Fusion Trend Pulse V2SCRIPT TITLE
Adaptive Fusion Trend Pulse V2 - Multi-Regime Strategy
DETAILED DESCRIPTION FOR PUBLICATION
🚀 INNOVATION SUMMARY
The Adaptive Fusion Trend Pulse V2 represents a breakthrough in algorithmic trading by introducing real-time market regime detection that automatically adapts strategy parameters based on current market conditions. Unlike static indicator combinations, this system dynamically adjusts its behavior across trending, choppy, and volatile market environments, providing a sophisticated multi-layered approach to market analysis.
🎯 CORE INNOVATIONS JUSTIFYING PROTECTED STATUS
1. Adaptive Market Regime Engine
Trending Market Detection: Uses ADX >25 with directional movement analysis
Volatile Market Classification: ATR-based volatility regime scoring (>1.2 threshold)
Choppy Market Identification: ADX <20 combined with volatility patterns
Dynamic Parameter Adjustment: All thresholds adapt based on detected regime
2. Multi-Component Fusion Algorithm
McGinley Dynamic Trend Baseline: Self-adjusting moving average that adapts to price velocity
Adaptive RMI (Relative Momentum Index): Enhanced RSI with momentum period adaptation
Zero-Lag EMA Smoothed CCI: Custom implementation reducing lag while maintaining signal quality
Hull MA Gradient Analysis: Slope strength normalized by ATR for trend confirmation
Volume Spike Detection: Regime-adjusted volume confirmation (0.8x-1.3x multipliers)
3. Intelligence Layer Features
Cooldown System: Prevents overtrading with regime-specific waiting periods (1-3 bars)
Performance Tracking: Real-time adaptation based on recent trade outcomes
Multi-Exchange Alert Integration: JSON-formatted alerts for automated trading
Comprehensive Dashboard: 16-metric real-time performance monitoring
📊 TECHNICAL SPECIFICATIONS
Market Regime Detection Philosophy:
The system continuously monitors market structure through volatility analysis and directional strength measurements. Rather than applying fixed thresholds, it creates dynamic response profiles that adjust the strategy's sensitivity, timing, and filtering based on the current market environment.
Adaptive Parameter Concept:
All strategy components modify their behavior based on regime classification. Volume requirements become more or less stringent, momentum thresholds shift to match market character, and exit timing adjusts to prevent whipsaws in different market conditions.
Entry Conditions (Both Long/Short):
McGinley trend alignment (close vs trend line)
Hull MA slope confirmation with ATR-normalized strength
Adaptive CCI above/below regime-specific thresholds
RMI momentum confirmation (>50 for long, <50 for short)
Volume spike exceeding regime-adjusted threshold
Regime-specific additional filters
Exit Strategy:
Dual take-profit system (2% and 4% default, customizable)
Momentum weakness detection (CCI reversal)
Trend breakdown (close below/above McGinley line)
Regime-specific urgency multipliers for faster exits in choppy markets
🎛️ USER CUSTOMIZATION OPTIONS
Core Parameters:
RMI Length & Momentum periods
CCI smoothing length
McGinley Dynamic length
Hull MA period for gradient analysis
Volume spike detection (length & multiplier)
Take profit levels (separate for long/short)
Adaptive Settings:
Market regime detection period (21 bars default)
Adaptation period for performance tracking (60 bars)
Volatility adaptation toggle
Trend strength filtering toggle
Momentum sensitivity multiplier (0.5-2.0 range)
Dashboard & Alerts:
Dashboard position (4 corners)
Dashboard size (Small/Normal/Large)
Transparency settings (0-100%)
Custom alert messages for bot integration
Date range filtering
🏆 UNIQUE VALUE PROPOSITIONS
1. Market Intelligence: First Pine Script strategy to implement comprehensive regime detection with parameter adaptation - most strategies use static settings regardless of market conditions.
2. Fusion Methodology: Combines 5+ distinct technical approaches (trend-following, momentum, volatility, volume, regime analysis) in a cohesive adaptive framework rather than simple indicator stacking.
3. Performance Optimization: Built-in learning system tracks recent performance and adjusts sensitivity - providing evolution rather than static rule-following.
4. Professional Integration: Enterprise-ready with JSON alert formatting, multi-exchange compatibility, and comprehensive performance tracking suitable for institutional use.
5. Visual Intelligence: Advanced dashboard provides 16 real-time metrics including regime classification, signal strength, and performance analytics - far beyond basic P&L displays.
🔧 TECHNICAL IMPLEMENTATION HIGHLIGHTS
Primary Applications:
Swing Trading: 4H-1D timeframes with regime-adapted entries
Algorithmic Trading: Automated execution via webhook alerts
Portfolio Management: Multi-timeframe analysis across different market conditions
Risk Management: Regime-aware position sizing and exit timing
Target Markets:
Cryptocurrency pairs (high volatility adaptation)
Forex majors (trending market optimization)
Stock indices (choppy market handling)
Commodities (volatile regime management)
🎯 WHY THIS ISN'T JUST AN INDICATOR MASHUP
Integrated Adaptation Framework: Unlike scripts that simply combine multiple indicators with static settings, this system creates a unified intelligence layer where each component influences and adapts to the others. The McGinley trend baseline doesn't just provide signals - it dynamically adjusts its sensitivity based on market regime detection. The momentum components modify their thresholds based on trend strength analysis.
Feedback Loop Architecture: The strategy incorporates a closed-loop learning system where recent performance influences future parameter selection. This creates evolution rather than static rule application. Most indicator combinations lack this adaptive learning capability.
Contextual Decision Making: Rather than treating each signal independently, the system uses contextual analysis where the same technical setup may generate different responses based on the current market regime. A momentum signal in a trending market triggers different behavior than the identical signal in choppy conditions.
Unified Risk Management: The regime detection doesn't just affect entries - it creates a comprehensive risk framework that adjusts exit timing, cooldown periods, and position management based on market character. This holistic approach distinguishes it from simple indicator stacking.
Custom Implementation Depth: Each component uses proprietary implementations (custom McGinley calculation, zero-lag CCI smoothing, enhanced RMI) rather than standard built-in functions, creating a cohesive algorithmic ecosystem rather than disconnected indicator outputs.
Custom Functions:
mcginley(): Proprietary implementation of McGinley Dynamic MA
rmi(): Enhanced Relative Momentum Index with custom parameters
zlema(): Zero-lag EMA for CCI smoothing
Regime classification algorithms with multi-factor analysis
Performance Optimizations:
Efficient variable management with proper scoping
Minimal repainting through careful historical referencing
Optimized calculations to prevent timeout issues
Memory-efficient tracking systems
Alert System:
JSON-formatted messages for API integration
Dynamic symbol/exchange substitution
Separate entry/exit/TP alert conditions
Customizable message formatting
⚡ WHY THIS REQUIRES PROTECTION
This strategy represents months of research into adaptive trading systems and market regime analysis. The specific combination of:
Proprietary regime detection algorithms
Custom adaptive parameter calculations
Multi-indicator fusion methodology
Performance-based learning system
Professional-grade implementation
Creates intellectual property that provides genuine competitive advantage. The methodology is not available in existing open-source scripts and represents original research into algorithmic trading adaptation.
🎯 EDUCATIONAL VALUE
Users gain exposure to:
Advanced market regime analysis techniques
Adaptive parameter optimization concepts
Multi-timeframe indicator fusion
Professional strategy development practices
Automated trading integration methods
The comprehensive dashboard and parameter explanations serve as a learning tool for understanding how professional algorithms adapt to changing market conditions.
CATEGORY SELECTION
Primary: Strategy
Secondary: Trend Analysis
SUGGESTED TAGS
adaptive, trend, momentum, regime, strategy, alerts, dashboard, mcginley, rmi, cci, professional
MANDATORY DISCLAIMER
Disclaimer: This strategy is for educational and informational purposes only. It does not constitute financial advice. Trading cryptocurrencies involves substantial risk, and past performance is not indicative of future results. Always backtest and forward-test before using on a live account. Use at your own risk.
볼래틸리티
🏆 UNMITIGATED LEVELS ACCUMULATIONPDH TO ATH RISK FREE
All the PDL have a buy limit which starts at 0.1 lots which will duplicate at the same time the capital incresases. All of the buy limits have TP in ATH for max reward.
Parallax Momentum MNQ Strategy# 📈 Parallax Momentum MNQ Strategy
## Overview
The Parallax Momentum MNQ Strategy is a sophisticated support/resistance breakout system specifically designed for Micro Nasdaq futures (MNQ) trading (also works on minis). This strategy combines dynamic level detection with momentum confirmation to identify high-probability entry opportunities while maintaining strict risk management protocols.
