5
One strategy dominates (>80%): Increase "Exploration Rate" to 0.20-0.25
Excessive chop blocking: Lower "Chop Sensitivity" to 0.7-0.8
Signal Interpretation
Dashboard Indicators:
"WAITING FOR SIGNAL": No confluence
"LONG ACTIVE ": Validated long entry
"SHORT ACTIVE ": Validated short entry
Chart Visuals:
Triangle markers: Entry signal (green = long, red = short)
Orange/red background: Chop zone
Lines: Support/resistance if enabled
Position Management
Entry: Enter on triangle marker, confirm direction matches dashboard, check confidence >60%
Stop-Loss: Entry ± 1.5× ATR or at structural swing point
Take-Profit:
TP1: Entry + 1.5R (take 50%, move SL to breakeven)
TP2: Entry + 3.0R (runner) or trail
Position Sizing:
Risk per trade = 1-2% of capital
Position size = (Account × Risk%) / (Entry - SL)
Recommended Settings by Instrument
Stocks (Large Cap): Balanced mode, Threshold 3.5, Thompson Sampling, Chop 1.0, 15min-1H, Training 300-500 bars
Forex Majors: Conservative-Balanced mode, Threshold 3.5-4.0, Thompson Sampling, Chop 0.8-1.0, 5min-30min, Training 400-600 bars
Cryptocurrency: Balanced-APEX mode, Threshold 3.0-3.5, Thompson Sampling, Chop 1.2-1.5, 15min-4H, Training 300-500 bars
Futures: Balanced mode, Threshold 3.5, UCB1 or Thompson, Chop 1.0, 5min-30min, Training 400-600 bars
Technical Approximations & Limitations
1. Thompson Sampling: Pseudo-Random Beta Distribution
Standard: Cryptographic RNG with true beta sampling
This Implementation: Box-Muller transform using market data as entropy source
Impact: Not cryptographically random but maintains exploration-exploitation balance. Sufficient for strategy selection.
2. Shadow Portfolio: Simplified Execution Model
Standard: Order book simulation with slippage, partial fills
This Implementation: Perfect fills at close price, no fees modeled
Impact: Real-world performance ~0.1-0.3% worse per trade due to execution costs.
3. Historical Training: Forward-Looking for Exits Only
Entry signals: Use only past data (causal, no bias)
Exit tracking: Uses future bars to determine SL/TP (forward-looking)
Impact: Acceptable because: (1) Entry logic remains valid, (2) Live trading mirrors training, (3) Improves learning quality. Training win rates reflect 8-bar evaluation window—live performance may differ if positions held longer.
4. Shannon Entropy & DFA: Simplified Calculations
Impact: 10-15% precision loss vs. academic implementations. Still captures predictability and persistence signals effectively.
General Limitations
No Predictive Guarantee: Past performance ≠ future results
Learning Period Required: Minimum 50-100 bars for stable statistics
Overfitting Risk: May not generalize to unprecedented conditions
Single-Instrument: No multi-asset correlation or sector context
Execution Assumptions: Degrades in illiquid markets (<100k volume), major news events, flash crashes
Risk Warnings & Disclaimers
No Guarantee of Profit: All trading involves substantial risk of loss. This indicator is a tool, not a guaranteed profit system.
System Failures: Software bugs possible despite testing. Use appropriate position sizing.
Market Regime Changes: Performance may degrade during extreme volatility (VIX >40), low liquidity periods, or fundamental regime shifts.
Broker-Specific Issues: Real-world execution includes slippage (0.1-0.5%), commissions, overnight financing costs, partial fills.
Forward-Looking Bias in Training: Historical training uses 8-bar forward window for exit evaluation. Dashboard "Training Win%" reflects this method. Real-time performance may differ.
Appropriate Use
This Indicator IS:
✅ Entry trigger system with confluence validation
✅ Risk management framework (automated SL/TP)
✅ Adaptive strategy selection engine
✅ Learning system that improves over time
This Indicator IS NOT:
❌ Complete trading strategy (requires position sizing, portfolio management)
❌ Replacement for due diligence
❌ Guaranteed profit generator
❌ Suitable for complete beginners
Recommended Complementary Analysis: Market context, volume profile, fundamental catalysts, higher timeframe alignment, support/resistance from other sources.
Conclusion
Chronos Reversal Labs V2.0 - Elite Edition synthesizes research from multi-armed bandit theory (Thompson Sampling, UCB, contextual bandits), market microstructure (geometric chop detection, zero-lag filters), and machine learning (shadow portfolio validation, historical pre-training, RSI method meta-learning).
Unlike typical indicator mashups, this system implements mathematically rigorous bandit algorithms with realistic performance validation, three-layer chop detection with adaptive strategy weighting, regime-specific learning, and full transparency on approximations and limitations.
The system is designed for intermediate to advanced traders who understand that no indicator is perfect, but through proper machine learning and realistic validation, we can build systems that improve over time and adapt to changing markets without manual intervention.
Use responsibly. Understand the limitations. Risk disclosure applies. Past performance does not guarantee future results.
Taking you to school. — Dskyz, Trade with insight. Trade with anticipation.
Momentum Master v1# Momentum Master v1 - Multi-Strategy Trading System
## SCRIPT OVERVIEW
Momentum Master v1 is a multi-strategy trading system that integrates 6 distinct trading methodologies (EMA Crossover, RSI Mean Reversion, Breakout, MACD Crossover, Bollinger Bands, Volume Breakout) through a shared risk management pipeline. This script implements a proprietary integration framework that creates synergistic value beyond what individual indicators provide, combining advanced technical analysis techniques with institutional flow analysis.
## TECHNICAL METHODOLOGY
### Multi-Strategy Signal Generation Framework
The script operates on a shared execution framework where all six trading strategies share the same risk management system, but each strategy uses its own unique entry logic:
1. **EMA Crossover System**: Detects momentum shifts using configurable fast/slow EMA periods (Standard 9/21, Fast 7/17, Slow 13/26, or Custom)
2. **RSI Mean Reversion**: Identifies overbought/oversold conditions for counter-trend opportunities
3. **Breakout Detection**: Captures price breakouts from consolidation zones
4. **MACD Crossover**: Uses MACD line crossovers to confirm trend changes
5. **Bollinger Bands**: Trades bounces from band extremes and breakouts
6. **Volume Breakout**: Confirms moves with above-average volume
**Why This Integration Creates Unique Value:**
This is not a simple indicator mashup. The proprietary integration framework creates synergistic value through:
- **Shared Risk Management**: All strategies share ATR-based stop loss calculation and multiple take profit levels (TP1-TP6 with ratios 1:2, 1:4, 1:6, 1:8, 1:10, 1:12)
- **Adaptive Confidence Scoring**: The system evaluates market context from multiple perspectives simultaneously
- **Shared Filter System**: Optional filters (RSI extremes, ADX trend strength, Volume confirmation, POC proximity) apply uniformly across all strategies
## FLOW ANALYSIS INTEGRATION
### Fair Value Gap (FVG) Retracement Validation
The script implements proprietary FVG detection with retracement validation logic:
- **200-bar lookback** with **20% ATR tolerance** for gap identification
- **Retracement confirmation**: Signals can require price to retrace into a recent FVG before entry (optional filter)
- **Size filtering**: Only displays FVGs above minimum ATR threshold (configurable)
- **Visual tracking**: Shows last N FVGs with color-coded boxes (bullish green, bearish red)
**How FVG Integration Enhances Strategy Signals:**
When a strategy generates a signal, the FVG system validates whether price has recently retraced into an institutional order flow gap. This adds a layer of confirmation that the move is supported by institutional activity, not just retail momentum.
### Order Block Detection with Directional Alignment
- **Institutional accumulation/distribution zones**: Identifies the last bullish/bearish candle before a significant move
- **Directional filter**: Optional setting to only allow trades aligned with the most recent order block direction
- **ATR-based size filtering**: Filters out noise by requiring minimum order block size
- **Visual display**: Shows order blocks as colored boxes extending N bars forward
**Integration Logic:**
Order blocks represent areas where institutions accumulated or distributed positions. When a strategy signal occurs near an order block, it indicates higher probability that the move will continue in the block's direction.
### Multi-Timeframe POC (Point of Control) Analysis
The script calculates and displays POC levels from multiple timeframes:
- **Volume Profile POC**: Highest volume price over last N bars (configurable lookback)
- **Session POC**: Point of control for current trading session
- **Daily POC**: Daily volume-weighted average price
- **Weekly POC**: Weekly volume-weighted average price (optional)
**POC Proximity Filtering:**
Optional filters allow signals only when price is within X ATR of a POC level. This ensures entries occur at statistically significant price levels where liquidity is concentrated.
## FIBONACCI EXTENSION SYSTEM
### Dynamic Fibonacci Calculation
- **Swing-based detection**: Automatically identifies swing highs and lows using configurable lookback period
- **Extension levels**: Calculates Fibonacci extension levels (0.618, 0.786, 1.0, 1.272, 1.414, 1.618, 2.0, 2.618)
- **Retracement levels**: Shows standard retracement levels (0.236, 0.382, 0.5, 0.618, 0.786)
- **Negative levels**: Optional negative Fibonacci levels (-0.27, -0.618) for extended targets
**How Fibonacci Enhances Risk Management:**
Take profit levels are automatically calculated using Fibonacci extension mathematics. The system identifies the swing structure and projects potential reversal zones, allowing traders to set targets based on mathematical probability rather than arbitrary price levels.
## LIQUIDITY ZONE DETECTION
### Buy and Sell Side Liquidity
- **Swing-based liquidity zones**: Identifies recent swing highs (sell-side liquidity) and swing lows (buy-side liquidity)
- **Configurable lookback**: Adjustable period for liquidity zone detection
- **Visual display**: Horizontal lines extending N bars forward to show liquidity targets
- **Maximum zones**: Limits display to most recent N zones to avoid chart clutter
**Trading Application:**
Liquidity zones represent areas where stop losses are likely clustered. Price often moves to "sweep" these liquidity zones before reversing, creating high-probability entry opportunities.
## RISK MANAGEMENT SYSTEM
### ATR-Based Stop Loss Calculation
- **Dynamic stop placement**: Stop loss calculated using ATR (Average True Range) with configurable multiplier
- **Adaptive to volatility**: Stop loss automatically adjusts to current market volatility conditions
- **Configurable ATR period**: Default 14-period ATR, adjustable from 5-30 periods
- **SL multiplier**: Adjustable from 0.5x to 10x ATR for different risk profiles
### Multiple Take Profit Levels
The system supports up to 6 take profit levels with fixed risk-reward ratios:
- **TP1**: 1:2 risk-reward ratio
- **TP2**: 1:4 risk-reward ratio
- **TP3**: 1:6 risk-reward ratio
- **TP4**: 1:8 risk-reward ratio (optional)
- **TP5**: 1:10 risk-reward ratio (optional)
- **TP6**: 1:12 risk-reward ratio (optional)
**Why Multiple TP Levels:**
This allows partial profit-taking at key Fibonacci extension levels while letting winners run. The system tracks win rates for each TP level, helping traders optimize their exit strategy.
## SIGNAL FILTERS (OPTIONAL ENHANCEMENTS)
### RSI Extreme Filter
- **Avoid overbought/oversold extremes**: Prevents entries when RSI is in extreme zones (default: >70 overbought, <30 oversold)
- **Configurable thresholds**: Adjustable RSI levels and calculation period
- **Purpose**: Reduces false signals in exhausted moves
### ADX Trend Strength Filter
- **Avoid choppy markets**: Only allows trades when ADX indicates trending conditions (default: ADX > 20)
- **Configurable threshold**: Adjustable ADX minimum value (10-50)
- **Purpose**: Filters out low-probability trades in ranging markets
### Volume Confirmation
- **Volume multiplier**: Requires volume above X times average (default: 1.1x)
- **Purpose**: Ensures moves are supported by institutional participation
### POC Proximity Filters
- **Volume POC filter**: Only enter when price is near Volume Profile POC
- **Session POC filter**: Only enter when price is near Session POC
- **Daily POC filter**: Only enter when price is near Daily POC
- **Weekly POC filter**: Only enter when price is near Weekly POC
- **Proximity threshold**: Configurable ATR multiplier for "near" definition (default: 2.0x ATR)
---
## DIVERGENCE DETECTION
### MFI (Money Flow Index) Divergence
- **Bullish divergence**: Price makes lower low, MFI makes higher low (potential reversal up)
- **Bearish divergence**: Price makes higher high, MFI makes lower high (potential reversal down)
- **Configurable lookback**: Adjustable period for divergence detection (default: 100 bars)
- **Minimum bars between divergences**: Prevents duplicate signals (default: 10 bars)
- **Advanced thresholds**: Separate thresholds for RSI, price, and MFI divergence strength
**Note**: Divergence detection is visual-only and does not filter trades. It provides additional market context for discretionary traders.
## MARKET CONTEXT TOOLS
### Session High/Low Lines
- **Recent session extremes**: Displays horizontal lines for session high and low
- **Configurable lookback**: Adjustable period for session calculation (default: 10 bars)
- **Purpose**: Identifies key intraday support/resistance levels
### Swing Point Detection
- **Automatic swing identification**: Marks significant swing highs and lows
- **Visual reference**: Helps identify market structure and trend direction
### Signal Overview Table
Real-time technical analysis overview:
- **Current RSI**: Relative Strength Index value
- **ATR**: Current Average True Range
- **ADX**: Average Directional Index (trend strength)
- **EMA status**: Current fast/slow EMA relationship (Bullish/Bearish/Neutral)
- **POC levels**: Current price relative to POC levels
- **Confidence score**: Calculated confidence percentage based on confluence
- **Volume trend**: Current volume trend direction
## CHART DISPLAY OPTIONS
### Entry/SL/TP Lines
- **Visual trade management**: Displays entry price, stop loss, and all take profit levels as horizontal lines
- **Configurable length**: Lines extend N bars forward (default: 30 bars)
- **Color-coded**: Different colors for entry, stop loss, and each TP level
### Win/Loss Labels
- **Trade verification**: Displays up to 500 individual win/loss labels on chart
- **Visual feedback**: Green labels for wins, red labels for losses
- **Performance tracking**: Helps verify strategy performance visually
## USAGE INSTRUCTIONS
### Initial Setup
1. **Select Strategy Mode**: Choose your preferred trading strategy from the dropdown (EMA Crossover, RSI Mean Reversion, Breakout, MACD Crossover, Bollinger Bands, Volume Breakout, or Disabled)
2. **Configure Risk Management**:
- Set ATR Length for stop loss calculation (default: 14)
- Set SL ATR Multiplier (default: 1.0)
- Enable additional TP levels if desired (TP4-TP6 are optional)
3. **Adjust Strategy Parameters**: Each strategy has its own settings group. Configure EMA periods, RSI settings, MACD parameters, etc., based on your selected strategy.
### Recommended Settings by Market Type
**Forex/Crypto (High Volatility)**:
- EMA Mode: Fast (7/17) or Custom (3/21)
- SL ATR Multiplier: 1.5-2.0
- Enable FVG retracement filter
- Enable Order Block directional filter
**Stocks (Moderate Volatility)**:
- EMA Mode: Standard (9/21)
- SL ATR Multiplier: 1.0-1.5
- Enable ADX filter to avoid choppy markets
- Enable Volume confirmation
**Indices (Lower Volatility)**:
- EMA Mode: Slow (13/26)
- SL ATR Multiplier: 0.8-1.2
- Enable POC proximity filters
- Enable RSI extreme filter
### Advanced Configuration
1. **Enable Optional Filters**: Navigate to "Signal Filters" section and enable filters that match your trading style
2. **Configure Market Analysis Tools**: Adjust FVG, Order Block, Fibonacci, and POC settings in their respective sections
3. **Customize Display**: Toggle chart display options to show/hide various elements based on your preference
---
## WHY THIS INDICATOR COMBINATION CREATES UNIQUE VALUE
### Multi-Layered Confluence Analysis
This script is not a simple indicator mashup. It implements a proprietary integration framework that creates synergistic value through three layers of analysis:
**Layer 1: Fibonacci Mathematics**
- Golden Zone identification (61.8%-78.6% retracement zone) using three-point trend-based calculation
- Extension targets based on swing structure mathematics
- Statistically significant retracement areas where price is likely to reverse
**Layer 2: Institutional Flow Analysis**
- Fair Value Gaps (FVGs) identify order flow gaps where price must return
- Order Blocks mark institutional accumulation/distribution zones
- Multi-timeframe POC analysis shows where liquidity is concentrated
- Liquidity zones identify where stop losses cluster
**Layer 3: Multi-Strategy Signal Generation**
- Six different entry methodologies provide multiple perspectives
- Shared risk management ensures consistent position sizing
- Adaptive confidence scoring evaluates confluence from all three layers
- Optional filters allow customization for different market conditions
### Proprietary Integration Framework
The unique value comes from how these components work together:
1. **Strategy generates signal** → 2. **FVG/Order Block validates institutional support** → 3. **POC confirms liquidity level** → 4. **Fibonacci provides target zones** → 5. **Risk management calculates optimal SL/TP placement**
This creates a complete trading system, not just a collection of indicators.
---
## TECHNICAL SPECIFICATIONS
- **Pine Script Version**: v6
- **Chart Type**: Overlay (displays on price chart)
- **Max Bars Back**: 5000 (for historical analysis)
- **Max Labels**: 500 (for win/loss tracking)
- **Compatibility**: Works on all timeframes and instruments
- **Performance**: Optimized for real-time execution
---
## DISCLAIMER
This script is a technical analysis tool and does not constitute financial, investment, trading, or other types of advice. Past performance does not guarantee future results. Always use proper risk management and never risk more than you can afford to lose. The script's signals are based on mathematical calculations and should be used in conjunction with your own analysis and risk management practices.
---
## SUPPORT AND ACCESS
This is an invite-only script. To request access:
1. Visit: www.pinescriptedge.com
2. Include your TradingView username and brief trading experience
3. Access will be reviewed and granted within 24 hours
**Note**: TradingView does NOT recommend paying for or using a script unless you fully trust its author and understand how it works. You may also find free, open-source alternatives in our community scripts.
---
## VERSION INFORMATION
**Momentum Master v1** - Initial release with multi-strategy framework and institutional flow analysis integration.
For updates and new features, follow the script or check the author's profile for version announcements.
Manifold Singularity EngineManifold Singularity Engine: Catastrophe Theory Detection Through Multi-Dimensional Topology Analysis
The Manifold Singularity Engine applies catastrophe theory from mathematical topology to multi-dimensional price space analysis, identifying potential reversal conditions by measuring manifold curvature, topological complexity, and fractal regime states. Unlike traditional reversal indicators that rely on price pattern recognition or momentum oscillators, this system reconstructs the underlying geometric surface (manifold) that price evolves upon and detects points where this topology undergoes catastrophic folding—mathematical singularities that correspond to forced directional changes in price dynamics.
The indicator combines three analytical frameworks: phase space reconstruction that embeds price data into a multi-dimensional coordinate system, catastrophe detection that measures when this embedded manifold reaches critical curvature thresholds indicating topology breaks, and Hurst exponent calculation that classifies the current fractal regime to adaptively weight detection sensitivity. This creates a geometry-based reversal detection system with visual feedback showing topology state, manifold distortion fields, and directional probability projections.
What Makes This Approach Different
Phase Space Embedding Construction
The core analytical method reconstructs price evolution as movement through a three-dimensional coordinate system rather than analyzing price as a one-dimensional time series. The system calculates normalized embedding coordinates: X = normalize(price_velocity, window) , Y = normalize(momentum_acceleration, window) , and Z = normalize(volume_weighted_returns, window) . These coordinates create a trajectory through phase space where price movement traces a path across a geometric surface—the market manifold.
This embedding approach differs fundamentally from traditional technical analysis by treating price not as a sequential data stream but as a dynamical system evolving on a curved surface in multi-dimensional space. The trajectory's geometric properties (curvature, complexity, folding) contain information about impending directional changes that single-dimension analysis cannot capture. When this manifold undergoes rapid topological deformation, price must respond with directional change—this is the mathematical basis for catastrophe detection.
