Bitwardex AI AlgoBitwardex AI Algo — Next-Generation Adaptive Market Intelligence
Bitwardex AI Algo is a multi-layered algorithmic trading framework designed to dynamically adapt to changing market structures.
Built upon a synthesis of cluster-based machine learning, stochastic filtering, volatility normalization, and adaptive risk modulation, this strategy operates as a self-adjusting analytical engine for modern traders.
🧠 Core Concept
At the heart of the system lies Adaptive Market Clustering methodology — a hybrid analytical architecture that combines pseudo-K-Means clustering, sigmoid feature normalization, and Gaussian price smoothing.
This unique framework isolates statistically stable price formations in real time, effectively filtering market noise and transient anomalies.
Each market input — price, volatility, momentum, or CCI deviation — is transformed into a unified metric space, where the algorithm identifies equilibrium clusters representing the probabilistic transition between impulse, consolidation, and reversal phases.
The result is a dynamic analytical structure capable of interpreting short-term volatility as contextual, not random.
⚙️ System Architecture
Bitwardex AI Algo operates through several integrated analytical layers:
1. Trend Intelligence Layer
Performs adaptive trend filtering using a combination of multi-timeframe Gaussian smoothing and ATR gradient mapping.
It adjusts sensitivity dynamically, ensuring smooth yet responsive trend detection without excessive lag.
2. Consolidation Risk Control
Evaluates price compression and volatility contraction zones, reducing trade exposure during low-energy phases.
This intelligent modulation maintains strategic consistency by aligning position sizing with structural volatility.
3. Cluster-Based Signal Engine
Applies a custom cluster-learning mechanism that groups market behavior into statistically meaningful formations.
Signals are generated only when probabilistic thresholds align with directional confirmation — significantly minimizing false breakouts and noise.
4. Adaptive Risk Framework
Implements real-time position sizing and leverage calibration.
Includes advanced Martingale control and position cap management, allowing the system to withstand high-volatility environments and event-driven distortions.
5. Multi-Target TP/SL & Breakeven System
Profit targets and stops are dynamically calculated via adaptive ATR- and ROI-based models.
The strategy supports up to four take-profit levels, a flexible trailing stop, and automatic breakeven logic — all clearly visualized on the chart.
6. Visual & Alert Engine
Comprehensive graphical interface displaying trend zones, TP/SL levels, trailing positions, and market phase indicators.
Customizable alerts allow seamless integration into both manual and automated workflows.
📊 Analytical Methods
Gaussian Smoothing Filter – minimizes short-term noise while preserving momentum integrity.
Sigmoid Normalization – aligns nonlinear market features into a comparable probability scale.
K-Means-like Clustering – identifies statistically consistent states of market equilibrium.
ATR-Based Sensitivity Modulation – scales responsiveness according to volatility intensity.
Trend Slope Reinforcement – dynamically adjusts the directional bias based on CCI correlation and mean deviation metrics.
🔍 Use Cases
Intraday mode: optimized for high-frequency environments with adaptive reaction time.
Swing mode: automatically deepens its analytical horizon on higher timeframes.
Analytical mode: may function purely as a market structure diagnostic tool, offering probabilistic context for manual traders.
💡 Visual & Functional Features
Dynamic trend color coding (bullish, bearish, neutral).
Auto-generated support and resistance zones.
Full visualization of entry, exit, TP/SL, trailing, and breakeven levels.
Informative trade panels and label-based data overlays.
User-configurable visual interface for all display elements.
⚠️ Disclaimer
Bitwardex AI Algo does not predict future prices or guarantee profits.
It is a probabilistic analytical framework that assists traders in filtering market noise and identifying contextually significant price behavior.
All performance results are historical simulations and may differ in live trading.
Always test and calibrate parameters according to your personal strategy and risk tolerance.
🇷🇺 Bitwardex AI Algo — интеллектуальная адаптивная стратегия нового поколения
Bitwardex AI Algo — это многоуровневая торговая система, способная адаптироваться к изменению рыночных структур и режимов волатильности.
Она объединяет в себе принципы кластерного машинного обучения, стохастической фильтрации, динамической нормализации волатильности и адаптивного управления рисками, формируя саморегулирующийся аналитический контур.
🧠 Концепция работы
В основе лежит методология Adaptive Market Clustering — гибридная архитектура, сочетающая псевдо-кластеризацию K-Means, сигмоидную нормализацию признаков и гауссово сглаживание ценовых траекторий.
Эта технология позволяет в реальном времени выделять статистически устойчивые ценовые паттерны, отсекая шум и кратковременные всплески.
Каждый поток данных (цена, ATR-волатильность, импульс, CCI-девиация и др.) преобразуется в унифицированное пространство признаков, где алгоритм выявляет зоны равновесия рынка, интерпретируя их как вероятностные переходы между импульсом, консолидацией и разворотом.
⚙️ Архитектура стратегии
1. Trend Intelligence Layer
Адаптивный тренд-фильтр с мультитаймфреймной логикой и гауссовым сглаживанием.
Он динамически изменяет чувствительность в зависимости от силы тренда и рыночного шума.
2. Consolidation Risk Control
Анализирует периоды сжатия диапазонов и снижает торговую активность во время консолидации.
Таким образом, стратегия регулирует риск и размер позиции пропорционально рыночной динамике.
3. Cluster-Based Signal Engine
Использует кластерное самообучение для выделения устойчивых рыночных состояний и формирования сигналов только при совпадении вероятностных и трендовых факторов.
4. Adaptive Risk Framework
Модуль управления капиталом, использующий динамическое перераспределение объёма, гибкое плечо и ограничения на максимальный риск.
Поддерживает модели Мартингейла и контроль агрессивности входов.
5. TP/SL & Breakeven System
Формирует многоуровневые цели прибыли (до 4 уровней TP), трейлинг-стоп, безубыточную зону и визуальное отображение всех параметров на графике.
6. Visual Analytics & Alert Engine
Отрисовывает все ключевые элементы: зоны тренда, TP/SL, trailing-уровни, зоны консолидации, а также уведомления о сигналах.
Поддерживает гибкую настройку интерфейса и формата уведомлений.
📊 Применяемые методы
Гауссово сглаживание для подавления шумов при сохранении инерции тренда.
Сигмоидная нормализация для унификации нелинейных параметров.
Псевдо-кластеризация K-Means для выделения равновесных рыночных состояний.
ATR-адаптация чувствительности для масштабирования под текущую волатильность.
Реинфорсмент угла тренда на основе CCI-корреляций и отклонений цены.
🔍 Режимы работы
Интрадей — для краткосрочной динамики и высокой реактивности.
Свинг-режим — оптимизация под среднесрочные сценарии.
Аналитический — используется как диагностический инструмент для оценки структуры рынка.
💡 Особенности визуализации
Цветовая идентификация фаз (тренд/флэт/разворот).
Автоматическая отрисовка уровней поддержки и сопротивления.
Подробное отображение TP/SL, трейлинг-зон и входов.
Информационные таблицы и визуальные метки позиций.
Полная кастомизация всех визуальных элементов под пользователя.
⚠️ Предупреждение
Bitwardex AI Algo не является инструментом прогнозирования и не гарантирует прибыль.
Это статистическая адаптивная система, направленная на фильтрацию рыночного шума и оценку вероятностных сценариев движения цены.
Перед использованием рекомендуется провести собственное тестирование и оптимизацию параметров под индивидуальный стиль торговли.
Statistics
Evergreen Solutions - ONEOverview
ONE is an adaptive strategy designed for all markets that captures short-term momentum in high-volatility conditions. It integrates RSI, volume analysis, chop filters, standard moving averages, and custom moving averages to identify when markets shift from range-based choppiness to high-probability opportunities. The system is structured to be reactive, focusing on trades with strong volatility expansion and statistically favorable win potential.
How to Use It
- Equities: A reliable options or swing-trading companion for large-cap tickers.
- Futures: Refined for intraday structure on index products (NQ, ES, RTY, GC, CL, YM).
- Forex: Designed to reduce false starts on illiquid currency pairs.
- Digital Assets: Tailored for the volatility of 24/7 markets while maintaining composure in high volatility.
When ONE executes a trade, a SL and TP plot is generated. These plots serve as delineated boundaries for the trade. Simply place your SL and TP, and walk away.