## 🎯 Key Features
### Core Strategy Logic
- **Dynamic Support/Resistance Detection**: Automatically identifies key levels using configurable lookback periods
- **Momentum Confirmation**: Volume-based filtering ensures trades align with market momentum
- **ATR-Based Risk Management**: Adaptive stop losses and take profits based on market volatility
- **Dual Entry System**: Both long and short opportunities with limit order execution
### Risk Management
- **ATR-Adaptive Stops**: Stop losses and take profits automatically adjust to market volatility
- **Reward-to-Risk Ratios**: Configurable R:R ratios with default 2:1 minimum
- **Maximum Loss Protection**: Optional daily loss limits to prevent overtrading
- **Session Time Filtering**: Trade only during specified market hours
### Strategy Modes
- **Conservative Mode**: 0.8x risk multiplier for cautious trading
- **Balanced Mode**: Standard 1.0x risk multiplier (default)
- **Aggressive Mode**: 1.2x risk multiplier for active trading
## 📊 Visual Features
### Dashboard Display
- Real-time strategy status and performance metrics
- Current support/resistance levels and ATR values
- Live risk-to-reward ratios for potential trades
- Win rate, profit factor, and drawdown statistics
- Adjustable dashboard size and positioning
### Chart Indicators
- Support and resistance lines with labels
- ATR-based levels (+/-1 ATR and +/-2 ATR)
- Dynamic visual updates as levels change
- Configurable line extensions and styling
## ⚙️ Configuration Options
### Entry Filters
- **Volume Filter**: Optional volume confirmation above SMA
- **Session Time Filter**: 12-hour format time restrictions
- **ATR vs Fixed Stops**: Choose between adaptive or fixed tick-based exits
### Risk Controls
- **ATR Period**: Default 14-period ATR calculation
- **Stop Loss Multiplier**: ATR-based stop distance (default 1.5x)
- **Take Profit Multiplier**: ATR-based target distance (default 1.5x)
- **Secondary Take Profit**: Optional TP2 with position scaling
## 📋 How It Works
### Entry Conditions
**Long Trades**: Triggered when price closes above support buffer but low touches support level, with volume and session confirmation
**Short Trades**: Triggered when price closes below resistance buffer but high touches resistance level, with volume and session confirmation
### Exit Strategy
- **Primary Take Profit**: ATR-based target with 2:1 R:R minimum
- **Stop Loss**: ATR-based protective stop
- **Optional TP2**: Extended target for partial profit taking
- **One Trade at a Time**: No overlapping positions
## 🎛️ Default Settings
- **Lookback Period**: 20 bars for support/resistance detection
- **ATR Period**: 14 bars for volatility calculation
- **Stop Loss**: 1.5x ATR from entry
- **Take Profit**: 1.5x ATR with 2:1 reward-to-risk ratio
- **Session**: 7:30 AM - 2:00 PM (configurable)
## ⚠️ Important Notes
### Risk Disclaimer
- This strategy is for educational and informational purposes only
- Past performance does not guarantee future results
- Always use proper position sizing and risk management
- Test thoroughly on historical data before live trading
- Consider market conditions and volatility when using
### Best Practices
- Backtest on sufficient historical data
- Start with conservative mode for new users
- Monitor performance regularly and adjust parameters as needed
- Use appropriate position sizing for your account
- Consider broker commissions and slippage in live trading
## 🔧 Customization
The strategy offers extensive customization options including:
- Adjustable time sessions with AM/PM format
- Configurable ATR and risk parameters
- Optional maximum daily loss limits
- Dashboard size and position controls
- Visual element toggles and styling
## 📈 Ideal For
- MNQ (Micro Nasdaq) futures traders
- Intraday momentum strategies
- Traders seeking systematic entry/exit rules
- Risk-conscious traders wanting automated stops
- Both beginner and experienced algorithmic traders
---
**Version**: Pine Script v5 Compatible
**Timeframe**: Works on multiple timeframes (test on 1m, 3m, 5m, 15m)
**Market**: Optimized for MNQ but adaptable to other instruments
**Strategy Type**: Trend following with momentum confirmation
RCI 2 Dashboards ✅ Strategy: RCI 2 Dashboards BY Sonu JAIN
This advanced strategy is built around the Rank Correlation Index (RCI), a unique momentum oscillator, and combines it with a comprehensive suite of powerful indicators to identify high-probability trading opportunities. The strategy’s core strength lies in its ability to filter signals using up to 12 different conditions for both long and short trades.
To make the decision-making process clear and intuitive, the strategy features two dynamic, customizable dashboards right on your chart. The first dashboard gives you a live, detailed breakdown of which conditions are met, while the second provides a real-time overview of the strategy’s performance.
How It Works
The strategy generates entry signals based on RCI crossovers and crossunders. These signals are then filtered by a customizable combination of other indicators to confirm the trade.
Long Entry:
The RCI crosses over its moving average.
All enabled long-side filters are met.
Short Entry:
The RCI crosses under its moving average.
All enabled short-side filters are met.
Key Features
RCI Crossover Logic: The core of the strategy is an RCI crossover/crossunder with a customizable moving average (MA). You can choose from SMA, EMA, SMMA (RMA), WMA, or VWMA.
12 Optional Filters: This strategy goes far beyond a simple RCI signal. You can enable or disable a wide range of filters to refine your entries. These include:
Trend: Supertrend, Parabolic SAR (SAR), and Vortex Indicator.
Volatility: Keltner Channels (KC) and Bollinger Bands (BB).
Momentum: Woodies CCI, Money Flow Index (MFI), and Relative Strength Index (RSI).
Volume: On-Balance Volume (OBV) and simple Volume analysis.
Directional Strength: Average Directional Index (ADX).
Timing: A time-of-day filter to trade only during specific market hours.
Dual Dashboards:
Detailed Condition Dashboard: This dashboard shows you exactly which of the 12 filters are currently met with a simple ✓ or ✗. This provides instant clarity on why a trade is or isn't being considered.
Performance Dashboard: This dashboard displays key performance metrics in real-time, including net profit, win rate, profit factor, max drawdown, and current/max winning and losing streaks. It also provides details on the most recent trade, such as entry, stop-loss, and exit prices.
Customizable Stop Loss: The strategy includes a fixed percentage-based stop loss for both long and short positions, which you can easily configure in the settings.
Trade Direction Control: You can choose to trade "Long Only," "Short Only," or "Long & Short," giving you complete control over your trading bias.
This strategy is a powerful tool for traders who want to build a robust, multi-filtered system. The included dashboards make it an excellent educational tool for understanding how different indicators work together to form a complete trading plan. You can use it to backtest and optimize your own unique combination of indicators to find the perfect setup for your market and timeframe.
Matrix Trading Strategy**Matrix Trading Strategy** is a multi-signal framework designed to identify and exploit intraday trends with controlled precision. It combines three independent entry engines—Opening Range Breakout (ORB), Ultimate Trend via ATR trailing, and a moving average crossover (MA Cross)—which can operate alone or in any combination, offering traders maximum flexibility.
Risk management is fully parameterizable: position sizing by percent of equity, fixed cash amount, or fixed quantity; SL/TP in pips aligned to the instrument’s tick size (`pipSize`); automatic break-even; ATR-based trailing stop (with an option to anchor to the UT line itself); and configurable partial exits (TP1/TP2). Daily trade limits, entry cooldowns, and forced end-of-session liquidation enforce strict discipline.
Visually, the script plots EMAs, a 1-minute VWAP, ORB levels, the UT trailing line, and signal markers, and it colors candles by RSI for rapid momentum assessment. Ready-to-use alerts for ORB, UT, and MA signals support seamless automation via webhooks.
All together, Matrix Trading is a modular framework that adapts effortlessly to cryptocurrencies, metals, or global indices, delivering realistic executions and transparent metrics in both backtests and live trading.
Advanced Supertrend StrategyA comprehensive Pine Script v5 strategy featuring an enhanced Supertrend indicator with multiple technical filters, risk management, and advanced signal confirmation for automated trading on TradingView.
## Features
- **Enhanced Supertrend**: Configurable ATR-based trend following with improved accuracy
- **RSI Filter**: Optional RSI-based signal filtering to avoid overbought/oversold conditions
- **Moving Average Filter**: Trend confirmation using SMA/EMA/WMA with customizable periods
- **Risk Management**: Built-in stop-loss and take-profit based on ATR multiples
- **Trend Strength Analysis**: Filters weak signals by requiring minimum trend duration
- **Breakout Confirmation**: Optional price breakout validation for stronger signals
- **Visual Interface**: Comprehensive chart plotting with multiple indicator overlays
- **Advanced Alerts**: Multiple alert conditions with detailed signal information
- **Backtesting**: Full strategy backtesting with commission and realistic execution
rsi indicator strategyRSIBB Strategy Based on Oversold, Overrbuy Bolinger Band Band. In usoil . Time Indicators is set and the timing is in 5 minutes
An example of Long. When the green marker appears, our entry point is High High If the price fails to reject our High High, our entry will change to the next candlestick. This process will continue until we enter the position.
A marker appears in purple when the green marker appears to us, in which information appears:
The first digit related to the strategist code
The second digit is that we have a few pips to be sure of the candlestick of our entry point
The third digit is our SL that is a coefficient of overall size of yogurt (HIGH - LOW)
Charmin is the digit of our tp that is a coefficient of overall size of yogurt (HIGH - LOW)
In 6 sets
استراتژی RSIBB بر اساس اشباع فروش، اشباع خرید، باند بولینگر. در این روش، اندیکاتورهای زمانی تنظیم شده و زمانبندی ۵ دقیقه است.
مثالی از موقعیت خرید. وقتی نشانگر سبز ظاهر میشود، نقطه ورود ما High است. اگر قیمت نتواند High ما را رد کند، ورود ما به کندل بعدی تغییر میکند. این فرآیند تا زمانی که وارد موقعیت شویم ادامه خواهد داشت.
وقتی نشانگر سبز برای ما ظاهر میشود، یک نشانگر به رنگ بنفش ظاهر میشود که در آن اطلاعات زیر ظاهر میشود:
رقم اول مربوط به کد استراتژیست است.
رقم دوم این است که ما چند پیپ برای اطمینان از کندل نقطه ورود خود داریم.
