ALMA & UT Bot Confluence StrategyALMA & UT Bot Confluence Strategy
This is a comprehensive trend-following and momentum strategy designed to identify high-probability trade setups by combining multiple layers of confirmation. It is built around an ALMA (Arnaud Legoux Moving Average) and a long-term EMA, and then enhances signal quality with the popular UT Bot indicator, a Volume Filter, and an adaptive hold mechanism.
The primary goal of this strategy is to filter out market noise, avoid low liquidity traps, and provide more robust and selective trading logic by adapting its timing to changing market volatility.
Key Features and How It Works
This strategy is not a simple crossover system. An entry signal is generated by the confluence of only a few conditions:
Underlying Trend and Signal Engine:
ALMA (Arnaud Legoux Moving Average): Provides a responsive, low-latency signal line for entries. EMA (Exponential Moving Average): A longer-term EMA acts as a primary trend filter, ensuring trades are executed only in line with the overall market trend.
Confirmation Layer:
UT Bot Confirmation: A trade is considered valid only when the UT Bot indicator provides a relevant buy or sell signal. This acts as a strong secondary confirmation, reducing false entries.
Advanced Filters for Signal Quality:
Volume Filter: This is an important safety mechanism that prevents trades from being executed in low-volume, illiquid markets where price action can be erratic and unreliable.
Momentum Filter (ADX and RSI): The strategy uses the ADX to check for sufficient market momentum and the RSI to ensure it doesn't enter overbought/oversold zones.
Volatility Filter (Bollinger Bands): This helps prevent entries when the price deviates too far from its average, preventing "buying at the top" or "selling at the bottom." Adaptive Timing (Dynamic Cool-Down):
Instead of a fixed waiting period between trades, this strategy uses a dynamic cooling-down period based on the ATR. It automatically waits longer during periods of high volatility (to prevent volatility) and becomes more responsive in calmer markets. How to Use This Strategy:
Long Entry (BUY): When all bullish conditions align, a green "BUY" triangle appears below the price.
Short Entry (SELL): When all bearish conditions align, a red "SELL" triangle appears above the price.
Trend Visualization: The chart background is color-coded according to UT Bot's trend direction (Green for an uptrend, Red for a downtrend), allowing for at-a-glance market analysis.
Double Exit Strategy Options
You have full control over how you exit trades:
Classic SL/TP: Use a standard Stop-Loss and Take-Profit order based on ATR (Average True Range) multipliers. UT Bot Trailing Stop (Recommended): A dynamic exit mechanism that follows the price allows your winning trades to catch up to larger trends while protecting your profits.
Disclaimer
This script is for educational purposes only and should not be construed as financial advice. Past performance is not indicative of future results. All trades involve risk. Before risking any capital, we strongly recommend extensively backtesting this strategy across your preferred assets and timeframes to understand its behavior and find settings that suit your personal trading style.
The author recommends using this strategy with Heikin-Ashi candlesticks. Using this method will significantly increase the strategy's trading success rate and profitability in backtests.
You should change the settings according to your preferred chart time range. You can find the best value for you by observing the value changes you make on the chart.
Bande e canali
ZapTeam Pro Strategy v6 — EMA The Pro Strategy v6 script is a versatile trading strategy for TradingView that combines trend indicators, filters, and levels.
Main features:
EMA 21, EMA 50, EMA 200 — trend detection and entry signals via EMA crossovers.
Ichimoku Cloud (optional) — trend filtering and price position relative to the cloud.
ETH Dominance filter (optional) — filters trades based on Ethereum dominance (ETH.D).
ATR Stop-Loss — dynamic stop-loss based on volatility.
Two take-profits (TP1 and TP2) with optional 50/50 split.
Dynamic Fibonacci Levels — automatic or manual swings, with 1.272 and 1.618 extensions.
Custom S/R Levels — user-defined support/resistance levels.
Level lines extend across the chart and automatically adjust when zooming or panning.
Designed for trading in trending market conditions on any timeframe.
The strategy calculates position size based on percentage risk per equity.
BB & RSI Trailing Stop StrategySimple BB & RSI generated using AI, gets 60% on S&P 500 with the right settings
Keltner Channel Based Grid Strategy # KC Grid Strategy - Keltner Channel Based Grid Trading System
## Strategy Overview
KC Grid Strategy is an innovative grid trading system that combines the power of Keltner Channels with dynamic position sizing to create a mean-reversion trading approach. This strategy automatically adjusts position sizes based on price deviation from the Keltner Channel center line, implementing a systematic grid-based approach that capitalizes on market volatility and price oscillations.
## Core Principles
### Keltner Channel Foundation
The strategy builds upon the Keltner Channel indicator, which consists of:
- **Center Line**: Moving average (EMA or SMA) of the price
- **Upper Band**: Center line + (ATR/TR/Range × Multiplier)
- **Lower Band**: Center line - (ATR/TR/Range × Multiplier)
### Grid Trading Logic
The strategy implements a sophisticated grid system where:
1. **Position Direction**: Inversely correlated to price position within the channel
- When price is above center line → Short positions
- When price is below center line → Long positions
2. **Position Size**: Proportional to distance from center line
- Greater deviation = Larger position size
3. **Grid Activation**: Positions are adjusted only when the difference exceeds a predefined grid threshold
### Mathematical Foundation
The core calculation uses the KC Rate formula:
```
kcRate = (close - ma) / bandWidth
targetPosition = kcRate × maxAmount × (-1)
```
This creates a mean-reversion system where positions increase as price moves further from the mean, expecting eventual return to equilibrium.
