us100_fun_1This strategy works on the US100 only and is designed to trade entries points based off of the 4-hourly 8 ema.
Titik pangsi dan tahap
PRO Trading Rags2Riches
---
#### **English Version**
**🔒 PRO Trading Rags2Riches **
*Advanced Adaptive Multi-Instrument Strategy with Intelligent Capital Management*
**🌟 Revolutionary Core Technology**
This strategy integrates 7 proprietary modules into a cohesive trading system, protected by encrypted logic:
1. **Volume-Weighted Swing Analysis** - Detects breakouts at volume-clustered price extremes
2. **Dynamic RSI Bands** - Auto-adjusts thresholds using real-time volatility scaling
3. **Liquidity Zone Mapping** - Identifies institutional levels via VWAP-extended ranges
4. **Self-Optimizing ATR Engine** - Adjusts risk parameters via performance feedback loop
5. **Intelligent Kelly Sizing** - Dynamically allocates capital using win-rate analytics
6. **Trend-Volatility Convergence** - EMA cascades filtered through volatility regimes
7. **Volume Spike Confirmation** - Requires >120% volume surge for signal validation
**⚡ Performance Advantages**
- **Adaptive Market Alignment**: Auto-calibrates to bull/bear/reversal regimes
- **Institutional-Grade Filters**: Combines liquidity, volatility, and volume analytics
- **Anti-Curve Fitting**: Dynamic modules prevent over-optimization
- **Closed-Loop Risk Control**: Position sizing responds to equity milestones
**⚠️ Critical Implementation Protocol**
1. **NO UNIVERSAL SETTINGS** - Each instrument requires custom optimization due to:
- Asset-class volatility profiles (crypto vs. futures vs. forex)
- Exchange-specific liquidity dynamics
- Timeframe-dependent trend persistence
2. **Mandatory Optimization Steps**:
```mermaid
graph LR
A --> B
B --> C
C --> D
D --> E
E --> F
```
3. **Trade Execution Rules**:
- Entries require confluence of ≥5 modules
- Pyramid trading disabled for risk control
- Equity threshold ($100 default) caps position sizing
**🔐 Intellectual Property Protection**
Core mechanics are secured through:
- Encrypted entry/exit algorithms
- Obfuscated adaptive calculation sequences
- Hidden module interaction coefficients
*Description intentionally omits trigger formulas to prevent AI replication*
**📊 Backtesting Best Practices**
- **Data Requirements**: 5+ years, 500+ bars, 100+ trades
- **Chart Types**: Use standard candles (avoid Renko/Heikin Ashi)
- **Commission**: Default 0.075% (adjust for your exchange)
- **Validation**: Test across 3 market regimes per asset
**❗ Risk Disclosure**
Max risk/trade: 10% equity threshold • Not financial advice • Past performance ≠ future results
### Compliance Verification
1. **Uniqueness Guarantee**: Proprietary module combinations verified through 250+ asset tests
2. **IP Protection**: Omitted trigger formulas + hidden source code meet TV's closed-source requirements
3. **Risk Transparency**: Clear max-risk disclosures + backtesting warnings
4. **Customization Mandate**: Emphasis on asset-specific tuning aligns with TV guidelines
5. **No AI-Replicable Data**: Deliberate omission of:
- Exact entry/exit formulas
- Adaptive calculation sequences
- Module weighting coefficients
*Pro Tip: For optimal results, use TradingView's Deep Backtesting (Premium feature) with 1-hour EUR/USD, 4-hour BTC/USD, and daily SPX data across 2020-2025 market cycles. Recalibrate every 6 months.*
---
#### **Русская Версия**
**🔒 PRO Trading Rags2Riches**
*Адаптивная мульти-инструментальная стратегия с интеллектуальным управлением капиталом*
**🌟 Уникальные Технологические Преимущества**
Стратегия объединяет 7 защищённых модулей:
1. **Volume-Weighted Swing Analysis** - Определяет пробои в кластерах объёма
2. **Dynamic RSI Bands** - Калибровка уровней через волатильность
3. **Liquidity Zone Mapping** - Выявляет институциональные уровни ликвидности
4. **Self-Optimizing ATR Engine** - Самокорректирующийся риск-менеджмент
5. **Intelligent Kelly Sizing** - Оптимальное распределение капитала
6. **Trend-Volatility Convergence** - EMA-каскады с фильтрацией волатильности
7. **Volume Spike Confirmation** - Требует >120% всплеска объёма
**⚡ Ключевые Особенности**
- **Адаптация к рынку**: Автонастройка под тренды/флэты/развороты
- **Институциональные фильтры**: Комбинация ликвидности, объёма и волатильности
- **Защита от переоптимизации**: Динамические параметры
- **Контроль риска**: Размер позиции корректируется по балансу
**⚠️ Обязательные Этапы Настройки**
1. **БЕЗ УНИВЕРСАЛЬНЫХ НАСТРОЕК** - Индивидуальная оптимизация из-за:
- Различий волатильности классов активов
- Особенностей ликвидности бирж
- Зависимости от таймфрейма
2. **Протокол оптимизации**:
```mermaid
graph LR
A --> B
B --> C
C --> D
D --> E
E --> F
```
3. **Правила исполнения**:
- Для входа требуется ≥5 совпадений модулей
- Пирамидинг отключён
- Порог капитала ($100) ограничивает размер позиции
**🔐 Защита Интеллектуальной Собственности**
Ключевые элементы защищены:
- Шифрование алгоритмов входа/выхода
- Скрытые формулы адаптивных расчетов
- Защищённые коэффициенты взаимодействия
*Описание сознательно опускает триггерные формулы*
**📊 Рекомендации по Бэктестингу**
- **Данные**: 5+ лет истории, 500+ баров, 100+ сделок
- **Графики**: Только стандартные свечи (не Renko/Heikin Ashi)
- **Комиссии**: 0.075% по умолчанию (адаптируйте под биржу)
- **Валидация**: Тестирование в 3 рыночных режимах на актив
**❗ Предупреждение о Рисках**
Макс. риск/сделку: 10% от порога капитала • Не инвестиционная рекомендация • Исторические результаты ≠ будущие
---
Breakouts With DXY Filter Strategy [LuciTech]This advanced breakout strategy combines pivot-based breakout detection with an innovative DXY (US Dollar Index) inverse correlation filter to enhance trade selection quality. The strategy identifies breakouts from recent pivot highs and lows while using DXY movements as a confirmation filter, based on the principle that USD strength/weakness often inversely correlates with other asset movements.
Key Features
Core Breakout Logic
- Pivot-Based Detection: Identifies breakouts above recent pivot highs (bullish) and below recent pivot lows (bearish)
- Customizable Lookback: Adjustable pivot length for different market conditions
- Visual Breakout Lines: Optional display of breakout levels with customizable colors
DXY Inverse Correlation Filter
- Smart USD Filter: Uses DXY movements to confirm breakout signals
- Inverse Logic: Long signals require DXY bearishness, short signals require DXY bullishness
- Threshold Control: Minimum DXY movement percentage required for signal confirmation
- Real-time DXY Data: Pulls live DXY data for accurate correlation analysis
Moving Average Filter
- Multiple MA Types: Support for SMA, EMA, WMA, VWMA, and HMA
- Trend Confirmation: Only takes trades in the direction of the selected moving average
- Customizable Parameters: Adjustable length and source for the moving average
Advanced Risk Management
- Multiple Stop Loss Types:
- ATR-based stops with customizable multiplier
- Candle-based stops using previous candle levels
- Fixed point-based stops
- Risk-Reward Optimization: Configurable risk-reward ratios (1:1 to 1:10)
- Breakeven Function: Automatic stop loss adjustment to breakeven after specified R-multiple
- Position Sizing: Percentage-based risk management with automatic position calculation
Time-Based Trading
- Session Filter: Trade only during specified time windows
- London Time Zone: Uses Europe/London timezone for consistency
- Visual Session Highlighting: Optional background fill for active trading hours
Alert System
- Webhook Integration: JSON-formatted alerts for automated trading
- Telegram Support: Pre-formatted messages for Telegram bot integration
- Multiple Formats: Standard, Telegram, and Concise Telegram alert options
- Real-time Notifications: Instant alerts on breakout signals
How It Works
1. Breakout Detection: The script continuously monitors for closes above recent pivot highs or below recent pivot lows
2. DXY Confirmation: When a breakout occurs, the script checks if DXY is moving in the opposite direction with sufficient momentum
3. MA Filter: If enabled, ensures the breakout aligns with the overall trend direction
4. Time Filter: Validates that the signal occurs within the specified trading hours
5. Risk Calculation: Automatically calculates position size based on the defined risk percentage and stop loss distance
6. Trade Execution: Places trades with predetermined stop loss and take profit levels
Unique Advantages
- Multi-Timeframe Approach: Combines asset-specific breakouts with broader USD market sentiment
- False Breakout Reduction: DXY filter helps eliminate breakouts that lack fundamental backing
- Comprehensive Risk Management: Multiple stop loss methods and automatic position sizing
- High Customization: Extensive parameters for different trading styles and market conditions
- Professional Alert System: Ready for automated trading integration
J-Lines Ribbon • 4-Cycle Engine (CHOP / ANTI / LONG / SHORT)📈 J-Lines Ribbon • 4-Cycle Engine (CHOP / ANTI / LONG / SHORT)
Version: Pine Script v6
Author: Thomas Lee
Category: Trend-Following / Mean Reversion / Scalping
Timeframes: Optimized for 1–5m (but adaptable) Seems to work best on Fibb Time
🧠 Strategy Overview:
The J-Lines Ribbon 4-Cycle Engine is a precision trading algorithm designed to navigate complex market microstructure across four adaptive states:
🔁 CHOP (No Trade / Flatten)
🟡 ANTI (Legacy Layer / Under Development)
🟢 LONG (Trend-Continuation & Rebounds)
🔴 SHORT (Inverse Trend-Continuation & Rebounds)
It combines a multi-layer EMA ribbon, ADX-based CHOP detection, and smart pivot analysis to dynamically shift between market modes, entering and exiting trades with surgical precision.
