Donchian Breakout Strategy📈 Donchian Breakout Strategy (Inspired by Way of the Turtle)
This strategy is a modern adaptation of the legendary Turtle Trading system as taught in Way of the Turtle by Curtis Faith — re-engineered for the crypto market’s volatility, 24/7 nature, and frequent fakeouts.
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🐢 Original Inspiration
The original Turtle system, created by Richard Dennis and William Eckhardt, used:
• Breakouts of Donchian Channels (20-day for entry, 10-day for exit)
• Volatility-based position sizing using ATR (N)
• Simple rules, big trend exposure, and pyramiding to grow winners
It was built for futures and commodities, trading daily bars, assuming stable trading hours and regulated markets.
⸻
🚀 What’s Different in This Strategy?
✅ Optimized for Crypto
• Adapts to constant volatility and price manipulation common in crypto
• Adds commission modeling for realistic results (0.045% default)
✅ Improved Entry Filtering
• Uses EMA filter to align with trend direction
• Adds RSI momentum check to avoid early or weak breakouts
• Optional volatility and volume filters to reduce false signals
✅ Smarter Exits
• ATR-based volatility stop loss, not just Donchian reversal
• Avoids pyramiding to reduce risk from sudden reversals
✅ Backtest-Friendly
• Default backtest window starts from 2025-01-01
• Fully configurable: long/short toggle, filter control, stop loss multiplier
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🧪 Use Case
• Best on trending coins with strong directional moves
• Avoids chop via filters, preserving capital
• Can be tuned for aggressive or conservative setups with just a few tweaks
Cerca negli script per "momentum"
Z-Score Normalized VIX StrategyThis strategy leverages the concept of the Z-score applied to multiple VIX-based volatility indices, specifically designed to capture market reversals based on the normalization of volatility. The strategy takes advantage of VIX-related indicators to measure extreme levels of market fear or greed and adjusts its position accordingly.
1. Overview of the Z-Score Methodology
The Z-score is a statistical measure that describes the position of a value relative to the mean of a distribution in terms of standard deviations. In this strategy, the Z-score is calculated for various volatility indices to assess how far their values are from their historical averages, thus normalizing volatility levels. The Z-score is calculated as follows:
Z = \frac{X - \mu}{\sigma}
Where:
• X is the current value of the volatility index.
• \mu is the mean of the index over a specified period.
• \sigma is the standard deviation of the index over the same period.
This measure tells us how many standard deviations the current value of the index is away from its average, indicating whether the market is experiencing unusually high or low volatility (fear or calm).
2. VIX Indices Used in the Strategy
The strategy utilizes four commonly referenced volatility indices:
• VIX (CBOE Volatility Index): Measures the market’s expectations of 30-day volatility based on S&P 500 options.
• VIX3M (3-Month VIX): Reflects expectations of volatility over the next three months.
• VIX9D (9-Day VIX): Reflects shorter-term volatility expectations.
• VVIX (VIX of VIX): Measures the volatility of the VIX itself, indicating the level of uncertainty in the volatility index.
These indices provide a comprehensive view of the current volatility landscape across different time horizons.
3. Strategy Logic
The strategy follows a long entry condition and an exit condition based on the combined Z-score of the selected volatility indices:
• Long Entry Condition: The strategy enters a long position when the combined Z-score of the selected VIX indices falls below a user-defined threshold, indicating an abnormally low level of volatility (suggesting a potential market bottom and a bullish reversal). The threshold is set as a negative value (e.g., -1), where a more negative Z-score implies greater deviation below the mean.
• Exit Condition: The strategy exits the long position when the combined Z-score exceeds the threshold (i.e., when the market volatility increases above the threshold, indicating a shift in market sentiment and reduced likelihood of continued upward momentum).
4. User Inputs
• Z-Score Lookback Period: The user can adjust the lookback period for calculating the Z-score (e.g., 6 periods).
• Z-Score Threshold: A customizable threshold value to define when the market has reached an extreme volatility level, triggering entries and exits.
The strategy also allows users to select which VIX indices to use, with checkboxes to enable or disable each index in the calculation of the combined Z-score.
5. Trade Execution Parameters
• Initial Capital: The strategy assumes an initial capital of $20,000.
• Pyramiding: The strategy does not allow pyramiding (multiple positions in the same direction).
• Commission and Slippage: The commission is set at $0.05 per contract, and slippage is set at 1 tick.
6. Statistical Basis of the Z-Score Approach
The Z-score methodology is a standard technique in statistics and finance, commonly used in risk management and for identifying outliers or unusual events. According to Dumas, Fleming, and Whaley (1998), volatility indices like the VIX serve as a useful proxy for market sentiment, particularly during periods of high uncertainty. By calculating the Z-score, we normalize volatility and quantify the degree to which the current volatility deviates from historical norms, allowing for systematic entry and exit based on these deviations.
7. Implications of the Strategy
This strategy aims to exploit market conditions where volatility has deviated significantly from its historical mean. When the Z-score falls below the threshold, it suggests that the market has become excessively calm, potentially indicating an overreaction to past market events. Entering long positions under such conditions could capture market reversals as fear subsides and volatility normalizes. Conversely, when the Z-score rises above the threshold, it signals increased volatility, which could be indicative of a bearish shift in the market, prompting an exit from the position.
By applying this Z-score normalized approach, the strategy seeks to achieve more consistent entry and exit points by reducing reliance on subjective interpretation of market conditions.
8. Scientific Sources
• Dumas, B., Fleming, J., & Whaley, R. (1998). “Implied Volatility Functions: Empirical Tests”. The Journal of Finance, 53(6), 2059-2106. This paper discusses the use of volatility indices and their empirical behavior, providing context for volatility-based strategies.
• Black, F., & Scholes, M. (1973). “The Pricing of Options and Corporate Liabilities”. Journal of Political Economy, 81(3), 637-654. The original Black-Scholes model, which forms the basis for many volatility-related strategies.
EMA Crossover (Short Focus with Trailing Stop)This strategy utilizes a combination of Exponential Moving Averages (EMA) and Simple Moving Averages (SMA) to generate entry and exit signals for both long and short positions. The core of the strategy is based on the 13-period EMA (short EMA) crossing the 33-period EMA (long EMA) for entering long trades, while a 13-period EMA crossing the 25-period EMA (mid EMA) generates short trade signals. The 100-period SMA and 200-period SMA serve as additional trend indicators to provide context for the market conditions. The strategy aims to capitalize on trend reversals and momentum shifts in the market.