## Parameter Guide
### Time Range Settings
- **Start Date**: Beginning of strategy execution period
- **End Date**: End of strategy execution period
### Core Parameters
1. **Number of Grids (NumGrid)**: Default 12
- Controls grid sensitivity and position adjustment frequency
- Higher values = More frequent but smaller adjustments
- Lower values = Less frequent but larger adjustments
2. **Length**: Default 10
- Period for moving average and volatility calculations
- Shorter periods = More responsive to recent price action
- Longer periods = Smoother, less noisy signals
3. **Grid Coefficient (kcRateMult)**: Default 1.33
- Multiplier for channel width calculation
- Higher values = Wider channels, less frequent trades
- Lower values = Narrower channels, more frequent trades
4. **Source**: Default Close
- Price source for calculations (Close, Open, High, Low, etc.)
- Close price typically provides most reliable signals
5. **Use Exponential MA**: Default True
- True = Uses EMA (more responsive to recent prices)
- False = Uses SMA (equal weight to all periods)
6. **Bands Style**: Default "Average True Range"
- **Average True Range**: Smoothed volatility measure (recommended)
- **True Range**: Current bar's volatility only
- **Range**: Simple high-low difference
## How to Use
### Setup Instructions
1. **Apply to Chart**: Add the strategy to your desired timeframe and instrument
2. **Configure Parameters**: Adjust settings based on market characteristics:
- Volatile markets: Increase Grid Coefficient, reduce Number of Grids
- Stable markets: Decrease Grid Coefficient, increase Number of Grids
3. **Set Time Range**: Define your backtesting or live trading period
4. **Monitor Performance**: Watch strategy performance metrics and adjust as needed
### Optimal Market Conditions
- **Range-bound markets**: Strategy performs best in sideways trending markets
- **High volatility**: Benefits from frequent price oscillations around the mean
- **Liquid instruments**: Ensures efficient order execution and minimal slippage
### Position Management
The strategy automatically:
- Calculates optimal position sizes based on account equity
- Adjusts positions incrementally as price moves through grid levels
- Maintains risk control through maximum position limits
- Executes trades only during specified time periods
## Risk Warnings
### ⚠️ Important Risk Considerations
1. **Trending Market Risk**:
- Strategy may underperform or generate losses in strong trending markets
- Mean-reversion assumption may fail during sustained directional moves
- Consider market regime analysis before deployment
2. **Leverage and Position Size Risk**:
- Strategy uses pyramiding (up to 20 positions)
- Large positions may accumulate during extended moves
- Monitor account equity and margin requirements closely
3. **Volatility Risk**:
- Sudden volatility spikes may trigger multiple rapid position adjustments
- Consider volatility filters during high-impact news events
- Backtest across different volatility regimes
4. **Execution Risk**:
- Strategy calculates on every tick (calc_on_every_tick = true)
- May generate frequent orders in volatile conditions
- Ensure adequate execution infrastructure and consider transaction costs
5. **Parameter Sensitivity**:
- Performance highly dependent on parameter optimization
- Over-optimization may lead to curve-fitting
- Regular parameter review and adjustment may be necessary
## Suitable Scenarios
### Ideal Market Conditions
- **Sideways/Range-bound markets**: Primary use case
- **Mean-reverting instruments**: Forex pairs, some commodities
- **Stable volatility environments**: Consistent ATR patterns
- **Liquid markets**: Major currency pairs, popular stocks/indices
## Important Notes
### Strategy Limitations
1. **No Stop Loss**: Strategy relies on mean reversion without traditional stop losses
2. **Capital Requirements**: Requires sufficient capital for grid-based position sizing
3. **Market Regime Dependency**: Performance varies significantly across different market conditions
## Disclaimer
This strategy is provided for educational and research purposes only. Past performance does not guarantee future results. Trading involves substantial risk of loss and is not suitable for all investors. Users should thoroughly test the strategy and understand its mechanics before risking real capital. The author assumes no responsibility for trading losses incurred through the use of this strategy.
---
# KC网格策略 - 基于肯特纳通道的网格交易系统
## 策略概述
KC网格策略是一个创新的网格交易系统，它将肯特纳通道的力量与动态仓位调整相结合，创建了一个均值回归交易方法。该策略根据价格偏离肯特纳通道中心线的程度自动调整仓位大小，实施系统化的网格方法，利用市场波动和价格振荡获利。
## 核心原理
### 肯特纳通道基础
该策略建立在肯特纳通道指标之上，包含：
- **中心线**: 价格的移动平均线（EMA或SMA）
- **上轨**: 中心线 + (ATR/TR/Range × 乘数)