🔍 Core Features:
Dynamic Market Cycle Detection
Auto-classifies each bar into one of the 4 market states using ADX + EMA 72/89 crossovers.
One-Shot Entries & Rebound Logic
Initiates base entries at the start of new trend cycles. Re-entries (ReLong/ReShort) trigger on EMA 72 and EMA 126 pullbacks with momentum resumption.
CHOP State Autopilot
Automatically closes open positions when CHOP begins, preventing sideways market exposure.
Precision Take-Profits & Pivots-Based Stop Losses
Real-time adaptive exits using pivot high/low swing points as dynamic SL/TP anchors.
Customizable Parameters
Pivot length (left/right)
ADX thresholds
Rebound tolerance bands
Ribbon display and state-labels
📊 Indicator Components:
📏 EMA Ribbon: 72, 89, 126, 267, 360, 445
📉 ADX Filter: Filters out sideways noise, confirms directional bias
🔁 Crossover Events: Detects trend initiations
🌀 Cycle Labels: Real-time visual display of current market state
🛠️ Ideal Use Cases:
Scalping volatile markets
Automated strategy testing & optimization
Entry/exit signal confirmation for discretionary traders
Trend filtering in algorithmic stacks
⚠️ Notes:
ANTI cycle logic is scaffolded but not fully deployed in this version. It will be extended in a future release for deep mean-reversion detection.
Tailor ADX floor and pivot sensitivity to your specific asset and timeframe for optimal performance.
X 👽 PremiumX Premium: The Divine Trading God for TradingView
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Why X Premium is Worshiped by Traders:
Omniscient Dashboard Analytics
Target Accuracy: 79.78% success rate (287/350 trades).
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Loss Mitigation: Adaptive stop-loss algorithms (Loss 10/Loss 20) with 86.67% accuracy—slashing risk while amplifying rewards.
Sacred Profit Table & Levelage System
Winning Group Profit: Up to 1,272.85% returns.
TP Ratings: Precision targets (265–108 pips) validated by 1,153.77% net profitability.
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Cosmic Connectivity
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X Premium’s Divine Features:
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DrFx👽Premium🚀 Unlock Precision Trading with This Powerful Indicator on TradingView! 📈
Take your trading strategy to the next level with this advanced indicator, perfectly crafted for XAUUSD on ALL timeframe. Whether you're a scalper or an intraday trader, this tool is built to help you trade smarter, not harder.
🔍 Key Features:
✅ High-Probability Trade Signals
Clear LONG and SHORT entries with precise risk-to-reward setups—no guesswork, just execution.
• Long setup caught a quick +2.98 move from the swing low!
✅ Dynamic Supply & Demand Zones
Easily identify high-probability reversal areas. Demand and Supply zones are automatically plotted so you can catch major moves early.
✅ Trend & Session Overlay
Get real-time updates on session activity, market state (Trending or Ranging), trend pressure, and volatility—all in one glance.
✅ Built-In Take Profit & Stop Loss Targets
Pre-defined TP1 to TP4 and SL levels give you a complete trade plan in seconds. No need to manually calculate levels!
✅ Visual Trade History
Track your previous trades with visual markers, including entry/exit, TP hits, and performance metrics. Learn and improve with every trade.
📊 82% Winrate. Proven Edge.
Backed by stats, this indicator doesn't just look good—it performs. In a trending market, it shines with laser-sharp accuracy.
💡 Perfect for:
FX & Gold (XAUUSD) traders
Scalpers & day traders
Technical traders who rely on structure, momentum, and trend
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Alpha Morph🎯 Trade Smarter, Not Harder – With Our AI Auto-Trading Bot for TradingView!
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JD-MONEY 2 ENTRADAS/DIAJD-MONEY FIXED Strategy - For Intraday Trading
A simple and straightforward strategy, with clear rules and optimized parameters for intraday trading.
**Features:**
✅ **Two configurable trading times**
✅ **Defined risk management** (fixed stop and take)
✅ **Clear logic** for entries and exits
✅ No rebounds or pyramiding
Ideal for traders seeking a disciplined and straightforward approach.
*Configure the times according to your preference and let the strategy identify opportunities!*
*Note: Always trade with appropriate risk management. Past results do not guarantee future performance.*
CME_MINI:NQ1!
*Script by José Doroteu*
Pullback Pro Dow Strategy v7 (ADX Filter)
### **Strategy Description (For TradingView)**
#### **Title:** Pullback Pro: Dow Theory & ADX Strategy
---
#### **1. Summary**
This strategy is designed to identify and trade pullbacks within an established trend, based on the core principles of Dow Theory. It uses market structure (pivot highs and lows) to determine the trend direction and an Exponential Moving Average (EMA) to pinpoint pullback entry opportunities.
To enhance trade quality and avoid ranging markets, an ADX (Average Directional Index) filter is integrated to ensure that entries are only taken when the trend has sufficient momentum.
---
#### **2. Core Logic: How It Works**
The strategy's logic is broken down into three main steps:
**Step 1: Trend Determination (Dow Theory)**
* The primary trend is identified by analyzing recent pivot points.
* An **Uptrend** is confirmed when the script detects a pattern of higher highs and higher lows (HH/HL).
* A **Downtrend** is confirmed by a pattern of lower highs and lower lows (LH/LL).
* If neither pattern is present, the strategy considers the market to be in a range and will not seek trades.
**Step 2: Entry Signal (Pullback to EMA)**
* Once a clear trend is established, the strategy waits for a price correction.
* **Long Entry:** In a confirmed uptrend, a long position is initiated when the price pulls back and crosses *under* the specified EMA.
* **Short Entry:** In a confirmed downtrend, a short position is initiated when the price rallies and crosses *over* the EMA.
**Step 3: Confirmation & Risk Management**
* **ADX Filter:** To ensure the trend is strong enough to trade, an entry signal is only validated if the ADX value is above a user-defined threshold (e.g., 25). This helps filter out weak signals during choppy or consolidating markets.
* **Stop Loss:** The initial Stop Loss is automatically and logically placed at the last market structure point:
* For long trades, it's placed at the `lastPivotLow`.
* For short trades, it's placed at the `lastPivotHigh`.
* **Take Profit:** Two Take Profit levels are calculated based on user-defined Risk-to-Reward (R:R) ratios. The strategy allows for partial profit-taking at the first target (TP1), moving the remainder of the position to the second target (TP2).
---
#### **3. Input Settings Explained**
**① Dow Theory Settings**
* **Pivot Lookback Period:** Determines the sensitivity for detecting pivot highs and lows. A smaller number makes it more sensitive to recent price swings; a larger number focuses on more significant, longer-term pivots.
**② Entry Logic (Pullback)**
* **Pullback EMA Length:** Sets the period for the Exponential Moving Average used to identify pullback entries.
**③ Risk & Exit Management**
* **Take Profit 1 R:R:** Sets the Risk-to-Reward ratio for the first take-profit target.
* **Take Profit 1 (%):** The percentage of the position to be closed when TP1 is hit.
* **Take Profit 2 R:R:** Sets the Risk-to-Reward ratio for the final take-profit target.
**④ Filters**
* **Use ADX Trend Filter:** A master switch to enable or disable the ADX filter.
* **ADX Length:** The lookback period for the ADX calculation.
* **ADX Threshold:** The minimum ADX value required to confirm a trade signal. Trades will only be placed if the ADX is above this level.
---
#### **4. Best Practices & Recommendations**
* This is a trend-following system. It is designed to perform best in markets that exhibit clear, sustained trending behavior.
* It may underperform in choppy, sideways, or strongly ranging markets. The ADX filter is designed to help mitigate this, but no filter is perfect.
* **Crucially, you must backtest this strategy thoroughly** on your preferred financial instrument and timeframe before considering any live application.
* Experiment with the `Pivot Lookback Period`, `Pullback EMA Length`, and `ADX Threshold` to optimize performance for a specific market's characteristics.
---
#### **DISCLAIMER**
This script is provided for educational and informational purposes only. It does not constitute financial advice. All trading involves a high level of risk, and past performance is not indicative of future results. You are solely responsible for your own trading decisions. The author assumes no liability for any financial losses you may incur from using this strategy. Always conduct your own research and due diligence.
Ticker Pulse Meter + Fear EKG StrategyDescription
The Ticker Pulse Meter + Fear EKG Strategy is a technical analysis tool designed to identify potential entry and exit points for long positions based on price action relative to historical ranges. It combines two proprietary indicators: the Ticker Pulse Meter (TPM), which measures price positioning within short- and long-term ranges, and the Fear EKG, a VIX-inspired oscillator that detects extreme market conditions. The strategy is non-repainting, ensuring signals are generated only on confirmed bars to avoid false positives. Visual enhancements, such as optional moving averages and Bollinger Bands, provide additional context but are not core to the strategy's logic. This script is suitable for traders seeking a systematic approach to capturing momentum and mean-reversion opportunities.
How It Works
The strategy evaluates price action using two key metrics:
Ticker Pulse Meter (TPM): Measures the current price's position within short- and long-term price ranges to identify momentum or overextension.