Modes of Operation
ONE Mode – A single-entry, single-exit design for simplicity.
Breakeven Mode – Shifts the stop to entry once a defined profit threshold is met, protecting capital in uncertain markets.
Multi Mode – Scales entries and exits to capture extended runs and adapt to different volatility regimes.
Conceptual Logic
Trend Detection: Uses custom and standard moving averages to define short-term directional bias.
Volatility Filter: Custom chop filters suppress trades during ranging price action.
Momentum Signal: RSI combined with volume analysis highlights moments of rapid volatility expansion and strong price acceleration.
Execution Rule: All trades trigger only on bar open; no repainting or lookahead data is used.
What Makes ONE Different
ONE’s originality lies in its adaptive trade-management modes and the integration of multiple filters (RSI + volume + choppiness + adaptive MAs) into a single framework. This reduces conflicting signals, emphasizes risk control, and keeps decision-making transparent for the trader.
- Consistency: ONE adapts seamlessly to all markets. It does not rely on hidden market structure; its design is universal.
- Simplicity: No learning curve. ONE was built so any trader — beginner or advanced — can trade immediately.
- Risk: Every mode respects capital preservation. Decisions are made to avoid catastrophic losses.
- Transparency: New positions enter only on bar open, with no hidden repainting or misleading lookaheads.
- Structure: ONE reflects the discipline of professional trading: structured, rules-based, and repeatable under changing conditions.
Backtest Defaults
Symbol: CME_MINI:NQ1!
Backtest range: Oct 31, 2024 – Oct 6, 2025
Account size: $10,000
Total trades: 859
Win rate: 62%
Total P&L: $113,160
Profit factor: 1.32
Sharpe ratio: 0.78
Sortino ratio: 5.78
Limitations
ONE does not guarantee profits. Effectiveness depends on liquidity, volatility, and market conditions. Past results do not imply future returns.
Galac III SOXL - Galac — SOXL strategy (long only). Purpose: swing trading leveraged semiconductor ETF (SOXL) with volatility‑aware position sizing. Core components: adaptive EMAs as trend filter, relative volume confirmation, volatility-adjusted position sizing and dynamic take-profit / stop-loss management. Default parameters: EMA_short=20, EMA_long=50, vol_rel_period=20, default stop ≈6% per trade. Backtests run with commissions=0.05% and slippage=0.2%. Backtest sample and timeframe are included in the attached results. Not intended for scalping. Risks and limitations: performs best in trending environments; may underperform in choppy, low-volume conditions. Past performance ≠ future results.
Squeeze Backtest by Shaqi v2.0Script to backtest price squeeze's. Works on long and short directions
AstraAlgo BacktesterOVERVIEW
The AstraAlgo Backtester allows traders to simulate and evaluate trading strategies directly on TradingView. By simulating trades across different timeframes and markets, it provides valuable insights into win rates, drawdowns, and overall strategy effectiveness.
SIGNAL MODES
Signal Modes generate proprietary trade signals based on live price data. Users can choose between Off, Basic, Advanced, or Custom modes to evaluate strategies under different conditions and refine their trading approach.
ADJUSTABLE BACKTESTING
Parameters for historical simulations can be customized to test different market conditions and trading scenarios. This allows traders to measure strategy performance, including win rate, profit/loss, and risk/reward ratios, helping refine and optimize strategies before live execution.
BAR COLORING
Bar Coloring highlights bullish and bearish bars on historical charts, allowing traders to visually assess trend direction and trade outcomes during backtesting. This makes it easier to analyze momentum and strategy effectiveness at a glance.
ASTRA CLOUD
Astra Cloud overlays dynamic support and resistance levels on live price data. These zones adapt automatically to past market movements, helping traders identify areas where trades would have reacted, aiding strategy evaluation and optimization.
Hosoda’s CloudsMany investors aim to develop trading systems with a high win rate, mistakenly associating it with substantial profits. In reality, high returns are typically achieved through greater exposure to market trends, which inevitably lowers the win rate due to increased risk and more volatile conditions.
The system I present, called “Hosoda’s Clouds” in honor of Goichi Hosoda , the creator of the Ichimoku Kinko Hyo indicator, is likely one of the first profitable systems many traders will encounter. Designed to capture trends, it performs best in markets with clear directional movements and is less suitable for range-bound markets like Forex, which often exhibit lateral price action.
This system is not recommended for low timeframes, such as minute charts, due to the random and emotionally driven nature of price movements in those periods. For a deeper exploration of this topic, I recommend reading my article “Timeframe is Everything”, which discusses the critical importance of selecting the appropriate timeframe.
I suggest testing and applying the “Hosoda’s Clouds” strategy on assets with a strong trending nature and a proven track record of performance. Ideal markets include Tesla (1-hour, 4-hour, and daily), BTC/USDT (daily), SPY (daily), and XAU/USD (daily), as these have consistently shown clear directional trends over time.
Commissions and Configuration
Commissions can be adjusted in the system’s settings to suit individual needs. For evaluating the effectiveness of “Hosoda’s Clouds,” I’ve used a standard commission of $1 per order as a baseline, though this can be modified in the code to accommodate different brokers or preferences.
The margin per trade is set to $1,000 by default, but users are encouraged to experiment with different margin settings in the configuration to match their trading style.
Rules of the “Hosoda’s Clouds” System (Bullish Strategy)
This strategy is designed to capture trending movements in bullish markets using the Ichimoku Kinko Hyo indicator. The rules are as follows:
Long Entry: A long position is triggered when the Tenkan-sen crosses above the Kijun-sen below the Ichimoku cloud, identifying potential reversals or bounces in a bearish context.
Stop Loss (SL): Placed at the low of the candle 12 bars prior to the entry candle. This setting has proven optimal in my tests, but it can be adjusted in the code based on risk tolerance.
Take Profit (TP): The position is closed when the Tenkan-sen crosses below the bottom of the Ichimoku cloud (the minimum of Senkou Span A and Senkou Span B).
Notes on the Code
margin_long=0: Ideal for strategies requiring a fixed position size, particularly useful for manual entries or testing with a constant capital allocation.
margin_long=100: Recommended for high-frequency systems where positions are closed quickly, simulating gradual growth based on realized profits and reflecting real-world broker constraints.
System Performance
The following performance metrics account for $1 per order commissions and were tested on the specified assets and timeframes:
Tesla (H1)
Trades: 148
Win Rate: 29.05%
Period: Jan 2, 2014 – Jan 6, 2020 (+172%)
Simple Annual Growth Rate: +34.3%
Trades: 130
Win Rate: 30.77%
Period: Jan 2, 2020 – Sep 24, 2025 (+858.90%)
Simple Annual Growth Rate: +150.7%
Tesla (H4)
Trades: 102
Win Rate: 32.35%
Period: Jun 29, 2010 – Sep 24, 2025 (+11,356.36%)
Simple Annual Growth Rate: +758.5%
Tesla (Daily)
Trades: 56
Win Rate: 35.71%
Period: Jun 29, 2010 – Sep 24, 2025 (+3,166.64%)
Simple Annual Growth Rate: +211.5%
BTC/USDT (Daily)
Trades: 44
Win Rate: 31.82%
Period: Sep 30, 2017 – Sep 24, 2025 (+2,592.23%)
Simple Annual Growth Rate: +324.8%
SPY (Daily)
Trades: 81
Win Rate: 37.04%
Period: Jan 23, 1993 – Sep 24, 2025 (+476.90%)
Simple Annual Growth Rate: +14.3%
XAU/USD (Daily)
Trades: 216
Win Rate: 32.87%
Period: Jan 6, 1833 – Sep 24, 2025 (+5,241.73%)
Simple Annual Growth Rate: +27.1%
SPX (Daily)
Trades: 217
Win Rate: 38.25%
Period: Feb 1, 1871 – Sep 24, 2025 (+16,791.02%)
Simple Annual Growth Rate: +108.1%
Conclusion
With the “ Hosoda’s Clouds ” strategy, I aim to showcase the potential of technical analysis to generate consistent profits in trending markets, challenging recent doubts about its effectiveness. My goal is for this system to serve as both a practical tool for traders and a source of inspiration for the trading community I deeply respect. I hope it encourages the creation of new strategies, fosters creativity in technical analysis, and empowers traders to approach the markets with confidence and discipline.
