Price Flip StrategyPrice Flip Strategy with User-Defined Ticker Max/Max
This strategy leverages an inverted price calculation based on user-defined maximum and minimum price levels over customizable lookback periods. It generates buy and sell signals by comparing the previous bar's original price to the inverted price, within a specified date range. The script plots key metrics, including ticker max/min, original and inverted prices, moving averages, and HLCC4 averages, with customizable visibility toggles and labels for easy analysis.
Key Features:
Customizable Inputs: Set lookback periods for ticker max/min, moving average length, and date range for signal generation.
Inverted Price Logic: Calculates an inverted price using ticker max/min to identify trading opportunities.
Flexible Visualization: Toggle visibility for plots (e.g., ticker max/min, prices, moving averages, HLCC4 averages) and last-bar labels with user-defined colors and sizes.
Trading Signals: Generates buy signals when the previous original price exceeds the inverted price, and sell signals when it falls below, with alerts for real-time notifications.
Labeling: Displays values on the last bar for all plotted metrics, aiding in quick reference.
How to Use:
Add to Chart: Apply the script to a TradingView chart via the Pine Editor.
Configure Settings:
Date Range: Set the start and end dates to define the active trading period.
Ticker Levels: Adjust the lookback periods for calculating ticker max and min (e.g., 100 bars for max, 100 for min).
Moving Averages: Set the length for exponential moving averages (default: 20 bars).
Plots and Labels: Enable/disable specific plots (e.g., Inverted Price, Original HLCC4) and customize label colors/sizes for clarity.
Interpret Signals:
Buy Signal: Triggered when the previous close price is above the inverted price; marked with an upward label.
Sell Signal: Triggered when the previous close price is below the inverted price; marked with a downward label.
Set Alerts: Use the built-in alert conditions to receive notifications for buy/sell signals.
Analyze Plots: Review plotted lines (e.g., ticker max/min, HLCC4 averages) and last-bar labels to assess price behavior.
Tips:
Use in trending markets by enabling ticker max for uptrends or ticker min for downtrends, as indicated in tooltips.
Adjust the label offset to prevent overlapping text on the last bar.
Test the strategy on a demo account to optimize lookback periods and moving average settings for your asset.
Disclaimer: This script is for educational purposes and should be tested thoroughly before use in live trading. Past performance is not indicative of future results.
Candlestick analysis
RSI Divergence Strategy - AliferCryptoStrategy Overview
The RSI Divergence Strategy is designed to identify potential reversals by detecting regular bullish and bearish divergences between price action and the Relative Strength Index (RSI). It automatically enters positions when a divergence is confirmed and manages risk with configurable stop-loss and take-profit levels.
Key Features
Automatic Divergence Detection: Scans for RSI pivot lows/highs vs. price pivots using user-defined lookback windows and bar ranges.
Dual SL/TP Methods:
- Swing-based: Stops placed a configurable percentage beyond the most recent swing high/low.
- ATR-based: Stops placed at a multiple of Average True Range, with a separate risk/reward multiplier.
Long and Short Entries: Buys on bullish divergences; sells short on bearish divergences.
Fully Customizable: Input groups for RSI, divergence, swing, ATR, and general SL/TP settings.
Visual Plotting: Marks divergences on chart and plots stop-loss (red) and take-profit (green) lines for active trades.
Alerts: Built-in alert conditions for both bullish and bearish RSI divergences.
Detailed Logic
RSI Calculation: Computes RSI of chosen source over a specified period.
Pivot Detection:
- Identifies RSI pivot lows/highs by scanning a lookback window to the left and right.
- Uses ta.barssince to ensure pivots are separated by a minimum/maximum number of bars.
Divergence Confirmation:
- Bullish: Price makes a lower low while RSI makes a higher low.
- Bearish: Price makes a higher high while RSI makes a lower high.
Entry:
- Opens a Long position when bullish divergence is true.
- Opens a Short position when bearish divergence is true.
Stop-Loss & Take-Profit:
- Swing Method: Computes the recent swing high/low then adjusts by a percentage margin.
- ATR Method: Uses the current ATR × multiplier applied to the entry price.
- Take-Profit: Calculated as entry price ± (risk × R/R ratio).
Exit Orders: Uses strategy.exit to place bracket orders (stop + limit) for both long and short positions.
Inputs and Configuration
RSI Settings: Length & price source for the RSI.
Divergence Settings: Pivot lookback parameters and valid bar ranges.
SL/TP Settings: Choice between Swing or ATR method.
Swing Settings: Swing lookback length, margin (%), and risk/reward ratio.
ATR Settings: ATR length, stop multiplier, and risk/reward ratio.
Usage Notes
Adjust the Pivot Lookback and Range values to suit the volatility and timeframe of your market.
Use higher ATR multipliers for wider stops in choppy conditions, or tighten swing margins in trending markets.
Backtest different R/R ratios to find the balance between win rate and reward.
Disclaimer
This script is for educational purposes only and does not constitute financial advice. Trading carries significant risk and you may lose more than your initial investment. Always conduct your own research and consider consulting a professional before making any trading decisions.
Supertrend Hombrok BotSupertrend Hombrok Bot – Automated Trading Strategy for Dynamic Market Conditions
This trading strategy script has been developed to operate automatically based on detailed market conditions. It combines the popular Supertrend indicator, RSI (Relative Strength Index), Volume, and ATR (Average True Range) to determine the best entry and exit points while maintaining proper risk management.
Key Features:
Supertrend as the Base: Uses the Supertrend indicator to identify the market's trend direction, generating buy signals when the market is in an uptrend and sell signals when in a downtrend.
RSI Filter: The RSI is used to determine overbought and oversold conditions, helping to avoid entries in extreme market conditions. Entries are avoided when RSI > 70 (overbought) and RSI < 30 (oversold), reducing the risk of false movements.
Volume Filter: The strategy checks if the trading volume is above the average multiplied by a user-defined factor. This ensures that only significant movements, with higher liquidity, are considered.
Candle Body Size: The strategy filters only candles with a body large enough relative to the ATR (Average True Range), ensuring that the price movements on the chart have sufficient strength.
Risk Management: The bot is configured to operate with an adjustable Risk/Reward Ratio (R:R). This means that for each trade, both Take Profit (TP) and Stop Loss (SL) are adjusted based on the market's volatility as measured by the ATR.
Automatic Entries and Exits: The script automatically executes entries based on the specified conditions and exits with predefined Stop Loss and Take Profit levels, ensuring risk is controlled for each trade.
How It Works:
Buy Condition: Triggered when the market is in an uptrend (Supertrend), the volume is above the adjusted average, the candle body is strong enough, and the RSI is below the overbought level.
Sell Condition: Triggered when the market is in a downtrend (Supertrend), the volume is above the adjusted average, the candle body is strong enough, and the RSI is above the oversold level.
Alerts:
Buy and Sell Alerts are configured with detailed information, including Stop Loss and Take Profit values, allowing the user to receive notifications when trading conditions are met.
Capital Management:
The capital per trade can be adjusted based on account size and risk profile.
Important Note:
Always test before trading with real capital: While the strategy has been designed based on solid technical analysis methods, always perform tests in real-time market conditions with demo accounts before applying the bot in live trading.
Disclaimer: This script is a tool to assist in the trading process and does not guarantee profit. Past performance is not indicative of future results, and the trader is always responsible for their investment decisions.
Gabriel's Price Action Strategy🧠 Gabriel's Price Action Strategy — Smart Signal Sequence with Dynamic Risk Control
Created by: OneWallStreetQuant
Strategy Type: Momentum-based Sequence Logic + Smart Volume & RSI Filters
Ideal For: Intraday scalping, swing trading, and momentum trend entries on stocks, forex, crypto, indices.
🚀 Overview
Gabriel's Price Action Strategy is a multi-layered, logic-driven trading system that combines:
✅ Candle Sequence Detection: Detects persistent bullish/bearish momentum using a smart configurable sequence of green/red candles.
✅ Structure Break Filtering: Prevents entries if recent price invalidates the momentum setup (e.g., a red candle breaks a bullish low).
✅ Custom Volume Engine: Integrates a hybrid tick-volume model using Negative/Positive Volume Index (NVI-PVI) to identify smart money flows.
✅ Advanced RSI Logic: Uses Jurik RSX for accurate oversold/overbought filtering.
✅ Optional MTF Trend Filter: Validates trend direction using a slope-based Jurik MA on higher timeframes.
✅ MPT-Based DMI Filter: Adds pyramid entries only during strong trend phases, based on Gain/Pain ratios and Ulcer-index smoothed ADX.
✅ Risk Management: ATR-based SL/TP and fully customizable trailing logic for both profit and stop-loss.
📈 Entry Logic
Trades are triggered only when:
A minimum number of recent candles are bullish/bearish (Min Green/Red Candles)
Structure has not been broken by opposite price action (optional)
Relative volume exceeds average (optional)
RSI is below overbought or above oversold (optional)
MTF slope is aligned with trend direction (optional)
💡 Key Features
Custom Candle Logic: Detects momentum shifts using a tunable lookback window (up to 50 bars).
Smart Volume Filtering: Volume is intelligently estimated using tick-based ranges and NVI-PVI deltas.
Risk Management Built-in: Set your ATR length, SL/TP multipliers, and dynamic trailing offsets with full control.
Scorecard System: A built-in scoring engine evaluates Win Rate, Drawdown, Sharpe Ratio, Recovery Factor, and Profit Factor — visualized on chart as a label.
Backtest-Friendly: Includes date range toggles, bar-magnifier support, and optimized execution on every tick.
📊 Strategy Scorecard (Label)
Automatically calculates:
✅ Total Trades
✅ Win Rate (%)
✅ Net Profit
✅ Profit Factor
✅ Expected Payoff
✅ Max & Avg Drawdown
✅ Recovery Factor
✅ Sharpe Ratio
✅ VaR (95%)
Plus, assigns a normalized score from 0 to 100 for evaluating overall robustness.
⚙️ Customization
Every module — from entry filters to pyramiding and trailing logic — is fully configurable:
Volume Filters ✅
RSI Filters ✅
Structure Break Checks ✅
HTF Jurik MA & Slope Threshold ✅
Multi-Timeframe Mode ✅
Backtest Score Visualization ✅
⚠️ Notes
Enable bar magnifier and calc on every tick for best accuracy.
On early bars, signal logic may delay until enough candles are available.
Best paired with assets showing directional volatility (SPY, BTC, ETH, Gold, etc.).
Ideally paired on trending timeframes such as M1, M5, M15, M30, 1HR, 4 Hourly, Daily, Weekly, Monthly, etc.
Return-to-Trend Wick Scalper — Full Control VersionReturn-to-Trend Wick Scalper — Modular Scalping Strategy for Gold (XAUUSD) & Indices
This is a precision-engineered scalping strategy designed primarily for high-volatility instruments such as Gold (XAUUSD), NASDAQ, and indices.
The system focuses on counter-trend pullbacks within the dominant daily trend, utilizing wick-based liquidity grabs (commonly referred to as “John Wick” candles) to identify high-probability return-to-trend opportunities.
