Bollinger Bands Filter (TradeChartist) / Owl of Profit remakeThis strategy, created by TradeChartist, uses Bollinger Bands to filter market conditions and generate precise signals for long and short positions based on price action relative to the Bollinger Bands.
Special thanks to TradeChartist for the inspiration!
Features:
Bollinger Bands Logic:
Long Entry: Triggered when the price crosses above the upper Bollinger Band.
Short Entry: Triggered when the price crosses below the lower Bollinger Band.
Customizable Settings:
Adjust the SMA period and Standard Deviation multiplier for Bollinger Bands to suit your trading style.
Enable or disable bar coloring based on Bollinger Bands logic.
Alerts and Visualization:
Clear alerts for both Long and Short signals.
Visual signals with triangle markers directly on the chart.
Shaded Bollinger Bands with customizable transparency for easier zone identification.
Bar Coloring:
Green for bullish conditions when the price is above the upper band.
Red for bearish conditions when the price is below the lower band.
This strategy is designed for educational and testing purposes. Use it as a foundation for backtesting and customization to your trading approach.
Visit my website for more tools and strategies: bybitindicators.com
Happy trading!
רצועות וערוצים
BB + MA / Owl of ProfitThis strategy combines Bollinger Bands (BB) and a Moving Average (MA) to identify trend-following entry and exit signals. It leverages Bollinger Bands for volatility-based breakouts and a Moving Average for trend confirmation.
Features:
Bollinger Bands:
Detects price volatility with customizable period and multiplier.
Generates signals based on price crossing the upper or lower bands.
Moving Average:
Supports both SMA (Simple Moving Average) and EMA (Exponential Moving Average).
Confirms trend direction for entry and exit conditions.
Entry Conditions:
Long: Price crosses above the lower Bollinger Band and is above the MA.
Short: Price crosses below the upper Bollinger Band and is below the MA.
Exit Conditions:
Long Exit: Price crosses below the MA or drops below it.
Short Exit: Price crosses above the MA or rises above it.
Customization Options:
Adjust Bollinger Bands period and multiplier for volatility sensitivity.
Choose between SMA or EMA for the Moving Average.
Visualization:
Bollinger Bands with shaded areas for easy identification of price ranges.
Visual markers for entry and exit signals directly on the chart.
This strategy is designed for educational and testing purposes. Use it as a foundation for further customization and backtesting on your preferred markets.
Visit my website for more tools and strategies: bybitindicators.com
Happy trading!
ATR + Pivot Points / Owl of ProfitThis strategy combines ATR (Average True Range) and Pivot Points for trade entries and exits. It uses dynamic stop loss and take profit levels based on ATR, and incorporates daily Pivot Points as key levels for decision-making.
Features:
Pivot Points: Calculates standard daily Pivot Points (Pivot, R1, R2, S1, S2) for support and resistance levels.
ATR Integration: Uses ATR to dynamically set stop loss and take profit levels with customizable multipliers.
Entry Conditions:
Long: Price crosses above R1.
Short: Price crosses below S1.
Exit Conditions:
Optional closing of positions when crossing the main pivot point.
Fully visualized Pivot Points for easy reference on the chart.
Customization Options:
Adjust Pivot Points calculation period.
Modify ATR length and multiplier for tailored risk management.
Enable or disable Pivot Points visualization.
This strategy is designed for demonstration and educational purposes. Use it as a foundation for further backtesting and customization.
Visit my website for more tools and strategies: bybitindicators.com
Happy trading!
Futures Engulfing Candle Size Strategy (Ticks, TP/SL)The Futures Candle Size Strategy is designed to identify and trade significant price movements in the futures market based on candle size. It is optimized for futures instruments like ES, NQ, or CL, where precise tick-level calculations are essential. The strategy includes a customizable take profit and stop loss in ticks and operates only within a specified time window (e.g., 7:00 AM to 9:15 AM CST).
Key Features:
Candle Size Threshold: Trades are triggered when the candle's high-to-low range exceeds the defined threshold in ticks.
Time Filter: Limits trades to the most active market hours, specifically between 7:00 AM and 9:15 AM CST.
Take Profit and Stop Loss: Customizable exit levels in ticks to manage risk and lock in profits.
Long and Short Trades: Automatically places buy or sell orders based on the candle's direction (bullish or bearish).
Alerts: Sends alerts whenever a trade is triggered, helping you stay informed in real-time.
How It Works:
The strategy calculates the size of each candle in ticks and compares it to the user-defined threshold.
If the candle size meets or exceeds the threshold within the specified time range, it triggers a long or short trade.
The trade automatically exits when the price hits the take profit or stop loss levels.
Mean Reversion Pro Strategy [tradeviZion]Mean Reversion Pro Strategy : User Guide
A mean reversion trading strategy for daily timeframe trading.
Introduction
Mean Reversion Pro Strategy is a technical trading system that operates on the daily timeframe. The strategy uses a dual Simple Moving Average (SMA) system combined with price range analysis to identify potential trading opportunities. It can be used on major indices and other markets with sufficient liquidity.