AI - Gaussian Channel Strategy AI – Gaussian Channel Strategy is a long-only swing trading strategy designed for Bitcoin and other assets on daily charts. It combines an adaptive Gaussian Channel with Supertrend and Stochastic RSI filters to identify potential bullish breakouts or pullback entries. The channel defines trend direction and volatility, while the Stochastic RSI provides momentum confirmation. Positions are opened only when the price closes above the channel’s upper band under favorable momentum conditions, and are closed when the price crosses back below the band.
This script is intended for educational and research purposes. Parameters such as poles, period length, ATR factor, and RSI settings can be adjusted to fit different markets and timeframes.
Disclaimer: This script does not guarantee profits and should not be considered financial advice. Past performance is not indicative of future results. Trading involves risk, and you are solely responsible for your own decisions and outcomes.
Lead Levels TP/SL v1.3 (close-only entries)Lead Levels — close-only signals, clean execution
Notice: Designed for BTC 15-minute charts only.
What it shows
Four reliability tiers: L1, L2, L3, L4.
A black “DON’T BET” marker for extreme conditions you should skip.
All triangles print only on bar close to avoid repaint.
How to read
▲ BUY L1–L4: higher level → stronger confidence.
▼ SELL L1–L4: higher level → stronger confidence.
DON’T BET (black): stand aside. No trade.
How to trade it
When a triangle prints, run a 1:1 target/stop:
Long: TP +1%, SL −1%.
Short: TP −1%, SL +1%.
Focus on normal conditions. Skip when the black marker appears.
One entry per signal. Keep sizing consistent.
Why traders like it
Close-only printing keeps charts honest.
Simple 1:1 playbook. No guesswork.
Median + Tendência + ATR (Yehuda Nahmias)📊 Median + Trend + ATR (By Yehuda Nahmias)
🚀 The indicator that combines Simplicity, Accuracy, and Risk Management
This script brings together three key pillars of professional trading:
✅ Dynamic Median → captures price midpoints and highlights reversal and breakout zones.
✅ Trend Filter (EMA) → ensures signals are aligned with the main market direction.
✅ Smart ADX + ATR → confirm trend strength and automatically calculate Stop Loss and Take Profit based on volatility.
🔔 How it works:
Buy/Sell Arrows: automatically appear when price crosses the median under valid trend and strength conditions (ADX).
Automatic Stops and Targets: SL and TP levels are plotted using ATR, ready for effective risk management.
3 Signal Modes:
🛡️ Conservative → fewer trades, stronger filtering.
⚖️ Standard → balance between frequency and accuracy.
⚡ Aggressive → more trades, captures shorter moves.
💡 Key Benefits:
Clear visuals: colored candles + BUY/SELL arrows.
Built-in risk management: position size is calculated based on % of equity.
Flexible: works on any asset (Forex, Crypto, Indices, Stocks).
🔑 Private access only.
If you’d like to use this strategy on your charts, contact me via my TradingView profile.
👉 Turn your analysis into objective signals and gain more confidence in your entries and exits!
KCandle Strategy 1.0# KCandle Strategy 1.0 - Trading Strategy Description
## Overview
The **KCandle Strategy** is an advanced Pine Script trading system based on bullish and bearish engulfing candlestick patterns, enhanced with sophisticated risk management and position optimization features.
## Core Logic
### Entry Signal Generation
- **Pattern Recognition**: Detects bullish and bearish engulfing candlestick formations
- **EMA Filter**: Uses a customizable EMA (default 25) to filter trades in the direction of the trend
- **Entry Levels**:
- **Long entries** at 25% of the candlestick range from the low
- **Short entries** at 75% of the candlestick range from the low
- **Signal Validation**: Orange candlesticks indicate valid setup conditions
### Risk Management System
#### 1. **Stop Loss & Take Profit**
- Configurable stop loss in pips
- Risk-reward ratio setting (default 2:1)
- Visual representation with colored lines and labels
#### 2. **Break-Even Management**
- Automatically moves stop loss to break-even when specified R:R is reached
- Customizable break-even offset for added protection
- Prevents losing trades after reaching profitability
#### 3. **Trailing Stop System**
- **Activation Trigger**: Activates when position reaches specified R:R level
- **Distance Control**: Maintains trailing stop at defined distance from entry
- **Step Management**: Moves stop loss forward in incremental R steps
- **Dynamic Protection**: Locks in profits while allowing for continued upside
### Advanced Features
#### Position Management
- **Pyramiding Support**: Optional multiple position entries with size reduction
- **Order Expiration**: Pending orders automatically cancel after specified bars
- **Position Sizing**: Percentage-based allocation with pyramid level adjustments
#### Visual Interface
- **Real-time Monitoring**: Comprehensive information panel with all strategy metrics
- **Historical Tracking**: Visual representation of past trades and levels
- **Color-coded Indicators**: Different colors for break-even, trailing, and standard stops
- **Debug Options**: Optional labels for troubleshooting and optimization
## Key Parameters
### Basic Settings
- **EMA Length**: Trend filter period
- **Stop Loss**: Risk per trade in pips
- **Risk/Reward**: Target profit ratio
- **Order Validity**: Duration of pending orders
### Risk Management
- **Break-Even R:R**: Profit level to trigger break-even
- **Trailing Activation**: R:R level to start trailing
- **Trailing Distance**: Stop distance from entry when trailing
- **Trailing Step**: Increment for stop loss advancement
## Strategy Benefits
1. **Objective Entry Signals**: Based on proven candlestick patterns
2. **Trend Alignment**: EMA filter ensures trades align with market direction
3. **Robust Risk Control**: Multiple layers of protection (SL, BE, Trailing)
4. **Profit Optimization**: Trailing stops maximize winning trade potential
5. **Flexibility**: Extensive customization options for different market conditions
6. **Visual Clarity**: Complete visual feedback for trade management
## Ideal Use Cases
- **Swing Trading**: Medium-term positions with trend-following approach
- **Breakout Trading**: Capturing momentum from engulfing patterns
- **Risk-Conscious Trading**: Suitable for traders prioritizing capital preservation
- **Multi-Timeframe**: Adaptable to various timeframes and instruments
---
*The KCandle Strategy combines traditional technical analysis with modern risk management techniques, providing traders with a comprehensive tool for systematic market participation.*
IB BreakoutIt marks the IB range (high, low, midpoint) from a chosen session window (default 9:30–10:30).
It plots the IB lines, midpoint (colored based on close), and extension levels (+/–25% and 50%).
After the IB session ends, it looks for breakouts:
Long if price closes above IB high.
Short if price closes below IB low.
Each trade targets the 25% extension in the breakout direction, with an optional stop at the opposite IB level.
It limits the number of trades per day and displays info (trades, position, IB range, next target) in a table.
Supertrend [TradingConToto]Supertrend — ADX/DI + EMA Gap + Breakout (with Mobile UI)
What makes it original
Supertrend combines trend strength (ADX/DI), multi-timeframe bias (EMA63 and EMA 200D equivalent), a structural filter based on the distance between EMA2400 and EMA4800 expressed in ATR units, and a momentum confirmation through a previous high breakout.
This is not a random mashup — it’s a sequence of filters designed to reduce trades in ranging markets and prioritize mature trends:
Direction: +DI > -DI (trend led by buyers).
Strength: ADX > mean(ADX) (avoids weak, choppy phases).
Short-term bias: Close > EMA63.
Long-term bias: Close > EMA4800 ≈ EMA200 daily on H1.
Momentum: Close > High (immediate breakout).
Structure: (EMA2400 − EMA4800) > k·ATR (ensures separation in ATR units, filters out flat phases).
Entries & exits
Entry: when all six conditions are met and no open position exists.
Exit: if +DI < -DI or Close < EMA63.
Visuals: EMA63 is painted green while in position and red otherwise, with a supertrend-style band; “BUY” labels appear below the green band and “SELL” labels above the red band.
UI: includes a compact table (mobile-friendly) showing the state of each condition.
Default parameters used in this publication
Initial capital: 10,000
Position size: 10% of equity (≤10% per trade is considered sustainable).
Commission: 0.01% per side (adjust to your broker/market).