- **下轨**: 中心线 - (ATR/TR/Range × 乘数)
### 网格交易逻辑
该策略实施复杂的网格系统：
1. **仓位方向**: 与价格在通道中的位置呈反向关系
- 当价格高于中心线时 → 空头仓位
- 当价格低于中心线时 → 多头仓位
2. **仓位大小**: 与距离中心线的距离成正比
- 偏离越大 = 仓位越大
3. **网格激活**: 只有当差异超过预定义的网格阈值时才调整仓位
### 数学基础
核心计算使用KC比率公式：
```
kcRate = (close - ma) / bandWidth
targetPosition = kcRate × maxAmount × (-1)
```
这创建了一个均值回归系统，当价格偏离均值越远时仓位越大，期望最终回归均衡。
## 参数说明
### 时间范围设置
- **开始日期**: 策略执行期间的开始时间
- **结束日期**: 策略执行期间的结束时间
### 核心参数
1. **网格数量 (NumGrid)**: 默认12
- 控制网格敏感度和仓位调整频率
- 较高值 = 更频繁但较小的调整
- 较低值 = 较少频繁但较大的调整
2. **长度**: 默认10
- 移动平均线和波动率计算的周期
- 较短周期 = 对近期价格行为更敏感
- 较长周期 = 更平滑，噪音更少的信号
3. **网格系数 (kcRateMult)**: 默认1.33
- 通道宽度计算的乘数
- 较高值 = 更宽的通道，较少频繁的交易
- 较低值 = 更窄的通道，更频繁的交易
4. **数据源**: 默认收盘价
- 计算的价格来源（收盘价、开盘价、最高价、最低价等）
- 收盘价通常提供最可靠的信号
5. **使用指数移动平均**: 默认True
- True = 使用EMA（对近期价格更敏感）
- False = 使用SMA（对所有周期等权重）
6. **通道样式**: 默认"平均真实范围"
- **平均真实范围**: 平滑的波动率测量（推荐）
- **真实范围**: 仅当前K线的波动率
- **范围**: 简单的高低价差
## 使用方法
### 设置说明
1. **应用到图表**: 将策略添加到您所需的时间框架和交易品种
2. **配置参数**: 根据市场特征调整设置：
- 波动市场：增加网格系数，减少网格数量
- 稳定市场：减少网格系数，增加网格数量
3. **设置时间范围**: 定义您的回测或实盘交易期间
4. **监控表现**: 观察策略表现指标并根据需要调整
### 最佳市场条件
- **区间震荡市场**: 策略在横盘趋势市场中表现最佳
- **高波动性**: 受益于围绕均值的频繁价格振荡
- **流动性强的品种**: 确保高效的订单执行和最小滑点
### 仓位管理
策略自动：
- 根据账户权益计算最优仓位大小
- 随着价格在网格水平移动逐步调整仓位
- 通过最大仓位限制维持风险控制
- 仅在指定时间段内执行交易
## 风险警示
### ⚠️ 重要风险考虑
1. **趋势市场风险**:
- 策略在强趋势市场中可能表现不佳或产生损失
- 在持续方向性移动期间均值回归假设可能失效
- 部署前考虑市场制度分析
2. **杠杆和仓位大小风险**:
- 策略使用金字塔加仓（最多20个仓位）
- 在延长移动期间可能积累大仓位
- 密切监控账户权益和保证金要求
3. **波动性风险**:
- 突然的波动性激增可能触发多次快速仓位调整
- 在高影响新闻事件期间考虑波动性过滤器
- 在不同波动性制度下进行回测
4. **执行风险**:
- 策略在每个tick上计算（calc_on_every_tick = true）
- 在波动条件下可能产生频繁订单
- 确保充足的执行基础设施并考虑交易成本
5. **参数敏感性**:
- 表现高度依赖于参数优化
- 过度优化可能导致曲线拟合
- 可能需要定期参数审查和调整
## 适用场景
### 理想市场条件
- **横盘/区间震荡市场**: 主要用例
- **均值回归品种**: 外汇对，某些商品
- **稳定波动性环境**: 一致的ATR模式
- **流动性市场**: 主要货币对，热门股票/指数
## 注意事项
### 策略限制
1. **无止损**: 策略依赖均值回归而无传统止损
2. **资金要求**: 需要充足资金进行基于网格的仓位调整
3. **市场制度依赖性**: 在不同市场条件下表现差异显著
## 免责声明
该策略仅供教育和研究目的。过往表现不保证未来结果。交易涉及重大损失风险，并非适合所有投资者。用户应在投入真实资金前彻底测试策略并理解其机制。作者对使用此策略产生的交易损失不承担任何责任。
---
**Strategy Version**: Pine Script v6
**Author**: Signal2Trade
**Last Updated**: 2025-8-9
**License**: Open Source (Mozilla Public License 2.0)
Vegas Tunnel StrategyVegas Tunnel Strategy is a trend-following breakout system based on exponential moving averages (EMAs). It uses a "tunnel" formed by the 144 EMA and 169 EMA to identify the market's long-term trend direction. Entry signals are generated when a shorter-term EMA (12 EMA) breaks above or below this tunnel, confirming momentum alignment.
Long Setup: Price and EMA12 are above the tunnel (EMA144 < EMA169); entry on pullback near the tunnel.
Short Setup: Price and EMA12 are below the tunnel (EMA144 > EMA169); entry on rebound near the tunnel.
Exit Rules: Fixed stop loss below/above the tunnel or based on ATR; take profit at 1.5–2× the risk.
This strategy works best on 4H or daily charts and is suitable for trending assets like FX pairs, gold, oil, or indices.
[Stratégia] VWAP Mean Magnet v9 (Simple Alert)This strategy is specifically designed for a ranging (sideways-moving) Bitcoin market.
A trade is only opened and signaled on the chart if all three of the following conditions are met simultaneously at the close of a candle:
Zone Entry
The price must cross into the signal zone: the red band for a Short (sell) position, or the green band for a Long (buy) position.
RSI Confirmation
The RSI indicator must also confirm the signal. For a Short, it must go above 65 (overbought condition). For a Long, it must fall below 25 (oversold condition).
Volume Filter
The volume on the entry candle cannot be excessively high. This safety filter is designed to prevent trades during risky, high-momentum breakouts.
Martin Strategy - No Loss Exit v3Martin Strategy - No Loss Exit v3Martin Strategy - No Loss Exit v3Martin Strategy - No Loss Exit v3
AUD/USD 1-Min Scalping Strategy with LabelsHere’s a complete TradingView Pine Script v5 for the 1-minute AUD/USD scalping strategy we just discussed. This strategy uses:
EMA 13 and EMA 26 for trend filtering
Bollinger Bands for volatility extremes
RSI (4) for momentum confirmation
Bollinger Bands SMA 20_2 StrategyMean reversion strategy using Bollinger Bands (20-period SMA with 2.0 standard deviation bands).
Trade Triggers:
🟢 BUY SIGNAL:
When: Price crosses above the lower Bollinger Band
Logic: Price has hit oversold territory and is bouncing back
Action: Places a long position with stop at the lower band
🔴 SELL SIGNAL:
When: Price crosses below the upper Bollinger Band
Logic: Price has hit overbought territory and is pulling back
Action: Places a short position with stop at the upper band
TOT Strategy, The ORB Titan (Configurable)This is a strategy script adapted from Deniscr 's indicator script found here:
All feedback welcome!