The strategy includes:
Trading System
Fast SMA for entry/exit points (5, 10, 15, 20 periods)
Slow SMA for trend reference (100, 200 periods)
Price range analysis (20% threshold)
Position management rules
Visual Elements
Gradient color indicators
Three themes (Dark/Light/Custom)
ATR-based visuals
Signal zones
Status Table
Current position information
Basic performance metrics
Strategy parameters
Optional messages
📊 Strategy Settings
Main Settings
Trading Mode
Options: Long Only, Short Only, Both
Default: Long Only
Position Size: 10% of equity
Starting Capital: $20,000
Moving Averages
Fast SMA: 5, 10, 15, or 20 periods
Slow SMA: 100 or 200 periods
Default: Fast=5, Slow=100
🎯 Entry and Exit Rules
Long Entry Conditions
All conditions must be met:
Price below Fast SMA
Price below 20% of current bar's range
Price above Slow SMA
No existing position
Short Entry Conditions
All conditions must be met:
Price above Fast SMA
Price above 80% of current bar's range
Price below Slow SMA
No existing position
Exit Rules
Long Positions
Exit when price crosses above Fast SMA
No fixed take-profit levels
No stop-loss (mean reversion approach)
Short Positions
Exit when price crosses below Fast SMA
No fixed take-profit levels
No stop-loss (mean reversion approach)
💼 Risk Management
Position Sizing
Default: 10% of equity per trade
Initial capital: $20,000
Commission: 0.01%
Slippage: 2 points
Maximum one position at a time
Risk Control
Use daily timeframe only
Avoid trading during major news events
Consider market conditions
Monitor overall exposure
📊 Performance Dashboard
The strategy includes a comprehensive status table displaying:
Strategy Parameters
Current SMA settings
Trading direction
Fast/Slow SMA ratio
Current Status
Active position (Flat/Long/Short)
Current price with color coding
Position status indicators
Performance Metrics
Net Profit (USD and %)
Win Rate with color grading
Profit Factor with thresholds
Maximum Drawdown percentage
Average Trade value
📱 Alert Settings
Entry Alerts
Long Entry (Buy Signal)
Short Entry (Sell Signal)
Exit Alerts
Long Exit (Take Profit)
Short Exit (Take Profit)
Alert Message Format
Strategy name
Signal type and direction
Current price
Fast SMA value
Slow SMA value
💡 Usage Tips
Consider starting with Long Only mode
Begin with default settings
Keep track of your trades
Review results regularly
Adjust settings as needed
Follow your trading plan
⚠️ Disclaimer
This strategy is for educational and informational purposes only. It is not financial advice. Always:
Conduct your own research
Test thoroughly before live trading
Use proper risk management
Consider your trading goals
Monitor market conditions
Never risk more than you can afford to lose
📋 Release Notes
14 January 2025
Added New Fast & Slow SMA Options:
Fibonacci-based periods: 8, 13, 21, 144, 233, 377
Additional period: 50
Complete Fast SMA options now: 5, 8, 10, 13, 15, 20, 21, 34, 50
Complete Slow SMA options now: 100, 144, 200, 233, 377
Bug Fixes:
Fixed Maximum Drawdown calculation in the performance table
Now using strategy.max_drawdown_percent for accurate DD reporting
Previous version showed incorrect DD values
Performance metrics now accurately reflect trading results
Performance Note:
Strategy tested with Fast/Slow SMA 13/377
Test conducted with 10% equity risk allocation
Daily Timeframe
For Beginners - How to Modify SMA Levels:
Find this line in the code:
fastLength = input.int(title="Fast SMA Length", defval=5, options= )
To add a new Fast SMA period: Add the number to the options list, e.g.,
To remove a Fast SMA period: Remove the number from the options list
For Slow SMA, find:
slowLength = input.int(title="Slow SMA Length", defval=100, options= )
Modify the options list the same way
⚠️ Note: Keep the periods that make sense for your trading timeframe
💡 Tip: Test any new combinations thoroughly before live trading
"Trade with Discipline, Manage Risk, Stay Consistent" - tradeviZion
Multi-Band Comparison Strategy (CRYPTO)Multi-Band Comparison Strategy (CRYPTO)
Optimized for Cryptocurrency Trading
This Pine Script strategy is built from the ground up for traders who want to take advantage of cryptocurrency volatility using a confluence of advanced statistical bands. The strategy layers Bollinger Bands, Quantile Bands, and a unique Power-Law Band to map out crucial support/resistance zones. It then focuses on a Trigger Line—the lower standard deviation band of the upper quantile—to pinpoint precise entry and exit signals.
Key Features
Bollinger Band Overlay
The upper Bollinger Band visually shifts to yellow when price exceeds it, turning black otherwise. This offers a straightforward way to gauge heightened momentum or potential market slowdowns.
Quantile & Power-Law Integration
The script calculates upper and lower quantile bands to assess probabilistic price extremes.
A Power-Law Band is also available to measure historically significant return levels, providing further insight into overbought or oversold conditions in fast-moving crypto markets.
Standard Deviation Trigger
The lower standard deviation band of the upper quantile acts as the strategy’s trigger. If price consistently holds above this line, the strategy interprets it as a strong bullish signal (“green” zone). Conversely, dipping below indicates a “red” zone, signaling potential reversals or exits.
Consecutive Bar Confirmation
To reduce choppy signals, you can fine-tune the number of consecutive bars required to confirm an entry or exit. This helps filter out noise and false breaks—critical in the often-volatile crypto realm.
Adaptive for Multiple Timeframes
Whether you’re scalping on a 5-minute chart or swing trading on daily candles, the strategy’s flexible confirmation and overlay options cater to different market conditions and trading styles.
Complete Plot Customization
Easily toggle visibility of each band or line—Bollinger, Quantile, Power-Law, and more.
Built-in Simple and Exponential Moving Averages can be enabled to further contextualize market trends.