Key Features:
✅ Dynamic Wick Reversal Detection: Detects reversal setups based on wick dominance and body ratio.
✅ Multiple Take Profit Levels: TP1, TP2, TP3 with individual enable/disable toggles and adjustable exit percentages.
✅ Time-Based Stop-Loss: Optional failsafe to close trades after exceeding a defined number of bars.
✅ VWAP Proximity Filter: Ensures entries happen near volume-weighted average price for precision.
✅ Pullback Depth Control: Filter for significant pullbacks using percentage of daily ATR.
✅ Dynamic Support & Resistance Validation: Confirms setups at key reactive levels.
✅ Volatility Filter: Avoids entries in overly volatile or dead market conditions.
✅ Aggressive Entry Mode: Optional early entry at pullback zones for faster fills.
✅ Paper Trading & Backtest Ready: Fully compatible with TradingView’s Paper Trading simulator.
Usage Notes:
Optimized for 5-minute chart entries.
Use in conjunction with Paper Trading for forward testing before live execution.
Can be connected to live brokers via alert webhooks and external bridges like PineConnector.
Instrument Focus:
Gold (XAUUSD) ✅
NASDAQ ✅
Dow Jones (US30) ✅
Other liquid indices ✅
Risk Note:
Always test thoroughly in Paper Trading before going live.
Optimize TP levels and filters according to market volatility conditions.
Designed for traders who want precision entries, flexibility in scaling out positions, and professional-grade risk control.
Trend Strategy + Impulse FilterThis is a Trend Strategy + Impulse Filter designed for trading in a dynamic market using both Simple Moving Average (SMA) and MACD indicators for trend and momentum analysis. The strategy includes risk management features like Stop Loss, Take Profit, and Trailing Stop to secure gains and limit losses. Additionally, it uses a Breakout Filter for confirmation, ensuring trades are taken only when the price breaks out from a specified range.
Key Features:
Trend Filter: Enter long when the price is above the SMA and MACD line crosses above the signal line. Enter short when the price is below the SMA and MACD line crosses below the signal line.
Breakout Filter: Only takes trades if the price breaks the previous high (for long) or low (for short) within a defined lookback period.
Risk Management: Set stop-loss and take-profit levels based on ATR for dynamic risk management.
Trailing Stop: Locks profits as the price moves in favor of the trade.
Position Sizing: Trade size is based on a percentage of the current equity.
Customizable Parameters: All indicators and risk management settings are adjustable to fit individual preferences.
This strategy is suitable for traders looking for a comprehensive approach that combines trend-following, momentum, and breakout filtering with solid risk management.
Ukrainian Description:
Це стратегія Trend + Impulse Filter, розроблена для торгівлі на динамічному ринку, використовуючи індикатори Простого ковзаючого середнього (SMA) та MACD для аналізу тренду та імпульсу. Стратегія включає в себе функції управління ризиками, такі як Stop Loss, Take Profit та Trailing Stop, щоб забезпечити прибутки та обмежити збитки. Крім того, вона використовує Breakout Filter для підтвердження, забезпечуючи виконання угод лише тоді, коли ціна пробиває визначений діапазон.
Основні характеристики:
Фільтр тренду: Вхід у лонг, коли ціна вище SMA, і MACD лінія перетинає сигнальну лінію знизу вгору. Вхід у шорт, коли ціна нижча за SMA, і MACD лінія перетинає сигнальну лінію зверху вниз.
Фільтр пробою: Торгові угоди відкриваються лише в разі пробою попереднього максимуму (для лонга) або мінімуму (для шорта) протягом заданого періоду.
Управління ризиками: Стоп-лосс та тейк-профіт визначаються на основі ATR для динамічного управління ризиками.
Trailing Stop: Фіксує прибутки, коли ціна рухається в бік угоди.
Розмір позиції: Розмір угоди залежить від відсотка від поточного балансу.
Налаштовувані параметри: Усі індикатори та налаштування управління ризиками можна відкоригувати відповідно до індивідуальних уподобань.
Ця стратегія підходить для трейдерів, які шукають комплексний підхід, що поєднує слідкування за трендом, імпульсом та фільтрацією пробоїв із надійним управлінням ризиками.
BTC Trading RobotOverview
This Pine Script strategy is designed for trading Bitcoin (BTC) by placing pending orders (BuyStop and SellStop) based on local price extremes. The script also implements a trailing stop mechanism to protect profits once a position becomes sufficiently profitable.
________________________________________
Inputs and Parameter Setup
1. Trading Profile:
o The strategy is set up specifically for BTC trading.
o The systemType input is set to 1, which means the strategy will calculate trade parameters using the BTC-specific inputs.
2. Common Trading Inputs:
o Risk Parameters: Although RiskPercent is defined, its actual use (e.g., for position sizing) isn’t implemented in this version.
o Trading Hours Filter:
SHInput and EHInput let you restrict trading to a specific hour range. If these are set (non-zero), orders will only be placed during the allowed hours.
3. BTC-Specific Inputs:
o Take Profit (TP) and Stop Loss (SL) Percentages:
TPasPctBTC and SLasPctBTC are used to determine the TP and SL levels as a percentage of the current price.
o Trailing Stop Parameters:
TSLasPctofTPBTC and TSLTgrasPctofTPBTC determine when and by how much a trailing stop is applied, again as percentages of the TP.
4. Other Parameters:
o BarsN is used to define the window (number of bars) over which the local high and low are calculated.
o OrderDistPoints acts as a buffer to prevent the entry orders from being triggered too early.
________________________________________
Trade Parameter Calculation
• Price Reference:
o The strategy uses the current closing price as the reference for calculations.
• Calculation of TP and SL Levels:
o If the systemType is set to BTC (value 1), then:
Take Profit Points (Tppoints) are calculated by multiplying the current price by TPasPctBTC.
Stop Loss Points (Slpoints) are calculated similarly using SLasPctBTC.
A buffer (OrderDistPoints) is set to half of the take profit points.
Trailing Stop Levels:
TslPoints is calculated as a fraction of the TP (using TSLTgrasPctofTPBTC).
TslTriggerPoints is similarly determined, which sets the profit level at which the trailing stop will start to activate.
________________________________________
Time Filtering
• Session Control:
o The current hour is compared against SHInput (start hour) and EHInput (end hour).
o If the current time falls outside the allowed window, the script will not place any new orders.
________________________________________
Entry Orders
• Local Price Extremes:
o The strategy calculates a local high and local low using a window of BarsN * 2 + 1 bars.
• Placing Stop Orders:
o BuyStop Order:
A long entry is triggered if the current price is less than the local high minus the order distance buffer.
The BuyStop order is set to trigger at the level of the local high.
o SellStop Order:
A short entry is triggered if the current price is greater than the local low plus the order distance buffer.
The SellStop order is set to trigger at the level of the local low.
Note: Orders are only placed if there is no current open position and if the session conditions are met.
________________________________________
Trailing Stop Logic
Once a position is open, the strategy monitors profit levels to protect gains:
• For Long Positions:
o The script calculates the profit as the difference between the current price and the average entry price.
o If this profit exceeds the TslTriggerPoints threshold, a trailing stop is applied by placing an exit order.
o The stop price is set at a distance below the current price, while a limit (profit target) is also defined.
• For Short Positions:
o The profit is calculated as the difference between the average entry price and the current price.
o A similar trailing stop exit is applied if the profit exceeds the trigger threshold.
________________________________________
Summary
In essence, this strategy works by:
• Defining entry levels based on recent local highs and lows.
• Placing pending stop orders to enter the market when those levels are breached.
• Filtering orders by time, ensuring trades are only taken during specified hours.
• Implementing a trailing stop mechanism to secure profits once the trade moves favorably.
This approach is designed to automate BTC trading based on price action and dynamic risk management, although further enhancements (like dynamic position sizing based on RiskPercent) could be added for a more complete risk management system.
Adaptive Fibonacci Pullback System -FibonacciFluxAdaptive Fibonacci Pullback System (AFPS) - FibonacciFlux
This work is licensed under a Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0). Original concepts by FibonacciFlux.
Abstract
The Adaptive Fibonacci Pullback System (AFPS) presents a sophisticated, institutional-grade algorithmic strategy engineered for high-probability trend pullback entries. Developed by FibonacciFlux, AFPS uniquely integrates a proprietary Multi-Fibonacci Supertrend engine (0.618, 1.618, 2.618 ratios) for harmonic volatility assessment, an Adaptive Moving Average (AMA) Channel providing dynamic market context, and a synergistic Multi-Timeframe (MTF) filter suite (RSI, MACD, Volume). This strategy transcends simple indicator combinations through its strict, multi-stage confluence validation logic. Historical simulations suggest that specific MTF filter configurations can yield exceptional performance metrics, potentially achieving Profit Factors exceeding 2.6 , indicative of institutional-level potential, while maintaining controlled risk under realistic trading parameters (managed equity risk, commission, slippage).
4 hourly MTF filtering
1. Introduction: Elevating Pullback Trading with Adaptive Confluence
Traditional pullback strategies often struggle with noise, false signals, and adapting to changing market dynamics. AFPS addresses these challenges by introducing a novel framework grounded in Fibonacci principles and adaptive logic. Instead of relying on static levels or single confirmations, AFPS seeks high-probability pullback entries within established trends by validating signals through a rigorous confluence of:
Harmonic Volatility Context: Understanding the trend's stability and potential turning points using the unique Multi-Fibonacci Supertrend.
Adaptive Market Structure: Assessing the prevailing trend regime via the AMA Channel.
Multi-Dimensional Confirmation: Filtering signals with lower-timeframe Momentum (RSI), Trend Alignment (MACD), and Market Conviction (Volume) using the MTF suite.
The objective is to achieve superior signal quality and adaptability, moving beyond conventional pullback methodologies.
2. Core Methodology: Synergistic Integration
AFPS's effectiveness stems from the engineered synergy between its core components:
2.1. Multi-Fibonacci Supertrend Engine: Utilizes specific Fibonacci ratios (0.618, 1.618, 2.618) applied to ATR, creating a multi-layered volatility envelope potentially resonant with market harmonics. The averaged and EMA-smoothed result (`smoothed_supertrend`) provides a robust, dynamic trend baseline and context filter.
// Key Components: Multi-Fibonacci Supertrend & Smoothing
average_supertrend = (supertrend1 + supertrend2 + supertrend3) / 3
smoothed_supertrend = ta.ema(average_supertrend, st_smooth_length)
2.2. Adaptive Moving Average (AMA) Channel: Provides dynamic market context. The `ama_midline` serves as a key filter in the entry logic, confirming the broader trend bias relative to adaptive price action. Extended Fibonacci levels derived from the channel width offer potential dynamic S/R zones.
// Key Component: AMA Midline
ama_midline = (ama_high_band + ama_low_band) / 2
2.3. Multi-Timeframe (MTF) Filter Suite: An optional but powerful validation layer (RSI, MACD, Volume) assessed on a lower timeframe. Acts as a **validation cascade** – signals must pass all enabled filters simultaneously.