Statistical normalization using z-score transformation (subtracting mean, dividing by standard deviation over a rolling window) ensures the coordinate system remains scale-invariant across different instruments and volatility regimes, allowing identical detection logic to function on forex, crypto, stocks, or indices without recalibration.
Catastrophe Score Calculation
The catastrophe detection formula implements a composite anomaly measurement combining multiple topology metrics: Catastrophe_Score = 0.45×Curvature_Percentile + 0.25×Complexity_Ratio + 0.20×Condition_Percentile + 0.10×Gradient_Percentile . Each component measures a distinct aspect of manifold distortion:
Curvature (κ) is computed using the discrete Laplacian operator: κ = √ , which measures how sharply the manifold surface bends at the current point. High curvature values indicate the surface is folding or developing a sharp corner—geometric precursors to catastrophic topology breaks. The Laplacian measures second derivatives (rate of change of rate of change), capturing acceleration in the trajectory's path through phase space.
Topological Complexity counts sign changes in the curvature field over the embedding window, measuring how chaotically the manifold twists and oscillates. A smooth, stable surface produces low complexity; a highly contorted, unstable surface produces high complexity. This metric detects when the geometric structure becomes informationally dense with multiple local extrema, suggesting an imminent topology simplification event (catastrophe).
Condition Number measures the Jacobian matrix's sensitivity: Condition = |Trace| / |Determinant|, where the Jacobian describes how small changes in price produce changes in the embedding coordinates. High condition numbers indicate numerical instability—points where the coordinate transformation becomes ill-conditioned, suggesting the manifold mapping is approaching a singularity.
Each metric is converted to percentile rank within a rolling window, then combined using weighted sum. The percentile transformation creates adaptive thresholds that automatically adjust to each instrument's characteristic topology without manual recalibration. The resulting 0-100% catastrophe score represents the current bar's position in the distribution of historical manifold distortion—values above the threshold (default 65%) indicate statistically extreme topology states where reversals become geometrically probable.
This multi-metric ensemble approach prevents false signals from isolated anomalies: all four geometric features must simultaneously indicate distortion for a high catastrophe score, ensuring only true manifold breaks trigger detection.
Hurst Exponent Regime Classification
The Hurst exponent calculation implements rescaled range (R/S) analysis to measure the fractal dimension of price returns: H = log(R/S) / log(n) , where R is the range of cumulative deviations from mean and S is the standard deviation. The resulting value classifies market behavior into three fractal regimes:
Trending Regime (H > 0.55) : Persistent price movement where future changes are positively correlated with past changes. The manifold exhibits directional momentum with smooth topology evolution. In this regime, catastrophe signals receive 1.2× confidence multiplier because manifold breaks in trending conditions produce high-magnitude directional changes.
Mean-Reverting Regime (H < 0.45) : Anti-persistent price movement where future changes tend to oppose past changes. The manifold exhibits oscillatory topology with frequent small-scale distortions. Catastrophe signals receive 0.8× confidence multiplier because reversal significance is diminished in choppy conditions where the manifold constantly folds at minor scales.
Random Walk Regime (H ≈ 0.50) : No statistical correlation in returns. The manifold evolution is geometrically neutral with moderate topology stability. Standard 1.0× confidence multiplier applies.
This adaptive weighting system solves a critical problem in reversal detection: the same geometric catastrophe has different trading implications depending on the fractal regime. A manifold fold in a strong trend suggests a significant reversal opportunity; the same fold in mean-reversion suggests a minor oscillation. The Hurst-based regime filter ensures detection sensitivity automatically adjusts to market character without requiring trader intervention.
The implementation uses logarithmic price returns rather than raw prices to ensure
stationarity, and applies the calculation over a configurable window (default 5 bars) to balance responsiveness with statistical validity. The Hurst value is then smoothed using exponential moving average to reduce noise while maintaining regime transition detection.
Multi-Layer Confirmation Architecture
The system implements five independent confirmation filters that must simultaneously validate
before any singularity signal generates:
1. Catastrophe Threshold : The composite anomaly score must exceed the configured threshold (default 0.65 on 0-1 scale), ensuring the manifold distortion is statistically extreme relative to recent history.
2. Pivot Structure Confirmation : Traditional swing high/low patterns (using ta.pivothigh and ta.pivotlow with configurable lookback) must form at the catastrophe bar. This ensures the geometric singularity coincides with observable price structure rather than occurring mid-swing where interpretation is ambiguous.
3. Swing Size Validation : The pivot magnitude must exceed a minimum threshold measured in ATR units (default 1.5× Average True Range). This filter prevents signals on insignificant price jiggles that lack meaningful reversal potential, ensuring only substantial swings with adequate risk/reward ratios generate signals.
4. Volume Confirmation : Current volume must exceed 1.3× the 20-period moving average, confirming genuine market participation rather than low-liquidity price noise. Manifold catastrophes without volume support often represent false topology breaks that don't translate to sustained directional change.
5. Regime Validity : The market must be classified as either trending (ADX > configured threshold, default 30) or volatile (ATR expansion > configured threshold, default 40% above 30-bar average), and must NOT be in choppy/ranging state. This critical filter prevents trading during geometrically unfavorable conditions where edge deteriorates.
All five conditions must evaluate true simultaneously for a signal to generate. This conjunction-based logic (AND not OR) dramatically reduces false positives while preserving true reversal detection. The architecture recognizes that geometric catastrophes occur frequently in noisy data, but only those catastrophes that align with confirming evidence across price structure, participation, and regime characteristics represent tradable opportunities.
A cooldown mechanism (default 8 bars between signals) prevents signal clustering at extended pivot zones where the manifold may undergo multiple small catastrophes during a single reversal process.
Direction Classification System
Unlike binary bull/bear systems, the indicator implements a voting mechanism combining four
directional indicators to classify each catastrophe:
Pivot Vote : +1 if pivot low, -1 if pivot high, 0 otherwise
Trend Vote : Based on slow frequency (55-period EMA) slope—+1 if rising, -1 if falling, 0 if flat
Flow Vote : Based on Y-gradient (momentum acceleration)—+1 if positive, -1 if negative, 0 if neutral
Mid-Band Vote : Based on price position relative to medium frequency (21-period EMA)—+1 if above, -1 if below, 0 if at
The total vote sum classifies the singularity: ≥2 votes = Bullish , ≤-2 votes = Bearish , -1 to +1 votes = Neutral (skip) . This majority-consensus approach ensures directional classification requires alignment across multiple timeframes and analysis dimensions rather than relying on a single indicator. Neutral signals (mixed voting) are displayed but should not be traded, as they represent geometric catastrophes without clear directional resolution.
Core Calculation Methodology
Embedding Coordinate Generation
Three normalized phase space coordinates are constructed from price data:
X-Dimension (Velocity Space):
price_velocity = close - close
X = (price_velocity - mean) / stdev over hurstWindow
Y-Dimension (Acceleration Space):
momentum = close - close
momentum_accel = momentum - momentum
Y = (momentum_accel - mean) / stdev over hurstWindow
Z-Dimension (Volume-Weighted Space):
vol_normalized = (volume - mean) / stdev over embedLength
roc = (close - close ) / close
Z = (roc × vol_normalized - mean) / stdev over hurstWindow
These coordinates define a point in 3D phase space for each bar. The trajectory connecting these points is the reconstructed manifold.
Gradient Field Calculation
First derivatives measure local manifold slope:
dX/dt = X - X
dY/dt = Y - Y
Gradient_Magnitude = √
The gradient direction indicates where the manifold is "pushing" price. Positive Y-gradient suggests upward topological pressure; negative Y-gradient suggests downward pressure.
Curvature Tensor Components
Second derivatives measure manifold bending using discrete Laplacian:
Laplacian_X = X - 2×X + X
Laplacian_Y = Y - 2×Y + Y
Laplacian_Magnitude = √
This is then normalized:
Curvature_Normalized = (Laplacian_Magnitude - mean) / stdev over embedLength
High normalized curvature (>1.5) indicates sharp manifold folding.
Complexity Accumulation
Sign changes in curvature field are counted:
Sign_Flip = 1 if sign(Curvature ) ≠ sign(Curvature ), else 0
Topological_Complexity = sum(Sign_Flip) over embedLength window
This measures oscillation frequency in the geometry. Complexity >5 indicates chaotic topology.
Condition Number Stability Analysis
Jacobian matrix sensitivity is approximated:
dX/dp = dX/dt / (price_change + epsilon)
dY/dp = dY/dt / (price_change + epsilon)
Jacobian_Determinant = (dX/dt × dY/dp) - (dX/dp × dY/dt)
Jacobian_Trace = dX/dt + dY/dp
Condition_Number = |Trace| / (|Determinant| + epsilon)
High condition numbers indicate numerical instability near singularities.
Catastrophe Score Assembly
Each metric is converted to percentile rank over embedLength window, then combined:
Curvature_Percentile = percentrank(abs(Curvature_Normalized), embedLength)
Gradient_Percentile = percentrank(Gradient_Magnitude, embedLength)
Condition_Percentile = percentrank(abs(Condition_Z_Score), embedLength)
Complexity_Ratio = clamp(Topological_Complexity / embedLength, 0, 1)
Final score:
Raw_Anomaly = 0.45×Curvature_P + 0.25×Complexity_R + 0.20×Condition_P + 0.10×Gradient_P
Catastrophe_Score = Raw_Anomaly × Hurst_Multiplier
Values are clamped to range.
Hurst Exponent Calculation
Rescaled range analysis on log returns:
Calculate log returns: r = log(close) - log(close )
Compute cumulative deviations from mean
Find range: R = max(cumulative_dev) - min(cumulative_dev)
Calculate standard deviation: S = stdev(r, hurstWindow)
Compute R/S ratio
Hurst = log(R/S) / log(hurstWindow)
Clamp to and smooth with 5-period EMA
Regime Classification Logic
Volatility Regime:
ATR_MA = SMA(ATR(14), 30)
Vol_Expansion = ATR / ATR_MA
Is_Volatile = Vol_Expansion > (1.0 + minVolExpansion)
Trend Regime (Corrected ADX):
Calculate directional movement (DM+, DM-)
Smooth with Wilder's RMA(14)
Compute DI+ and DI- as percentages
Calculate DX = |DI+ - DI-| / (DI+ + DI-) × 100
ADX = RMA(DX, 14)
Is_Trending = ADX > (trendStrength × 100)
Chop Detection:
Is_Chopping = NOT Is_Trending AND NOT Is_Volatile
Regime Validity:
Regime_Valid = (Is_Trending OR Is_Volatile) AND NOT Is_Chopping
Signal Generation Logic
For each bar:
Check if catastrophe score > topologyStrength threshold
Verify regime is valid
Confirm Hurst alignment (trending or mean-reverting with pivot)
Validate pivot quality (price extended outside spectral bands then re-entered)
Confirm volume/volatility participation
Check cooldown period has elapsed
If all true: compute directional vote
If vote ≥2: Bullish Singularity
If vote ≤-2: Bearish Singularity
If -1 to +1: Neutral (display but skip)
All conditions must be true for signal generation.
Visual System Architecture
Spectral Decomposition Layers
Three harmonic frequency bands visualize entropy state:
Layer 1 (Surface Frequency):
Center: EMA(8)
Width: ±0.3 × 0.5 × ATR
Transparency: 75% (most visible)
Represents fast oscillations
Layer 2 (Mid Frequency):
Center: EMA(21)
Width: ±0.5 × 0.5 × ATR
Transparency: 85%
Represents medium cycles
Layer 3 (Deep Frequency):
Center: EMA(55)
Width: ±0.7 × 0.5 × ATR
Transparency: 92% (most transparent)
Represents slow baseline
Convergence of layers indicates low entropy (stable topology). Divergence indicates high entropy (catastrophe building). This decomposition reveals how different frequency components of price movement interact—when all three align, the manifold is in equilibrium; when they separate, topology is unstable.
Energy Radiance Fields
Concentric boxes emanate from each singularity bar:
For each singularity, 5 layers are generated:
Layer n: bar_index ± (n × 1.5 bars), close ± (n × 0.4 × ATR)
Transparency gradient: inner 75% → outer 95%
Color matches signal direction
These fields visualize the "energy well" of the catastrophe—wider fields indicate stronger topology distortion. The exponential expansion creates a natural radiance effect.
Singularity Node Geometry
N-sided polygon (default hexagon) at each signal bar:
Vertices calculated using polar coordinates
Rotation angle: bar_index × 0.1 (creates animation)
Radius: ATR × singularity_strength × 2
Connects vertices with colored lines
The rotating geometric primitive marks the exact catastrophe bar with visual prominence.
Gradient Flow Field
Directional arrows display manifold slope:
Spawns every 3 bars when gradient_magnitude > 0.1
Symbol: "↗" if dY/dt > 0.1, "↘" if dY/dt < -0.1, "→" if neutral
Color: Bull/bear/neutral based on direction
Density limited to flowDensity parameter
Arrows cluster when gradient is strong, creating intuitive topology visualization.
Probability Projection Cones
Forward trajectory from each singularity:
Projects 10 bars forward
Direction based on vote classification
Center line: close + (direction × ATR × 3)
Uncertainty width: ATR × singularity_strength × 2
Dashed boundaries, solid center
These are mathematical projections based on current gradient, not price targets. They visualize expected manifold evolution if topology continues current trajectory.
Dashboard Metrics Explanation
The real-time control panel displays six core metrics plus regime status:
H (Hurst Exponent):
Value: Current Hurst (0-1 scale)
Label: TREND (>0.55), REVERT (<0.45), or RANDOM (0.45-0.55)
Icon: Direction arrow based on regime
Purpose: Shows fractal character—only trade when favorable
Σ (Catastrophe Score):
Value: Current composite anomaly (0-100%)
Bar gauge shows relative strength
Icon: ◆ if above threshold, ○ if below
Purpose: Primary signal strength indicator
κ (Curvature):
Value: Normalized Laplacian magnitude
Direction arrow shows sign
Color codes severity (green<0.8, yellow<1.5, red≥1.5)
Purpose: Shows manifold bending intensity
⟳ (Topology Complexity):
Value: Count of sign flips in curvature
Icon: ◆ if >3, ○ otherwise
Color codes chaos level
Purpose: Indicates geometric instability
V (Volatility Expansion):
Value: ATR expansion percentage above 30-bar average
Icon: ● if volatile, ○ otherwise
Purpose: Confirms energy present for reversal
T (Trend Strength):
Value: ADX reading (0-100)
Icon: ● if trending, ○ otherwise
Purpose: Shows directional bias strength
R (Regime):
Label: EXPLOSIVE / TREND / VOLATILE / CHOP / NEUTRAL
Icon: ✓ if valid, ✗ if invalid
Purpose: Go/no-go filter for trading
STATE (Bottom Display):
Shows: "◆ BULL SINGULARITY" (green), "◆ BEAR SINGULARITY" (red), "◆ WEAK/NEUTRAL" (orange), or "— Monitoring —" (gray)
Purpose: Current signal status at a glance
How to Use This Indicator
Initial Setup and Configuration
Apply the indicator to your chart with default settings as a starting point. The default parameters (21-bar embedding, 5-bar Hurst window, 2.5σ singularity threshold, 0.65 topology confirmation) are optimized for balanced detection across most instruments and timeframes. For very fast markets (scalping crypto, 1-5min charts), consider reducing embedding depth to 13-15 bars and Hurst window to 3 bars for more responsive detection. For slower markets (swing trading stocks, 4H-Daily charts), increase embedding depth to 34-55 bars and Hurst window to 8-10 bars for more stable topology measurement.
Enable the dashboard (top right recommended) to monitor real-time metrics. The control panel is your primary decision interface—glancing at the dashboard should instantly communicate whether conditions favor trading and what the current topology state is. Position and size the dashboard to remain visible but not obscure price action.
Enable regime filtering (strongly recommended) to prevent trading during choppy/ranging conditions where geometric edge deteriorates. This single setting can dramatically improve overall performance by eliminating low-probability environments.
Reading Dashboard Metrics for Trade Readiness
Before considering any trade, verify the dashboard shows favorable conditions:
Hurst (H) Check:
The Hurst Exponent reading is your first filter. Only consider trades when H > 0.50 . Ideal conditions show H > 0.60 with "TREND" label—this indicates persistent directional price movement where manifold catastrophes produce significant reversals. When H < 0.45 (REVERT label), the market is mean-reverting and catastrophes represent minor oscillations rather than substantial pivots. Do not trade in mean-reverting regimes unless you're explicitly using range-bound strategies (which this indicator is not optimized for). When H ≈ 0.50 (RANDOM label), edge is neutral—acceptable but not ideal.
Catastrophe (Σ) Monitoring:
Watch the Σ percentage build over time. Readings consistently below 50% indicate stable topology with no imminent reversals. When Σ rises above 60-65%, manifold distortion is approaching critical levels. Signals only fire when Σ exceeds the configured threshold (default 65%), so this metric pre-warns you of potential upcoming catastrophes. High-conviction setups show Σ > 75%.
Regime (R) Validation:
The regime classification must read TREND, VOLATILE, or EXPLOSIVE—never trade when it reads CHOP or NEUTRAL. The checkmark (✓) must be present in the regime cell for trading conditions to be valid. If you see an X (✗), skip all signals until regime improves. This filter alone eliminates most losing trades by avoiding geometrically unfavorable environments.
Combined High-Conviction Profile:
The strongest trading opportunities show simultaneously:
H > 0.60 (strong trending regime)
Σ > 75% (extreme topology distortion)
R = EXPLOSIVE or TREND with ✓
κ (Curvature) > 1.5 (sharp manifold fold)
⟳ (Complexity) > 4 (chaotic geometry)
V (Volatility) showing elevated ATR expansion
When all metrics align in this configuration, the manifold is undergoing severe distortion in a favorable fractal regime—these represent maximum-conviction reversal opportunities.
Signal Interpretation and Entry Logic
Bullish Singularity (▲ Green Triangle Below Bar):
This marker appears when the system detects a manifold catastrophe at a price low with bullish directional consensus. All five confirmation filters have aligned: topology score exceeded threshold, pivot low structure formed, swing size was significant, volume/volatility confirmed participation, and regime was valid. The green color indicates the directional vote totaled +2 or higher (majority bullish).
Trading Approach: Consider long entry on the bar immediately following the signal (bar after the triangle). The singularity bar itself is where the geometric catastrophe occurred—entering after allows you to see if price confirms the reversal. Place stop loss below the singularity bar's low (with buffer of 0.5-1.0 ATR for volatility). Initial target can be the previous swing high, or use the probability cone projection as a guide (though not a guarantee). Monitor the dashboard STATE—if it flips to "◆ BEAR SINGULARITY" or Hurst drops significantly, consider exiting even if target not reached.
Bearish Singularity (▼ Red Triangle Above Bar):
This marker appears when the system detects a manifold catastrophe at a price high with bearish directional consensus. Same five-filter confirmation process as bullish signals. The red color indicates directional vote totaled -2 or lower (majority bearish).
Trading Approach: Consider short entry on the bar following the signal. Place stop loss above the singularity bar's high (with buffer). Target previous swing low or use cone projection as reference. Exit if opposite signal fires or Hurst deteriorates.
Neutral Signal (● Orange Circle at Price Level):
This marker indicates the catastrophe detection system identified a topology break that passed catastrophe threshold and regime filters, but the directional voting system produced a mixed result (vote between -1 and +1). This means the four directional components (pivot, trend, flow, mid-band) are not in agreement about which way the reversal should resolve.
Trading Approach: Skip these signals. Neutral markers are displayed for analytical completeness but should not be traded. They represent geometric catastrophes without clear directional resolution—essentially, the manifold is breaking but the direction of the break is ambiguous. Trading neutral signals dramatically increases false signal rate. Only trade green (bullish) or red (bearish) singularities.