Linear Mean Reversion Strategy📘 Strategy Introduction: Linear Mean Reversion with Fixed Stop
This strategy implements a simple yet powerful mean reversion model that assumes price tends to oscillate around a dynamic average over time. It identifies statistically significant deviations from the moving average using a z-score, and enters trades expecting a return to the mean.
🧠 Core Logic:
A z-score is calculated by comparing the current price to its moving average, normalized by standard deviation, over a user-defined half-life window.
Trades are entered when the z-score crosses a threshold (e.g., ±1), signaling overbought or oversold conditions.
The strategy exits positions either when price reverts back near the mean (z-score close to 0), or if a fixed stop loss of 100 points is hit, whichever comes first.
⚙️ Key Features:
Dynamic mean and volatility estimation using moving average and standard deviation
Configurable z-score thresholds for entry and exit
Position size scaling based on z-score magnitude
Fixed stop loss to control risk and avoid prolonged drawdowns
🧪 Use Case:
Ideal for range-bound markets or assets that exhibit stationary behavior around a mean, this strategy is especially useful on assets with mean-reverting characteristics like currency pairs, ETFs, or large-cap stocks. It is best suited for traders looking for short-term reversions rather than long-term trends.
BTC 1m Chop Top/Bottom Reversal (Stable Entries)Strategy Description: BTC 5m Chop Top/Bottom Reversal (Stable Entries)
This strategy is engineered to capture precise reversal points during Bitcoin’s choppy or sideways price action on the 5-minute timeframe. It identifies short-term tops and bottoms using a confluence of volatility bands, momentum indicators, and price structure, optimized for high-probability scalping and intraday reversals.
Core Logic:
Volatility Filter: Uses an EMA with ATR bands to define overextended price zones.
Momentum Divergence: Confirms reversals using RSI and MACD histogram shifts.
Price Action Filter: Requires candle confirmation in the direction of the trade.
Locked Signal Logic: Prevents repaints and disappearing trades by confirming signals only once per bar.
Trade Parameters:
Short Entry: Above upper band + overbought RSI + weakening MACD + bearish candle
Long Entry: Below lower band + oversold RSI + strengthening MACD + bullish candle
Take Profit: ±0.75%
Stop Loss: ±0.4%
This setup is tuned for traders using tight risk control and leverage, where execution precision and minimal drawdown tolerance are critical.
Range Filter Strategy [Real Backtest]Range Filter Strategy - Real Backtesting
# Overview
Advanced Range Filter strategy designed for realistic backtesting with precise execution timing and comprehensive risk management. Built specifically for cryptocurrency markets with customizable parameters for different assets and timeframes.
Core Algorithm
Range Filter Technology:
- Smooth Average Range calculation using dual EMA filtering
- Dynamic range-based price filtering to identify trend direction
- Anti-noise filtering system to reduce false signals
- Directional momentum tracking with upward/downward counters
Key Features
Real-Time Execution (No Delay)
- Process orders on tick: Immediate execution without waiting for bar close
- Bar magnifier integration for intrabar precision
- Calculate on every tick for maximum responsiveness
- Standard OHLC bypass for enhanced accuracy
Realistic Price Simulation
- HL2 entry pricing (High+Low)/2 for realistic fills
- Configurable spread buffer simulation
- Random slippage generation (0 to max slippage)
- Market liquidity validation before entry
Advanced Signal Filtering
- Volume-based filtering with customizable ratio
- Optional signal confirmation system (1-3 bars)
- Anti-repetition logic to prevent duplicate signals
- Daily trade limit controls
Risk Management
- Fixed Risk:Reward ratios with precise point calculation
- Automatic stop loss and take profit execution
- Position size management
- Maximum daily trades limitation
Alert System
- Real-time alerts synchronized with strategy execution
- Multiple alert types: Setup, Entry, Exit, Status
- Customizable message formatting with price/time inclusion
- TradingView alert panel integration
Default Parameters
Optimized for BTC 5-minute charts:
- Sampling Period: 100
- Range Multiplier: 3.0
- Risk: 50 points
- Reward: 100 points (1:2 R:R)
- Spread Buffer: 2.0 points
- Max Slippage: 1.0 points
Signal Logic
Long Entry Conditions:
- Price above Range Filter line
- Upward momentum confirmed
- Volume requirements met (if enabled)
- Confirmation period completed (if enabled)
- Daily trade limit not exceeded
Short Entry Conditions:
- Price below Range Filter line
- Downward momentum confirmed
- Volume requirements met (if enabled)
- Confirmation period completed (if enabled)
- Daily trade limit not exceeded
Visual Elements
- Range Filter line with directional coloring
- Upper and lower target bands
- Entry signal markers
- Risk/Reward ratio boxes
- Real-time settings dashboard
Customization Options
Market Adaptation:
- Adjust Sampling Period for different timeframes
- Modify Range Multiplier for various volatility levels
- Configure spread/slippage for different brokers
- Set appropriate R:R ratios for trading style
Filtering Controls:
- Enable/disable volume filtering
- Adjust confirmation requirements
- Set daily trade limits
- Customize alert preferences
Performance Features
- Realistic backtesting results aligned with live trading
- Elimination of look-ahead bias
- Proper order execution simulation
- Comprehensive trade statistics
Alert Configuration
Alert Types Available:
- Entry signals with complete trade information
- Setup alerts for early preparation
- Exit notifications for position management
- Filter direction changes for market context
Message Format:
Symbol - Action | Price: XX.XX | Stop: XX.XX | Target: XX.XX | Time: HH:MM
Usage Recommendations
Optimal Settings:
- Bitcoin/Major Crypto: Default parameters
- Forex: Reduce sampling period to 50-70, multiplier to 2.0-2.5
- Stocks: Reduce sampling period to 30-50, multiplier to 1.0-1.8
- Gold: Sampling period 60-80, multiplier 1.5-2.0
TradingView Configuration:
- Recalculate: "On every tick"
- Orders: "Use bar magnifier"
- Data: Real-time feed recommended
Risk Disclaimer
This strategy is designed for educational and analytical purposes. Past performance does not guarantee future results. Always test thoroughly on paper trading before live implementation. Consider market conditions, broker execution, and personal risk tolerance when using any automated trading system.
