在腳本中搜尋"high low"
Stochastic Momentum multi. strategyThe Stochastic Momentum Index (Stoch MTM, SMI) is based on the Stochastic Oscillator. The difference is that the Stochastic Oscillator calculates where the close is relative to the high/low range, while the SMI calculates where the close is relative to the midpoint of the high/low range. The values of the SMI range from +100 to -100. When the close is greater than the midpoint, the SMI is above zero, when the close is less than than the midpoint, the SMI is below zero.
The SMI is interpreted the same way as the Stochastic Oscillator. Extreme high/low SMI values indicate overbought/oversold conditions. A buy signal is generated when the SMI rises above -50, or when it crosses above the signal line. A sell signal is generated when the SMI falls below +50, or when it crosses below the signal line. Also look for divergence with the price to signal the end of a trend or indicate a false trend.
The Stochastic Momentum Index was developed by William Blau and was introduced in his article in the January, 1993 issue of Technical Analysis of Stocks & Commodities magazine.
Chaikin Volatility Strategy Backtest Chaikin's Volatility indicator compares the spread between a security's
high and low prices. It quantifies volatility as a widening of the range
between the high and the low price.
You can use in the xPrice1 and xPrice2 any series: Open, High, Low, Close, HL2,
HLC3, OHLC4 and ect...
You can change long to short in the Input Settings
Please, use it only for learning or paper trading. Do not for real trading.
EMA 12-26-100 Momentum Strategy# Triple EMA Multi-Signal Momentum Strategy
## 📊 Overview
**Triple EMA Multi-Signal** is a comprehensive trend-following momentum strategy designed specifically for cryptocurrency markets. It combines multiple technical indicators and signal types to identify high-probability trading opportunities while maintaining strict risk management protocols.
The strategy excels in trending markets and uses adaptive position sizing with trailing stops to maximize profits during strong trends while protecting capital during choppy conditions.
## 🎯 Core Algorithm
### Triple EMA System
The strategy employs a three-layer EMA system to identify trend direction and strength:
- **Fast EMA (12)**: Quick response to price changes
- **Slow EMA (26)**: Confirmation of trend direction
- **Trend EMA (100)**: Overall market bias filter
Trades are only taken when all three EMAs align in the same direction, ensuring we trade with the dominant trend.
### Multi-Signal Confirmation (8 Signal Types)
The strategy requires at least 1-2 confirmed signals from multiple independent sources before entering a position:
1. **EMA Crossover** - Fast EMA crossing Slow EMA (primary signal)
2. **MACD Cross** - MACD line crossing signal line (momentum confirmation)
3. **RSI Reversal** - RSI bouncing from oversold/overbought zones
4. **Price Action** - Strong bullish/bearish candles (>60% of range)
5. **Volume Spike** - Above-average volume confirmation
6. **Breakout** - Price breaking 20-period high/low with volume
7. **Pullback to EMA** - Trend continuation after healthy retracement
8. **Bollinger Bounce** - Price bouncing from BB bands
This multi-signal approach significantly reduces false signals and improves win rate.
## 💰 Risk Management
### Position Sizing
- Default: 20-25% of equity per trade
- Adjustable based on risk tolerance
- Smaller positions recommended for leveraged trading
### Stop Loss & Take Profit
- **Stop Loss**: 2.0% (tight control of risk)
- **Take Profit**: 5.5% (2.75:1 reward-to-risk ratio)
- Both levels are fixed at entry to avoid emotional decisions
### Trailing Stop System
- Activates after 1.8% profit
- Trails at 1.3% below current price
- Locks in profits during extended trends
- Automatically adjusts as price moves in your favor
### Maximum Hold Time
- 36-48 hours maximum (configurable)
- Designed to minimize funding rate costs on futures
- Forces position closure to avoid excessive exposure
- Helps maintain capital velocity
## 📈 Key Features
### Trend Filters
- **ADX Filter**: Ensures sufficient trend strength (threshold: 20)
- **EMA Alignment**: All three EMAs must confirm trend direction
- **RSI Boundaries**: Avoids extreme overbought/oversold entries
### Volume Analysis
- Volume must exceed 20-period moving average
- Configurable multiplier (default: 1.0x)
- Helps identify institutional participation
### Automatic Exit Conditions
1. Take Profit target reached
2. Stop Loss triggered
3. Trailing stop activated
4. Trend reversal (EMA cross in opposite direction)
5. Maximum hold time exceeded
## 🎮 Recommended Settings
### For Spot Trading (Conservative)
```
Position Size: 15-20%
Stop Loss: 2.5%
Take Profit: 6.0%
Max Hold: 72 hours
Leverage: 1x
```
### For Futures 3-5x Leverage (Balanced)
```
Position Size: 12-15%
Stop Loss: 2.0%
Take Profit: 5.5%
Max Hold: 36 hours
Trailing: Active
```
### For Aggressive Trading 5-10x (High Risk)
```
Position Size: 8-12%
Stop Loss: 1.5%
Take Profit: 4.5%
Max Hold: 24 hours
ADX Filter: Disabled
```
## 📊 Performance Metrics
### Backtested Results (BTC/USDT 1H, 2 years)
- **Total Return**: ~19% (spot) / ~75% (5x leverage)*
- **Total Trades**: 240-300
- **Win Rate**: 49-52%
- **Profit Factor**: 1.25-1.50
- **Max Drawdown**: ~18-22%
- **Average Trade**: 0.5-3 days
*Leverage results exclude funding rates and real-world slippage
### Optimal Timeframes
- **1 Hour**: Best for active trading (recommended)
- **4 Hour**: More stable, fewer signals
- **15 Min**: High frequency (requires monitoring)
### Best Performing Assets
- BTC/USDT (most tested)
- ETH/USDT
- Major altcoins with good liquidity
- Not recommended for low-cap or illiquid pairs
## ⚙️ How to Use
1. **Add to Chart**: Apply strategy to 1H BTC/USDT chart
2. **Adjust Settings**: Configure risk parameters based on your preference
3. **Review Signals**: Green = Long, Red = Short, labels show signal count
4. **Monitor Performance**: Check strategy tester for detailed statistics
5. **Optimize**: Use strategy optimization to find best parameters for your market
## 🎨 Visual Indicators
The strategy provides clear visual feedback:
- **EMA Lines**: Blue (Fast), Red (Slow), Orange (Trend)
- **BUY/SELL Labels**: Show entry points with signal count
- **Stop/Target Lines**: Red (SL), Green (TP) displayed during active trades
- **Background Color**: Light green (long), light red (short) when in position
- **Info Panel**: Shows current trend, RSI, ADX, and volume status
## ⚠️ Important Notes
### Risk Disclaimer
- This strategy is for educational purposes only
- Past performance does not guarantee future results
- Cryptocurrency trading involves substantial risk
- Only trade with capital you can afford to lose
- Always use proper position sizing and risk management
### Limitations
- Performs poorly in sideways/choppy markets
- Requires sufficient liquidity for best execution
- Backtests do not include:
- Real-world slippage (especially during volatility)
- Funding rates (for perpetual futures)
- Exchange downtime or connection issues
- Emotional trading decisions
### For Futures Trading
If using this strategy on futures with leverage:
- Reduce position size proportionally to leverage
- Account for funding rates (~0.01% per 8h)
- Set max hold time to minimize funding costs
- Use lower leverage (3-5x max recommended)
- Monitor liquidation price carefully
## 🔧 Customization
All parameters are fully customizable:
- EMA periods (fast/slow/trend)
- MACD settings (12/26/9)
- RSI levels (30/70)
- Stop Loss / Take Profit percentages
- Trailing stop activation and offset
- Volume multiplier
- ADX threshold
- Maximum hold time
## 📚 Strategy Logic
The strategy follows this decision tree:
```
1. Check Trend Direction (EMA alignment)
↓
2. Scan for Entry Signals (8 types)
↓
3. Confirm with Filters (ADX, Volume, RSI)
↓
4. Enter Position with Fixed SL/TP
↓
5. Monitor for Exit Conditions:
- TP Hit → Close with profit
- SL Hit → Close with loss
- Trailing Active → Follow price
- Trend Reversal → Close position
- Max Time → Force close
```
## 🎓 Best Practices
1. **Start Conservative**: Use smaller position sizes initially
2. **Track Performance**: Monitor actual vs backtested results
3. **Optimize Regularly**: Market conditions change, adapt parameters
4. **Combine with Analysis**: Don't rely solely on automated signals
5. **Manage Emotions**: Stick to the system, avoid manual overrides
6. **Paper Trade First**: Test on demo before risking real capital
## 📞 Support & Updates
This strategy is actively maintained and updated based on:
- Market condition changes
- User feedback and suggestions
- Performance optimization
- Bug fixes and improvements
## 🏆 Conclusion
Triple EMA Multi-Signal Strategy offers a robust, systematic approach to cryptocurrency trading by combining trend following, momentum indicators, and strict risk management. Its multi-signal confirmation system helps filter false signals while the trailing stop mechanism captures extended trends.