Why It Excels at Crypto
Cryptocurrencies are known for rapid price swings, and this strategy addresses exactly that by combining multiple statistical methods. The quantile-based confirmation reduces noise, while Bollinger and Power-Law bands help highlight breakout regions in trending markets. Traders have reported that it works seamlessly across various coins and tokens, adapting its triggers to each asset’s unique volatility profile.
Give it a try on your favorite cryptocurrency pairs. With advanced data handling, crisp visual cues, and adjustable confirmation logic, the Multi-Band Comparison Strategy provides a robust framework to capture profitable moves and mitigate risk in the ever-evolving crypto space.
Falcon Liquidity Grab StrategyHow to Use This Script for Commodities and Indices
Best Timeframes: Start with 15-minute charts but test on higher timeframes like 1 hour for indices.
Risk Settings: Adjust the stop_loss_points and take_profit_multiplier to match the volatility of the chosen instrument.
FON60DK by leventsahThe strategy generates buy and sell signals using the Tillson T3 and TOTT (Twin Optimized Trend Tracker) indicators. Additionally, the Williams %R indicator is used to filter the signals. Below is an explanation of the main components of the code:
1. Input Parameters:
Tillson T3 and TOTT parameters: Separate parameters are defined for both buy (AL) and sell (SAT) conditions. These parameters control the sensitivity and behavior of the indicators.
Williams %R period: The period for the Williams %R indicator is set to determine overbought and oversold levels.
2. Tillson T3 Calculation:
The Tillson T3 indicator is a smoothed moving average that uses an exponential moving average (EMA) with additional smoothing. The formula calculates a weighted average of multiple EMAs to produce a smoother line.
The t3 function computes the Tillson T3 value based on the close price and the input parameters.
3. TOTT Calculation (Twin Optimized Trend Tracker):
The TOTT indicator is a trend-following tool that adjusts its sensitivity based on market conditions. It uses a combination of price action and a volatility coefficient to determine trend direction.
The Var_Func function calculates the TOTT value, which is then used to derive the OTT (Optimized Trend Tracker) levels for both buy and sell conditions.
4. Williams %R Calculation:
Williams %R is a momentum oscillator that measures overbought and oversold levels. It is calculated using the highest high and lowest low over a specified period.
5. Buy and Sell Conditions:
Buy Condition: A buy signal is generated when the Tillson T3 value crosses above the TOTT upper band (OTTup) and the Williams %R is above -20 (indicating an oversold condition).
Sell Condition: A sell signal is generated when the Tillson T3 value crosses below the TOTT lower band (OTTdnS) and the Williams %R is above -70 (used to close long positions).
6. Strategy Execution:
The strategy.entry function is used to open a long position when the buy condition is met.
The strategy.close function is used to close the long position when the sell condition is met.
7. Visualization:
The bars on the chart are colored green when a long position is open.
The Tillson T3, TOTT upper band (OTTup), and TOTT lower band (OTTdn) are plotted on the chart for both buy and sell conditions.
8. Plots:
The Tillson T3 values for buy and sell conditions are plotted in blue.
The TOTT upper and lower bands are plotted in green and red, respectively, for both buy and sell conditions.
Summary:
This strategy combines trend-following indicators (Tillson T3 and TOTT) with a momentum oscillator (Williams %R) to generate buy and sell signals. The use of separate parameters for buy and sell conditions allows for fine-tuning the strategy based on market behavior. The visual elements, such as colored bars and plotted indicators, help traders quickly identify signals and trends on the chart.
Fibonacci Trend - Aynet1. Inputs
lookbackPeriod: Defines the number of bars to consider for calculating swing highs and lows. Default is 20.
fibLevel1 to fibLevel5: Fibonacci retracement levels to calculate price levels (23.6%, 38.2%, 50%, 61.8%, 78.6%).
useTime: Enables or disables time-based Fibonacci projections.
riskPercent: Defines the percentage of risk for trading purposes (currently not used in calculations).
2. Functions
isSwingHigh(index): Identifies a swing high at the given index, where the high of that candle is higher than both its previous and subsequent candles.
isSwingLow(index): Identifies a swing low at the given index, where the low of that candle is lower than both its previous and subsequent candles.
3. Variables
swingHigh and swingLow: Store the most recent swing high and swing low prices.
swingHighTime and swingLowTime: Store the timestamps of the swing high and swing low.
fib1 to fib5: Fibonacci levels based on the difference between swingHigh and swingLow.
4. Swing Point Detection
The script checks if the last bar is a swing high or swing low using the isSwingHigh() and isSwingLow() functions.
If a swing high is detected:
The high price is stored in swingHigh.
The timestamp of the swing high is stored in swingHighTime.
If a swing low is detected:
The low price is stored in swingLow.
The timestamp of the swing low is stored in swingLowTime.
5. Fibonacci Levels Calculation
If both swingHigh and swingLow are defined, the script calculates the Fibonacci retracement levels (fib1 to fib5) based on the price difference (priceDiff = swingHigh - swingLow).
6. Plotting Fibonacci Levels
Fibonacci levels (fib1 to fib5) are plotted as horizontal lines using the line.new() function.
Labels (e.g., "23.6%") are added near the lines to indicate the level.
Lines and labels are color-coded:
23.6% → Blue
38.2% → Green
50.0% → Yellow
61.8% → Orange
78.6% → Red
7. Filling Between Fibonacci Levels
The plot() function creates lines for each Fibonacci level.