رقم سوم SL ما است که ضریبی از اندازه کلی ماست (HIGH - LOW) است.
چارمین رقم tp ما است که ضریبی از اندازه کلی ماست (HIGH - LOW) است.
PRO Trading Rags2Riches
---
#### **English Version**
**🔒 PRO Trading Rags2Riches **
*Advanced Adaptive Multi-Instrument Strategy with Intelligent Capital Management*
**🌟 Revolutionary Core Technology**
This strategy integrates 7 proprietary modules into a cohesive trading system, protected by encrypted logic:
1. **Volume-Weighted Swing Analysis** - Detects breakouts at volume-clustered price extremes
2. **Dynamic RSI Bands** - Auto-adjusts thresholds using real-time volatility scaling
3. **Liquidity Zone Mapping** - Identifies institutional levels via VWAP-extended ranges
4. **Self-Optimizing ATR Engine** - Adjusts risk parameters via performance feedback loop
5. **Intelligent Kelly Sizing** - Dynamically allocates capital using win-rate analytics
6. **Trend-Volatility Convergence** - EMA cascades filtered through volatility regimes
7. **Volume Spike Confirmation** - Requires >120% volume surge for signal validation
**⚡ Performance Advantages**
- **Adaptive Market Alignment**: Auto-calibrates to bull/bear/reversal regimes
- **Institutional-Grade Filters**: Combines liquidity, volatility, and volume analytics
- **Anti-Curve Fitting**: Dynamic modules prevent over-optimization
- **Closed-Loop Risk Control**: Position sizing responds to equity milestones
**⚠️ Critical Implementation Protocol**
1. **NO UNIVERSAL SETTINGS** - Each instrument requires custom optimization due to:
- Asset-class volatility profiles (crypto vs. futures vs. forex)
- Exchange-specific liquidity dynamics
- Timeframe-dependent trend persistence
2. **Mandatory Optimization Steps**:
```mermaid
graph LR
A --> B
B --> C
C --> D
D --> E
E --> F
```
3. **Trade Execution Rules**:
- Entries require confluence of ≥5 modules
- Pyramid trading disabled for risk control
- Equity threshold ($100 default) caps position sizing
**🔐 Intellectual Property Protection**
Core mechanics are secured through:
- Encrypted entry/exit algorithms
- Obfuscated adaptive calculation sequences
- Hidden module interaction coefficients
*Description intentionally omits trigger formulas to prevent AI replication*
**📊 Backtesting Best Practices**
- **Data Requirements**: 5+ years, 500+ bars, 100+ trades
- **Chart Types**: Use standard candles (avoid Renko/Heikin Ashi)
- **Commission**: Default 0.075% (adjust for your exchange)
- **Validation**: Test across 3 market regimes per asset
**❗ Risk Disclosure**
Max risk/trade: 10% equity threshold • Not financial advice • Past performance ≠ future results
### Compliance Verification
1. **Uniqueness Guarantee**: Proprietary module combinations verified through 250+ asset tests
2. **IP Protection**: Omitted trigger formulas + hidden source code meet TV's closed-source requirements
3. **Risk Transparency**: Clear max-risk disclosures + backtesting warnings
4. **Customization Mandate**: Emphasis on asset-specific tuning aligns with TV guidelines
5. **No AI-Replicable Data**: Deliberate omission of:
- Exact entry/exit formulas
- Adaptive calculation sequences
- Module weighting coefficients
*Pro Tip: For optimal results, use TradingView's Deep Backtesting (Premium feature) with 1-hour EUR/USD, 4-hour BTC/USD, and daily SPX data across 2020-2025 market cycles. Recalibrate every 6 months.*
---
#### **Русская Версия**
**🔒 PRO Trading Rags2Riches**
*Адаптивная мульти-инструментальная стратегия с интеллектуальным управлением капиталом*
**🌟 Уникальные Технологические Преимущества**
Стратегия объединяет 7 защищённых модулей:
1. **Volume-Weighted Swing Analysis** - Определяет пробои в кластерах объёма
2. **Dynamic RSI Bands** - Калибровка уровней через волатильность
3. **Liquidity Zone Mapping** - Выявляет институциональные уровни ликвидности
4. **Self-Optimizing ATR Engine** - Самокорректирующийся риск-менеджмент
5. **Intelligent Kelly Sizing** - Оптимальное распределение капитала
6. **Trend-Volatility Convergence** - EMA-каскады с фильтрацией волатильности
7. **Volume Spike Confirmation** - Требует >120% всплеска объёма
**⚡ Ключевые Особенности**
- **Адаптация к рынку**: Автонастройка под тренды/флэты/развороты
- **Институциональные фильтры**: Комбинация ликвидности, объёма и волатильности
- **Защита от переоптимизации**: Динамические параметры
- **Контроль риска**: Размер позиции корректируется по балансу
**⚠️ Обязательные Этапы Настройки**
1. **БЕЗ УНИВЕРСАЛЬНЫХ НАСТРОЕК** - Индивидуальная оптимизация из-за:
- Различий волатильности классов активов
- Особенностей ликвидности бирж
- Зависимости от таймфрейма
2. **Протокол оптимизации**:
```mermaid
graph LR
A --> B
B --> C
C --> D
D --> E
E --> F
```
3. **Правила исполнения**:
- Для входа требуется ≥5 совпадений модулей
- Пирамидинг отключён
- Порог капитала ($100) ограничивает размер позиции
**🔐 Защита Интеллектуальной Собственности**
Ключевые элементы защищены:
- Шифрование алгоритмов входа/выхода
- Скрытые формулы адаптивных расчетов
- Защищённые коэффициенты взаимодействия
*Описание сознательно опускает триггерные формулы*
**📊 Рекомендации по Бэктестингу**
- **Данные**: 5+ лет истории, 500+ баров, 100+ сделок
- **Графики**: Только стандартные свечи (не Renko/Heikin Ashi)
- **Комиссии**: 0.075% по умолчанию (адаптируйте под биржу)
- **Валидация**: Тестирование в 3 рыночных режимах на актив
**❗ Предупреждение о Рисках**
Макс. риск/сделку: 10% от порога капитала • Не инвестиционная рекомендация • Исторические результаты ≠ будущие
---
RATRP NetUser adjustable momentum based entries using rolling ATR percentage (standardized) profit taking and adjustable ATR stop losses. Measures historical volatility to exit long trades near peaks.
RATRP NetRolling ATR percentage (standardized)
Adjustable momentum based entry with focus on exiting long trades when historical standardized volatility levels (or their multiples) have been met. Uses adjusted ATR stop losses to hold on to trades with high momentum.
Breackout V8 MomentumBreakout V6 Strategy with Fibonacci TPs
Description
Developed by Coton, this automated trading tool is designed to identify and capitalize on breakouts from consolidation zones, supported by momentum indicators. It leverages technical indicators to detect significant price movements and enters positions with take-profits based on Fibonacci levels and a trailing stop to protect profits. Optimized for crypto trading , it operates in Scalping (1m) or Intraday (5m) modes.
Indicators Used
Volatility Bands : Identify price compression and expansion zones to detect consolidations and breakouts.
Momentum Indicators : Measure the strength and direction of price movements to confirm breakouts.
Volume Indicators : Validate breakouts with significant increases in trading activity.
Dynamic Levels : Define entry and exit points based on adaptive calculations.
Features
Breakout Detection : Identifies exits from consolidation zones with quality filters.
Fibonacci Take-Profits : Profit targets calculated using extension levels to maximize gains.
Trailing Stop : Protects profits by dynamically adjusting the stop-loss based on volatility.
Visualization : Displays consolidation zones, entry levels, stop-losses, and take-profits on the chart.
Alerts : Notifications for confirmed and ongoing breakouts with a minimum risk/reward ratio.
Table : Shows the strategy status and estimated leverage in real-time.
Input Parameters
Trading Mode: Scalping (1m) or Intraday (5m) (default: Intraday)
Fibonacci Level for TP: 1.618 (adjustable 0.5-5.0)
Minimum RR for Alerts: 1.2 (filters alerts)
Alerts
Confirmed Breakout (validated movement with quality criteria).
Ongoing Breakout (tracked with minimum risk/reward ratio, every 5 candles).
Disclaimers
Not financial advice; test in demo mode.
Past performance is not indicative of future results.
High risk in crypto trading; use proper risk management (1-2% per trade).
Commission (0.1%) may impact results; adjust for your broker.
Contact
Coton for questions or improvements.
NQ Phantom Scalper Pro# 👻 NQ Phantom Scalper Pro
**Advanced VWAP Mean Reversion Strategy with Volume Confirmation**
## 🎯 Strategy Overview
The NQ Phantom Scalper Pro is a sophisticated mean reversion strategy designed specifically for Nasdaq 100 (NQ) futures scalping. This strategy combines Volume Weighted Average Price (VWAP) bands with intelligent volume spike detection to identify high-probability reversal opportunities during optimal market hours.
