The Best Strategy Template[LuciTech]Hello Traders,
This is a powerful and flexible strategy template designed to help you create, backtest, and deploy your own custom trading strategies. This template is not a ready-to-use strategy but a framework that simplifies the development process by providing a wide range of pre-built features and functionalities.
What It Does
The LuciTech Strategy Template provides a robust foundation for building your own automated trading strategies. It includes a comprehensive set of features that are essential for any serious trading strategy, allowing you to focus on your unique trading logic without having to code everything from scratch.
Key Features
The LuciTech Strategy Template integrates several powerful features to enhance your strategy development:
•
Advanced Risk Management: This includes robust controls for defining your Risk Percentage per Trade, setting a precise Risk-to-Reward Ratio, and implementing an intelligent Breakeven Stop-Loss mechanism that automatically adjusts your stop to the entry price once a specified profit threshold is reached. These elements are crucial for capital preservation and consistent profitability.
•
Flexible Stop-Loss Options: The template offers adaptable stop-loss calculation methods, allowing you to choose between ATR-Based Stop-Loss, which dynamically adjusts to market volatility, and Candle-Based Stop-Loss, which uses structural price points from previous candles. This flexibility ensures the stop-loss strategy aligns with diverse trading styles.
•
Time-Based Filtering: Optimize your strategy's performance by restricting trading activity to specific hours of the day. This feature allows you to avoid unfavorable market conditions or focus on periods of higher liquidity and volatility relevant to your strategy.
•
Customizable Webhook Alerts: Stay informed with advanced notification capabilities. The template supports sending detailed webhook alerts in various JSON formats (Standard, Telegram, Concise Telegram) to external platforms, facilitating real-time monitoring and potential integration with automated trading systems.
•
Comprehensive Visual Customization: Enhance your analytical clarity with extensive visual options. You can customize the colors of entry, stop-loss, and take-profit lines, and effectively visualize market inefficiencies by displaying and customizing Fair Value Gap (FVG) boxes directly on your chart.
How It Does It
The LuciTech Strategy Template is meticulously crafted using Pine Script, TradingView's powerful and expressive programming language. The underlying architecture is designed for clarity and modularity, allowing for straightforward integration of your unique trading signals. At its core, the template operates by taking user-defined entry and exit conditions and then applying a sophisticated layer of risk management, position sizing, and trade execution logic.
For instance, when a longCondition or shortCondition is met, the template dynamically calculates the appropriate position size. This calculation is based on your specified risk_percent of equity and the stop_distance (the distance between your entry price and the calculated stop-loss level). This ensures that each trade adheres to your predefined risk parameters, a critical component of disciplined trading.
The flexibility in stop-loss calculation is achieved through a switch statement that evaluates the sl_type input. Whether you choose an ATR-based stop, which adapts to market volatility, or a candle-based stop, which uses structural price points, the template seamlessly integrates these methods. The ATR calculation itself is further refined by allowing various smoothing methods (RMA, SMA, EMA, WMA), providing granular control over how volatility is measured.
Time-based filtering is implemented by comparing the current bar's time with user-defined start_hour, start_minute, end_hour, and end_minute inputs. This allows the strategy to activate or deactivate trading during specific market sessions or periods of the day, a valuable tool for optimizing performance and avoiding unfavorable conditions.
Furthermore, the template incorporates advanced webhook alert functionality. When a trade is executed, a customizable JSON message is formatted based on your webhook_format selection (Standard, Telegram, or Concise Telegram) and sent via alert function. This enables seamless integration with external services for real-time notifications or even automated trade execution through third-party platforms.
Visual feedback is paramount for understanding strategy behavior. The template utilizes plot and fill functions to clearly display entry prices, stop-loss levels, and take-profit targets directly on the chart. Customizable colors for these elements, along with dedicated options for Fair Value Gap (FVG) boxes, enhance the visual analysis during backtesting and live trading, making it easier to interpret the strategy's actions.
How It's Original
The LuciTech Strategy Template distinguishes itself in the crowded landscape of TradingView scripts through its unique combination of integrated, advanced risk management features, highly flexible stop-loss methodologies, and sophisticated alerting capabilities, all within a user-friendly and modular framework. While many templates offer basic entry/exit signal integration, LuciTech goes several steps further by providing a robust, ready-to-use infrastructure for managing the entire trade lifecycle once a signal is generated.
Unlike templates that might require users to piece together various risk management components or code complex stop-loss logic from scratch, LuciTech offers these critical functionalities out-of-the-box. The inclusion of dynamic position sizing based on a user-defined risk percentage, a configurable risk-to-reward ratio, and an intelligent breakeven mechanism significantly elevates its utility. This comprehensive approach to capital preservation and profit targeting is a cornerstone of professional trading and is often overlooked or simplified in generic templates.
Furthermore, the template's provision for multiple stop-loss calculation types—ATR-based for volatility adaptation, and candle-based for structural support/resistance—demonstrates a deep understanding of diverse trading strategies. The underlying code for these calculations is already implemented, saving developers considerable time and effort. The subtle yet powerful inclusion of FVG (Fair Value Gap) related inputs also hints at advanced price action concepts, offering a sophisticated layer of analysis and execution that is not commonly found in general-purpose templates.
The advanced webhook alerting system, with its support for various JSON formats tailored for platforms like Telegram, showcases an originality in catering to the needs of modern, automated trading setups. This moves beyond simple TradingView pop-up alerts, enabling seamless integration with external systems for real-time trade monitoring and execution. This level of external connectivity and customizable data output is a significant differentiator.