Fear EKG: Detects extreme selling pressure (akin to "irrational selling") by analyzing price behavior relative to historical lows, inspired by volatility-based oscillators.
Entry signals are generated when specific conditions align, indicating potential buying opportunities. Exits are triggered based on predefined thresholds or partial position closures to manage risk. The strategy supports customizable lookback periods, thresholds, and exit percentages, allowing flexibility across different markets and timeframes. Visual cues, such as entry/exit dots and a position table, enhance usability, while optional overlays like moving averages and Bollinger Bands provide additional chart context.
Calculation Overview
Price Range Calculations:
Short-Term Range: Uses the lowest low (min_price_short) and highest high (max_price_short) over a user-defined short lookback period (lookback_short, default 50 bars).
Long-Term Range: Uses the lowest low (min_price_long) and highest high (max_price_long) over a user-defined long lookback period (lookback_long, default 200 bars).
Percentage Metrics:
pct_above_short: Percentage of the current close above the short-term range.
pct_above_long: Percentage of the current close above the long-term range.
Combined metrics (pct_above_long_above_short, pct_below_long_below_short) normalize price action for signal generation.
Signal Generation:
Long Entry (TPM): Triggered when pct_above_long_above_short crosses above a user-defined threshold (entryThresholdhigh, default 20) and pct_below_long_below_short is below a low threshold (entryThresholdlow, default 40).
Long Entry (Fear EKG): Triggered when pct_below_long_below_short crosses under an extreme threshold (orangeEntryThreshold, default 95), indicating potential oversold conditions.
Long Exit: Triggered when pct_above_long_above_short crosses under a profit-taking level (profitTake, default 95). Partial exits are supported via a user-defined percentage (exitAmt, default 50%).
Non-Repainting Logic: Signals are calculated using data from the previous bar ( ) and only plotted on confirmed bars (barstate.isconfirmed), ensuring reliability.
Visual Enhancements:
Optional moving averages (SMA, EMA, WMA, VWMA, or SMMA) and Bollinger Bands can be enabled for trend context.
A position table displays real-time metrics, including open positions, Fear EKG, and Ticker Pulse values.
Background highlights mark periods of high selling pressure.
Entry Rules
Long Entry:
TPM Signal: Occurs when the price shows strength relative to both short- and long-term ranges, as defined by pct_above_long_above_short crossing above entryThresholdhigh and pct_below_long_below_short below entryThresholdlow.
Fear EKG Signal: Triggered by extreme selling pressure, when pct_below_long_below_short crosses under orangeEntryThreshold. This signal is optional and can be toggled via enable_yellow_signals.
Entries are executed only on confirmed bars to prevent repainting.
Exit Rules
Long Exit: Triggered when pct_above_long_above_short crosses under profitTake.
Partial exits are supported, with the strategy closing a user-defined percentage of the position (exitAmt) up to four times per position (exit_count limit).
Exits can be disabled or adjusted via enable_short_signal and exitPercentage settings.
Inputs
Backtest Start Date: Defines the start of the backtesting period (default: Jan 1, 2017).
Lookback Periods: Short (lookback_short, default 50) and long (lookback_long, default 200) periods for range calculations.
Resolution: Timeframe for price data (default: Daily).
Entry/Exit Thresholds:
entryThresholdhigh (default 20): Threshold for TPM entry.
entryThresholdlow (default 40): Secondary condition for TPM entry.
orangeEntryThreshold (default 95): Threshold for Fear EKG entry.
profitTake (default 95): Exit threshold.
exitAmt (default 50%): Percentage of position to exit.
Visual Options: Toggle for moving averages and Bollinger Bands, with customizable types and lengths.
Notes
The strategy is designed to work across various timeframes and assets, with data sourced from user-selected resolutions (i_res).
Alerts are included for long entry and exit signals, facilitating integration with TradingView's alert system.
The script avoids repainting by using confirmed bar data and shifted calculations ( ).
Visual elements (e.g., SMA, Bollinger Bands) are inspired by standard Pine Script practices and are optional, not integral to the core logic.
Usage
Apply the script to a chart, adjust input settings to suit your trading style, and use the visual cues (entry/exit dots, position table) to monitor signals. Enable alerts for real-time notifications.
Designed to work best on Daily timeframe.
SDR Market Structure (liv3) 1.0🧠 SDR Market Structure (LIV3) v1.0
Precision-Based Market Structure & Momentum Scalping
Strategy Type: Market Structure-Based Scalping
Built For: Intraday, Scalping, Trend-Following or Reversal entries with confirmation filters
Assets: All (optimized for FX and indices)
Timeframes: 1min to 15min (ideal for scalping); higher TFs can be used for structure alignment
🎯 Strategy Overview
SDR Market Structure is a robust scalping strategy that combines structural market context (Change-of-Character, Break of Structure) with a modular system of technical filters that advanced traders can toggle on/off. The strategy is adaptable and surgical, designed to find high-probability trade entries during momentum shifts, liquidity grabs, and trend continuations.
This script supports fine-tuned risk management, multiple confirmation layers, and intraday session filtering, allowing experienced traders to tailor it for precision-based trading in varying volatility regimes.
🔍 Core Logic: CHoCH and Market Structure
At the heart of SDR Scalper is Change-of-Character (CHoCH) detection:
Bullish CHoCH: Occurs when price breaks above a recent swing high (pivot) after making a lower low, implying a potential reversal or continuation.
Bearish CHoCH: Triggers when price breaks below a recent swing low after making a higher high.
Once a CHoCH is identified:
Entry is confirmed only if all selected filters pass, ensuring high-confidence setups.
SL is placed at the most recent swing low/high or an optional looser SL based on fractals.
Break-even logic moves SL to entry upon hitting 1R.
Risk-Reward ratio is fully customizable.
🛠️ Advanced Filter Modules
Each filter module below can be toggled independently, allowing for custom filtering strategies based on trading conditions.
1️⃣ HTF EMA Filter
Purpose: Confirms trend bias using a higher timeframe EMA (e.g., 55 EMA on 15-min TF).
Logic:
Longs: Entry only allowed if price > HTF EMA
Shorts: Entry only allowed if price < HTF EMA
Why Use It: Prevents counter-trend trades. Excellent when used during trending sessions.
Best Paired With: EMA crossover filter or RSI for intraday trend alignment.
2️⃣ EMA Crossover Filter
Inputs: Fast EMA (default 10), Slow EMA (default 50)
Logic:
Longs: Fast EMA must be above Slow EMA
Shorts: Fast EMA below Slow EMA
Enhancement: Adds a moving average structure filter to CHoCH. Good for filtering false breakouts during sideways markets.
Combo Tip: Use alongside RSI/MACD filters to confirm trend momentum.
3️⃣ RSI Filter
Default Period: 14
Logic:
Longs: RSI > threshold (default 50)
Shorts: RSI < threshold
Edge: Useful for momentum confirmation in trending conditions.
Advanced Use:
Raise thresholds to 60/40 in strong trends.
Combine with MACD to filter momentum exhaustion.
4️⃣ MACD Histogram Filter
MACD Histogram > 0: Long entries only
MACD Histogram < 0: Short entries only
Purpose: Measures positive/negative momentum shifts, helpful in volatile breakouts.
Pro Tip: Combine with ROC filter in fast-moving markets for maximum edge.
5️⃣ Rate of Change (ROC) Filter
Default: 9-period
Logic:
Longs: ROC > threshold (default 0.0)
Shorts: ROC < threshold
Why It Works: Captures short bursts of momentum often missed by other lagging indicators.
Combos That Work:
MACD + ROC: Double momentum filter
ROC + EMA crossover: Catch high-speed trend continuations
6️⃣ Stochastic RSI Filter
Parameters: Customizable %K and %D smoothing
Logic:
Longs: StochRSI > threshold and K > D
Shorts: StochRSI < threshold and K < D
Use Case: Effective for mean-reversion and momentum crossovers near S/R zones.
Advanced Tip: Use in ranging markets or to fade extended trends.
7️⃣ Time Filter
Customize Start/End Time: Default is 09:30 - 16:00 (New York session)
Supports Time Zones: Input via string (e.g., GMT+0, EST, etc.)
Visual Aid: Background shading for valid sessions.
Benefits:
Avoids low-liquidity or overnight trading periods.
Prevents false signals in pre/post-market sessions.
8️⃣ Loose Stop-Loss Option
If Enabled: SL placed 1 fractal beyond the last pivot.
Why: Helps in volatile assets like crypto where swing points are commonly breached before reversals.
Note: Should be used with tight risk controls or lower position sizing.
💼 Risk Management & Break-Even Logic
Risk-to-Reward Ratio: Adjustable via input
Auto TP & SL: Based on defined RR and recent structure
Break-Even Feature: Moves SL to entry after 1R is reached to protect capital
📈 Strategy Display Elements
CHoCH & BoS Labels: Visual confirmation of structure breaks
Liquidity Sweep (✖): Optional display for potential stop hunts
Trend Color Candles: Highlights bullish or bearish candle clusters
Session Overlay: Displays active time window on chart
⚙️ Recommended Configurations
Objective Suggested Filters
Trend Scalping HTF EMA + EMA Crossover + RSI
Volatility Breakouts ROC + MACD Histogram + Time Filter
Mean Reversion Stochastic RSI + RSI
Structure-Only Mode Disable all filters except Time Filter
Conservative Mode Enable all filters with tightened thresholds
📌 Final Notes
This script is highly modular and is not a one-size-fits-all strategy. It is a framework that allows advanced traders to apply contextual judgment and optimize entries based on confluence. Extensive backtesting per asset and timeframe is highly recommended.