The strategy is suitable for both manual traders looking for high-probability setups and algorithmic traders seeking a proven systematic approach.
**Remember**: No strategy wins 100% of the time. Success comes from consistent application, proper risk management, and continuous adaptation to changing market conditions.
---
*Version: 1.0*
*Last Updated: November 2025*
*Tested on: BTC/USDT, ETH/USDT (1H, 4H timeframes)*
*Recommended Capital: $5,000+ for optimal position sizing*
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)
[3Commas] Alligator StrategyThe Alligator Strategy
🔷 What it does: This script implements the Alligator Strategy, a trend-following method created by Bill Williams. It uses three customizable moving averages (SMMAs or RMAs) "Jaws," "Teeth," and "Lips" to identify market trends and potential trade opportunities. Additionally, it includes built-in stop-loss and take-profit options for enhanced risk management.
🔷 Who is it for:
Trend Traders: Those who prefer trading in markets with clear directional movement.
Advanced Users: Traders who require customizable tools and dynamic risk management features.
Beginners: Accessible to those new to trading, thanks to its intuitive visual representation of trends and pre-configured settings.
Bot Users: Supports direct signal integration for bot automation, including entries, take-profits, and stop-losses.
🔷 How does it work: The Alligator Jaws, Teeth, and Lips are smoothed moving averages (SMA, EMA, RMA, or WMA) calculated based on the selected source price ( hl2 = (high+low)/2 by default). Their lengths and offsets are customizable:
Jaws: Length 21 , offset 13.
Teeth: Length 13, offset 8.
Lips: Length 8 , offset 5.
When the lines align and spread apart (e.g., Lips > Teeth > Jaws for an uptrend), the strategy identifies a trending market.
Entry Conditions:
Long Trades: Triggered when Close > Lips > Teeth > Jaws.
Short Trades: Triggered when Close < Lips < Teeth < Jaws.
🔷 Why it’s unique:
Customization: Flexible settings for moving average types and lengths to adapt to different market conditions and strategy tester configurations.
Built-in Filters: Trend filters that can reduce false signals in certain scenarios, making it more reliable for trending markets.
Take Profit and Stop Loss:
Configurable as either percentage-based or dynamic.
Stop-loss levels adjust dynamically using the Alligator lines.
Fast exit logic moves the stop-loss closer to the price when trades are in profit.
3Commas Bot Compatibility: Designed for automated trading, allowing traders to configure and execute the strategy seamlessly.
🔷 Considerations Before Using the Indicator
🔸Why the Forward Offset: By shifting the averages forward, the Alligator helps traders focus on established trends while filtering out short-term market noise.
The standard configurations of 13-8, 8-5, and 5-3 were selected based on Bill Williams’ studies of market behavior. However, these values can be adjusted to suit different market conditions:
Volatile Markets: Faster settings (e.g., 10-6, 6-4, 3-2) may provide earlier signals.
Less Volatile Markets: Slower settings (e.g., 21-13, 13-8, 8-5) can help avoid noise and reduce false signals.
🔸Best Timeframes to Use: The Alligator can be applied across all timeframes, but certain timeframes offer better reliability.
Higher Timeframes (H4, D1, W1): Ideal for identifying significant trends and for swing or position trading.
Lower Timeframes: Not recommended due to increased noise but may work for scalping with additional confirmation tools.
🔸Disadvantages of the Alligator Strategy:
Exhausted Entry Levels: High buying levels or low selling levels can lead to momentum exhaustion and potential pullbacks.
False Signals in Ranges: Consolidating markets can produce unreliable signals.
Lagging Indicator: As it is based on moving averages, it may delay reacting to sudden price changes.
🔸Advantages of the Alligator Strategy:
Trend Focused: Simplifies the identification of trending markets.
Noise Reduction: Forward shifts and smoothed averages help filter out short-term price fluctuations.
Broad Applicability: Suitable for forex, crypto, stocks, and commodities.
🔸Important Considerations:
While the Alligator Strategy provides a systematic way to analyze markets, it does not guarantee successful outcomes. Results in trading depend on multiple factors, including market conditions, trader discipline, and risk management. Past performance of the strategy does not ensure future success, and traders should always approach the market with caution.
Risk Management: Define stop-loss levels, position size, and profit targets before entering any trade. Be prepared for the possibility of losses and ensure that your approach aligns with your overall trading plan.
🔷 STRATEGY PROPERTIES
Symbol: BINANCE:BTCUSDT (Spot).
Timeframe: 1D (Daily Timeframe).
Test Period: All historical data available.
Initial Capital: 10000 USDT.
Order Size per Trade: 1% of Capital, you can use a higher value e.g. 5%, be cautious that the Max Drawdown does not exceed 10%, as it would indicate a very risky trading approach.
Commission: Binance commission 0.1%, adjust according to the exchange being used, lower numbers will generate unrealistic results. By using low values e.g. 5%, it allows us to adapt over time and check the functioning of the strategy.
Slippage: 5 ticks, for pairs with low liquidity or very large orders, this number should be increased as the order may not be filled at the desired level.
Margin for Long and Short Positions: 100%.
Indicator Settings: Default Configuration.
Alligator: Source hl2 | Calculation RMA | Jaw 21-13, Teeth 13-8, Lips 8-5.
Strategy: Long & Short.
Max Stop Loss per Trade: 10% of Trade Size.
Exit trades on opposite signal: Enable.
Alligator Stop Loss: Enable.
Alligator Fast Exit: Enable.
🔷 STRATEGY RESULTS
⚠️ Remember, past results do not guarantee future performance.
Net Profit: +355.68 USDT (+3.56%).
Total Closed Trades: 103.
Percent Profitable: 47.57%.
Profit Factor: 1.927.
Max Drawdown: -57.99 USDT (-0.56%).
Average Trade: +3.45 USDT (+3.41%).
Average # Bars in Trades: 16.
🔷 HOW TO USE
🔸Adjust the Alligator Settings:
The default values generally work well: Source hl2 | Calculation RMA | Jaw 21-13, Teeth 13-8, Lips 8-5. However, if you want to use it on timeframes smaller than 4H (4 hours), consider increasing the values to better filter market noise.
Please review the "Indicator Settings" section for configuration.
🔸Choose a Symbol that Typically Trends:
Select an asset that tends to create trends. However, the Strategy Tester results may display poor performance, making it less suitable for sending signals to bots.
🔸Add Trend Filters:
You can enable trend filters like MA and SuperTrend. By default, these are disabled as they are often unnecessary, but you can experiment with their configuration to see if they optimize the strategy's results.
Please review the "Indicator Settings" section for configuration.
🔸Enable Stop Loss Levels:
Activate Stop Loss features, such as Stop Loss % or Alligator Stop Loss. If both are enabled, the one closest to the price during the trade will be applied.
Please review the "Indicator Settings" section for configuration.
🔸Enable Take Profit Levels:
Activate Take Profit options, such as Take Profit % or Alligator Fast Exit. If both are enabled, the one that triggers first will be executed.
Please review the "Indicator Settings" section for configuration.
This is an example with the default settings and how Alligator Stop Loss and Alligator Fast Exit are activated:
In this example, we additionally enable the Take Profit at 10%. We can observe that the Alligator Stop Loss is the active one since it is closer to the price. When the price moves 10% in favor or against the trade, the position is closed. Although the Alligator Fast Exit is enabled, it does not activate because the trades are closed beforehand.
🔸Results Review:
It is important to check the Max Drawdown. This value should ideally not exceed 10% of your capital. Consider adjusting the trade size to ensure this threshold is not surpassed.
Remember to include the correct values for commission and slippage according to the symbol and exchange where you are conducting the tests. Otherwise, the results will not be realistic.
If you are satisfied with the results, you may consider automating your trades. However, it is strongly recommended to use a small amount of capital or a demo account to test proper execution before committing real funds.
🔸Create alerts to trigger the DCA Bot
Verify Messages: Ensure the message matches the one specified by the DCA Bot.
Multi-Pair Configuration: For multi-pair setups, enable the option to add the symbol in the correct format.
Signal Settings: Enable whether you want to receive long or short signals (Entry | TP | SL), copy and paste the the messages for the DCA Bots configured in 3Commas.
Alert Setup:
When creating an alert, set the condition to the indicator and choose "alert() function call only.
Enter any desired Alert Name.
Open the Notifications tab, enable Webhook URL, and paste the Webhook URL from 3Commas.
For more details, refer to the 3Commas section: "How to use TradingView Custom Signals.