In essence, the LuciTech Strategy Template is original not just in its individual features, but in how these features are cohesively integrated to form a powerful, opinionated, yet highly adaptable system. It empowers traders to focus their creative energy on developing their core entry/exit signals, confident that the underlying framework will handle the complexities of risk management, trade execution, and external communication with precision and flexibility. It's a comprehensive solution designed to accelerate the development of robust and professional trading strategies.
How to Modify the Logic to Apply Your Strategy
The LuciTech Strategy Template is designed with modularity in mind, making it exceptionally straightforward to integrate your unique trading strategy logic. The template provides a clear separation between the core strategy management (risk, position sizing, exits) and the entry signal generation. This allows you to easily plug in your own buy and sell conditions without altering the robust underlying framework.
Here’s a step-by-step guide on how to adapt the template to your specific trading strategy:
1.
Locate the Strategy Logic Section:
Open the Pine Script editor in TradingView and navigate to the section clearly marked with the comment //Strategy Logic Example:. This is where the template’s placeholder entry conditions (a simple moving average crossover) are defined.
2.
Define Your Custom Entry Conditions:
Within this section, you will find variables such as longCondition and shortCondition. These are boolean variables that determine when a long or short trade should be initiated. Replace the existing example logic with your own custom buy and sell conditions. Your conditions can be based on any combination of indicators, price action patterns, candlestick formations, or other market analysis techniques. For example, if your strategy involves a combination of RSI and MACD, you would define longCondition as (rsi > 50 and macd_line > signal_line) and shortCondition as (rsi < 50 and macd_line < signal_line).
3.
Leverage the Template’s Built-in Features:
Once your longCondition and shortCondition are defined, the rest of the template automatically takes over. The integrated risk management module will calculate the appropriate position size based on your Risk % input and the chosen Stop Loss Type. The Risk:Reward ratio will determine your take-profit levels, and the Breakeven at R feature will manage your stop-loss dynamically. The time filter (Use Time Filter) will ensure your trades only occur within your specified hours, and the webhook alerts will notify you of trade executions.
Indicators and strategies
EnsembleX📌 EnsembleX – Multi-Feature Voting Strategy
//@version=5
//@fenyesk
🔹 Overview
EnsembleX is a multi-indicator ensemble trading strategy that combines price action, momentum, volume, and volatility signals into a unified consensus model. Instead of relying on a single indicator, EnsembleX uses a weighted voting system to determine trade entries and exits, making it more adaptive across different market conditions (crypto, forex, and equities).
The system calculates feature-engineered signals, normalizes them, applies lagged context, and then uses ensemble consensus weighting to decide whether to go long or short. An adaptive threshold (ATR-based) ensures risk-sensitive entries during volatile or quiet regimes.
🔹 Core Features
📈 Trend & Momentum Features
EMA Slope (f_slope): Captures directional bias and steepness of trend.
RSI (f_rsi): Measures overbought/oversold conditions with normalization.
CCI (f_cci): Detects price deviations from mean for extreme reversals.
ADX (f_adx, DMI+/-): Evaluates trend strength and directional dominance.
📊 Volatility Features
Standard Deviation (f_stdev): Captures volatility spikes relative to history.
Bollinger Band Position (f_bb): Measures where price sits within BB envelope.
Log Returns (f_logr): Tracks distribution-adjusted price changes.
💵 Volume-Based Features
MFI (f_mfi): Volume-weighted momentum confirming price moves.
Volume Pressure (f_vol): Combines normalized volume ratio with price change.
🧮 Feature Engineering
Normalization & Z-score scaling: Keeps features comparable across regimes.
Lag Features (optional): Adds short-term historical context to signals.
Composite Aggregates:
Momentum Composite (mom): RSI + CCI + MFI blend.
Trend Composite (trd): ADX + Slope blend.
Volatility Composite (volat): StDev + Volume blend.
🔹 Signal Generation
Each feature produces an expert signal (+1 bull, -1 bear, 0 neutral). Examples:
RSI rising from oversold → Bull signal.
ADX strong + DMI+ dominance → Bull signal.
Bollinger Band breakout + reversal → Bear signal.
Volume pressure > threshold → Directional confirmation.
🔹 Ensemble Voting Mechanism
Each signal is assigned a weight (weight_rsi, weight_adx, weight_mfi, etc.).
Final bull/bear confidence is computed as a weighted probability.
Trades trigger only when consensus ≥ threshold.
Threshold adapts dynamically based on ATR / volatility regime.
🔹 Trading Logic
✅ Long Entry:
Bull consensus ≥ threshold and stronger than bear side.
✅ Short Entry:
Bear consensus ≥ threshold and stronger than bull side.
✅ Optional Exits:
Close on opposite signal flip (configurable by position side).
🔹 Visualization
Plots bull and bear confidence curves.
Plots both base threshold and adaptive ATR-adjusted threshold.
Easy to see how consensus builds before trades trigger.
⚡ Key Benefits
Robustness: Reduces reliance on any single indicator.
Flexibility: Works across assets and timeframes (crypto, forex, stocks).
Adaptive: Threshold adjusts automatically in volatile or quiet markets.
Transparency: Plotted consensus and threshold lines make signals easy to interpret.
📢 Usage Notes
Best used on 1h–4h for swing trades, or 5m–15m for intraday setups.
Combine with risk management (TP/SL, position sizing) for live trading.
Ensemble weights (weight_rsi, weight_adx, etc.) can be tuned per asset.