Best Settings Found for Gold 15-Minute Timeframe
After extensive testing and optimization, these are the most effective settings I've discovered for trading Gold (XAUUSD) on the 15-minute timeframe:
Core Filter Settings:
Sampling Period: 100
Range Multiplier: 3.0
Professional Execution Engine:
Realistic Entry: Enabled (HL2)
Spread Buffer: 2 points
Dynamic Slippage: Enabled with max 1 point
Volume Filter: Enabled at 1.7x ratio
Signal Confirmation: Enabled with 1 bar confirmation
Risk Management:
Stop Loss: 50 points
Take Profit: 100 points (2:1 Risk-Reward)
Max Trades Per Day: 5
These settings provide an excellent balance between signal accuracy and realistic market execution. The volume filter at 1.7x ensures we only trade during periods of sufficient market activity, while the 1-bar confirmation helps filter out false signals. The spread buffer and slippage settings account for real trading costs, making backtest results more realistic and achievable in live trading.
Range Filter Strategy [Arabic Real Backtest]استراتيجية مرشح النطاق - اختبار واقعي
نظرة عامة
استراتيجية مرشح النطاق المتقدمة مصممة للاختبار الواقعي مع توقيت تنفيذ دقيق وإدارة مخاطر شاملة. تم بناؤها خصيصًا لأسواق العملات الرقمية مع معلمات قابلة للتخصيص لأصول وفترات زمنية مختلفة.
الخوارزمية الأساسية
تقنية مرشح النطاق:
* حساب متوسط النطاق السلس باستخدام فلترة مزدوجة للـ EMA
* فلترة أسعار استنادًا إلى النطاق الديناميكي لتحديد اتجاه الاتجاه
* نظام فلترة ضد الضوضاء لتقليل الإشارات الخاطئة
* تتبع الزخم الاتجاهي مع عدادات للأعلى/للأسفل
الميزات الرئيسية
**التنفيذ الفوري (بدون تأخير)**
* معالجة الأوامر عند كل نقطة: تنفيذ فوري دون انتظار إغلاق الشمعة
* تكامل مكبر الشمعة للحصول على دقة داخل الشمعة
* الحساب في كل نقطة لضمان الاستجابة القصوى
* تجاوز OHLC القياسي لزيادة الدقة
**محاكاة الأسعار الواقعية**
* تسعير الدخول باستخدام HL2 (High+Low)/2 لملء واقعي
* محاكاة للبُعد العازل للسعر القابل للتخصيص
* إنشاء انزلاق عشوائي (من 0 إلى الحد الأقصى للانزلاق)
* التحقق من سيولة السوق قبل الدخول
**فلترة الإشارات المتقدمة**
* فلترة استنادًا إلى الحجم مع نسبة قابلة للتخصيص
* نظام تأكيد الإشارة اختياري (من 1 إلى 3 شموع)
* منطق مضاد للتكرار لمنع الإشارات المكررة
* التحكم في حد التداول اليومي
**إدارة المخاطر**
* نسب ثابتة للمخاطرة: العائد مع حساب دقيق للنقاط
* تنفيذ وقف الخسارة وجني الأرباح تلقائيًا
* إدارة حجم المركز
* تحديد الحد الأقصى للصفقات اليومية
**نظام التنبيهات**
* تنبيهات فورية متزامنة مع تنفيذ الاستراتيجية
* أنواع متعددة من التنبيهات: إعداد، دخول، خروج، حالة
* تخصيص تنسيق الرسائل مع تضمين السعر/الوقت
* تكامل مع لوحة تنبيهات TradingView
المعلمات الافتراضية
محسن لرسوم بيانية لفترة 5 دقائق لبيتكوين:
* فترة العينة: 100
* معامل النطاق: 3.0
* المخاطرة: 50 نقطة
* المكافأة: 100 نقطة (نسبة 1:2)
* بُعد الانتشار: 2.0 نقطة
* الحد الأقصى للانزلاق: 1.0 نقطة
منطق الإشارة
**شروط الدخول الطويل:**
* السعر فوق خط مرشح النطاق
* تأكيد الزخم الصاعد
* تلبية متطلبات الحجم (إذا تم تمكينها)
* اكتمال فترة التأكيد (إذا تم تمكينها)
* لم يتم تجاوز حد الصفقات اليومية
**شروط الدخول القصير:**
* السعر تحت خط مرشح النطاق
* تأكيد الزخم الهابط
* تلبية متطلبات الحجم (إذا تم تمكينها)
* اكتمال فترة التأكيد (إذا تم تمكينها)
* لم يتم تجاوز حد الصفقات اليومية
العناصر البصرية
* خط مرشح النطاق مع تلوين الاتجاه
* الأشرطة العليا والسفلى المستهدفة
* علامات إشارات الدخول
* صناديق نسبة المخاطرة/العائد
* لوحة إعدادات حية
خيارات التخصيص
**التكيف مع السوق:**
* تعديل فترة العينة لبيانات الزمن المختلفة
* تعديل معامل النطاق لمستويات التقلب المختلفة
* تكوين الانتشار/الانزلاق لوسطاء مختلفين
* تحديد النسب المناسبة للمخاطرة/العائد حسب أسلوب التداول
**ضوابط الفلترة:**
* تمكين/تعطيل فلترة الحجم
* تعديل متطلبات التأكيد
* تعيين حدود الصفقات اليومية
* تخصيص تفضيلات التنبيه
الميزات المتعلقة بالأداء
* نتائج اختبار واقعية متوافقة مع التداول المباشر
* القضاء على تحيز المستقبل
* محاكاة تنفيذ الأوامر بشكل صحيح
* إحصائيات تداول شاملة
تكوين التنبيه
**أنواع التنبيهات المتاحة:**
* إشارات الدخول مع معلومات التداول الكاملة
* تنبيهات الإعداد للتحضير المبكر
* إشعارات الخروج لإدارة المراكز
* فلترة التغيرات في الاتجاه لظروف السوق
**تنسيق الرسائل:**
رمز - الإجراء | السعر: XX.XX | الوقف: XX.XX | الهدف: XX.XX | الوقت: HH\:MM
التوصيات لاستخدام الاستراتيجية
**الإعدادات المثلى:**
* بيتكوين/العملات الرقمية الرئيسية: المعلمات الافتراضية
* الفوركس: تقليل فترة العينة إلى 50-70، المعامل إلى 2.0-2.5
* الأسهم: تقليل فترة العينة إلى 30-50، المعامل إلى 1.0-1.8
* الذهب: فترة العينة 60-80، المعامل 1.5-2.0
**تكوين TradingView:**
* إعادة الحساب: "على كل نقطة"