The strategy is designed to execute trades swiftly with an emphasis on entering positions when conditions align in real time. For long entries, the strategy initiates a buy when the 13 EMA is greater than the 33 EMA, indicating a bullish trend. For short entries, the 13 EMA crossing below the 33 EMA signals a bearish trend, prompting a short position. Importantly, the code includes built-in exit conditions for both long and short positions. Long positions are exited when the 13 EMA falls below the 33 EMA, while short positions are closed when the 13 EMA crosses above the 25 EMA.
A key feature of the strategy is the use of trailing stops for both long and short positions. This dynamic exit method adjusts the stop level as the market moves in favor of the trade, locking in profits while reducing the risk of losses. The trailing stop for long positions is based on the high price of the current bar, while the trailing stop for short positions is set using the low price, providing more flexibility in managing risk. This trailing stop mechanism helps to capture profits from favorable market moves while ensuring that positions are exited if the market moves against them.
This strategy works best on the daily timeframe and is optimized for major cryptocurrency pairs. The daily chart allows for the EMAs to provide more reliable signals, as the strategy is designed to capture broader trends rather than short-term market fluctuations. Using it on major crypto pairs increases its effectiveness as these assets tend to have strong and sustained trends, providing better opportunities for the strategy to perform well.
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.
FUMO GHOST V1.1FUMO GHOST V1.0 is a high-precision trend-following strategy that identifies explosive price continuations using EMA + Supertrend logic, filtered through Heikin Ashi confirmation candles.
This strategy is designed to operate across timeframes — from scalping (1M) to swing trading (1H+) — using adaptive auto-settings for sensitivity.
It’s built to be minimal, efficient, and bold — just like the #FUMO mindset.
🔍 Core Logic:
Supertrend (ATR-based) defines trend direction
EMA is used as a momentum baseline
Heikin Ashi logic filters entries:
Long: price above EMA, trend up, HA candle strong (open == low)
Short: price below EMA, trend down, HA candle weak (open == high)
Exit: triggered automatically on Supertrend reversal
This system is designed to stay in the trend as long as it’s valid — no scalping in/out or rapid re-entries.
⚙ Strategy Settings:
Auto-adjusts EMA & ATR parameters by timeframe (1M to 1D)
Manual override available (use_custom = true)
“Silent Mode” hides all visuals for minimal charting
Uses internal Heikin Ashi logic, regardless of visible candles
🧪 Backtest Notes:
Backtest is powered by TradingView’s built-in strategy() engine
Default risk: 10% equity per trade
For accurate simulation, enable “Use standard OHLC” in strategy settings — this ensures reliable backtest when internal Heikin Ashi logic is used
🔒 Why is the code protected?
This script uses:
A unique combination of Supertrend + EMA + Heikin Ashi filters
Internal timeframe-aware parameter scaling
Logic tuned specifically for explosive trend continuations
While freely available for public use, the source code is closed to protect the inner mechanism and prevent reverse engineering.
FUMO GHOST V1.0 is built for clarity, conviction, and confidence.
Make your next trade bold.
Make Fuck U Money — 24/7.
LUX CLARA - EMA + VWAP (No ATR Filter) - v6EMA STRAT SHOUT OUTOUTLIERSSSSS
Overview:
an intraday strategy built around two core principles:
Trend Confirmation using the 50 EMA (Exponential Moving Average) in relation to the VWAP (Volume-Weighted Average Price).
Entry Signals triggered by the 8 EMA crossing the 50 EMA in the direction of that confirmed trend.
Key Logic:
Bullish Trend if the 50 EMA is above VWAP. Only long entries are allowed when the 8 EMA crosses above the 50 EMA during that bullish phase.
Bearish Trend if the 50 EMA is below VWAP. Only short entries are allowed when the 8 EMA crosses below the 50 EMA during that bearish phase.
Intraday Focus: Trades are restricted to a user-defined session window (default 7:30 AM–11:30 AM), aligning entries/exits with peak intraday liquidity.
Exit Rule: Positions close automatically when the 8 EMA crosses back in the opposite direction of the entry.
Why It Works:
EMA + VWAP helps detect both immediate momentum (EMAs) and overall institutional bias (VWAP).
By confining trades to a set intraday window, the strategy aims to capture morning volatility while avoiding choppy afternoon or overnight sessions.
Customization:
Users can adjust EMA lengths, session times, or incorporate stops/targets for additional risk management.
It can be tested on various symbols and intraday timeframes to gauge performance and robustness.
Smart Grid Scalping (Pullback) Strategy[BullByte]The Smart Grid Scalping (Pullback) Strategy is a high-frequency trading strategy designed for short-term traders who seek to capitalize on market pullbacks. This strategy utilizes a dynamic ATR-based grid system to define optimal entry points, ensuring precise trade execution. It integrates volatility filtering and an RSI-based confirmation mechanism to enhance signal accuracy and reduce false entries.
This strategy is specifically optimized for scalping by dynamically adjusting trade levels based on current market conditions. The grid-based system helps capture retracement opportunities while maintaining strict trade management through predefined profit targets and trailing stop-loss mechanisms.
Key Features :
1. ATR-Based Grid System :
- Uses a 10-period ATR to dynamically calculate grid levels for entry points.
- Prevents chasing trades by ensuring price has reached key levels before executing entries.
2. No Trade Zone Protection :
- Avoids low-volatility zones where price action is indecisive.
- Ensures only high-momentum trades are executed to improve success rate.
3. RSI-Based Entry Confirmation :
- Long trades are triggered when RSI is below 30 (oversold) and price is in the lower grid zone.
- Short trades are triggered when RSI is above 70 (overbought) and price is in the upper grid zone.
4. Automated Trade Execution :
- Long Entry: Triggered when price drops below the first grid level with sufficient volatility.
- Short Entry: Triggered when price exceeds the highest grid level with sufficient volatility.
5. Take Profit & Trailing Stop :
- Profit target set at a customizable percentage (default 0.2%).
- Adaptive trailing stop mechanism using ATR to lock in profits while minimizing premature exits.
6. Visual Trade Annotations :
- Clearly labeled "LONG" and "SHORT" markers appear at trade entries for better visualization.
- Grid levels are plotted dynamically to aid decision-making.
Strategy Logic :
- The script first calculates the ATR-based grid levels and ensures price action has sufficient volatility before allowing trades.
- An additional RSI filter is used to ensure trades are taken at ideal market conditions.