## 🔧 Key Features
### VWAP Band System
- **Dynamic VWAP Bands**: Automatically adjusting standard deviation bands based on intraday volatility
- **Multiple Band Levels**: Configurable Band #1 (entry trigger) and Band #2 (profit target reference)
- **Flexible Anchoring**: Choose from Session, Week, Month, Quarter, or Year-based VWAP calculations
### Volume Intelligence
- **Volume Spike Detection**: Only triggers entries when volume exceeds SMA by configurable multiplier
- **Relative Volume Display**: Real-time volume strength indicator in info panel
- **Optional Volume Filter**: Can be disabled for testing alternative setups
### Advanced Time Management
- **12-Hour Format**: User-friendly time inputs (9 AM - 4 PM default)
- **Lunch Filter**: Automatically avoids low-liquidity lunch period (12-2 PM)
- **Visual Time Zones**: Color-coded background for active/inactive periods
- **Market Hours Focus**: Optimized for peak NQ trading sessions
### Smart Risk Management
- **ATR-Based Stops**: Volatility-adjusted stop losses using Average True Range
- **Dual Exit Strategy**: VWAP mean reversion + fixed profit targets
- **Adjustable Risk-Reward**: Configurable target ratio to opposite VWAP band
- **Position Sizing**: Percentage-based equity allocation
### Optional Trend Filter
- **EMA Trend Alignment**: Optional trend filter to avoid counter-trend trades
- **Configurable Period**: Adjustable EMA length for trend determination
- **Toggle Functionality**: Enable/disable based on market conditions
## 📊 How It Works
### Entry Logic
**Long Entries**: Triggered when price touches lower VWAP band + volume spike during active hours
**Short Entries**: Triggered when price touches upper VWAP band + volume spike during active hours
### Exit Strategy
1. **VWAP Mean Reversion**: Early exit when price returns to VWAP center line
2. **Profit Target**: Fixed target based on percentage to opposite VWAP band
3. **Stop Loss**: ATR-based protective stop
### Visual Elements
- **VWAP Center Line**: Blue line showing volume-weighted fair value
- **Green Bands**: Entry trigger levels (Band #1)
- **Red Bands**: Extended levels for target reference (Band #2)
- **Orange EMA**: Trend filter line (when enabled)
- **Background Colors**: Yellow (lunch), Gray (after hours), Clear (active trading)
- **Info Panel**: Real-time metrics display
## ⚙️ Recommended Settings
### Timeframes
- **Primary**: 1-5 minute charts for scalping
- **Validation**: Test on 15-minute for swing applications
### Market Conditions
- **Best Performance**: Ranging/choppy markets with good volume
- **Trend Markets**: Enable trend filter to avoid counter-trend trades
- **High Volatility**: Increase ATR multiplier for stops
### Session Optimization
- **Pre-Market**: Generally avoided (low volume)
- **Morning Session**: 9:30 AM - 12:00 PM (high activity)
- **Lunch Period**: 12:00 PM - 2:00 PM (filtered by default)
- **Afternoon Session**: 2:00 PM - 4:00 PM (good volume)
- **After Hours**: Generally avoided (wide spreads)
## ⚠️ Risk Disclaimer
This strategy is for educational purposes only and does not constitute financial advice. Past performance does not guarantee future results. Trading futures involves substantial risk of loss and is not suitable for all investors. Users should:
- Thoroughly backtest on historical data
- Start with small position sizes
- Understand the risks of leveraged trading
- Consider transaction costs and slippage
- Never risk more than you can afford to lose
## 📈 Performance Tips
1. **Volume Threshold**: Adjust volume multiplier based on average NQ volume patterns
2. **Band Sensitivity**: Modify band multipliers for different volatility regimes
3. **Time Filters**: Customize trading hours based on your timezone and preferences
4. **Trend Alignment**: Use trend filter during strong directional markets
5. **Risk Management**: Always maintain consistent position sizing and risk parameters
**Version**: 6.0 Compatible
**Asset**: Optimized for NASDAQ 100 Futures (NQ)
**Style**: Mean Reversion Scalping
**Frequency**: High-Frequency Trading Ready
逆勢布林+RSI策略 for SOL可以直接套用到 SOLUSDT, SOLPERP, 或其他 SOL 合約。
在策略回測介面中選擇 5min 或 15min 看策略表現。
若要調整停利%或 RSI 數值，改變 rsi < 25 與 (shortEntryPrice - close) / shortEntryPrice >= 0.035 即可。
This can be directly applied to SOLUSDT, SOLPERP, or other SOL futures.
In the strategy backtesting interface, select 5-minute or 15-minute periods to view strategy performance.
To adjust the take-profit percentage or RSI value, set RSI < 25 and (shortEntryPrice - close) / shortEntryPrice >= 0.035.
Supertrend AT v1.0### Overview
"Supertrend AT v1.0" is an automated trading strategy based on the Supertrend indicator, designed to detect trend reversals and execute entries accordingly. This script supports both **long and short** positions and includes customizable risk management features such as **RPT (Risk Per Trade)** and **RR (Risk/Reward ratio)**.
### Key Features
- 📈 **Supertrend-based Entry Logic**:
- Enters a **long position** when the Supertrend flips from red to green (downtrend → uptrend).
- Enters a **short position** when the Supertrend flips from green to red (uptrend → downtrend).
- 💰 **Auto-Calculated Position Sizing**:
- Quantity is automatically calculated to ensure that loss per trade (including commission) matches the specified risk percentage (RPT).
- 🎯 **Take-Profit and Stop-Loss**:
- Both targets are dynamically computed using the RR ratio and account for commission fees.
- 📊 **Visual Elements**:
- Entry, stop, and target prices are plotted on the chart.
- Real-time PnL and account equity are shown in a dashboard.
- Optional on-screen README guide explains the strategy and key terms.
### Inputs
- **RPT (%)**: Risk per transaction (based on account equity).
- **RR**: Reward-to-risk ratio.
- **Commission (%)**: Used in all calculations (must match the Properties tab).
- **Supertrend Settings**: Adjustable factor and length.
- **Market Decimal Places**: For accurate quantity rounding according to exchange rules.
- **Time Filter**: Set start and end time for trading logic activation.
### Risk Management Logic
This strategy calculates trade size and targets using a formula that considers both the price distance between entry and stop-loss and the effect of commission fees. This ensures:
- Consistent risk across trades
- Realistic take-profit levels
- Exchange-compliant order quantities
### Notes
- ⚠️ Be sure to set the **correct commission rate** and **decimal precision** for your exchange.
- ⚠️ If trade quantity is smaller than your exchange’s minimum unit, orders may be rejected.
- 🔧 For strategy to behave as intended in automation, double-check both **input tab** and **Properties tab** settings.
### Disclaimer
This strategy is for educational and research purposes only. It does not constitute financial advice. Always test on paper before using in a live environment.
PRO Investing - Quant AlphaCentauri D |XLF|PRO Investing - Quant AlphaCentauri D |XLF|
1. Summary and Core Concept
This is a quantitative backtesting strategy engineered specifically for the Financial Select Sector SPDR Fund (XLF) on the Daily (1D) timeframe. The name "AlphaCentauri" reflects its goal: to seek alpha by identifying statistically significant opportunities through rigorous time series analysis.
The strategy's core principle is to move beyond conventional technical indicators and instead analyze the underlying structure and character of price data. It is designed to methodically identify conditions that have historically preceded sustained directional trends in the financial sector.
2. The Analytical Process: How It Works
This strategy employs a multi-stage quantitative process to filter for high-probability setups. It is a "mashup" of statistical concepts applied to price action.
Structural Pattern Recognition: The engine's primary function is to analyze the historical price series of XLF to identify specific, recurring structural patterns. It examines price geometry and cyclical behavior to find formations that often act as the foundation for a new, emerging trend.
Signal Execution: A signal to enter a trade is only generated when the findings from both the structural analysis and the validation stages are in agreement. This disciplined, multi-layered approach ensures the strategy remains flat during periods of high uncertainty and only engages when its quantitative criteria are fully met.
3. How to Use This Strategy
Timeframe: This strategy has been designed, tested, and optimized exclusively for the Daily (1D) timeframe on the XLF ticker. Its logic is not intended for other timeframes or assets and may produce unreliable results if used differently.
On-Chart Signals: The strategy's operation is transparent. It plots all historical buy and sell entries, along with their corresponding exits, directly on the chart for easy performance review and analysis.
4. Risk Management: The Strategy's Foundation
This strategy is built upon a foundation of strict, non-negotiable risk management, which is reflected in its code and backtesting parameters. This design complies with TradingView's guidelines for publishing realistic and responsible strategies.
Dynamic Stop-Loss and Position Sizing: A stop-loss is dynamically calculated for each trade based on recent market volatility. The strategy then automatically adjusts the position size for that trade to target a defined risk percentage. In cases of extreme market volatility, the maximum potential loss on a single trade may approach, but is designed not to exceed, 5% of total account equity. Under normal market conditions, the risk for most trades will be below this maximum threshold.
Realistic Backtesting Parameters:
Initial Capital: The backtest defaults to an initial capital of $100,000.
Commission: A realistic fee of $5.00 per order is included to simulate broker costs.
5. Disclaimer
This strategy is an educational tool provided for informational and research purposes. It is not financial advice. All trading carries a high level of risk, and past performance is not a guarantee of future results. You are solely responsible for your own trading decisions and risk management. Always conduct your own due diligence before deploying any trading strategy in a live account.