* الأوامر: "استخدام مكبر الشمعة"
* البيانات: يوصى باستخدام التغذية الحية
إخلاء المسؤولية
تم تصميم هذه الاستراتيجية لأغراض تعليمية وتحليلية. الأداء السابق لا يضمن النتائج المستقبلية. يجب دائمًا إجراء اختبارات شاملة على التداول الورقي قبل التنفيذ المباشر. يجب أخذ ظروف السوق، تنفيذ الوسيط، والتحمل الشخصي للمخاطر في الاعتبار عند استخدام أي نظام تداول آلي.
Range Filter Strategy - Real Backtesting
# Overview
Advanced Range Filter strategy designed for realistic backtesting with precise execution timing and comprehensive risk management. Built specifically for cryptocurrency markets with customizable parameters for different assets and timeframes.
Core Algorithm
Range Filter Technology:
- Smooth Average Range calculation using dual EMA filtering
- Dynamic range-based price filtering to identify trend direction
- Anti-noise filtering system to reduce false signals
- Directional momentum tracking with upward/downward counters
Key Features
Real-Time Execution (No Delay)
- Process orders on tick: Immediate execution without waiting for bar close
- Bar magnifier integration for intrabar precision
- Calculate on every tick for maximum responsiveness
- Standard OHLC bypass for enhanced accuracy
Realistic Price Simulation
- HL2 entry pricing (High+Low)/2 for realistic fills
- Configurable spread buffer simulation
- Random slippage generation (0 to max slippage)
- Market liquidity validation before entry
Advanced Signal Filtering
- Volume-based filtering with customizable ratio
- Optional signal confirmation system (1-3 bars)
- Anti-repetition logic to prevent duplicate signals
- Daily trade limit controls
Risk Management
- Fixed Risk:Reward ratios with precise point calculation
- Automatic stop loss and take profit execution
- Position size management
- Maximum daily trades limitation
Alert System
- Real-time alerts synchronized with strategy execution
- Multiple alert types: Setup, Entry, Exit, Status
- Customizable message formatting with price/time inclusion
- TradingView alert panel integration
Default Parameters
Optimized for BTC 5-minute charts:
- Sampling Period: 100
- Range Multiplier: 3.0
- Risk: 50 points
- Reward: 100 points (1:2 R:R)
- Spread Buffer: 2.0 points
- Max Slippage: 1.0 points
Signal Logic
Long Entry Conditions:
- Price above Range Filter line
- Upward momentum confirmed
- Volume requirements met (if enabled)
- Confirmation period completed (if enabled)
- Daily trade limit not exceeded
Short Entry Conditions:
- Price below Range Filter line
- Downward momentum confirmed
- Volume requirements met (if enabled)
- Confirmation period completed (if enabled)
- Daily trade limit not exceeded
Visual Elements
- Range Filter line with directional coloring
- Upper and lower target bands
- Entry signal markers
- Risk/Reward ratio boxes
- Real-time settings dashboard
Customization Options
Market Adaptation:
- Adjust Sampling Period for different timeframes
- Modify Range Multiplier for various volatility levels
- Configure spread/slippage for different brokers
- Set appropriate R:R ratios for trading style
Filtering Controls:
- Enable/disable volume filtering
- Adjust confirmation requirements
- Set daily trade limits
- Customize alert preferences
Performance Features
- Realistic backtesting results aligned with live trading
- Elimination of look-ahead bias
- Proper order execution simulation
- Comprehensive trade statistics
Alert Configuration
Alert Types Available:
- Entry signals with complete trade information
- Setup alerts for early preparation
- Exit notifications for position management
- Filter direction changes for market context
Message Format:
Symbol - Action | Price: XX.XX | Stop: XX.XX | Target: XX.XX | Time: HH:MM
Usage Recommendations
Optimal Settings:
- Bitcoin/Major Crypto: Default parameters
- Forex: Reduce sampling period to 50-70, multiplier to 2.0-2.5
- Stocks: Reduce sampling period to 30-50, multiplier to 1.0-1.8
- Gold: Sampling period 60-80, multiplier 1.5-2.0
TradingView Configuration:
- Recalculate: "On every tick"
- Orders: "Use bar magnifier"
- Data: Real-time feed recommended
Risk Disclaimer
This strategy is designed for educational and analytical purposes. Past performance does not guarantee future results. Always test thoroughly on paper trading before live implementation. Consider market conditions, broker execution, and personal risk tolerance when using any automated trading system.