The fill() function is used to fill the space between two levels with semi-transparent colors:
Blue → Between fib1 and fib2
Green → Between fib2 and fib3
Yellow → Between fib3 and fib4
Orange → Between fib4 and fib5
8. Time-Based Fibonacci Projections
If useTime is enabled:
The time difference (timeDiff) between the swing high and swing low is calculated.
Fibonacci time projections are added based on multiples of 23.6%.
If the current time reaches a projected time, a label (e.g., "T1", "T2") is displayed near the high price.
9. Trading Logic
Two placeholder variables are defined for trading logic:
longCondition: Tracks whether a condition for a long trade is met (currently not implemented).
shortCondition: Tracks whether a condition for a short trade is met (currently not implemented).
These variables can be extended to define entry/exit signals based on Fibonacci levels.
How It Works
Detect Swing Points: It identifies recent swing high and swing low points on the chart.
Calculate Fibonacci Levels: Based on the swing points, it computes retracement levels.
Visualize Levels: Plots the levels on the chart with labels and fills between them.
Time Projections: Optionally calculates time-based projections for future price movements.
Trading Opportunities: The framework provides tools for detecting potential reversal or breakout zones using Fibonacci levels.
Hull Suite by MRS**Hull Suite by MRS Strategy Indicator**
The Hull Suite by MRS Strategy is a technical analysis tool designed to provide insights into market trends using variations of the Hull Moving Average (HMA). This strategy aims to help traders identify optimal entry points for both long and short positions by utilizing multiple types of Hull-based indicators.
### Key Features:
1. **Hull Moving Average Variations**: The indicator offers three different Hull Moving Average variants:
- **HMA (Hull Moving Average)**: A fast-moving average that minimizes lag and reacts quickly to price changes.
- **EHMA (Enhanced Hull Moving Average)**: A smoother version of HMA with reduced noise, offering a clearer view of market trends.
- **THMA (Triple Hull Moving Average)**: A more complex Hull average that aims to provide a stronger confirmation of trend direction.
2. **Customizable Parameters**:
- **Source Selection**: Allows traders to choose the source for calculation (e.g., closing prices).
- **Length**: A configurable parameter to adjust the period over which the moving average is calculated (e.g., 55-period for swing entries).
- **Trend Coloring**: Users can enable automatic color-coding of the Hull moving average to reflect whether the market is in an uptrend (green) or downtrend (red).
- **Candle Color**: Option to color candles based on Hull's trend, further improving the visual clarity of trend direction.
3. **Entry and Exit Signals**:
- **Buy Signal**: Generated when the Hull moving average crosses above its historical value, indicating a potential upward price movement.
- **Sell Signal**: Triggered when the Hull moving average crosses below its historical value, signaling a potential downward price movement.
- The strategy can be customized to work with long, short, or both directions, making it adaptable for various market conditions.
4. **Visual Representation**:
- **Hull Bands**: The indicator can plot the Hull moving average as bands, with customizable transparency to suit individual preferences.
- **Band Filler**: The area between the two Hull moving averages is filled, making it easier to identify trends at a glance.
5. **Backtesting and Strategy Execution**: This strategy can be tested on historical data with adjustable backtest start and stop dates, providing traders with a better understanding of its performance before live trading.
### Purpose:
The Hull Suite by MRS Strategy is designed to assist traders in determining the optimal time to enter and exit the market based on robust Hull moving averages. With its flexibility, it can be used for trend-following, swing trading, or other strategic applications.
HOD/LOD/PMH/PML/PDH/PDL Strategy by @tradingbauhaus This script is a trading strategy @tradingbauhaus designed to trade based on key price levels, such as the High of Day (HOD), Low of Day (LOD), Premarket High (PMH), Premarket Low (PML), Previous Day High (PDH), and Previous Day Low (PDL). Below, I’ll explain in detail what the script does:
Core Functionality of the Script:
Calculates Key Price Levels:
HOD (High of Day): The highest price of the current day.
LOD (Low of Day): The lowest price of the current day.
PMH (Premarket High): The highest price during the premarket session (before the market opens).
PML (Premarket Low): The lowest price during the premarket session.
PDH (Previous Day High): The highest price of the previous day.
PDL (Previous Day Low): The lowest price of the previous day.
Draws Horizontal Lines on the Chart:
Plots horizontal lines on the chart for each key level (HOD, LOD, PMH, PML, PDH, PDL) with specific colors for easy visual identification.
Defines Entry and Exit Rules:
Long Entry (Buy): If the price crosses above the PMH (Premarket High) or the PDH (Previous Day High).
Short Entry (Sell): If the price crosses below the PML (Premarket Low) or the PDL (Previous Day Low).
Long Exit: If the price reaches the HOD (High of Day) during a long position.
Short Exit: If the price reaches the LOD (Low of Day) during a short position.
How the Script Works Step by Step:
Calculates Key Levels:
Uses the request.security function to fetch the HOD and LOD of the current day, as well as the highs and lows of the previous day (PDH and PDL).
Calculates the PMH and PML during the premarket session (before 9:30 AM).
Plots Levels on the Chart:
Uses the plot function to draw horizontal lines on the chart representing the key levels (HOD, LOD, PMH, PML, PDH, PDL).
Each level has a specific color for easy identification:
HOD: White.
LOD: Purple.
PDH: Orange.
PDL: Blue.
PMH: Green.
PML: Red.
Defines Trading Rules:
Uses conditions with ta.crossover and ta.crossunder to detect when the price crosses key levels.