Visual Confirmation Using Spectral Layers
The three colored ribbons (spectral decomposition layers) provide entropy visualization that helps confirm signal quality:
Divergent Layers (High Entropy State):
When the three frequency bands (fast 8-period, medium 21-period, slow 55-period) are separated with significant gaps between them, the manifold is in high entropy state—different frequency components of price movement are pulling in different directions. This geometric tension precedes catastrophes. Strong signals often occur when layers are divergent before the signal, then begin reconverging immediately after.
Convergent Layers (Low Entropy State):
When all three ribbons are tightly clustered or overlapping, the manifold is in equilibrium—all frequency components agree. This stable geometry makes catastrophe detection more reliable because topology breaks clearly stand out against the baseline stability. If you see layers converge, then a singularity fires, then layers diverge, this pattern suggests a genuine regime transition.
Signal Quality Assessment:
High-quality singularity signals should show:
Divergent layers (high entropy) in the 5-10 bars before signal
Singularity bar occurs when price has extended outside at least one of the spectral bands (shows pivot extended beyond equilibrium)
Close of singularity bar re-enters the spectral band zone (shows mean reversion starting)
Layers begin reconverging in 3-5 bars after signal (shows new equilibrium forming)
This pattern visually confirms the geometric narrative: manifold became unstable (divergence), reached critical distortion (extended outside equilibrium), broke catastrophically (singularity), and is now stabilizing in new direction (reconvergence).
Using Energy Fields for Trade Management
The concentric glowing boxes around each singularity visualize the topology distortion
magnitude:
Wide Energy Fields (5+ Layers Visible):
Large radiance indicates strong catastrophe with high manifold curvature. These represent significant topology breaks and typically precede larger price moves. Wide fields justify wider profit targets and longer hold times. The outer edge of the largest box can serve as a dynamic support/resistance zone—price often respects these geometric boundaries.
Narrow Energy Fields (2-3 Layers):
Smaller radiance indicates moderate catastrophe. While still valid signals (all filters passed), expect smaller follow-through. Use tighter profit targets and be prepared for quicker exit if momentum doesn't develop. These are valid but lower-conviction trades.
Field Interaction Zones:
When energy fields from consecutive signals overlap or touch, this indicates a prolonged topology distortion region—often corresponds to consolidation zones or complex reversal patterns (head-and-shoulders, double tops/bottoms). Be more cautious in these areas as the manifold is undergoing extended restructuring rather than a clean catastrophe.
Probability Cone Projections
The dashed cone extending forward from each singularity is a mathematical projection, not a
price target:
Cone Direction:
The center line direction (upward for bullish, downward for bearish, flat for neutral) shows the expected trajectory based on current manifold gradient and singularity direction. This is where the topology suggests price "should" go if the catastrophe completes normally.
Cone Width:
The uncertainty band (upper and lower dashed boundaries) represents the range of outcomes given current volatility (ATR-based). Wider cones indicate higher uncertainty—expect more price volatility even if direction is correct. Narrower cones suggest more constrained movement.
Price-Cone Interaction:
Price following near the center line = catastrophe resolving as expected, geometric projection accurate
Price breaking above upper cone = stronger-than-expected reversal, consider holding for larger targets
Price breaking below lower cone (for bullish signal) = catastrophe failing, manifold may be re-folding in opposite direction, consider exit
Price oscillating within cone = normal reversal process, hold position
The 10-bar projection length means cones show expected behavior over the next ~10 bars. Don't confuse this with longer-term price targets.
Gradient Flow Field Interpretation
The directional arrows (↗, ↘, →) scattered across the chart show the manifold's Y-gradient (vertical acceleration dimension):
Upward Arrows (↗):
Positive Y-gradient indicates the momentum acceleration dimension is pushing upward—the manifold topology has upward "slope" at this location. Clusters of upward arrows suggest bullish topological pressure building. These often appear before bullish singularities fire.
Downward Arrows (↘):
Negative Y-gradient indicates downward topological pressure. Clusters precede bearish singularities.
Horizontal Arrows (→):
Neutral gradient indicates balanced topology with no strong directional pressure.
Using Flow Field:
The arrows provide real-time topology state information even between singularity signals. If you're in a long position from a bullish singularity and begin seeing increasing downward arrows appearing, this suggests manifold gradient is shifting—consider tightening stops. Conversely, if arrows remain upward or neutral, topology supports continuation.
Don't confuse arrow direction with immediate price direction—arrows show geometric slope, not price prediction. They're confirmatory context, not entry signals themselves.
Parameter Optimization for Your Trading Style
For Scalping / Fast Trading (1m-15m charts):
Embedding Depth: 13-15 bars (faster topology reconstruction)
Hurst Window: 3 bars (responsive fractal detection)
Singularity Threshold: 2.0-2.3σ (more sensitive)
Topology Confirmation: 0.55-0.60 (lower barrier)
Min Swing Size: 0.8-1.2 ATR (accepts smaller moves)
Pivot Lookback: 3-4 bars (quick pivot detection)
This configuration increases signal frequency for active trading but requires diligent monitoring as false signal rate increases. Use tighter stops.
For Day Trading / Standard Approach (15m-4H charts):
Keep default settings (21 embed, 5 Hurst, 2.5σ, 0.65 confirmation, 1.5 ATR, 5 pivot)
These are balanced for quality over quantity
Best win rate and risk/reward ratio
Recommended for most traders
For Swing Trading / Position Trading (4H-Daily charts):
Embedding Depth: 34-55 bars (stable long-term topology)
Hurst Window: 8-10 bars (smooth fractal measurement)
Singularity Threshold: 3.0-3.5σ (only extreme catastrophes)
Topology Confirmation: 0.75-0.85 (high conviction only)
Min Swing Size: 2.5-4.0 ATR (major moves only)
Pivot Lookback: 8-13 bars (confirmed swings)
This configuration produces infrequent but highly reliable signals suitable for position sizing and longer hold times.
Volatility Adaptation:
In extremely volatile instruments (crypto, penny stocks), increase Min Volatility Expansion to 0.6-0.8 to avoid over-signaling during "always volatile" conditions. In stable instruments (major forex pairs, blue-chip stocks), decrease to 0.3 to allow signals during moderate volatility spikes.
Trend vs Range Preference:
If you prefer trading only strong trends, increase Min Trend Strength to 0.5-0.6 (ADX > 50-60). If you're comfortable with volatility-based trading in weaker trends, decrease to 0.2 (ADX > 20). The default 0.3 balances both approaches.
Complete Trading Workflow Example
Step 1 - Pre-Session Setup:
Load chart with MSE indicator. Check dashboard position is visible. Verify regime filter is enabled. Review recent signals to gauge current instrument behavior.
Step 2 - Market Assessment:
Observe dashboard Hurst reading. If H < 0.45 (mean-reverting), consider skipping this session or using other strategies. If H > 0.50, proceed. Check regime shows TREND, VOLATILE, or EXPLOSIVE with checkmark—if CHOP, wait for regime shift alert.
Step 3 - Signal Wait:
Monitor catastrophe score (Σ). Watch for it climbing above 60%. Observe spectral layers—look for divergence building. If you see curvature (κ) rising above 1.0 and complexity (⟳) increasing, catastrophe is building. Do not anticipate—wait for the actual signal marker.
Step 4 - Signal Recognition:
▲ Bullish or ▼ Bearish triangle appears at a bar. Dashboard STATE changes to "◆ BULL/BEAR SINGULARITY". Energy field appears around the signal bar. Check signal quality:
Was Σ > 70% at signal? (Higher quality)
Are energy fields wide? (Stronger catastrophe)
Did layers diverge before and reconverge after? (Clean break)
Is Hurst still > 0.55? (Good regime)
Step 5 - Entry Decision:
If signal is green/red (not orange neutral), all confirmations look strong, and no immediate contradicting factors appear, prepare entry on next bar open. Wait for confirmation bar to form—ideally it should close in the signal direction (bullish signal → bar closes higher, bearish signal → bar closes lower).
Step 6 - Position Entry:
Enter at open or shortly after open of bar following signal bar. Set stop loss: for bullish signals, place stop at singularity_bar_low - (0.75 × ATR); for bearish signals, place stop at singularity_bar_high + (0.75 × ATR). The buffer accommodates volatility while protecting against catastrophe failure.
Step 7 - Trade Management:
Monitor dashboard continuously:
If Hurst drops below 0.45, consider reducing position
If opposite singularity fires, exit immediately (manifold has re-folded)
If catastrophe score drops below 40% and stays there, topology has stabilized—consider partial profit taking
Watch gradient flow arrows—if they shift to opposite direction persistently, tighten stops
Step 8 - Profit Taking:
Use probability cone as a guide—if price reaches outer cone boundary, consider taking partial profits. If price follows center line cleanly, hold for larger target. Traditional technical targets work well: previous swing high/low, round numbers, Fibonacci extensions. Don't expect precision—manifold projections give direction and magnitude estimates, not exact prices.
Step 9 - Exit:
Exit on: (a) opposite signal appears, (b) dashboard shows regime became invalid (checkmark changes to X), (c) technical target reached, (d) Hurst deteriorates significantly, (e) stop loss hit, or (f) time-based exit if using session limits. Never hold through opposite singularity signals—the manifold has broken in the other direction and your trade thesis is invalidated.
Step 10 - Post-Trade Review:
After exit, review: Did the probability cone projection align with actual price movement? Were the energy fields proportional to move size? Did spectral layers show expected reconvergence? Use these observations to calibrate your interpretation of signal quality over time.
Best Performance Conditions
This topology-based approach performs optimally in specific market environments:
Favorable Conditions:
Well-Developed Swing Structure: Markets with clear rhythm of advances and declines where pivots form at regular intervals. The manifold reconstruction depends on swing formation, so instruments that trend in clear waves work best. Stocks, major forex pairs during active sessions, and established crypto assets typically exhibit this characteristic.
Sufficient Volatility for Topology Development: The embedding process requires meaningful price movement to construct multi-dimensional coordinates. Extremely quiet markets (tight consolidations, holiday trading, after-hours) lack the volatility needed for manifold differentiation. Look for ATR expansion above average—when volatility is present, geometry becomes meaningful.
Trending with Periodic Reversals: The ideal environment is not pure trend (which rarely reverses) nor pure range (which reverses constantly at small scale), but rather trending behavior punctuated by occasional significant counter-trend reversals. This creates the catastrophe conditions the system is designed to detect: manifold building directional momentum, then undergoing sharp topology break at extremes.
Liquid Instruments Where EMAs Reflect True Flow: The spectral layers and frequency decomposition require that moving averages genuinely represent market consensus. Thinly traded instruments with sporadic orders don't create smooth manifold topology. Prefer instruments with consistent volume where EMA calculations reflect actual capital flow rather than random tick sequences.
Challenging Conditions:
Extremely Choppy / Whipsaw Markets: When price oscillates rapidly with no directional persistence (Hurst < 0.40), the manifold undergoes constant micro-catastrophes that don't translate to tradable reversals. The regime filter helps avoid these, but awareness is important. If you see multiple neutral signals clustering with no follow-through, market is too chaotic for this approach.
Very Low Volatility Consolidation: Tight ranges with ATR below average cause the embedding coordinates to compress into a small region of phase space, reducing geometric differentiation. The manifold becomes nearly flat, and catastrophe detection loses sensitivity. The regime filter's volatility component addresses this, but manually avoiding dead markets improves results.
Gap-Heavy Instruments: Stocks that gap frequently (opening outside previous close) create discontinuities in the manifold trajectory. The embedding process assumes continuous evolution, so gaps introduce artifacts. Most gaps don't invalidate the approach, but instruments with daily gaps >2% regularly may show degraded performance. Consider using higher timeframes (4H, Daily) where gaps are less proportionally significant.
Parabolic Moves / Blowoff Tops: When price enters an exponential acceleration phase (vertical rally or crash), the manifold evolves too rapidly for the standard embedding window to track. Catastrophe detection may lag or produce false signals mid-move. These conditions are rare but identifiable by Hurst > 0.75 combined with ATR expansion >2.0× average. If detected, consider sitting out or using very tight stops as geometry is in extreme distortion.
The system adapts by reducing signal frequency in poor conditions—if you notice long periods with no signals, the topology likely lacks the geometric structure needed for reliable catastrophe detection. This is a feature, not a bug: it prevents forced trading during unfavorable environments.
Theoretical Justification for Approach
Why Manifold Embedding?
Traditional technical analysis treats price as a one-dimensional time series: current price is predicted from past prices in sequential order. This approach ignores the structure of price dynamics—the relationships between velocity, acceleration, and participation that govern how price actually evolves.
Dynamical systems theory (from physics and mathematics) provides an alternative framework: treat price as a state variable in a multi-dimensional phase space. In this view, each market condition corresponds to a point in N-dimensional space, and market evolution is a trajectory through this space. The geometry of this space (its topology) constrains what trajectories are possible.
Manifold embedding reconstructs this hidden geometric structure from observable price data. By creating coordinates from velocity, momentum acceleration, and volume-weighted returns, we map price evolution onto a 3D surface. This surface—the manifold—reveals geometric relationships that aren't visible in price charts alone.
The mathematical theorem underlying this approach (Takens' Embedding Theorem from dynamical systems theory) proves that for deterministic or weakly stochastic systems, a state space reconstruction from time-delayed observations of a single variable captures the essential dynamics of the full system. We apply this principle: even though we only observe price, the embedded coordinates (derivatives of price) reconstruct the underlying dynamical structure.
Why Catastrophe Theory?
Catastrophe theory, developed by mathematician René Thom (Fields Medal 1958), describes how continuous systems can undergo sudden discontinuous changes when control parameters reach critical values. A classic example: gradually increasing force on a beam causes smooth bending, then sudden catastrophic buckling. The beam's geometry reaches a critical curvature where topology must break.
Markets exhibit analogous behavior: gradual price changes build tension in the manifold topology until critical distortion is reached, then abrupt directional change occurs (reversal). Catastrophes aren't random—they're mathematically necessary when geometric constraints are violated.
The indicator detects these geometric precursors: high curvature (manifold bending sharply), high complexity (topology oscillating chaotically), high condition number (coordinate mapping becoming singular). These metrics quantify how close the manifold is to a catastrophic fold. When all simultaneously reach extreme values, topology break is imminent.
This provides a logical foundation for reversal detection that doesn't rely on pattern recognition or historical correlation. We're measuring geometric properties that mathematically must change when systems reach critical states. This is why the approach works across different instruments and timeframes—the underlying geometry is universal.
Why Hurst Exponent?
Markets exhibit fractal behavior: patterns at different time scales show statistical self-similarity. The Hurst exponent quantifies this fractal structure by measuring long-range dependence in returns.
Critically for trading, Hurst determines whether recent price movement predicts future direction (H > 0.5) or predicts the opposite (H < 0.5). This is regime detection: trending vs mean-reverting behavior.
The same manifold catastrophe has different trading implications depending on regime. In trending regime (high Hurst), catastrophes represent significant reversal opportunities because the manifold has been building directional momentum that suddenly breaks. In mean-reverting regime (low Hurst), catastrophes represent minor oscillations because the manifold constantly folds at small scales.
By weighting catastrophe signals based on Hurst, the system adapts detection sensitivity to the current fractal regime. This is a form of meta-analysis: not just detecting geometric breaks, but evaluating whether those breaks are meaningful in the current fractal context.
Why Multi-Layer Confirmation?
Geometric anomalies occur frequently in noisy market data. Not every high-curvature point represents a tradable reversal—many are artifacts of microstructure noise, order flow imbalances, or low-liquidity ticks.
The five-filter confirmation system (catastrophe threshold, pivot structure, swing size, volume, regime) addresses this by requiring geometric anomalies to align with observable market evidence. This conjunction-based logic implements the principle: extraordinary claims require extraordinary evidence .
A manifold catastrophe (extraordinary geometric event) alone is not sufficient. We additionally require: price formed a pivot (visible structure), swing was significant (adequate magnitude), volume confirmed participation (capital backed the move), and regime was favorable (trending or volatile, not chopping). Only when all five dimensions agree do we have sufficient evidence that the geometric anomaly represents a genuine reversal opportunity rather than noise.
This multi-dimensional approach is analogous to medical diagnosis: no single test is conclusive, but when multiple independent tests all suggest the same condition, confidence increases dramatically. Each filter removes a different category of false signals, and their combination creates a robust detection system.
The result is a signal set with dramatically improved reliability compared to any single metric alone. This is the power of ensemble methods applied to geometric analysis.
Important Disclaimers
This indicator applies mathematical topology and catastrophe theory to multi-dimensional price space reconstruction. It identifies geometric conditions where manifold curvature, topological complexity, and coordinate singularities suggest potential reversal zones based on phase space analysis. It should not be used as a standalone trading system.
The embedding coordinates, catastrophe scores, and Hurst calculations are deterministic mathematical formulas applied to historical price data. These measurements describe current and recent geometric relationships in the reconstructed manifold but do not predict future price movements. Past geometric patterns and singularity markers do not guarantee future market behavior will follow similar topology evolution.
The manifold reconstruction assumes certain mathematical properties (sufficient embedding dimension, quasi-stationarity, continuous dynamics) that may not hold in all market conditions. Gaps, flash crashes, circuit breakers, news events, and other discontinuities can violate these assumptions. The system attempts to filter problematic conditions through regime classification, but cannot eliminate all edge cases.
The spectral decomposition, energy fields, and probability cones are visualization aids that represent mathematical constructs, not price predictions. The probability cone projects current gradient forward assuming topology continues current trajectory—this is a mathematical "if-then" statement, not a forecast. Market topology can and does change unexpectedly.
All trading involves substantial risk. The singularity markers represent analytical conditions where geometric mathematics align with threshold criteria, not certainty of directional change. Use appropriate risk management for every trade: position sizing based on account risk tolerance (typically 1-2% maximum risk per trade), stop losses placed beyond recent structure plus volatility buffer, and never risk capital needed for living expenses.
The confirmation filters (pivot, swing size, volume, regime) are designed to reduce false signals but cannot eliminate them entirely. Markets can produce geometric anomalies that pass all filters yet fail to develop into sustained reversals. This is inherent to probabilistic systems operating on noisy real-world data.
No indicator can guarantee profitable trades or eliminate losses. The catastrophe detection provides an analytical framework for identifying potential reversal conditions, but actual trading outcomes depend on numerous factors including execution, slippage, spreads, position sizing, risk management, psychological discipline, and market conditions that may change after signal generation.
Use this tool as one component of a comprehensive trading plan that includes multiple forms of analysis, proper risk management, emotional discipline, and realistic expectations about win rates and drawdowns. Combine catastrophe signals with additional confirmation methods such as support/resistance analysis, volume patterns, multi-timeframe alignment, and broader market context.
The spacing filter, cooldown mechanism, and regime validation are designed to reduce noise and over-signaling, but market conditions can change rapidly and render any analytical signal invalid. Always use stop losses and never risk capital you cannot afford to lose. Past performance of detection accuracy does not guarantee future results.
Technical Implementation Notes
All calculations execute on closed bars only—signals and metric values do not repaint after bar close. The indicator does not use any lookahead bias in its calculations. However, the pivot detection mechanism (ta.pivothigh and ta.pivotlow) inherently identifies pivots with a lag equal to the lookback parameter, meaning the actual pivot occurred at bar but is recognized at bar . This is standard behavior for pivot functions and is not repainting—once recognized, the pivot bar never changes.
The normalization system (z-score transformation over rolling windows) requires approximately 30-50 bars of historical data to establish stable statistics. Values in the first 30-50 bars after adding the indicator may show instability as the rolling means and standard deviations converge. Allow adequate warmup period before relying on signals.
The spectral layer arrays, energy field boxes, gradient flow labels, and node geometry lines are subject to TradingView drawing object limits (500 lines, 500 boxes, 500 labels per indicator as specified in settings). The system implements automatic cleanup by deleting oldest objects when limits approach, but on very long charts with many signals, some historical visual elements may be removed to stay within limits. This does not affect signal generation or dashboard metrics—only historical visual artifacts.
Dashboard and visual rendering update only on the last bar to minimize computational overhead. The catastrophe detection logic executes on every bar, but table cells and drawing objects refresh conditionally to optimize performance. If experiencing chart lag, reduce visual complexity: disable spectral layers, energy fields, or flow field to improve rendering speed. Core signal detection continues to function with all visual elements disabled.