2.4. High-Confluence Entry Logic: The core innovation. A pullback entry requires a specific sequence and validation:
Price interaction with `average_supertrend` and recovery above/below `smoothed_supertrend`.
Price confirmation relative to the `ama_midline`.
Simultaneous validation by all enabled MTF filters.
// Simplified Long Entry Logic Example (incorporates key elements)
long_entry_condition = enable_long_positions and
(low < average_supertrend and close > smoothed_supertrend) and // Pullback & Recovery
(close > ama_midline and close > ama_midline) and // AMA Confirmation
(rsi_filter_long_ok and macd_filter_long_ok and volume_filter_ok) // MTF Validation
This strict, multi-stage confluence significantly elevates signal quality compared to simpler pullback approaches.
1hourly filtering
3. Realistic Implementation and Performance Potential
AFPS is designed for practical application, incorporating realistic defaults and highlighting performance potential with crucial context:
3.1. Realistic Default Strategy Settings:
The script includes responsible default parameters:
strategy('Adaptive Fibonacci Pullback System - FibonacciFlux', shorttitle = "AFPS", ...,
initial_capital = 10000, // Accessible capital
default_qty_type = strategy.percent_of_equity, // Equity-based risk
default_qty_value = 4, // Default 4% equity risk per initial trade
commission_type = strategy.commission.percent,
commission_value = 0.03, // Realistic commission
slippage = 2, // Realistic slippage
pyramiding = 2 // Limited pyramiding allowed
)
Note: The default 4% risk (`default_qty_value = 4`) requires careful user assessment and adjustment based on individual risk tolerance.
3.2. Historical Performance Insights & Institutional Potential:
Backtesting provides insights into historical behavior under specific conditions (always specify Asset/Timeframe/Dates when sharing results):
Default Performance Example: With defaults, historical tests might show characteristics like Overall PF ~1.38, Max DD ~1.16%, with potential Long/Short performance variance (e.g., Long PF 1.6+, Short PF < 1).
Optimized MTF Filter Performance: Crucially, historical simulations demonstrate that meticulous configuration of the MTF filters (particularly RSI and potentially others depending on market) can significantly enhance performance. Under specific, optimized MTF filter settings combined with appropriate risk management (e.g., 7.5% risk), historical tests have indicated the potential to achieve **Profit Factors exceeding 2.6**, alongside controlled drawdowns (e.g., ~1.32%). This level of performance, if consistently achievable (which requires ongoing adaptation), aligns with metrics often sought in institutional trading environments.
Disclaimer Reminder: These results are strictly historical simulations. Past performance does not guarantee future results. Achieving high performance requires careful parameter tuning, adaptation to changing markets, and robust risk management.
3.3. Emphasizing Risk Management:
Effective use of AFPS mandates active risk management. Utilize the built-in Stop Loss, Take Profit, and Trailing Stop features. The `pyramiding = 2` setting requires particularly diligent oversight. Do not rely solely on default settings.
4. Conclusion: Advancing Trend Pullback Strategies
The Adaptive Fibonacci Pullback System (AFPS) offers a sophisticated, theoretically grounded, and highly adaptable framework for identifying and executing high-probability trend pullback trades. Its unique blend of Fibonacci resonance, adaptive context, and multi-dimensional MTF filtering represents a significant advancement over conventional methods. While requiring thoughtful implementation and risk management, AFPS provides discerning traders with a powerful tool potentially capable of achieving institutional-level performance characteristics under optimized conditions.
Acknowledgments
Developed by FibonacciFlux. Inspired by principles of Fibonacci analysis, adaptive averaging, and multi-timeframe confirmation techniques explored within the trading community.
Disclaimer
Trading involves substantial risk. AFPS is an analytical tool, not a guarantee of profit. Past performance is not indicative of future results. Market conditions change. Users are solely responsible for their decisions and risk management. Thorough testing is essential. Deploy at your own considered risk.
Smart Money Breakout & Order Block StrategySmart Money Breakout & Order Block Strategy
Created by Shubham
This strategy was developed by Shubham, designed to provide traders with a structured approach to smart money trading by combining breakout entries and order block reversals. It focuses on liquidity zones, volatility filters, and ATR-based stop management to adapt to different market conditions.
🔹 Strategy Overview
The Smart Money Breakout & Order Block Strategy is built for traders who want to identify institutional moves while avoiding false breakouts. This non-repainting strategy helps traders detect:
✅ Momentum Breakouts – Price breaking key support & resistance levels.
✅ Order Block Reversals – Institutional buying & selling zones.
✅ Dynamic Stop Management – No fixed SL/TP; uses ATR-based trailing stops.
✅ Volatility Filtering – Avoids choppy market conditions.
🔹 Trading Logic
1️⃣ Breakout Trading (Momentum Entries)
Long Entry: When price breaks above resistance with high volatility.
Short Entry: When price breaks below support with high volatility.
2️⃣ Order Block Reversals (Liquidity Entries)
Bullish Order Block: A strong price rejection after consecutive bearish candles signals smart money accumulation, triggering a long trade.
Bearish Order Block: A strong price rejection after consecutive bullish candles signals smart money distribution, triggering a short trade.
3️⃣ Volatility Filter (False Signal Prevention)
Uses normalized volatility to ensure breakouts are backed by strong momentum.
Helps filter out low-volume, choppy market conditions.
4️⃣ ATR-Based Position Management (Dynamic Stops & Trailing Stop)
No fixed SL/TP → Uses ATR-based stop-loss to adapt to market volatility.
Implements a trailing stop for maximizing potential profits in trending markets.
🔹 Key Features
✔️ Developed by Shubham – Designed for precision trading with institutional techniques.
✔️ Smart Money Concept – Identifies liquidity zones, breakouts, and order blocks.
✔️ Volatility Filter – Prevents false breakouts by analyzing market momentum.
✔️ ATR-Based Dynamic Stops – No fixed SL/TP, making it more adaptive.
✔️ Trailing Stop Functionality – Allows profits to run while reducing risk.
✔️ Fully Automated Execution – Uses TradingView’s strategy functions for automatic trade placement and exits.
✔️ Commission-Adjusted Backtesting – Includes realistic commission settings to ensure accurate results.
📊 Backtesting & Realistic Expectations
✅ Best for Higher Timeframes (1H, 4H, Daily) – Avoids market noise.
✅ Most Effective in Trending & Volatile Markets – Crypto, forex, indices, and commodities.
✅ Performance Varies with Market Conditions – Works best in strong trends.
✅ No Unrealistic Promises – Strategy performance is dependent on market behavior and risk management.
📌 IMPORTANT DISCLAIMER:
This strategy is provided for educational purposes only and should not be considered financial advice. Past performance in backtesting does not guarantee future results. Users should conduct their own research before applying this strategy in live markets.
🚀 Developed by Shubham – Test it yourself and see how it performs! 🚀
TrendSync Pro (SMC)📊 TrendSync Pro (SMC) – Advanced Trend-Following Strategy with HTF Alignment
Created by Shubham Singh
🔍 Strategy Overview
TrendSync Pro (SMC) is a precision-based smart trend-following strategy inspired by Smart Money Concepts (SMC). It combines: Real-time pivot-based trendline detection
Higher Time Frame (HTF) filtering to align trades with dominant trend
Risk management via adjustable Stop Loss (SL) and Take Profit (TP)
Directional control — trade only bullish, bearish, or both setups
Realistic backtesting using commissions and slippage
Pre-optimized profiles for scalpers, intraday, swing, and long-term traders
🧠 How It Works:
🔧 Strategy Settings Image:
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The strategy dynamically identifies trend direction by using swing high/low pivots. When a new pivot forms: It draws a trendline from the last significant pivot
Detects whether the trend is up (based on pivot lows) or down (based on pivot highs)
Waits for price to break above/below the trendline
Confirms with HTF price direction (HTF close > previous HTF close = bullish)
Only then it triggers a long or short trade
It exits either at TP, SL, or a manual trendline break
🛠️ Adjustable Parameters:
Trend Period: Length for pivot detection (affects sensitivity of trendlines)
HTF Timeframe: Aligns lower timeframe entries with higher timeframe direction
SL% and TP%: Customize your risk-reward profile
Commission & Slippage: Make backtests more realistic
Trade Direction: Choose to trade: Long only, Short only, or Both
🎛️ Trade Direction Control:
In settings, you can choose: Bullish Only: Executes only long entries
Bearish Only: Executes only short entries
Both: Executes both long and short entries when conditions are met
This allows you to align trades with your own market bias or external analysis.
📈 Entry Logic: Long Entry:
• Price crosses above trendline
• HTF is bullish (HTF close > previous close)
• Latest pivot is a low (trend is considered up)
Short Entry:
• Price crosses below trendline
• HTF is bearish (HTF close < previous close)
• Latest pivot is a high (trend is considered down)
📉 Exit Logic: Hit Take Profit or Stop Loss
Manual trendline invalidation: If price crosses opposite of the trend direction
⏰ Best Timeframes & Recommended Settings:
Scalping (1m to 5m):
HTF = 15m | Trend Period = 7
SL = 0.5% | TP = 1% to 2%
Intraday (15m to 30m):
HTF = 1H | Trend Period = 10–14
SL = 0.75% | TP = 2% to 3%
6 Hour Trading (30m to 1H):
HTF = 4H | Trend Period = 20
SL = 1% | TP = 4% to 6%
Swing Trading (4H to 1D):
HTF = 1D | Trend Period = 35
SL = 2% | TP = 8% to 12%
Long-Term Investing (1D+):
HTF = 1W | Trend Period = 50
SL = 3% | TP = 15%+
Note: These are recommended base settings. Adjust based on volatility, asset class, or personal trading style.
📸 Testing Note:
beeimg.com
TradingView limits test length to 20k bars (~40 trades on smaller timeframes). To show long-term results: Test on higher timeframes (e.g., 1H, 4H, 1D)
Share images of backtest result in description
Host longer test result screenshots on Imgur or any public drive
📍 Asset Behavior Insight:
This strategy works on multiple assets, including BTC, ETH, etc.
Performance varies by trend strength:
Sometimes BTC performs better than ETH
Other times ETH gives better results
That’s normal as both assets follow different volatility and trend behavior
It’s a trend-following setup. Longer and clearer the trend → better the results.
✅ Best Practices: Avoid ranging markets
Use proper SL/TP for each timeframe
Use directional filter if you already have a directional bias
Always forward test before going live
⚠️ Trading Disclaimer:
This script is for educational and backtesting purposes only. Trading involves risk. Always use risk management and never invest more than you can afford to lose.
Enhanced Range Filter Strategy with ATR TP/SLBuilt by Omotola
## **Enhanced Range Filter Strategy: A Comprehensive Overview**
### **1. Introduction**
The **Enhanced Range Filter Strategy** is a powerful technical trading system designed to identify high-probability trading opportunities while filtering out market noise. It utilizes **range-based trend filtering**, **momentum confirmation**, and **volatility-based risk management** to generate precise entry and exit signals. This strategy is particularly useful for traders who aim to capitalize on trend-following setups while avoiding choppy, ranging market conditions.