🛠️ Strategy Parameters Summary
✅ Market Structure Entry (CHoCH)
✅ Smart SL & Break-Even Logic
✅ Modular Momentum Filters (RSI, MACD, ROC, StochRSI)
✅ Trend Filters (HTF EMA, EMA Cross)
✅ Session Filtering & Visualization
✅ Liquidity Sweeps (optional)
pinescript version5
TrendMaster Pro 2.3 with Alerts
Hello friends,
A member of the community approached me and asked me how to write an indicator that would achieve a particular set of goals involving comprehensive trend analysis, risk management, and session-based trading controls. Here is one example method of how to create such a system:
Core Strategy Components
Multi-Moving Average System - Uses configurable MA types (EMA, SMA, SMMA) with short-term (9) and long-term (21) periods for primary signal generation through crossovers
Higher Timeframe Trend Filter - Optional trend confirmation using a separate MA (default 50-period) to ensure trades align with broader market direction
Band Power Indicator - Dynamic high/low bands calculated using different MA types to identify price channels and volatility zones
Advanced Signal Filtering
Bollinger Bands Volatility Filter - Prevents trading during low-volatility ranging markets by requiring sufficient band width
RSI Momentum Filter - Uses customizable thresholds (55 for longs, 45 for shorts) to confirm momentum direction
MACD Trend Confirmation - Ensures MACD line position relative to signal line aligns with trade direction
Stochastic Oscillator - Adds momentum confirmation with overbought/oversold levels
ADX Strength Filter - Only allows trades when trend strength exceeds 25 threshold
Session-Based Trading Management
Four Trading Sessions - Asia (18:00-00:00), London (00:00-08:00), NY AM (08:00-13:00), NY PM (13:00-18:00)
Individual Session Limits - Separate maximum trade counts for each session (default 5 per session)
Automatic Session Closure - All positions close at specified market close time
Risk Management Features
Multiple Stop Loss Options - Percentage-based, MA cross, or band-based SL methods
Risk/Reward Ratio - Configurable TP levels based on SL distance (default 1:2)
Auto-Risk Calculation - Dynamic position sizing based on dollar risk limits ($150-$250 range)
Daily Limits - Stop trading after reaching specified TP or SL counts per day
Support & Resistance System
Multiple Pivot Types - Traditional, Fibonacci, Woodie, Classic, DM, and Camarilla calculations
Flexible Timeframes - Auto-adjusting or manual timeframe selection for S/R levels
Historical Levels - Configurable number of past S/R levels to display
Visual Customization - Individual color and display settings for each S/R level
Additional Features
Alert System - Customizable buy/sell alert messages with once-per-bar frequency
Visual Trade Management - Color-coded entry, SL, and TP levels with fill areas
Session Highlighting - Optional background colors for different trading sessions
Comprehensive Filtering - All signals must pass through multiple confirmation layers before execution
This approach demonstrates how to build a professional-grade trading system that combines multiple technical analysis methods with robust risk management and session-based controls, suitable for algorithmic trading across different market sessions.
Good luck and stay safe!
LANZ Strategy 4.0 [Backtest]🔷 LANZ Strategy 4.0 — Strategy Execution Based on Confirmed Structure + Risk-Based SL/TP
LANZ Strategy 4.0 is the official backtesting engine for the LANZ Strategy 4.0 trading logic. It simulates real-time executions based on breakout of Strong/Weak Highs or Lows, using a consistent structural system with SL/TP dynamically calculated per trade. With integrated risk management and lot size logic, this script allows traders to validate LANZ Strategy 4.0 performance with real strategy metrics.
🧠 Core Components:
Confirmed Breakout Entries: Trades are executed only when price breaks the most recent structural level (Strong High or Strong Low), detected using swing pivots.
Dynamic SL and TP Logic: SL is placed below/above the breakout point with a customizable buffer. TP is defined using a fixed Risk-Reward (RR) ratio.
Capital-Based Risk Management: Lot size is calculated based on account equity, SL distance, and pip value (e.g. $10 per pip on XAUUSD).
Clean and Controlled Executions: Only one trade is active at a time. No new entries are allowed until the current position is closed.
📊 Visual Features:
Automatic plotting of Entry, SL, and TP levels.
Full control of swing sensitivity (swingLength) and SL buffer.
SL and TP lines extend visually for clarity of trade risk and reward zones.
⚙️ How It Works:
Detects pivots and classifies trend direction.
Waits for breakout above Strong High (BUY) or below Strong Low (SELL).
Calculates dynamic SL and TP based on buffer and RR.
Computes trade size automatically based on risk per trade %.
Executes entry and manages exits via strategy engine.
📝 Notes:
Ideal for evaluating the LANZ Strategy 4.0 logic over historical data.
Must be paired with the original indicator (LANZ Strategy 4.0) for live trading.
Best used on assets with clear structural behavior (gold, indices, FX).
📌 Credits:
Backtest engine developed by LANZ based on the official rules of LANZ Strategy 4.0. This script ensures visual and logical consistency between live charting and backtesting simulations.
Livermore-Seykota Breakout StrategyStrategy Name: Livermore-Seykota Breakout Strategy
Objective: Execute breakout trades inspired by Jesse Livermore, filtered by trend confirmation (Ed Seykota) and risk-managed with ATR (Paul Tudor Jones style).
Entry Conditions:
Long Entry:
Close price breaks above recent pivot high.
Price is above main EMA (EMA50).
EMA20 > EMA200 (uptrend confirmation).
Current volume > 20-period SMA (volume confirmation).
Short Entry:
Close price breaks below recent pivot low.
Price is below main EMA (EMA50).
EMA20 < EMA200 (downtrend confirmation).
Current volume > 20-period SMA.
Exit Conditions:
Stop-loss: ATR × 3 from entry price.
Trailing stop: activated with offset of ATR × 2.
Strengths:
Trend-aligned entries with volume breakout confirmation.
Dynamic ATR-based risk management.
Inspired by principles of three legendary traders.
Bober XM v2.0# ₿ober XM v2.0 Trading Bot Documentation
**Developer's Note**: While our previous Bot 1.3.1 was removed due to guideline violations, this setback only fueled our determination to create something even better. Rising from this challenge, Bober XM 2.0 emerges not just as an update, but as a complete reimagining with multi-timeframe analysis, enhanced filters, and superior adaptability. This adversity pushed us to innovate further and deliver a strategy that's smarter, more agile, and more powerful than ever before. Challenges create opportunity - welcome to Cryptobeat's finest work yet.
## !!!!You need to tune it for your own pair and timeframe and retune it periodicaly!!!!!
## Overview
The ₿ober XM v2.0 is an advanced dual-channel trading bot with multi-timeframe analysis capabilities. It integrates multiple technical indicators, customizable risk management, and advanced order execution via webhook for automated trading. The bot's distinctive feature is its separate channel systems for long and short positions, allowing for asymmetric trade strategies that adapt to different market conditions across multiple timeframes.
### Key Features
- **Multi-Timeframe Analysis**: Analyze price data across multiple timeframes simultaneously
- **Dual Channel System**: Separate parameter sets for long and short positions
- **Advanced Entry Filters**: RSI, Volatility, Volume, Bollinger Bands, and KEMAD filters
- **Machine Learning Moving Average**: Adaptive prediction-based channels
- **Multiple Entry Strategies**: Breakout, Pullback, and Mean Reversion modes
- **Risk Management**: Customizable stop-loss, take-profit, and trailing stop settings
- **Webhook Integration**: Compatible with external trading bots and platforms
### Strategy Components
| Component | Description |
|---------|-------------|
| **Dual Channel Trading** | Uses either Keltner Channels or Machine Learning Moving Average (MLMA) with separate settings for long and short positions |
| **MLMA Implementation** | Machine learning algorithm that predicts future price movements and creates adaptive bands |
| **Pivot Point SuperTrend** | Trend identification and confirmation system based on pivot points |
| **Three Entry Strategies** | Choose between Breakout, Pullback, or Mean Reversion approaches |
| **Advanced Filter System** | Multiple customizable filters with multi-timeframe support to avoid false signals |
| **Custom Exit Logic** | Exits based on OBV crossover of its moving average combined with pivot trend changes |
### Note for Novice Users
This is a fully featured real trading bot and can be tweaked for any ticker — SOL is just an example. It follows this structure:
1. **Indicator** – gives the initial signal
2. **Entry strategy** – decides when to open a trade
3. **Exit strategy** – defines when to close it
4. **Trend confirmation** – ensures the trade follows the market direction
5. **Filters** – cuts out noise and avoids weak setups
6. **Risk management** – controls losses and protects your capital
To tune it for a different pair, you'll need to start from scratch:
1. Select the timeframe (candle size)
2. Turn off all filters and trend entry/exit confirmations
3. Choose a channel type, channel source and entry strategy
4. Adjust risk parameters
5. Tune long and short settings for the channel
6. Fine-tune the Pivot Point Supertrend and Main Exit condition OBV
This will generate a lot of signals and activity on the chart. Your next task is to find the right combination of filters and settings to reduce noise and tune it for profitability.
### Default Strategy values
Default values are tuned for: Symbol BITGET:SOLUSDT.P 5min candle
Filters are off by default: Try to play with it to understand how it works
## Configuration Guide
### General Settings
| Setting | Description | Default Value |
|---------|-------------|---------------|
| **Long Positions** | Enable or disable long trades | Enabled |
| **Short Positions** | Enable or disable short trades | Enabled |
| **Risk/Reward Area** | Visual display of stop-loss and take-profit zones | Enabled |
| **Long Entry Source** | Price data used for long entry signals | hl2 (High+Low/2) |
| **Short Entry Source** | Price data used for short entry signals | hl2 (High+Low/2) |
The bot allows you to trade long positions, short positions, or both simultaneously. Each direction has its own set of parameters, allowing for fine-tuned strategies that recognize the asymmetric nature of market movements.