Slippage: 1 tick
Pyramiding: 0 (only one position at a time)
Adjust commission/slippage to match your market. For US equities, commissions are often per share; for spot crypto, 0.10–0.20% total is common. I publish with 0.01% per side as a conservative example to avoid overestimating results.
Recommended backtest dataset
Timeframe: H1
Multi-cycle window (e.g. 2015–today)
Symbols with high liquidity (e.g. NASDAQ-100 large caps, or BTC/ETH spot) to generate 100+ trades. Avoid cherry-picked short windows.
Why each filter matters
+DI > -DI + ADX > mean: reduce counter-trend trades and weak signals.
Close > EMA63 + Close > EMA4800: enforce trend alignment in short and long horizons.
Breakout High : requires immediate momentum, avoids early entries.
EMA gap in ATR units: blocks flat or compressed structures where EMA200D aligns with price.
Limitations
The breakout filter may skip healthy pullbacks; the design prioritizes continuation over perfect entry price.
No fixed trailing stop/TP; exits depend on trend degradation via DI/EMA63.
Results vary with real costs (commissions, slippage, funding). Adjust defaults to your broker.
How to use
Apply it on a clean chart (no other indicators when publishing).
Keep in mind the default parameters above; if you change them, mention it in your notes and use the same values in the Strategy Tester.
Ensure your dataset produces 100+ trades for statistical validity.
AI KNN-Dual SuperTrend MTF - by Trading Pine Lab🇬🇧
The AI KNN-Dual SuperTrend MTF is a next-generation trading strategy that merges two higher-timeframe SuperTrends with dual KNN (K-Nearest Neighbors) classifiers, an ADX/DMI filter, and a Pivot Percentile bias module. This layered architecture ensures stronger signal confirmation by requiring consensus across AI models, multi-timeframe SuperTrends, and statistical filters.
Entries occur only when both SuperTrends align with bullish or bearish KNN labels, while the ADX/DMI filter validates momentum. Exits are managed dynamically with adaptive trailing stops (ST ± ATR × factor) or when market conditions flip according to percentile bias.
All parameters are fully configurable:
-Trading direction filter: Long / Short / Both.
-KNN classifiers: neighbors (K), dataset size (N), smoothing lengths.
-Dual SuperTrend: higher timeframes, ATR length, ATR factor, baseline type.
-ADX/DMI filter: customizable length and timeframe.
-Pivot Percentile module: multi-scale statistical bias.
-Visualization: AI markers, ribbons, aura lines, and per-trend coloring.
Bull-Bear Power ZScore - by Trading Pine Lab🇬🇧
The Bull-Bear Power ZScore Strategy is an advanced trading framework that integrates Bull-Bear Power (BBP) with a statistical Z-Score model.
BBP measures the relative strength of buyers vs. sellers against an EMA baseline, while the Z-Score standardizes this relationship to detect statistically significant breakouts.
This dual-layer approach provides early trend detection while reducing noise from raw momentum signals.
Entries are triggered when the Z-Score crosses above or below its threshold (long above +T, short below –T). Exits occur when the Z-Score crosses back to zero, ensuring trades close when momentum fades.
A dynamic multi-level take-profit system is integrated, using ATR-based targets (TP1, TP2, TP3) that automatically adapt to **volume context** (high/medium/low) and **percentile analysis** (distribution of price and volume).
This ensures profit targets stretch in strong environments and tighten in weaker conditions, optimizing both risk and reward.
All parameters are fully configurable:
-Bull-Bear Power Settings: EMA length, Z-Score length, Z-Score threshold.
-Take Profit Settings: enable/disable TP system, ATR period, TP1–TP3 multipliers, TP1–TP3 position sizes.
-Volume Analysis: volume MA period, high/medium/low multipliers, adjustment factors.
-Percentile Analysis: percentile lookback period, high/medium/low thresholds, adjustment factors.
ETH/BTC/XRP Strategy - Powered by BCHETH/BTC/XRP Strategy — Cross-Asset Momentum-Based Strategy
Overview
This strategy aims to identify medium-term long trade opportunities on ETH/BTC/XRP 2 or 4 hour charts by leveraging cross-asset momentum signals from Bitcoin Cash (BCH) relative to Ethereum (ETH). It integrates volatility filters, volume validation, and momentum confirmations to improve trade timing and risk management.
Key Features and Logic
Cross-Asset Momentum Filter: Enters long trades when BCH outperforms ETH in the prior candle, supporting relative strength confirmation.
Volume Confirmation: BCH volume must exceed 135% of its 20-period average, validating market interest before entry signals.
Volatility Filter: ETH price near or below 110% of the lower Bollinger Band (20 periods, 2σ) indicates oversold conditions.
Momentum Indicators: ETH RSI below 70 ensures the asset is not overbought, coupled with BCH MACD line crossing above its signal line for bullish bias.
Risk Controls: Includes trailing stop losses and take profit targets to protect gains and limit drawdowns.
Timing Constraints: Controlled cooldown periods between trades help prevent overtrading and false signals.
Usage Recommendations
Optimized for 2 or 4hour ETH/BTC/XRP USDT candles; 5-minute data optionally used for finer entries and exits.
Suitable for traders seeking dynamic timing based on multi-asset interactions rather than blind holding.
Works as a complement within diversified or rotational strategies focusing on Ethereum exposure.
Performance Summary (Backtest Jan 2023 – Jul 2025) ; ETHUSDT 2hour basis.
Total trades: 65
Win rate: 61.5%
Profit factor: 5.1
Note: The sample size is limited; results should be interpreted with caution. Past performance is not indicative of future results.
Important Notes
This script represents an original combination of cross-asset momentum with volatility and volume filters tailored to ETH and BCH interaction.
Source code is protected to safeguard unique implementation details while allowing free usage without restrictions.
Use appropriate risk management, and consider these signals as part of a broader trading analysis.
No guarantees on profitability; trading involves significant risk.
Lunar calendar day Crypto Trading StrategyLunar calendar day Crypto Trading Strategy
This strategy explores the potential impact of the lunar calendar on cryptocurrency price cycles.
It implements a simple but unconventional rule:
Buy on the 5th day of each lunar month
Sell on the 26th day of the lunar month
No trades between January 1 (solar) and Lunar New Year’s Day (holiday buffer period)
Research background
Several academic studies have investigated the influence of lunar cycles on financial markets. Their findings suggest:
Returns tend to be higher around the full moon compared to the new moon.
Periods between the full moon and the waning phase often show stronger average returns than the waxing phase.
This strategy combines those observations into a practical implementation by testing fixed entry (lunar day 5) and exit (lunar day 26) points, while excluding the transition period from solar New Year to Lunar New Year, effectively capturing mid-month lunar effects.
How it works
The script includes a custom lunar date calculation function, reconstructing lunar months and days for each year (2020–2026).
On lunar day 5, the strategy opens a long position with 100% of equity.
On lunar day 26, the strategy closes the position.
No trades are executed between Jan 1 and Lunar New Year’s Day.
All trades include:
Commission: 0.1%
Slippage: 3 ticks
Position sizing uses the entire equity (100%) for simplicity, but this is not recommended for live trading.
Why this is original
Unlike mashups of built-in indicators, this script:
Implements a full lunar calendar system inside Pine Script.
Translates academic findings on lunar effects into an applied backtest.
Adds a realistic trading filter (holiday gap) based on cultural/seasonal calendar rules.
Provides researchers and traders with a framework to explore non-traditional, time-based signals.
Notes
This is an experimental, research-oriented strategy, not financial advice.
Results are highly dependent on the chosen period (2020–2026).
Using 100% equity per trade is for simplification only and is not a viable money management practice.
The purpose is to investigate whether cyclical patterns linked to lunar time can provide any statistical edge in ETHUSDT.
Triple Momentum Strategy High Winrate Nifty & Bank OPT & FUT🚀High Accuracy Triple Momentum Strategy - Access High Winrate
This system is designed for job holders who want to invest and trade using a proven, back tested strategy without needing to sit in front of charts all day.
📢 Need auto-trade alerts?