---
### **2. Key Components of the Strategy**
#### **A. Range Filter (Trend Determination)**
- The **Range Filter** smooths price fluctuations and helps identify clear trends.
- It calculates an **adjusted price range** based on a **sampling period** and a **multiplier**, ensuring a dynamic trend-following approach.
- **Uptrends:** When the current price is above the range filter and the trend is strengthening.
- **Downtrends:** When the price falls below the range filter and momentum confirms the move.
#### **B. RSI (Relative Strength Index) as Momentum Confirmation**
- RSI is used to **filter out weak trades** and prevent entries during overbought/oversold conditions.
- **Buy Signals:** RSI is above a certain threshold (e.g., 50) in an uptrend.
- **Sell Signals:** RSI is below a certain threshold (e.g., 50) in a downtrend.
#### **C. ADX (Average Directional Index) for Trend Strength Confirmation**
- ADX ensures that trades are only taken when the trend has **sufficient strength**.
- Avoids trading in low-volatility, ranging markets.
- **Threshold (e.g., 25):** Only trade when ADX is above this value, indicating a strong trend.
#### **D. ATR (Average True Range) for Risk Management**
- **Stop Loss (SL):** Placed **one ATR below** (for long trades) or **one ATR above** (for short trades).
- **Take Profit (TP):** Set at a **3:1 reward-to-risk ratio**, using ATR to determine realistic price targets.
- Ensures volatility-adjusted risk management.
---
### **3. Entry and Exit Conditions**
#### **📈 Buy (Long) Entry Conditions:**
1. **Price is above the Range Filter** → Indicates an uptrend.
2. **Upward trend strength is positive** (confirmed via trend counter).
3. **RSI is above the buy threshold** (e.g., 50, to confirm momentum).
4. **ADX confirms trend strength** (e.g., above 25).
5. **Volatility is supportive** (using ATR analysis).
#### **📉 Sell (Short) Entry Conditions:**
1. **Price is below the Range Filter** → Indicates a downtrend.
2. **Downward trend strength is positive** (confirmed via trend counter).
3. **RSI is below the sell threshold** (e.g., 50, to confirm momentum).
4. **ADX confirms trend strength** (e.g., above 25).
5. **Volatility is supportive** (using ATR analysis).
#### **🚪 Exit Conditions:**
- **Stop Loss (SL):**
- **Long Trades:** 1 ATR below entry price.
- **Short Trades:** 1 ATR above entry price.
- **Take Profit (TP):**
- Set at **3x the risk distance** to achieve a favorable risk-reward ratio.
- **Ranging Market Exit:**
- If ADX falls below the threshold, indicating a weakening trend.
---
### **4. Visualization & Alerts**
- **Colored range filter line** changes based on trend direction.
- **Buy and Sell signals** appear as labels on the chart.
- **Stop Loss and Take Profit levels** are plotted as dashed lines.
- **Gray background highlights ranging markets** where trading is avoided.
- **Alerts trigger on Buy, Sell, and Ranging Market conditions** for automation.
---
### **5. Advantages of the Enhanced Range Filter Strategy**
✅ **Trend-Following with Noise Reduction** → Helps avoid false signals by filtering out weak trends.
✅ **Momentum Confirmation with RSI & ADX** → Ensures that only strong, valid trades are executed.
✅ **Volatility-Based Risk Management** → ATR ensures adaptive stop loss and take profit placements.
✅ **Works on Multiple Timeframes** → Effective for day trading, swing trading, and scalping.
✅ **Visually Intuitive** → Clearly displays trade signals, SL/TP levels, and trend conditions.
---
### **6. Who Should Use This Strategy?**
✔ **Trend Traders** who want to enter trades with momentum confirmation.
✔ **Swing Traders** looking for medium-term opportunities with a solid risk-reward ratio.
✔ **Scalpers** who need precise entries and exits to minimize false signals.
✔ **Algorithmic Traders** using alerts for automated execution.
---
### **7. Conclusion**
The **Enhanced Range Filter Strategy** is a powerful trading tool that combines **trend-following techniques, momentum indicators, and risk management** into a structured, rule-based system. By leveraging **Range Filters, RSI, ADX, and ATR**, traders can improve trade accuracy, manage risk effectively, and filter out unfavorable market conditions.
This strategy is **ideal for traders looking for a systematic, disciplined approach** to capturing trends while **avoiding market noise and false breakouts**. 🚀
GQT GPT - Volume-based Support & Resistance Zones V2搞钱兔，搞钱是为了更好的生活。
Title: GQT GPT - Volume-based Support & Resistance Zones V2
Overview:
This strategy is implemented in PineScript v5 and is designed to identify key support and resistance zones based on volume-driven fractal analysis on a 1-hour timeframe. It computes fractal high points (for resistance) and fractal low points (for support) using volume moving averages and specific price action criteria. These zones are visually represented on the chart with customizable lines and zone fills.
Trading Logic:
• Entry: The strategy initiates a long position when the price crosses into the support zone (i.e., when the price drops into a predetermined support area).
• Exit: The long position is closed when the price enters the resistance zone (i.e., when the price rises into a predetermined resistance area).
• Time Frame: Trading signals are generated solely from the 1-hour chart. The strategy is only active within a specified start and end date.
• Note: Only long trades are executed; short selling is not part of the strategy.
Visualization and Parameters:
• Support/Resistance Zones: The zones are drawn based on calculated fractal values, with options to extend the lines to the right for easier tracking.
• Customization: Users can configure the appearance, such as line style (solid, dotted, dashed), line width, colors, and label positions.
• Volume Filtering: A volume moving average threshold is used to confirm the fractal signals, enhancing the reliability of the support and resistance levels.
• Alerts: The strategy includes alert conditions for when the price enters the support or resistance zones, allowing for timely notifications.
⸻
搞钱兔，搞钱是为了更好的生活。
标题： GQT GPT - 基于成交量的支撑与阻力区间 V2
概述：
本策略使用 PineScript v5 实现，旨在基于成交量驱动的分形分析，在1小时级别的图表上识别关键支撑与阻力区间。策略通过成交量移动平均线和特定的价格行为标准计算分形高点（阻力）和分形低点（支撑），并以自定义的线条和区间填充形式直观地显示在图表上。
交易逻辑：
• 进场条件： 当价格进入支撑区间（即价格跌入预设支撑区域）时，策略在没有持仓的情况下发出做多信号。
• 离场条件： 当价格进入阻力区间（即价格上升至预设阻力区域）时，持有多头头寸则会被平仓。
• 时间范围： 策略的信号仅基于1小时级别的图表，并且仅在指定的开始日期与结束日期之间生效。
• 备注： 本策略仅执行多头交易，不进行空头操作。
可视化与参数设置：
• 支撑/阻力区间： 根据计算得出的分形值绘制支撑与阻力线，可选择将线条延伸至右侧，便于后续观察。
• 自定义选项： 用户可以调整线条样式（实线、点线、虚线）、线宽、颜色及标签位置，以满足个性化需求。
• 成交量过滤： 策略使用成交量移动平均阈值来确认分形信号，提高支撑和阻力区间的有效性。
• 警报功能： 当价格进入支撑或阻力区间时，策略会触发警报条件，方便用户及时关注市场变化。
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2:45 AM Candle High/Low Crossing Bars2:45 AM Candle High/Low Crossing Bars is an indicator that focuses on the trading view 2:45am NY TIME high and low indicating green for buy and red bars for sell, with the 2:45am new york time highlight/ If the next candle sweeps the low we buy while if it sweeps the high we sell, all time zoon must be the new York UTC time.
Box Chart Overlay StrategyExploring the Box Chart Overlay Strategy with RSI & Bollinger Confirmation
The “Box Chart Overlay Strategy by BD” is a sophisticated TradingView strategy script written in Pine Script (version 5). It combines a box charting method with two widely used technical indicators—Relative Strength Index (RSI) and Bollinger Bands—to generate trade entries. In this article, we break down the strategy’s components, its logic, and how it visually represents trading signals on the chart.
1. Strategy Setup and User Inputs
Strategy Declaration
At the top of the script, the strategy is declared with key parameters:
Overlay: The indicator is plotted directly on the price chart.
Initial Capital & Position Sizing: It uses a simulated trading account with an initial capital of 10,000 and positions sized as a percentage of equity (10% by default).
Commission: A commission of 0.1% is factored into trades.
Input Parameters
The strategy is highly customizable. Users can adjust various inputs such as:
Box Settings:
Box Size (RSboxSize): Defines the size of each price “box.”
Box Options: Choose from three modes:
Standard: Boxes are calculated continuously from the start of the chart.
Anchored: The first box is fixed at a specified time and price.
Daily Reset: The boxes reset each day based on a defined session time.
Color Customizations:
Options to customize the appearance of boxes, borders, labels, and even repainting the candles based on the current price’s relation to box levels.
RSI Settings:
Length, overbought, and oversold levels are set to filter trades.
Bollinger Bands Settings:
Users can set the length of the moving average and the multiplier for standard deviation, which will be used to compute the upper and lower bands.
2. The Box Chart Mechanism
Box Construction
The core idea of a box chart is to group price movement into discrete blocks—or boxes—of a fixed size. In this strategy:
Standard Mode:
The script calculates boxes starting at a rounded price level. When the price moves sufficiently above or below the current box’s boundaries, a new box is drawn.
Anchored and Daily Reset Modes:
These modes allow traders to control where the box calculations begin or to reset them during a specific intraday session.
Visual Elements
Several custom functions handle the visual components:
drawBoxUp() and drawBoxDn():
These functions create boxes in bullish or bearish directions respectively, based on whether the price has exceeded the current box’s high or low.
drawLines() and drawLabels():
Lines are drawn to extend the current box levels, and labels are updated to display key levels or the “remainder” (the difference needed to trigger a new box).
Projected Boxes:
A “projected” box is drawn to indicate potential upcoming box levels, providing an additional visual cue about the price action.
3. Integrating RSI and Bollinger Bands for Trade Confirmation
RSI Integration
The strategy computes the RSI using a user-defined length. It then uses the following conditions to validate entries:
Long Trades (Box Up):
The strategy waits for the RSI to be at or below the oversold level before considering a long entry.
Short Trades (Box Down):
It requires the RSI to be at or above the overbought level before triggering a short entry.
Bollinger Bands Confirmation
In addition to the RSI filter:
For Long Entries:
The price must be at or below the lower Bollinger Band.
For Short Entries:
The price must be at or above the upper Bollinger Band.
By combining these filters with the box breakout logic, the strategy aims to enhance the quality of its trade signals.
4. Dynamic Trade Entries and Alerts
Box Logic and Entry Functions
Two key functions—BoxUpFunc() and BoxDownFunc()—handle the creation of new boxes and also check if trade conditions are met:
When a new box is drawn, the script evaluates if the RSI and Bollinger conditions align.
If conditions are satisfied, the script places an entry order:
Long Entry: Initiated when the price moves upward, RSI indicates oversold, and the price touches or falls below the lower Bollinger Band.
Short Entry: Triggered when the price falls downward, RSI signals overbought, and the price touches or exceeds the upper Bollinger Band.