Long Entry: If the price crosses above the PMH or PDH, a long position (buy) is opened.
Short Entry: If the price crosses below the PML or PDL, a short position (sell) is opened.
Long Exit: If the price reaches the HOD during a long position, the position is closed.
Short Exit: If the price reaches the LOD during a short position, the position is closed.
Executes Orders Automatically:
Uses the strategy.entry and strategy.close functions to open and close positions automatically based on the defined rules.
Advantages of This Strategy:
Based on Key Levels: Uses important price levels that often act as support and resistance.
Easy to Visualize: Horizontal lines on the chart make it easy to identify levels.
Automated: Entries and exits are executed automatically based on the defined rules.
Limitations of This Strategy:
Dependent on Volatility: Works best in markets with significant price movements.
False Crosses: There may be false crosses that generate incorrect signals.
No Advanced Risk Management: Does not include dynamic stop-loss or take-profit mechanisms.
How to Improve the Strategy:
Add Stop-Loss and Take-Profit: To limit losses and lock in profits.
Filter Signals with Indicators: Use RSI, MACD, or other indicators to confirm signals.
Optimize Levels: Adjust key levels based on the asset’s behavior.
In summary, this script is a trading strategy that operates based on key price levels, such as HOD, LOD, PMH, PML, PDH, and PDL. It is useful for traders who want to trade based on significant support and resistance levels.
Bollinger Band Touch with SMI and MACD AngleThis strategy is intended for short timeframes to enter and exit when price touches lower and upper bollinger bands with confluence on RSI and MACD
Mean Reversion V-FThis strategy workings on high volatile stock or crypto assets
It using 5 dynamic band's to get in the long position.
In same time depends on the band increases the units of the asset to get in the next position.
The unit's of the asset can be adjusted. Make sure to adjust the unit for different asset.
The bands are determined of main SMA.
There is no stop loss.
Take profit is trialing - HMA or % or average price + take profit - note if you use % trailing back test is not realistic but is working on real time.
Deviations can be adjust depends on the asset volatility.
IU EMA Channel StrategyIU EMA Channel Strategy
Overview:
The IU EMA Channel Strategy is a simple yet effective trend-following strategy that uses two Exponential Moving Averages (EMAs) based on the high and low prices. It provides clear entry and exit signals by identifying price crossovers relative to the EMAs while incorporating a built-in Risk-to-Reward Ratio (RTR) for effective risk management.
Inputs ( Settings ):
- RTR (Risk-to-Reward Ratio): Define the ratio for risk-to-reward (default = 2).
- EMA Length: Adjust the length of the EMA channels (default = 100).
How the Strategy Works
1. EMA Channels:
- High-based EMA: EMA calculated on the high price.
- Low-based EMA: EMA calculated on the low price.
The area between these two EMAs creates a "channel" that visually highlights potential support and resistance zones.
2. Entry Rules:
- Long Entry: When the price closes above the high-based EMA (crossover).
- Short Entry: When the price closes below the low-based EMA (crossunder).
These entries ensure trades are taken in the direction of momentum.
3. Stop Loss (SL) and Take Profit (TP):
- Stop Loss:
- For long positions, the SL is set at the previous bar's low.
- For short positions, the SL is set at the previous bar's high.
- Take Profit:
- TP is automatically calculated using the Risk-to-Reward Ratio (RTR) you define.
- Example: If RTR = 2, the TP will be 2x the risk distance.
4. Exit Rules:
- Positions are closed at either the stop loss or the take profit level.
- The strategy manages exits automatically to enforce disciplined risk management.
Visual Features
1. EMA Channels:
- The high and low EMAs are dynamically color-coded:
- Green: Price is above the EMA (bullish condition).
- Red: Price is below the EMA (bearish condition).
- The area between the EMAs is shaded for better visual clarity.
2. Stop Loss and Take Profit Zones:
- SL and TP levels are plotted for both long and short positions.
- Zones are filled with:
- Red: Stop Loss area.
- Green: Take Profit area.
Be sure to manage your risk and position size properly.
Custom Strategy: ETH Martingale 2.0Strategic characteristics
ETH Little Martin 2.0 is a self-developed trading strategy based on the Martingale strategy, mainly used for trading ETH (Ethereum). The core idea of this strategy is to place orders in the same direction at a fixed price interval, and then use Martin's multiple investment principle to reduce losses, but this is also the main source of losses.
Parameter description:
1 Interval： The minimum spacing for taking profit, stop loss, and opening/closing of orders. Different targets have different spacing. Taking ETH as an example, it is generally recommended to have a spacing of 2% for fluctuations in the target.
2 Base Price： This is the price at which you triggered the first order. Similarly, I am using ETH as an example. If you have other targets, I suggest using the initial value of a price that can be backtesting. The Base Price is only an initial order price and has no impact on subsequent orders.
3 Initial Order Amount： Users can set an initial order amount to control the risk of each transaction. If the stop loss is reached, we will double the amount based on this value. This refers to the value of the position held, not the number of positions held.
4 Loss Multiplier： The strategy will increase the next order amount based on the set multiple after the stop loss, in order to make up for the previous losses through a larger position. Note that after taking profit, it will be reset to 1 times the Initial Order Amount.
5. Long Short Operation: The first order of the strategy is a multiple entry, and in subsequent orders, if the stop loss is reached, a reverse order will be opened. The position value of a one-way order is based on the Loss Multiplier multiple investment, so it is generally recommended that the Loss Multiplier default to 2.