The Hurst calculation uses logarithmic returns rather than raw price to ensure stationarity, and implements clipping to range to handle edge cases where R/S analysis produces invalid values (which can occur during extended periods of identical prices or numerical overflow). The 5-period EMA smoothing reduces noise while maintaining responsiveness to regime transitions.
The condition number calculation adds epsilon (1e-10) to denominators to prevent division by zero when Jacobian determinant approaches zero—which is precisely the singularity condition we're detecting. This numerical stability measure ensures the indicator doesn't crash when detecting the very phenomena it's designed to identify.
The indicator has been tested across multiple timeframes (5-minute through daily) and multiple asset classes (forex majors, stock indices, individual equities, cryptocurrencies, commodities, futures). It functions identically across all instruments due to the adaptive normalization approach and percentage-based metrics. No instrument-specific code or parameter sets are required.
The color scheme system implements seven preset themes plus custom mode. Color assignments are applied globally and affect all visual elements simultaneously. The opacity calculation system multiplies component-specific transparency with master opacity to create hierarchical control—adjusting master opacity affects all visuals proportionally while maintaining their relative transparency relationships.
All alert conditions trigger only on bar close to prevent false alerts from intrabar fluctuations. The regime transition alerts (VALID/INVALID) are particularly useful for knowing when trading edge appears or disappears, allowing traders to adjust activity levels accordingly.
— Dskyz, Trade with insight. Trade with anticipation.
📊 Monitor F&M - RLYONSCRIPT OBJECTIVE
It's a confluence system that combines four key indicators to identify high-probability trading setups. It basically tells you when and where to enter the market with greater confidence.
🔧 THE 4 BASE INDICATORS
1. ADX (Average Directional Index)
What it measures: The strength of the trend (not the direction)
How to use it:
ADX ≥ 25 = STRONG trend ✅
ADX < 25 = Weak or sideways trend
What it does: Filters trades. You only look for entries when there is real strength in the market.
2. DI+ and DI- (Directional Indicators)
What it measures: The direction of the trend.
How to use it:
DI+ > DI- = Bullish trend 📈
DI- > DI+ = Bearish trend 📉
What it does: Defines whether you are looking for buys or sells.
3. TTM Squeeze (Bollinger Bands + Keltner Channels)
What it measures: Volatility compression and explosion.
States:
Squeeze ON 🔴: Volatility compressed (like a tightened spring).
Squeeze OFF 🟢: Volatility released (the spring is released = strong movement).
Transition 🔵: Changing state.
Momentum: The green/red histogram shows the direction of the movement.
Green rising = Strong bullish trend.
Red falling = Strong bearish trend.
4. RSI (Relative Strength Index)
What it measures: Whether the price is overbought or oversold.
Zones:
RSI > 70 = Overbought ⚠️ (be careful with purchases)
RSI < 30 = Oversold ✅ (bullish opportunity zone)
RSI 40-60 = Neutral zone/ideal for pullbacks
🎯 THE 2 MAIN STRATEGIES
STRATEGY 1: MOMENTUM (The strongest) 🚀
BUY setup:
✅ Squeeze released (changed from ON to OFF)
✅ Momentum green AND growing
✅ ADX ≥ 25 (strong trend)
✅ RSI not overbought (< 70)
SELL setup:
✅ Squeeze released (changed from ON to OFF)
✅ Momentum red AND Decreasing
✅ ADX ≥ 25 (strong trend)
✅ RSI not oversold (> 30)
When to trade: When you see the triangle 🚀 on the chart
STRATEGY 2: PULLBACK (Established trend) 📈📉
BUY setup:
✅ DI+ > DI- (established uptrend)
✅ ADX ≥ 25 (strong trend)
✅ RSI between 40-55 (healthy pullback)
✅ Momentum starting to turn upward
SELL setup:
✅ DI- > DI+ (established downtrend)
✅ ADX ≥ 25 (strong trend)
✅ RSI between 45-60 (healthy pullback)
✅ Momentum starting to turn downward
When to trade: When you see the "PB" circle in the graph
Gabriel's Squeeze Momentum📊 Gabriel’s Squeeze Momentum — Deluxe Volatility + Momentum Suite
An advanced, all-in-one squeeze & momentum framework that times volatility compression/expansion and trend shifts, with optional CVD (cumulative volume delta) momentum, ATR zone context, Discontinued Signal Lines (DSL) scalps, Colored DMI trend label, Williams VIX Fix (WVF) low-volatility exhaustion pings, Buff’s VTTI/VPCI volume confirmation, and real-time divergence detection.
What it does:
Discover Squeezes. They occur when volatility contracts, often preceding significant price moves.
Measures momentum with a fast, ATR-normalized linear regression—optionally on Price or CVD—so you see direction and “how hard it’s pushing.”
🧭 Signal Legend ~ Colors the squeeze so you instantly know regime:
🟡 / 🟣 (Tight/Very Tight): Coiled spring; prepare a plan.
🔴 / ⚫ = (Regular/Wide): Watch for Divergences between Price and Momentum.
🟢 (Fired): Expansion started; trade with momentum cross and bias.
Adds context bands at ±1/±2/±3 ATR (“trend / expansion / OB-OS”) to filter late or weak signals.
DSL (Discontinued Signal Lines) give early scalp flips on momentum vs. adaptive bands.
DMI label & triangles communicate trend strength and whether +DI / −DI is in control.
Williams VIX Fix flags capitulation/exhaustion style spikes (with optional VIX proxy).
VTTI/VPCI modules confirm when volume aligns with price trend or contradicts it.
Divergences (regular & hidden) auto-draw with optional live (may repaint) or on-close.
🎢 Squeeze Momentum — How the Logic Works 🎢
The Squeeze Momentum model is built on the principle of volatility compression and expansion. In markets, periods of low volatility are often followed by explosive moves, while high volatility eventually contracts. The “squeeze” seeks to identify these compression phases and prepare traders for the likely expansion that follows.
This indicator achieves that by comparing Bollinger Bands (BB) to Keltner Channels (KC).
Bands: Bollinger vs. Keltner
Bollinger Bands (BB): Calculated using a Simple Moving Average (SMA) of price and standard deviations (σ) of the closing price. The bands expand and contract depending on volatility.
Keltner Channels (KC): Built from an SMA plus/minus multiples of the Average True Range (ATR). Unlike some simplified squeeze indicators that approximate ATR, this implementation uses a true ATR-based KC, ensuring accuracy across different assets and timeframes.
By comparing whether the Bollinger Bands are inside or outside the Keltner Channels, the indicator identifies different squeeze regimes, each representing a distinct volatility environment.
📦 Regime Colors
The squeeze states are color-coded for quick interpretation:
🔹Wide Squeeze (⚫): BB inside KC with a high ATR multiplier. Extremely low volatility, often before major expansion.
🔹Normal Squeeze (🔴): BB inside KC with a moderate ATR multiplier (about 25% more sensitive than Wide). Typical compression setting.
🔹Narrow Squeeze (🟡): BB inside KC with a lower ATR multiplier (about 50% more sensitive than Wide). Signals tighter compression.
🔹Very Narrow Squeeze (🟣): BB inside KC with the lowest ATR multiplier (100% more sensitive than Wide). Indicates extreme coiling.
🔹Fired Squeeze (🟢): BB break outside KC. Marks the release of volatility and potential trend acceleration.
This multi-layered system improves upon classical SQZPRO by using precisely calculated Keltner Channels and multiple sensitivity levels, giving traders more granular information about volatility states.
🔒 Multi-Timeframe Support
The indicator automatically adjusts squeeze thresholds for different timeframes — hourly, 4-hour, daily, weekly, and monthly charts. Each regime has been manually tuned for its timeframe, allowing traders to use the same tool whether scalping, swing trading, or holding longer-term positions.
🎯 Momentum Core
Detecting a squeeze is only half the equation — the indicator also includes a momentum engine to determine direction and strength.
Price momentum is measured as the distance of Close from its Highest High and Lowest Low range, smoothed with a Simple Moving Average, and refined with Linear Regression.
This value is then divided by ATR, normalizing momentum relative to volatility.
Optionally, CVD Mode (Cumulative Volume Delta ÷ Volume) can replace price momentum for assets where order-flow and volume dynamics dominate (e.g., crypto).
🦆 Signal Line
Momentum is paired with a Simple Moving Average signal line:
🔹Bullish: Momentum > Signal.
🔹Bearish: Momentum < Signal.
This crossover logic provides directional bias and filters for false squeezes.
🚀 When to Use Price vs. CVD
CVD Mode (Crypto, FX with tick volume): Best for assets with strong volume/order-flow signals.
Price Mode (Equities, Commodities, Higher TFs): Best for assets with irregular or thin volume data.
🛢️ATR Zones (context filter) 🛢️
Its design is straightforward yet effective: it measures the difference between the current price from its highest highs, lowest lows, and a moving average over a chosen period, then expresses that difference in terms of the Average True Range (ATR) over the same period. By normalizing price deviations against volatility, ATR provides a clear sense of how far and how fast price is moving relative to its “normal” range.
Interpreting the Zone
Positive Values: When it is above zero, price is trading above its HH, LL, and moving average, suggesting bullish momentum. The higher the value, the stronger the momentum relative to volatility.
Negative Values: When the Momentum is below zero, price is trading below its HH, LL, and moving average, signaling bearish momentum. The deeper the reading, the stronger the downside pressure.
Magnitude Matters: Because the Momentum is expressed in ATR units, traders can immediately gauge whether the move is small (less than 1 ATR), moderate (1–2 ATRs), or extreme (3+ ATRs). This makes it especially useful for assessing overbought or oversold conditions in a normalized way.
Strengths:
🔹Volatility-Normalized: Unlike simple squeeze momentum oscillators that have different OB/OS levels, this Momentum adjusts for volatility. This makes signals more consistent across assets with different volatility profiles.
🔹Simplicity:
±1 ATR: trending zone (bulls above +1, bears below −1)
±2 ATR: expansion (keep, add, or trail). Stretch/risk of mean reversion.
±3 ATR: potential exhaustion/mean-revert zone.
🔹Momentum Clarity: By framing momentum in ATR terms, it is easier to distinguish between a small deviation from trend and a genuinely significant move. Sometimes it is a good sign that it trend to ±3/2 ATR, looks for similar directional moves.
Color: The script shades +2/+3 (OB) and −2/−3 (OS) areas and provides swing alerts at ±1 ATR.
💚 What Are Discontinued Signal Lines (DSL)? 💚
In technical analysis, one of the most common tools for smoothing out noisy data is the signal line. This concept appears in many indicators, such as the MACD or stochastic oscillator, where the raw value of an indicator is compared to a smoothed version of itself. The signal line acts as a lagging filter, making it easier to identify shifts in momentum, crossovers, and directional changes.
While useful, the classic signal line approach has limitations. By design, a single smoothed line introduces lag, which means traders may receive signals later than ideal. Additionally, a one-size-fits-all smoothing process often struggles to adapt to different levels of volatility or rapidly changing market conditions.
This is where Discontinued Signal Lines (DSL) come in. DSL is an advanced extension of the traditional signal line concept. Instead of relying on just one smoothed comparison, DSL employs multiple adaptive lines that adjust dynamically to the current state of the indicator. These adaptive lines effectively “discontinue” the dependence on a single, fixed smoothing method, producing a more flexible and nuanced representation of market conditions.
How DSL Works?
Traditional Signal Line: Compares an the Momentum against its own moving average. Provides crossover signals when the raw indicator value moves above or below the smoothed line.
Strength: reduces noise. Weakness: delayed signals and limited adaptability.
DSL Extension: Uses multiple adaptive lines that respond differently to the indicator’s current behavior. Instead of one static moving average, the DSL approach creates faster and slower “reaction lines.” These lines adapt dynamically, capturing acceleration or deceleration in the indicator’s state.
Result: Traders see how momentum is evolving across multiple adaptive thresholds. This reduces false signals and improves responsiveness in volatile conditions.
Benefits of Discontinued Signal Lines
🔹Nuanced Trend Detection
DSL doesn’t just flag when momentum changes direction—it shows the quality of that shift, highlighting whether it is gaining strength, losing steam, or consolidating.
🔹Adaptability Across Markets
Because DSL adjusts to the Momentum’s own dynamics, it works well across different asset classes and timeframes, from equities and futures to forex and crypto.
🔹Earlier Signal Recognition
Multiple adaptive lines allow traders to spot developing trends earlier than with a single smoothed signal line, without being overwhelmed by raw indicator noise.
🔹Better Confirmation
DSL is particularly useful for confirmation. If both adaptive lines agree then a fill is applied in the direction, confidence in the trend is higher as the color turns bull/bear.
🔹Practical Uses
Momentum Trading: Spot acceleration or deceleration in trend strength.
Trend Confirmation: Verify whether a breakout has momentum behind it.
Noise Filtering: Smooth out erratic moves while retaining adaptability.
⚖️ Colored Directional Movement Index (CDMI) ⚖️
The Directional Movement Index (DMI), created by J. Welles Wilder, is one of the most respected trend-following indicators in technical analysis. It is actually a family of three separate indicators combined into one: the +DI (Positive Directional Indicator), the –DI (Negative Directional Indicator), and the ADX (Average Directional Index). Together, they measure not only whether the market is trending but also the strength of that trend. Traders have used the DMI for decades to identify trend direction, gauge momentum, and filter out periods of market noise.
However, despite its reliability, the traditional DMI can be challenging to interpret. Reading three separate lines at once and extracting meaningful signals requires both experience and careful observation. This complexity often discourages newer traders from fully utilizing its power.
The Colored Directional Movement Index (CDMI) is a modern reinterpretation of Wilder’s classic tool. It condenses the same information into a single visual line while using color, shape, and density to communicate what’s happening beneath the surface. The goal is simple: make the DMI’s insights faster to read, easier to act upon, and more intuitive to integrate into trading decisions.
Key Features of CDMI
🔹Color Scale for Trend Strength
The main triangle changes its base color depending on the strength of the DI reading. Dark Red or Green, colors correspond to stronger trends, while faded Gray or lighter yellow tones signal weaker or fading trends. This makes it visually clear when the market is consolidating versus trending strongly.
🔹Color Density for Momentum
Beyond strength, the CDMI uses color density to represent momentum in the trend’s strength. If the ADX is rising (trend gaining momentum), the triangles grows more darker. If the ADX is falling (trend losing momentum), the triangle becomes paler. This provides an instant sense of whether a trend is accelerating or decelerating.
🔹Directional Triangles for Trend Direction
To replace the separate +DI and –DI lines, the CDMI plots small triangle shapes along the bottom axis. An upward-facing triangle indicates that +DI is dominant, confirming bullish direction. A downward-facing triangle signals –DI dominance, confirming bearish direction. This way, both strength and direction are shown without the clutter of multiple overlapping lines.
🔹Label Display for Detailed Values
For traders who want precise data alongside the visuals, CDMI includes a label that shows:
Current trend strength (ADX value).
Current +DI and –DI values.
Momentum status of the ADX (rising or falling).
Historical values of DMI readings, so traders can track how the indicator has evolved over time.
Tooltips are also available to explain “How to read the colored DMI line”, making this version more beginner-friendly.
Why CDMI Matters
The CDMI retains the proven reliability of Wilder’s DMI while solving its biggest drawback—interpretation difficulty. Instead of juggling three separate plots, traders get a single, information-rich line supplemented with intuitive shapes and labels. This streamlined format makes trend verification, momentum analysis, and signal confirmation much faster.
For trading applications, the CDMI can help:
Confirm Entries by showing whether the market is trending strongly enough to justify a position.
Avoid False Signals by filtering out periods of low ADX (weak trend).
Enhance Timing by tracking momentum shifts in trend strength.
By simplifying the complexity of the original DMI into an elegant, color-coded tool, the CDMI makes one of technical analysis’ most advanced indicators practical for everyday use.
😅 The VIX, the Williams Vix Fix, and Market Bottoms 😎
The VIX, formally known as the CBOE Volatility Index, has long been considered one of the most reliable indicators for spotting major market bottoms. Often referred to as the “fear gauge,” it measures the market’s expectation of volatility in the S&P 500 over the next 30 days. When fear grips investors and volatility spikes, the VIX rises sharply. Historically, these moments of extreme fear often coincide with powerful buying opportunities, as markets have a tendency to rebound once panic selling exhausts itself.
Larry Williams, a well-known trader and author, developed the Williams Vix Fix as a way to replicate the insights of the VIX across any tradable asset. While the VIX itself is tied specifically to S&P 500 options, Williams wanted a tool that could capture similar panic-driven dynamics in stocks, futures, forex, and other markets where the VIX is not directly applicable. His “fix” uses price action and volatility formulas to approximate the same emotional extremes reflected in the official VIX, creating almost identical results in practice. This makes the Williams Vix Fix a powerful addition to the trader’s toolbox, allowing the same principle that works on U.S. equities to be applied universally.
One of the most important characteristics of both the VIX and the Williams Vix Fix is that they are far more reliable at signaling market bottoms than market tops. The reason is psychological as much as it is mathematical. At market bottoms, fear and panic are widespread. Retail investors often capitulate, selling in a frenzy as prices drop. This panic drives volatility higher, producing the spikes we see in the VIX. At the same time, professional traders and institutions—those with larger capital and more disciplined strategies—tend to step in when volatility is stretched. They buy when others are fearful, using the panic of retail investors as an opportunity to acquire assets at discounted prices. This confluence of retail panic and institutional buying power is what makes the VIX such a strong bottom-finding tool.
In contrast, at market tops, the dynamic is very different. Tops tend not to be marked by panic or fear. Instead, they form quietly as enthusiasm fades, liquidity dries up, and buying interest wanes. Investors are often complacent, assuming prices will continue to rise, while professional money begins distributing their positions. Because there is no surge in fear, volatility remains muted, and the VIX does not offer a clear warning. This is why traders who rely on the VIX or the Williams Vix Fix must understand its limitations: it is exceptional for detecting bottoms but less useful for anticipating tops.
For traders, the lesson is straightforward. When you see the VIX or Williams Vix Fix spiking to extreme levels, it often indicates a high-probability environment for a rebound. These tools should not be used in isolation, but when combined with support levels, sentiment indicators, and market breadth, they can provide some of the most reliable bottom-fishing signals available. While no indicator is perfect, few have stood the test of time as consistently as the VIX—and thanks to Williams’ adaptation, its power can now be applied to nearly every market.
Indicator Signals (Great in risk-off charts):
🔹Flags spike events (tops/bottoms) with both original and filtered (AE/FE) criteria.
🔹Great as a risk overlay: tighten stops into AE/FE, or require “no spike” to enter.
🤯 Volume Comfirmation: VTTI & VPCI (Buff Dormeier) 🤯
Volume Trend Technical Indicator (VTTI)
The Volume Trend Technical Indicator (VTTI) is a momentum-style tool that analyzes how volume trends interact with price movement. Unlike basic volume measures that simply report how many shares or contracts were traded, the VTTI evaluates whether volume is expanding or contracting in the same direction as the prevailing price trend. The underlying logic is that healthy trends are supported by rising volume, while weakening trends often occur on shrinking volume.
At its core, VTTI looks at the rate of change in volume compared to price movements. By smoothing and normalizing these relationships, the indicator helps traders determine whether momentum is accelerating, decelerating, or diverging.
Rising VTTI: Suggests that volume is confirming the current price trend, strengthening the case for continuation. Flips BG Green after crossing it's signal.
Falling VTTI: Indicates that the trend may be losing participation, often a sign of possible consolidation or reversal. Flips BG Red after crossing it's signal.
Traders often use VTTI to filter entries and exits. For example, if price breaks out but VTTI does not rise above zero, the breakout may lack conviction. On the other hand, when both price and VTTI are aligned, probability of continuation improves.
Volume Price Confirmation Indicator (VPCI)
The Volume Price Confirmation Indicator (VPCI), developed by Buff Dormeier, takes the relationship between price and volume a step further. While traditional indicators like On-Balance Volume (OBV) or Chaikin Money Flow look at cumulative patterns, VPCI breaks price and volume into trend and volatility components and then recombines them to measure how well they confirm each other.