A dedicated **indicator version with real-time BUY/SELL/EXIT alerts** is available to this code same strategy script
📊 Results: No Repainting
Historical Win Rate: 90.0% (314/349 signals)
Study Period: 1 Year on NIFTY Futures
Educational Return: 81.4% annualized
Max Drawdown: ₹49,132.50
📊 Optimized Parameters:
"This strategy achieves 90% win rate on NIFTY Futures using optimized settings:
📈PARAM A: 69
📉PARAM B: 34
⚡PARAM C : 10
🎯 Source: Close
📊PARAM D: 39
🔴 Use Live Bar Signals: Enabled (may repaint)
💰 Long Profit %: 0.09
💸 Short Profit %: 0.05
💡 Features:
Non-repainting signal methodology
🧠 Triple Momentum Engine
🎯 Works best on **15-minute timeframe (Index Nifty Futures)**
Clean BUY/SELL/EXIT educational logic
Risk management principles included
🔎 Clean BUY / SELL / EXIT logic, optimized for high-probability trades
📧 Educational Access:
Send TradingView message for access.
📌 **Important Notes:**
- 🟢 Signals are real-time & backtest-matching (normal 1–2 pt slippage can occur its normal )
- 🧪 This tool has been **extensively tested**, and results shown are from actual backtests on TradingView
🔒 Access is invite-only for quality control
⚠️ Disclaimer:
Shared for learning and research purposes only. Not financial advice. Past educational results don't guarantee future outcomes. Trading involves risk of loss. We are not SEBI registered.
#MomentumStrategy #TradingEducation #InviteOnly #NIFTYFutures #AlgoTrading #EducationalStrategy
Triple Momentum Strategy: #NIFTY Futures # High Winrate 🚀 Triple Momentum Strategy – Smart Automation for Working Professionals
This system is designed for job holders who want to invest and trade using a proven, back tested strategy without needing to sit in front of charts all day.
📢 Need auto-trade alerts?
A dedicated **indicator version with real-time BUY/SELL/EXIT alerts** is available to this code same strategy script
Access will be provided upon request. DM @ here in message trade view or @@ pharsha8676@gmail.com @@@ to get it.
📈 **Proven Backtest Performance (Verified by Strategy Tester):**
- ✅ Net Profit: ₹8,16,588.75
- ✅ Win Rate: 90.0% (314 out of 349 trades)
- ✅ Profit Factor: 3.15
- ✅ Max Drawdown: ₹49,132.50
- ✅ Backtest Duration: 1 Year
- ✅ Annualized Return: 81.4%
💡 **Key Features:**
- 🔁 **Non-Repainting Signals** – What you see in back test is what you get in live charts
- ⚡ **Real-Time Ready** – Signals fire on bar close with excellent precision
- 🧠 Triple Momentum Engine
- 🎯 Works best on **15-minute timeframe (Index Nifty Futures)**
- 🔎 Clean BUY / SELL / EXIT logic, optimized for high-probability trades
- 📊 Verified with TradingView’s built-in strategy tester
📌 **Important Notes:**
- 🟢 Signals are real-time & backtest-matching (normal 1–2 pt slippage can occur its normal )
- 🧪 This tool has been **extensively tested**, and results shown are from actual backtests on TradingView
- 🔒 **Access is invite-only to maintain signal quality and avoid misuse*
Your preferred trading style (manual or auto)
👀 Limited access spots available.
🔐 This script is part of a carefully curated library used by serious traders.
🛡️ Note: This tool is shared for research and educational purposes. It is not financial advice. Use at your own discretion.
#MomentumStrategy #TradingEdge #InviteOnly #Index Nifty Futures #NIFTYFutures #AlgoTrading #Strategy # winrate best #BEST Strategy
Multi Channel GRID & DCA LTF [trade_lexx]Multi Channel GRID & DCA LTF
Usage Guide
Part 1: The concept and general possibilities of the "Multi Channel GRID & DCA LTF" strategy
Introduction
Welcome to the guide to "Multi Channel GRID & DCA LTF", a powerful and versatile automated trading strategy for the TradingView platform. This tool was developed for traders who are looking for flexibility, control and a high degree of adaptability to various market conditions.
The strategy is based on a hybrid approach that combines two popular and time-tested techniques.:
1. GRID (grid trading): The classic method of averaging a position is by placing a grid of limit orders.
2. DCA (Dollar Cost averaging): Smart position averaging based on signals from external indicators.
However, "Multi Channel GRID & DCA LTF" goes far beyond the simple combination of these two techniques. The strategy includes a number of unique and innovative features, such as cascading MultiGRID grids for dealing with extreme volatility, Channel Mode range trading mode for profiting from sideways movement, and Low Time Frame analysis (LTF) to achieve surgical accuracy in backtesting. Deep customization options for risk management, capital, take profits, and stop losses allow you to configure a strategy for almost any trading style, asset, and timeframe.
The basic idea: How does it work?
Let's take a detailed look at each of the key concepts embedded in the logic of the strategy.
1. GRID — Automatic placement of buy and sell orders at certain price intervals.
This is a fundamental mode of operation. Its main goal is to systematically improve the average entry price for a position if the market is going against you.
* The principle of operation: After opening the base (first) order (`BO`), the strategy automatically places a series of pending limit orders (here they are called "safety orders" or "SO") at certain price intervals. For a long position, orders are placed below the entry price, and for a short position, orders are placed higher.
* Target: When the price moves against an open position, it consistently hits and executes safety orders. Each such execution adds additional volume to the position at a more favorable price, thereby shifting the overall average entry price (`position_avg_price') closer to the current market price. This means that a much smaller corrective movement will be required to gain ground.
* Flexibility: You have full control over the geometry of the grid: the number of safety orders, the percentage distance between them (`SO Step`), and you can even set a coefficient that will increase this step for each subsequent order (`SO Multiplier`), creating an expanding grid.
2. DCA (Signal Averaging) — Smart Averaging
This mode adds an additional layer of analysis to the averaging process. Instead of just buying/selling at the set price levels, the strategy waits for a confirmation signal.
* Working principle: You can connect any external indicator (for example, RSI, CCI, or even your own complex signal system) to the strategy, which outputs numerical values. As standard, 1 is used for a long signal, and -1 is used for a short signal. The strategy will place the next averaging order only at the moment when it receives the appropriate signal.
* Goal: To average a position not just during a fall (or a rise for a short), but at the moments that your main trading system considers the most favorable for this. This allows you to avoid "catching falling knives" and enter only if there are good reasons.
3. Hybrid Mode (GRID+DCA) is the best of the previous two modes
This mode is designed for maximum filtering and control. It requires two conditions to be fulfilled simultaneously.
* Working principle: The safety order will be executed only if the price has reached the calculated grid level and a confirmation signal has been received from your external indicator. If a confirmation signal is received from an external indicator, the next calculated grid level activates the limit order.
* Goal: To create the most reliable averaging system that protects against premature entries and requires double confirmation (both by price and indicator) before increasing the position size.
4. MultiGRID — Adaptation to extreme volatility
This is one of the most powerful and unique features of a strategy designed to survive and make a profit in the face of strong, protracted trends or "black swans".
* The problem it solves: The usual grid of orders has a limited depth. If the price goes beyond the last safety order, the strategy loses the opportunity to average and becomes vulnerable.
* The principle of operation: The MultiGRID function allows you to create "cascades" — several grids following one another. When all the orders of the first grid are executed, the strategy does not stop. Instead, she can activate the second, third (and so on) a grid of orders. The new grid can be activated by one of two triggers:
1. Offset: The new grid is activated when the price passes another set percentage deviation from the last executed order.
2. Signal: The new grid is activated when a signal is received from an external indicator.
* Goal: To significantly expand the working range of the strategy. This allows it to adapt to strong market movements that would "break" the usual grid, and continue to effectively average a position at a much greater depth of decline or growth.
5. Channel Mode — Trading in the range
This feature turns a standard averaging strategy into a machine for "farming" profits within a price channel that is formed during a sideways market movement.
* The problem it solves: In the standard grid strategy, after partially closing a take profit position, the volume of this part "leaves" the trade until the deal is fully closed. You are missing the opportunity to reuse this capital.
* Operating principle: When Channel Mode is enabled, the following happens. Suppose the price went against you, executed several safety orders, and then turned around and reached one of the partial take profits. At this point, the strategy is:
1. Fixes the profit, as it should be.
2. Instantly places a new limit order to buy (or sell for a short) at exactly the same price level where the last triggered safety order was executed. The volume of this order is equal to the volume of the part that was just closed for take profit.
3. If the price goes down again and executes this "repeat" order, the strategy immediately sets a corresponding take profit for it at the level where the previous profit was taken.