Finalize Alerts: Click Create, you're done! Alerts will now be sent automatically in the correct format to 3Commas.
🔷 INDICATOR SETTINGS
🔸Alligator Settings
MA's source: Source price for Alligator moving averages.
MA's Type: Type of calculation for MA's.
Jaw and Offset: Jaw length and offset to the right.
Teeth and Offset: Teethlength and offset to the right.
Lips and Offset: Lips length and offset to the right.
🔸Alligator Style
Plot Alligator: Show Alligator Ribbon.
Plot MA's: Show Alligator MA's.
Colors: Main and Gradient Colors for Bullish Alligator, Berish Alligator, Neutral Alligator. For gradient colors it is recommended to use an opacity of 15.
🔸MA & SuperTrend Filters
MA & Plot: Activate MA Filter and Plot MA on the chart.
Long Entries: When activated, it will only execute entries if the price is above the MA
Short Entries: When activated, it will only execute entries if the price is below the MA.
Source: Source price for moving average calculations.
Length: Candles to be used by the MA calculations.
Type: Type of calculation for MA.
Timeframe: Here you can select a larger timeframe for the filter.
ST & Plot: Activate SuperTrend Filter and Plot SuperTrend on the chart.
Long Entries: When activated, it will only execute entries if the price is above the SuperTrend.
Short Entries: When activated, it will only execute entries if the price is below the SuperTrend.
Source: Source price for SuperTrend calculations.
Length: Candles to be used by the SuperTrend calculations.
Factor: ATR multiplier of the SuperTrend.
Timeframe: Here you can select a larger timeframe for the filter.
🔸Strategy Tester
Strategy: Order Type direction in which trades are executed.
Take Profit %: When activated, the entered value will be used as the Take Profit in percentage from the entry price level.
Stop Loss %: When activated, the entered value will be used as the Stop Loss in percentage from the entry price level. If Alligator Stop Loss is activated, the closest one to the price will be used.
Exit trades on opposite signal: This option closes the trade if the opposite condition is met. For instance, if we are in a long position and a sell signal is triggered, the long position will be closed, and a short position will be opened. The same applies inversely.
Alligator Stop Loss: In a long trade, the lower part of the Alligator indicator will be used as a dynamic stop loss. Similarly, in a short trade, the upper part of the indicator will be used.
Alligator Fast Exit: Its purpose is to attempt to protect movements in favor of the trade's direction. In the case of long trades, once the price and the upper part of the Alligator indicator are above the trade's entry price, the stop loss will be moved to the upper part. For short trades, once the price and the lower part of the Alligator indicator are below the trade's entry price, the stop loss will be moved to the lower part of the Alligator indicator.
Alligator Squeeze Entry: When activated, entries will only be executed if they meet the condition after a neutral zone of the Alligator indicator.
Alligator Squeeze Exit: When this option is activated, any open trades will be closed when the Alligator indicator enters a neutral mode.
Use Custom Test Period: When enabled signals only works in the selected time window. If disabled it will use all historical data available on the chart.
Test Start and End: Once the Custom Test Period is enabled, here you select the start and end date that you want to analyze.
🔸3Commas DCA Bot Signals
Check Messages: Enable the table to review the messages to be sent to the bot.
Entry | TP | SL: Enable this options to send Buy Entry, Take Profit (TP), and Stop Loss (SL) signals to 3Commas.
Deal Entry and Deal Exit : Copy and paste the message for the deal start signal and close order at Market Price of the DCA Bot you created in 3Commas. This is the message that will be sent with the alert to the Bot, you must verify that it is the same as the 3Commas bot so that it can process properly so that it executes and starts the trade.
DCA Bot Multi-Pair: You must activate it if you want to use the signals in a DCA Bot Multi-pair in the text box you must enter (using the 3Commas format) the symbol in which you are creating the alert, you can check the format of each symbol when you create the bot.
🔷 CONCLUSION
The Alligator Strategy is a valuable tool for identifying potential trends and improving decision-making. However, no trading strategy is foolproof. Careful consideration of market conditions, proper risk management, and personal trading goals are essential. Use the Alligator as part of a broader trading system, and remember that consistent learning and discipline are key to success in trading.
👨🏻💻💭 We hope this tool helps enhance your trading. Your feedback is invaluable, so feel free to share any suggestions for improvements or new features you'd like to see implemented.
____________________________________________________________________
The information and publications within the 3Commas TradingView account are not meant to be and do not constitute financial, investment, trading, or other types of advice or recommendations supplied or endorsed by 3Commas and any of the parties acting on behalf of 3Commas, including its employees, contractors, ambassadors, etc.
SSL ST Strategy – Accuracy Enhanced v2.0 (Parser Safe)This strategy is built to identify high-probability trend breakouts using a combination of SSL Channel, Baseline, Hull / EMA signals, and Candle-based confirmations.
The goal is to filter noise, avoid false breakouts, and enter only when the trend is truly shifting.
This strategy identifies high-probability trend breakouts using SSL Channel, Baseline, Hull/EMA, and candle
confirmations.
1. SSL shows trend shift when price breaks high/low levels.
2. Baseline filters direction (price above = buy bias, below = sell bias).
3. Hull/EMA gives early momentum confirmation.
4. Candle breakout ensures real momentum (breaks previous high/low).
5. Optional filters: ATR, reversal logic, continuation entries.
6. Exits occur on SSL flip, baseline cross, or weakness
Disclaimer
This strategy is provided strictly for educational and informational purposes only. It does not guarantee any profit, nor does it protect against losses of any kind. Financial markets are inherently unpredictable, and any market movement can only be assumed or estimated with a probability that is never guaranteed and can often be no better than a 50/50 chance.
By using this strategy, you acknowledge that all trading decisions are made solely at your own risk. I am not liable for any profits, losses, or financial consequences incurred by anyone using or relying on this strategy. Always perform your own research, manage your risk responsibly, and consult with a qualified financial advisor before trading.
Titan EMA Liquidity [Stansbooth]
🔥 Precision EMA + FVG Liquidity Sweep System
Advanced Buy/Sell Signal Engine for High-Probability Trade Entries
Unlock a new level of precision with this all-in-one market structure indicator built for traders who demand accuracy, clarity, and confidence.
This tool combines EMA trend filtration , Fair Value Gap (FVG) detection , and liquidity sweep analysis to deliver powerful buy and sell signals that align with institutional price behavior.
✅ Key Features
Dynamic EMA Trend Filter:
Identifies true trend direction and filters out low-quality trades. Signals only trigger when momentum aligns with higher-timeframe directional bias.
Smart FVG Detection:
Automatically highlights bullish and bearish Fair Value Gaps, helping you spot premium/discount zones where institutional traders seek entries.
Liquidity Sweep Identification:
Detects equal highs/lows, stop hunts, and engineered liquidity grabs—then confirms reversals when price sweeps liquidity and returns inside structure.
High-Accuracy Signal Engine:
Buy/Sell alerts trigger only when three layers agree:
1. EMA trend alignment
2. FVG confirmation
3. Liquidity sweep completion
This results in cleaner signals , fewer false entries, and strong trend continuation setups.
Optimized for All Market Conditions:
Works for scalping, day trading, and swing trading across Forex, Crypto, Indices, and Stocks.
What This Indicator Helps You Achieve
Capture smart-money style entries with reduced drawdown
Enter after liquidity grabs instead of before them
Avoid chop with EMA-filtered market direction
Spot precision premium/discount zones using automatic FVG mapping
Obtain high-confidence Buy/Sell signals based on institutional concept
Why Traders Love It
This system isn’t just another signal generator—it’s a market-structure aware model that reads the chart the same way professional traders do.
Every signal is based on probability stacking , giving you the clarity and confidence to take the best setups while ignoring noise.
Stratégie SMC V18.2 (BTC/EUR FINAL R3 - Tendance)This strategy is an automated implementation of Smart Money Concepts (SMC), designed to operate on the Bitcoin/Euro (BTC/EUR) chart using the 15-minute Timeframe (M15).It focuses on identifying high-probability zones (Order Blocks) after a confirmed Break of Structure (BOS) and a Liquidity Sweep, utilizing an H1/EMA 200 trend filter to only execute trades in the direction of the dominant market flow.Risk management is strict: every trade uses a fixed Risk-to-Reward Ratio (R:R) of 1:3.🧱 Core Logic Components
1. Trend Filter (H1/EMA 200)Objective: To avoid counter-trend entries, which has allowed the success rate to increase to nearly $65\%$ in backtests.Mechanism: A $200$-period EMA is plotted on a higher timeframe (Default: H1/60 minutes).Long (Buy): Entry is only permitted if the current price (M15) is above the trend EMA.Short (Sell): Entry is only permitted if the current price (M15) is below the trend EMA.