👉 This script is designed for backtesting and research. Results vary depending on the asset, timeframe, and parameter tuning.
QFL StDev Mean Reversal σ-Based Levels v.1.0🔹 Theory Behind the QFL σ-Based Mean Reversal Strategy
1. QFL Core Concept (Base + Bounce)
The QFL (Quickfingers Luc) method is a mean-reversion trading strategy built around the idea of “bases”:
A base is a strong support level, typically formed after a sharp move down, where buyers defended price.
When price drops below the base, it is considered an “overreaction” or “fake breakdown.”
The logic: after such a drop, price often snaps back upward (mean reversion).
In short:
Identify strong bases with volume confirmation.
Wait for a breakdown below the base (oversold condition).
Enter a long trade betting on a bounce back toward the mean.
2. σ-Based Levels (Standard Deviation Bands)
This version enhances QFL using statistics.
A moving average (SMA) of price defines the mean.
Standard Deviation (σ) measures volatility.
Multiple σ-levels define dynamic support/resistance:
Upper Band (Mean + 3σ) → Overbought zone.
Entry Band (Mean – 2σ) → Oversold trigger for entries.
TP Level (Mean + 3σ) → Take-profit target.
SL Level (Mean – 3σ) → Stop-loss safeguard.
This makes the strategy adaptive to volatility instead of relying on static levels.
3. Volume Confirmation
Not every dip below a base is worth trading. To filter noise:
The script requires pivot low detection (local support formation).
That pivot must coincide with volume spike confirmation:
Volume > SMA(Volume) × Factor.
This ensures breakdowns are meaningful, not just random dips.
4. Mean Reversion Logic
Entry triggers when:
A valid base has been established.
Price drops below the Entry Band (–2σ).
No active position is open.
Exit logic:
Take Profit → when price reaches the upper σ-based TP level.
Stop Loss → when price breaches the lower σ-based SL level.
This balances risk/reward using statistically significant levels.
🔹 Usage in TradingView
1. Adding to Chart
Copy and paste the script into TradingView Pine Editor.
Click Add to Chart → It overlays σ-bands, base levels, entry signals, and exit zones.
2. Inputs & Tuning Parameters
Volume Factor (default: 2.0)
Controls how strong a volume spike must be to confirm a base.
Higher = stricter filtering (fewer but stronger signals).
StDev Length (default: 20)
Window size for SMA + σ.
Shorter = more reactive (good for scalping).
Longer = smoother, more stable (good for swing trading).
Base Bounce Sigma (default: 3.0)
Defines how much price must bounce above pivot low to validate it as a base.
Drop Below Sigma (default: 2.0)
Defines how far below the mean price must drop to trigger entry (oversold).
Take Profit Sigma (default: 3.0)
Exit level above mean.
Higher = greedier (larger TP, fewer hits).
Lower = safer (quicker exits).
Stop Loss Sigma (default: 3.0)
Safety net if price continues falling instead of reverting.
Adjust based on asset volatility.
3. Chart Visuals
Blue line = Detected base.
Purple band = Entry zone (–2σ).
Green line = Take-profit target (+3σ).
Maroon line = Stop-loss boundary (–3σ).
Background purple highlight = Mean reversion signal zone.
Gray fill = Risk/reward channel from entry to TP.
4. Alerts
Entry Alert → When entry condition triggers.
Exit Alert → When trade closes (TP/SL).
Useful for automation with brokers via webhooks.
5. Best Markets & Timeframes
Works well on crypto, forex, and volatile equities.
Effective on 5m–1h charts for intraday trading.
On higher timeframes (4h–1D), it identifies swing trade reversals.
🔹 Strengths & Weaknesses
✅ Strengths
Combines QFL base logic with statistical volatility filtering.
Dynamic (σ-based) → adapts to changing volatility.
Filters weak setups with volume confirmation.
Provides automated TP & SL for risk management.
⚠️ Weaknesses
Mean reversion assumes price will bounce → vulnerable in strong trends.
Works better in ranging / sideways markets than trending ones.
Parameters must be optimized for each asset & timeframe.
Volume confirmation may be less reliable in markets with fake volume (e.g., some altcoins).
✅ In summary:
The QFL σ Mean Reversal Strategy is a volatility-adaptive, volume-filtered mean reversion system. It detects bases with pivot + volume logic, waits for an oversold drop below σ-bands, and enters trades betting on a bounce back toward the mean. TP and SL are defined statistically, making it more robust than traditional fixed-level QFL implementations.
维加斯双通道策略Vegas Channel Comprehensive Strategy Description
Strategy Overview
A comprehensive trading strategy based on the Vegas Dual Channel indicator, supporting dynamic position sizing and fund management. The strategy employs a multi-signal fusion mechanism including classic price crossover signals, breakout signals, and retest signals, combined with trend filtering, RSI+MACD filtering, and volume filtering to ensure signal reliability.