Improvement direction
Although this strategy already has a certain trading logic, there are still some improvement directions that can be considered:
1. Dynamic adjustment of spacing: Currently, the spacing is fixed, and it can be considered to dynamically adjust the spacing based on market volatility to improve the adaptability of the strategy. Try using dynamic spacing, which may be more suitable for the actual market situation.
2. Filtering criteria: Orders and no orders can be optimized separately. The biggest problem with this strategy is that it will result in continuous losses during fluctuations, and eventually increase the investment amount. You can consider filtering out some fluctuations or only focusing on trend trends.
3. Risk management: Add more risk management measures, such as setting a maximum loss limit to avoid huge losses caused by continuous stop loss.
4. Optimize the stop loss multiple: Currently, the stop loss multiple is fixed, and it can be considered to dynamically adjust the multiple according to market conditions to reduce risk.
DCA Strategy with Mean Reversion and Bollinger BandDCA Strategy with Mean Reversion and Bollinger Band
The Dollar-Cost Averaging (DCA) Strategy with Mean Reversion and Bollinger Bands is a sophisticated trading strategy that combines the principles of DCA, mean reversion, and technical analysis using Bollinger Bands. This strategy aims to capitalize on market corrections by systematically entering positions during periods of price pullbacks and reversion to the mean.
Key Concepts and Principles
1. Dollar-Cost Averaging (DCA)
DCA is an investment strategy that involves regularly purchasing a fixed dollar amount of an asset, regardless of its price. The idea behind DCA is that by spreading out investments over time, the impact of market volatility is reduced, and investors can avoid making large investments at inopportune times. The strategy reduces the risk of buying all at once during a market high and can smooth out the cost of purchasing assets over time.
In the context of this strategy, the Investment Amount (USD) is set by the user and represents the amount of capital to be invested in each buy order. The strategy executes buy orders whenever the price crosses below the lower Bollinger Band, which suggests a potential market correction or pullback. This is an effective way to average the entry price and avoid the emotional pitfalls of trying to time the market perfectly.
2. Mean Reversion
Mean reversion is a concept that suggests prices will tend to return to their historical average or mean over time. In this strategy, mean reversion is implemented using the Bollinger Bands, which are based on a moving average and standard deviation. The lower band is considered a potential buy signal when the price crosses below it, indicating that the asset has become oversold or underpriced relative to its historical average. This triggers the DCA buy order.
Mean reversion strategies are popular because they exploit the natural tendency of prices to revert to their mean after experiencing extreme deviations, such as during market corrections or panic selling.
3. Bollinger Bands
Bollinger Bands are a technical analysis tool that consists of three lines:
Middle Band: The moving average, usually a 200-period Exponential Moving Average (EMA) in this strategy. This serves as the "mean" or baseline.
Upper Band: The middle band plus a certain number of standard deviations (multiplier). The upper band is used to identify overbought conditions.
Lower Band: The middle band minus a certain number of standard deviations (multiplier). The lower band is used to identify oversold conditions.
In this strategy, the Bollinger Bands are used to identify potential entry points for DCA trades. When the price crosses below the lower band, this is seen as a potential opportunity for mean reversion, suggesting that the asset may be oversold and could reverse back toward the middle band (the EMA). Conversely, when the price crosses above the upper band, it indicates overbought conditions and signals potential market exhaustion.
4. Time-Based Entry and Exit
The strategy has specific entry and exit points defined by time parameters:
Open Date: The date when the strategy begins opening positions.
Close Date: The date when all positions are closed.
This time-bound approach ensures that the strategy is active only during a specified window, which can be useful for testing specific market conditions or focusing on a particular time frame.
5. Position Sizing
Position sizing is determined by the Investment Amount (USD), which is the fixed amount to be invested in each buy order. The quantity of the asset to be purchased is calculated by dividing the investment amount by the current price of the asset (investment_amount / close). This ensures that the amount invested remains constant despite fluctuations in the asset's price.
6. Closing All Positions
The strategy includes an exit rule that closes all positions once the specified close date is reached. This allows for controlled exits and limits the exposure to market fluctuations beyond the strategy's timeframe.
7. Background Color Based on Price Relative to Bollinger Bands
The script uses the background color of the chart to provide visual feedback about the price's relationship with the Bollinger Bands:
Red background indicates the price is above the upper band, signaling overbought conditions.
Green background indicates the price is below the lower band, signaling oversold conditions.
This provides an easy-to-interpret visual cue for traders to assess the current market environment.
Postscript: Configuring Initial Capital for Backtesting
To ensure the backtest results align with the actual investment scenario, users must adjust the Initial Capital in the TradingView strategy properties. This is done by calculating the Initial Capital as the product of the Total Closed Trades and the Investment Amount (USD). For instance:
If the user is investing 100 USD per trade and has 10 closed trades, the Initial Capital should be set to 1,000 USD.
Similarly, if the user is investing 200 USD per trade and has 24 closed trades, the Initial Capital should be set to 4,800 USD.
This adjustment ensures that the backtesting results reflect the actual capital deployed in the strategy and provides an accurate representation of potential gains and losses.
Conclusion
The DCA strategy with Mean Reversion and Bollinger Bands is a systematic approach to investing that leverages the power of regular investments and technical analysis to reduce market timing risks. By combining DCA with the insights offered by Bollinger Bands and mean reversion, this strategy offers a structured way to navigate volatile markets while targeting favorable entry points. The clear entry and exit rules, coupled with time-based constraints, make it a robust and disciplined approach to long-term investing.