* Goal: To create a continuous buy-sell cycle within the local range (channel). The lower limit of the channel is the price of the last averaging, and the upper limit is the price of a partial take profit. This allows you to repeatedly profit from sideways price fluctuations, without waiting for the full closure of the main, large transaction.
6. LTF (Lower Timeframe Analysis) — Surgical precision of backtesting
This feature is critically important for obtaining reliable results during historical testing (backtesting) of grid strategies.
* The problem it solves: The standard testing mechanism in TradingView has a serious limitation. Working, for example, on a 4-hour chart, he sees only 4 candle points: Open, High, Low and Close. He does not know in what order the price moved within these 4 hours. He could have touched High first and then Low, or vice versa. For grid strategies, this is fatal — the engine can show that a take profit has been executed, although in reality the price first went down, collected the entire grid of orders and only then turned around.
* How it works: When you turn on the LTF mode, the strategy for each candle on your main chart (for example, 4H) requests and analyzes all candles from the lower timeframe you specified (for example, 1-minute). Then it virtually trades the entire price path for these minute candles, executing orders, take profits and stop losses in the sequence in which they would occur in reality. It works in the single take profit mode of the Grid strategy.
* Goal: To provide the most realistic and reliable backtest that reflects the real dynamics of the market. This allows you to avoid false expectations and accurately assess the potential performance of the strategy.
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Part 2: Detailed description of the strategy settings
This section is your main guide to all the switches and options available in the strategy. Understanding each setting is the key to unlocking the full potential of this powerful tool.
1. 🛡️ Risk Management 🛡️
This group contains fundamental parameters that determine the basic logic of risk management and the geometry of grid orders.
* Strategy type: Determines the direction of transactions.
* Long: The strategy will only open long positions (buy).
* Short: The strategy will only open short positions (sell).
* Both: The strategy will work both ways, opening long or short depending on the incoming signal.
* SO Count: Sets the maximum number of Safety (averaging) Orders (SO) that the strategy will place within the same grid. If you have MultiGRID enabled, this number applies to each individual grid.
* SO Step (%): This is the base percentage deviation from the entry price at which the first safety order will be placed. For example, at a value of 0.5, the first SO in a long trade will be placed 0.5% lower than the opening price of the base order.
* SO Multiplier: A coefficient that exponentially increases the step for each subsequent safety order. This allows you to create an expanding grid where averaging orders are placed further and further apart, which is effective with strong and accelerating price movements.
* *The step formula for the nth order*: Step(N) = (SO Step) * (SO Multiplier ^(N-1)).
* If the value is 1, all steps will be the same.
* With a value of 1.6, the step of the second SO will be 1.6 times larger than the first, the step of the third will be 1.6 times larger than the second, and so on.
* 1️⃣ TP/SL: These are simplified settings for quick configuration. They allow you to turn on/off the main take profit and stop loss and set basic percentage values for them. More detailed settings for these parameters can be found in the relevant sections below.
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2. 💰 Money Management 💰
Everything related to position size, leverage, and capital is configured here.
* Volume BO (Base Order): Determines the size of the trade's opening order.
* Volume BO: A fixed amount in the quote currency (for example, in USDT).
* USDT (check mark): Manages the information in the comments to the orders. If enabled, the volume of orders in USDT will be displayed in the comments. This is convenient for visual analysis and for sending the amount of USDT by the placeholder {{strategy.order.comment}} via webhooks when connecting the strategy to the exchange or trading terminals.
* or % of deposit: The amount calculated as a percentage of the available capital of the strategy. The check mark to the right of this field enables this mode. Important: using a percentage activates the effect of compounding (compound interest), as the amount of each new transaction will be automatically recalculated based on the current capital (initial capital + profit/loss). If enabled, the percentage of orders will be displayed in the comments. This is convenient for visual analysis and for sending percentages on the placeholder {{strategy.order.comment}} via webhooks when connecting the strategy to the stock exchange, trading terminals, or creating Copy trading.
* Martingale: The coefficient applied to the volume of orders. It increases the size of each subsequent insurance order compared to the base one.
* Volume formula for the nth SO: Volume SO (N) = (Volume BO) * (Martingale^N).
* With a value of 1.2, the volume of the first SO will be 1.2 times greater than the base, the second — 1.44 times (`1.2 * 1.2`) and so on.
* Leverage: Specify the size of your leverage. This parameter is used exclusively for calculating and displaying the approximate liquidation price. It does not affect the size of positions, but it helps to visually assess the risks.
* Liquidation: Enables or disables the calculation and display of the liquidation line on the chart.
* Margin type: Allows you to select a method for calculating the liquidation price, simulating the logic of exchanges:
* Isolated: The liquidation price is calculated based on the size and leverage of the current open position only.
* Cross: The calculation simulates using the entire available balance to maintain a position. In the strategy, the liquidation price is calculated as the level at which the loss on the current transaction is equal to the current capital.
* Commission (%): Specify the percentage of your exchange's commission per transaction. The correct value of this parameter is crucial for obtaining realistic backtest results.
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3. 🕸️ Grid Management 🕸️
This group is responsible for the logic of safety orders and advanced mechanics such as Channel Mode and MultiGRID.
* SO Type: Defines the logic of placing averaging orders.
* GRID: Classic grid. All safety orders are placed in advance as limit orders.
* DCA: Signal averaging. The strategy is waiting for a signal from an external indicator to place a market averaging order.
* GRID+DCA: Hybrid. The strategy waits for a signal, and if it arrives, places a limit order at the appropriate price level of the grid or executes a market order if the signal has arrived below the limit order level.
* Signal for SO: A data source (indicator) that will be used for signals in DCA and GRID+DCA modes.
* ↔️ Channel Mode: When this option is enabled, the strategy tries to trade in a sideways range. After partially closing a take profit position, it immediately places a limit order for re-entry at the price of the last triggered safety order. This creates a buy-sell cycle within the local channel.
* Best Price Only: This filter adds an additional condition for averaging in DCA and MultiGRID modes (when it operates on a signal). The next averaging order or a new grid will be activated only if the current price is more favorable (lower for long, higher for short) than the price of the previous entry.
* 🧩 MultiGRID ⮕ Enables cascading grid mode.
* Grid Count: The total number of grids that can be activated sequentially.
* Offset: Percentage deviation from the price of the last order of the previous grid. When this margin is reached, the following grid of orders is activated (this mode does not require a signal).
* Or signal: Allows you to use the signal from an external indicator as a trigger to activate the next grid. The checkmark on the right turns on this mode.
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4. 🎯 Entry and Stop 🎯
This group of settings allows you to fine-tune the conditions for starting a new trade and all aspects related to protective stop orders, including the complex mechanics of trailing and managing SL after partial take profits.
* 🎯 Signal: A data source (indicator) that will be used to determine when to enter a trade. The strategy expects a value of 1 for the start of a long trade and -1 for a short trade.
* Min Bars: Sets the minimum number of candles that must pass from the moment of opening the previous trade to the moment of opening the next one. A value of 0 disables this filter. This is a useful tool to prevent overly frequent entries in a "noisy" market.
* Non-stop: If this option is enabled, the strategy ignores the Entry Signal and opens a new trade immediately after closing the previous one (taking into account the Min Bars filter, if it is set). This turns the strategy into a constantly working mechanism that is always on the market.
* 🛑 SL Type: Defines the base price from which the stop loss percentage will be calculated. The stop loss in the first section must be enabled for this block of settings to work.
* From the entry point: SL is always calculated from the opening price of the very first base order. It remains static throughout the entire transaction unless it is moved by other functions.
* From breakeven line: SL is dynamically recalculated and shifted each time a safety order is executed. It always follows the average price of the position, being at a given percentage distance from it.
* From last executed SO: SL is recalculated from the price of the last executed order, whether it is a base or a safety order.
* From last SO: SL is calculated from the price of the most recent possible safety order in the grid. This is usually the most remote and conservative type of SL.
* Trailing SL Type: Defines the algorithm by which the stop loss will move after its activation.
* Standard: Classic trailing. After activation, SL will follow the price at a fixed distance.
* ATR: SL will follow the price at a distance equal to the value of the ATR indicator multiplied by the specified multiplier.
* External Source: SL will follow any selected line of the third-party indicator.