2. Order Block (OB) DetectionA potential Order Block is identified on the previous candle if it is
accompanied by an inefficiency (FVG - Fair Value Gap).
3. Advanced SMC ValidationBOS (Break of Structure): A recent BOS must be confirmed by breaking the swing high/low defined by the swing length (Default: 4 M15 candles).Liquidity (Liquidity Sweep): The Order Block zone must have swept recent liquidity (defined by the Liquidity Search Length) within a certain tolerance (Default: $0.1\%$).Point of Interest: The OB must form in a premium zone (for shorts) or a discount zone (for longs) relative to the current swing range (above or below the $50\%$ level of the range).
4. Execution and Risk ManagementEntry: The trade is triggered when the price touches the active Order Block (mitigation).Stop Loss (SL): The SL is fixed at the low of the OB (for longs) or the high of the OB (for shorts).Take Profit (TP): The TP is strictly set at a level corresponding to 3 times the SL distance (R:R 1:3).Lot Sizing: The trade quantity is calculated to risk a fixed amount (Default: 2.00 Euros) per transaction, capped by a Lot Max and Lot Min defined by the user.
Input Parameters (Optimized for BTC/EUR M15)Users can adjust these parameters to modify sensitivity and risk profile. The default values are those optimized for the high-performing backtest (Profit Factor $> 3$).ParameterDescriptionDefault Value (M15)Long. Swing (BOS)Candle length used to define the swing (and thus the BOS).4Long. Recherche Liq.Number of candles to scan to confirm a liquidity sweep.7Tolérance Liq. (%)Price tolerance to validate the liquidity sweep (as a percentage of price).0.1Timeframe TendanceChart timeframe used for the EMA filter (e.g., 60 = H1).60 (H1)Longueur EMA TendancePeriods used for the trend EMA.200Lot Max (Quantité Max BTC)Maximum quantity of BTC the strategy is allowed to trade.0.01Lot Min Réel (Exigence Broker)Minimum quantity required by the broker/exchange.0.00001
Volume Momentum Strategy [MA/VWAP Cross]Deconstructing the Volume Momentum Strategy: An Analysis of MA-VWAP Cross Mechanics
Introduction
The "Volume Momentum Strategy " is a technical trading algorithm programmed in Pine Script v6 for the TradingView platform. At its core, the strategy is a trend-following system that utilizes the interaction between a specific Moving Average (MA) and the Volume Weighted Average Price (VWAP) to generate trade signals. While the primary execution logic relies on price crossovers, the strategy incorporates a sophisticated secondary layer of analysis using the Commodity Channel Index (CCI) and Stochastic Oscillator. Uniquely, these secondary indicators are applied to volume data rather than price, serving as a gauge for market participation and momentum intensity.
The Core Engine: MA and VWAP Crossover
The primary engine driving the strategy's buy and sell decisions is the crossover relationship between a user-defined Moving Average and the VWAP.
1. The Anchor (VWAP): The strategy calculates the Volume Weighted Average Price based on the HLC3 (High, Low, Close divided by 3) source. VWAP serves as the dynamic benchmark for "fair value" throughout the trading session.
2. The Trigger (Moving Average): The script allows for flexibility in defining the "fast" line, offering options such as Simple (SMA), Exponential (EMA), or Hull Moving Averages.
3. The Signal:
o A Long (Buy) signal is generated when the chosen MA crosses over the VWAP. This suggests that short-term price momentum is exceeding the average volume-weighted price of the session, indicating bullish sentiment.
o A Short (Sell) signal is generated when the MA crosses under the VWAP, indicating bearish pressure where price is being pushed below the session's volume-weighted average.
The Role of CCI and Stochastic: Analyzing Volume Momentum
The prompt specifically inquires about how the CCI and Stochastic indicators fit into this process. In standard technical analysis, these oscillators are used to identify overbought or oversold price conditions. However, this strategy repurposes them to analyze Volume Momentum.
1. The Calculation
Instead of using close prices as the input source, the script passes volume data into both indicator functions:
• Volume CCI: Calculated as ta.cci(volume, cciLength). This measures the deviation of current volume from its statistical average.
• Volume Stochastic: Calculated as ta.stoch(volume, volume, volume, stochLength). This gauges the current volume relative to its recent range.
2. The "Volume Spike" Condition
The strategy combines these two indicators to define a specific market condition labeled isVolumeSpike. A volume spike is confirmed only when both conditions are met simultaneously:
• The Volume CCI must be greater than a defined threshold (default: 100).
• The Volume Stochastic must be greater than a defined threshold (default: 80).
3. Integration into the Process
It is critical to note how this script currently applies this "Volume Spike" logic:
• Visual Confirmation: In the current version of the code, the isVolumeSpike boolean is used strictly for visual feedback. When a spike is detected, the script paints the specific price bar yellow and plots a small triangle marker below the bar.
• Strategic Implication: While the code calculates these metrics, the variables long_condition and short_condition currently rely solely on the MA/VWAP crossover. The developer has left the volume logic as a visual overlay, noting in the comments that it serves as a "visual/alert" or a potential filter.
• Potential Alpha: Conceptually, this setup implies that a trader should look for the MA/VWAP crossover to occur coincidentally with—or shortly after—a "Volume Spike" (yellow bar). This would confirm that the price move is backed by significant institutional participation (volume) rather than just retail noise.
Risk Management and Time Constraints
The strategy wraps these technical signals in a robust risk management framework. It includes hard-coded time windows (start/stop trading times) and a "Close All" function to prevent holding positions overnight. Furthermore, it employs both percentage-based and dollar-based Stop Loss and Take Profit mechanisms, ensuring that every entry—whether generated by a high-momentum crossover or a standard trend move—has a predefined exit plan.
Conclusion
The "Volume Momentum Strategy" is a hybrid system. It executes trades based on the reliable trend signal of MA crossing VWAP but informs the trader with advanced volume analytics. By processing volume through the CCI and Stochastic calculations, it provides a "heads-up" display regarding the intensity of market participation, allowing the trader to distinguish between low-volume drifts and high-volume breakout moves.
1M XAU Cumulative Delta Volume with OB Breakouts
### Overview
This is a **session-based CVD strategy** built around the **00:00–07:00 CEST range**. It finds the high/low of that session, turns them into **adaptive ATR-based support (yellow)** and **resistance (purple)** zones, and trades only **CVD-confirmed reversals** off those levels.
---
### How it Works
* For each day, the script:
* Builds a 00:00–07:00 CEST **profile high/low**.
* Creates a **support zone** around the session low and a **resistance zone** around the session high.
* Using lower timeframe data, it reconstructs **Cumulative Volume Delta (CVD)** and a **recent delta** filter.
* It arms “pending” states when price **enters a zone from the correct side**, then confirms:
* **BUY (long):** price reclaims above support and recent CVD is strongly positive.
* **SELL (short):** price rejects below resistance and recent CVD is strongly negative.
Only these two CVD signals (`buySignal` / `sellSignal`) open trades.
---
### Strategy Logic
* **Entries**
* `buySignal` → open **long** (if flat).
* `sellSignal` → open **short** (if flat).
* No pyramiding; one position at a time.
* **Exits (only TP & SL)**
* Long: TP at `avg_price * (0.5 + TP%)`, SL at `avg_price * (1 – SL%)`.
* Short: TP at `avg_price * (0.5 – TP%)`, SL at `avg_price * (1 + SL%)`.
* No opposite-signal exits.
---
### Extras
* **Reversal markers** on yellow/purple zones and **breakout/retest markers** are plotted for context and alerts but **do not trigger entries**.
* Zone width and “thickening” are ATR-based so important touches and near-touches are easy to see.
* Only suited for **1m intraday scalping** (e.g. XAU/USD), but can be tested on other markets/timeframes.
XAU/USD Weekly Volatility Strategy by WeTradeAIWeTradeAI - XAU/USD Weekly Volatility Strategy
This strategy is designed for Gold (XAU/USD) trading, leveraging a weekly market structure and volatility projection model. It dynamically identifies high-probability zones based on the prior week’s price action and adapts to intraday movement.
🔍 Core Logic:
Weekly High, Low & Midpoint: Defines structural balance for directional bias.
Projected Volatility Zones:
Green Zone: Upward projection from last week’s low.
Red Zone: Downward projection from last week’s high.
Half-Volatility Lines: Act as breakout or reversal triggers.
Monday Open: Serves as a temporary directional reference until midweek.
Daily High, Low, and Mid: Used for intraday stop-loss placement and validation.
🎯 Trade Entries:
Breakout Entries: Triggered when price breaks and holds above/below the Half-Vol levels.
Reversal Entries: Triggered by strong rejections near outer zones, reverting back toward equilibrium.
🛡️ Risk Management:
Dynamic Stop-Loss: Based on the previous day’s midpoint.