In essence, VPCI asks: “Does volume confirm what price is signaling?”
The formula integrates:
Price Trend Component – whether the market is trending upward or downward.
Volume Trend Component – whether trading activity supports that price trend.
Volatility Adjustments – to account for irregular swings.
The resulting oscillator fluctuates around a zero line:
Positive VPCI: Indicates that price and volume trends are in agreement (bullish confirmation).
Negative VPCI: Suggests that price and volume are diverging (bearish warning or false move).
Crossovers of Zero: Can serve as potential buy or sell signals, depending on context.
A key strength of VPCI is its sensitivity to divergence. When prices continue rising but VPCI begins falling, it often foreshadows a weakening rally. Conversely, a rising VPCI during a flat or down market can highlight early accumulation.
VTTI (Entry Signal) vs. VPCI (Exit Signal)
While both indicators study price-volume dynamics, their focus differs:
VTTI is simpler, emphasizing the trend of volume relative to price for momentum confirmation.
VPCI is more advanced, decomposing both price and volume into multiple components to produce a nuanced oscillator.
Used together, they provide complementary insights. VTTI helps quickly spot whether volume is supporting a move, while VPCI offers deeper confirmation and highlights subtle divergences.
Note: The Up/Down Volume Alert works better on the 4 HR, for Daily scalps or 30 minute for HR scalps. Intraday it's 2/10 minute.
🦅 Divergence toolkit 🦅
Divergences in Technical Analysis
Divergence occurs when the price action of an asset moves in one direction while a technical indicator, such as RSI, MACD, or Momentum, moves in the opposite direction. This disagreement between price and indicator often signals a shift in underlying market dynamics. Traders use divergences to anticipate either potential reversals or continuations in trends.
There are two main types of divergences: regular divergences, which typically precede reversals, and hidden divergences, which suggest continuation of the current trend.
Regular Divergence (Reversal Signals)
A regular divergence occurs when price and indicator disagree during a trend extension. These divergences signal that momentum is no longer fully supporting the current trend and that a reversal may be imminent.
🔹Regular Bullish Divergence
Price Action: Forms a lower low.
Indicator: Forms a higher low.
Interpretation: Price is making new lows, but the indicator is gaining strength. This suggests that selling pressure is weakening, and a reversal to the upside may occur.
Example: RSI rising while price dips to fresh lows.
🔹Regular Bearish Divergence
Price Action: Forms a higher high.
Indicator: Forms a lower high.
Interpretation: Price is reaching new highs, but the indicator shows weakening momentum. This implies that buying pressure is fading, warning of a potential downside reversal.
Example: MACD histogram falling while price makes higher highs.
Regular divergences are often spotted near the end of trends and are most powerful when aligned with key support/resistance levels or overbought/oversold conditions.
Hidden Divergence (Continuation Signals)
A hidden divergence occurs during retracements within a trend. Unlike regular divergences, hidden divergences suggest that the prevailing trend still has strength and is likely to continue.
🔹Hidden Bullish Divergence
Price Action: Forms a higher low.
Indicator: Forms a lower low.
Interpretation: Price is retracing within an uptrend, but the indicator is overshooting downward. This shows that momentum remains intact, supporting continuation upward.
🔹Hidden Bearish Divergence
Price Action: Forms a lower high.
Indicator: Forms a higher high.
Interpretation: Price is retracing within a downtrend, while the indicator overshoots upward. This indicates that bearish momentum remains strong, supporting continuation downward.
Hidden divergences often appear during pullbacks, helping traders time entries in the direction of the prevailing trend.
Practical Use of Divergences
🔹Trend Reversal Alerts – Regular divergences are early warnings that a trend may be ending.
🔹Trend Continuation Signals – Hidden divergences help confirm that retracements are simply pauses, not full reversals.
🔹Confluence with Other Tools – Divergences are more reliable when combined with support/resistance, candlestick patterns, or volume analysis.
🔹Multi-Timeframe Analysis – Spotting divergences on higher timeframes often produces stronger signals.
🕭🔔🛎️ Alert 🛎️🔔🕭
🔹Squeeze
🟢 Fired Squeeze
⚫ Low (Wide) Squeeze / 🔴 Normal / 🟡 Tight / 🟣 Very Tight
🔹Momentum
🐂 Bullish Trend Reversal (Crossover of Momentum and Signal from sub −2)
🐻 Bearish Trend Reversal (Crossover of Momentum and Signal from above +2)
📈 Bullish Swing (cross above +1 ATR) / 📉 Bearish Swing (cross below −1 ATR)
🔹DSL
💚 Bullish DSL Scalp / 💔 Bearish DSL Scalp
🔹Volume
🎯 Strong Up Volume (VPCI > 0 and VTTI up)
⏳ Strong Down Volume (VPCI < 0 and VTTI down)
🔹Divergences
🦅 Bullish, 🦆 Bearish, 🦅 Bullish Hidden, 🦆 Bearish Hidden
Management: Search Vanguard ETFs in your browser, look up full list of VOO holdings. Download it, or copy paste all the ticker symbols. Place that with a AI, just ask it to place , in between each ticker. NVDA, TSLA, AVGO, etc. Create a new watchlist, in the + add all tickers separated by commas. Place a watchlist alert ⚠️ only available for premium + subscribers.
Practical playbook
1) Classic Squeeze Break
Setup: 🔴(D)/🟡(2D)/🟣(3D) squeeze → wait for 🟢(1HR) Fired.
Confirm: Momentum > Signal and above +1 ATR (or DMI strong & rising).
Manage: add on pullbacks that hold +1 ATR; scale near +2 ATR or WVF AE/FE.
2) DSL Scalp in Trend
Setup: Clear trend (DMI strong) + DSL bull/bear trigger in the direction of trend.
Filter: avoid tight/very tight yellow/purple unless you want micro-scalps.
Exit: opposite DSL or ATR midline loss.
3) Mean-Reversion Fade
Setup: Momentum extended to ±3 ATR, WVF spike, and a regular divergence.
Entry: Counter signal only when mom crosses back through ±3 ATR toward mid. Exit early if squeeze ⚫/🔴, Momentum may extend to ±3/2 ATR in the same direction.
Risk: reduce size; this is a fade, not trend following.
4) Volume-Confirmed Breakout
Setup: Squeeze → 🟢 Fired + VPCI > 0 and VTTI up → trend continuation.
Manage: trail behind +1 ATR (long) or −1 ATR (short). 9 SMA works good.
Inputs at a glance (key ones)
Mode: Price or CVD momentum; Squeeze Sensitivity (σ); Momentum Length; Signal Length; ATR Smoothing.
🧮 Colors:
SQZMOM: per squeeze regime, momentum, ATR fills.
DSL: On/Off, Fast/Slow, Length.
ATR Zones: Bullish/Bearish levels (±1), ±2/±3 zone lines & fills.
DMI: Lengths, key & weak thresholds, label on/off.
WVF/VIX: Lookbacks, bands, AE/FE toggles, VIX proxy symbol.
VTTI/VPCI: Fast/slow/signal (VTTI), Short/Long (VPCI), and volume source (Tick/CVD/NVI/PVI/OBV/PVT/AccDist/VWAP).
Divergences: Regular/Hidden toggles, Sensitivity %, Lifetime, Live vs On-Close, Lines/Labels.
🔎 Suggested defaults (feel free to tweak)
Calibration: Size Momentum, so that when it's above zero the asset is trending up. For the signal, it can be kept the same or lower.
Intraday (60–240m): σ = 2.0, 18~20, 3~5, DSL Fast, DMI key 23, weak 17.
Daily/Weekly: keep σ = 2.0, consider DSL Slow, DMI key 25, weak 20, widen ATR filters; lean on VPCI/VTTI (4-HR).
CVD mode: use where tick/volume quality is high (index futures, liquid equities, crypto majors).
🪟 Tips & caveats
Swing Screener: Favor liquid underlyings (index futures/ETFs, large caps). Large-Cap, 2 M Vol, Mid-Cap, 500K Vol. Squeeze: BB( 20) upper < KC (20) upper, and BB (20) lower > KC (20) lower. Optional: Price above 9 SMA, 21 SMA, and 50 SMA, they are my SMA of choice. 200 SMA too, unless you are willing to fish in a bear market. Vice-versa for shorts. Optional: ADX 4 HR > 17, or 23 depending on what you are looking for.
Scalp Screener: Same as above, change the D 9 SMA to 5, and the BB/KC from D to 1 HR. Scalps may last 2~3 days.
Position Screener: Change all daily setting to W, aside from Volume. Optional: PEG < 1.5, FCF > 0, ROA > 8% or ROE > 6%.
Good with Moving averages (9/21/50) and low-volume zones.
Position size by IV, ATR, and account risk. Consider stop/hedge rules around ±2/±3 ATR.
Let alerts stage your watchlist; act only on combined squeeze + momentum signals.
Divergences in live mode can repaint (Real-Time); for algo or alerts, use on-close.
Tight/Very tight squeezes are great for scalps but choppy; combine with DMI rising + VPCI>0.
±3 ATR is exhaustion context, not an auto-fade—look for WVF/Div/DSL confirmation.
For alerts, pair “Fired Squeeze + Bullish Swing” (or bearish) to avoid false starts.
🎯 How to Trade Entry ~ Recap:
Tight/very tight squeeze → fires → momentum crosses up (or DSL bull).
Exit/Flip: Momentum crosses down into/after expansion or hits +2/+3 ATR with fade signs. Filter: Avoid fresh longs at +3 ATR; avoid fresh shorts at −3 ATR unless fading with confirmation.
📐 Options Integrations
✅ Risk Reversal/Modified Risk Reversal (Bullish: Short Put + Long Call)
Use when: Squeeze fires up from 🟡/🟣 and momentum crosses above signal (or zero/DSL).
Playbook Entry: On or just after the bullish fire and momentum upcross. DMI or Volume supports trend as well.
Structure: Sell a put at/just below the −2 ATR reference (or recent swing support). Buy a call at/above the breakout zone (prior high/mid-range +1 to +2 ATR).
A classic risk reversal is a long call plus a short put. That’s a very bullish structure—you gain if the price rallies (via the call), and you collect a premium by selling a put. But it has a naked downside risk. The modified risk reversal fixes that by adding a long lower put (making the short put into a defined put credit spread).
Management: If momentum stays above signal, ride toward +2 → +3 ATR. Sell the put near the current price → receive big premium. Buy the lower put → spend part of that premium (risk cap). Buy the call above the current price → spend more, but the short put premium mostly pays for it.
Exits/Adjust: Momentum downcross or squeeze flips back on (new compression) → reduce. If price retests −1/−2 ATR and holds, you can roll the short put down/out.
Breakout = Big Success; No Breakout = you keep the initial credit. Reversal = Max loss is capped by the long lower put.
✅ Iron Condor (Neutral: Short OTM Put Spread + Short OTM Call Spread)
Use when: Squeeze is active (🟡/🟣), momentum is flat near zero, and there is no directional edge. 🟢 lasts for around 5~8 bars typically. I measure the historical duration of it, and wait for a range period to occur.
Playbook Entry: During compression, set wings outside ±2 ATR (or recent range extremes). I prefer identifying boxes where the rectangle pattern occurs on the chart.
Management: Time decay works while price remains trapped in the coil. High-winrate ~80%, but 1 loser can wipe most of the gains.
Exits/Adjust: If a squeeze fires and momentum breaks hard one way, close the losing side, consider converting to a vertical or rotating to a directional spread aligned with momentum.
4HR-Bullish, closing one wing:
Tip: Align daily/weekly context with your intraday entries. 9 > 50 on Weekly, similar on Daily. Sell premium into compression; switch to directional spreads on expansion and momentum confirmation.
✅ Naked Call/Puts (Directional: 10~30 Delta Calls)
Stick to naked calls and puts when the squeezes are fired from either 🔴 or ⚫.
Look for Strikes slightly out of the money with an OI and Volume spread less than <10%.
If Strike Date is >45, manage 21 Days before expiration. Scalp: Expiration Strikes of 1/4 of the Squeeze period. Leap: Expiration Strikes of 1.75x of the Squeeze period.
📐 Futures Integrations
Playbook Entry:
Verify if the squeeze on the hourly is red or green, and enter on the 2- or 5-minute during a similar squeeze state.
Trend-Following: Traditional 2 Renko Block above 21 SMA and Momentum is bullish, or vice versa. (2~ES, 5~NQ)
Structure: Go long at/just below the ATR reference (or recent swing support). Exit below the breakout zone (prior high/mid-range +1 to +2 ATR).
Management: If momentum stays above +1 ATR ride toward +2 → +3 ATR, etc. House-money, should be kept.
Exits/Adjust: Momentum downcross or squeeze flips back on (new compression) → exit. On Renko Charts, lower the sensitivity to 0.7~1. If price retests 0/−1/−2 ATR and holds, you can enter when the 9 SMA flips. The 50 SMA is better for Daily and up; I wouldn't trade against it then.
📌 FOMO Trading Playbook
Credits & License
Credits: @JF10R (Multi-Timeframe Squeeze), @BigBeluga (DSL), @OskarGallard (Colored DMI base), @ChrisMoody (WVF ideas), @PineCodersTASC (VTTI/VPCI), @EliCobra (Divergence toolkit).
License: Mozilla Public License 2.0 (MPL-2.0).
Author: © GabrielAmadeusLau
BB+EMA+TAB by RAThis is EMA based indicator that gives buy/sell signals on the crossover of EMA 1 and EMA 2, also it can fill green /red color between EMA 1 & EMA 2. it also have EMA 3 and EMA 4, which are independent. Bollinger Band (BB) is also there for breakout signals. This indicator also plot a table which shows the values of RSI, ATR, ADX for last 5 candles which helps making trade decisions. RSI values change colors to red/green according to RSI is below/above 50, and ADX values change colors to red/green/grey/orange .. red/green according to EMA 1 and EMA 2 crossover and if ADX value is above 20, grey when ADX value is below 15, orange when ADX value is between 15 and 20 i.e. building momentum. ADX filter is also available in the script.. if on.. then buy/sell signals will be filtered through ADX values as prescribed by the user. This indicator also features HTF EMA crossover filter.. if on .. then buy/sell signals will be aligned with HTF EMA crossover i.e. only buy signals on the chart will come if HTF EMA 1>HTF EMA 2... and only sell signals on the chart will come if HTF EMA 1
5 Min Scalping Oscillator### Overview
The 5 Min Scalping Oscillator is a custom oscillator designed to provide traders with a unified momentum signal by fusing normalized versions of the Relative Strength Index (RSI), Stochastic RSI, and Commodity Channel Index (CCI). This combination creates a more balanced view of market momentum, overbought/oversold conditions, and potential reversals, while incorporating adaptive smoothing, dynamic thresholds, and market condition filters to reduce noise and false signals. Unlike standalone oscillators, the 5 Min Scalping Oscillator adapts to trending or sideways regimes, volatility levels, and higher timeframe biases, making it particularly suited for short-term charts like 5-minute timeframes where quick, filtered signals are valuable.
### Purpose and Originality of the Fusion
Traditional oscillators like RSI measure momentum but can lag in volatile markets; Stochastic RSI adds sensitivity to RSI extremes but often generates excessive noise; and CCI identifies cyclical deviations but may overreact to minor price swings. The 5 Min Scalping Oscillator addresses these limitations by weighting and blending their normalized outputs (RSI at 45%, Stochastic RSI at 35%, and CCI at 20%) into a single raw oscillator value. This weighted fusion creates a hybrid signal that balances lag reduction with noise filtering, resulting in a more robust indicator for identifying reversal opportunities.
The originality lies in extending this fusion with:
- **Adaptive Smoothing via KAMA (Kaufman's Adaptive Moving Average):** Adjusts responsiveness based on market efficiency, speeding up in trends and slowing in ranges—unlike fixed EMAs, this helps preserve signal integrity without over-smoothing.
- **Dynamic Overbought/Oversold Thresholds:** Calculated using rolling percentiles over a user-defined lookback (default 200+ periods), these levels adapt to recent oscillator behavior rather than relying on static values like 70/30, making the indicator more responsive to asset-specific volatility.
- **Multi-Factor Filters:** Integrates ADX for trend detection, ATR percentiles for volatility confirmation, and optional higher timeframe RSI bias to ensure signals align with broader market context. This layered approach reduces false positives (e.g., ignoring low-volatility crossovers) and adds a confidence score based on filter alignment, which is not typically found in simple mashups.
This design justifies the combination: it's not a mere overlay of indicators but a purposeful integration that enhances usefulness by providing context-aware signals, helping traders avoid common pitfalls like trading against the trend or in low-volatility chop. The result is an original tool that performs better in diverse conditions, especially on 5-minute charts for intraday trading, where rapid adaptations are key.
### How It Works
The 5 Min Scalping Oscillator processes price data through these steps:
1. **Normalization and Fusion:**
- RSI (default length 10) is normalized to a -1 to +1 scale using a tanh transformation for bounded output.
- Stochastic RSI (default length 14) is derived from RSI highs/lows and scaled similarly.
- CCI (default length 14) is tanh-normalized to align with the others.
- These are weighted and summed into a raw value, emphasizing RSI for core momentum while using Stochastic RSI for edge sensitivity and CCI for cycle detection.
2. **Smoothing and Signal Line:**
- The raw value is smoothed (default KAMA with fast/slow periods 2/30 and efficiency length 10) to reduce whipsaws.
- A shorter signal line (half the smoothing length) is added for crossover detections.
3. **Filters and Enhancements:**
- **Trend Regime:** ADX (default length 14, threshold 20) classifies markets as trending (ADX > threshold) or sideways, allowing signals in both but prioritizing alignment.
- **Volatility Check:** ATR (default length 14) percentile (default 85%) ensures signals only trigger in above-average volatility, filtering out flat markets.
- **Higher Timeframe Bias:** Optional RSI (default length 14 on 60-minute timeframe) provides bull/neutral/bear bias (above 55, 45-55, below 45), requiring signal alignment (e.g., bullish signals only if bias is neutral or bull).
- **Dynamic Levels:** Percentiles (default OB 85%, OS 15%) over recent oscillator values set adaptive overbought/oversold lines.
4. **Signal Generation:**
- Bullish (B) signals on upward crossovers of the smoothed line over the signal line, filtered by conditions.
- Bearish (S) signals on downward crossunders.
- Each signal includes a confidence score (0-100) based on factors like trend alignment (25 points), volatility (15 points), and bias (20 points if strong, 10 if neutral).
The output includes a glowing oscillator line, histogram for divergence spotting, dynamic levels, shapes/labels for signals, and a dashboard table summarizing regime, ADX, bias, levels, and last signal.
### How to Use It
This indicator is easy to apply and interpret, even for beginners:
- **Adding to Chart:** Apply the 5 Min Scalping Oscillator to a clean chart (no other indicators unless explained). It's non-overlay, so it appears in a separate pane. For 5-minute timeframes, keep defaults or tweak lengths shorter for faster response (e.g., RSI 8-12).
- **Interpreting Signals:**
- Look for green upward triangles labeled "B" (bullish) at the bottom for potential entry opportunities in uptrends or reversals.
- Red downward triangles labeled "S" (bearish) at the top signal potential exits or shorts.
- Higher confidence scores (e.g., 70+) indicate stronger alignment—use these for priority trades.
- Watch the histogram for divergences (e.g., price higher highs but histogram lower highs suggest weakening momentum).
- Dynamic OB (green line) and OS (red line) help gauge extremes; signals near these are more reliable.
- **Dashboard:** At the bottom-right, it shows real-time info like "Trending" or "Sideways" regime, ADX value, HTF bias (Bull/Neutral/Bear), OB/OS levels, and last signal—use this for quick context.
- **Customization:** Adjust inputs via the settings panel:
- Toggle KAMA for adaptive vs. EMA smoothing.
- Set HTF to "60" for 1-hour bias on 5-min charts.
- Increase ADX threshold to 25 for stricter trend filtering.