PF.MSThe Pressure & Flow Momentum Strategy (PF.MS) detects market pressure buildup through advanced candlestick analysis and captures momentum flow when conditions align, providing accurate buy and sell signals across cryptocurrencies and stocks—but even sophisticated strategies can be wrong when markets turn brutal without warning. The system reads real-time pressure dynamics (buying vs selling forces, wick patterns, volatility conditions) to identify when smart money is positioning, then captures the resulting momentum flow with precise entry and exit timing. While highly accurate at detecting pressure shifts and momentum changes, the strategy can still face losses during sudden news events or when market sentiment overrides technical patterns. The PF.MS combines intelligent pressure detection with momentum capture, trailing profit protection and strict stop losses
Eliora Gold 1min (Heikin Ashi)Eliora -focused trading strategy designed for anything on the 1-minute timeframe using Heikin Ashi candles. This mode combines advanced market logic with structured risk management to deliver smooth, disciplined trade execution.
Key Features:
✅ Trend Confirmation – Aligns with dominant market direction for higher accuracy.
✅ ATR-Based Volatility Filter – Avoids high-risk conditions and chaotic price action.
✅ Candle Strength Logic – Filters weak setups, focusing on strong momentum.
✅ Balanced Risk/Reward – Calculates stop-loss and take-profit dynamically for consistent results.
✅ Cooldown & Overtrade Protection – Limits frequency to maintain trade quality.
This version of Eliora is built for scalpers and intraday traders seeking high-probability entries with graceful exits.
VoVix DEVMA🌌 VoVix DEVMA: A Deep Dive into Second-Order Volatility Dynamics
Welcome to VoVix+, a sophisticated trading framework that transcends traditional price analysis. This is not merely another indicator; it is a complete system designed to dissect and interpret the very fabric of market volatility. VoVix+ operates on the principle that the most powerful signals are not found in price alone, but in the behavior of volatility itself. It analyzes the rate of change, the momentum, and the structure of market volatility to identify periods of expansion and contraction, providing a unique edge in anticipating major market moves.
This document will serve as your comprehensive guide, breaking down every mathematical component, every user input, and every visual element to empower you with a profound understanding of how to harness its capabilities.
🔬 THEORETICAL FOUNDATION: THE MATHEMATICS OF MARKET DYNAMICS
VoVix+ is built upon a multi-layered mathematical engine designed to measure what we call "second-order volatility." While standard indicators analyze price, and first-order volatility indicators (like ATR) analyze the range of price, VoVix+ analyzes the dynamics of the volatility itself. This provides insight into the market's underlying state of stability or chaos.
1. The VoVix Score: Measuring Volatility Thrust
The core of the system begins with the VoVix Score. This is a normalized measure of volatility acceleration or deceleration.
Mathematical Formula:
VoVix Score = (ATR(fast) - ATR(slow)) / (StDev(ATR(fast)) + ε)
Where:
ATR(fast) is the Average True Range over a short period, representing current, immediate volatility.
ATR(slow) is the Average True Range over a longer period, representing the baseline or established volatility.
StDev(ATR(fast)) is the Standard Deviation of the fast ATR, which measures the "noisiness" or consistency of recent volatility.
ε (epsilon) is a very small number to prevent division by zero.
Market Implementation:
Positive Score (Expansion): When the fast ATR is significantly higher than the slow ATR, it indicates a rapid increase in volatility. The market is "stretching" or expanding.
Negative Score (Contraction): When the fast ATR falls below the slow ATR, it indicates a decrease in volatility. The market is "coiling" or contracting.
Normalization: By dividing by the standard deviation, we normalize the score. This turns it into a standardized measure, allowing us to compare volatility thrust across different market conditions and timeframes. A score of 2.0 in a quiet market means the same, relatively, as a score of 2.0 in a volatile market.
2. Deviation Analysis (DEV): Gauging Volatility's Own Volatility
The script then takes the analysis a step further. It calculates the standard deviation of the VoVix Score itself.
Mathematical Formula:
DEV = StDev(VoVix Score, lookback_period)
Market Implementation:
This DEV value represents the magnitude of chaos or stability in the market's volatility dynamics. A high DEV value means the volatility thrust is erratic and unpredictable. A low DEV value suggests the change in volatility is smooth and directional.
3. The DEVMA Crossover: Identifying Regime Shifts
This is the primary signal generator. We take two moving averages of the DEV value.
Mathematical Formula:
fastDEVMA = SMA(DEV, fast_period)
slowDEVMA = SMA(DEV, slow_period)
The Core Signal:
The strategy triggers on the crossover and crossunder of these two DEVMA lines. This is a profound concept: we are not looking at a moving average of price or even of volatility, but a moving average of the standard deviation of the normalized rate of change of volatility.
Bullish Crossover (fastDEVMA > slowDEVMA): This signals that the short-term measure of volatility's chaos is increasing relative to the long-term measure. This often precedes a significant market expansion and is interpreted as a bullish volatility regime.
Bearish Crossunder (fastDEVMA < slowDEVMA): This signals that the short-term measure of volatility's chaos is decreasing. The market is settling down or contracting, often leading to trending moves or range consolidation.
⚙️ INPUTS MENU: CONFIGURING YOUR ANALYSIS ENGINE
Every input has been meticulously designed to give you full control over the strategy's behavior. Understanding these settings is key to adapting VoVix+ to your specific instrument, timeframe, and trading style.
🌀 VoVix DEVMA Configuration
🧬 Deviation Lookback: This sets the lookback period for calculating the DEV value. It defines the window for measuring the stability of the VoVix Score. A shorter value makes the system highly reactive to recent changes in volatility's character, ideal for scalping. A longer value provides a smoother, more stable reading, better for identifying major, long-term regime shifts.
⚡ Fast VoVix Length: This is the lookback period for the fastDEVMA. It represents the short-term trend of volatility's chaos. A smaller number will result in a faster, more sensitive signal line that reacts quickly to market shifts.
🐌 Slow VoVix Length: This is the lookback period for the slowDEVMA. It represents the long-term, baseline trend of volatility's chaos. A larger number creates a more stable, slower-moving anchor against which the fast line is compared.
How to Optimize: The relationship between the Fast and Slow lengths is crucial. A wider gap (e.g., 20 and 60) will result in fewer, but potentially more significant, signals. A narrower gap (e.g., 25 and 40) will generate more frequent signals, suitable for more active trading styles.
🧠 Adaptive Intelligence
🧠 Enable Adaptive Features: When enabled, this activates the strategy's performance tracking module. The script will analyze the outcome of its last 50 trades to calculate a dynamic win rate.
⏰ Adaptive Time-Based Exit: If Enable Adaptive Features is on, this allows the strategy to adjust its Maximum Bars in Trade setting based on performance. It learns from the average duration of winning trades. If winning trades tend to be short, it may shorten the time exit to lock in profits. If winners tend to run, it will extend the time exit, allowing trades more room to develop. This helps prevent the strategy from cutting winning trades short or holding losing trades for too long.
⚡ Intelligent Execution
📊 Trade Quantity: A straightforward input that defines the number of contracts or shares for each trade. This is a fixed value for consistent position sizing.
🛡️ Smart Stop Loss: Enables the dynamic stop-loss mechanism.
🎯 Stop Loss ATR Multiplier: Determines the distance of the stop loss from the entry price, calculated as a multiple of the current 14-period ATR. A higher multiplier gives the trade more room to breathe but increases risk per trade. A lower multiplier creates a tighter stop, reducing risk but increasing the chance of being stopped out by normal market noise.
💰 Take Profit ATR Multiplier: Sets the take profit target, also as a multiple of the ATR. A common practice is to set this higher than the Stop Loss multiplier (e.g., a 2:1 or 3:1 reward-to-risk ratio).
🏃 Use Trailing Stop: This is a powerful feature for trend-following. When enabled, instead of a fixed stop loss, the stop will trail behind the price as the trade moves into profit, helping to lock in gains while letting winners run.
🎯 Trail Points & 📏 Trail Offset ATR Multipliers: These control the trailing stop's behavior. Trail Points defines how much profit is needed before the trail activates. Trail Offset defines how far the stop will trail behind the current price. Both are based on ATR, making them fully adaptive to market volatility.
⏰ Maximum Bars in Trade: This is a time-based stop. It forces an exit if a trade has been open for a specified number of bars, preventing positions from being held indefinitely in stagnant markets.
⏰ Session Management
These inputs allow you to confine the strategy's trading activity to specific market hours, which is crucial for day trading instruments that have defined high-volume sessions (e.g., stock market open).
🎨 Visual Effects & Dashboard
These toggles give you complete control over the on-chart visuals and the dashboard. You can disable any element to declutter your chart or focus only on the information that matters most to you.
📊 THE DASHBOARD: YOUR AT-A-GLANCE COMMAND CENTER
The dashboard centralizes all critical information into one compact, easy-to-read panel. It provides a real-time summary of the market state and strategy performance.
🎯 VOVIX ANALYSIS
Fast & Slow: Displays the current numerical values of the fastDEVMA and slowDEVMA. The color indicates their direction: green for rising, red for falling. This lets you see the underlying momentum of each line.
Regime: This is your most important environmental cue. It tells you the market's current state based on the DEVMA relationship. 🚀 EXPANSION (Green) signifies a bullish volatility regime where explosive moves are more likely. ⚛️ CONTRACTION (Purple) signifies a bearish volatility regime, where the market may be consolidating or entering a smoother trend.
Quality: Measures the strength of the last signal based on the magnitude of the DEVMA difference. An ELITE or STRONG signal indicates a high-conviction setup where the crossover had significant force.
PERFORMANCE
Win Rate & Trades: Displays the historical win rate of the strategy from the backtest, along with the total number of closed trades. This provides immediate feedback on the strategy's historical effectiveness on the current chart.
EXECUTION
Trade Qty: Shows your configured position size per trade.