Enhanced Swing Trading Strategy//@version=5
strategy("Enhanced Swing Trading Strategy", overlay=true)
// Input Parameters
smaShortLength = input.int(50, title="Short SMA Length")
smaLongLength = input.int(200, title="Long SMA Length")
rsiLength = input.int(14, title="RSI Length")
rsiOverbought = input.int(70, title="RSI Overbought Level")
rsiOversold = input.int(30, title="RSI Oversold Level")
takeProfitPerc = input.float(2.0, title="Take Profit (%)")
stopLossPerc = input.float(1.0, title="Stop Loss (%)")
riskPerc = input.float(1.0, title="Risk per Trade (%)")
alertOnSignal = input.bool(true, title="Enable Alerts")
// Indicators
smaShort = ta.sma(close, smaShortLength)
smaLong = ta.sma(close, smaLongLength)
rsi = ta.rsi(close, rsiLength)
= ta.macd(close, 12, 26, 9)
// Conditions
longCondition = ta.crossover(smaShort, smaLong) and rsi > rsiOversold and macdLine > signalLine
shortCondition = ta.crossunder(smaShort, smaLong) and rsi < rsiOverbought and macdLine < signalLine
// Position Sizing based on Risk
capital = strategy.equity
riskAmount = capital * (riskPerc / 100)
stopLossValue = riskAmount / (stopLossPerc / 100)
positionSize = stopLossValue / close
// Entry Signals
if (longCondition)
strategy.entry("Long", strategy.long, qty=positionSize)
if alertOnSignal
alert("Swing Trading: Long Position Opened", alert.freq_once)
if (shortCondition)
strategy.entry("Short", strategy.short, qty=positionSize)
if alertOnSignal
alert("Swing Trading: Short Position Opened", alert.freq_once)
// Exit Conditions
strategy.exit("Take Profit/Stop Loss",
from_entry="Long",
profit=takeProfitPerc,
loss=stopLossPerc)
strategy.exit("Take Profit/Stop Loss",
from_entry="Short",
profit=takeProfitPerc,
loss=stopLossPerc)
// Plotting
plot(smaShort, color=color.blue, title="SMA 50")
plot(smaLong, color=color.red, title="SMA 200")
hline(rsiOverbought, "RSI Overbought", color=color.red)
hline(rsiOversold, "RSI Oversold", color=color.green)
plot(macdLine, color=color.green, title="MACD Line")
plot(signalLine, color=color.orange, title="Signal Line")
// Draw Entry and Exit Labels
if (strategy.position_size > 0)
label.new(bar_index, high, "Long Open", style=label.style_label_up, color=color.green)
if (strategy.position_size < 0)
label.new(bar_index, low, "Short Open", style=label.style_label_down, color=color.red)
Bollinger Breakout Strategy with Direction Control [4H crypto]Bollinger Breakout Strategy with Direction Control - User Guide
This strategy leverages Bollinger Bands, RSI, and directional filters to identify potential breakout trading opportunities. It is designed for traders looking to capitalize on significant price movements while maintaining control over trade direction (long, short, or both). Here’s how to use this strategy effectively:
How the Strategy Works
Indicators Used:
Bollinger Bands:
A volatility-based indicator with an upper and lower band around a simple moving average (SMA). The bands expand or contract based on market volatility.
RSI (Relative Strength Index):
Measures momentum to determine overbought or oversold conditions. In this strategy, RSI is used to confirm breakout strength.
Trade Direction Control:
You can select whether to trade:
Long only: Buy positions.
Short only: Sell positions.
Both: Trade in both directions depending on conditions.
Breakout Conditions:
Long Trade:
The price closes above the upper Bollinger Band.
RSI is above the midline (50), confirming upward momentum.
The "Trade Direction" setting allows either "Long" or "Both."
Short Trade:
The price closes below the lower Bollinger Band.
RSI is below the midline (50), confirming downward momentum.
The "Trade Direction" setting allows either "Short" or "Both."
Risk Management:
Stop-Loss:
Long trades: Set at 2% below the entry price.
Short trades: Set at 2% above the entry price.
Take-Profit:
Calculated using a Risk/Reward Ratio (default is 2:1).
Adjust this in the strategy settings.
Inputs and Customization
Key Parameters:
Bollinger Bands Length: Default is 20. Adjust based on the desired sensitivity.
Multiplier: Default is 2.0. Higher values widen the bands; lower values narrow them.
RSI Length: Default is 14, which is standard for RSI.
Risk/Reward Ratio: Default is 2.0. Increase for more aggressive profit targets, decrease for conservative exits.
Trade Direction:
Options: "Long," "Short," or "Both."
Example: Set to "Long" in a bullish market to focus only on buy trades.
How to Use This Strategy
Adding the Strategy:
Paste the script into TradingView’s Pine Editor and add it to your chart.
Setting Parameters:
Adjust the Bollinger Band settings, RSI, and Risk/Reward Ratio to fit the asset and timeframe you're trading.
Analyzing Signals:
Green line (Upper Band): Signals breakout potential for long trades.
Red line (Lower Band): Signals breakout potential for short trades.
Blue line (Basis): Central Bollinger Band (SMA), helpful for understanding price trends.
Testing the Strategy:
Use the Strategy Tester in TradingView to backtest performance on your chosen asset and timeframe.
Optimizing for Assets:
Forex pairs, cryptocurrencies (like BTC), or stocks with high volatility are ideal for this strategy.
Works best on higher timeframes like 4H or Daily.