- Once a trade is executed, the script implements a trailing stop and predefined take profit to maximize gains while reducing risks.
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Disclaimer :
Risk Warning :
This strategy is provided for educational and informational purposes only. Trading involves significant risk, and past performance is not indicative of future results. Users are advised to conduct their own due diligence and risk management before using this strategy in live trading.
The developer and publisher of this script are not responsible for any financial losses incurred by the use of this strategy. Market conditions, slippage, and execution quality can affect real-world trading outcomes.
Use this script at your own discretion and always trade responsibly.
Profit Trailing BBandsProfit Trailing Trend BBands v4.7.5 with Double Trailing SL
A TradingView Pine Script Strategy
Created by Kevin Bourn and refined with the help of Grok 3 (xAI)
Overview
Welcome to Profit Trailing Trend BBands v4.7.5, a dynamic trading strategy designed to ride trends and lock in profits with a unique double trailing stop-loss mechanism. Built for TradingView’s Pine Script v6, this strategy combines Bollinger Bands for trend detection with a smart trailing system that doubles down on profit protection. Whether you’re trading XRP or any other asset, this tool aims to maximize gains while keeping risk in check—all with a clean, visual interface.
What It Does
Identifies Trends: Uses Bollinger Bands to spot uptrends (price crossing above the upper band) and downtrends (price crossing below the lower band).
Enters Positions: Opens long or short trades based on trend signals, with customizable position sizing and leverage.
Trails Profits: Employs a two-stage trailing stop-loss:
Initial Trailing SL: Acts as a take-profit level, set as a percentage (%) or dollar ($) distance from the entry price.
Tightened Trailing SL: Once the initial profit target is hit, the stop-loss tightens to half the initial distance, locking in gains as the trend continues.
Manages Risk: Includes a margin call feature to exit losing positions before they blow up your account.
Visualizes Everything: Plots Bollinger Bands (blue upper, orange lower) and a red stepped trailing stop-loss line for easy tracking.
Why Built It?
Captures Trends: Bollinger Bands are a proven way to catch momentum, and we tuned them for responsiveness (short length, moderate multiplier).
Secures Profits: Traditional trailing stops often leave money on the table or exit too early. The double trailing SL first takes a chunk of profit, then tightens up to ride the rest of the move.
Stays Flexible: Traders can tweak price sources, stop-loss types (% or $), and position sizing to fit their style.
Looks Good: Clear visuals help you see the strategy in action without cluttering your chart.
Originally refined for XRP, it’s versatile enough for most markets — crypto, forex, stocks, you name it.
How It Works
Core Components
Bollinger Bands:
Calculated using a simple moving average (SMA) and standard deviation.
Default settings: 6-period length, 1.66 multiplier.
Upper Band (blue): SMA + (1.66 × StdDev).
Lower Band (orange): SMA - (1.66 × StdDev).
Trend signals: Price crossing above the upper band triggers a long, below the lower band triggers a short.
Double Trailing Stop-Loss:
Initial SL: Set via "Trailing Stop-Loss Value" (default 6% or $6). Trails the price at this distance and doubles as the first profit target.
Tightened SL: Once price hits the initial SL distance in profit (e.g., +6%), the SL tightens to half (e.g., 3%) and continues trailing, locking in gains.
Visualized as a red stepped line, only visible during active positions.
Position Sizing:
Choose "% of Equity" (default 30%) or "Amount in $" to set trade size.
Leverage (default 10x) amplifies positions, capped by available equity to avoid overexposure.
Margin Call:
Exits positions if drawdown exceeds the "Margin %" (default 10%) to protect your account.
Backtesting Filter:
Starts trading after a user-defined date (default: Jan 1, 2020) for focused historical analysis.
Trade Logic
Long Entry: Price crosses above the upper Bollinger Band → Closes any short position, opens a long.
Short Entry: Price crosses below the lower Bollinger Band → Closes any long position, opens a short.
Exit: Position closes when price hits the trailing stop-loss or triggers a margin call.
How to Use It
Setup
Add to TradingView:
Open TradingView, go to the Pine Editor, paste the script, and click "Add to Chart."
Ensure you’re using Pine Script v6 (the script includes @version=6).
Configure Inputs:
Start Date for Backtesting: Set the date to begin historical testing (default: Jan 1, 2020).
BB Length & Mult: Adjust Bollinger Band sensitivity (default: 6, 1.66).
BB Price Source: Choose the price for BBands (default: Close).
Trend Price Source: Choose the price for trend detection (default: Close).
Trailing Stop-Loss Type: Pick "%" or "$" (default: Trailing SL %).
Trailing Stop-Loss Value: Set the initial SL distance (default: 6).
Margin %: Define the max drawdown before exit (default: 10%).
Order Size Type & Value: Set position size as % of equity (default: 30%) or $ amount.
Leverage: Adjust leverage (default: 10x).
Run It:
Use the Strategy Tester tab to backtest on your chosen asset and timeframe.
Watch the chart for blue/orange Bollinger Bands and the red trailing SL line.
Tips for Traders
Timeframes: Works on any timeframe, but test 1H or 4H for XRP—great balance of signals and noise.
Assets: Optimized for XRP, but tweak slValue and mult for other markets (e.g., tighter SL for low-volatility pairs).
Risk Management: Keep marginPercent low (5-10%) for volatile assets; adjust leverage based on your risk tolerance.
Visuals: The red stepped SL line shows only during trades—zoom in to see its tightening in action.
Visuals on the Chart
Blue Line: Upper Bollinger Band (trend entry for longs).
Orange Line: Lower Bollinger Band (trend entry for shorts).
Red Stepped Line: Trailing Stop-Loss (shifts tighter after the first profit target).
Order Labels: Short tags like "OL" (Open Long), "CS" (Close Short), "LSL" (Long Stop-Loss), etc., mark trades.
Disclaimer
Trading involves risk. This strategy is for educational and experimental use—backtest thoroughly and use at your own risk. Past performance doesn’t guarantee future results. Not financial advice—just a tool from traders, for traders.
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.
Litecoin Trailing-Stop StrategyAltcoins Trailing-Stop Strategy
This strategy is based on a momentum breakout approach using PKAMA (Powered Kaufman Adaptive Moving Average) as a trend filter, and a delayed trailing stop mechanism to manage risk effectively.
It has been designed and fine-tuned Altcoins, which historically shows consistent volatility patterns and clean trend structures, especially on intraday timeframes like 15m and 30m.