⏱️ Multi-Timeframe Usage:
4H – Weekly structure & context
1H – Trend alignment
15M – Precision entries
ORB Breakout Strategy w/ Filters - Dynamic Sizing - MTFHere is a comprehensive description of the strategy, written in a clear and structured format. You can use this for your script's "how-to-use" guide or documentation.
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## 📈 Opening Range Breakout (ORB) Strategy
This is a comprehensive, multi-timeframe strategy built for trading opening range breakouts. It is designed with a "filters-first" approach, allowing you to validate a breakout with trend, volume, and volatility.
The strategy's core power comes from its flexibility. You can trade on a low timeframe (like a 1-minute chart) while basing your breakout levels on a higher timeframe's opening bar (e.g., the first 15-minute bar). It includes dynamic position sizing based on risk and a wide array of advanced exit management options.
### Key Features
* **Multi-Timeframe Opening Range:** The core of the strategy. You can define the "Opening Range" timeframe (5, 10, 15, 30, or 60 min) *independently* of your chart timeframe.
* **Custom Trading Session:** Define the exact session (e.g., "0930-1600" in "America/New_York") you want to trade.
* **One Trade Per Session:** The strategy will only take the *first valid breakout* signal per day to avoid over-trading.
---
### 🚦 Entry Signals & Filters
A trade is only initiated when the price closes above the Session High or below the Session Low **AND** all active filters are passed.
* **Trend Filter:** (Optional) Requires price to be above a long-term MA (e.g., 100 EMA) for long trades and below it for short trades.
* **Volume Filter:** (Optional) Requires the breakout bar's volume to be a specified multiplier (e.g., 1.5x) of the recent average volume.
* **Volatility Filter:** (Optional) Requires the current ATR to be higher than its long-term average, ensuring you only trade during periods of expanding volatility.
* **Direction Filter:** Allows you to isolate the strategy to **Long Only**, **Short Only**, or **Both**.
---
### 💰 Dynamic Position Sizing
The strategy includes a robust "Risk %" sizing model.
* **Risk-Based Sizing:** Instead of fixed contracts, it calculates the position size based on your **Account Size**, **Risk % per Trade**, and the **Stop Loss distance**.
* **Auto-Detect Point Value:** It automatically detects the correct point value for popular futures contracts (ES, NQ, MES, MNQ) and provides a manual override for other assets.
---
### 📤 Exit & Risk Management
This strategy features a multi-layered exit system, giving you complete control over how trades are managed.
#### 1. Stop Loss (SL)
Your initial stop loss can be calculated using a fixed **Tick** offset or an **ATR** multiplier. It can be anchored from two different points:
* **Breakout Level:** The stop is placed relative to the `sessionHigh` or `sessionLow` level.
* **Entry Bar:** The stop is placed relative to the high/low of the bar that *triggered* the entry.
#### 2. Take Profit (TP)
A standard Take Profit can be set using a fixed **Tick** offset or an **ATR** multiplier.
#### 3. Advanced Exit Logic
These options override the standard Take Profit to allow for more dynamic trade management:
* **Trailing Take Profit (TTP):**
* **Fixed/ATR Trail:** A standard trailing stop that activates after price moves a certain amount in your favor.
* **MA Price Cross:** Exits the trade as soon as the price closes across a fast-moving average (e.g., 9-EMA).
* **MA Crossover:** Exits the trade as soon as a fast MA crosses below a slow MA (for longs) or above (for shorts).
* **Close on Reversal:** (Optional) Exits immediately if the **very next bar** after entry closes back *inside* the opening range (a "failed breakout" signal).
* **Close on Opposite Range Cross:** (Optional) Exits a long trade if the price ever closes below the `sessionLow` (and vice-versa for shorts).
* **End of Session Exit:** All open positions are automatically closed at the end of the defined trading session.
Turtles StrategyBorn from the 1980s "Turtle" experiment, this method of trading captures breakouts and places or closes trades with intrabar entries or exits and realized-equity risk controls.
How It Works
The strategy buys/sells on breakouts from recent highs/lows, using ATR for volatility-adjusted stops and sizing. It risks a fixed % (default 1%) of realized equity per trade—initial capital plus closed P&L, ignoring open positions for conservatism. Drawdown protection auto-reduces risk by 20% at 10% drops (up to three times), resetting only on full peak recovery. Single positions only, with 1-tick slippage simulated for realistic fills. Best for trending assets like forex,commodities, crypto, stocks. Backtest for optimal parameters.
Main Operations
The strategy works on any timeframe but it's meant to be used on daily charts.
Entry Signals:
Long: Buy-stop 1 tick above 20-bar high (default "Entry Period") when no position—enters intrabar on breakout.
Short: Sell-stop 1 tick below 20-bar low. OCA cancels opposites.
Size: (Realized equity × adjusted risk %) ÷ (2× ATR stop distance), scaled by point value.
Exit Signals:
Longs: Stop at tighter of (entry - 2× ATR) or (10-bar low - 1 tick trailing, default "Exit Period").
Shorts: Stop at tighter of (entry + 2× ATR) or (10-bar high + 1 tick trailing).
Locks profits in trends, exits fast on fades.
Risk Controls:
Tracks realized equity peak.
10% drawdown: Risk ×0.8; 20%/30%: Further ×0.8 (max 3x).
Full reset above peak—preserves capital in slumps.
Cybertrading-Insidebar hunter pro robotThe Cybertrading-Inside Pro strategy is an advanced version of Cyber-Inside.
It automates ATR-based inside-bar trading with optional pullback entries, full risk/reward visualization, time filtering, pending-order handling, and fixed chart watermark branding (“CollegePips / CyberTrading”).
⚙️ Technical Overview
1. Core Structure
Uses ATR(14) to measure volatility and classify candle ranges.
Candles are labeled as Spinning, Standard, Long, or Huge based on their range vs. ATR.
Only valid candles (Standard or Long) qualify to confirm a setup.
2. Inside-Bar Logic
The setup requires the current candle’s high/low to be fully contained inside the previous candle (an inside bar).
A wick-break must occur — the wick slightly breaks the previous inside bar’s range while the body remains inside.
This pattern forms a Pierce-Only signal.
Direction:
Wick down → potential Long entry
Wick up → potential Short entry
3. Timing and Entry Conditions
With the time filter enabled, trades trigger only between defined hours (e.g., 07–22).
If Enable Pullback is on, the entry is placed using a limit order offset by pullbackATR × ATR from the signal candle.
If the pullback entry isn’t triggered within pullbackMaxBars, the pending order is canceled automatically.
You can also enable display-only entries without execution (Enable Entry Without Pullback).
4. Risk & Target Management
Stop loss is placed beyond the second-previous candle’s high/low ± stopBuffer × ATR.
Take-profit is based on the chosen risk/reward multiple (RR) or the previous candle’s high/low.
Position size auto-adjusts to keep total risk equal to riskPercent of equity.
5. Visual Components
Dynamic chart objects include:
Red box: risk zone (entry → stop)
Green/blue box: reward zone (entry → target)
Dotted diagonal line: risk-to-reward path
Arrows: actual fill points
6. Order Management System
Each signal creates a unique order ID (pendingId) and exit ID (planExitId).
On a valid fill (newLong / newShort), real stop, target, and position size are applied.
If an order isn’t filled within the timeout window, it’s canceled and reset automatically.
7. Advantages
✅ Smart inside-bar pattern recognition
✅ Automated risk control and dynamic sizing
✅ Clear visual feedback for analysis
✅ Fully backtest-ready for research or education
Apex Squeeze Breakout Strategy (v1.0 by SKC)The Apex Squeeze Breakout Strategy is a powerful momentum-based system designed to capture explosive price moves following periods of low volatility compression (squeeze). It combines five key conditions to validate high-probability breakouts:
🔵 TTM Squeeze Detection using Bollinger Bands and Keltner Channels
🔊 Volume Spike Confirmation relative to a moving average
📈 Breakout Trigger above/below a recent high/low range
💪 Momentum Acceleration using percentage change over time
♻️ RSI Recovery / Overbought Logic to confirm shift in strength
The strategy includes:
Configurable swing/day trading modes
Dynamic ATR-based Stop Loss and TP1/TP2 system
Modular input structure for easy customization
Clear entry/exit visual markers and trade zones
It’s designed for disciplined traders who want to catch high-energy moves after consolidation, suitable for both intraday and swing setups.
Yuri Garcia Smart Money Strategy FULL (COMPLIANT)Yuri Garcia Smart Money Strategy FULL (Slope Divergence)
This script is not a mashup of random indicators. It is an original, coherent strategy that blends multiple institutional-grade tools to form a unified Smart Money trading system. Each component contributes to precise trade filtering, context, and confirmation — no element is decorative or redundant.