* Period and Multiplier: Common parameters for all types of trailing.
* Source: The source of the line for the trailing SL of the third-party indicator.
* Trailing SL after entry: The mode of activation of the trailing SL after entering the transaction
* SL management after TP (sections 1️⃣, 2️⃣, 3️⃣): These three blocks allow you to create a complex stop loss management logic as profits are recorded.
For each take profit level (TP1, TP2, TP3), you can configure:
* SL BE / SL TP1 / SL TP2: When the corresponding TP is reached, the stop loss will be moved to the breakeven point (for TP1), to the TP1 price level (for TP2) or to the TP2 price level (for TP3).
* Trailing SL: When the corresponding TP is reached, the trailing stop loss is activated according to the settings above.
* By ↔️ Signal: A very powerful option. If it is enabled, the above action (SL transfer or trailing activation) will occur when the opposite trading signal is received from an external indicator. This allows you to protect profits or reduce losses if the market turns sharply, even before reaching the target.
* SL Delay ⮕ Allows you to delay the activation of the stop loss.
* Number of Bars: The Stop loss will be physically placed on the market only after the specified number of candles has passed since entering the trade. This can help to avoid "taking out" the stop with a random short movement (squiz) immediately after opening a position.
* SL Block: Unique defensive mechanics for trading both ways (`Strategy Type: Both`).
* Number of SL: If the strategy receives the specified number of stop losses in a row in one direction (for example, 2 stops long), it temporarily blocks the opportunity to open new trades in that direction.
* Lock Reset mode:
* By direction: The lock is lifted if a profitable trade is closed in the allowed direction or if a stop loss is triggered in the opposite direction.
* First profit: The lock is lifted after closing any profitable transaction, regardless of its direction.
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5. ✅ Take Profit ✅
This group of settings provides comprehensive control over profit taking, from a simple take profit to a complex system of partial closures and trailing.
* ✅ TP Type: Defines the base price for calculating the percentage deviation of the take profit.
* From entry point: TP is calculated from the base order price.
* From breakeven line: TP dynamically follows the average position price.
* From last executed SO: TP is calculated from the price of the last executed order.
* Filters for closing on signal
* Only ➕: If TP is triggered by a signal, the deal will be closed only if it is in the black relative to the average price.
* Or >TP: If TP is triggered by a signal, the trade will be closed only if the closing price is better than (or equal to) the estimated price of this TP.
* TP type of trailing: Yes, take profit has a trailing too! It works differently than the SL trailing.
* Standard / ATR: After the price touches the "virtual" TP level, the trailing is activated. He does not place a stop order, but begins to move away from the price, dynamically moving the limit order to close further and further in the profitable direction, allowing him to collect the maximum from the impulse movement.
* External Source: TP will follow any selected line of the third-party indicator.
* Period and Multiplier: Parameters for calculating the trailing margin TP.
* Source: The source of the line for the trailing TP of the third-party indicator.
* TP level settings (sections 1️⃣, 2️⃣, 3️⃣, 4️⃣): The strategy supports up to four independent take profit levels, which allows for a flexible system of partial commits.
For each level, you can set:
* TP: Enable the level and set its percentage deviation from the base price.
* Size: What percentage of the current position will be closed when this level is reached. For the last active TP, this parameter is ignored, and 100% of the remaining position is closed.
* Trailing TP: Enable the above-described trailing mechanism for this particular level.
* Signal: Enable closing based on the signal from the external indicator for this level.
* Or take: If both the closing on the signal and the limit order are enabled, then whatever comes first will work.
* After SO: Activate this TP level only after the specified number of safety orders has been executed. This allows you to set closer targets for riskier (deeply averaged) positions.
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6. 🔬 GRID and MultiGrid Analysis on Lower TFs (LTF) 🔬
This group activates one of the most important functions for accurate testing of grid strategies.
* Enable LTF Calculation ⮕ The main switch of the analysis mode on the lower timeframes.
* Timeframe selection: A drop-down list where you can select a timeframe for detailed analysis. For example, if your main schedule is 1 hour, you can select 1 minute here. The strategy will emulate the trading of minute candles within each hour candle.
❗️Important: As mentioned in the first part, the use of this mode is critically necessary to obtain realistic backtest results, especially for strategies with a dense grid of orders. Without it, the results may be overly optimistic and not reflect the real dynamics of the market. It should be remembered that TradingView imposes a limit on the number of intra-bars (minor TF bars) that can be requested. This is usually about 100,000 bars.
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7. 🕘 Backtest Date Range 🕘
This group allows you to focus testing on a specific historical period.
* Limit Date Range: Enables date filtering.
* Start time: The date and time when the strategy will start analyzing and opening deals.
* End time: The date and time after which the strategy will stop opening new deals and complete testing.
// ------------------------
8. 🎨 Visualization 🎨
All the options responsible for the appearance and information content of the chart are collected here.
* Show PnL labels: Enables/disables the display of text labels with the result (profit/loss) after closing each trade.
* Statistics Table: Enables/disables the main dashboard with detailed statistics on the results of the backtest.
* Strategy Settings Table: Enables/disables an additional panel that summarizes all the key parameters of the current configuration.
* Monthly Profit Table: Enables/disables a table with a breakdown of percentage returns by month and year.
* Table settings: For each of the three tables, you can individually adjust the Text size and Table Position on the screen to position them as conveniently as possible.
* Decimal places: Defines how many decimal places will be displayed in numeric values in tables and on labels.
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9. ✉️ Webhook Settings ✉️
This group is intended for traders who want to automate trading on strategy signals using third-party services and exchanges (for example, 3Commas, WunderTrading, Cryptorobotics, Cryptohopper, Bitsgap, Binance, ByBit, OKX, Pionex, Bitget or proprietary solutions).
For each key event in the strategy, there is a separate switch and a text field:
* Webhook for Open: Enable and set a message for the webhook that will be sent when the base order is opened.
* Webhook for Averaging: A message sent when executing any insurance order.
* Webhook for Take Profit: A message sent when closing on take profit (including partial ones).
* Webhook for Stop-Loss: A message sent when a stop loss is closed.
You can insert a JSON code or any other message format that your service requires for automation into the text fields. The strategy supports special placeholders (for example, `{{strategy.order.alert_message}}`), which allow you to dynamically insert the necessary data into the message, such as the amount of USDT or the percentage of the deposit for entry, averaging and take profit orders.
Valid H/L Strategy Tester with MFE/MAE Analytics
## Overview
A data-driven trading indicator that identifies valid high/low price levels and provides statistical insights through Maximum Favorable Excursion (MFE) and Maximum Adverse Excursion (MAE) analytics. Make informed trading decisions based on historical price behavior rather than guesswork.
## Key Features
### 🎯 Smart Pattern Recognition
- Automatically detects valid highs and lows with confirmation system
- Color-coded candles and lines for clear visual identification
- Inside/Outside print filtering for higher probability setups
### 📊 Statistical Analytics
- Analyzes up to 500 historical setups for MFE/MAE calculations
- 1-hour and 3-hour timeframe data with percentile-based targets (20th, 50th, 80th)
- Real-time performance tracking with comprehensive statistics table
### ⚙️ Flexible Strategy Options
**Entry Methods:** Confirmation-based or MAE percentile entries
**Take Profit:** MFE-based, fixed points, percentage, or R:R ratio targets
**Risk Management:** Multiple stop loss types with position sizing controls
### 🕐 Advanced Time Filtering
- Session filters (Asia, London, New York)
- Individual hourly controls (24-hour precision in ET)
- Pre-configured for optimal NY trading hours (9 AM - 2 PM)
### 📈 Visual Dashboard
- MFE target lines (blue) and MAE risk lines (orange)
- Customizable colors, styles, and line weights
- Statistics table showing daily/hourly/weekly performance breakdowns
## How It Works
1. **Pattern Detection** - Scans for valid high/low formations using price structure and gap behavior
2. **Statistical Analysis** - Calculates historical MFE/MAE percentiles from past setups
3. **Trade Framework** - Executes entries/exits based on your configuration with real-time performance tracking
## Ideal For
- **Day/Swing Traders** seeking data-driven entry/exit levels
- **Risk Managers** wanting historical drawdown data for stop placement
- **Performance Trackers** needing detailed analytics across timeframes and sessions
- **Flexible Strategies** - adapts to scalping, day trading, or swing trading styles
## Quick Setup
1. Select analysis timeframe (default: 5-minute)
2. Choose entry method and exit strategy
3. Enable MFE/MAE analytics display
4. Apply session/hourly filters
5. Customize visual elements and table settings
Transform your trading from guesswork to statistical precision with historical price behavior insights.