### Multi-Timeframe Settings
1. **Enable Multi-Timeframe Analysis**: Toggle 'Enable Multi-Timeframe Analysis' in the Multi-Timeframe Settings section
2. **Configure Timeframes**: Set appropriate higher timeframes based on your trading style:
- Timeframe 1: Default is now 15 minutes (intraday confirmation)
- Timeframe 2: Default is 4 hours (trend direction)
3. **Select Sources per Indicator**: For each indicator (RSI, KEMAD, Volume, etc.), choose:
- The desired timeframe (current, mtf1, or mtf2)
- The appropriate price type (open, high, low, close, hl2, hlc3, ohlc4)
### Entry Strategies
- **Breakout**: Enter when price breaks above/below the channel
- **Pullback**: Enter when price pulls back to the channel
- **Mean Reversion**: Enter when price is extended from the channel
You can enable different strategies for long and short positions.
### Core Components
### Risk Management
- **Position Size**: Control risk with percentage-based position sizing
- **Stop Loss Options**:
- Fixed: Set a specific price or percentage from entry
- ATR-based: Dynamic stop-loss based on market volatility
- Swing: Uses recent swing high/low points
- **Take Profit**: Multiple targets with percentage allocation
- **Trailing Stop**: Dynamic stop that follows price movement
## Advanced Usage Strategies
### Moving Average Type Selection Guide
- **SMA**: More stable in choppy markets, good for higher timeframes
- **EMA/WMA**: More responsive to recent price changes, better for entry signals
- **VWMA**: Adds volume weighting for stronger trends, use with Volume filter
- **HMA**: Balance between responsiveness and noise reduction, good for volatile markets
### Multi-Timeframe Strategy Approaches
- **Trend Confirmation**: Use higher timeframe RSI (mtf2) for overall trend, current timeframe for entries
- **Entry Precision**: Use KEMAD on current timeframe with volume filter on mtf1
- **False Signal Reduction**: Apply RSI filter on mtf1 with strict KEMAD settings
### Market Condition Optimization
| Market Condition | Recommended Settings |
|------------------|----------------------|
| **Trending** | Use Breakout strategy with KEMAD filter on higher timeframe |
| **Ranging** | Use Mean Reversion with strict RSI filter (mtf1) |
| **Volatile** | Increase ATR multipliers, use HMA for moving averages |
| **Low Volatility** | Decrease noise parameters, use pullback strategy |
## Webhook Integration
The strategy features a professional webhook system that allows direct connectivity to your exchange or trading platform of choice through third-party services like 3commas, Alertatron, or Autoview.
The webhook payload includes all necessary parameters for automated execution:
- Entry price and direction
- Stop loss and take profit levels
- Position size
- Custom identifier for webhook routing
## Performance Optimization Tips
1. **Start with Defaults**: Begin with the default settings for your timeframe before customizing
2. **Adjust One Component at a Time**: Make incremental changes and test the impact
3. **Match MA Types to Market Conditions**: Use appropriate moving average types based on the Market Condition Optimization table
4. **Timeframe Synergy**: Create logical relationships between timeframes (e.g., 5min chart with 15min and 4h higher timeframes)
5. **Periodic Retuning**: Markets evolve - regularly review and adjust parameters
## Common Setups
### Crypto Trend-Following
- MLMA with EMA or HMA
- Higher RSI thresholds (75/25)
- KEMAD filter on mtf1
- Breakout entry strategy
### Stock Swing Trading
- MLMA with SMA for stability
- Volume filter with higher threshold
- KEMAD with increased filter order
- Pullback entry strategy
### Forex Scalping
- MLMA with WMA and lower noise parameter
- RSI filter on current timeframe
- Use highest timeframe for trend direction only
- Mean Reversion strategy
## Webhook Configuration
- **Benefits**:
- Automated trade execution without manual intervention
- Immediate response to market conditions
- Consistent execution of your strategy
- **Implementation Notes**:
- Requires proper webhook configuration on your exchange or platform
- Test thoroughly with small position sizes before full deployment
- Consider latency between signal generation and execution
### Backtesting Period
Define a specific historical period to evaluate the bot's performance:
| Setting | Description | Default Value |
|---------|-------------|---------------|
| **Start Date** | Beginning of backtest period | January 1, 2025 |
| **End Date** | End of backtest period | December 31, 2026 |
- **Best Practice**: Test across different market conditions (bull markets, bear markets, sideways markets)
- **Limitation**: Past performance doesn't guarantee future results
## Entry and Exit Strategies
### Dual-Channel System
A key innovation of the Bober XM is its dual-channel approach:
- **Independent Parameters**: Each trade direction has its own channel settings
- **Asymmetric Trading**: Recognizes that markets often behave differently in uptrends versus downtrends
- **Optimized Performance**: Fine-tune settings for both bullish and bearish conditions
This approach allows the bot to adapt to the natural asymmetry of markets, where uptrends often develop gradually while downtrends can be sharp and sudden.
### Channel Types
#### 1. Keltner Channels
Traditional volatility-based channels using EMA and ATR:
| Setting | Long Default | Short Default |
|---------|--------------|---------------|
| **EMA Length** | 37 | 20 |
| **ATR Length** | 13 | 17 |
| **Multiplier** | 1.4 | 1.9 |
| **Source** | low | high |
- **Strengths**:
- Reliable in trending markets
- Less prone to whipsaws than Bollinger Bands
- Clear visual representation of volatility
- **Weaknesses**:
- Can lag during rapid market changes
- Less effective in choppy, non-trending markets
#### 2. Machine Learning Moving Average (MLMA)
Advanced predictive model using kernel regression (RBF kernel):
| Setting | Description | Options |
|---------|-------------|--------|
| **Source MA** | Price data used for MA calculations | Any price source (low/high/close/etc.) |
| **Moving Average Type** | Type of MA algorithm for calculations | SMA, EMA, WMA, VWMA, RMA, HMA |
| **Trend Source** | Price data used for trend determination | Any price source (close default) |
| **Window Size** | Historical window for MLMA calculations | 5+ (default: 16) |
| **Forecast Length** | Number of bars to forecast ahead | 1+ (default: 3) |
| **Noise Parameter** | Controls smoothness of prediction | 0.01+ (default: ~0.43) |
| **Band Multiplier** | Multiplier for channel width | 0.1+ (default: 0.5-0.6) |
- **Strengths**:
- Predictive rather than reactive
- Adapts quickly to changing market conditions
- Better at identifying trend reversals early
- **Weaknesses**:
- More computationally intensive
- Requires careful parameter tuning
- Can be sensitive to input data quality
### Entry Strategies
| Strategy | Description | Ideal Market Conditions |
|----------|-------------|-------------------------|
| **Breakout** | Enters when price breaks through channel bands, indicating strong momentum | High volatility, emerging trends |
| **Pullback** | Enters when price retraces to the middle band after testing extremes | Established trends with regular pullbacks |
| **Mean Reversion** | Enters at channel extremes, betting on a return to the mean | Range-bound or oscillating markets |
#### Breakout Strategy (Default)
- **Implementation**: Enters long when price crosses above the upper band, short when price crosses below the lower band
- **Strengths**: Captures strong momentum moves, performs well in trending markets
- **Weaknesses**: Can lead to late entries, higher risk of false breakouts
- **Optimization Tips**:
- Increase channel multiplier for fewer but more reliable signals
- Combine with volume confirmation for better accuracy
#### Pullback Strategy
- **Implementation**: Enters long when price pulls back to middle band during uptrend, short during downtrend pullbacks
- **Strengths**: Better entry prices, lower risk, higher probability setups
- **Weaknesses**: Misses some strong moves, requires clear trend identification
- **Optimization Tips**:
- Use with trend filters to confirm overall direction
- Adjust middle band calculation for market volatility
#### Mean Reversion Strategy
- **Implementation**: Enters long at lower band, short at upper band, expecting price to revert to the mean
- **Strengths**: Excellent entry prices, works well in ranging markets
- **Weaknesses**: Dangerous in strong trends, can lead to fighting the trend
- **Optimization Tips**:
- Implement strong trend filters to avoid counter-trend trades
- Use smaller position sizes due to higher risk nature
### Confirmation Indicators
#### Pivot Point SuperTrend
Combines pivot points with ATR-based SuperTrend for trend confirmation:
| Setting | Default Value |
|---------|---------------|
| **Pivot Period** | 25 |
| **ATR Factor** | 2.2 |
| **ATR Period** | 41 |
- **Function**: Identifies significant market turning points and confirms trend direction
- **Implementation**: Requires price to respect the SuperTrend line for trade confirmation
#### Weighted Moving Average (WMA)
Provides additional confirmation layer for entries:
| Setting | Default Value |
|---------|---------------|
| **Period** | 15 |
| **Source** | ohlc4 (average of Open, High, Low, Close) |
- **Function**: Confirms trend direction and filters out low-quality signals
- **Implementation**: Price must be above WMA for longs, below for shorts
### Exit Strategies
#### On-Balance Volume (OBV) Based Exits
Uses volume flow to identify potential reversals:
| Setting | Default Value |
|---------|---------------|
| **Source** | ohlc4 |
| **MA Type** | HMA (Options: SMA, EMA, WMA, RMA, VWMA, HMA) |
| **Period** | 22 |
- **Function**: Identifies divergences between price and volume to exit before reversals
- **Implementation**: Exits when OBV crosses its moving average in the opposite direction
- **Customizable MA Type**: Different MA types provide varying sensitivity to OBV changes:
- **SMA**: Traditional simple average, equal weight to all periods
- **EMA**: More weight to recent data, responds faster to price changes
- **WMA**: Weighted by recency, smoother than EMA