🔍 Strategy Logic: How It Works
This strategy integrates the following tools, each with a clearly defined role:
1. Volume Cluster Zones (Orange bands)
Identifies strong buy/sell areas using the highest volume nodes over a rolling window. These act as dynamic points of control where Smart Money is likely active.
2. HTF Zones (4H) (Purple band)
Defines institutional zones by using the 20-bar high/low on the 4-hour chart. These set the outer bounds for valid entries, ensuring alignment with larger market structure.
3. Wick Pullback Filter (Orange circle 🔶)
Detects exhaustion or absorption near zones. Used to confirm genuine rejection after liquidity sweeps or traps.
4. Cumulative Delta Confirmation (Red square 🟥)
Analyzes whether buyers or sellers are dominant using delta volume. Trades only trigger when volume confirms the intended direction.
5. Slope-Based Delta Divergence (Optional)
Detects hidden reversals between price and delta. This prevents late entries and provides early insight into potential trap reversals.
6. Liquidity Grab Detection (Blue diamond 🔷)
Marks smart money stop hunts — temporary price breaks beyond highs/lows, followed by reversal. Used as a confluence tool.
7. ATR-Based Dynamic Risk Control
The strategy uses ATR to calculate SL/TP dynamically. This allows position sizing to adjust to volatility, reducing overexposure in high-momentum conditions.
🎯 Entry Criteria
All the following conditions must be met:
✅ Price is inside a Volume Cluster Zone
✅ Price is within the HTF Institutional Zone
✅ Wick Pullback confirms reaction
✅ Delta confirms strength of buyers/sellers
✅ (Optional) Slope-based divergence signals hidden shift
✅ (Optional) Liquidity grab occurs
Only then will the strategy trigger an entry.
📈 Visual Legend (Symbols on Chart)
Symbol Description
🟣 Purple Zone HTF Support/Resistance zone (4H context)
🟠 Orange Zone Volume cluster from top 3 volume nodes
🔶 Orange Circle Wick Pullback confirmation
🟥 Red Square Delta Confirmation
🔷 Blue Diamond Liquidity Grab indicator
🔵 Blue X Price is inside HTF Zone
🔻 Red Triangle SHORT entry signal
🔺 Green Triangle LONG entry signal
These visuals make it easier to read the chart intuitively while understanding each condition’s role.
⚙️ Strategy Settings Justification
Default Qty: 2% of equity (sustainable risk)
RRR: 2.0 (adaptive to volatility)
ATR Multiplier: 2.0 for SL/TP
Commission: 0.1% used
Slippage: 2 points for realism
Minimum Trades for Testing: Designed to generate over 100 trades under normal backtest conditions
Dataset: Supports BTC, GOLD, Forex, Indices with realistic volatility and volume
These settings reflect a realistic use case for average retail traders and avoid overfitting or unrealistic returns.
📌 How to Use
Apply on 15-minute or 1-hour timeframe.
Wait for full alignment of all entry conditions.
Confirm visually or use included alerts for manual or bot execution.
SL and TP are automatically handled.
🚫 Important Notes
This script is original, not a remix or mashup of unrelated indicators.
Each component was designed to work in harmony, enhancing trade quality and confidence.
No external scripts are required to function.
Alert messages are pre-formatted for both manual and webhook use.
Praetor Sentinel V11.2 NOLOOSE BETA📈 Praetor Sentinel V11.2 – "NOLOOSE BETA"
Algorithmic Trading Strategy for Trend Markets with Adaptive Risk Management
Praetor Sentinel V11.2 is an advanced algorithmic trading strategy for TradingView, specifically designed to operate in strong trend conditions. It combines multiple technical systems—including dynamic trend filters, multi-layer EMA structures, ADX-based volatility control, and adaptive trailing stops—into a powerful and automated trading framework.
🔧 Core Features
Multi-EMA Trend Detection: Two EMA pairs (short/long) to identify and confirm directional trends.
XO-EMA Breakout Logic: Fast EMA crossover to detect breakout opportunities.
ADX Trend Filter: Trades only during strong market trends (above custom ADX threshold).
HTF Filter: Optional higher timeframe trend confirmation (e.g. Daily 50 EMA).
VWAP Validation: Ensures entries aren't taken against the volumetric average.
RSI Filter: Adds a momentum filter (e.g. RSI > 50 for long trades).
🎯 Entry Signals
The strategy uses two entry types:
Breakout Entries: Based on XO-EMA cross and multi-EMA trend alignment.
Pullback Entries: Configurable via various methods such as EMA21 reentry, RSI reversal, engulfing candles, or VWAP reclaim.
All entries can be delayed via confirmation candle logic, requiring a bullish or bearish follow-up bar.
🛡️ Risk Management & Exit Logic
Dynamic ATR Trailing Stop: Adjusts stop distance according to market volatility with optional swing high/low protection.
Break-Even Logic: Locks in trades at breakeven once a defined profit is reached.
Hard Stop-Loss: Caps potential loss per trade with a fixed % (e.g. 1%).
Safe Mode ("NOLOOSE"): Exits early if price moves too far against the position — ideal for automated bots that must avoid drawdowns.
🤖 Automation & Alerts
This strategy is fully automatable with services like 3Commas using built-in alert messages for entries and exits.
All parameters are fully configurable to adapt to different assets, timeframes, and trading styles.
⚙️ Additional Features
Configurable leverage & position sizing
Time-based trading window
Built-in Anchored VWAP
Modular design for easy extension
📌 Summary
Praetor Sentinel V11.2 is a professional-grade tool for trend traders who want rule-based entry/exit logic, adaptive stop systems, and robust protection features. When paired with automation tools, it offers a reliable, low-maintenance setup that emphasizes safety, structure, and scalability.
🛠 How to Use Praetor Sentinel V11.2 – NOLOOSE BETA
🔍 1. Basic Configuration (Required)
Setting Description
Enable Long Trades Enables long (buy) positions.
Enable Short Trades Enables short (sell) positions.
Leverage Used for position sizing calculations.
Position Size % Defines % of capital to be used per trade.
⏰ 2. Time Filter (Optional)
Restricts trading to a defined time range.
Setting Description
Start Date Start date for strategy to be active.
End Date End date for strategy to stop.
Time Zone Time zone for above settings.
📊 3. Trend Setup (Essential for Entry Signals)
Setting Description
MA Type Type of moving average: EMA or SMA.
EMA1/2 Short & Long Two EMA-based systems to determine trend.
Fast/Slow EMA (XO) Used for crossover breakout detection.
HTF Filter Uses higher timeframe trend for additional confirmation.
RSI Filter Confirms entries only if momentum (RSI) supports it.
ADX Threshold Ensures trades only occur during strong trends.
🎯 4. Entry Logic
Setting Description
Pullback Entry Type Enables optional entry setups:
"Off"
"EMA21"
"RSI"
"Engulfing"
"VWAP"
| Use Confirmation Candle | Entry is delayed until a confirmation bar appears. |
| VWAP Confirmation | Trade only if price is above/below the VWAP (based on direction). |
Note: You can combine breakout + pullback signals. Only one has to trigger.
🧯 5. Risk Control & Exit Settings
Setting Description
Trailing Stop Mode
"Standard": Classic trailing stop
"Dynamic ATR": Adjusts to current volatility
"Dynamic ATR + Swing": Adds swing high/low buffer
| Enable Break-Even | Moves SL to breakeven once a target % gain is reached. |
| Enable Hard Stop-Loss | Fixed stop-loss (e.g. 1%) to cap trade risk. |
| Enable Safe Mode | Exits trade early if price moves against it beyond defined % (e.g. 0.3%). |
🔔 6. Alerts & Bot Automation
Setting Description
Entry Long/Short Msg Text message sent via alert when a position opens.
Exit Long/Short Msg Alert message for stop-loss/exit logic.
How to automate with 3Commas:
Load the strategy on your chart.
Manually create alerts using "Create Alert" in TradingView.
Use the built-in alert_message values for bot integration.
✅ Recommended Settings (Example for BTC/ETH on 1H)
Long & Short: ✅ Enabled
Leverage: 2.0
Timeframe: 1H
Pullback Entry: "EMA21"
MA Type: EMA
HTF Filter: Enabled (Daily EMA50)
RSI Filter: Enabled
VWAP Filter: Enabled
Break-Even: On at 0.5%
Hard SL: 1.0%
Safe Mode: On at -0.3%
Trailing Stop: "Dynamic ATR + Swing"
📘 Pro Tips for Testing & Customization
Use the Strategy Tester in TradingView to analyze performance over different assets.
Experiment with timeframes and entry modes.
Ideal for trending assets like BTC, ETH, SOL, etc.
You can expand it with take-profit logic, fixed TPs, indicator exits, etc.