Alerts
Built-in alert functions notify traders when a new box level is reached. Users can set custom alert messages to ensure they are aware of potential trade opportunities as soon as the conditions are met.
5. Visual Enhancements and Candle Repainting
The script also includes options for repainting candles based on their relation to the current box’s boundaries:
Above, Below, or Within the Box:
Candles are color-coded using user-defined colors, making it easier to visually assess where the price is in relation to the box levels.
Labels and Lines:
These continuously update to reflect current levels and provide an immediate visual reference for potential breakout points.
Conclusion
The Box Chart Overlay Strategy by BD is a multi-faceted approach that marries the traditional box chart technique with modern technical indicators—RSI and Bollinger Bands—to refine entry signals. By offering various customization options for box creation, visual styling, and confirmation criteria, the strategy allows traders to adapt it to different market conditions and personal trading styles. Whether you prefer a continuously running “Standard” mode or a more controlled “Anchored” or “Daily Reset” approach, this strategy provides a robust framework for integrating price action with momentum and volatility measures.
Qullamaggie [Modified] | FractalystWhat's the purpose of this strategy?
The strategy aims to identify high-probability breakout setups in trending markets, inspired by Kristjan "Qullamaggie" Kullamägi’s approach.
It focuses on capturing explosive price moves after periods of consolidation, using technical criteria like moving averages, breakouts, trailing stop-loss and momentum confirmation.
Ideal for swing traders seeking to ride strong trends while managing risk.
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How does the strategy work?
The strategy follows a systematic process to capture high-momentum breakouts:
Pre-Breakout Criteria:
Prior Price Surge: Identifies stocks that have rallied 30-100%+ in recent month(s), signaling strong underlying momentum (per Qullamaggie’s volatility expansion principles).
Consolidation Phase: Looks for a tightening price range (e.g., flag, pennant, or tight base), indicating a potential "coiling" before continuation.
Trend Confirmation: Uses moving averages (e.g., 20/50/200 EMA) to ensure the stock is trading above key averages on the daily chart, confirming an uptrend.
Price Break: Enters when price clears the consolidation high with conviction.
Risk Management:
Initial Stop Loss: Placed below the consolidation low or a recent swing point to limit downside.
Break-Even Adjustment: Moves stop loss to breakeven once the trade reaches 1.5x risk-to-reward (RR), securing a "free trade" while letting winners run.
Trailing Stop (Unique Edge):
Market Structure Trailing: Instead of trailing via moving averages, the stop is dynamically adjusted using structural invalidation level. This adapts to price action, allowing the trade to stay open during volatile retracements while locking in gains as new structure forms.
Why This Matters: Most strategies use rigid trailing stops (e.g., below the 10EMA), which often exit prematurely in choppy markets. By trailing based on structure, this strategy avoids "noise" and captures larger trends, directly boosting overall returns.
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What markets or timeframes is this suited for?
This is a long-only strategy designed for trending markets, and it performs best in:
Markets: Stocks (especially high-growth, liquid equities), cryptocurrencies (major pairs with strong volatility), commodities (e.g., oil, gold), and futures (index/commodity futures).
Timeframes: Primarily daily charts for swing trades (1-30 day holds), though weekly charts can help confirm broader trends.
Key Advantage: The TradingView script allows instant backtesting with adjustable parameters
You can:
- Test historical performance across multiple markets to identify which assets align best with the strategy.
- Optimize settings (e.g., trailing stop sensitivity, moving averages etc.) to match a market’s volatility profile.
Build a diversified portfolio by filtering for markets that show consistent profitability in backtests.
For example, you might discover cryptos require tighter trailing stops due to volatility, while stocks thrive with wider structural stops. The script automates this analysis, letting you to trade confidently.
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What indicators or tools does the strategy use?
The strategy combines customizable technical tools with strict anti-lookahead safeguards:
Core Indicators:
Moving Averages: Adjustable periods (e.g., 20/50/200 EMA or SMA) and timeframes (daily/weekly) to confirm trend alignment. Users can test combinations (e.g., 10EMA vs. 20EMA) to optimize for specific markets.
Breakout Parameters:
Consolidation Length: Adjustable window to define the "tightness" of the pre-breakout pattern.
Entry Models: Flexible entry logics (Breakouts and fractals)
Anti-Lookahead Design:
All calculations (e.g., moving averages, consolidation ranges, volume averages) use only closed/confirmed data available at the time of the signal.
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How do I manage risk with this strategy?
The strategy prioritizes customizable risk controls to align with your trading style and account size:
User-Defined Risk Inputs:
Risk Per Trade: Set a % of Equity (e.g., 1-2%) to determine position size. The strategy auto-calculates shares/contracts to match your selected risk per trade.
Flexibility: Choose between fixed risk or equity-based scaling.
The script adjusts position sizing dynamically based on your selection.
Pyramiding Feature:
Customizable Entries: Adjust the number of pyramiding trades allowed (e.g., 1-3 additional positions) in the strategy settings. Each new entry is triggered only if the prior trade hits its 1.5x RR target and the trend remains intact.
Risk-Scaled Additions: New positions use profits from prior trades, compounding gains without increasing initial risk.
Risk-Free Trade Mechanic:
Once a trade reaches 1.5x RR, the stop loss is moved to breakeven, eliminating downside risk.
The strategy then opens a new position (if pyramiding is enabled) using a portion of the locked-in profit. This "snowballs" winners while keeping total capital exposure stable.
Impact on Net Profit & Drawdown:
Net Profit Boost: Pyramiding lets you ride multi-leg trends aggressively. For example, a 100% runner could generate 2-3x more profit vs. a single-entry approach.
Controlled Drawdowns: Since new positions are funded by profits (not initial capital), max drawdown stays anchored to your original risk per trade (e.g., 1-2% of account). Even if later entries fail, the breakeven stop on prior trades protects overall equity.
Why This Works: Most strategies either over-leverage (increasing drawdowns) or exit too early. By recycling profits into new positions only after securing risk-free capital, this approach mimics hedge fund "scaling in" tactics while staying retail-trader friendly.
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How does the strategy identify market structure for its trailing stoploss?
The strategy identifies market structure by utilizing an efficient logic with for loops to pinpoint the first swing candle that features a pivot of 2. This marks the beginning of the break of structure, where the market's previous trend or pattern is considered invalidated or changed.
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What are the underlying calculations?
The underlying calculations involve:
Identifying Swing Points: The strategy looks for swing highs (marked with blue Xs) and swing lows (marked with red Xs). A swing high is identified when a candle's high is higher than the highs of the candles before and after it. Conversely, a swing low is when a candle's low is lower than the lows of the candles before and after it.
Break of Structure (BOS):
Bullish BOS: This occurs when the price breaks above the swing high level of the previous structure, indicating a potential shift to a bullish trend.
Bearish BOS: This happens when the price breaks below the swing low level of the previous structure, signaling a potential shift to a bearish trend.
Structural Liquidity and Invalidation:
Structural Liquidity: After a break of structure, liquidity levels are updated to the first swing high in a bullish BOS or the first swing low in a bearish BOS.
Structural Invalidation: If the price moves back to the level of the first swing low before the bullish BOS or the first swing high before the bearish BOS, it invalidates the break of structure, suggesting a potential reversal or continuation of the previous trend.
This method provides users with a technical approach to filter market regimes, offering an advantage by minimizing the risk of overfitting to historical data, which is often a concern with traditional indicators like moving averages.
By focusing on identifying pivotal swing points and the subsequent breaks of structure, the strategy maintains a balance between sensitivity to market changes and robustness against historical data anomalies, ensuring a more adaptable and potentially more reliable market analysis tool.
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What entry criteria are used in this script?
The script uses two entry models for trading decisions: BreakOut and Fractal.
Underlying Calculations:
Breakout: The script records the most recent swing high by storing it in a variable. When the price closes above this recorded level, and all other predefined conditions are satisfied, the script triggers a breakout entry. This approach is considered conservative because it waits for the price to confirm a breakout above the previous high before entering a trade. As shown in the image, as soon as the price closes above the new candle (first tick), the long entry gets taken. The stop-loss is initially set and then moved to break-even once the price moves in favor of the trade.
Fractal: This method involves identifying a swing low with a period of 2, which means it looks for a low point where the price is lower than the two candles before and after it. Once this pattern is detected, the script executes the trade. This is an aggressive approach since it doesn't wait for further price confirmation. In the image, this is represented by the 'Fractal 2' label where the script identifies and acts on the swing low pattern.
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What type of stop-loss identification method are used in this strategy?
This strategy employs two types of stop-loss methods: Initial Stop-loss and Trailing Stop-Loss.
Underlying Calculations:
Initial Stop-loss:
ATR Based: The strategy uses the Average True Range (ATR) to set an initial stop-loss, which helps in accounting for market volatility without predicting price direction.
Calculation:
- First, the True Range (TR) is calculated for each period, which is the greatest of:
- Current Period High - Current Period Low
- Absolute Value of Current Period High - Previous Period Close
- Absolute Value of Current Period Low - Previous Period Close
- The ATR is then the moving average of these TR values over a specified period, typically 14 periods by default. This ATR value can be used to set the stop-loss at a distance from the entry price that reflects the current market volatility.
Swing Low Based:
For this method, the stop-loss is set based on the most recent swing low identified in the market structure analysis. This approach uses the lowest point of the recent price action as a reference for setting the stop-loss.
Trailing Stop-Loss:
The strategy uses structural liquidity and structural invalidation levels across multiple timeframes to adjust the stop-loss once the trade is profitable. This method involves:
Detecting Structural Liquidity: After a break of structure, the liquidity levels are updated to the first swing high in a bullish scenario or the first swing low in a bearish scenario. These levels serve as potential areas where the price might find support or resistance, allowing the stop-loss to trail the price movement.
Detecting Structural Invalidation: If the price returns to the level of the first swing low before a bullish break of structure or the first swing high before a bearish break of structure, it suggests the trend might be reversing or invalidating, prompting the adjustment of the stop-loss to lock in profits or minimize losses.
By using these methods, the strategy dynamically adjusts the initial stop-loss based on market volatility, helping to protect against adverse price movements while allowing for enough room for trades to develop. The ATR-based stop-loss adapts to the current market conditions by considering the volatility, ensuring that the stop-loss is not too tight during volatile periods, which could lead to premature exits, nor too loose during calm markets, which might result in larger losses. Similarly, the swing low based stop-loss provides a logical exit point if the market structure changes unfavorably.
Each market behaves differently across various timeframes, and it is essential to test different parameters and optimizations to find out which trailing stop-loss method gives you the desired results and performance. This involves backtesting the strategy with different settings for the ATR period, the distance from the swing low, and how the trailing stop-loss reacts to structural liquidity and invalidation levels.
Through this process, you can tailor the strategy to perform optimally in different market environments, ensuring that the stop-loss mechanism supports the trade's longevity while safeguarding against significant drawdowns.
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What type of break-even method is used in this strategy? What are the underlying calculations?
Moves the initial stop-loss to the entry price when the price reaches a certain RR ratio.