Mutanabby_AI | ATR+ | Trend-Following StrategyThis document presents the Mutanabby_AI | ATR+ Pine Script strategy, a systematic approach designed for trend identification and risk-managed position entry in financial markets. The strategy is engineered for long-only positions and integrates volatility-adjusted components to enhance signal robustness and trade management.
Strategic Design and Methodological Basis
The Mutanabby_AI | ATR+ strategy is constructed upon a foundation of established technical analysis principles, with a focus on objective signal generation and realistic trade execution.
Heikin Ashi for Trend Filtering: The core price data is processed via Heikin Ashi (HA) methodology to mitigate transient market noise and accentuate underlying trend direction. The script offers three distinct HA calculation modes, allowing for comparative analysis and validation:
Manual Calculation: Provides a transparent and deterministic computation of HA values.
ticker.heikinashi(): Utilizes TradingView's built-in function, employing confirmed historical bars to prevent repainting artifacts.
Regular Candles: Allows for direct comparison with standard OHLC price action.
This multi-methodological approach to trend smoothing is critical for robust signal generation.
Adaptive ATR Trailing Stop: A key component is the Average True Range (ATR)-based trailing stop. ATR serves as a dynamic measure of market volatility. The strategy incorporates user-defined parameters (
Key Value and ATR Period) to calibrate the sensitivity of this trailing stop, enabling adaptation to varying market volatility regimes. This mechanism is designed to provide a dynamic exit point, preserving capital and locking in gains as a trend progresses.
EMA Crossover for Signal Generation: Entry and exit signals are derived from the interaction between the Heikin Ashi derived price source and an Exponential Moving Average (EMA). A crossover event between these two components is utilized to objectively identify shifts in momentum, signaling potential long entry or exit points.
Rigorous Stop Loss Implementation: A critical feature for risk mitigation, the strategy includes an optional stop loss. This stop loss can be configured as a percentage or fixed point deviation from the entry price. Importantly, stop loss execution is based on real market prices, not the synthetic Heikin Ashi values. This design choice ensures that risk management is grounded in actual market liquidity and price levels, providing a more accurate representation of potential drawdowns during backtesting and live operation.
Backtesting Protocol: The strategy is configured for realistic backtesting, employing fill_orders_on_standard_ohlc=true to simulate order execution at standard OHLC prices. A configurable Date Filter is included to define specific historical periods for performance evaluation.
Data Visualization and Metrics: The script provides on-chart visual overlays for buy/sell signals, the ATR trailing stop, and the stop loss level. An integrated information table displays real-time strategy parameters, current position status, trend direction, and key price levels, facilitating immediate quantitative assessment.
Applicability
The Mutanabby_AI | ATR+ strategy is particularly suited for:
Cryptocurrency Markets: The inherent volatility of assets such as #Bitcoin and #Ethereum makes the ATR-based trailing stop a relevant tool for dynamic risk management.
Systematic Trend Following: Individuals employing systematic methodologies for trend capture will find the objective signal generation and rule-based execution aligned with their approach.
Pine Script Developers and Quants: The transparent code structure and emphasis on realistic backtesting provide a valuable framework for further analysis, modification, and integration into broader quantitative models.
Automated Trading Systems: The clear, deterministic entry and exit conditions facilitate integration into automated trading environments.
Implementation and Evaluation
To evaluate the Mutanabby_AI | ATR+ strategy, apply the script to your chosen chart on TradingView. Adjust the input parameters (Key Value, ATR Period, Heikin Ashi Method, Stop Loss Settings) to observe performance across various asset classes and timeframes. Comprehensive backtesting is recommended to assess the strategy's historical performance characteristics, including profitability, drawdown, and risk-adjusted returns.
I'd love to hear your thoughts, feedback, and any optimizations you discover! Drop a comment below, give it a like if you find it useful, and share your results.
Backtest - Strategy Builder [AlgoAlpha]🟠 OVERVIEW
This script by AlgoAlpha is a modular Strategy Builder designed to let traders test custom trade entry and exit logic on TradingView without writing their own Pine code. It acts as a framework where users can connect multiple external signals, chain them in sequences, and run backtests with built-in leverage, margin, and risk controls. Its main strength is flexibility—you can define up to five sequential steps for entry and exit conditions on both long and short sides, with logic connectors (AND/OR) controlling how conditions combine. This lets you test complex multi-step confirmation workflows in a controlled, visual backtesting environment.
🟠 CONCEPTS
The system works by linking external signals —these can be values from other indicators, and/or custom sources—to conditional checks like “greater than,” “less than,” or “crossover.” You can stack these checks into steps , where all conditions in a step must pass before the sequence moves to the next. This creates a chain of logic that must be completed before a trade triggers. On execution, the strategy sizes positions according to your chosen leverage mode ( Cross or Isolated ) and allocation method ( Percent of equity or absolute USD value]). Liquidation prices are simulated for both modes, allowing realistic margin behaviour in testing. The script also tracks performance metrics like Sharpe, Sortino, profit factor, drawdown, and win rate in real time.
🟠 FEATURES
Up to 5 sequential steps for both long and short entries, each with multiple conditions linked by AND/OR logic.
Two leverage modes ( Cross and Isolated ) with independent long/short leverage multipliers.
Separate multi-step exit triggers for longs and shorts, with optional TP/SL levels or opposite-side triggers for flipping positions.
Position sizing by equity percent or fixed USD amount, applied before leverage.
Realistic liquidation price simulation for margin testing.
Built-in trade gating and validation—prevents trades if configuration rules aren’t met (e.g., no exit defined for an active side).
Full performance dashboard table showing live strategy status, warnings, and metrics.
Configurable bar coloring based on position side and TP/SL level drawing on chart.
Integration with TradingView's strategy backtester, allowing users to view more detailed metrics and test the strategy over custom time horizons.
🟠 USAGE
Add the strategy to your chart. In the settings, under Master Settings , enable longs/shorts, select leverage mode, set leverage multipliers, and define position sizing. Then, configure your Long Trigger and Short Trigger groups: turn on conditions, pick which external signal they reference, choose the comparison type, and assign them to a sequence step. For exits, use the corresponding Exit Long Trigger and Exit Short Trigger groups, with the option to link exits to opposite-side entries for auto-flips. You can also enable TP and/or SL exits with custom sources for the TP/SL levels. Once set, the strategy will simulate trades, show performance stats in the on-chart table, and highlight any configuration issues before execution. This makes it suitable for testing both simple single-signal systems and complex, multi-filtered strategies under realistic leverage and margin constraints.
🟠 EXAMPLE
The backtester on its own does not contain any indicator calculation; it requires input from external indicators to function. In this example, we'll be using AlgoAlpha's Smart Signals Assistant indicator to demonstrate how to build a strategy using this script.
We first define the conditions beforehand:
Entry :
Longs – SSA Bullish signal (strong OR weak)
Shorts – SSA Bearish signal (strong OR weak)
Exit
Longs/Shorts: (TP/SL hit OR opposing signal fires)
Other Parameters (⚠️Example only, tune this based on proper risk management and settings)
Long Leverage: default (3x)
Short Leverage: default (3x)
Position Size: default (10% of equity)
Steps
Load up the required indicators (in this example, the Smart Signals Assistant).
Ensure the required plots are being output by the indicator properly (signals and TP/SL levels are being plotted).
Open the Strategy Builder settings and scroll down to "CONDITION SETUP"; input the signals from the external indicator.
Configure the exit conditions, add in the TP/SL levels from the external indicator, and add an additional exit condition → {{Opposite Direction}} Entry Trigger.
After configuring the entry and exit conditions, the strategy should now be running. You can view information on the strategy in TradingView's backtesting report and also in the Strategy Builder's information table (default top right corner).
It is important to note that the strategy provided above is just an example, and the complexity of possible strategies stretches beyond what was shown in this short demonstration. Always incorporate proper risk management and ensure thorough testing before trading with live capital.