- **Best Practices:** Combine with price action (e.g., support/resistance) or volume for confirmation. On 5-min charts, pair with a 1-hour HTF for intraday scalping. Always use stop-losses and risk no more than 1-2% per trade.
### Default Settings Explanation
Defaults are optimized for 5-minute charts on volatile assets like stocks or forex:
- RSI/Stoch/CCI lengths (10/14/14): Shorter for quick momentum capture.
- Signal smoothing (5): Responsive without excessive lag.
- ADX threshold (20): Balances trend detection.
- ATR percentile (0.85): Filters ~15% of low-vol signals.
- HTF RSI (14 on 60-min): Aligns with hourly trends.
- Percentiles (OB 85%, OS 15%): Adaptive to recent data.
If changing, test on historical data to ensure fit—e.g., longer lengths for less noisy assets.
### Disclaimer
The 5 Min Scalping Oscillator is an educational tool to visualize momentum and does not guarantee profits or predict future performance. All signals are based on historical calculations and should not be used as standalone trading advice. Past results are not indicative of future outcomes. Traders must conduct their own analysis, use proper risk management, and consider market conditions. No claims are made about accuracy, reliability, or performance.
AI's Opinion Trading System V21. Complete Summary of the Indicator Script
AI’s Opinion Trading System V2 is an advanced, multi-factor trading tool designed for the TradingView platform. It combines several technical indicators (moving averages, RSI, MACD, ADX, ATR, and volume analysis) to generate buy, sell, and hold signals. The script features a customizable AI “consensus” engine that weighs multiple indicator signals, applies user-defined filters, and outputs actionable trade instructions with clear stop loss and take profit levels. The indicator also tracks sentiment, volume delta, and allows for advanced features like pyramiding (adding to positions), custom stop loss/take profit prices, and flexible signal confirmation logic. All key data and signals are displayed in a dynamic, color-coded table on the chart for easy review.
2. Full Explanation of the Table
The table is a real-time dashboard summarizing the indicator’s logic and recommendations for the most recent bars. It is color-coded for clarity and designed to help traders quickly understand market conditions and AI-driven trade signals.
Columns (from left to right):
Column Name What it Shows
Bar The time context: “Now” for the current bar, then “Bar -1”, “Bar -2”, etc. for previous bars.
Raw Consensus The raw AI consensus for each bar: “Buy”, “Sell”, or “-” (neutral).
Up Vol The amount of volume on up (rising) bars.
Down Vol The amount of volume on down (falling) bars.
Delta The difference between up and down volume. Green if positive, red if negative, gray if neutral.
Close The closing price for each bar, color-coded by price change.
Sentiment Diff The difference between the close and average sentiment price (a custom sentiment calculation).
Lookback The number of bars used for sentiment calculation (if enabled).
ADX The ADX value (trend strength).
ATR The ATR value (volatility measure).
Vol>Avg “Yes” (green) if volume is above average, “No” (red) otherwise.
Confirm Whether the AI signal is confirmed over the required bars.
Logic Output The AI’s interpreted signal after applying user-selected logic: “Buy”, “Sell”, or “-”.
Final Action The final signal after all filters: “Buy”, “Sell”, or “-”.
Trade Instruction A plain-English instruction: Buy/Sell/Add/Hold/No Action, with price, stop loss, and take profit.
Color Coding:
Green: Positive/bullish values or signals
Red: Negative/bearish values or signals
Gray: Neutral or inactive
Blue background: For all table cells, for visual clarity
White text: Default, except for color-coded cells
3. Full User Instructions for Every Input/Style Option
Below are plain-language instructions for every user-adjustable option in the indicator’s input and style pages:
Inputs
Table Location
What it does: Sets where the summary table appears on your chart.
How to use: Choose from 9 positions (Top Left, Top Center, Top Right, etc.) to avoid overlapping with other chart elements.
Decimal Places
What it does: Controls how many decimal places prices and values are displayed with.
How to use: Increase for assets with very small prices (e.g., SHIB), decrease for stocks or forex.
Show Sentiment Lookback?
What it does: Shows or hides the “Lookback” column in the table, which displays how many bars are used in the sentiment calculation.
How to use: Turn off if you want a simpler table.
AI View Mode
What it does: Selects the logic for how the AI combines signals from different indicators.
Majority: Follows the most common signal among all indicators.
Weighted: Uses custom weights for each type of signal.
Custom: Lets you define your own logic (see below).
How to use: Pick the logic style that matches your trading philosophy.
AI Consensus Weight / Vol Delta Weight / Sentiment Weight
What they do: When using “Weighted” AI View Mode, these let you set how much influence each factor (indicator consensus, volume delta, sentiment) has on the final signal.
How to use: Increase a weight to make that factor more important in the AI’s decision.
Custom AI View Logic
What it does: Lets advanced users write their own logic for when the AI should signal a trade (e.g., “ai==1 and delta>0 and sentiment>0”).
How to use: Only use if you understand basic boolean logic.
Use Custom Stop Loss/Take Profit Prices?
What it does: If enabled, you can enter your own fixed stop loss and take profit prices for buys and sells.
How to use: Turn on to override the auto-calculated SL/TP and enter your desired prices below.
Custom Buy/Sell Stop Loss/Take Profit Price
What they do: If custom SL/TP is enabled, these fields let you set exact prices for stop loss and take profit on both buy and sell trades.
How to use: Enter your preferred price, or leave at 0 for auto-calculation.
Sentiment Lookback
What it does: Sets how many bars the sentiment calculation should look back.
How to use: Increase to smooth out sentiment, decrease for faster reaction.
Max Pyramid Adds
What it does: Limits how many times you can add to an existing position (pyramiding).
How to use: Set to 1 for no adds, higher for more aggressive scaling in trends.
Signal Preset
What it does: Quick-sets a group of signal parameters (see below) for “Robust”, “Standard”, “Freedom”, or “Custom”.
How to use: Pick a preset, or select “Custom” to adjust everything manually.
Min Bars for Signal Confirmation
What it does: Sets how many bars a signal must persist before it’s considered valid.
How to use: Increase for more robust, less frequent signals; decrease for faster, but possibly less reliable, signals.
ADX Length
What it does: Sets the period for the ADX (trend strength) calculation.
How to use: Longer = smoother, shorter = more sensitive.
ADX Trend Threshold
What it does: Sets the minimum ADX value to consider a trend “strong.”
How to use: Raise for stricter trend confirmation, lower for more trades.
ATR Length
What it does: Sets the period for the ATR (volatility) calculation.
How to use: Longer = smoother volatility, shorter = more reactive.
Volume Confirmation Lookback
What it does: Sets how many bars are used to calculate the average volume.
How to use: Longer = more stable volume baseline, shorter = more sensitive.
Volume Confirmation Multiplier
What it does: Sets how much current volume must exceed average volume to be considered “high.”
How to use: Increase for stricter volume filter.
RSI Flat Min / RSI Flat Max
What they do: Define the RSI range considered “flat” (i.e., not trending).
How to use: Widen to be stricter about requiring a trend, narrow for more trades.
Style Page
Most style settings (such as plot colors, label sizes, and shapes) are preset in the script for visual clarity.
You can adjust plot visibility and colors (for signals, stop loss, take profit) in the TradingView “Style” tab as with any indicator.
Buy Signal: Shows as a green triangle below the bar when a buy is triggered.
Sell Signal: Shows as a red triangle above the bar when a sell is triggered.
Stop Loss/Take Profit Lines: Red and green lines for SL/TP, visible when a trade is active.
SL/TP Labels: Small colored markers at the SL/TP levels for each trade.
How to use:
Toggle visibility or change colors in the Style tab if you wish to match your chart theme or preferences.
In Summary
This indicator is highly customizable—you can tune every aspect of the AI logic, risk management, signal filtering, and table display to suit your trading style.
The table gives you a real-time, comprehensive view of all relevant signals, filters, and trade instructions.
All inputs are designed to be intuitive—hover over them in TradingView for tooltips, or refer to the explanations above for details.
Gorgo's Hybrid Oscillator STrategy**Indicator Name:** Gorgo's Hybrid Oscillator STrategy (G.H.O.S.T.)
**Purpose:**
The Gorgo's Hybrid Oscillator STrategy (G.H.O.S.T.) is a multi-component technical analysis tool designed to identify overbought and oversold market conditions, assess trend strength, and signal potential buy and sell opportunities. By combining elements from RSI, Ultimate Oscillator, Stochastic CCI, and ADX, this custom indicator provides a comprehensive view of momentum, trend intensity, and volume context to enhance decision-making.
---
**Components and Logic:**
1. **RSI (Relative Strength Index):**
* Calculated using a customizable period (default: 14) and based on the hlc3 price source.
* Measures recent price changes to evaluate overbought/oversold conditions.
* Incorporated in the final oscillator average.
2. **Ultimate Oscillator:**
* Combines three timeframes (7, 14, 28 by default) to smooth out price movements.
* Uses true range and buying pressure for multi-frame momentum analysis.
* Averaged together with RSI to create the main oscillator signal.
3. **Stochastic CCI:**
* Applies a stochastic process to the Commodity Channel Index (CCI).
* Smooths the %K and %D lines (default: 3 each) to detect subtle reversals.
* Generates oversold (<35) and overbought (>69) signals, plotted as yellow circles.
4. **ADX + DI (Average Directional Index):**
* Determines trend strength using ADX and directional movement indicators (DI).
* ADX threshold is set at 24 by default to filter weak trends.
* Colored histogram columns:
* Green: Strong bullish trend.
* Red: Strong bearish trend.
* Gray: Weak/no trend.
5. **Volume Analysis:**
* Calculates a 9-period SMA of volume.
* Detects significant volume spikes (2.7× the average by default) to validate breakouts or fakeouts.
6. **Oscillator Output ("osc") and Levels:**
* The main plotted oscillator line is the average of the RSI and Ultimate Oscillator.
* Important horizontal lines:
* Overbought (69.0)
* Oversold (35.0)
* Midline (52.0): Neutral reference point.
* ADX threshold line (24.0)
---
**Signals:**
1. **Buy Signal Conditions:**
* Close is less than or equal to open (candle is red).
* Oscillator is decreasing and below oversold level.
* Stochastic CCI is below midline.
* Volume is above average, or excessive volume with oscillator falling below 40.
* ADX confirms trend presence (either above 15 or meeting threshold).
2. **Sell Signal Conditions:**
* ADX increasing and confirming trend.
* Oscillator is increasing and above overbought level.
* Stochastic CCI is above midline.
* Volume is above average, or very high with oscillator above 60.
3. **Visual Feedback:**
* Yellow dots highlight oversold/overbought Stochastic CCI.
* Oscillator line in cyan.
* Background colors:
* Light red for buy signals.
* White for sell signals.
4. **Alerts:**
* Built-in `alertcondition()` calls allow automated alerts for buy and sell events.
---
**Usage Guide:**
* **Best Use Cases:** Trend-following and reversal strategies on any timeframe.
* **Avoid Using Alone:** Use G.H.O.S.T. in conjunction with price action, support/resistance, and other confluence tools.
* **Customization:** All thresholds, periods, and volumes are user-editable from the settings panel.
---
**Interpretation Summary:**
G.H.O.S.T. excels at filtering out noise by combining different oscillators and volume signals to offer contextually valid entries and exits. A bullish (buy) signal typically suggests a market under pressure but potentially bottoming out, while a bearish (sell) signal highlights likely exhaustion after a strong upward push.
This hybrid approach makes the G.H.O.S.T. a reliable ally in volatile or choppy conditions where single-indicator strategies might fail.
RACZ-SIGNAL-V2.1RACZ-SIGNAL-V2.1 – Reactive Analytical Confluence Zones
Developed by: RACZ Trading
Indicator Type: Multi-Factor Confluence System
Overlay: Off (separate pane)
Purpose: Detect powerful trade opportunities through confluence of technical signals.
⸻
🔍 What is RACZ?
RACZ stands for Reactive Analytical Confluence Zones.
It’s a high-precision trading tool built for traders who rely on multi-signal confirmation, momentum alignment, and market structure awareness.
Rather than relying on a single technical metric, RACZ dynamically combines RSI, VWAP-RSI, Divergence, ADX, and Volume Analytics to produce a composite signal score from 0 to 12 — the higher the score, the stronger the signal.
⸻
🧠 How It Works – Core Components
1. RSI Analysis
• Detects momentum shifts.
• Compares RSI value to overbought (default: 67) and oversold (default: 33) thresholds.
• Adds points to Bullish or Bearish score.
2. VWAP-RSI
• Uses RSI based on VWAP (Volume Weighted Average Price).
• Adds weight to signals influenced by volume-adjusted price movement.
3. Divergence Detection
• Detects potential reversal zones.
• Bullish Divergence: RSI crosses up from low zone.
• Bearish Divergence: RSI crosses down from high zone.
• Strong confluence signal when present.
4. ADX Dynamic Strength Filter
• Custom-calculated ADX (trend strength indicator).
• Uses a dynamic threshold derived from SMA of ADX over a lookback period, scaled by a factor (default 0.9).
• Ensures signals are only validated in strong trend environments.
5. Volume Z-Score
• Detects anomalies in volume behavior.
• Z-score applied to 20-period volume average & deviation.
• Labels spikes, drops, high/low volume conditions.
⸻
📊 Signal Scoring Logic
Each component (RSI, VWAP-RSI, Divergence, ADX) can score up to 3 points each.
• Bullish Score: Total from bullish alignment of each factor.
• Bearish Score: Total from bearish alignment of each factor.
• Signal Power = max(bullish, bearish)
📈 Signal Interpretation
• BUY: Bullish Score > Bearish Score
• SELL: Bearish Score > Bullish Score
• NEUTRAL: Scores are equal
• Signal power is plotted on a 0–12 histogram:
• 0–5 = Weak
• 6–8 = Medium
• 9–12 = Strong (High Confluence Zone)
🖥️ Live Status Panel (Top-Right Corner)
This real-time panel helps you break down the signal:Component
Value Explanation: RSI / VWAP / DIV / ADX
Shows points contributing to signal
SIGNAL: Current market bias (BUY, SELL, NEUTRAL)
VOLUME: Volume classification (Spike, Drop, High, Low, Normal)
Color-coded for quick interpretation.
✅ How to Use
1. Look at Histogram: Bars ≥6 suggest valid setups, especially ≥9.
2. Confirm Panel Agreement: Check which components are supporting the signal.
3. Validate Volume: Unusual spikes/drops often precede strong moves.
4. Follow Direction: Use BUY/SELL signals aligned with signal power and trend.
⸻
⚙️ Customizable Inputs
• RSI period, overbought/oversold levels
• VWAP-RSI period
• ADX period and dynamic threshold settings
• Fully adjustable to fit any trading style
⸻
🚀 Why Choose RACZ?
• Clarity: Scores & signals derived from multiple tools, not just one.
• Confluence Logic: Designed for traders who look for confirmation across indicators.
• Speed: Real-time responsiveness to changing market dynamics.
• Volume Awareness: Integrated volume intelligence gives a deeper edge.
⸻
⚠️ Disclaimer
This indicator is intended strictly for educational and informational purposes only. It is not financial advice and should not be used to make actual investment decisions. Always conduct your own research or consult with a licensed financial advisor before trading or investing. Use of this script is at your own risk.
NeuroFlow Pro IndicatorThe **NeuroFlow Pro Indicator** is a comprehensive technical analysis tool designed for traders on the TradingView platform. It provides actionable buy and sell signals by combining multiple technical indicators, including Moving Averages, MACD, RSI, Stochastic RSI, SuperTrend, Ichimoku Cloud, Bollinger Bands, and Volume analysis. The indicator generates a **Composite Score** (0–100) that reflects market conditions, with low scores indicating bullish opportunities and high scores suggesting bearish conditions. It also identifies key trend reversal points and significant EMA crossovers (Golden Cross and Death Cross) to help traders make informed decisions.
**Key Features**:
- **Composite Score**: Aggregates signals from multiple indicators to provide a single, easy-to-read metric.
- **Buy/Sell Signals**: Generates clear signals for potential long (buy) and short (sell) opportunities.
- **Golden/Death Cross**: Marks EMA 50 crossing above (🚀) or below (💀) EMA 200, indicating major trend shifts.
- **Dashboard**: Displays real-time metrics like trend direction, momentum, volume, and signal confidence.
- **Customizable Alerts**: Notifies users of buy/sell signals, divergences, and EMA crossovers via TradingView’s alert system.
- **Multi-Timeframe Analysis**: Incorporates higher timeframe trends for enhanced signal reliability.
- **Candlestick Patterns**: Optionally includes patterns like Hammer, Engulfing, or Morning Star for signal confirmation.
This indicator is ideal for traders seeking a robust, all-in-one tool to identify trading opportunities across various markets (e.g., crypto, stocks, forex) and timeframes (e.g., 1H, 4H, daily).
User Guide for NeuroFlow Pro Indicator
Understanding the Indicator
- **Dashboard**:
- Located on the chart (left or right, configurable), it shows real-time metrics:
- **Comp Score**: Composite Score (0–100); low (<30) is bullish, high (>70) is bearish.
- **Trend**: Bullish, Bearish, or Neutral
- **MTF Trend**: Trend from a higher timeframe (e.g., 60m or 240m).
- **Momentum**: RSI and Stochastic RSI-based momentum (Bullish, Bearish, Neutral).
- **MFI**: Money Flow Index (Inflow, Outflow, Neutral).
- **Volatility**: High or Low based on ATR and Bollinger Bands.
- **Volume**: High, Low, or Neutral relative to volume MA.
- **Ichimoku**: Bullish, Bearish, or Neutral based on cloud position.
- **ADX Strength**: Strong or Weak trend based on ADX.
- **Divergence**: Bullish, Bearish, or Neutral for RSI/MACD divergences.
- **Reversal**: Bullish or Bearish reversal potential with confidence percentage.
- **Signal Status**: Long (buy), Short (sell), or None.
- **Signal Confid**: Confidence percentage for the current signal.
- **Chart Visuals**:
- **EMA 50 (White)**: Fast-moving average for short-term trends.
- **EMA 200 (Blue)**: Long-moving average for long-term trends.
- **Golden Cross (🚀)**: Green rocket emoji when EMA 50 crosses above EMA 200 (bullish).
- **Death Cross (💀)**: Red skull emoji when EMA 50 crosses below EMA 200 (bearish).
- **Alerts**:
- Configurable for Buy/Sell Signals, Golden/Death Cross, and Bullish/Bearish Divergences.
Configuring Settings
1. **Open Settings**:
- Right-click the indicator’s name on the chart and select “Settings,” or double-click the indicator in the chart’s indicator list.
2. **Key Settings to Customize**:
- **Strategy Settings**:
- **Max ATR Multiplier**: Adjusts sensitivity to volatility (default: 3.0).
- **Main Settings**:
- **Candlestick Pattern**: Choose Hammer, Engulfing, Morning Star, or Custom (default: Hammer).
- **Multi-Timeframe Period**: Set higher timeframe for trend analysis (e.g., 60m, 240m, Daily; default: 60m).
- **Higher Timeframe**: Secondary timeframe for confirmation (default: 240m).
- **Use Candlestick Patterns**: Enable/disable pattern-based signals (default: off).
- **Use Volume Filter**: Require high volume for signals (default: on).
- **Use ADX Filter**: Require strong trend for signals (default: on).
- **Momentum Settings**:
- **RSI/Stochastic/MFI Lengths**: Adjust periods for RSI, Stochastic RSI, and MFI (defaults: 14, 14, 60).
- **EMA Lengths**: Fast (50), Slow (100), Long (200) for trend and crossovers.
- **ATR/ADX Lengths**: Volatility and trend strength periods (default: 14).
- **SuperTrend/Bollinger/Ichimoku Settings**:
- Customize periods and multipliers (defaults: SuperTrend 10/3.0, Bollinger 20/2.0, Ichimoku 9/26/52).
- **MACD Settings**:
- **MACD Preset**: Auto (timeframe-based), 1H (3-10-16), 4H (5-34-21), D (5-15-9), or Custom (default: Auto).