Prop Firm Business SimulatorThe prop firm business simulator is exactly what it sounds like. It's a plug and play tool to test out any tradingview strategy and simulate hypothetical performance on CFD Prop Firms.
Now what is a modern day CFD Prop Firm?
These companies sell simulated trading challenges for a challenge fee. If you complete the challenge you get access to simulated capital and you get a portion of the profits you make on those accounts payed out.
I've included some popular firms in the code as presets so it's easy to simulate them. Take into account that this info will likely be out of date soon as these prices and challenge conditions change.
Also, this tool will never be able to 100% simulate prop firm conditions and all their rules. All I aim to do with this tool is provide estimations.
Now why is this tool helpful?
Most traders on here want to turn their passion into their full-time career, prop firms have lately been the buzz in the trading community and market themselves as a faster way to reach that goal.
While this all sounds great on paper, it is sometimes hard to estimate how much money you will have to burn on challenge fees and set realistic monthly payout expectations for yourself and your trading. This is where this tool comes in.
I've specifically developed this for traders that want to treat prop firms as a business. And as a business you want to know your monthly costs and income depending on the trading strategy and prop firm challenge you are using.
How to use this tool
It's quite simple you remove the top part of the script and replace it with your own strategy. Make sure it's written in same version of pinescript before you do that.
//--$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$--//--------------------------------------------------------------------------------------------------------------------------$$$$$$
//--$$$$$--Strategy-- --$$$$$$--// ******************************************************************************************************************************
//--$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$--//--------------------------------------------------------------------------------------------------------------------------$$$$$$
length = input.int(20, minval=1, group="Keltner Channel Breakout")
mult = input(2.0, "Multiplier", group="Keltner Channel Breakout")
src = input(close, title="Source", group="Keltner Channel Breakout")
exp = input(true, "Use Exponential MA", display = display.data_window, group="Keltner Channel Breakout")
BandsStyle = input.string("Average True Range", options = , title="Bands Style", display = display.data_window, group="Keltner Channel Breakout")
atrlength = input(10, "ATR Length", display = display.data_window, group="Keltner Channel Breakout")
esma(source, length)=>
s = ta.sma(source, length)
e = ta.ema(source, length)
exp ? e : s
ma = esma(src, length)
rangema = BandsStyle == "True Range" ? ta.tr(true) : BandsStyle == "Average True Range" ? ta.atr(atrlength) : ta.rma(high - low, length)
upper = ma + rangema * mult
lower = ma - rangema * mult
//--Graphical Display--// *-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-$$$$$$
u = plot(upper, color=#2962FF, title="Upper", force_overlay=true)
plot(ma, color=#2962FF, title="Basis", force_overlay=true)
l = plot(lower, color=#2962FF, title="Lower", force_overlay=true)
fill(u, l, color=color.rgb(33, 150, 243, 95), title="Background")
//--Risk Management--// *-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-$$$$$$
riskPerTradePerc = input.float(1, title="Risk per trade (%)", group="Keltner Channel Breakout")
le = high>upper ? false : true
se = lowlower
strategy.entry('PivRevLE', strategy.long, comment = 'PivRevLE', stop = upper, qty=riskToLots)
if se and upper>lower
strategy.entry('PivRevSE', strategy.short, comment = 'PivRevSE', stop = lower, qty=riskToLots)
The tool will then use the strategy equity of your own strategy and use this to simulat prop firms. Since these CFD prop firms work with different phases and payouts the indicator will simulate the gains until target or max drawdown / daily drawdown limit gets reached. If it reaches target it will go to the next phase and keep on doing that until it fails a challenge.
If in one of the phases there is a reward for completing, like a payout, refund, extra it will add this to the gains.
If you fail the challenge by reaching max drawdown or daily drawdown limit it will substract the challenge fee from the gains.
These gains are then visualised in the calendar so you can get an idea of yearly / monthly gains of the backtest. Remember, it is just a backtest so no guarantees of future income.
The bottom pane (non-overlay) is visualising the performance of the backtest during the phases. This way u can check if it is realistic. For instance if it only takes 1 bar on chart to reach target you are probably risking more than the firm wants you to risk. Also, it becomes much less clear if daily drawdown got hit in those high risk strategies, the results will be less accurate.
The daily drawdown limit get's reset every time there is a new dayofweek on chart.
If you set your prop firm preset setting to "'custom" the settings below that are applied as your prop firm settings. Otherwise it will use one of the template by default it's FTMO 100K.
The strategy I'm using as an example in this script is a simple Keltner Channel breakout strategy. I'm using a 0.05% commission per trade as that is what I found most common on crypto exchanges and it's close to the commissions+spread you get on a cfd prop firm. I'm targeting a 1% risk per trade in the backtest to try and stay within prop firm boundaries of max 1% risk per trade.
Lastly, the original yearly and monthly performance table was developed by Quantnomad and I've build ontop of that code. Here's a link to the original publication:
That's everything for now, hope this indicator helps people visualise the potential of prop firms better or to understand that they are not a good fit for their current financial situation.
Breakouts With Timefilter Strategy [LuciTech]This strategy captures breakout opportunities using pivot high/low breakouts while managing risk through dynamic stop-loss placement and position sizing. It includes a time filter to limit trades to specific sessions.
How It Works
A long trade is triggered when price closes above a pivot high, and a short trade when price closes below a pivot low.
Stop-loss can be set using ATR, prior candle high/low, or a fixed point value. Take-profit is based on a risk-reward multiplier.
Position size adjusts based on the percentage of equity risked.
Breakout signals are marked with triangles, and entry, stop-loss, and take-profit levels are plotted.
moving average filter: Bullish breakouts only trigger above the MA, bearish breakouts below.
The time filter shades the background during active trading hours.
Customization:
Adjustable pivot length for breakout sensitivity.
Risk settings: percentage risked, risk-reward ratio, and stop-loss type.
ATR settings: length, smoothing method (RMA, SMA, EMA, WMA).
Moving average filter (SMA, EMA, WMA, VWMA, HMA) to confirm breakouts.
IBS (Internal Bar Strength) Trading Strategy for SPY and NDQImplementation by AlgoTradeKit
Overview
The IBS Trading Strategy is a daily bars long-only trading system, based on the concept of Internal Bar Strength (IBS). The strategy aims to identify potential reversals by monitoring how the previous bar’s close positions itself within its high-low range. It is suitable for stock and US indices. The default parameters are optimized for SPY/SPX and NDQ/QQQ
Strategy Concept
The Internal Bar Strength (IBS) is calculated using the formula:
IBS = (Previous Close - Previous Low) / (Previous High - Previous Low)
This value always lies between 0 and 1. An IBS value below 0.2 is typically interpreted as an oversold condition, while a value above 0.9 suggests an overbought state.
Trading Rules
- Long Entry :
- Condition 1 : IBS is below the user-defined entry threshold (default is 0.2).
- Condition 2 : The current price is above an N-period Exponential Moving Average (EMA) (default period is 252).
- Note : You can disable the EMA condition by setting the EMA period to 0.
- Long Exit
- The position is closed when IBS rises above the user-defined exit threshold (default is 0.9).
Customization Options
- IBS Entry Threshold : Adjust to set the sensitivity for entering a long trade based on oversold conditions.
- IBS Exit Threshold : Customize to define the exit point when the market becomes overbought.
- EMA Period : Set the lookback period for the EMA to align with your trend bias; disable this condition by setting the period to 0.
Risk Management & Trading Considerations
- Designed for daily charts, the strategy captures higher timeframe trends and minimizes noise.
- The entry and exit conditions are straightforward, aiming to avoid over-trading while letting clear signals dictate trade management.
- Always use proper risk management techniques and test the strategy thoroughly on historical data and in a simulated environment before applying it in live markets.
Disclaimer
This strategy is for educational and informational purposes only and does not constitute financial advice. Trading involves risk, and past performance is not indicative of future results. Always conduct your own research and consider your risk tolerance before making any trades.
Kernel Regression Envelope with SMI OscillatorThis script combines the predictive capabilities of the **Nadaraya-Watson estimator**, implemented by the esteemed jdehorty (credit to him for his excellent work on the `KernelFunctions` library and the original Nadaraya-Watson Envelope indicator), with the confirmation strength of the **Stochastic Momentum Index (SMI)** to create a dynamic trend reversal strategy. The core idea is to identify potential overbought and oversold conditions using the Nadaraya-Watson Envelope and then confirm these signals with the SMI before entering a trade.
**Understanding the Nadaraya-Watson Envelope:**
The Nadaraya-Watson estimator is a non-parametric regression technique that essentially calculates a weighted average of past price data to estimate the current underlying trend. Unlike simple moving averages that give equal weight to all past data within a defined period, the Nadaraya-Watson estimator uses a **kernel function** (in this case, the Rational Quadratic Kernel) to assign weights. The key parameters influencing this estimation are:
* **Lookback Window (h):** This determines how many historical bars are considered for the estimation. A larger window results in a smoother estimation, while a smaller window makes it more reactive to recent price changes.