Strategy Logic:
Entry Conditions:
Long when PKAMA indicates an upward move
Short when PKAMA detects a downward trend
Minimum spacing of 30 bars between trades to avoid overtrading
Trailing Stop:
Activated only after a customizable delay (delayBars)
User can set trailing stop % and delay independently
Helps avoid premature exits due to short-term volatility
Customizable Parameters:
This strategy uses a custom implementation of PKAMA (Powered Kaufman Adaptive Moving Average), inspired by the work of alexgrover
PKAMA is a volatility-aware moving average that adjusts dynamically to market conditions, making it ideal for altcoins where trend strength and direction change frequently.
This script is for educational and experimental purposes only. It is not financial advice. Please test thoroughly before using it in live conditions, and always adapt parameters to your specific asset and time frame.
Feedback is welcome! Feel free to clone and adapt it for your own trading style.
02 SMC + BB Breakout (Improved)This strategy combines Smart Money Concepts (SMC) with Bollinger Band breakouts to identify potential trading opportunities. SMC focuses on identifying key price levels and market structure shifts, while Bollinger Bands help pinpoint overbought/oversold conditions and potential breakout points. The strategy also incorporates higher timeframe trend confirmation to filter out trades that go against the prevailing trend.
Key Components:
Bollinger Bands:
Calculated using a Simple Moving Average (SMA) of the closing price and a standard deviation multiplier.
The strategy uses the upper and lower bands to identify potential breakout points.
The SMA (basis) acts as a centerline and potential support/resistance level.
The fill between the upper and lower bands can be toggled by the user.
Higher Timeframe Trend Confirmation:
The strategy allows for optional confirmation of the current trend using a higher timeframe (e.g., daily).
It calculates the SMA of the higher timeframe's closing prices.
A bullish trend is confirmed if the higher timeframe's closing price is above its SMA.
This helps filter out trades that go against the prevailing long-term trend.
Smart Money Concepts (SMC):
Order Blocks:
Simplified as recent price clusters, identified by the highest high and lowest low over a specified lookback period.
These levels are considered potential areas of support or resistance.
Liquidity Zones (Swing Highs/Lows):
Identified by recent swing highs and lows, indicating areas where liquidity may be present.
The Swing highs and lows are calculated based on user defined lookback periods.
Market Structure Shift (MSS):
Identifies potential changes in market structure.
A bullish MSS occurs when the closing price breaks above a previous swing high.
A bearish MSS occurs when the closing price breaks below a previous swing low.
The swing high and low values used for the MSS are calculated based on the user defined swing length.
Entry Conditions:
Long Entry:
The closing price crosses above the upper Bollinger Band.
If higher timeframe confirmation is enabled, the higher timeframe trend must be bullish.
A bullish MSS must have occurred.
Short Entry:
The closing price crosses below the lower Bollinger Band.
If higher timeframe confirmation is enabled, the higher timeframe trend must be bearish.
A bearish MSS must have occurred.
Exit Conditions:
Long Exit:
The closing price crosses below the Bollinger Band basis.
Or the Closing price falls below 99% of the order block low.
Short Exit:
The closing price crosses above the Bollinger Band basis.
Or the closing price rises above 101% of the order block high.
Position Sizing:
The strategy calculates the position size based on a fixed percentage (5%) of the strategy's equity.
This helps manage risk by limiting the potential loss per trade.
Visualizations:
Bollinger Bands (upper, lower, and basis) are plotted on the chart.
SMC elements (order blocks, swing highs/lows) are plotted as lines, with user-adjustable visibility.
Entry and exit signals are plotted as shapes on the chart.
The Bollinger band fill opacity is adjustable by the user.
Trading Logic:
The strategy aims to capitalize on Bollinger Band breakouts that are confirmed by SMC signals and higher timeframe trend. It looks for breakouts that align with potential market structure shifts and key price levels (order blocks, swing highs/lows). The higher timeframe filter helps avoid trades that go against the overall trend.
In essence, the strategy attempts to identify high-probability breakout trades by combining momentum (Bollinger Bands) with structural analysis (SMC) and trend confirmation.
Key User-Adjustable Parameters:
Bollinger Bands Length
Standard Deviation Multiplier
Higher Timeframe
Higher Timeframe Confirmation (on/off)
SMC Elements Visibility (on/off)
Order block lookback length.
Swing lookback length.
Bollinger band fill opacity.
This detailed description should provide a comprehensive understanding of the strategy's logic and components.
***DISCLAIMER: This strategy is for educational purposes only. It is not financial advice. Past performance is not indicative of future results. Use at your own risk. Always perform thorough backtesting and forward testing before using any strategy in live trading.***
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!
EMA 10/55/200 - LONG ONLY MTF (4h with 1D & 1W confirmation)Title: EMA 10/55/200 - Long Only Multi-Timeframe Strategy (4h with 1D & 1W confirmation)
Description:
This strategy is designed for trend-following long entries using a combination of exponential moving averages (EMAs) on the 4-hour chart, confirmed by higher timeframe trends from the daily (1D) and weekly (1W) charts.
🔍 How It Works
🔹 Entry Conditions (4h chart):
EMA 10 crosses above EMA 55 and price is above EMA 55
OR
EMA 55 crosses above EMA 200
OR
EMA 10 crosses above EMA 500
These entries indicate short-term momentum aligning with medium/long-term trend strength.
🔹 Confirmation (multi-timeframe alignment):
Daily (1D): EMA 55 is above EMA 200
Weekly (1W): EMA 55 is above EMA 200
This ensures that we only enter long trades when the higher timeframes support an uptrend, reducing false signals during sideways or bearish markets.
🛑 Exit Conditions
Bearish crossover of EMA 10 below EMA 200 or EMA 500
Stop Loss: 5% below entry price
⚙️ Backtest Settings
Capital allocation per trade: 10% of equity
Commission: 0.1%
Slippage: 2 ticks
These are realistic conditions for crypto, forex, and stocks.
📈 Best Used On
Timeframe: 4h
Instruments: Trending markets like BTC/ETH, FX majors, or growth stocks
Works best in volatile or trending environments
⚠️ Disclaimer
This is a backtest tool and educational resource. Always validate on demo accounts before applying to real capital. Do your own due diligence.
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.
ThinkTech AI SignalsThink Tech AI Strategy
The Think Tech AI Strategy provides a structured approach to trading by integrating liquidity-based entries, ATR volatility thresholds, and dynamic risk management. This strategy generates buy and sell signals while automatically calculating take profit and stop loss levels, boasting a 64% win rate based on historical data.