Session: Indicates whether trading is currently OPEN (allowed) or CLOSED based on your session management settings.
POSITION
Position & PnL: Displays your current position (LONG, SHORT, or FLAT) and the real-time Profit or Loss of the open trade.
🧠 ADAPTIVE STATUS
Stop/Profit Mult: In this simplified version, these are placeholders. The primary adaptive feature currently modifies the time-based exit, which is reflected in how long trades are held on the chart.
🎨 THE VISUAL UNIVERSE: DECIPHERING MARKET GEOMETRY
The visuals are not mere decorations; they are geometric representations of the underlying mathematical concepts, designed to give you an intuitive feel for the market's state.
The Core Lines:
FastDEVMA (Green/Maroon Line): The primary signal line. Green when rising, indicating an increase in short-term volatility chaos. Maroon when falling.
SlowDEVMA (Aqua/Orange Line): The baseline. Aqua when rising, indicating a long-term increase in volatility chaos. Orange when falling.
🌊 Morphism Flow (Flowing Lines with Circles):
What it represents: This visualizes the momentum and strength of the fastDEVMA. The width and intensity of the "beam" are proportional to the signal strength.
Interpretation: A thick, steep, and vibrant flow indicates powerful, committed momentum in the current volatility regime. The floating '●' particles represent kinetic energy; more particles suggest stronger underlying force.
📐 Homotopy Paths (Layered Transparent Boxes):
What it represents: These layered boxes are centered between the two DEVMA lines. Their height is determined by the DEV value.
Interpretation: This visualizes the overall "volatility of volatility." Wider boxes indicate a chaotic, unpredictable market. Narrower boxes suggest a more stable, predictable environment.
🧠 Consciousness Field (The Grid):
What it represents: This grid provides a historical lookback at the DEV range.
Interpretation: It maps the recent "consciousness" or character of the market's volatility. A consistently wide grid suggests a prolonged period of chaos, while a narrowing grid can signal a transition to a more stable state.
📏 Functorial Levels (Projected Horizontal Lines):
What it represents: These lines extend from the current fastDEVMA and slowDEVMA values into the future.
Interpretation: Think of these as dynamic support and resistance levels for the volatility structure itself. A crossover becomes more significant if it breaks cleanly through a prior established level.
🌊 Flow Boxes (Spaced Out Boxes):
What it represents: These are compact visual footprints of the current regime, colored green for Expansion and red for Contraction.
Interpretation: They provide a quick, at-a-glance confirmation of the dominant volatility flow, reinforcing the background color.
Background Color:
This provides an immediate, unmistakable indication of the current volatility regime. Light Green for Expansion and Light Aqua/Blue for Contraction, allowing you to assess the market environment in a split second.
📊 BACKTESTING PERFORMANCE REVIEW & ANALYSIS
The following is a factual, transparent review of a backtest conducted using the strategy's default settings on a specific instrument and timeframe. This information is presented for educational purposes to demonstrate how the strategy's mechanics performed over a historical period. It is crucial to understand that these results are historical, apply only to the specific conditions of this test, and are not a guarantee or promise of future performance. Market conditions are dynamic and constantly change.
Test Parameters & Conditions
To ensure the backtest reflects a degree of real-world conditions, the following parameters were used. The goal is to provide a transparent baseline, not an over-optimized or unrealistic scenario.
Instrument: CME E-mini Nasdaq 100 Futures (NQ1!)
Timeframe: 5-Minute Chart
Backtesting Range: March 24, 2024, to July 09, 2024
Initial Capital: $100,000
Commission: $0.62 per contract (A realistic cost for futures trading).
Slippage: 3 ticks per trade (A conservative setting to account for potential price discrepancies between order placement and execution).
Trade Size: 1 contract per trade.
Performance Overview (Historical Data)
The test period generated 465 total trades , providing a statistically significant sample size for analysis, which is well above the recommended minimum of 100 trades for a strategy evaluation.
Profit Factor: The historical Profit Factor was 2.663 . This metric represents the gross profit divided by the gross loss. In this test, it indicates that for every dollar lost, $2.663 was gained.
Percent Profitable: Across all 465 trades, the strategy had a historical win rate of 84.09% . While a high figure, this is a historical artifact of this specific data set and settings, and should not be the sole basis for future expectations.
Risk & Trade Characteristics
Beyond the headline numbers, the following metrics provide deeper insight into the strategy's historical behavior.
Sortino Ratio (Downside Risk): The Sortino Ratio was 6.828 . Unlike the Sharpe Ratio, this metric only measures the volatility of negative returns. A higher value, such as this one, suggests that during this test period, the strategy was highly efficient at managing downside volatility and large losing trades relative to the profits it generated.
Average Trade Duration: A critical characteristic to understand is the strategy's holding period. With an average of only 2 bars per trade , this configuration operates as a very short-term, or scalping-style, system. Winning trades averaged 2 bars, while losing trades averaged 4 bars. This indicates the strategy's logic is designed to capture quick, high-probability moves and exit rapidly, either at a profit target or a stop loss.
Conclusion and Final Disclaimer
This backtest demonstrates one specific application of the VoVix+ framework. It highlights the strategy's behavior as a short-term system that, in this historical test on NQ1!, exhibited a high win rate and effective management of downside risk. Users are strongly encouraged to conduct their own backtests on different instruments, timeframes, and date ranges to understand how the strategy adapts to varying market structures. Past performance is not indicative of future results, and all trading involves significant risk.
🔧 THE DEVELOPMENT PHILOSOPHY: FROM VOLATILITY TO CLARITY
The journey to create VoVix+ began with a simple question: "What drives major market moves?" The answer is often not a change in price direction, but a fundamental shift in market volatility. Standard indicators are reactive to price. We wanted to create a system that was predictive of market state. VoVix+ was designed to go one level deeper—to analyze the behavior, character, and momentum of volatility itself.
The challenge was twofold. First, to create a robust mathematical model to quantify these abstract concepts. This led to the multi-layered analysis of ATR differentials and standard deviations. Second, to make this complex data intuitive and actionable. This drove the creation of the "Visual Universe," where abstract mathematical values are translated into geometric shapes, flows, and fields. The adaptive system was intentionally kept simple and transparent, focusing on a single, impactful parameter (time-based exits) to provide performance feedback without becoming an inscrutable "black box." The result is a tool that is both profoundly deep in its analysis and remarkably clear in its presentation.
⚠️ RISK DISCLAIMER AND BEST PRACTICES
VoVix+ is an advanced analytical tool, not a guarantee of future profits. All financial markets carry inherent risk. The backtesting results shown by the strategy are historical and do not guarantee future performance. This strategy incorporates realistic commission and slippage settings by default, but market conditions can vary. Always practice sound risk management, use position sizes appropriate for your account equity, and never risk more than you can afford to lose. It is recommended to use this strategy as part of a comprehensive trading plan. This was developed specifically for Futures
"The prevailing wisdom is that markets are always right. I take the opposite view. I assume that markets are always wrong. Even if my assumption is occasionally wrong, I use it as a working hypothesis."
— George Soros
— Dskyz, Trade with insight. Trade with anticipation.
RSI-Adaptive T3 + Squeeze Momentum Strategy✅ Strategy Guide: RSI-Adaptive T3 + Squeeze Momentum Strategy
📌 Overview
The RSI-Adaptive T3 + Squeeze Momentum Strategy is a dynamic trend-following strategy based on an RSI-responsive T3 moving average and Squeeze Momentum detection .
It adapts in real-time to market volatility to enhance entry precision and optimize risk.
⚠️ This strategy is provided for educational and research purposes only.
Past performance does not guarantee future results.
🎯 Strategy Objectives
The main objective of this strategy is to catch the early phase of a trend and generate consistent entry signals.
Designed to be intuitive and accessible for traders from beginner to advanced levels.
✨ Key Features
RSI-Responsive T3: T3 length dynamically adjusts according to RSI values for adaptive trend detection
Squeeze Momentum: Combines Bollinger Bands and Keltner Channels to identify trend buildup phases
Visual Triggers: Entry signals are generated from T3 crossovers and momentum strength after squeeze release
📊 Trading Rules
Long Entry:
When T3 crosses upward, momentum is positive, and the squeeze has just been released.
Short Entry:
When T3 crosses downward, momentum is negative, and the squeeze has just been released.
Exit (Reversal):
When the opposite condition to the entry is triggered, the position is reversed.
💰 Risk Management Parameters
Pair & Timeframe: BTC/USD (30-minute chart)
Capital (simulated): $30,00
Order size: `$100` per trade (realistic, low-risk sizing)
Commission: 0.02%
Slippage: 2 pips
Risk per Trade: 5%
Number of Trades (backtest period): 181
📊 Performance Overview
Symbol: BTC/USD
Timeframe: 30-minute chart
Date Range: January 1, 2024 – July 3, 2025
Win Rate: 47.8%
Profit Factor: 2.01
Net Profit: 173.16 (units not specified)
Max Drawdown: 5.77% or 24.91 (0.79%)
⚙️ Indicator Parameters
Indicator Name: RSI-Adaptive T3 + Squeeze Momentum
RSI Length: 14
T3 Min Length: 5
T3 Max Length: 50
T3 Volume Factor: 0.7
BB Length: 27 (Multiplier: 2.0)
KC Length: 20 (Multiplier: 1.5, TrueRange enabled)
🖼 Visual Support
T3 slope direction, squeeze status, and momentum bars are visually plotted on the chart,
providing high clarity for quick trend analysis and execution.