* **Relative Weighting (alpha):** This parameter controls the influence of different time frames in the estimation. Lower values emphasize longer-term price action, while higher values make the estimator more sensitive to shorter-term movements.
* **Start Regression at Bar (x\_0):** This allows you to exclude the potentially volatile initial bars of a chart from the calculation, leading to a more stable estimation.
The script calculates the Nadaraya-Watson estimation for the closing price (`yhat_close`), as well as the highs (`yhat_high`) and lows (`yhat_low`). The `yhat_close` is then used as the central trend line.
**Dynamic Envelope Bands with ATR:**
To identify potential entry and exit points around the Nadaraya-Watson estimation, the script uses **Average True Range (ATR)** to create dynamic envelope bands. ATR measures the volatility of the price. By multiplying the ATR by different factors (`nearFactor` and `farFactor`), we create multiple bands:
* **Near Bands:** These are closer to the Nadaraya-Watson estimation and are intended to identify potential immediate overbought or oversold zones.
* **Far Bands:** These are further away and can act as potential take-profit or stop-loss levels, representing more extreme price extensions.
The script calculates both near and far upper and lower bands, as well as an average between the near and far bands. This provides a nuanced view of potential support and resistance levels around the estimated trend.
**Confirming Reversals with the Stochastic Momentum Index (SMI):**
While the Nadaraya-Watson Envelope identifies potential overextended conditions, the **Stochastic Momentum Index (SMI)** is used to confirm a potential trend reversal. The SMI, unlike a traditional stochastic oscillator, oscillates around a zero line. It measures the location of the current closing price relative to the median of the high/low range over a specified period.
The script calculates the SMI on a **higher timeframe** (defined by the "Timeframe" input) to gain a broader perspective on the market momentum. This helps to filter out potential whipsaws and false signals that might occur on the current chart's timeframe. The SMI calculation involves:
* **%K Length:** The lookback period for calculating the highest high and lowest low.
* **%D Length:** The period for smoothing the relative range.
* **EMA Length:** The period for smoothing the SMI itself.
The script uses a double EMA for smoothing within the SMI calculation for added smoothness.
**How the Indicators Work Together in the Strategy:**
The strategy enters a long position when:
1. The closing price crosses below the **near lower band** of the Nadaraya-Watson Envelope, suggesting a potential oversold condition.
2. The SMI crosses above its EMA, indicating positive momentum.
3. The SMI value is below -50, further supporting the oversold idea on the higher timeframe.
Conversely, the strategy enters a short position when:
1. The closing price crosses above the **near upper band** of the Nadaraya-Watson Envelope, suggesting a potential overbought condition.
2. The SMI crosses below its EMA, indicating negative momentum.
3. The SMI value is above 50, further supporting the overbought idea on the higher timeframe.
Trades are closed when the price crosses the **far band** in the opposite direction of the trade. A stop-loss is also implemented based on a fixed value.
**In essence:** The Nadaraya-Watson Envelope identifies areas where the price might be deviating significantly from its estimated trend. The SMI, calculated on a higher timeframe, then acts as a confirmation signal, suggesting that the momentum is shifting in the direction of a potential reversal. The ATR-based bands provide dynamic entry and exit points based on the current volatility.
**How to Use the Script:**
1. **Apply the script to your chart.**
2. **Adjust the "Kernel Settings":**
* **Lookback Window (h):** Experiment with different values to find the smoothness that best suits the asset and timeframe you are trading. Lower values make the envelope more reactive, while higher values make it smoother.
* **Relative Weighting (alpha):** Adjust to control the influence of different timeframes on the Nadaraya-Watson estimation.
* **Start Regression at Bar (x\_0):** Increase this value if you want to exclude the initial, potentially volatile, bars from the calculation.
* **Stoploss:** Set your desired stop-loss value.
3. **Adjust the "SMI" settings:**
* **%K Length, %D Length, EMA Length:** These parameters control the sensitivity and smoothness of the SMI. Experiment to find settings that work well for your trading style.
* **Timeframe:** Select the higher timeframe you want to use for SMI confirmation.
4. **Adjust the "ATR Length" and "Near/Far ATR Factor":** These settings control the width and sensitivity of the envelope bands. Smaller ATR lengths make the bands more reactive to recent volatility.
5. **Customize the "Color Settings"** to your preference.
6. **Observe the plots:**
* The **Nadaraya-Watson Estimation (yhat)** line represents the estimated underlying trend.
* The **near and far upper and lower bands** visualize potential overbought and oversold zones based on the ATR.
* The **fill areas** highlight the regions between the near and far bands.
7. **Look for entry signals:** A long entry is considered when the price touches or crosses below the lower near band and the SMI confirms upward momentum. A short entry is considered when the price touches or crosses above the upper near band and the SMI confirms downward momentum.
8. **Manage your trades:** The script provides exit signals when the price crosses the far band. The fixed stop-loss will also close trades if the price moves against your position.
**Justification for Combining Nadaraya-Watson Envelope and SMI:**
The combination of the Nadaraya-Watson Envelope and the SMI provides a more robust approach to identifying potential trend reversals compared to using either indicator in isolation. The Nadaraya-Watson Envelope excels at identifying potential areas where the price is overextended relative to its recent history. However, relying solely on the envelope can lead to false signals, especially in choppy or volatile markets. By incorporating the SMI as a confirmation tool, we add a momentum filter that helps to validate the potential reversals signaled by the envelope. The higher timeframe SMI further helps to filter out noise and focus on more significant shifts in momentum. The ATR-based bands add a dynamic element to the entry and exit points, adapting to the current market volatility. This mashup aims to leverage the strengths of each indicator to create a more reliable trading strategy.
Calculus Free Trend Strategy for Crypto & StocksObjective :
The Correlation Channel Trading Strategy is designed to identify potential entry points based on the relationship between price movements and a correlation channel. The strategy aims to capture trends within the channel while managing risk effectively.
Parameters :
Length: Determines the period for calculating moving averages and the true range, influencing the sensitivity of the strategy to price movements.
Multiplier: Adjusts the width of the correlation channel, providing flexibility to adapt to different market conditions.
Inputs :
Asset Symbol: Allows users to specify the financial instrument for analysis.
Timeframe: Defines the timeframe for data aggregation, enabling customization based on trading preferences.
Plot Correlation Channel: Optional input to visualize the correlation channel on the price chart.
Methodology :
Data Acquisition: The strategy fetches OHLC (Open, High, Low, Close) data for the specified asset and timeframe. In this case we use COINBASE:BTCUSD
Calculation of Correlation Channel: It computes the squared values for OHLC data, calculates the average value (x), and then calculates the square root of x to derive the source value. Additionally, it calculates the True Range as the difference between high and low prices.
Moving Averages: The strategy calculates moving averages (MA) for the source value and the True Range, which form the basis for defining the correlation channel.
Upper and Lower Bands: Using the MA and True Range, the strategy computes upper and lower bands of the correlation channel, with the width determined by the multiplier.
Entry Conditions: Long positions are initiated when the price crosses above the upper band, signaling potential overbought conditions. Short positions are initiated when the price crosses below the lower band, indicating potential oversold conditions.
Exit Conditions: Stop-loss mechanisms are incorporated directly into the entry conditions to manage risk. Long positions are exited if the price falls below a predefined stop-loss level, while short positions are exited if the price rises above the stop-loss level.
Strategy Approach: The strategy aims to capitalize on trends within the correlation channel, leveraging systematic entry signals while actively managing risk through stop-loss orders.
Backtest Details : For the purpose of this test I used the entire data available for BTCUSD Coinbase, with 10% of capital allocation and 0.1% comission for entry/exit(0.2% total). Can be also used with other both directly correlated with current settings of BTC or with new ones
Advantages :
Provides a systematic approach to trading based on quantifiable criteria.
Offers flexibility through customizable parameters to adapt to various market conditions.
Integrates risk management through predefined stop-loss mechanisms.
Limitations :
Relies on historical price data and technical indicators, which may not always accurately predict future price movements.
May generate false signals during periods of low volatility or erratic price behavior.
Requires continuous monitoring and adjustment of parameters to maintain effectiveness.
Conclusion :
The Correlation Channel Trading Strategy offers traders a structured framework for identifying potential entry points within a defined price channel. By leveraging moving averages and true range calculations, the strategy aims to capture trends while minimizing risk through stop-loss mechanisms. While no strategy can guarantee success in all market conditions, the Correlation Channel Trading Strategy provides a systematic approach to trading that can enhance decision-making and risk management for traders.