Usage
The strategy can be used to identify key breakout and retest opportunities. Liquidity-based zones act as potential accumulation and distribution areas and may serve as future support or resistance levels. Buy and sell zones are identified using liquidity zones and ATR-based filters. Risk management is built-in, automatically calculating take profit and stop loss levels using ATR multipliers. Volume and trend filtering options help confirm directional bias using a 50 EMA and RSI filter. The strategy also allows for session-based trading, limiting trades to key market hours for higher probability setups.
Settings
The risk/reward ratio can be adjusted to define the desired stop loss and take profit calculations. The ATR length and threshold determine ATR-based breakout conditions for dynamic entries. Liquidity period settings allow for customized analysis of price structure for support and resistance zones. Additional trend and RSI filters can be enabled to refine trade signals based on moving averages and momentum conditions. A session filter is included to restrict trade signals to specific market hours.
Style
The strategy includes options to display liquidity lines, showing key support and resistance areas. The first 15-minute candle breakout zones can also be visualized to highlight critical market structure points. A win/loss statistics table is included to track trade performance directly on the chart.
This strategy is intended for descriptive analysis and should be used alongside other confluence factors. Optimize your trading process with Think Tech AI today!
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
Maxima MAX1📌 Overview:
This strategy is a Simple Moving Average (SMA) Crossover system with an optional Relative Strength Index (RSI) filter for better trade confirmation. It allows traders to customize key parameters and backtest results within a specific date range.
📊 How It Works:
✅ Entry Conditions:
The closing price must be above both the Fast SMA and Slow SMA.
(Optional) RSI must be above a threshold (default: 50) for additional confirmation.
❌ Exit Condition:
The closing price drops below the Fast SMA, signaling an exit.
🔧 Customizable Inputs:
SMA Lengths: Adjust both Fast and Slow SMA values.
RSI Filter: Enable/disable RSI confirmation with a custom length & threshold.
Backtest Date Range: Choose a start and end date for testing historical performance.
🚀 Why Use This Strategy?
✔ Ideal for trend-following traders looking for momentum-based entries.
✔ Provides an additional RSI filter to reduce false signals.
✔ Helps traders refine their strategy by testing different parameters.
📢 How to Use:
1️⃣ Customize the SMA lengths, RSI settings, and date range.
2️⃣ Enable/Disable the RSI filter as needed.
3️⃣ Analyze historical performance and optimize for different markets.
⚠ Disclaimer:
This strategy is for educational purposes only. Always backtest thoroughly before using it in live trading.
MACD Crossover Strategy MACD Crossover Strategy:
This strategy is based on the Moving Average Convergence Divergence (MACD) indicator, a popular tool used in technical analysis to identify potential trend changes and momentum in price movements. The strategy focuses on MACD crossovers within a specific "important zone" to generate trading signals.
Key Components:
1. MACD Calculation: The strategy uses customizable parameters for fast length (default 12), slow length (default 26), and signal length (default 9) to calculate the MACD line and signal line.
2. Important Zone: Defined by upper and lower thresholds (default 0.5 and -0.5), this zone helps filter out potentially less significant crossovers.
3. Entry Conditions:
- Long (Buy) Entry: When the MACD line crosses above the signal line within the important zone.
- Short (Sell) Entry: When the MACD line crosses below the signal line within the important zone.
4. Exit Conditions: The strategy closes positions on opposite crossover signals. Long positions are closed on bearish crossovers, and short positions on bullish crossovers.
5. Visualization:
- MACD line (blue) and signal line (orange) are plotted.
- The zero line, upper threshold, and lower threshold are displayed for reference.
- Buy signals are represented by green triangles at the bottom of the chart.
- Sell signals are shown as red triangles at the top of the chart.
This strategy aims to capture trend changes while filtering out potentially false signals that occur when the MACD is at extreme values. By focusing on crossovers within the important zone, the strategy attempts to identify more reliable trading opportunities.
Traders can adjust the MACD parameters and the important zone thresholds to fine-tune the strategy for different assets or timeframes. As with any trading strategy, it's crucial to thoroughly backtest and consider risk management before using it in live trading.
Double Bollinger Bands Strategy with Signals (By Rolwin)Double Bollinger Bands Strategy with Signals 1.0 (By Rolwin)
📌 Overview
The Double Bollinger Bands Strategy is a trend-following system that utilizes two sets of Bollinger Bands (2 standard deviations and 3 standard deviations) to identify high-probability entry and exit points. This strategy helps traders capitalize on strong price movements and potential reversals by detecting overbought and oversold conditions more effectively.
📊 How It Works
• Bollinger Bands Setup:
o Middle Band: 20-period Simple Moving Average (SMA)
o Upper & Lower Bands (2 SD): Standard Bollinger Bands (±2 standard deviations)
o Extreme Bands (3 SD): Additional Bollinger Bands (±3 standard deviations) for extreme price moves
• Entry Signals:
✅ Buy (Long Entry): When the price crosses above the lower 3SD band (oversold zone)
❌ Sell (Short Entry): When the price crosses below the upper 3SD band (overbought zone)
• Exit Signals:
🔼 Exit Long: When the price reaches the upper 2SD band
🔽 Exit Short: When the price reaches the lower 2SD band
• Additional Features:
✅ Buy & Sell Signals plotted directly on the chart
🎨 Candles turn white when price touches the extreme 3SD band
🔥 Why Use This Strategy?
✔️ Clear Entry & Exit Points: Based on strong statistical levels
✔️ Effective in Trending & Reversal Markets: Captures both momentum & mean reversion setups
✔️ Easy-to-Use Visualization: Signals & bands make it beginner-friendly
✔️ Customizable: Adjust Bollinger Band length and multipliers to fit different assets & timeframes
⚠️ Risk Management Tip
While this strategy provides high-probability trade signals, it is essential to use stop-loss orders (e.g., ATR-based) and proper position sizing to manage risk effectively.
📈 Try it out and optimize the settings for your favorite markets! 🚀
FVG Breakout Lite by tradingbauhausExplanation of "FVG Breakout Lite by tradingbauhaus"
This script is a trading strategy built for TradingView that helps you spot and trade "Fair Value Gaps" (FVGs)—price areas where the market moved quickly, leaving a gap that might act as support or resistance later. It’s designed to catch breakout opportunities when the price moves strongly in one direction, with extra filters to make trades more reliable. Here’s how it works and how you can use it:
What It Does
1. Finds Fair Value Gaps (FVGs):
A "Bullish FVG" happens when the price jumps up quickly, leaving a gap below where it didn’t trade much (e.g., today’s low is higher than the high from two bars ago).