Core Features
Dynamic Position Sizing: Continue adding positions on same-direction signals, close all positions on opposite signals
Smart Take Profit/Stop Loss: ATR-based dynamic TP/SL, updated with each new signal
Fund Management: Supports dynamic total amount management for compound growth
Time Filtering: Configurable trading time ranges
Risk Control: Maximum order limit to prevent over-leveraging
Leverage Usage Instructions
Important: This strategy does not use TradingView's margin functionality
Setup Method
Total Amount = Actual Funds × Leverage Multiplier
Example: Have 100U actual funds, want to use 10x leverage → Set total amount to 100 × 10 = 1000U
Trading Amount Calculation
Each trade percentage is calculated based on leveraged amount
Example: Set 10% → Actually trade 100U margin × 10x leverage = 1000U trading amount
Maximum Orders Configuration
Must be used in conjunction with leveraged amount
Example: 1000U total amount, 10% per trade, maximum 10 orders = maximum use of 1000U
Note: Do not exceed 100% of total amount to avoid over-leveraging
Parameter Configuration Recommendations
Leverage Configuration Examples
Actual funds 100U, 5x leverage, total amount setting 500U, 10% per trade, 50U per trade, recommended maximum orders 10
Actual funds 100U, 10x leverage, total amount setting 1000U, 10% per trade, 100U per trade, recommended maximum orders 10
Actual funds 100U, 20x leverage, total amount setting 2000U, 5% per trade, 100U per trade, recommended maximum orders 20
Risk Control
Conservative: 5-10x leverage, 10% per trade, maximum 5-8 orders
Aggressive: 10-20x leverage, 5-10% per trade, maximum 10-15 orders
Extreme: 20x+ leverage, 2-5% per trade, maximum 20+ orders
Strategy Advantages
Signal Reliability: Multiple filtering mechanisms reduce false signals
Capital Efficiency: Dynamic fund management for compound growth
Risk Controllable: Maximum order limits prevent liquidation
Flexible Configuration: Supports various leverage and fund allocation schemes
Time Control: Configurable trading hours to avoid high-risk periods
Usage Notes
Ensure total amount is set correctly (actual funds × leverage multiplier)
Maximum orders should not exceed the range allowed by total funds
Recommend starting with conservative configuration and gradually adjusting parameters
Regularly monitor strategy performance and adjust parameters timely
维加斯通道综合策略说明
策略概述
基于维加斯双通道指标的综合交易策略，支持动态加仓和资金管理。策略采用多信号融合机制，包括经典价穿信号、突破信号和回踩信号，结合趋势过滤、RSI+MACD过滤和成交量过滤，确保信号的可靠性。
核心功能
动态加仓：同向信号继续加仓，反向信号全部平仓
智能止盈止损：基于ATR的动态止盈止损，每次新信号更新
资金管理：支持动态总金额管理，实现复利增长
时间过滤：可设置交易时间范围
风险控制：最大订单数限制，防止过度加仓
杠杆使用说明
重要：本策略不使用TradingView的保证金功能
设置方法
总资金 = 实际资金 × 杠杆倍数
示例：实际有100U，想使用10倍杠杆 → 总资金设置为 100 × 10 = 1000U
交易金额计算
每笔交易百分比基于杠杆后的金额计算
示例：设置10% → 实际交易 100U保证金 × 10倍杠杆 = 1000U交易金额
最大订单数配置
必须配合杠杆后的金额使用
示例：1000U总资金，10%单笔，最大10单 = 最多使用1000U
注意：不要超过总资金的100%，避免过度杠杆
参数配置建议
杠杆配置示例
实际资金100U，5倍杠杆，总资金设置500U，单笔百分比10%，单笔金额50U，建议最大订单数10单
实际资金100U，10倍杠杆，总资金设置1000U，单笔百分比10%，单笔金额100U，建议最大订单数10单
实际资金100U，20倍杠杆，总资金设置2000U，单笔百分比5%，单笔金额100U，建议最大订单数20单
风险控制
保守型：5-10倍杠杆，10%单笔，最大5-8单
激进型：10-20倍杠杆，5-10%单笔，最大10-15单
极限型：20倍以上杠杆，2-5%单笔，最大20单以上
策略优势
信号可靠性：多重过滤机制，减少假信号
资金效率：动态资金管理，实现复利增长
风险可控：最大订单数限制，防止爆仓
灵活配置：支持多种杠杆和资金配置方案
时间控制：可设置交易时间，避开高风险时段
使用注意事项
确保总资金设置正确（实际资金×杠杆倍数）
最大订单数不要超过总资金允许的范围
建议从保守配置开始，逐步调整参数
定期监控策略表现，及时调整参数
[Outperforms Bitcoin Since 2011] Professional MA StrategyThis Strategy OUTPEFORMS Bitcoin since 2011.
Timeframe: Daily
MA used (Fast and Slow): WMA (Weighted Moving Average)
Fast MA Length: 30 days (Reflects the Monthly Trend - Short Term Perspective)
Slow MA Length: 360 days (Reflects the Annual Trend - Long Term Perspective)
Position Size: 100% of equity
Margin for Long = 10% of equity
Margin for Short = 10% of equity
Open Long = Typical Price Crosses Above its Fast MA and Price is above its Slow MA
Open Short = Typical Price Crosses Below its Fast MA and Price is below its Slow MA
Close Long = Typical Price Crosses Below its Fast MA
Close Short = Typical Price Crosses Below its Fast MA
note: Typical Price = (high + low + close) / 3
KCandle Strategy 1.0# KCandle Strategy 1.0 - Trading Strategy Description
## Overview
The **KCandle Strategy** is an advanced Pine Script trading system based on bullish and bearish engulfing candlestick patterns, enhanced with sophisticated risk management and position optimization features.