Calculation:
Break-even level = Entry Price + (Initial Risk * RR Ratio)
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What tables are available in this script?
- Summary: Provides a general overview, displaying key performance parameters such as Net Profit, Profit Factor, Max Drawdown, Average Trade, Closed Trades and more.
Total Commission: Displays the cumulative commissions incurred from all trades executed within the selected backtesting window. This value is derived by summing the commission fees for each trade on your chart.
Average Commission: Represents the average commission per trade, calculated by dividing the Total Commission by the total number of closed trades. This metric is crucial for assessing the impact of trading costs on overall profitability.
Avg Trade: The sum of money gained or lost by the average trade generated by a strategy. Calculated by dividing the Net Profit by the overall number of closed trades. An important value since it must be large enough to cover the commission and slippage costs of trading the strategy and still bring a profit.
MaxDD: Displays the largest drawdown of losses, i.e., the maximum possible loss that the strategy could have incurred among all of the trades it has made. This value is calculated separately for every bar that the strategy spends with an open position.
Profit Factor: The amount of money a trading strategy made for every unit of money it lost (in the selected currency). This value is calculated by dividing gross profits by gross losses.
Avg RR: This is calculated by dividing the average winning trade by the average losing trade. This field is not a very meaningful value by itself because it does not take into account the ratio of the number of winning vs losing trades, and strategies can have different approaches to profitability. A strategy may trade at every possibility in order to capture many small profits, yet have an average losing trade greater than the average winning trade. The higher this value is, the better, but it should be considered together with the percentage of winning trades and the net profit.
Winrate: The percentage of winning trades generated by a strategy. Calculated by dividing the number of winning trades by the total number of closed trades generated by a strategy. Percent profitable is not a very reliable measure by itself. A strategy could have many small winning trades, making the percent profitable high with a small average winning trade, or a few big winning trades accounting for a low percent profitable and a big average winning trade. Most mean-reversion successful strategies have a percent profitability of 40-80% but are profitable due to risk management control.
BE Trades: Number of break-even trades, excluding commission/slippage.
Losing Trades: The total number of losing trades generated by the strategy.
Winning Trades: The total number of winning trades generated by the strategy.
Total Trades: Total number of taken traders visible your charts.
Net Profit: The overall profit or loss (in the selected currency) achieved by the trading strategy in the test period. The value is the sum of all values from the Profit column (on the List of Trades tab), taking into account the sign.
- Monthly: Displays performance data on a month-by-month basis, allowing users to analyze performance trends over each month and year.
- Weekly: Displays performance data on a week-by-week basis, helping users to understand weekly performance variations.
- UI Table: A user-friendly table that allows users to view and save the selected strategy parameters from user inputs. This table enables easy access to key settings and configurations, providing a straightforward solution for saving strategy parameters by simply taking a screenshot with Alt + S or ⌥ + S.
User-input styles and customizations:
Please note that all background colors in the style are disabled by default to enhance visualization.
How to Use This Strategy to Create a Profitable Edge and Systems?
Choose Your Strategy mode:
- Decide whether you are creating an investing strategy or a trading strategy.
Select a Market:
- Choose a one-sided market such as stocks, indices, or cryptocurrencies.
Historical Data:
- Ensure the historical data covers at least 10 years of price action for robust backtesting.
Timeframe Selection:
- Choose the timeframe you are comfortable trading with. It is strongly recommended to use a timeframe above 15 minutes to minimize the impact of commissions/slippage on your profits.
Set Commission and Slippage:
- Properly set the commission and slippage in the strategy properties according to your broker/prop firm specifications.
Parameter Optimization:
- Use trial and error to test different parameters until you find the performance results you are looking for in the summary table or, preferably, through deep backtesting using the strategy tester.
Trade Count:
- Ensure the number of trades is 200 or more; the higher, the better for statistical significance.
Positive Average Trade:
- Make sure the average trade is above zero.
(An important value since it must be large enough to cover the commission and slippage costs of trading the strategy and still bring a profit.)
Performance Metrics:
- Look for a high profit factor, and net profit with minimum drawdown.
- Ideally, aim for a drawdown under 20-30%, depending on your risk tolerance.
Refinement and Optimization:
- Try out different markets and timeframes.
- Continue working on refining your edge using the available filters and components to further optimize your strategy.
What Makes This Strategy Unique?
This strategy combines flexibility, smart risk management, and momentum focus in a way that’s rare and practical:
1. Adapts to Any Market Rhythm
Works on daily, weekly, or intraday charts without code changes.
Uses two entry types: classic breakouts (like trending stocks) or fractal patterns (to avoid false starts).
2. Smarter Stop-Loss System
No rigid rules: Stops adjust based on price structure (e.g., new “higher lows”), not fixed percentages.
Avoids whipsaws: Tightens stops only when the trend strengthens, not in choppy markets.
3. Safe Profit-Boosting Pyramiding
Adds new positions only after prior trades are risk-free (stops moved above breakeven).
Scales up using locked-in profits, not new capital, to grow gains safely.
4. Built-In Momentum Check
Tracks 1/3/6-month price growth to spotlight stocks with strong, lasting momentum.
Terms and Conditions | Disclaimer
Our charting tools are provided for informational and educational purposes only and should not be construed as financial, investment, or trading advice. They are not intended to forecast market movements or offer specific recommendations. Users should understand that past performance does not guarantee future results and should not base financial decisions solely on historical data.
Built-in components, features, and functionalities of our charting tools are the intellectual property of @Fractalyst Unauthorized use, reproduction, or distribution of these proprietary elements is prohibited.
- By continuing to use our charting tools, the user acknowledges and accepts the Terms and Conditions outlined in this legal disclaimer and agrees to respect our intellectual property rights and comply with all applicable laws and regulations.
Scalping Strategy Signal v2 by [INFINITYTRADER]Overview
This Pine Script (v6) implements a scalping strategy that uses higher timeframe data (default: 4H) to generate entry and exit signals, originally designed for the 15-minute timeframe with an option for 30-minute charts. The "Scalping Strategy Signal v2 by " integrates moving averages, RSI, volume, ATR, and candlestick patterns to identify trading opportunities. It features adjustable risk management with ATR-based stop-loss, take-profit, and trailing stops, plus dynamic position sizing based on user-set capital. Trades trigger only on the higher timeframe candle close (e.g., 4H) to limit activity within the same period. This closed-source script offers a structured scalping approach, blending multiple entry methods and risk controls for adaptability across market conditions.
What Makes It Unique
Unlike typical scalping scripts relying on single-indicator triggers (e.g., RSI alone or basic MA crossovers), this strategy combines four distinct entry methods—standard MA crossovers, RSI-based momentum shifts, trend-following shorts, and candlestick pattern logic—evaluated on a 4H timeframe for confirmation. This multi-layered design, paired with re-entry logic after losses and a mix of manual, ATR-based, and trailing exits, aims to balance trade frequency and reliability. The higher timeframe filter adds precision not commonly found in simpler scalping tools, while the 30-minute option enhances consistency by reducing noise.
How It Works
Timeframe Logic
Runs on a base timeframe (designed for 15-minute charts, with a 30-minute option) while pulling data from a user-chosen higher timeframe (default: 4H) for signal accuracy.
Limits entries to the close of each 4H candle, ensuring one trade per period to avoid over-trading in volatile conditions.
Indicators and Data
Moving Averages : Employs 21-period and 50-period simple moving averages on the higher timeframe to detect trends and signal entries/exits.
Volume : Requires volume to exceed 70% of its 20-period average on the higher timeframe for momentum confirmation.
RSI : Uses a 14-period RSI for overbought/oversold filtering and a 6-period RSI for precise entry timing.
ATR : Applies a 14-period Average True Range on the higher timeframe to set adaptive stop-loss and take-profit levels.
Candlestick Patterns : Analyzes consecutive green or red 4H bars for trend continuation signals.
Why These Indicators
The blend of moving averages, RSI, volume, ATR, and candlestick patterns forms a robust scalping framework. Moving averages establish trend context, RSI filters momentum and avoids extremes, volume confirms market activity, ATR adjusts risk to volatility, and candlestick patterns enhance entry timing with price action insights. Together, they target small, frequent moves in flat or trending markets, with the 4H filter reducing false signals common in lower-timeframe scalping.
Entry Conditions
Four entry methods are evaluated at the 4H candle close:
Standard Long Entry: Price crosses above the 21-period moving average, volume exceeds 70% of its 20-period average, and the 1H 14-period RSI is below 70—confirms uptrend momentum.
Special Long Entry: The 6-period RSI crosses above 23, price is more than 1.5 times the ATR from the 21-period moving average, and price exceeds its prior close—targets oversold bounces with a stop-loss at the 4H candle’s low.
Short Entries:
- RSI-Based: The 6-period RSI crosses below 68 with volume support—catches overbought pullbacks.
- Trend-Based: Price crosses below the 21-period moving average, volume is above 70% of its average, and the 1H 14-period RSI is above 30—confirms downtrends.
Red/Green Bar Logic: Two consecutive green 4H bars for longs or red 4H bars for shorts—uses candlestick patterns for continuation, with a tight stop-loss from the base timeframe candle.
Re-Entry Logic
Long : After a losing special long, triggers when the 6-period RSI crosses 27 and price crosses the 21-period moving average.
Short : After a losing short, triggers when the 6-period RSI crosses 50 and price crosses below the 21-period moving average.
Purpose: Offers recovery opportunities with stricter conditions.
Exit Conditions
Manual Exits: Longs close if the 21-period MA crosses below the 50-period MA or the 1H 14-period RSI exceeds 68; shorts close if the 21-period MA crosses above the 50-period MA or RSI drops below 25.
ATR-Based TP/SL: Stop-loss is entry price ± ATR × 1.5 (default); take-profit is ± ATR × 4 (default), checked at 4H close.
Trailing Stop: Adjusts ±6x ATR from peak/trough, closing if price retraces within 1x ATR.
Special/Tight SL: Special longs exit if price opens below the 4H candle’s low; 4th method entries use the base timeframe candle’s low/high, checked every bar.
Position Sizing
Bases trade value on user-set capital (default: 100 USDT), dividing by the higher timeframe close price for dynamic sizing.
Visualization
Displays a table at the bottom-right with current/previous signals, TP/SL levels, equity, trading pair, and trade size—color-coded for clarity (green for buy, red for sell).
Inputs
Initial Capital (USDT): Sets trade value (default: 100, min: 1).
ATR Stop-Loss Multiplier: Adjusts SL distance (default: 1.5, min: 1).
ATR Take-Profit Multiplier: Adjusts TP distance (default: 4, min: 1).
Higher Timeframe: Selects analysis timeframe (options: 1m, 5m, 15m, 30m, 1H, 4H, D, W; default: 4H).
Usage Notes
Intended Timeframe: Designed for 15-minute charts with 4H confirmation for precision and frequency; 30-minute charts improve consistency by reducing noise.
Backtesting: Adjust ATR multipliers and capital to match your asset’s volatility and risk tolerance.
Risk Management: Combines manual, ATR, and trailing exits—monitor to avoid overexposure.