A "Bearish FVG" is the opposite: the price drops fast, leaving a gap above (e.g., today’s high is lower than the low from two bars ago).
The script draws colored boxes on your chart to show these gaps: green for bullish, red for bearish.
2. Spots Breakouts:
It looks for "strong" FVGs by comparing them to a trend (based on the highest highs and lowest lows over a set period).
If a bullish gap forms above the recent highs, or a bearish gap below the recent lows, it’s marked as a breakout opportunity.
3. Adds a Volume Check:
Trades only happen if the market’s volume is higher than usual (e.g., 1.2x the average volume over the last 20 bars). This helps ensure the breakout has real momentum behind it.
4. Trades Automatically:
Long Trades (Buy): If a bullish breakout FVG forms and volume is high, it buys at the current price.
Short Trades (Sell): If a bearish breakout FVG forms with high volume, it sells short.
Each trade comes with a stop loss (to limit losses) and a take profit (to lock in gains), both adjustable by you.
5. Shows Mitigation Lines (Optional):
If you turn on "Display Mitigation Zones," it draws lines at the edge of each breakout FVG. These lines show where the price might return to "fill" the gap later, helping you see key levels.
6. Includes Webull Costs:
The script factors in real trading fees from Webull, like tiny SEC and FINRA fees for selling, and a daily margin cost if you’re borrowing money to trade. These don’t show up on the chart but affect the strategy’s performance in backtesting.
How to Use It
1. Add to Your Chart:
Copy the script into TradingView’s Pine Editor, click "Add to Chart," and it’ll start drawing FVGs and running the strategy.
2. Customize Settings:
Trend Period (Default: 25): How many bars it looks back to define the trend. Longer periods mean fewer but stronger signals.
Volume Lookback (Default: 20) & Volume Threshold (Default: 1.2): Adjust how it measures "high volume." Increase the threshold for stricter trades.
Stop Loss % (Default: 1.5%) & Take Profit % (Default: 3%): Set how much you’re willing to lose or aim to gain per trade.
Margin Rate % (Default: 8.74%): Webull’s rate for borrowing money—lower it if your account qualifies for a better rate.
Display Mitigation Zones (Default: On): Toggle this to see or hide the gap lines.
Colors: Change the green (bullish) and red (bearish) shades to suit your chart.
3. Backtest It:
Go to the "Strategy Tester" tab in TradingView to see how it performs on past data. It’ll show trades, profits, losses, and Webull fees included.
4. Watch It Work:
Green boxes mean bullish FVGs; red boxes mean bearish FVGs. If volume spikes and the price breaks out, you’ll see trades happen automatically.
What to Expect
Visuals: You’ll see colored boxes for FVGs and optional lines showing where they start. These help you spot key price zones even if you’re not trading.
Trades: It’s selective—only trades when FVGs align with a breakout and volume confirms it. Expect fewer trades but with higher potential.
Risk: The stop loss keeps losses in check, while the take profit aims for a 2:1 reward-to-risk ratio by default (3% gain vs. 1.5% loss).
Costs: Webull’s fees are small but baked into the results, so you’re seeing a realistic picture of profits.
Tips for Users
Test it on a small timeframe (like 5-minute charts) for day trading or a larger one (like daily) for swing trading.
Play with the volume threshold—if you get too few trades, lower it (e.g., 1.1); if too many, raise it (e.g., 1.5).
Watch how price reacts to the mitigation lines—they’re often support or resistance zones traders target.
This strategy is lightweight, focused, and built for traders who like breakouts with a bit of confirmation. It’s not foolproof (no strategy is!), but it gives you a clear way to trade FVGs with some smart filters.
Slark Signal XtremeStrategy Description: Slark Signal Xtreme
The Slark Signal Xtreme is an innovative trading strategy designed to identify and capitalize on market opportunities by leveraging pivots, trend breakouts, and dynamic risk management. This strategy combines day-of-week and time filters with a ticks-based Stop Loss (SL) and Take Profit (TP) system, delivering customized signals and real-time alerts. Ideal for traders seeking a structured and highly customizable approach, Slark Signal Xtreme also incorporates advanced visual tools for efficient trade management.
Key Features:
Pivot- and Breakout-Based Signals: Utilizes pivot detection (highs/lows) combined with an ATR-based slope calculation to pinpoint trend changes and potential entry or exit points.
Dynamic Stop-Loss (SL) and Take-Profit (TP) Levels: Automatically calculates SL and TP based on the entry price and user-defined tick settings, adapting to volatility and optimizing risk management.
Time and Day Filters: Allows you to select specific days of the week and trading sessions during which signals are generated, avoiding low-liquidity periods or unwanted high volatility.
Customizable Risk Management: Lets you define the number of ticks for SL and TP, trading hours, initial capital, pyramiding, and commissions, tailoring the strategy to various risk profiles and assets.
Enhanced Visualization:
- SL and TP Boxes: Displays rectangular boxes on the chart indicating SL and TP levels, streamlining trade management.
- Candle Color Changes: Candles can be colored according to price position relative to pivot lines (bullish, bearish, or neutral).
- Session Highlight: Shades the chart background during the selected trading hours, providing immediate context on when the strategy is active.
Automated Alerts: Generates customizable alerts in TradingView whenever a buy or sell signal is triggered, detailing the timing, instrument, and SL/TP levels.
How the Strategy Works:
Technical Indicator Calculations:
- Pivot High/Low and Slope: Identifies price pivot points and calculates slope (based on ATR) to measure trend strength.
- Time and Day Filters: Signals only trigger within the specified days and hours, helping avoid undesirable market conditions.
Generating Buy and Sell Signals:
- Buy Signal (Long): Activated when price breaks above a downward pivot-based trendline or meets the condition for higher pivots.
- Sell Signal (Short): Activated when price breaks below an upward pivot-based trendline or meets the condition for lower pivots.
- Operation Conditions: Signals are only generated on selected days and during chosen trading hours, avoiding periods of low liquidity or excessive volatility.
Dynamic SL and TP Calculation:
- Stop-Loss (SL) and Take-Profit (TP): Determined by the entry price ± a user-defined number of ticks.
- SL and TP Visualization: Boxes are drawn on the chart from the entry price to SL/TP levels, enabling clear visual reference for trade management.
Order Execution and Alerts:
- Order Execution: When a signal is generated, Slark Signal Xtreme automatically opens a long or short position in TradingView’s backtesting environment.