Dubic EMA StrategyThe Dubic EMA Strategy is a trend-following and volatility-aware strategy that combines dual EMA filters with intelligent range and noise detection to provide clean, actionable entries. It's designed to avoid choppy markets, enhance trade precision, and adapt to different market conditions.
✅ Key Features:
Dual EMA Filter: Enters long when price is above both EMA High & EMA Low, and short when below both.
Range Filter: Avoids entries during tight consolidations or sideways markets.
Volatility Filter: Prevents trading in low-ATR conditions.
Dynamic Risk Management:
ATR-based or fixed % Stop Loss and Take Profit.
Optional Parabolic SAR trailing stop.
One Trade per Trend: Prevents re-entry until trend direction changes.
Unbroken Range Visualization: Detects and displays consolidation zones that can lead to breakouts.
Alerts & Labels: Clean BUY/SELL signals with alerts and chart labels.
🧩 Customization Options:
Adjustable EMA length
Toggle between ATR or % based SL/TP
Volatility threshold
Range detection sensitivity
Enable/disable SAR trailing stop
This strategy works best on trending assets and timeframes with volatility (e.g., crypto, forex, indices). Suitable for both manual trading and automation.
🛠️ Built for clarity, control, and precision.
📈 Backtest, optimize, and deploy with confidence.
[Stratégia] VWAP Mean Magnet v2 (VolSzűrő)Ez a stratégia BTC- oldalazó időszakára van kifejlestve 1 perces chartra.
4H Bollinger Breakout StrategyThis strategy leverages Bollinger Bands on the 4-hour timeframe for long and short trades in trending or ranging markets. Entries trigger on BB breakouts with optional filters for volume, trend, and RSI. Exits occur on opposite BB crosses. Customizable for long-only, short-only, or indicator mode via code comments. Supports forex, stocks, or crypto with full equity allocation and 0.1% commission.
Length (Default: 20): Period for BB basis and std dev; shorter for sensitivity, longer for smoothing.
Basis MA Type (Default: SMA): Selects MA for middle band (SMA, EMA, etc.); EMA for faster response.
Source (Default: Close): Price input for calculations; use close for standard accuracy.
StdDev Multiplier (Default: 1.8): Band width control; higher for fewer signals, lower for more.
Offset (Default: 0): Shifts BB plots; typically unchanged.
Use Filters (Default: True): Applies volume, trend, RSI checks to filter signals.
Volume MA Length (Default: 20): For volume filter (long: >105% avg, short: >120%).
Trend MA Length (Default: 80): SMA for trend filter (long: above MA, short: below).
RSI Length (Default: 14): For short filter (entry if RSI <85).
Use Long/Short Signals (Defaults: True): Toggles directions; long entry on lower BB crossover, short on upper crossunder.
Visuals: BB plots (blue basis, red upper, green lower), orange trend MA, filled background.
Labels/Alerts: Green/red for long entry/exit, yellow/purple for short; alert conditions included.
Combo 2/20 EMA & Bandpass Filter by TamarokDescription:
This strategy combines a 2/20 exponential moving average (EMA) crossover with a custom bandpass filter to generate buy and sell signals.
Use the Fast EMA and Slow EMA inputs to adjust trend sensitivity, and the Bandpass Filter Length, Delta, and Zones to fine-tune momentum turns.
Signals occur when both EMA and BPF agree in direction, with optional reversal and time filters.
How to use:
1. Add the script to your chart in TradingView.
2. Adjust the EMA and BP Filter parameters to match your asset’s volatility.
3. Enable ‘Reverse Signals’ to trade counter-trend, or use the time filter to limit sessions.
4. Set alerts on Long Alert and Short Alert for automated notifications.
Inspiration:
Based on HPotter’s original combo strategy (Stocks & Commodities Mar 2010).
Updated to Pine Script v6 with streamlined code and alerts.
WARNING:
For purpose educate only
Opening-Range BreakoutNote: Default trading date range looks mediocre. Set date range to "Entire History" to see full effect of the strategy. 50.91% profitable trades, 1.178 profit factor, steady profits and limited drawdown. Total P&L: $154,141.18, Max Drawdown: $18,624.36. High R^2
█ Overview
The Opening-Range Breakout strategy is a mechanical, session‑based day‑trading system designed to capture the initial burst of directional momentum immediately following the market open. It defines a user‑configurable “opening range” window, measures its high and low boundaries, then places breakout stop orders at those levels once the range closes. Built‑in filters on minimum range width, reward‑to‑risk ratios, and optional reversal logic help refine entries and manage risk dynamically.
█ How It Works
Opening‑Range Formation
Between 9:30–10:15 AM ET (configurable), the script tracks the highest high and lowest low to form the day’s opening range box.
On the first bar after the range window closes, the range high (OR_high) and low (OR_low) are “locked in.”
Range‑Width Filter
To avoid false breakouts in low‑volatility mornings, the range must be at least X% of the current price (default 0.35%).
If the measured opening-range width < minimum threshold, no orders are placed that day.
Entry & Order Placement
Long: a stop‑buy order at the opening‑range high.
Short: a stop‑sell order at the opening‑range low.
Only one side can trigger (or both if reverse logic is enabled after a losing trade).
Risk Management
Once triggered, each trade uses an ATR‑style stop-loss defined as a percentage retracement of the range (default 50% of range width).
Profit target is set at a configurable Reward/Risk Ratio (default 1.1×).
Optional: Reverse on Stop‑Loss – if the initial breakout loses, immediately reverse into the opposite side on the same day.
Session Exit
Any open positions are closed at the end of the regular trading day (default 3:45 PM ET window end, with hard flat at session close).
Visual cues are provided via green (range high) and red (range low) step‑line plots directly on the chart, allowing you to see the range box and breakout triggers in real time.
█ Why It Works
Early Momentum Capture: The first 15 – 60 minutes of trading encapsulate overnight news digestion and institutional order flow, creating a well‑defined volatility “range.”