Limitations: 4H candle-close dependency may delay entries in fast markets; RSI/volume filters can reduce trades in low-momentum periods.
Backtest Observations
Tested on BTC/USDT (4H higher timeframe, default settings: Initial Capital: 100 USDT, ATR SL: 1.5x, ATR TP: 4x) across market conditions, comparing 15-minute and 30-minute charts:
Bull Market (Jul 2023 - Dec 2023):
15-Minute: 277 long, 219 short; Win Rate: 42.74%; P&L: 108%; Drawdown: 1.99%; Profit Factor: 3.074.
30-Minute: 257 long, 215 short; Win Rate: 49.58%; P&L: 116.85%; Drawdown: 2.34%; Profit Factor: 3.14.
Notes: Moving average crossovers and green bar patterns suited this bullish phase; 30-minute improved win rate and P&L by filtering weaker signals.
Bear Market (Jan 2022 - Jun 2022):
15-Minute: 262 long, 211 short; Win Rate: 44.4%; P&L: 239.80%; Drawdown: 3.74%; Profit Factor: 3.419.
30-Minute: 250 long, 200 short; Win Rate: 52.22%; P&L: 258.77%; Drawdown: 5.34%; Profit Factor: 3.461.
Notes: Red bar patterns and RSI shorts thrived in the downtrend; 30-minute cut choppy reversals for better consistency.
Flat Market (Jan 2021 - Jun 2021):
15-Minute: 280 long, 208 short; Win Rate: 51.84%; P&L: 340.33%; Drawdown: 9.59%; Profit Factor: 2.924.
30-Minute: 270 long, 209 short; Win Rate: 55.11%; P&L: 315.42%; Drawdown: 7.21%; Profit Factor: 2.598.
Notes: High trade frequency and P&L showed strength in ranges; 30-minute lowered drawdown for better risk control.
Results reflect historical performance on BTC/USDT with default settings—users should test on their assets and timeframes. Past performance does not guarantee future results and is shared only to illustrate the strategy’s behavior.
Why It Works Well in Flat Markets
A "flat market" lacks strong directional trends, with price oscillating around moving averages, as in Jan 2021 - Jun 2021 for BTC/USDT. This strategy excels here because its crossover-based entries trigger frequently in tight ranges. In trending markets, an exit might not be followed by a new entry without a pullback, but flat markets produce multiple crossovers, enabling more trades. ATR-based TP/SL and trailing stops capture these small swings, while RSI and volume filters ensure momentum, driving high P&L and win rates.
Technical Details
Built in Pine Script v6 for TradingView compatibility.
Prevents overlapping trades with long/short checks.
Handles edge cases like zero division and auto-detects the trading pair’s base currency (e.g., BTC from BTCUSDT).
This strategy suits scalpers seeking structured entries and risk management. Test on 15-minute or 30-minute charts to match your style and market conditions.
PowerZone Trading StrategyExplanation of the PowerZone Trading Strategy for Your Users
The PowerZone Trading Strategy is an automated trading strategy that detects strong price movements (called "PowerZones") and generates signals to enter a long (buy) or short (sell) position, complete with predefined take profit and stop loss levels. Here’s how it works, step by step:
1. What is a PowerZone?
A "PowerZone" (PZ) is a zone on the chart where the price has shown a significant and consistent movement over a specific number of candles (bars). There are two types:
Bullish PowerZone (Bullish PZ): Occurs when the price rises consistently over several candles after an initial bearish candle.
Bearish PowerZone (Bearish PZ): Occurs when the price falls consistently over several candles after an initial bullish candle.
The code analyzes:
A set number of candles (e.g., 5, adjustable via "Periods").
A minimum percentage move (adjustable via "Min % Move for PowerZone") to qualify as a strong zone.
Whether to use the full candle range (highs and lows) or just open/close prices (toggle with "Use Full Range ").
2. How Does It Detect PowerZones?
Bullish PowerZone:
Looks for an initial bearish candle (close below open).
Checks that the next candles (e.g., 5) are all bullish (close above open).
Ensures the total price movement exceeds the minimum percentage set.
Defines a range: from the high (or open) to the low of the initial candle.
Bearish PowerZone:
Looks for an initial bullish candle (close above open).
Checks that the next candles are all bearish (close below open).
Ensures the total price movement exceeds the minimum percentage.
Defines a range: from the high to the low (or close) of the initial candle.
These zones are drawn on the chart with lines: green or white for bullish, red or blue for bearish, depending on the color scheme ("DARK" or "BRIGHT").
3. When Does It Enter a Trade?
The strategy waits for a breakout from the PowerZone range to enter a trade:
Buy (Long): When the price breaks above the high of a Bullish PowerZone.
Sell (Short): When the price breaks below the low of a Bearish PowerZone.
The position size is set to 100% of available equity (adjustable in the code).
4. Take Profit and Stop Loss
Take Profit (TP): Calculated as a multiple (adjustable via "Take Profit Factor," default 1.5) of the PowerZone height. For example:
For a buy, TP = Entry price + (PZ height × 1.5).
For a sell, TP = Entry price - (PZ height × 1.5).
Stop Loss (SL): Calculated as a multiple (adjustable via "Stop Loss Factor," default 1.0) of the PZ height, placed below the range for buys or above for sells.
5. Visualization on the Chart
PowerZones are displayed with lines on the chart (you can hide them with "Show Bullish Channel" or "Show Bearish Channel").
An optional info panel ("Show Info Panel") displays key levels: PZ high and low, TP, and SL.
You can also enable brief documentation on the chart ("Show Documentation") explaining the basic rules.
6. Alerts
The code generates automatic alerts in TradingView:
For a bullish breakout: "Bullish PowerZone Breakout - LONG!"
For a bearish breakdown: "Bearish PowerZone Breakdown - SHORT!"
7. Customization
You can tweak:
The number of candles to detect a PZ ("Periods").
The minimum percentage move ("Min % Move").
Whether to use highs/lows or just open/close ("Use Full Range").
The TP and SL factors.
The color scheme and what elements to display on the chart.
Practical Example
Imagine you set "Periods = 5" and "Min % Move = 2%":
An initial bearish candle appears, followed by 5 consecutive bullish candles.
The total move exceeds 2%.
A Bullish PowerZone is drawn with a high and low.
If the price breaks above the high, you enter a long position with a TP 1.5 times the PZ height and an SL equal to the height below.
The system executes the trade and exits automatically at TP or SL.
Conclusion
This strategy is great for capturing strong price movements after consolidation or momentum zones. It’s automated, visual, and customizable, making it useful for both beginner and advanced traders. Try it out and adjust it to fit your trading style!
Reversal & Breakout Strategy with ORB### Reversal & Breakout Strategy with ORB
This strategy combines three distinct trading approaches—reversals, trend breakouts, and opening range breakouts (ORB)—into a single, cohesive system. The goal is to capture high-probability setups across different market conditions, leveraging a mashup of technical indicators for confirmation and risk management. Below, I’ll explain why this combination works, how the components interact, and how to use it effectively.
#### Why the Mashup?
- **Reversals**: Identifies overextended moves using RSI (overbought/oversold) and SMA50 crosses, filtered by VWAP and SMA200 trend direction. This targets mean-reversion opportunities in trending markets.
- **Breakouts**: Uses EMA9/EMA20 crossovers with VWAP and SMA200 confirmation to catch momentum-driven trend continuations.
- **Opening Range Breakout (ORB)**: Detects early momentum by breaking the high/low of a user-defined opening range (default: 15 bars) with volume confirmation. This adds a time-based edge, ideal for intraday trading.
The synergy comes from blending these methods: reversals catch pullbacks, breakouts ride trends, and ORB exploits early volatility—all filtered by trend (SMA200) and anchored by VWAP for context.
#### How It Works
1. **Indicators**:
- **EMA9/EMA20**: Fast-moving averages for breakout signals.
- **SMA50**: Medium-term trend filter for reversals.
- **SMA200**: Long-term trend direction to align trades.
- **RSI (14)**: Measures overbought (>70) or oversold (<30) conditions.
- **VWAP**: Acts as a dynamic support/resistance level.
- **ATR (14)**: Sets stop-loss distance (default: 1.5x ATR).
- **Volume**: Confirms ORB breakouts (1.5x average volume of opening range).
2. **Entry Conditions**:
- **Long**: Triggers on reversal (SMA50 cross + RSI < 30 + below VWAP + uptrend), breakout (EMA9 > EMA20 + above VWAP + uptrend), or ORB (break above opening range high + volume).
- **Short**: Triggers on reversal (SMA50 cross + RSI > 70 + above VWAP + downtrend), breakout (EMA9 < EMA20 + below VWAP + downtrend), or ORB (break below opening range low + volume).
3. **Risk Management**:
- Risks 5% of equity per trade (based on the initial capital set in the strategy tester).
- Stop-loss: Based on lowest low/highest high over 7 bars ± 1.5x ATR.
- Targets: Two exits at 1:1 and 1:2 risk:reward (50% of position at each).
- Break-even: Stop moves to entry price after the first target is hit.
4. **Backtesting Settings**:
- Commission: Hardcoded at 0.1% per trade (realistic for most brokers).
- Slippage: Hardcoded at 2 ticks (realistic for most markets).
- Tested on datasets yielding 100+ trades (e.g., 2-min or 5-min charts over months).
#### How to Use It
- **Timeframe**: Works best on intraday (2-min, 5-min) or daily charts. Adjust `Opening Range Bars` (e.g., 15 bars = 30 min on 2-min chart) for your timeframe.
- **Settings**:
- Set your initial equity in the TradingView strategy tester’s "Properties" tab under "Initial Capital" (e.g., $10,000). The script automatically risks 5% of this equity per trade.
- Adjust `Stop Loss ATR Multiplier` or `Risk:Reward Targets` based on your risk tolerance.
- Note that commission (0.1%) and slippage (2 ticks) are fixed in the script for backtesting consistency.
- **Execution**: Enter on signal, monitor plotted stop (red) and targets (green/blue). The strategy supports pyramiding (up to 2 positions) for scaling into trends.
#### Backtesting Notes
Results are realistic with commission (0.1%) and slippage (2 ticks) included. For a sufficient sample, test on volatile instruments (e.g., stocks, forex) over 3-6 months on lower timeframes. The default 1.5x ATR stop may seem wide, but it’s justified to avoid premature exits in volatile markets—feel free to tweak it with justification. The script assumes an initial capital of $10,000 in the strategy tester for the 5% risk calculation (e.g., $500 risk per trade); adjust this in the "Properties" tab as needed.
This mashup isn’t just a random mix; it’s a deliberate fusion of complementary strategies, offering traders flexibility across market phases. Questions? Let me know!
IU Bigger than range strategyDESCRIPTION
IU Bigger Than Range Strategy is designed to capture breakout opportunities by identifying candles that are significantly larger than the previous range. It dynamically calculates the high and low of the last N candles and enters trades when the current candle's range exceeds the previous range. The strategy includes multiple stop-loss methods (Previous High/Low, ATR, Swing High/Low) and automatically manages take-profit and stop-loss levels based on user-defined risk-to-reward ratios. This versatile strategy is optimized for higher timeframes and assets like BTC but can be fine-tuned for different instruments and intervals.