- Alerts: Customizable alerts can be set up to provide real-time notifications (via TradingView or third-party integrations), offering essential details like instrument, time, SL/TP, etc.
Trade Management and Monitoring:
- Automatic Closure: Each trade is automatically closed upon reaching its SL or TP, ensuring disciplined risk control.
- Trade Summary: TradingView’s built-in reporting tools list all trades with cumulative results, simplifying performance evaluation.
Additional Visualization:
- Candle Coloring by Trend: Candles can be colored bullish, bearish, or neutral based on the pivot-driven trend detection.
- Operational Range Highlighting: The chart background is shaded during the permitted trading hours, clarifying when the strategy is active and enhancing visibility.
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Strategy Properties (Important)
This backtest was conducted in TradingView under the following configuration:
Initial Capital: 1000 USD
Order Size: 10,000 contracts (adjust according to the traded asset)
Commission: 0.05 USD per order
Slippage: 1 tick
Pyramiding: 1 order
Price Verification for Limit Orders: 0 ticks
Recalculate on Every Tick & On Bar Close: Enabled
Bar Magnifier for Backtesting Precision: Enabled
These properties provide a realistic view of the strategy’s performance. However, default parameters may vary depending on each user or market:
Order Size: Should be calculated according to the asset traded and your desired risk level.
Commission and Slippage: Costs can vary by market and instrument; there is no universal default that guarantees realistic results.
All users are strongly recommended to adjust these properties within the script settings to match their own trading accounts and platforms, ensuring the most accurate backtest results.
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Backtesting Results:
- Net Profit: +28.70
- Total Trades: 397
- Winning Trades: 138
- Win Rate: 34.76%
- Profit Factor: 1.07
- Sharpe Ratio: 1.25
- Sortino Ratio: 1.45
- Average Bars per Trade: 24
- Average Profit per Trade: 1.45
These numbers provide an overview of the strategy’s historical performance, demonstrating its potential for profitability given appropriate risk management.
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Interpretation of Results:
- The strategy can be profitable despite a relatively modest win rate, thanks to a suitable risk-reward ratio.
- A profit factor of 1.07 indicates that total profits slightly exceed total losses.
- It is essential to monitor drawdown and ensure it aligns with your personal risk tolerance.
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Risk Warning:
Trading leveraged financial instruments carries a high level of risk and may not be suitable for all investors. Before trading, carefully consider your investment objectives, experience level, and risk tolerance. Past performance does not guarantee future results. Always perform additional testing and adjust the strategy to your specific needs.
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What Makes This Strategy Original?
Focus on Pivots and Time/Day Filters: Rather than purely relying on momentum indicators, Slark Signal Xtreme uses pivot-based signals and scheduling filters to capture higher-liquidity, directional market moves.
Dynamic Risk Management: Ticks-based SL/TP and customizable trading sessions enable precise adaptation to various markets and trading styles.
Advanced Visualization Tools: SL/TP boxes, candle coloring, and session highlights streamline market interpretation and facilitate real-time decision-making.
Seamless Alert Integration: Although native TradingView alerts are provided, it can be integrated with third-party messaging services (Telegram, Discord, etc.) for enhanced automation.
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Additional Considerations
Continuous Testing and Optimization: Regularly backtest and fine-tune parameters (SL, TP, time filters, etc.) to accommodate changing market conditions.
Complementary Analysis: Combine this strategy with other technical or fundamental tools to confirm signals.
Rigorous Risk Management: Ensure SL/TP levels and position sizes conform to your overall risk management plan.
Updates and Support: Future updates and improvements may be released based on community feedback. For questions or suggestions, feel free to reach out.
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Example Configuration
Assume you want to run Slark Signal Xtreme with these settings:
Trading Days: Monday to Friday
Trading Hours: 8:00 to 11:00 (exchange or broker time)
Stop Loss (SL) in Ticks: 100
Take Profit (TP) in Ticks: 300
SL/TP Box Extension: 20 bars
Initial Capital: 1000 USD
Risk per Trade: 1% of capital
Commissions & Slippage: 0.05 USD commission, 1 tick slippage
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Conclusion
The Slark Signal Xtreme strategy delivers a robust and adaptable solution by merging pivots, time/day filters, flexible risk parameters, and advanced visualization. Its distinctive and customizable design makes it a powerful resource for traders aiming to diversify their methods and exploit trend breakouts under specific conditions. Fully compatible with TradingView, Slark Signal Xtreme can enhance your trading toolkit and foster a more systematic approach to your operations.
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Final Disclaimer:
Financial markets are inherently volatile and pose significant risks. This strategy should be employed as part of a comprehensive trading plan and does not guarantee positive outcomes. Always consult a qualified financial advisor before making investment decisions. The use of Slark Signal Xtreme is solely at the user’s discretion, who must evaluate personal risk tolerance and financial objectives.
ChronoSync | QuantEdgeB Introducing ChronoSync by QuantEdgeB
🛠️ Overview
ChronoSync is a multi-layered universal strategy designed for adaptability across various assets, timeframes, and market conditions. By integrating five high-quality indicators, it generates a dynamic, aggregated signal that enhances decision-making and optimizes performance in trending and mean-reverting environments.
📊 Key Strengths
✔️ Multi-indicator fusion for enhanced accuracy
✔️ Built-in adaptive filtering techniques
✔️ Works across varied market regimes
✔️ Provides quantifiable, rule-based signals
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✨ Key Features
🔹 Universal Signal Aggregation
Combines five complementary indicators to form a balanced, adaptive signal, ensuring robust performance across different market conditions.
🔹 Advanced Filtering Techniques
Utilizes Gaussian smoothing, average true range and standard deviation filtering, indicator normalization, and other non-lagging filters to refine trend detection and minimize noise.
🔹 Dynamic Market Adaptation
Employs percentile-based filtering and normalization techniques, allowing it to adjust dynamically to volatility shifts.
🔹 Modular & Customizable
Each indicator can be toggled independently, allowing traders to fine-tune the strategy based on their specific market outlook.
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📊 How It Works & Signal Generation
⚙ Multi-Layer Signal Aggregation: ChronoSync calculates individual trend signals from five indicators, combining their outputs into a Final Strategy Score to determine trade signals.