## Core Logic
### Entry Signal Generation
- **Pattern Recognition**: Detects bullish and bearish engulfing candlestick formations
- **EMA Filter**: Uses a customizable EMA (default 25) to filter trades in the direction of the trend
- **Entry Levels**:
- **Long entries** at 25% of the candlestick range from the low
- **Short entries** at 75% of the candlestick range from the low
- **Signal Validation**: Orange candlesticks indicate valid setup conditions
### Risk Management System
#### 1. **Stop Loss & Take Profit**
- Configurable stop loss in pips
- Risk-reward ratio setting (default 2:1)
- Visual representation with colored lines and labels
#### 2. **Break-Even Management**
- Automatically moves stop loss to break-even when specified R:R is reached
- Customizable break-even offset for added protection
- Prevents losing trades after reaching profitability
#### 3. **Trailing Stop System**
- **Activation Trigger**: Activates when position reaches specified R:R level
- **Distance Control**: Maintains trailing stop at defined distance from entry
- **Step Management**: Moves stop loss forward in incremental R steps
- **Dynamic Protection**: Locks in profits while allowing for continued upside
### Advanced Features
#### Position Management
- **Pyramiding Support**: Optional multiple position entries with size reduction
- **Order Expiration**: Pending orders automatically cancel after specified bars
- **Position Sizing**: Percentage-based allocation with pyramid level adjustments
#### Visual Interface
- **Real-time Monitoring**: Comprehensive information panel with all strategy metrics
- **Historical Tracking**: Visual representation of past trades and levels
- **Color-coded Indicators**: Different colors for break-even, trailing, and standard stops
- **Debug Options**: Optional labels for troubleshooting and optimization
## Key Parameters
### Basic Settings
- **EMA Length**: Trend filter period
- **Stop Loss**: Risk per trade in pips
- **Risk/Reward**: Target profit ratio
- **Order Validity**: Duration of pending orders
### Risk Management
- **Break-Even R:R**: Profit level to trigger break-even
- **Trailing Activation**: R:R level to start trailing
- **Trailing Distance**: Stop distance from entry when trailing
- **Trailing Step**: Increment for stop loss advancement
## Strategy Benefits
1. **Objective Entry Signals**: Based on proven candlestick patterns
2. **Trend Alignment**: EMA filter ensures trades align with market direction
3. **Robust Risk Control**: Multiple layers of protection (SL, BE, Trailing)
4. **Profit Optimization**: Trailing stops maximize winning trade potential
5. **Flexibility**: Extensive customization options for different market conditions
6. **Visual Clarity**: Complete visual feedback for trade management
## Ideal Use Cases
- **Swing Trading**: Medium-term positions with trend-following approach
- **Breakout Trading**: Capturing momentum from engulfing patterns
- **Risk-Conscious Trading**: Suitable for traders prioritizing capital preservation
- **Multi-Timeframe**: Adaptable to various timeframes and instruments
---
*The KCandle Strategy combines traditional technical analysis with modern risk management techniques, providing traders with a comprehensive tool for systematic market participation.*
EnsembleX📌 EnsembleX – Multi-Feature Voting Strategy
//@version=5
//@fenyesk
🔹 Overview
EnsembleX is a multi-indicator ensemble trading Strategy that combines price action, momentum, volume, and volatility signals into a unified consensus model. Instead of relying on a single indicator, EnsembleX uses a weighted voting system to determine trade entries and exits, making it more adaptive across different market conditions (crypto, forex, and equities).
The system calculates feature-engineered signals, normalizes them, applies lagged context, and then uses ensemble consensus weighting to decide whether to go long or short. An adaptive threshold (ATR-based) ensures risk-sensitive entries during volatile or quiet regimes.
🔹 Core Features
📈 Trend & Momentum Features
EMA Slope (f_slope): Captures directional bias and steepness of trend.
RSI (f_rsi): Measures overbought/oversold conditions with normalization.
CCI (f_cci): Detects price deviations from mean for extreme reversals.
ADX (f_adx, DMI+/-): Evaluates trend strength and directional dominance.
📊 Volatility Features
Standard Deviation (f_stdev): Captures volatility spikes relative to history.
Bollinger Band Position (f_bb): Measures where price sits within BB envelope.
Log Returns (f_logr): Tracks distribution-adjusted price changes.
💵 Volume-Based Features
MFI (f_mfi): Volume-weighted momentum confirming price moves.
Volume Pressure (f_vol): Combines normalized volume ratio with price change.
🧮 Feature Engineering
Normalization & Z-score scaling: Keeps features comparable across regimes.
Lag Features (optional): Adds short-term historical context to signals.
Composite Aggregates:
Momentum Composite (mom): RSI + CCI + MFI blend.
Trend Composite (trd): ADX + Slope blend.
Volatility Composite (volat): StDev + Volume blend.
🔹 Signal Generation
Each feature produces an expert signal (+1 bull, -1 bear, 0 neutral). Examples:
RSI rising from oversold → Bull signal.
ADX strong + DMI+ dominance → Bull signal.
Bollinger Band breakout + reversal → Bear signal.
Volume pressure > threshold → Directional confirmation.
🔹 Ensemble Voting Mechanism
Each signal is assigned a weight (weight_rsi, weight_adx, weight_mfi, etc.).
Final bull/bear confidence is computed as a weighted probability.
Trades trigger only when consensus ≥ threshold.
Threshold adapts dynamically based on ATR / volatility regime.
🔹 Trading Logic
✅ Long Entry:
Bull consensus ≥ threshold and stronger than bear side.
✅ Short Entry:
Bear consensus ≥ threshold and stronger than bull side.
✅ Optional Exits:
Close on opposite signal flip (configurable by position side).
🔹 Visualization
Plots bull and bear confidence curves.
Plots both base threshold and adaptive ATR-adjusted threshold.
Easy to see how consensus builds before trades trigger.
⚡ Key Benefits
Robustness: Reduces reliance on any single indicator.