- **Custom MACD Lengths**: Fast (12), Slow (26), Signal (9) for Custom preset.
- **Weights Settings**:
- Adjust weights for trend, momentum, volatility, etc., to prioritize certain indicators (defaults: Trend 1.0, Momentum 0.3, etc.).
- **Threshold Settings**:
- **Bullish/Bearish Reversal Thresholds**: Set score thresholds for reversals (default: 30/70).
- **ADX Threshold**: Minimum ADX for trend strength (default: 20).
- **Signal Thresholds**: Base (70) and alert (80) thresholds for signals.
- **Dashboard Settings**:
- **Position**: Left or Right (default: Right).
- **Show/Hide Metrics**: Enable/disable dashboard rows (e.g., Comp Score, Trend, MFI; all enabled by default except Volatility and Volume MA).
3. **Save Changes**:
- Click “OK” to apply settings. The dashboard and plots update instantly.
Using the Indicator
1. **Interpreting Signals**:
- **Buy Signal (Long)**: Appears when Composite Score is low (≤30), with at least two bullish confirmations . Shown as “Long” in Signal Status with confidence percentage.
- **Sell Signal (Short)**: Appears when Composite Score is high (≥70), with at least two bearish confirmations. Shown as “Short” in Signal Status.
- **Golden Cross (🚀)**: Indicates a bullish trend when EMA 50 crosses above EMA 200. Look for confirmation from Composite Score and Signal Status.
- **Death Cross (💀)**: Indicates a bearish trend when EMA 50 crosses below EMA 200. Confirm with dashboard metrics.
- **Reversal Signals**: Dashboard shows “Bullish” or “Bearish” with a percentage when reversal conditions are met .
2. **Monitoring the Dashboard**:
- Use the dashboard to assess market conditions in real-time.
- Green (bullish), red (bearish), or gray (neutral) colors highlight key metrics.
- Check “Signal Confid” for confidence in buy/sell signals (higher is better, e.g., >60%).
3. **Trading Decisions**:
- Combine signals with your own analysis (e.g., support/resistance, news).
- Use Golden/Death Cross for long-term trend confirmation.
- Avoid trading in high volatility (dashboard: “Volatility: High”) unless experienced
Best Practices
- **Timeframe Selection**:
- Use higher timeframes (e.g., 4H, Daily) for more reliable signals, especially for Golden/Death Cross.
- Lower timeframes (e.g., 5m, 15m) may produce more signals but with higher noise.
- **Confirm Signals**:
- Cross-check buy/sell signals with dashboard metrics (e.g., Trend, MFI, ADX).
- Use Golden/Death Cross as a trend filter rather than a standalone signal.
- **Risk Management**:
- Always use stop-losses and position sizing based on your risk tolerance.
- Avoid trading during high volatility unless part of your strategy.
- **Regular Updates**:
- Monitor TradingView for script updates from the author (KoKalito) to access new features or bug fixes.
Troubleshooting
- **No Signals**:
- Ensure the chart timeframe matches your settings (e.g., 60m for MTF Period).
- Check if filters (Volume, ADX) are too strict; try disabling them.
- **Dashboard Missing**:
- Verify “Dashboard Position” is set to Left or Right.
- Ensure dashboard metrics are enabled (e.g., Show Comp Score).
- **Alerts Not Triggering**:
- Confirm the alert condition is set to “NeuroFlow Pro Indicator” and the correct option (e.g., “Golden Cross Alert”).
- Check TradingView’s “Alerts” panel for errors or expired alerts.
- Reapply the indicator to the chart if it was recently updated.
- **EMA Crosses Not Showing**:
- Zoom in on the chart to see 🚀 (Golden Cross) or 💀 (Death Cross) symbols.
- Ensure EMA 50 and EMA 200 lengths are not identical (defaults: 50, 200).
Support
- **Author**: KoKalito (check TradingView profile for updates or contact info).
- **TradingView Community**: Post questions in the TradingView Pine Script community or forums.
- **Documentation**: Refer to TradingView’s Pine Script v5 documentation for advanced customization.
- **Risk Warning**: Trading involves risk. Use the indicator as a tool, not a guarantee of profits. Always conduct your own analysis and manage risk appropriately.
Happy trading with **NeuroFlow Pro Indicator**! 🚀
Combined EMA Technical AnalysisThis script is written in Pine Script (version 5) for TradingView and creates a comprehensive technical analysis indicator called "Combined EMA Technical Analysis." It overlays multiple technical indicators on a price chart, including Exponential Moving Averages (EMAs), VWAP, MACD, PSAR, RSI, Bollinger Bands, ADX, and external data from the S&P 500 (SPX) and VIX indices. The script also provides visual cues through colors, shapes, and a customizable table to help traders interpret market conditions.
Here’s a breakdown of the script:
---
### **1. Purpose**
- The script combines several popular technical indicators to analyze price trends, momentum, volatility, and market sentiment.
- It uses color coding (green for bullish, red for bearish, gray/white for neutral) and a table to display key information.
---
### **2. Custom Colors**
- Defines custom RGB colors for bullish (`customGreen`), bearish (`customRed`), and neutral (`neutralGray`) signals to enhance visual clarity.
---
### **3. User Inputs**
- **EMA Colors**: Users can customize the colors of five EMAs (8, 20, 9, 21, 50 periods).
- **MACD Settings**: Adjustable short length (12), long length (26), and signal length (9).
- **RSI Settings**: Adjustable length (14).
- **Bollinger Bands Settings**: Length (20), multiplier (2), and proximity threshold (0.1% of band width).
- **ADX Settings**: Adjustable length (14).
- **Table Settings**: Position (e.g., "Bottom Right") and text size (e.g., "Small").
---
### **4. Indicator Calculations**
#### **Exponential Moving Averages (EMAs)**
- Calculates five EMAs: 8, 20, 9, 21, and 50 periods based on the closing price.
- Used to identify short-term and long-term trends.
#### **Volume Weighted Average Price (VWAP)**
- Resets daily and calculates the average price weighted by volume.
- Color-coded: green if price > VWAP (bullish), red if price < VWAP (bearish), white if neutral.
#### **MACD (Moving Average Convergence Divergence)**
- Uses short (12) and long (26) EMAs to compute the MACD line, with a 9-period signal line.
- Displays "Bullish" (green) if MACD > signal, "Bearish" (red) if MACD < signal.
#### **Parabolic SAR (PSAR)**
- Calculated with acceleration factors (start: 0.02, increment: 0.02, max: 0.2).
- Indicates trend direction: green if price > PSAR (bullish), red if price < PSAR (bearish).
#### **Relative Strength Index (RSI)**
- Measures momentum over 14 periods.
- Highlighted in green if > 70 (overbought), red if < 30 (oversold), white otherwise.
#### **Bollinger Bands (BB)**
- Uses a 20-period SMA with a 2-standard-deviation multiplier.
- Color-coded based on price position:
- Green: Above upper band or close to it.
- Red: Below lower band or close to it.
- Gray: Neutral (within bands).
#### **Average Directional Index (ADX)**
- Manually calculates ADX to measure trend strength:
- Strong trend: ADX > 25.
- Very strong trend: ADX > 50.
- Direction: Bullish if +DI > -DI, bearish if -DI > +DI.
#### **EMA Crosses**
- Detects bullish (crossover) and bearish (crossunder) events for:
- EMA 9 vs. EMA 21.
- EMA 8 vs. EMA 20.
- Visualized with green (bullish) or red (bearish) circles.
#### **SPX and VIX Data**
- Fetches daily closing prices for the S&P 500 (SPX) and VIX (volatility index).
- SPX trend: Bullish if EMA 9 > EMA 21, bearish if EMA 9 < EMA 21.
- VIX levels: High (> 25, fear), Low (< 15, stability).
- VIX color: Green if SPX bullish and VIX low, red if SPX bearish and VIX high, white otherwise.
---
### **5. Visual Outputs**
#### **Plots**
- EMAs, VWAP, and PSAR are plotted on the chart with their respective colors.
- EMA crosses are marked with circles (green for bullish, red for bearish).
#### **Table**
- Displays a summary of indicators in a customizable position and size.
- Indicators shown (if enabled):
- EMA 8/20, 9/21, 50: Green dot if bullish, red if bearish.
- VWAP: Green if price > VWAP, red if price < VWAP.
- MACD: Green if bullish, red if bearish.
- MACD Zero: Green if MACD > 0, red if MACD < 0.
- PSAR: Green if price > PSAR, red if price < PSAR.
- ADX: Arrows for very strong trends (↑/↓), dots for weaker trends, colored by direction.
- Bollinger Bands: Arrows (↑/↓) or dots based on price position.
- RSI: Numeric value, colored by overbought/oversold levels.
- VIX: Numeric value, colored based on SPX trend and VIX level.
---
### **6. Alerts**
- Triggers alerts for EMA 8/20 crosses:
- Bullish: "EMA 8/20 Bullish Cross on Candle Close!"
- Bearish: "EMA 8/20 Bearish Cross on Candle Close!"
---
### **7. Key Features**
- **Flexibility**: Users can toggle indicators on/off in the table and adjust parameters.
- **Visual Clarity**: Consistent use of green (bullish), red (bearish), and neutral colors.
- **Comprehensive**: Combines trend, momentum, volatility, and market sentiment indicators.
---
### **How to Use**
1. Add the script to TradingView.
2. Customize inputs (colors, lengths, table position) as needed.
3. Interpret the chart and table:
- Green signals suggest bullish conditions.
- Red signals suggest bearish conditions.
- Neutral signals indicate indecision or consolidation.
4. Set up alerts for EMA crosses to catch trend changes.
This script is ideal for traders who want a multi-indicator dashboard to monitor price action and market conditions efficiently.
Supertrend + MACD with Advanced FiltersDetailed Guide
1. Indicator Overview
Purpose:
This enhanced indicator combines Supertrend and MACD to signal potential trend changes. In addition, it now includes several extra filters for more reliable signals:
Multi-Timeframe (MTF) Confirmation: Checks a higher timeframe’s trend.
ADX (Momentum) Filter: Ensures the market is trending strongly.
Dynamic Factor Adjustment: Adapts the Supertrend sensitivity to current volatility.
Volume Filter: Verifies that current volume is above average.
Each filter can be enabled or disabled according to your preference.
How It Works:
The Supertrend calculates dynamic support/resistance levels based on ATR and an adjustable factor, while MACD identifies momentum shifts via its crossovers. The additional filters then confirm whether the conditions meet your criteria for a trend change. If all enabled filters align, the indicator plots a shape and triggers an alert.
2. Supertrend Component with Dynamic Factor
Base Factor & ATR Period:
The Supertrend uses these inputs to compute its dynamic bands.
Dynamic Factor Toggle:
When enabled, the factor is adjusted by comparing the current ATR to its simple moving average. This makes the indicator adapt to higher or lower volatility conditions, helping to reduce false signals.
3. MACD Component
Parameters:
Standard MACD settings (Fast MA, Slow MA, Signal Smoothing) determine the responsiveness of the MACD line. Crossovers between the MACD line and its signal line indicate potential trend reversals.
4. Multi-Timeframe (MTF) Filter
Function:
If enabled, the indicator uses a higher timeframe’s simple moving average (SMA) to confirm the prevailing trend.
Bullish Confirmation: The current close is above the higher timeframe SMA.
Bearish Confirmation: The current close is below the higher timeframe SMA.
5. ADX Filter (Momentum)
Custom Calculation:
Since the built-in ta.adx function may not be available, a custom ADX is calculated. This involves:
Determining positive and negative directional movements (DMs).
Smoothing these values to obtain +DI and -DI.
Calculating the DX and then smoothing it to yield the ADX.
Threshold:
Only signals where the ADX exceeds the set threshold (default 20) are considered valid, ensuring that the market is trending strongly enough.
6. Volume Filter
Function:
Checks if the current volume exceeds the average volume (SMA) multiplied by a specified factor. This helps confirm that a price move is supported by sufficient trading activity.
7. Combined Signal Logic & Alerts
Final Signal:
A bullish signal is generated when:
MACD shows a bullish crossover,
Supertrend indicates an uptrend,
And all enabled filters (MTF, ADX, volume) confirm the signal.
The bearish signal is generated similarly in the opposite direction.
Alerts:
Alert conditions are set so that TradingView can notify you via pop-up, email, or SMS when these combined conditions are met.
8. User Adjustments
Toggle Filters:
Use the on/off switches for MTF, ADX, and Volume filters as needed.
Parameter Tuning:
Adjust the ATR period, base factor, higher timeframe settings, ADX period/threshold, and volume multiplier to match your trading style and market conditions.
Backtesting:
Always backtest your settings to ensure that they perform well with your strategy.
Fortuna Trend Predictor**Fortuna Trend Predictor**
### Overview
**Fortuna Trend Predictor** is a powerful trend analysis tool that combines multiple technical indicators to estimate trend strength, volatility, and probability of price movement direction. This indicator is designed to help traders identify potential trend shifts and confirm trade setups with improved accuracy.
### Key Features
- **Trend Strength Analysis**: Uses the difference between short-term and long-term Exponential Moving Averages (EMA) normalized by the Average True Range (ATR) to determine trend strength.
- **Directional Strength via ADX**: Calculates the Average Directional Index (ADX) manually to measure the strength of the trend, regardless of its direction.
- **Probability Estimation**: Provides a probabilistic assessment of price movement direction based on trend strength.
- **Volume Confirmation**: Incorporates a volume filter that validates signals when the trading volume is above its moving average.
- **Volatility Filter**: Uses ATR to identify high-volatility conditions, helping traders avoid false signals during low-volatility periods.
- **Overbought & Oversold Levels**: Includes RSI-based horizontal reference lines to highlight potential reversal zones.
### Indicator Components
1. **ATR (Average True Range)**: Measures market volatility and serves as a denominator to normalize EMA differences.
2. **EMA (Exponential Moving Averages)**:
- **Short EMA (20-period)** - Captures short-term price movements.
- **Long EMA (50-period)** - Identifies the overall trend.
3. **Trend Strength Calculation**:
- Formula: `(Short EMA - Long EMA) / ATR`
- The higher the value, the stronger the trend.
4. **ADX Calculation**:
- Computes +DI and -DI manually to generate ADX values.
- Higher ADX indicates a stronger trend.
5. **Volume Filter**:
- Compares current volume to a 20-period moving average.
- Signals are more reliable when volume exceeds its average.
6. **Volatility Filter**:
- Detects whether ATR is above its own moving average, multiplied by a user-defined threshold.
7. **Probability Plot**:
- Formula: `50 + 50 * (Trend Strength / (1 + abs(Trend Strength)))`
- Values range from 0 to 100, indicating potential movement direction.
### How to Use
- When **Probability Line is above 70**, the trend is strong and likely to continue.
- When **Probability Line is below 30**, the trend is weak or possibly reversing.
- A rising **ADX** confirms strong trends, while a falling ADX suggests consolidation.
- Combine with price action and other confirmation tools for best results.
### Notes
- This indicator does not generate buy/sell signals but serves as a decision-support tool.
- Works best on higher timeframes (H1 and above) to filter out noise.
---
### Example Chart
*The chart below demonstrates how Fortuna Trend Predictor can help identify strong trends and avoid false breakouts by confirming signals with volume and volatility filters.*
Profit Hunter @DaviddTechProfit Hunter @DaviddTech is an advanced multi-strategy indicator designed to give traders a significant edge in identifying high-probability trading opportunities across all market conditions. By combining the power of T3 adaptive moving averages, ADX-based trend strength analysis, SuperTrend trailing stops, and dynamic support/resistance detection, this indicator delivers a complete trading system in one powerful package.
## 📊 Recommended Usage
Timeframes: Most effective on 1H, 4H, and Daily charts for swing trading; 5M and 15M for day trading
Markets: Works across all markets including Forex, Crypto, Indices, and Stocks
Setup Guidelines: Look for T3 crossovers with strong ADX readings (>25) coinciding with breakout signals (yellow dots/red crosses) near key support/resistance levels for highest probability entries
## 🔥 Key Features:
### T3 Adaptive Trend Detection:
Utilizes premium T3 adaptive indicators instead of standard EMAs for superior smoothing and accuracy
Dynamic color-shifting cloud formation between fast and slow T3 lines reveals immediate trend direction
Proprietary transparency algorithm intensifies cloud colors during strong trends based on real-time ADX readings
### Advanced Support & Resistance Mapping:
Automatically identifies and marks key market structure levels during T3 crossovers
Dynamic horizontal level plotting with optional extension for monitoring future price interactions
Intelligent level validation - converts to dotted lines when price breaks through, maintaining visual clarity
### SuperTrend Trailing Stoploss System:
Professional-grade white trailing stop indicator adapts to market volatility using ATR calculations
Generates precise entry and exit signals with optional buy/sell labels at critical reversal points
Visual trend state highlighting for immediate assessment of current market position
### Breakout Detection & Confirmation:
Sophisticated dual-algorithm breakout system combining Bollinger Bands and Keltner Channels
Visual breakout alerts with yellow dots (bullish) and red crosses (bearish) for instant pattern recognition
Validates breakouts against T3 trend direction to minimize false signals
### Alpha Edge Color System:
Utilizes DaviddTech's signature color scheme with bullish green and bearish pink
Revolutionary transparency algorithm translates ADX readings into precise visual intensity
Higher ADX values produce more vivid colors, instantly communicating trend strength without additional indicators
## 💰 Trading Applications:
Alpha Discovery: Identify emerging trends before the majority of market participants
Precision Entry/Exit: Use SuperTrend signals combined with support/resistance levels for optimal trade execution
Risk Management: Set stops based on the white trailing stoploss line for mathematically-optimized protection
Trend Confirmation: Validate setups using the T3 cloud direction and ADX-based intensity
Breakout Trading: Capture explosive moves with confirmed Bollinger/Keltner breakout signals
Swing Position Management: Monitor extended support/resistance levels for multi-day positioning
## ✨ Strategy Example
As shown in the chart image, ideal entries occur when:
The T3 cloud turns bullish (green) or bearish (pink) with strong color intensity
A yellow dot (bullish) or red cross (bearish) breakout signal appears
Price respects the white SuperTrend line as support/resistance
The trade aligns with key horizontal support/resistance levels identified by the indicator
## 📝 Attribution
This indicator builds upon and enhances concepts from:
Market Trend Levels Detector by BigBeluga (support/resistance detection framework)
T3 indicator implementation by DaviddTech (adaptive moving average system)
Average Directional Index (ADX) methodology for trend strength measurement
Profit Hunter @DaviddTech represents the culmination of advanced technical analysis methodologies in one seamless system.
MT-Trend Zone IdentifierTrend Zone Identifier – A Dynamic Market Trend Mapping Tool
Overview
The Trend Zone Identifier is an advanced TradingView indicator that helps traders visualize different market trend phases. By leveraging Pivot Points, Moving Averages (MA), ADX (Average Directional Index), and Retest Confirmation, this tool identifies uptrend, downtrend, and ranging (sideways) conditions dynamically.
This indicator is designed to segment the market into clear trend zones, allowing traders to distinguish between confirmed trends, trend transitions (pending zones), and ranging markets. It provides an intuitive visual overlay to enhance market structure analysis and assist in decision-making.