✅ Long Entry: Triggered when the aggregated final score surpasses the long threshold
❌ Short Entry (Cash Mode): Triggered when the final signal falls below the short threshold
🎨 Color Visualization: Changes dynamically to reflect market conditions
🔹 Volatility Adaptable: Traders can adjust the long and short signal thresholds to fine-tune sensitivity to volatility—wider thresholds reduce false signals in choppy markets, while narrower thresholds increase responsiveness in high-momentum trends.
🖥️ Dashboard & Signal Display:
• Displays individual indicator values and final aggregation score
• Signals (Long / Cash) appear directly on the chart when the label display is turned on
• Customizable visual settings to match user preferences
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👥 Who is this for?
✔ Swing & Medium-Term Traders → Ideal for multi-day to multi-week trades.
✔Long-Term Investors & Trend Followers – Designed for traders and investors with a months-to-years horizon who seek to capture market trends on a cycle basis.
✔ Quantitative Traders → Structured, rules-based approach for systematic execution
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📊 Expanded Explanation : How the Five Indicators Work Together in ChronoSync
The ChronoSync strategy is built upon five carefully selected indicators, each fulfilling a crucial role in trend detection, volatility adaptation, and signal refinement. The synergy between these components ensures that signals are both robust and adaptable to different market conditions.
🔗 The Five-Indicator Synergy
Each indicator plays a specific role in the trend-following system, working together to enhance the strength, reliability, and adaptability of trade signals:
1️⃣ VIDYA ATR Gaussian Filter → Noise-Reduced Trend Detection
✔ What it Does:
The VIDYA ATR Gaussian Filter combines a volatility-adjusted moving average (VIDYA) with Gaussian smoothing to enhance trend clarity while minimizing market noise.
✔ Why It's Important:
• VIDYA dynamically adjusts to price fluctuations, ensuring smoother trend signals.
• Gaussian filtering eliminates erratic price movements that could otherwise trigger false entries/exits.
• By applying ATR filtering, the indicator remains adaptive to different volatility environments.
✔ How It Works With Others:
• Works in tandem with Kijun ATR & Dual SD Kijun to confirm long-term price trends while filtering out market noise.
• Enhances signal stability by reducing whipsaws in choppy conditions.
2️⃣ Kijun ATR & Dual SD Kijun → Trend Confirmation & Volatility Filtering
✔ What it Does:
The Kijun ATR and Dual SD Kijun components combine trend structure with volatility adjustments to capture sustained price moves.
✔ Why It's Important:
• The Kijun ATR dynamically adjusts to price swings, allowing the system to filter out market noise and identify valid breakout conditions.
• The Dual SD Kijun introduces an extra layer of confirmation by incorporating a standard deviation-based volatility filter to assess trend strength.
✔ How It Works With Others:
• Confirms trends initiated by VIDYA ATR Gaussian Filter, ensuring signals are based on structural price movements rather than short-term fluctuations.
• Complements PRC-ALMA Adaptive Bands in detecting price deviations and trend shifts.
3️⃣ VIDYA Loop Function → Iterative Trend Reinforcement
✔ What it Does:
The VIDYA Loop Function applies a recursive method to track sustained trends, using a loop-based iterative calculation.
✔ Why It's Important:
• Identifies persistent trends by aggregating historical VIDYA changes over a defined loop window.
• Helps eliminate short-lived price movements by smoothing trend signals over time.
✔ How It Works With Others:
• Enhances Bollinger Bands % SD by providing an additional trend strength confirmation.
• Strengthens Kijun ATR signals by filtering out weak or temporary price movements.
4️⃣ PRC-ALMA Adaptive Bands → Mean Reversion & Trend Filtering
✔ What it Does:
The PRC-ALMA Adaptive Bands combine a percentile-based ranking system with an adaptive smoothing function (ALMA) to define overbought/oversold zones within trend movements.
✔ Why It's Important:
• Adaptive percentile-based ranking ensures the indicator adjusts to market shifts dynamically.
• ALMA filtering ensures non-lagging trend detection, reducing delays in trade signals.
• Acts as a contrarian filter for trend exhaustion signals.
✔ How It Works With Others:
• Complements VIDYA ATR & Kijun ATR by refining trend-following entries.
• Provides mean-reverting insights to balance aggressive trend-following signals.
5️⃣ Bollinger Bands % SD → Volatility Expansion & Trend Strength Evaluation
✔ What it Does:
The Bollinger Bands % SD indicator measures price positioning relative to standard deviation bounds, helping assess volatility-driven trend strength.
✔ Why It's Important:
• Measures price movements relative to historical volatility thresholds.
• Helps determine when price action is statistically stretched (i.e., strong trend moves vs. mean-reverting pullbacks).
• Allows dynamic market adaptation, ensuring that signals remain relevant across different volatility phases.
✔ How It Works With Others:
• Enhances PRC-ALMA by confirming whether a price move is an actual breakout or a short-term deviation.
• Validates VIDYA ATR & Kijun ATR signals by ensuring the trend has sufficient strength to continue.
The ChronoSync strategy ensures a balanced fusion of trend-following and volatility adaptation. Each component adds a distinct layer of analysis, reducing false signals and improving robustness:
✅ Trend Identification → VIDYA ATR, Kijun ATR, & Dual SD Kijun
✅ Noise Reduction & Trend Confirmation → VIDYA Loop Function & Gaussian Smoothing
✅ Volatility Adaptation & Overbought/Oversold Conditions → PRC-ALMA Adaptive Bands & Bollinger Bands % SD
This multi-layered approach ensures that no single indicator dominates the strategy, allowing it to adapt dynamically to various market conditions.
📌 Conclusion
ChronoSync is a universal trend aggregation strategy, built on adaptive multi-indicator filtering and robust risk management. Designed for dynamic market conditions, it offers a rule-based, quantifiable approach to trend identification. Whether used as a standalone trading system or an auxiliary confirmation tool, it provides a scientific, data-driven edge for traders navigating volatile markets.
🔹 Disclaimer: Past performance is not indicative of future results. No trading strategy can guarantee success in financial markets.
🔹 Strategic Advice: Always backtest, optimize, and align parameters with your trading objectives and risk tolerance before live trading.
GM+For a Short Trade:
When a bullish candle (close > open) is larger than the previous candle and the MACD histogram for the past three bars is consecutively lower (suggesting weakening upward momentum), the script enters a short position.
For a Long Trade:
When a bearish candle (close < open) is larger (in body size) than the previous candle and the MACD histogram for the past three bars is consecutively higher (suggesting the downward move is losing strength), the script enters a long position.
Position Management:
There are no stop loss or take profit levels. The position is closed only when an opposite signal appears.