Flexibility: Works across assets and timeframes (crypto, forex, stocks).
Adaptive: Threshold adjusts automatically in volatile or quiet markets.
Transparency: Plotted consensus and threshold lines make signals easy to interpret.
📢 Usage Notes
Best used on 1h–4h for swing trades, or 5m–15m for intraday setups.
Combine with risk management (TP/SL, position sizing) for live trading.
Ensemble weights (weight_rsi, weight_adx, etc.) can be tuned per asset.
👉 This script is designed for backtesting and research. Results vary depending on the asset, timeframe, and parameter tuning.
Weekend Hunter Ultimate v6.2 Weekend Hunter Ultimate v6.2 - Automated Crypto Weekend Trading System
OVERVIEW:
Specialized trading strategy designed for cryptocurrency weekend markets (Saturday-Sunday) when institutional traders are typically offline and market dynamics differ significantly from weekdays. Optimized for 15-minute timeframe execution with multi-timeframe confluence analysis.
KEY FEATURES:
- Weekend-Only Trading: Automatically activates during configurable weekend hours
- Dynamic Leverage: 5-20x leverage adjusted based on market safety and signal confidence
- Multi-Timeframe Analysis: Combines 4H trend, 1H momentum, and 15M execution
- 10 Pre-configured Crypto Pairs: BTC, ETH, LINK, XRP, DOGE, SOL, AVAX, PEPE, TON, POL
- Position & Risk Management: Max 4 concurrent positions, -30% account protection
- Smart Trailing Stops: Protects profits when approaching targets
RISK MANAGEMENT:
- Maximum daily loss: 5% (configurable)
- Maximum weekend loss: 15% (configurable)
- Per-position risk: Capped at 120-156 USDT
- Emergency stops for flash crashes (8% moves)
- Consecutive loss protection (4 losses = pause)
TECHNICAL INDICATORS:
- CVD (Cumulative Volume Delta) divergence detection
- ATR-based dynamic stop loss and take profit
- RSI, MACD, Bollinger Bands confluence
- Volume surge confirmation (1.5x average)
- Weekend liquidity adjustments
INTEGRATION:
- Designed for Bybit Futures (0.075% taker fee)
- WunderTrading webhook compatibility via JSON alerts
- Minimum position size: 120 USDT (Bybit requirement)
- Initial capital: $500 recommended
TARGET METRICS:
- Win rate target: 65%
- Average win: 5.5%
- Average loss: 1.8%
- Risk-reward ratio: ~3:1
IMPORTANT DISCLAIMERS:
- Past performance does not guarantee future results
- Leveraged trading carries substantial risk of loss
- Weekend crypto markets have 13% of normal liquidity
- Not suitable for traders who cannot afford to lose their entire investment
- Requires continuous monitoring and adjustment
USAGE:
1. Apply to 15-minute charts only
2. Configure weekend hours for your timezone
3. Set up webhook alerts for automation
4. Monitor performance table in top-right corner
5. Adjust parameters based on your risk tolerance
This is an experimental strategy for educational purposes. Always test with small amounts first and never invest more than you can afford to lose completely.
Zaman Bazlı Slope & Delta RSI Stratejisi (HA & Source Seçimli)5 ayrı zaman diliminde çalışan rsi ortalamaları ile hesap yaparak sinyal üreten bir strateji
Parametric Multiplier Backtester🧪 An experimental educational tool for visual market analysis and idea testing through the multiplication and interaction of core technical parameters. It allows you to observe in real time how the combination of indicators affects the resulting curve and the potential efficiency of trading strategies.
📖 Detailed Description
1. Philosophy & Purpose of the Tool
This backtester is not created to search for the “Holy Grail,” but for deep learning and analysis. It is intended for:
👶 Beginner traders – to visually understand how basic indicators work and interact with each other.
🧠 Experienced analysts – to search for new ideas and non-obvious relationships between different aspects of the market (trend, volatility, momentum, volume).
The core idea is combining parameters through multiplication.
👉 Why multiplication? Unlike simple addition, multiplication strengthens signals only when several factors align in the same direction. If at least one parameter shows weakness (close to zero in normalized form), it suppresses the overall result, serving as a filter for false signals.
2. How does it work?
Step 1: Parameter Selection
The tool gathers data from 9 popular indicators: 📈 Price, RSI, ADX, Momentum, ROC, ATR, Volume, Acceleration, Slope.
Step 2: Normalization
Since these indicators differ in nature and scale (e.g., RSI from 0–100 vs ATR in points), they are brought to a unified range. Each parameter is normalized within a given period (Normalization Period). This is the key step for proper functioning.
Step 3: Multiplication
The parameters enabled by the user are multiplied, creating a new derived value — Product Line. This line is an aggregated reflection of the selected market model.
Step 4: Smoothing
The resulting line can be noisy. The Smooth Product Line function (via SMA) reduces noise and highlights the main trend.
Step 5: Interpretation
The smoothed Product Line is compared with its own moving average (Mean Line). Crossovers generate trading signals.
3. What conclusions can be drawn from multiplying parameters?
⚡ RSI × Momentum × Volume – Strength of momentum confirmed by volume. High values may indicate strong, volume-backed moves.
📊 ADX × ATR – Strength of trend and its volatility. High values may signal the beginning of a strong trending move with high volatility.
🚀 Price × Slope × Acceleration – Combined speed and acceleration of the trend. Shows not only where price is going, but with what acceleration.
❌ Disabling parameters – By turning parameters on/off (e.g., Volume), you can instantly see how important each factor is for the current market situation.