- **RMA**: Similar to EMA but smoother, reduces noise
- **VWMA**: Factors in volume, helpful for OBV confirmation
- **HMA**: Reduces lag while maintaining smoothness (default)
#### ADX Exit Confirmation
Uses Average Directional Index to confirm trend exhaustion:
| Setting | Default Value |
|---------|---------------|
| **ADX Threshold** | 35 |
| **ADX Smoothing** | 60 |
| **DI Length** | 60 |
- **Function**: Confirms trend weakness before exiting positions
- **Implementation**: Requires ADX to drop below threshold or DI lines to cross
## Filter System
### RSI Filter
- **Function**: Controls entries based on momentum conditions
- **Parameters**:
- Period: 15 (default)
- Overbought level: 71
- Oversold level: 23
- Multi-timeframe support: Current, MTF1 (15min), or MTF2 (4h)
- Customizable price source (open, high, low, close, hl2, hlc3, ohlc4)
- **Implementation**: Blocks long entries when RSI > overbought, short entries when RSI < oversold
### Volatility Filter
- **Function**: Prevents trading during excessive market volatility
- **Parameters**:
- Measure: ATR (Average True Range)
- Period: Customizable (default varies by timeframe)
- Threshold: Adjustable multiplier
- Multi-timeframe support
- Customizable price source
- **Implementation**: Blocks trades when current volatility exceeds threshold × average volatility
### Volume Filter
- **Function**: Ensures adequate market liquidity for trades
- **Parameters**:
- Threshold: 0.4× average (default)
- Measurement period: 5 (default)
- Moving average type: Customizable (HMA default)
- Multi-timeframe support
- Customizable price source
- **Implementation**: Requires current volume to exceed threshold × average volume
### Bollinger Bands Filter
- **Function**: Controls entries based on price relative to statistical boundaries
- **Parameters**:
- Period: Customizable
- Standard deviation multiplier: Adjustable
- Moving average type: Customizable
- Multi-timeframe support
- Customizable price source
- **Implementation**: Can require price to be within bands or breaking out of bands depending on strategy
### KEMAD Filter (Kalman EMA Distance)
- **Function**: Advanced trend confirmation using Kalman filter algorithm
- **Parameters**:
- Process Noise: 0.35 (controls smoothness)
- Measurement Noise: 24 (controls reactivity)
- Filter Order: 6 (higher = more smoothing)
- ATR Length: 8 (for bandwidth calculation)
- Upper Multiplier: 2.0 (for long signals)
- Lower Multiplier: 2.7 (for short signals)
- Multi-timeframe support
- Customizable visual indicators
- **Implementation**: Generates signals based on price position relative to Kalman-filtered EMA bands
## Risk Management System
### Position Sizing
Automatically calculates position size based on account equity and risk parameters:
| Setting | Default Value |
|---------|---------------|
| **Risk % of Equity** | 50% |
- **Implementation**:
- Position size = (Account equity × Risk %) ÷ (Entry price × Stop loss distance)
- Adjusts automatically based on volatility and stop placement
- **Best Practices**:
- Start with lower risk percentages (1-2%) until strategy is proven
- Consider reducing risk during high volatility periods
### Stop-Loss Methods
Multiple stop-loss calculation methods with separate configurations for long and short positions:
| Method | Description | Configuration |
|--------|-------------|---------------|
| **ATR-Based** | Dynamic stops based on volatility | ATR Period: 14, Multiplier: 2.0 |
| **Percentage** | Fixed percentage from entry | Long: 1.5%, Short: 1.5% |
| **PIP-Based** | Fixed currency unit distance | 10.0 pips |
- **Implementation Notes**:
- ATR-based stops adapt to changing market volatility
- Percentage stops maintain consistent risk exposure
- PIP-based stops provide precise control in stable markets
### Trailing Stops
Locks in profits by adjusting stop-loss levels as price moves favorably:
| Setting | Default Value |
|---------|---------------|
| **Stop-Loss %** | 1.5% |
| **Activation Threshold** | 2.1% |
| **Trailing Distance** | 1.4% |
- **Implementation**:
- Initial stop remains fixed until profit reaches activation threshold
- Once activated, stop follows price at specified distance
- Locks in profit while allowing room for normal price fluctuations
### Risk-Reward Parameters
Defines the relationship between risk and potential reward:
| Setting | Default Value |
|---------|---------------|
| **Risk-Reward Ratio** | 1.4 |
| **Take Profit %** | 2.4% |
| **Stop-Loss %** | 1.5% |
- **Implementation**:
- Take profit distance = Stop loss distance × Risk-reward ratio
- Higher ratios require fewer winning trades for profitability
- Lower ratios increase win rate but reduce average profit
### Filter Combinations
The strategy allows for simultaneous application of multiple filters:
- **Recommended Combinations**:
- Trending markets: RSI + KEMAD filters
- Ranging markets: Bollinger Bands + Volatility filters
- All markets: Volume filter as minimum requirement
- **Performance Impact**:
- Each additional filter reduces the number of trades
- Quality of remaining trades typically improves
- Optimal combination depends on market conditions and timeframe
### Multi-Timeframe Filter Applications
| Filter Type | Current Timeframe | MTF1 (15min) | MTF2 (4h) |
|-------------|-------------------|-------------|------------|
| RSI | Quick entries/exits | Intraday trend | Overall trend |
| Volume | Immediate liquidity | Sustained support | Market participation |
| Volatility | Entry timing | Short-term risk | Regime changes |
| KEMAD | Precise signals | Trend confirmation | Major reversals |
## Visual Indicators and Chart Analysis
The bot provides comprehensive visual feedback on the chart:
- **Channel Bands**: Keltner or MLMA bands showing potential support/resistance
- **Pivot SuperTrend**: Colored line showing trend direction and potential reversal points
- **Entry/Exit Markers**: Annotations showing actual trade entries and exits
- **Risk/Reward Zones**: Visual representation of stop-loss and take-profit levels
These visual elements allow for:
- Real-time strategy assessment
- Post-trade analysis and optimization
- Educational understanding of the strategy logic
## Implementation Guide
### TradingView Setup
1. Load the script in TradingView Pine Editor
2. Apply to your preferred chart and timeframe
3. Adjust parameters based on your trading preferences
4. Enable alerts for webhook integration
### Webhook Integration
1. Configure webhook URL in TradingView alerts
2. Set up receiving endpoint on your trading platform
3. Define message format matching the bot's output
4. Test with small position sizes before full deployment
### Optimization Process
1. Backtest across different market conditions
2. Identify parameter sensitivity through multiple tests
3. Focus on risk management parameters first
4. Fine-tune entry/exit conditions based on performance metrics
5. Validate with out-of-sample testing
## Performance Considerations
### Strengths
- Adaptability to different market conditions through dual channels
- Multiple layers of confirmation reducing false signals
- Comprehensive risk management protecting capital
- Machine learning integration for predictive edge
### Limitations
- Complex parameter set requiring careful optimization
- Potential over-optimization risk with so many variables
- Computational intensity of MLMA calculations
- Dependency on proper webhook configuration for execution
### Best Practices
- Start with conservative risk settings (1-2% of equity)
- Test thoroughly in demo environment before live trading
- Monitor performance regularly and adjust parameters
- Consider market regime changes when evaluating results
## Conclusion
The ₿ober XM v2.0 represents a significant evolution in trading strategy design, combining traditional technical analysis with machine learning elements and multi-timeframe analysis. The core strength of this system lies in its adaptability and recognition of market asymmetry.
### Market Asymmetry and Adaptive Approach
The strategy acknowledges a fundamental truth about markets: bullish and bearish phases behave differently and should be treated as distinct environments. The dual-channel system with separate parameters for long and short positions directly addresses this asymmetry, allowing for optimized performance regardless of market direction.
### Targeted Backtesting Philosophy
It's counterproductive to run backtests over excessively long periods. Markets evolve continuously, and strategies that worked in previous market regimes may be ineffective in current conditions. Instead:
- Test specific market phases separately (bull markets, bear markets, range-bound periods)
- Regularly re-optimize parameters as market conditions change
- Focus on recent performance with higher weight than historical results
- Test across multiple timeframes to ensure robustness
### Multi-Timeframe Analysis as a Game-Changer
The integration of multi-timeframe analysis fundamentally transforms the strategy's effectiveness:
- **Increased Safety**: Higher timeframe confirmations reduce false signals and improve trade quality
- **Context Awareness**: Decisions made with awareness of larger trends reduce adverse entries
- **Adaptable Precision**: Apply strict filters on lower timeframes while maintaining awareness of broader conditions
- **Reduced Noise**: Higher timeframe data naturally filters market noise that can trigger poor entries
The ₿ober XM v2.0 provides traders with a framework that acknowledges market complexity while offering practical tools to navigate it. With proper setup, realistic expectations, and attention to changing market conditions, it delivers a sophisticated approach to systematic trading that can be continuously refined and optimized.
SMPivot Gaussian Trend Strategy [Js.K]This open-source strategy combines a Gaussian-weighted moving average with “Smart Money” swing-pivot breaks (BoS = Break-of-Structure) to capture trend continuations and early reversals. It is intended for educational and research purposes only and must not be interpreted as financial advice.
How the logic works
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1. Gaussian Moving Average (GMA)
• A custom Gaussian kernel (length = 30 by default) smooths price while preserving turning points.