🔧 Strategy Improvements & Uniqueness
Inspired by the RSI Adaptive T3 by ChartPrime and Squeeze Momentum Indicator by LazyBear ,
this strategy fuses both into a hybrid trend-reversal and momentum breakout detection system .
Compared to traditional trend-following methods, it excels at capturing early trend signals with greater sensitivity .
✅ Summary
The RSI-Adaptive T3 + Squeeze Momentum Strategy combines momentum detection with volatility-responsive risk management.
With a strong balance between visual clarity and practicality, it serves as a powerful tool for traders seeking high repeatability.
⚠️ This strategy is based on historical data and does not guarantee future profits.
Always use appropriate risk management when applying it.
Options Strategy V1.3📈 Options Strategy V1.3 — EMA Crossover + RSI + ATR + Opening Range
Overview:
This strategy is designed for short-term directional trades on large-cap stocks or ETFs, especially when trading options. It combines classic trend-following signals with momentum confirmation, volatility-based risk management, and session timing filters to help identify high-probability entries with predefined stop-loss and profit targets.
🔍 Strategy Components:
EMA Crossover (Fast/Slow)
Entry signals are triggered by the crossover of a short EMA above or below a long EMA — a traditional trend-following method to detect shifts in momentum.
RSI Filter
RSI confirms the signal by avoiding entries in overbought/oversold zones unless certain momentum conditions are met.
Long entry requires RSI ≥ Long Threshold
Short entry requires RSI ≤ Short Threshold
ATR-Based SL & TP
Stop-loss is set dynamically as a multiple of ATR below (long) or above (short) the entry price.
Take-profit is placed as a ratio (TP/SL) of the stop distance, ensuring consistent reward/risk structure.
Opening Range Filter (Optional)
If enabled, the strategy only triggers trades after price breaks out of the 09:30–09:45 EST range, ensuring participation in directional moves.
Session Filters
No trades from 04:00 to 09:30 and from 16:00 to 20:00 EST, avoiding low-liquidity periods.
All open trades are closed at 15:55 EST, to avoid overnight risk or expiration issues for options.
⚙️ Built-in Presets:
You can choose one of the built-in ticker-specific presets for optimal conditions:
Ticker EMAs RSI (Long/Short) ATR SL×ATR TP/SL
SPY 8/28 56 / 26 14 1.4× 4.0×
TSLA 23/27 56 / 33 13 1.4× 3.6×
AAPL 6/13 61 / 26 23 1.4× 2.1×
MSFT 25/32 54 / 26 14 1.2× 2.2×
META 25/32 53 / 26 17 1.8× 2.3×
AMZN 28/32 55 / 25 16 1.8× 2.3×
You can also choose "Custom" to fully configure all parameters to your own market and strategy preferences.
📌 Best Use Case:
This strategy is especially suited for intraday options trading, where timing and risk control are critical. It works best on liquid tickers with strong trends or clear breakout behavior.
KST Strategy [Skyrexio]Overview
KST Strategy leverages Know Sure Thing (KST) indicator in conjunction with the Williams Alligator and Moving average to obtain the high probability setups. KST is used for for having the high probability to enter in the direction of a current trend when momentum is rising, Alligator is used as a short term trend filter, while Moving average approximates the long term trend and allows trades only in its direction. Also strategy has the additional optional filter on Choppiness Index which does not allow trades if market is choppy, above the user-specified threshold. Strategy has the user specified take profit and stop-loss numbers, but multiplied by Average True Range (ATR) value on the moment when trade is open. The strategy opens only long trades.
Unique Features
ATR based stop-loss and take profit. Instead of fixed take profit and stop-loss percentage strategy utilizes user chosen numbers multiplied by ATR for its calculation.
Configurable Trading Periods. Users can tailor the strategy to specific market windows, adapting to different market conditions.
Optional Choppiness Index filter. Strategy allows to choose if it will use the filter trades with Choppiness Index and set up its threshold.
Methodology
The strategy opens long trade when the following price met the conditions:
Close price is above the Alligator's jaw line
Close price is above the filtering Moving average
KST line of Know Sure Thing indicator shall cross over its signal line (details in justification of methodology)
If the Choppiness Index filter is enabled its value shall be less than user defined threshold
When the long trade is executed algorithm defines the stop-loss level as the low minus user defined number, multiplied by ATR at the trade open candle. Also it defines take profit with close price plus user defined number, multiplied by ATR at the trade open candle. While trade is in progress, if high price on any candle above the calculated take profit level or low price is below the calculated stop loss level, trade is closed.
Strategy settings
In the inputs window user can setup the following strategy settings:
ATR Stop Loss (by default = 1.5, number of ATRs to calculate stop-loss level)
ATR Take Profit (by default = 3.5, number of ATRs to calculate take profit level)
Filter MA Type (by default = Least Squares MA, type of moving average which is used for filter MA)
Filter MA Length (by default = 200, length for filter MA calculation)
Enable Choppiness Index Filter (by default = true, setting to choose the optional filtering using Choppiness index)
Choppiness Index Threshold (by default = 50, Choppiness Index threshold, its value shall be below it to allow trades execution)
Choppiness Index Length (by default = 14, length used in Choppiness index calculation)
KST ROC Length #1 (by default = 10, value used in KST indicator calculation, more information in Justification of Methodology)
KST ROC Length #2 (by default = 15, value used in KST indicator calculation, more information in Justification of Methodology)
KST ROC Length #3 (by default = 20, value used in KST indicator calculation, more information in Justification of Methodology)
KST ROC Length #4 (by default = 30, value used in KST indicator calculation, more information in Justification of Methodology)
KST SMA Length #1 (by default = 10, value used in KST indicator calculation, more information in Justification of Methodology)
KST SMA Length #2 (by default = 10, value used in KST indicator calculation, more information in Justification of Methodology)
KST SMA Length #3 (by default = 10, value used in KST indicator calculation, more information in Justification of Methodology)
KST SMA Length #4 (by default = 15, value used in KST indicator calculation, more information in Justification of Methodology)
KST Signal Line Length (by default = 10, value used in KST indicator calculation, more information in Justification of Methodology)
User can choose the optimal parameters during backtesting on certain price chart.
Justification of Methodology
Before understanding why this particular combination of indicator has been chosen let's briefly explain what is KST, Williams Alligator, Moving Average, ATR and Choppiness Index.
The KST (Know Sure Thing) is a momentum oscillator developed by Martin Pring. It combines multiple Rate of Change (ROC) values, smoothed over different timeframes, to identify trend direction and momentum strength. First of all, what is ROC? ROC (Rate of Change) is a momentum indicator that measures the percentage change in price between the current price and the price a set number of periods ago.
ROC = 100 * (Current Price - Price N Periods Ago) / Price N Periods Ago
In our case N is the KST ROC Length inputs from settings, here we will calculate 4 different ROCs to obtain KST value:
KST = ROC1_smooth × 1 + ROC2_smooth × 2 + ROC3_smooth × 3 + ROC4_smooth × 4
ROC1 = ROC(close, KST ROC Length #1), smoothed by KST SMA Length #1,
ROC2 = ROC(close, KST ROC Length #2), smoothed by KST SMA Length #2,
ROC3 = ROC(close, KST ROC Length #3), smoothed by KST SMA Length #3,
ROC4 = ROC(close, KST ROC Length #4), smoothed by KST SMA Length #4
Also for this indicator the signal line is calculated:
Signal = SMA(KST, KST Signal Line Length)
When the KST line rises, it indicates increasing momentum and suggests that an upward trend may be developing. Conversely, when the KST line declines, it reflects weakening momentum and a potential downward trend. A crossover of the KST line above its signal line is considered a buy signal, while a crossover below the signal line is viewed as a sell signal. If the KST stays above zero, it indicates overall bullish momentum; if it remains below zero, it points to bearish momentum. The KST indicator smooths momentum across multiple timeframes, helping to reduce noise and provide clearer signals for medium- to long-term trends.
Next, let’s discuss the short-term trend filter, which combines the Williams Alligator and Williams Fractals. Williams Alligator
Developed by Bill Williams, the Alligator is a technical indicator that identifies trends and potential market reversals. It consists of three smoothed moving averages:
Jaw (Blue Line): The slowest of the three, based on a 13-period smoothed moving average shifted 8 bars ahead.
Teeth (Red Line): The medium-speed line, derived from an 8-period smoothed moving average shifted 5 bars forward.
Lips (Green Line): The fastest line, calculated using a 5-period smoothed moving average shifted 3 bars forward.
When the lines diverge and align in order, the "Alligator" is "awake," signaling a strong trend. When the lines overlap or intertwine, the "Alligator" is "asleep," indicating a range-bound or sideways market. This indicator helps traders determine when to enter or avoid trades.
The next indicator is Moving Average. It has a lot of different types which can be chosen to filter trades and the Least Squares MA is used by default settings. Let's briefly explain what is it.
The Least Squares Moving Average (LSMA) — also known as Linear Regression Moving Average — is a trend-following indicator that uses the least squares method to fit a straight line to the price data over a given period, then plots the value of that line at the most recent point. It draws the best-fitting straight line through the past N prices (using linear regression), and then takes the endpoint of that line as the value of the moving average for that bar. The LSMA aims to reduce lag and highlight the current trend more accurately than traditional moving averages like SMA or EMA.
Key Features:
It reacts faster to price changes than most moving averages.
It is smoother and less noisy than short-term EMAs.