4. Real-Time Mode & Instant Feedback
The main educational value of this tool is interactivity:
🔄 Turn indicators on/off in real time.
⏱ Change their periods and instantly observe how the Product Line shape and behavior changes.
📉 Immediately see how these changes affect historical trading signals (blue/red arrows) and strategy performance metrics (Profit Factor, Net Profit, etc.).
This process develops “market intuition” and helps understand which settings work better under different conditions (trend vs range).
5. Default Settings & Recommendations
⚙️ Default settings are optimized for demonstration on the 4H timeframe of the SOLUSDT crypto pair.
Parameter Settings: Switch group (Use RSI, Use ADX, etc.).
Normalization Period (20): Lower = more sensitive, Higher = smoother.
Smooth Product Line (true): Enabled by default for clarity.
Smoothing Period (200): Main sensitivity setting.
Trend Filter: Optional 200-SMA filter. Strategy trades only in the main trend direction.
⚠️ Important Warning: This is an experimental & educational tool. The signals it generates are the result of a mathematical model and are not a ready-to-use trading strategy. Always backtest ideas and apply risk management before risking real money.
EMA Crossover Cloud w/Range-Bound FilterA focused 1-minute EMA crossover trading strategy designed to identify high-probability momentum trades while filtering out low-volatility consolidation periods that typically result in whipsaw losses. Features intelligent range-bound detection and progressive market attention alerts to help traders manage focus and avoid overtrading during unfavorable conditions.
Key Features:
EMA Crossover Signals: 10/20 EMA crossovers with volume surge confirmation (1.3x 20-bar average)
Range-Bound Filter: Automatically detects when price is consolidating in tight ranges (0.5% threshold) and blocks trading signals during these periods
Progressive Consolidation Stages: Visual alerts progress through Range Bound (red) → Coiling (yellow) → Loading (orange) → Trending (green) to indicate market compression and potential breakout timing
Market Attention Gauge: Helps manage focus between active trading and other activities with states: Active (watch close), Building (check frequently), Quiet (check occasionally), Dead (handle other business)
Smart RSI Exits: Cloud-based and RSI extreme level exits with conservative stop losses
Dual Mode Operation: Separate settings allow full backtesting performance while providing visual stay-out warnings for manual trading
How to Use:
Entry Signals: Trade aqua up-triangles (long) and orange down-triangles (short) when they appear with volume confirmation
Stay-Out Warnings: Ignore gray "RANGE" triangles - these indicate crossovers during range-bound periods that should be avoided
Monitor Top-Right Display:
Range: Current 60-bar dollar range
Attention: Market activity level for focus management
Status: Consolidation stage (trade green/yellow, avoid red, prepare for orange)
Position Sizing: Default 167 shares per signal, optimized for the crossover frequency
Alerts: Enable consolidation stage alerts and market attention alerts for automated notifications
Recommended Settings:
Timeframe: 1-minute charts
Symbol: Optimized for volatile stocks like TSLA
"Apply Filter to Backtest": Keep OFF for realistic backtesting, ON to see filtered results
Risk Management:
The strategy includes built-in overtrading protection by identifying and blocking trades during low-volatility periods. The progressive consolidation alerts help identify when markets are "loading" for significant moves, allowing traders to position appropriately for higher-probability setups.
JFC 21:52JFC 21:52 — Brief Description
Concept: Pure time/price rule, no indicators.
Reference: Close at 21:20 (chart/exchange timezone).
Entry (21:52):
– LONG if price is below the 21:20 close.
– SHORT if price is above the 21:20 close.
– Equal → no trade.
Exit: Force close at 22:13.
Frequency: Max one trade per day.
Note: Use 1-minute resolution and the correct chart timezone; market must be trading at those times.
Indecision Candle with 2 Candle Confirmation + 500 EMA - parthibIndecision Candle with 2 Candle Confirmation + 500 EMA
Indecision Candle with 2 Candle Confirmation + 500 EMA
Indecision Candle with 2 Candle Confirmation + 500 EMAIndecision Candle with 2 Candle Confirmation + 500 EMAIndecision Candle with 2 Candle Confirmation + 500 EMA
Hybrid RSI Strategy [Heifereum ]This is a hybrid script that combines visual RSI indicator signals with an optional backtestable trading strategy.
BUY Entry: When RSI crosses above the oversold level (default 30)
SELL Exit: When RSI crosses below the overbought level (default 70)
Timeframe: Works best on trending assets (crypto, forex, indices) in 5min to 1H
Backtest Toggle: Turn ON/OFF live testing using the Enable Backtest Mode? setting
Visual Cues: Buy/Sell labels, background coloring, and alerts ready for webhook automation
Use this strategy to visually explore RSI dynamics, run performance backtests, or hook up to external bots via alerts.
Fidelweiss One-Minute BOS Hunter [Heikin Ashi Candles]Volatility Scalper M1 is a one-minute trading strategy designed for highly volatile markets.
It combines market structure (BOS/ChoCH, support & resistance fractals) with trend filters (ADX, DMI, HMA, Linear Regression) to identify high-probability breakout setups.
Key features:
Dynamic entry signals based on broken support/resistance and trend confirmation
Take Profit & Stop Loss automatically calculated from average entry price
Optional one-side-only trading mode
Time filters (block trading during specific hours/dates)
Daily force exit and drawdown protection options
Visual table with live PnL, dominance metrics, ADX, and ATR
This strategy is intended for scalping on the M1 timeframe, but can be adapted to other timeframes.