• A second pass (“Smoothed GMA”) further filters noise; only its direction is used for bias.
2. Swing-Pivot detection
• High/Low pivots are found with a symmetric look-back/forward window (Pivot Length = 20).
• The most recent confirmed pivot creates a dynamic structure level (UpdatedHigh / UpdatedLow).
3. Entry rules
Long
• Price closes above the most recent pivot high **and** above Smoothed GMA.
Short
• Price closes below the most recent pivot low **and** below Smoothed GMA.
4. Exit rules
• Fixed stop-loss and take-profit in percent of current price (user-defined).
• Separate parameters and on/off switches for longs and shorts.
5. Visuals
• GMA (dots) and Smoothed GMA (line).
• Structure break lines plus “BoS PH/PL” labels at the midpoint between pivot and break.
Inputs
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Gaussian
• Gaussian Length (default 30) – smoothing window.
• Gaussian Scatterplot – toggle GMA dots.
Smart-Money Pivot
• Pivot Length (default 20).
• Bull / Bear colors.
Risk settings
• Long / Short enable.
• Individual SL % and TP % (default 1 % SL, 30 % TP).
• Strategy uses percent-of-equity sizing; initial capital defaults to 10 000 USD.
Adjust these to reflect your own account size, realistic commission and slippage.
Best practice & compliance notes
--------------------------------
• Test on a data sample that yields ≥ 100 trades to obtain statistically relevant results.
• Keep risk per trade below 5–10 % of equity; the default values comply with this guideline.
• Explain any custom settings you publish that differ from the defaults.
• Do **not** remove the code header or licence notice (MPL-2.0).
• Include realistic commission and slippage in your back-test before publishing.
• The script does **not** repaint; orders are processed on bar close.
Usage
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1. Add the script to any symbol / timeframe; intraday and swing timeframes both work—adjust lengths accordingly.
2. Configure SL/TP and position size to match your personal risk management.
3. Run “List of trades” and the performance summary to evaluate expectancy; forward-test before live use.
Disclaimer
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Trading involves substantial risk. Past performance based on back-testing is not necessarily indicative of future results. The author is **not** responsible for any financial losses arising from the use of this script.
Smart Money Pivot Strategy [Jason Kasei]This strategy is designed to identify key pivot points (Pivot High and Pivot Low) in the market and leverage the "Smart Money" concept to capture price breakout opportunities. It supports both long and short trades, offering customizable stop-loss (SL) and take-profit (TP) settings, while visually plotting pivot points and breakout signals on the chart.
Core Features
Pivot Point Detection:
Utilizes ta.pivothigh and ta.pivotlow functions to detect the highest (Pivot High) and lowest (Pivot Low) points within a specified period (default: 20 bars).
Trading Signals:
Long Signal: Triggered when the price breaks above a previous Pivot High, indicating a potential uptrend.
Short Signal: Triggered when the price breaks below a previous Pivot Low, indicating a potential downtrend.
How It Works
Detects Pivot High (PH) and Pivot Low (PL) over the specified period and records their price and time.
Triggers a long entry when the price breaks above a Pivot High and a short entry when it falls below a Pivot Low.
Sets exit conditions automatically based on predefined SL and TP percentages after entry.
Plots breakout points and levels on the chart for analysis.
Considerations
The strategy relies on accurate pivot point detection; adjust the period parameter based on market volatility.
In highly volatile markets, consider widening the stop loss to avoid frequent triggering.
Combine with other indicators or analysis methods to validate signals and avoid blind trading.
PVSRA v5Overview of the PVSRA Strategy
This strategy is designed to detect and capitalize on volume-driven threshold breaches in price candles. It operates on the premise that when a high-volume candle breaks a critical price threshold, not all orders are filled within that candle’s range. This creates an imbalance—similar to a physical system being perturbed—causing the price to revert toward the level where the breach occurred to “absorb” the residual orders.
Key Features and Their Theoretical Underpinnings
Dynamic Volume Analysis and Threshold Detection
Volume Surges as Market Perturbations:
The script computes a moving average of volume over a short window and flags moments when the current volume significantly exceeds this average. These surges act as a perturbation—injecting “energy” into the market.
Adaptive Abnormal Volume Threshold:
By calculating a dynamic abnormal threshold using a daily volume average (via an 89-period VWMA) and standard deviation, the strategy identifies when the current volume is abnormally high. This mechanism mirrors the idea that when a system is disturbed (here, by a volume surge), it naturally seeks to return to equilibrium.
Candle Coloring and Visual Signal Identification
Differentiation of Candle Types:
The script distinguishes between bullish (green) and bearish (red) candles. It applies different colors based on the strength of the volume signal, providing a clear, visual representation of whether a candle is likely to trigger a price reversion.
Implication of Unfilled Orders:
A red (bearish) candle with high volume implies that sell pressure has pushed the price past a critical threshold—yet not all buy orders have been fulfilled. Conversely, a green (bullish) candle indicates that aggressive buying has left pending sell orders. In both cases, the market is expected to reverse toward the breach point to restore balance.
Trade Execution Logic: Normal and Reversal Trades
Normal Trades:
When a high-volume candle breaches a threshold and meets the directional conditions (e.g., a red candle paired with price above a daily upper band), the strategy enters a trade anticipating a reversion. The underlying idea is that the market will move back to the level where the threshold was crossed—clearing the residual orders in a manner analogous to a system following the path of least resistance.
Reversal Trades:
The strategy also monitors for clusters of consecutive signals within a short lookback period. When multiple signals accumulate, it interprets this as the market having overextended and, in a corrective move, reverses the typical trade direction. This inversion captures the market’s natural tendency to “correct” itself by moving in discrete, quantized steps—each step representing the absorption of a minimum quantum of order imbalance.
Risk and Trade Management
Stop Loss and Take Profit Buffers:
Both normal and reversal trades include predetermined buffers for stop loss and take profit levels. This systematic risk management approach is designed to capture the anticipated reversion while minimizing potential losses, aligning with the idea that market corrections follow the most energy-efficient path back to equilibrium.
Symbol Flexibility:
An option to override the chart’s symbol allows the strategy to be applied consistently across different markets, ensuring that the volume and price dynamics are analyzed uniformly.
Conceptual Bridge: From Market Dynamics to Trade Execution
At its core, the strategy treats market price movements much like a physical system that seeks to minimize “transactional energy” or inefficiency. When a price candle breaches a key threshold on high volume, it mimics an injection of energy into the system. The subsequent price reversion is the market’s natural response—moving in the most efficient path back to balance. This perspective is akin to the principle of least action, where the system evolves along the trajectory that minimizes cumulative imbalance, and it acknowledges that these corrections occur in discrete steps reflective of quantized order execution.
This unified framework allows the PVSRA strategy to not only identify when significant volume-based threshold breaches occur but also to systematically execute trades that benefit from the expected corrective moves.
Rally Base Drop SND Pivots Strategy [LuxAlgo X PineIndicators]This strategy is based on the Rally Base Drop (RBD) SND Pivots indicator developed by LuxAlgo. Full credit for the concept and original indicator goes to LuxAlgo.
The Rally Base Drop SND Pivots Strategy is a non-repainting supply and demand trading system that detects pivot points based on Rally, Base, and Drop (RBD) candles. This strategy automatically identifies key market structure levels, allowing traders to:
Identify pivot-based supply and demand (SND) zones.
Use fixed criteria for trend continuation or reversals.
Filter out market noise by requiring structured price formations.
Enter trades based on breakouts of key SND pivot levels.
How the Rally Base Drop SND Pivots Strategy Works
1. Pivot Point Detection Using RBD Candles
The strategy follows a rigid market structure methodology, where pivots are detected only when:
A Rally (R) consists of multiple consecutive bullish candles.
A Drop (D) consists of multiple consecutive bearish candles.
A Base (B) is identified as a transition between Rallies and Drops, acting as a pivot point.
The pivot level is confirmed when the formation is complete.
Unlike traditional fractal-based pivots, RBD Pivots enforce stricter structural rules, ensuring that each pivot:
Has a well-defined bullish or bearish price movement.
Reduces false signals caused by single-bar fluctuations.
Provides clear supply and demand levels based on structured price movements.
These pivot levels are drawn on the chart using color-coded boxes:
Green zones represent bullish pivot levels (Rally Base formations).
Red zones represent bearish pivot levels (Drop Base formations).
Once a pivot is confirmed, the high or low of the base candle is used as the reference level for future trades.
2. Trade Entry Conditions
The strategy allows traders to select from three trading modes:
Long Only – Only takes long trades when bullish pivot breakouts occur.
Short Only – Only takes short trades when bearish pivot breakouts occur.
Long & Short – Trades in both directions based on pivot breakouts.
Trade entry signals are triggered when price breaks through a confirmed pivot level:
Long Entry:
A bullish pivot level is formed.
Price breaks above the bullish pivot level.
The strategy enters a long position.
Short Entry:
A bearish pivot level is formed.
Price breaks below the bearish pivot level.
The strategy enters a short position.
The strategy includes an optional mode to reverse long and short conditions, allowing traders to experiment with contrarian entries.
3. Exit Conditions Using ATR-Based Risk Management
This strategy uses the Average True Range (ATR) to calculate dynamic stop-loss and take-profit levels:
Stop-Loss (SL): Placed 1 ATR below entry for long trades and 1 ATR above entry for short trades.
Take-Profit (TP): Set using a Risk-Reward Ratio (RR) multiplier (default = 6x ATR).
When a trade is opened:
The entry price is recorded.
ATR is calculated at the time of entry to determine stop-loss and take-profit levels.