USER INPUTS:
Look back Length: Number of candles to calculate the high-low range. Default is 22.
Risk to Reward: Sets the target reward relative to the stop-loss distance. Default is 3.
Stop Loss Method: Choose between:(Default is "Previous High/Low")
- Previous High/Low
- ATR (Average True Range)
- Swing High/Low
ATR Length: Defines the length for ATR calculation (only applicable when ATR is selected as the stop-loss method) (Default is 14).
ATR Factor: Multiplier applied to the ATR to determine stop-loss distance(Default is 2).
Swing High/Low Length: Specifies the length for identifying swing points (only applicable when Swing High/Low is selected as the stop-loss method).(Default is 2)
LONG CONDITION:
The current candle’s range (absolute difference between open and close) is greater than the previous range.
The closing price is higher than the opening price (bullish candle).
SHORT CONDITIONS:
The current candle’s range exceeds the previous range.
The closing price is lower than the opening price (bearish candle).
LONG EXIT:
Stop-loss:
- Previous Low
- ATR-based trailing stop
- Recent Swing Low
Take-profit:
- Defined by the Risk-to-Reward ratio (default 3x the stop-loss distance).
SHORT EXIT:
Stop-loss:
- Previous High
- ATR-based trailing stop
- Recent Swing High
Take-profit:
- Defined by the Risk-to-Reward ratio (default 3x the stop-loss distance).
ALERTS:
Long Entry Triggered
Short Entry Triggered
WHY IT IS UNIQUE:
This strategy dynamically adapts to different market conditions by identifying candles that exceed the previous range, ensuring that it only enters trades during strong breakout scenarios.
Multiple stop-loss methods provide flexibility for different trading styles and risk profiles.
The visual representation of stop-loss and take-profit levels with color-coded plots improves trade monitoring and decision-making.
HOW USERS CAN BENEFIT FROM IT:
Ideal for breakout traders looking to capitalize on momentum-driven price moves.
Provides flexibility to customize stop-loss methods and fine-tune risk management parameters.
Helps minimize drawdowns with a strong risk-to-reward framework while maximizing profit potential.
Liquidity + Internal Market Shift StrategyLiquidity + Internal Market Shift Strategy
This strategy combines liquidity zone analysis with the internal market structure, aiming to identify high-probability entry points. It uses key liquidity levels (local highs and lows) to track the price's interaction with significant market levels and then employs internal market shifts to trigger trades.
Key Features:
Internal Shift Logic: Instead of relying on traditional candlestick patterns like engulfing candles, this strategy utilizes internal market shifts. A bullish shift occurs when the price breaks previous bearish levels, and a bearish shift happens when the price breaks previous bullish levels, indicating a change in market direction.
Liquidity Zones: The strategy dynamically identifies key liquidity zones (local highs and lows) to detect potential reversal points and prevent trades in weak market conditions.
Mode Options: You can choose to run the strategy in "Both," "Bullish Only," or "Bearish Only" modes, allowing for flexibility based on market conditions.
Stop-Loss and Take-Profit: Customizable stop-loss and take-profit levels are integrated to manage risk and lock in profits.
Time Range Control: You can specify the time range for trading, ensuring the strategy only operates during the desired period.
This strategy is ideal for traders who want to combine liquidity analysis with internal structure shifts for precise market entries and exits.
This description clearly outlines the strategy's logic, the flexibility it provides, and how it works. You can adjust it further to match your personal trading style or preferences!
ETH/USDT EMA Crossover Strategy - OptimizedStrategy Name: EMA Crossover Strategy for ETH/USDT
Description:
This trading strategy is designed for the ETH/USDT pair and is based on exponential moving average (EMA) crossovers combined with momentum and volatility indicators. The strategy uses multiple filters to identify high-probability signals in both bullish and bearish trends, making it suitable for traders looking to trade in trending markets.
Strategy Components
EMAs (Exponential Moving Averages):
EMA 200: Used to identify the primary trend. If the price is above the EMA 200, it is considered a bullish trend; if below, a bearish trend.
EMA 50: Acts as an additional filter to confirm the trend.
EMA 20 and EMA 50 Short: These short-term EMAs generate entry signals through crossovers. A bullish crossover (EMA 20 crosses above EMA 50 Short) is a buy signal, while a bearish crossover (EMA 20 crosses below EMA 50 Short) is a sell signal.
RSI (Relative Strength Index):
The RSI is used to avoid overbought or oversold conditions. Long trades are only taken when the RSI is above 30, and short trades when the RSI is below 70.
ATR (Average True Range):
The ATR is used as a volatility filter. Trades are only taken when there is sufficient volatility, helping to avoid false signals in quiet markets.
Volume:
A volume filter is used to confirm sufficient market participation in the price movement. Trades are only taken when volume is above average.
Strategy Logic
Long Trades:
The price must be above the EMA 200 (bullish trend).
The EMA 20 must cross above the EMA 50 Short.
The RSI must be above 30.
The ATR must indicate sufficient volatility.
Volume must be above average.
Short Trades:
The price must be below the EMA 200 (bearish trend).
The EMA 20 must cross below the EMA 50 Short.
The RSI must be below 70.
The ATR must indicate sufficient volatility.
Volume must be above average.
How to Use the Strategy
Setup:
Add the script to your ETH/USDT chart on TradingView.
Adjust the parameters according to your preferences (e.g., EMA periods, RSI, ATR, etc.).
Signals:
Buy and sell signals will be displayed directly on the chart.
Long trades are indicated with an upward arrow, and short trades with a downward arrow.
Risk Management:
Use stop-loss and take-profit orders in all trades.
Consider a risk-reward ratio of at least 1:2.
Backtesting:
Test the strategy on historical data to evaluate its performance before using it live.
Advantages of the Strategy
Trend-focused: The strategy is designed to trade in trending markets, increasing the probability of success.
Multiple filters: The use of RSI, ATR, and volume reduces false signals.
Adaptability: It can be adjusted for different timeframes, although it is recommended to test it on 5-minute and 15-minute charts for ETH/USDT.
Warnings
Sideways markets: The strategy may generate false signals in markets without a clear trend. It is recommended to avoid trading in such conditions.
Optimization: Make sure to optimize the parameters according to the market and timeframe you are using.
Risk management: Never trade without stop-loss and take-profit orders.
Author
Jose J. Sanchez Cuevas
Version
v1.0
Gold Scalping BOS & CHoCHThis strategy is designed for scalping gold (XAU/USD) on the 3-minute timeframe, utilizing Break of Structure (BOS) and Change of Character (CHoCH) to identify high-probability trade setups. Unlike traditional SMA crossover strategies, this method focuses purely on price action and market structure shifts, allowing for early entries and better risk management.
Core Concepts:
Break of Structure (BOS) – Confirms a continuation of the trend when price breaks the last swing high (bullish) or last swing low (bearish).
Change of Character (CHoCH) – Detects possible trend reversals by identifying a shift in market momentum.
Dynamic Support & Resistance – Uses the last 10-bar highs and lows to determine adaptive stop-loss (SL) and take-profit (TP) levels.
Risk-to-Reward Ratio (1:2 RR) – Ensures trades are executed with a favorable risk/reward ratio.
Entry Conditions:
Buy Entry:
BOS (Bullish) confirmed (price breaks the previous swing high).
CHoCH (Bullish) confirms trend shift.
Price crosses back above the last swing low (confirmation of support).
Sell Entry:
BOS (Bearish) confirmed (price breaks the previous swing low).
CHoCH (Bearish) confirms trend shift.
Price crosses back below the last swing high (confirmation of resistance).
Exit Conditions:
Stop Loss (SL): Set at the most recent dynamic support (for buys) or resistance (for sells).
Take Profit (TP): 2x the risk (1:2 risk-reward ratio).
Advantages of This Strategy:
✅ No lagging indicators – Uses price action for real-time entries.
✅ High probability setups – Focuses only on strong structural breaks.
✅ Adaptive SL/TP – Uses real market structure instead of fixed values.
✅ Optimized for Scalping – Best suited for quick in-and-out trades.
Best Time to Trade:
🔹 London & New York Sessions (High volatility for gold).
Grease Trap V1.0The Grease Trap V1.0 indicator is a dynamic, Fibonacci-based strategy that calculates unique moving averages to generate trading signals. Below is an overview of its main components and functionality:
How It Works
Fibonacci Grouped Averages:
Dynamic Fibonacci Sequence:
The indicator uses a custom function that dynamically builds a Fibonacci sequence. The user can set the number of Fibonacci elements for two separate calculations:
One for the Indicator Average (default: 9 elements).
One for the Base Average (default: 14 elements).
Grouped Averaging:
Using these Fibonacci numbers, the script groups historical closing prices into segments. For each group (with a length determined by a Fibonacci number), it computes an average. These individual group averages are then averaged together to produce a single dynamic average.
Plotting and Visual Cues:
Two Lines:
The indicator plots two lines on the chart:
Primary Dynamic Fibonacci Grouped Average
Base Dynamic Fibonacci Grouped Average
Color Coding:
The colors of these lines change based on their relationship to the current high price and to each other. For example, if the primary average is above the high or crosses above the base average, it might be shown in green or yellow, whereas certain conditions trigger red, signaling caution.
Crossover Dots:
When the primary average crosses above the base (a bullish signal), a green dot is plotted. Conversely, when it crosses below (a bearish signal), a red dot is displayed. These dots help visually pinpoint the moments of potential trade entry or exit.
Trading Signals and Orders:
Buy Signal:
Triggered when the primary average crosses above the base average. On a buy signal:
If in a short position, it closes that position.
Then, it enters a long position.
Sell Signal:
Triggered when the primary average crosses below the base average. On a sell signal:
If in a long position, it closes that position.
Then, it enters a short position.
Profit Target Management:
The indicator includes automated profit management:
For long positions, it sets an exit order when the price rises by a user-defined percentage (default: 2%).
For short positions, it sets an exit order when the price falls by a similar percentage.
Alerts:
The script is equipped with alert conditions. Traders receive notifications whenever a buy or sell signal is generated, helping them stay on top of potential trading opportunities.
Customization
User Inputs:
Traders can adjust:
The number of Fibonacci elements for each average calculation.
Profit target percentages for both long and short positions.
Data Length Requirement:
The script ensures it uses at least 200 data points (or the total number of available bars, whichever is greater) for a robust calculation of the averages.
In Summary
The Grease Trap V1.0 indicator combines the mathematical elegance of Fibonacci sequences with dynamic grouped averaging. It offers:
Innovative Moving Averages: Based on Fibonacci groupings of historical price data.
Clear Visual Cues: Through color-coded lines and crossover dots.
Automated Trading Actions: With built-in order management and profit targets.
Alert Notifications: So traders are instantly aware of key market signals.
This makes the Grease Trap V1.0 a comprehensive tool for both signal generation and automated strategy execution, suitable for traders looking to integrate Fibonacci principles into their trading systems.