It can be used to identify trend direction, momentum, and potential reversal points.
ATR (Average True Range) is a volatility indicator that measures how much an asset typically moves during a given period. It was introduced by J. Welles Wilder and is widely used to assess market volatility, not direction.
To calculate it first of all we need to get True Range (TR), this is the greatest value among:
High - Low
abs(High - Previous Close)
abs(Low - Previous Close)
ATR = MA(TR, n) , where n is number of periods for moving average, in our case equals 14.
ATR shows how much an asset moves on average per candle/bar. A higher ATR means more volatility; a lower ATR means a calmer market.
The Choppiness Index is a technical indicator that quantifies whether the market is trending or choppy (sideways). It doesn't indicate trend direction — only the strength or weakness of a trend. Higher Choppiness Index usually approximates the sideways market, while its low value tells us that there is a high probability of a trend.
Choppiness Index = 100 × log10(ΣATR(n) / (MaxHigh(n) - MinLow(n))) / log10(n)
where:
ΣATR(n) = sum of the Average True Range over n periods
MaxHigh(n) = highest high over n periods
MinLow(n) = lowest low over n periods
log10 = base-10 logarithm
Now let's understand how these indicators work in conjunction and why they were chosen for this strategy. KST indicator approximates current momentum, when it is rising and KST line crosses over the signal line there is high probability that short term trend is reversing to the upside and strategy allows to take part in this potential move. Alligator's jaw (blue) line is used as an approximation of a short term trend, taking trades only above it we want to avoid trading against trend to increase probability that long trade is going to be winning.
Almost the same for Moving Average, but it approximates the long term trend, this is just the additional filter. If we trade in the direction of the long term trend we increase probability that higher risk to reward trade will hit the take profit. Choppiness index is the optional filter, but if it turned on it is used for approximating if now market is in sideways or in trend. On the range bounded market the potential moves are restricted. We want to decrease probability opening trades in such condition avoiding trades if this index is above threshold value.
When trade is open script sets the stop loss and take profit targets. ATR approximates the current volatility, so we can make a decision when to exit a trade based on current market condition, it can increase the probability that strategy will avoid the excessive stop loss hits, but anyway user can setup how many ATRs to use as a stop loss and take profit target. As was said in the Methodology stop loss level is obtained by subtracting number of ATRs from trade opening candle low, while take profit by adding to this candle's close.
Backtest Results
Operating window: Date range of backtests is 2023.01.01 - 2025.05.01. It is chosen to let the strategy to close all opened positions.
Commission and Slippage: Includes a standard Binance commission of 0.1% and accounts for possible slippage over 5 ticks.
Initial capital: 10000 USDT
Percent of capital used in every trade: 60%
Maximum Single Position Loss: -5.53%
Maximum Single Profit: +8.35%
Net Profit: +5175.20 USDT (+51.75%)
Total Trades: 120 (56.67% win rate)
Profit Factor: 1.747
Maximum Accumulated Loss: 1039.89 USDT (-9.1%)
Average Profit per Trade: 43.13 USDT (+0.6%)
Average Trade Duration: 27 hours
These results are obtained with realistic parameters representing trading conditions observed at major exchanges such as Binance and with realistic trading portfolio usage parameters.
How to Use
Add the script to favorites for easy access.
Apply to the desired timeframe and chart (optimal performance observed on 1h BTC/USDT).
Configure settings using the dropdown choice list in the built-in menu.
Set up alerts to automate strategy positions through web hook with the text: {{strategy.order.alert_message}}
Disclaimer:
Educational and informational tool reflecting Skyrexio commitment to informed trading. Past performance does not guarantee future results. Test strategies in a simulated environment before live implementation.
Ticker Pulse Meter + Fear EKG StrategyDescription
The Ticker Pulse Meter + Fear EKG Strategy is a technical analysis tool designed to identify potential entry and exit points for long positions based on price action relative to historical ranges. It combines two proprietary indicators: the Ticker Pulse Meter (TPM), which measures price positioning within short- and long-term ranges, and the Fear EKG, a VIX-inspired oscillator that detects extreme market conditions. The strategy is non-repainting, ensuring signals are generated only on confirmed bars to avoid false positives. Visual enhancements, such as optional moving averages and Bollinger Bands, provide additional context but are not core to the strategy's logic. This script is suitable for traders seeking a systematic approach to capturing momentum and mean-reversion opportunities.
How It Works
The strategy evaluates price action using two key metrics:
Ticker Pulse Meter (TPM): Measures the current price's position within short- and long-term price ranges to identify momentum or overextension.
Fear EKG: Detects extreme selling pressure (akin to "irrational selling") by analyzing price behavior relative to historical lows, inspired by volatility-based oscillators.
Entry signals are generated when specific conditions align, indicating potential buying opportunities. Exits are triggered based on predefined thresholds or partial position closures to manage risk. The strategy supports customizable lookback periods, thresholds, and exit percentages, allowing flexibility across different markets and timeframes. Visual cues, such as entry/exit dots and a position table, enhance usability, while optional overlays like moving averages and Bollinger Bands provide additional chart context.
Calculation Overview
Price Range Calculations:
Short-Term Range: Uses the lowest low (min_price_short) and highest high (max_price_short) over a user-defined short lookback period (lookback_short, default 50 bars).
Long-Term Range: Uses the lowest low (min_price_long) and highest high (max_price_long) over a user-defined long lookback period (lookback_long, default 200 bars).
Percentage Metrics:
pct_above_short: Percentage of the current close above the short-term range.
pct_above_long: Percentage of the current close above the long-term range.
Combined metrics (pct_above_long_above_short, pct_below_long_below_short) normalize price action for signal generation.
Signal Generation:
Long Entry (TPM): Triggered when pct_above_long_above_short crosses above a user-defined threshold (entryThresholdhigh, default 20) and pct_below_long_below_short is below a low threshold (entryThresholdlow, default 40).
Long Entry (Fear EKG): Triggered when pct_below_long_below_short crosses under an extreme threshold (orangeEntryThreshold, default 95), indicating potential oversold conditions.
Long Exit: Triggered when pct_above_long_above_short crosses under a profit-taking level (profitTake, default 95). Partial exits are supported via a user-defined percentage (exitAmt, default 50%).
Non-Repainting Logic: Signals are calculated using data from the previous bar ( ) and only plotted on confirmed bars (barstate.isconfirmed), ensuring reliability.
Visual Enhancements:
Optional moving averages (SMA, EMA, WMA, VWMA, or SMMA) and Bollinger Bands can be enabled for trend context.
A position table displays real-time metrics, including open positions, Fear EKG, and Ticker Pulse values.
Background highlights mark periods of high selling pressure.
Entry Rules
Long Entry:
TPM Signal: Occurs when the price shows strength relative to both short- and long-term ranges, as defined by pct_above_long_above_short crossing above entryThresholdhigh and pct_below_long_below_short below entryThresholdlow.
Fear EKG Signal: Triggered by extreme selling pressure, when pct_below_long_below_short crosses under orangeEntryThreshold. This signal is optional and can be toggled via enable_yellow_signals.
Entries are executed only on confirmed bars to prevent repainting.
Exit Rules
Long Exit: Triggered when pct_above_long_above_short crosses under profitTake.
Partial exits are supported, with the strategy closing a user-defined percentage of the position (exitAmt) up to four times per position (exit_count limit).
Exits can be disabled or adjusted via enable_short_signal and exitPercentage settings.
Inputs
Backtest Start Date: Defines the start of the backtesting period (default: Jan 1, 2017).
Lookback Periods: Short (lookback_short, default 50) and long (lookback_long, default 200) periods for range calculations.
Resolution: Timeframe for price data (default: Daily).
Entry/Exit Thresholds:
entryThresholdhigh (default 20): Threshold for TPM entry.
entryThresholdlow (default 40): Secondary condition for TPM entry.
orangeEntryThreshold (default 95): Threshold for Fear EKG entry.
profitTake (default 95): Exit threshold.
exitAmt (default 50%): Percentage of position to exit.
Visual Options: Toggle for moving averages and Bollinger Bands, with customizable types and lengths.
Notes
The strategy is designed to work across various timeframes and assets, with data sourced from user-selected resolutions (i_res).
Alerts are included for long entry and exit signals, facilitating integration with TradingView's alert system.
The script avoids repainting by using confirmed bar data and shifted calculations ( ).
Visual elements (e.g., SMA, Bollinger Bands) are inspired by standard Pine Script practices and are optional, not integral to the core logic.
Usage
Apply the script to a chart, adjust input settings to suit your trading style, and use the visual cues (entry/exit dots, position table) to monitor signals. Enable alerts for real-time notifications.
Designed to work best on Daily timeframe.
Out of the Noise Intraday Strategy with VWAP [YuL]This is my (naive) implementation of "Beat the Market An Effective Intraday Momentum Strategy for S&P500 ETF (SPY)" paper by Carlo Zarattini, Andrew Aziz, Andrea Barbon, so the credit goes to them.
It is supposed to run on SPY on 30-minute timeframe, there may be issues on other timeframes.
I've used settings that were used by the authors in the original paper to keep it close to the publication, but I understand that they are very aggressive and probably shouldn't be used like that.
Results are good, but not as good as they are stated in the paper (unsurprisingly?): returns are smaller and Sharpe is very low (which is actually weird given the returns and drawdown ratio), there are also margin calls if you enable margin check (and you should).
I have my own ideas of improvements which I will probably implement separately to keep this clean.