Key Features
✔ Trend Zone Identification – Classifies price action into Uptrend (Green), Downtrend (Red), Pending Confirmation (Light Colors), and Sideways Market (Gray/Neutral)
✔ Pivot-Based Breakout & Breakdown Detection – Uses pivot highs/lows to determine trend shifts
✔ Moving Average & ADX Validation – Ensures the trend is backed by MA structure and ADX trend strength
✔ Pullback Confirmation – Allows trend confirmation based on price retesting key levels
✔ Extreme Volatility & Gaps Filtering – Optional ATR-based extreme movement filtering to avoid false signals
✔ Multi-Timeframe Support – Option to integrate higher timeframe trend validation
✔ Customizable Sensitivity – Fine-tune MA smoothing, ADX thresholds, pivot detection, and pullback range
How It Works
1. Trend Classification
• Uptrend (Green): Price is above a key MA, ADX confirms strength, and a pivot breakout occurs
• Downtrend (Red): Price is below a key MA, ADX confirms strength, and a pivot breakdown occurs
• Pending Trend (Light Colors): Initial trend breakout or breakdown is detected but requires further confirmation
• Sideways/Ranging (Gray): ADX signals a weak trend, and price remains within a neutral zone
2. Retest & Confirmation Logic
• A trend is only confirmed after a breakout or breakdown followed by a successful retest
• If the market fails the retest, the indicator resets to a neutral state
3. Custom Filters for Optimization
• Enable or disable volume filtering for confirmation
• Adjust pivot sensitivity to detect major or minor swing points
• Choose to require consecutive bars confirming the breakout/breakdown
Ideal Use Cases
🔹 Swing traders who want to capture trend transitions early
🔹 Trend-following traders who rely on confirmed market cycles
🔹 Range traders looking to identify sideways market zones
🔹 Algorithmic traders who need clean trend segmentation for automated strategies
Final Thoughts
The Trend Zone Identifier is a versatile market structure indicator that helps traders define trend cycles visually and avoid trading against weak trends. By providing clear breakout, breakdown, and retest conditions, it enhances market clarity and reduces decision-making errors.
➡ Add this to your TradingView workspace and start analyzing market trends like a pro! 🚀
MTF Signal XpertMTF Signal Xpert – Detailed Description
Overview:
MTF Signal Xpert is a proprietary, open‑source trading signal indicator that fuses multiple technical analysis methods into one cohesive strategy. Developed after rigorous backtesting and extensive research, this advanced tool is designed to deliver clear BUY and SELL signals by analyzing trend, momentum, and volatility across various timeframes. Its integrated approach not only enhances signal reliability but also incorporates dynamic risk management, helping traders protect their capital while navigating complex market conditions.
Detailed Explanation of How It Works:
Trend Detection via Moving Averages
Dual Moving Averages:
MTF Signal Xpert computes two moving averages—a fast MA and a slow MA—with the flexibility to choose from Simple (SMA), Exponential (EMA), or Hull (HMA) methods. This dual-MA system helps identify the prevailing market trend by contrasting short-term momentum with longer-term trends.
Crossover Logic:
A BUY signal is initiated when the fast MA crosses above the slow MA, coupled with the condition that the current price is above the lower Bollinger Band. This suggests that the market may be emerging from a lower price region. Conversely, a SELL signal is generated when the fast MA crosses below the slow MA and the price is below the upper Bollinger Band, indicating potential bearish pressure.
Recent Crossover Confirmation:
To ensure that signals reflect current market dynamics, the script tracks the number of bars since the moving average crossover event. Only crossovers that occur within a user-defined “candle confirmation” period are considered, which helps filter out outdated signals and improves overall signal accuracy.
Volatility and Price Extremes with Bollinger Bands
Calculation of Bands:
Bollinger Bands are calculated using a 20‑period simple moving average as the central basis, with the upper and lower bands derived from a standard deviation multiplier. This creates dynamic boundaries that adjust according to recent market volatility.
Signal Reinforcement:
For BUY signals, the condition that the price is above the lower Bollinger Band suggests an undervalued market condition, while for SELL signals, the price falling below the upper Bollinger Band reinforces the bearish bias. This volatility context adds depth to the moving average crossover signals.
Momentum Confirmation Using Multiple Oscillators
RSI (Relative Strength Index):
The RSI is computed over 14 periods to determine if the market is in an overbought or oversold state. Only readings within an optimal range (defined by user inputs) validate the signal, ensuring that entries are made during balanced conditions.
MACD (Moving Average Convergence Divergence):
The MACD line is compared with its signal line to assess momentum. A bullish scenario is confirmed when the MACD line is above the signal line, while a bearish scenario is indicated when it is below, thus adding another layer of confirmation.
Awesome Oscillator (AO):
The AO measures the difference between short-term and long-term simple moving averages of the median price. Positive AO values support BUY signals, while negative values back SELL signals, offering additional momentum insight.
ADX (Average Directional Index):
The ADX quantifies trend strength. MTF Signal Xpert only considers signals when the ADX value exceeds a specified threshold, ensuring that trades are taken in strongly trending markets.
Optional Stochastic Oscillator:
An optional stochastic oscillator filter can be enabled to further refine signals. It checks for overbought conditions (supporting SELL signals) or oversold conditions (supporting BUY signals), thus reducing ambiguity.
Multi-Timeframe Verification
Higher Timeframe Filter:
To align short-term signals with broader market trends, the script calculates an EMA on a higher timeframe as specified by the user. This multi-timeframe approach helps ensure that signals on the primary chart are consistent with the overall trend, thereby reducing false signals.
Dynamic Risk Management with ATR
ATR-Based Calculations:
The Average True Range (ATR) is used to measure current market volatility. This value is multiplied by a user-defined factor to dynamically determine stop loss (SL) and take profit (TP) levels, adapting to changing market conditions.
Visual SL/TP Markers:
The calculated SL and TP levels are plotted on the chart as distinct colored dots, enabling traders to quickly identify recommended exit points.
Optional Trailing Stop:
An optional trailing stop feature is available, which adjusts the stop loss as the trade moves favorably, helping to lock in profits while protecting against sudden reversals.
Risk/Reward Ratio Calculation:
MTF Signal Xpert computes a risk/reward ratio based on the dynamic SL and TP levels. This quantitative measure allows traders to assess whether the potential reward justifies the risk associated with a trade.
Condition Weighting and Signal Scoring
Binary Condition Checks:
Each technical condition—ranging from moving average crossovers, Bollinger Band positioning, and RSI range to MACD, AO, ADX, and volume filters—is assigned a binary score (1 if met, 0 if not).
Cumulative Scoring:
These individual scores are summed to generate cumulative bullish and bearish scores, quantifying the overall strength of the signal and providing traders with an objective measure of its viability.
Detailed Signal Explanation:
A comprehensive explanation string is generated, outlining which conditions contributed to the current BUY or SELL signal. This explanation is displayed on an on‑chart dashboard, offering transparency and clarity into the signal generation process.
On-Chart Visualizations and Debug Information
Chart Elements:
The indicator plots all key components—moving averages, Bollinger Bands, SL and TP markers—directly on the chart, providing a clear visual framework for understanding market conditions.
Combined Dashboard:
A dedicated dashboard displays key metrics such as RSI, ADX, and the bullish/bearish scores, alongside a detailed explanation of the current signal. This consolidated view allows traders to quickly grasp the underlying logic.
Debug Table (Optional):
For advanced users, an optional debug table is available. This table breaks down each individual condition, indicating which criteria were met or not met, thus aiding in further analysis and strategy refinement.
Mashup Justification and Originality
MTF Signal Xpert is more than just an aggregation of existing indicators—it is an original synthesis designed to address real-world trading complexities. Here’s how its components work together:
Integrated Trend, Volatility, and Momentum Analysis:
By combining moving averages, Bollinger Bands, and multiple oscillators (RSI, MACD, AO, ADX, and an optional stochastic), the indicator captures diverse market dynamics. Each component reinforces the others, reducing noise and filtering out false signals.
Multi-Timeframe Analysis:
The inclusion of a higher timeframe filter aligns short-term signals with longer-term trends, enhancing overall reliability and reducing the potential for contradictory signals.
Adaptive Risk Management:
Dynamic stop loss and take profit levels, determined using ATR, ensure that the risk management strategy adapts to current market conditions. The optional trailing stop further refines this approach, protecting profits as the market evolves.
Quantitative Signal Scoring:
The condition weighting system provides an objective measure of signal strength, giving traders clear insight into how each technical component contributes to the final decision.
How to Use MTF Signal Xpert:
Input Customization:
Adjust the moving average type and period settings, ATR multipliers, and oscillator thresholds to align with your trading style and the specific market conditions.
Enable or disable the optional stochastic oscillator and trailing stop based on your preference.
Interpreting the Signals:
When a BUY or SELL signal appears, refer to the on‑chart dashboard, which displays key metrics (e.g., RSI, ADX, bullish/bearish scores) along with a detailed breakdown of the conditions that triggered the signal.
Review the SL and TP markers on the chart to understand the associated risk/reward setup.
Risk Management:
Use the dynamically calculated stop loss and take profit levels as guidelines for setting your exit points.
Evaluate the provided risk/reward ratio to ensure that the potential reward justifies the risk before entering a trade.
Debugging and Verification:
Advanced users can enable the debug table to see a condition-by-condition breakdown of the signal generation process, helping refine the strategy and deepen understanding of market dynamics.
Disclaimer:
MTF Signal Xpert is intended for educational and analytical purposes only. Although it is based on robust technical analysis methods and has undergone extensive backtesting, past performance is not indicative of future results. Traders should employ proper risk management and adjust the settings to suit their financial circumstances and risk tolerance.
MTF Signal Xpert represents a comprehensive, original approach to trading signal generation. By blending trend detection, volatility assessment, momentum analysis, multi-timeframe alignment, and adaptive risk management into one integrated system, it provides traders with actionable signals and the transparency needed to understand the logic behind them.
Continuous Multi-Factor Trend Oscillator with Rolling Liquidity
// **Overview**
This script generates a *Continuous Multi-Factor Trend Oscillator* that integrates multiple market dynamics, including **long-term trends**, **short-term trends**, **volume adjustments**, **volatility factors**, **ADX trend strength**, and **rolling liquidity**. The result is a smooth, dynamic oscillator that reflects comprehensive market conditions.
### **Key Features**
1. **Long-Term Trend Score (LT Score)**: Measures the deviation of price from its EMA, normalized by standard deviation. Captures broad trend direction.
2. **Short-Term Trend Score (ST Score)**: Evaluates the slope of a short-period EMA, normalized by ATR, to reflect shorter-term momentum.
3. **Volume Adjustment**: Adjusts trend scores based on the relative volume compared to its moving average.
4. **Volatility Adjustment**: Incorporates ATR into the scoring system, penalizing or boosting scores based on current volatility compared to historical norms.
5. **ADX Trend Strength**: Uses ADX to identify trend strength, scaling scores positively or negatively depending on whether the market is trending or ranging.
6. **Rolling Liquidity**: Analyzes persistent buying or selling pressure by aggregating net buy/sell liquidity over a rolling lookback period.
### **Calculation Workflow**
- **Inputs**: Configurable parameters like long/short periods, ATR period, ADX smoothing, and volume lookback.
- **Trend Scores**: LT and ST scores are computed separately to capture trend dynamics across different timeframes.
- **Adjustments**: Volume, volatility, ADX, and rolling liquidity adjustments are calculated and scaled appropriately.
- **Final Oscillator**: Combines all scores into a single value and applies smoothing for clarity.
### **How It Works**
1. *Long-Term and Short-Term Trends*: Trend scores are calculated based on EMAs and normalized using standard deviation or ATR.
2. *Volume and Liquidity Factors*: Incorporates net up/down volume and liquidity to reflect market participation levels.
3. *ADX Strength*: Distinguishes trending vs. ranging markets, influencing the oscillator direction accordingly.
4. *Final Output*: All factors are combined into a single oscillator, smoothed using an EMA.
### **Visualization**
- The oscillator is plotted as a continuous line with dynamic scaling:
- **Above 75**: *Very Bullish*
- **Below -75**: *Very Bearish*
- **Threshold Levels (50/-50, 10/-10)**: Provide additional interpretative guidance.
- **Labels**: Displays sentiment at the last bar for quick reference (e.g., *Strongly Bullish*, *Neutral*).
### **Use Cases**
- Ideal for identifying market conditions (bullish, bearish, neutral) based on multiple factors.
- Can serve as a confirmation tool alongside price action or other indicators.
### **Customizable Parameters**
- All periods (e.g., long-term, short-term, ATR, ADX) and lookbacks are adjustable, allowing fine-tuning based on market behavior and trading preferences.
How to use:
Eze Profit Range Detection FilterThe Range Detection Filter is a technical analysis tool designed to help traders identify range-bound market conditions and focus on breakout opportunities. It combines the ATR (Average True Range) for volatility analysis and the ADX (Average Directional Index) for trend strength evaluation to highlight consolidation phases and alert traders when the market is ready to break out.
This indicator provides visual cues and customizable alerts, making it suitable for traders looking to avoid false signals during choppy markets and capitalize on trending moves following a breakout.
What Makes It Unique?
ATR for Volatility:
Measures market volatility by comparing ATR with its moving average.
Consolidation phases are flagged when ATR remains below its moving average for a sustained period.
ADX for Trend Strength:
Monitors trend strength, confirming range-bound conditions when ADX falls below a user-defined threshold (default: 20).
Combines with ATR to ensure accurate detection of trendless periods.
Breakout Alerts:
Notifies traders of breakout opportunities when the price moves outside the highest high or lowest low of the range.
How It Works:
Range Detection:
The market is considered "in range" when:
ATR is below its moving average, indicating low volatility.
ADX is below the threshold, confirming a lack of trend strength.
Visual Indication:
A yellow background highlights range-bound conditions, allowing traders to avoid low-probability trades.
Breakout Detection:
Alerts are triggered for breakouts above or below the range to help traders identify potential opportunities.
Features:
Range Highlighting:
Automatically detects and highlights range-bound markets using a yellow background.
Breakout Alerts:
Sends alerts for breakouts above or below the range once the market exits consolidation.
Customizable Inputs:
ATR length, moving average length, and ADX parameters are fully adjustable to adapt to various trading styles and asset classes.
Multi-Timeframe Compatibility:
Suitable for all markets and timeframes, including stocks, forex, and cryptocurrencies.
How to Use:
Identify Ranges:
Avoid trading when the yellow background appears, signaling a range-bound market.
Focus on Breakouts:
Look for alerts indicating breakouts above or below the range for potential trending opportunities.
Combine with Other Indicators:
Use volume analysis, momentum oscillators, or candlestick patterns to confirm breakout signals.
Credits:
This script utilizes widely accepted methodologies for ATR and ADX calculations. ADX is calculated manually using directional movement (+DI and -DI) for precise trend detection. The concept has been adapted and enhanced to create this comprehensive range-detection tool.
Notes:
This indicator is intended for educational purposes and should not be used as standalone financial advice.
Always incorporate this tool into a broader trading strategy for optimal results.
Swing Crossings - TradingEDThis case study is based on different previous studies: ADX Performance , MACD Performance & RSI Performance, with different counts to compare different oscillations of each indicator. Actually, this indicator is complementary to those previously mentioned. The use of this indicator is restricted to private use, and it can be used only by invitation. Different functionalities have been added to the original codes, such as alerts and signals that seek to make trading much easier to interpret by any type of trading operator of any experience level, from beginner to intermediate and advanced .
Key components of the original ADX indicator:
• The DIRECTIONAL MOVEMENT INDEX (DMI) is a technical indicator that measures both the strength and direction of a price movement and is intended to reduce false signals.
• The DMI uses two standard indicators, one negative ( -DI ) and one positive ( +DI ), in conjunction with a third, the AVERAGE DIRECTIONAL INDEX ( ADX ), which is non-directional but shows momentum.
• The larger the spread between the two primary lines, the stronger the price trend. If +DI is way above -DI the price trend is strongly up. If -DI is way above +DI then the price trend is strongly down.
• ADX measures the strength of the trend, either up or down; a reading above 20 indicates a strong trend.
ADX is plotted as a single line with values ranging from a low of zero to a high of 100. ADX is non-directional; it registers trend strength whether price is trending up or down. The indicator is usually plotted in the same window as the two DMI lines, from which ADX is derived. When +DI is above -DI , there is more upward pressure than downward pressure in the price. Conversely, if -DI is above +DI , then there is more downward pressure on the price. This indicator may help traders assess the trend direction. Crossovers between the lines are also sometimes used as trade signals to buy or sell, theay are the main trade signals. A long trade is taken when the +DI crosses above the -DI and an uptrend could be underway. Meanwhile, a sell signal occurs when the +DI instead crosses below the -DI .
Key components of the original RSI indicator:
● The Relative Strength Index ( RSI ) is a popular momentum oscillator developed in 1978.
● The RSI provides technical traders signals about bullish and bearish price momentum, and it is often plotted beneath the graph of an asset's price.
● An asset is usually considered overbought when the RSI is above 70% and oversold when it is below 30%.
It is a momentum indicator used in technical analysis that measures the magnitude of recent price changes to assess overbought or oversold conditions in the price of an asset. The RSI is displayed as an oscillator (a line chart moving between two extremes) and can read from 0 to 100. Overbought does not necessarily mean that the price will reverse lower, just as oversold does not mean that the price will reverse higher. Rather, the overbought and oversold conditions simply alert traders that the RSI is near the extremes of its recent readings.
Key components of the original MACD indicator:
● The Moving Average Convergence Divergence ( MACD ) is calculated by subtracting a long period (26) Exponential Moving Average ( EMA ) from a short (12) period EMA .
● MACD triggers technical signals when it crosses above (to buy) or below (to sell) its signal line.
● The speed of crossovers is also taken as a signal of a market is overbought or oversold.
● MACD helps traders to understand whether the bullish or bearish movement in the price is strengthening or weakening.
It is a momentum indicator that follows the trend and shows the relationship between two moving averages of the price of a security. It can function as a trigger for buy and sell signals, when you cross above (to buy) or below (to sell) your signal line. It helps to understand if the movement is bullish or bearish , if it is getting stronger or weaker. The further the MACD is above or below its baseline, it indicates that the distance between the two EMAs will be growing, often shown with a histogram that graphically represents the distance between the MACD and its signal line, and It is used to identify when the bullish or bearish momentum.
Main functions of this modified indicator:
1) The SOURCE for the counts can be determined by the trader (close, open, etc).
2) In some cases, you can select the type of MOVING AVERAGE, among many available options ( SMA , EMA , DEMA , HMA , etc.)
3) The MEASURE can be based on a CANDLES count if you are trading OHLC Charts from 1D onwards, or if your trading is intraday, you can also select counts by MINUTES, HOURS or DAYS, depending on your trading style.
4) LENGTH, by default it will be loaded as in the STRATEGY, but considering the previous point, you can modify it according to your convenience.
5) You have the option to hide or show a LABEL at the top of the chart, with respect to the signals: BULLISH green, BEARISH red. *
6) You have the option to hide or show INDICATORS or SIGNALS based on EACH OSCILLATION.
Main performance functions of this modified indicator:
I) In the case of the PERFORMANCE that appears at the right of the chart, you have the option to adjust the WIDTH of each box.
II) The TEXT of the PERFORMANCE is not modifiable, but you can customize the default color. *
III) The BACKGROUND of the PERFORMANCE, you can customize the default color. *
IV) You have the option to hide or show a PERFORMANCE that appears at the right of the chart.
Main functions to customize the style of this indicator:
a) For any type of SIGNAL, it is painted as a VERTICAL LINE in the graph, you can change the color that comes by default. *
b) In the case of the LABELS that appear at the top, the text is not modifiable, but you can customize both the type of label and change the default color. *
c) When you have a SHORT SIGNAL or a LONG SIGNAL, you can change the EMOTICON that comes by default. **
* By default, they are marked as red for downtrends and green for uptrends.
** By default, they are marked with an emoticon indicating the possible direction of the price, down if it is bearish or up if it is bullish .
StableF-MainIt is combination of Built in Super trend and Adx with take profit
uptrend is considered when +dmi is above -dmi and +dmi is above 25 and adx is above 25 and supertrend gives Buy
downtrend is considered when -dmi is above +dmi and -dmi is above 25 and adx is above 25 and supertrend give sell
use fibo for target by taking as previous swing high and swing low
-supertrend crossover is referred as buy plotshape
-supertrend cross under is referred as Sell plotshape
-keep stoploss at dot line of supertrend
-adx-dmi crossover (+dmi crossed above -dmi) is shown by Triangle Up symbol
-adx-dmi crossunder( -dmi crosses below +dmi) is shown by Triangle down symbol
--Cross symbol with blue line with linewidth 2 is referred as Take profit
--combine this with adx -dmi setting with 7 and 14
----disclaimer-----
used free built in supertrend and adx so u can use same setting in other broker or in trading view
not responsible for any loss or gain
-only for educational purpose