It is optimized for volatile assets (crypto, forex, indices) where quick entries and exits are crucial.
⚠️ Disclaimer: This script is for educational purposes only. It is not financial advice. Always backtest thoroughly and use proper risk management.
Ekoparaloji Strategy Plus V2For spot transactions, set your starting capital at 40% of your equity. For forward (leveraged) transactions, you can set your starting capital as equity.
BBAWE 事件合約This is a paid version. Please contact me or follow me.
✅ Key Features
Strict 1-bar confirmation for cleaner entries.
Fast EMA filter to avoid false breakouts.
Cooldown system to reduce overtrading.
Visual markers for Key Bars and trade entries.
Fully customizable parameters (BB period, EMA length, cooldown bars).
📈 Best Suited For
Short-term scalping or intraday setups.
Catching quick reversals or momentum continuation.
Traders who need stricter signal validation to filter noise.
event contract boll 事件合約Bollinger Bands (BB)
Strict t1 Confirmation
Only the very next candle (t1) is checked:
Long
Short
Prevents rapid-fire entries in choppy markets.✅ Key Features
Strict 1-bar confirmation for cleaner entries.
Fast EMA filter to avoid false breakouts.
Cooldown system to reduce overtrading.
Visual markers for Key Bars and trade entries.
Fully customizable parameters (BB period, EMA length, cooldown bars).
📈 Best Suited For
Short-term scalping or intraday setups.
Catching quick reversals or momentum continuation.
Traders who need stricter signal validation to filter noise.
MIRRORPIP SUPERTREND BASICThis is a plug and play strategy that is fully automated with Mirrorpip
Anyone can automate crypto trading using this pine
Currently this works with
- DELTA EXCHANGE INDIA
- COIN DCX
-COIN SWITCH
MOHStrategy Description
Uses Heikin Ashi candles to filter market noise and identify trend direction.
Entry is allowed only when strong HA candles appear (bullish without lower wick, bearish without upper wick).
Doji candles signal possible reversal.
استخدام شموع Heikin Ashi لتقليل الضوضاء وتحديد اتجاه الترند.
الدخول فقط عند ظهور شموع قوية (صاعدة بدون ذيل سفلي، هابطة بدون ذيل علوي).
شمعة الدوجي = إشارة انعكاس محتملة.
Ekoparaloji Strategy PlusFor spot transactions, set your starting capital at 40% of your equity. For forward (leveraged) transactions, you can set your starting capital as equity.
VYM-1D (E.Trader)Summary
Strategy on VYM (Vanguard High Dividend Yield ETF), 1D timeframe (2006–2025).
Initial capital: 1,000 USD, 100% reinvest.
Long-only strategy with realistic commissions and slippage (Interactive Brokers: $0.005/share, 3 ticks).
Key results (2006–2025)
• Total P&L: +639.61%
• CAGR: ~11.2% (vs Buy & Hold: 6.9%) → ~1.6x higher annualized return
• Profit factor: 2.39
• Winning trades: 68.66%
• Max drawdown: below 20% (see note below)
• Time in the market: ~56% (trading days basis)
• Buy & Hold return: +172.67% → Strategy outperforms by ~3.7x
Aberrant Max Drawdown to Signal
The reported max drawdown of 42% is not fully representative of actual risk.
It is inflated by data anomalies in TradingView’s historical VYM feed, specifically:
• May 6, 2010 (Flash Crash): spurious low print around June 11, 2010 generated an artificial drawdown >40%.
• Sep 17, 2015: another spike in adjusted data created a false drawdown >27%.
These artifacts are technical issues in the data, not sustained losses.
When corrected, the realistic historical drawdown is below 20%, aligning with expected volatility for a dividend-focused ETF.
Strategy logic
• Restricted to VYM on ARCA, in daily timeframe
• Long entries only (no shorts)
• Exploits two major biases: 1) trends and 2) overreactions
• Excludes very high VIX periods
• Implements calculated stop-losses
• Integrates commission and slippage to reflect real trading conditions (based on Interactive Brokers usage)
Focus 2008–2009 (Financial crisis, May 31, 2008 – Dec 31, 2009)
• Total return: +70.54%
• Profit factor: 39.35
• Winning trades: 94.12%
• Max drawdown: 4.70%
Buy & Hold over the same period: –12.96%
Focus 2020 (COVID crash, Jan 31, 2020 – Dec 31, 2021)
• Total return: +26.63%
• Profit factor: 2.32
• Winning trades: 64.29%
• Max drawdown: 13.55%
Buy & Hold return: +16.90%
Observations
• Strong outperformance vs Buy & Hold with less exposure
• Robust across crises (2008, COVID-2020)
• Limited drawdowns (below 20%), faster recoveries
Model validation and parameter weighting
To check robustness and avoid overfitting, I use a simple weighted-parameters ratio (explained in more detail here: Reddit post ).
In this strategy:
• 4 primary parameters (weight 1)
• 5 secondary parameters (weight 0.5)
• Weighted param count = 4×1 + 5×0.5 = 6.5
• Total trades = 268
• Ratio = 268 ÷ 6.5 ≈ 41
Since this ratio is well above the 25 threshold I usually apply, it appears the model is not overfitted — especially given its consistent gains even through crises such as 2008 and COVID-2020.
Disclaimer
This is an educational backtest. It does not constitute investment advice.
Past performance does not guarantee future results. Use at your own risk.
Further notes
In practice, systematic strategies like this are usually executed through automation to avoid human bias and ensure consistency. For those interested, I share more about my general approach and related tools here: emailtrader.app