Mechanical Discipline: Clear, rule‑based entries and exits remove emotional guesswork, ensuring consistency.
Volatility Filtering: By requiring a minimum range width, the system avoids choppy, low‑range days where false breakouts are common.
Dynamic Sizing: Stops and targets scale with the opening range, adapting automatically to each day’s volatility environment.
█ How to Use
Set Your Instruments & Timeframe
-Apply to any futures contract on a 1‑ to 5‑minute chart.
-Ensure chart timezone is set to America/New_York.
Configure Inputs
-Opening‑Range Window: e.g. “0930-1015” for a 45‑minute range.
-Min. OR Width (%): e.g. 0.35 for 0.35% of current price.
-Reward/Risk Ratio: e.g. 1.1 for a modest profit target above your stop.
-Max OR Retracement %: e.g. 50 to set stop at 50% of range width.
-One Trade Per Day: toggle to limit to a single breakout.
-Reverse on Stop Loss: toggle to flip direction after a losing breakout.
Monitor the Chart
-Watch the green and red range boundaries form during the session open.
-Orders will automatically submit on the first bar after the range window closes, conditioned on your filters.
Review & Adjust
-Backtest across multiple months to validate performance on your preferred contract.
-Tweak range duration, minimum width, and R/R multiple to fit your risk tolerance and desired win‑rate vs. expectancy balance.
█ Settings Reference
Input Defaults
Opening‑Range Window - Time window to form OR (HHMM-HHMM) - 0930–1015
Regular Trading Day - Full session for EOD flat (HHMM-HHMM) - 0930–1545
Min. OR Width (%) - Minimum OR size as % of close to trigger orders - 0.35
Reward/Risk Ratio - Profit target multiple of stop‑loss distance - 1.1
Max OR Retracement (%) - % of OR width to use as stop‑loss distance - 50
One Trade Per Day - Limit to a single breakout order per day - false
Reverse on Stop Loss - Reverse direction immediately after a losing trade - true
Disclaimer
This strategy description and any accompanying code are provided for educational purposes only and do not constitute financial advice or a solicitation to trade. Futures trading involves substantial risk, including possible loss of capital. Past performance is not indicative of future results. Traders should assess their own risk tolerance and conduct thorough backtesting and forward-testing before committing real capital.
ALMA Optimized Strategy - Volatility Filter + UT BotThe strategy you provided is an ALMA Optimized Strategy implemented in Pine Script™ version 5 for TradingView. Here is a brief English summary of what it is and how it works:
It is a trend-following strategy combining multiple technical indicators to optimize trade entries and exits.
The core moving average used is the ALMA (Arnaud Legoux Moving Average), known for smoother and less lagging price smoothing compared to traditional EMAs or SMAs.
The strategy also uses other indicators:
Fast EMA (Exponential Moving Average)
EMA 50
ATR (Average True Range) for volatility measurement and dynamic stop loss and take profit levels
RSI (Relative Strength Index) for momentum with overbought/oversold levels
ADX (Average Directional Index) for confirming trend strength
Bollinger Bands as a volatility filter
Buy signals trigger when volatility is sufficient (ATR filter), price is above EMA 50 and ALMA, RSI indicates bullish momentum, ADX confirms trend strength, price is below the upper Bollinger Band, and there is a cooldown period to prevent repeated buys within a short time.
Sell signals are generated when price crosses below the fast EMA.
The strategy manages position entries and exits dynamically, applying ATR-based stop loss and take profit levels, and optionally a time-based exit.
Additionally, the script integrates the UT Bot, an ATR-based trailing stop and signal system, enhancing trade exit precision.
Buy and sell signals are visually marked on the chart with colored triangles for easy identification.
In essence, this strategy blends advanced smoothing (ALMA) with volatility filters and trend/momentum indicators to generate reliable buy and sell signals, while managing risk dynamically through ATR-based stops and profit targets. It aims to adapt to changing market conditions by filtering noise and confirming trends before entering trades.
Intraday Combo Strategy HHStochastic RSI Momentum/Reversal quickly identifies overbought/oversold zones
MACD Momentum/Trend confirms a trend reversal, a late but powerful signal
Supertrend Trend Tracking provides clear and concise buy/sell signals
Bollinger Bands Volatility shows price deviation during breakouts/squeezes
ADX Trend Strength measures trend strength to filter out false signals
Setup: Smooth Gaussian + Adaptive Supertrend (Manual Vol)Overview
This strategy combines two powerful trend-based tools originally developed by Algo Alpha: the Smooth Gaussian Trend (simulated) and the Adaptive Supertrend. The objective is to capture sustained bullish movements in periods of controlled volatility by filtering for high-probability entries.
Entry Logic
Long Entry Conditions:
The closing price is above the Smooth Gaussian Trend line (with length = 75), and
The volatility setting from the Adaptive Supertrend is manually defined as either 2 or 3
Exit Condition:
The closing price falls below the Smooth Gaussian Trend line
This script uses a simulated version of the Gaussian Trend line via double-smoothed SMA, as the original Algo Alpha indicator is protected and cannot be accessed directly in code.
Features
Plots entry and exit signals directly on the chart
Manual toggle to enable or disable the volatility filter
Lightweight design to allow flexible backtesting even without access to proprietary indicators
Important Note
This strategy does not connect to the actual Adaptive Supertrend from Algo Alpha. Users must manually input the volatility level based on what they observe on the chart when the original indicator is also applied. The Smooth Gaussian Trend is approximated and may differ slightly from the original.
Suggested Use
Recommended timeframes: 1H, 4H, or Daily
Best used alongside the original indicators displayed on the chart
Consider incorporating additional structure, momentum, or volume filters to enhance performance
If you have suggestions or would like to contribute improvements, feel free to reach out or fork the script.