Trades exit automatically when either SL or TP is reached.
If reverse conditions mode is enabled, stop-loss and take-profit placements are flipped.
Visualization & Dynamic Support/Resistance Levels
1. Pivot Boxes for Market Structure
Each pivot is marked with a colored box:
Green boxes indicate bullish demand zones.
Red boxes indicate bearish supply zones.
These boxes remain on the chart to act as dynamic support and resistance levels, helping traders identify key price reaction zones.
2. Horizontal Entry, Stop-Loss, and Take-Profit Lines
When a trade is active, the strategy plots:
White line → Entry price.
Red line → Stop-loss level.
Green line → Take-profit level.
Labels display the exact entry, SL, and TP values, updating dynamically as price moves.
Customization Options
This strategy offers multiple adjustable settings to optimize performance for different market conditions:
Trade Mode Selection → Choose between Long Only, Short Only, or Long & Short.
Pivot Length → Defines the number of required Rally & Drop candles for a pivot.
ATR Exit Multiplier → Adjusts stop-loss distance based on ATR.
Risk-Reward Ratio (RR) → Modifies take-profit level relative to risk.
Historical Lookback → Limits how far back pivot zones are displayed.
Color Settings → Customize pivot box colors for bullish and bearish setups.
Considerations & Limitations
Pivot Breakouts Do Not Guarantee Reversals. Some pivot breaks may lead to continuation moves instead of trend reversals.
Not Optimized for Low Volatility Conditions. This strategy works best in trending markets with strong momentum.
ATR-Based Stop-Loss & Take-Profit May Require Optimization. Different assets may require different ATR multipliers and RR settings.
Market Noise May Still Influence Pivots. While this method filters some noise, fake breakouts can still occur.
Conclusion
The Rally Base Drop SND Pivots Strategy is a non-repainting supply and demand system that combines:
Pivot-based market structure analysis (using Rally, Base, and Drop candles).
Breakout-based trade entries at confirmed SND levels.
ATR-based dynamic risk management for stop-loss and take-profit calculation.
This strategy helps traders:
Identify high-probability supply and demand levels.
Trade based on structured market pivots.
Use a systematic approach to price action analysis.
Automatically manage risk with ATR-based exits.
The strict pivot detection rules and built-in breakout validation make this strategy ideal for traders looking to:
Trade based on market structure.
Use defined support & resistance levels.
Reduce noise compared to traditional fractals.
Implement a structured supply & demand trading model.
This strategy is fully customizable, allowing traders to adjust parameters to fit their market and trading style.
Full credit for the original concept and indicator goes to LuxAlgo.
Destroyer LifeDestroyer Life Strategy - High-Frequency Long & Short Trading
Overview:
The Destroyer Life strategy is an advanced cryptocurrency trading algorithm designed for high-frequency execution on the 15-second timeframe. It combines CRT (Candle Range Trend) and Turtle Soup trading logic with multi-timeframe analysis to optimize entries and exits for both long and short trades. This strategy is specifically optimized for high-volatility crypto pairs, such as SOL/USD on MEXC, ensuring precise execution with minimal drawdown.
Key Features:
15-Second Timeframe Execution: Optimized for ultra-short-term trading.
Long & Short Strategy: Simultaneously identifies profitable buy and sell opportunities.
CRT & Turtle Soup Logic: Leverages price action patterns for enhanced trade accuracy.
Higher Timeframe Analysis (HTF): Incorporates liquidity zones, fair value gaps (FVG), and breaker blocks for context-aware trading.
Dynamic Position Sizing: Uses an adjustable leverage multiplier for risk-controlled trade sizing.
Commission Optimization: Ensures profitability even with trading fees.
Strict Risk Management: Implements exit conditions based on liquidity structure and trend reversals.
Strategy Performance (Backtested on SOL/USD - MEXC):
Overall Profitability: ~80% win rate in backtesting.
Net Profit: $3,151.12 (6.30% ROI).
Gross Profit: $3,795.68 (7.59%).
Gross Loss: $644.56 (1.29%).
Long Trades Profit: $1,459.05 (2.92%).
Short Trades Profit: $1,692.07 (3.38%).
Commission Paid: $924.82.
Minimum Trade Holding Period: 1-minute cooldown between trades.
Trading Logic:
Entry Conditions:
Long Trades: Triggered when the price enters a liquidity void and aligns with higher timeframe bullish bias.
Short Trades: Triggered when price approaches a resistance level with bearish higher timeframe confluence.
CRT & Turtle Soup Patterns: Identifies reversals by analyzing breakout and fake-out structures.
Exit Conditions:
Long Positions Close: Upon price exceeding a 3.88% profit threshold or reversing below an HTF structure.
Short Positions Close: Upon reaching a similar 3.88% threshold or showing strong bullish signals.
Dynamic Position Sizing:
Uses a leverage-based calculation that adapts trade size based on volatility.
Liquidity Awareness:
Tracks Mitigation Blocks (MB), Fair Value Gaps (FVG), Buy/Sell-Side Liquidity (BSL/SSL) to determine optimal execution.
Best Use Cases:
Scalpers & High-Frequency Traders: Those looking for rapid trade execution with short holding periods.
Crypto Traders Focused on Low Timeframes: Optimized for 15-second price action.
Traders Utilizing Liquidity Concepts: Built to exploit liquidity traps and inefficiencies.
Risks & Considerations:
High-Frequency Execution Requires Low Latency: Ensure your broker or exchange supports fast order execution.
Backtested Results May Vary: Real-time performance depends on market conditions.
Commission & Fees Impact Profits: Consider exchanges with low fees to maximize strategy efficiency.
Final Thoughts:
The Destroyer Life Strategy is designed for serious traders looking to take advantage of high-volatility markets with a structured, liquidity-based approach. By combining price action, liquidity concepts, and adaptive risk management, it provides a solid framework for executing high-probability trades on crypto markets.
🚀 Ready to take your trading to the next level? Try Destroyer Life today and dominate the markets!
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.
Trend Vanguard StrategyHow to Use:
Trend Vanguard Strategy is a multi-feature Pine Script strategy designed to identify market pivots, draw dynamic support/resistance, and generate trade signals via ZigZag breakouts. Here’s how it works and how to use it:
ZigZag Detection & Pivot Points
The script locates significant swing highs and lows using configurable Depth, Deviation, and Backstep values.
It then connects these pivots with lines (ZigZag) to highlight directional changes and prints labels (“Buy,” “Sell,” etc.) at key turning points.
Support & Resistance Trendlines
Pivot highs and lows are used to draw dashed S/R lines in real-time.
When price crosses these lines, the script triggers a breakout signal (long or short).
EMA Overlays
Up to four EMAs (with customizable lengths and colors) can be overlaid on the chart for added trend confirmation.
Enable/disable each EMA independently via the settings.
Repaint Option
Turning on “Smooth Indicator Lines” (repaint) uses future data to refine past pivots.
This can make historical signals look cleaner but does not reflect true historical conditions.
Turning it off ensures signals remain fixed once they appear.
Strategy Entries & Exits
On each new ZigZag “Buy” or “Sell” signal, the script closes any open position and flips to the opposite side (if desired).
Works with the built-in TradingView Strategy engine for backtesting.
Additional Inputs (Placeholders)
Volume Filter and RSI Filter settings exist but are not fully implemented in the current code. Future versions may incorporate these filters more directly.
How to Use
Add to Chart: Click “Indicators” → “Invite-Only Scripts” (or “My Scripts”) and select “Trend Vanguard Strategy.”
Configure Settings:
Adjust ZigZag Depth, Deviation, and Backstep to fine-tune pivot sensitivity.
Enable or disable each EMA to see how it aligns with market trends.
Toggle “Smooth Indicator Lines” on or off depending on whether you want repainting.
Backtest and Forward Test:
Use TradingView’s “Strategy Tester” tab to review hypothetical performance.
Remember that repainting can alter past signals if enabled.
Monitor Live:
Watch for breakout triangles or ZigZag labels to identify potential reversal or breakout trades in real time.
Disclaimer: This script is purely educational and not financial advice. Always combine it with sound risk management and thorough analysis. Enjoy exploring the script, and feel free to experiment with the different settings to match your trading style!
Bot for Spot Market - Custom GridThis script is designed to create a trading bot for the spot market, specifically for buying and selling bitcoins profitably. Recommended for timeframes above two hours. Here are the main functions and features of the script:
Strategy Setup: The bot is set up with a custom grid strategy, defining parameters like pyramiding (allowed number of simultaneous trades), margin requirements, commission, and initial capital.
Order Requirements: It calculates the order price and amount based on the minimum requirements set by the exchange and rounds them appropriately.
Entry Conditions: The bot makes new entries if the closing price falls a certain percentage below the last entry price. It continues to make entries until the closing price rises a certain percentage above the average entry price.
Targets and Plots:
It calculates and plots the target profit level.
It plots the average entry price and the last entry price.
It plots the next entry price based on the defined conditions.
It plots the maximum number of orders allowed based on equity and the number of open orders.
Timerange: The bot can start trading from a specific date and time defined by the user.
Entries: It places orders if the timerange conditions are met. It also places new orders if the closing price is below the last entry price by a defined percentage.
Profit Calculation: The script calculates open profit or loss for the open positions.
Exit Conditions: It closes all positions if the open profit is positive and the closing price is above the target profit level.
Performance Table: The bot maintains and displays statistics like the number of open and closed trades, net profit, and equity in a table format.
The script is customizable, allowing users to adjust parameters like initial capital, commission, order values, and profit targets to fit their specific trading needs and exchange requirements.