Best Practices
Combine with Volume: Confirm breakouts with increased volume for higher reliability.
Avoid Sideways Markets: Use additional trend filters (like ADX) to avoid trades in low-volatility conditions.
Optimize Parameters: Regularly adjust the Bollinger Bands multiplier and RSI settings to match the asset's behavior.
By utilizing this strategy, you can effectively trade breakouts while maintaining flexibility in trade direction. Adjust the parameters to match your trading style and market conditions for optimal results!
Fibonacci Levels Strategy with High/Low Criteria-AYNETThis code represents a TradingView strategy that uses Fibonacci levels in conjunction with high/low price criteria over specified lookback periods to determine buy (long) and sell (short) conditions. Below is an explanation of each main part of the code:
Explanation of Key Sections
User Inputs for Higher Time Frame and Candle Settings
Users can select a higher time frame (timeframe) for analysis and specify whether to use the "Current" or "Last" higher time frame (HTF) candle for calculating Fibonacci levels.
The currentlast setting allows flexibility between using real-time or the most recent closed higher time frame candle.
Lookback Periods for High/Low Criteria
Two lookback periods, lowestLookback and highestLookback, allow users to set the number of bars to consider when finding the lowest and highest prices, respectively.
This determines the criteria for entering trades based on how recent highs or lows compare to current prices.
Fibonacci Levels Configuration
Fibonacci levels (0%, 23.6%, 38.2%, 50%, 61.8%, 78.6%, and 100%) are configurable. These are used to calculate price levels between the high and low of the higher time frame candle.
Each level represents a retracement or extension relative to the high/low range of the HTF candle, providing important price levels for decision-making.
HTF Candle Calculation
HTF candle data is calculated based on the higher time frame selected by the user, using the newbar check to reset htfhigh, htflow, and htfopen values.
The values are updated with each new HTF bar or as prices move within the same HTF bar to track the highest high and lowest low accurately.
Set Fibonacci Levels Array
Using the calculated HTF candle's high, low, and open, the Fibonacci levels are computed by interpolating these values according to the user-defined Fibonacci levels.
A fibLevels array stores these computed values.
Plotting Fibonacci Levels
Each Fibonacci level is plotted on the chart with a different color, providing visual indicators for potential support/resistance levels.
High/Low Price Criteria Calculation
The lowest and highest prices over the specified lookback periods (lowestLookback and highestLookback) are calculated and plotted on the chart. These serve as dynamic levels to trigger long or short entries.
Trade Signal Conditions
longCondition: A long (buy) signal is generated when the price crosses above both the lowest price criteria and the 50% Fibonacci level.
shortCondition: A short (sell) signal is generated when the price crosses below both the highest price criteria and the 50% Fibonacci level.
Executing Trades
Based on the longCondition and shortCondition, trades are entered with the strategy.entry() function, using the labels "Long" and "Short" for tracking on the chart.
Strategy Use
This strategy allows traders to utilize Fibonacci retracement levels and recent highs/lows to identify trend continuation or reversal points, potentially providing entry points aligned with larger market structure. Adjusting the lowestLookback and highestLookback along with Fibonacci levels enables a customizable approach to suit different trading styles and market conditions.
Honest Volatility Grid [Honestcowboy]The Honest Volatility Grid is an attempt at creating a robust grid trading strategy but without standard levels.
Normal grid systems use price levels like 1.01;1.02;1.03;1.04... and place an order at each of these levels. In this program instead we create a grid using keltner channels using a long term moving average.
🟦 IS THIS EVEN USEFUL?
The idea is to have a more fluid style of trading where levels expand and follow price and do not stick to precreated levels. This however also makes each closed trade different instead of using fixed take profit levels. In this strategy a take profit level can even be a loss. It is useful as a strategy because it works in a different way than most strategies, making it a good tool to diversify a portfolio of trading strategies.
🟦 STRATEGY
There are 10 levels below the moving average and 10 above the moving average. For each side of the moving average the strategy uses 1 to 3 orders maximum (3 shorts at top, 3 longs at bottom). For instance you buy at level 2 below moving average and you increase position size when level 6 is reached (a cheaper price) in order to spread risks.
By default the strategy exits all trades when the moving average is reached, this makes it a mean reversion strategy. It is specifically designed for the forex market as these in my experience exhibit a lot of ranging behaviour on all the timeframes below daily.
There is also a stop loss at the outer band by default, in case price moves too far from the mean.
What are the risks?
In case price decides to stay below the moving average and never reaches the outer band one trade can create a very substantial loss, as the bands will keep following price and are not at a fixed level.
Explanation of default parameters
By default the strategy uses a starting capital of 25000$, this is realistic for retail traders.
Lot sizes at each level are set to minimum lot size 0.01, there is no reason for the default to be risky, if you want to risk more or increase equity curve increase the number at your own risk.
Slippage set to 20 points: that's a normal 2 pip slippage you will find on brokers.
Fill limit assumtion 20 points: so it takes 2 pips to confirm a fill, normal forex spread.
Commission is set to 0.00005 per contract: this means that for each contract traded there is a 5$ or whatever base currency pair has as commission. The number is set to 0.00005 because pinescript does not know that 1 contract is 100000 units. So we divide the number by 100000 to get a realistic commission.
The script will also multiply lot size by 100000 because pinescript does not know that lots are 100000 units in forex.
Extra safety limit
Normally the script uses strategy.exit() to exit trades at TP or SL. But because these are created 1 bar after a limit or stop order is filled in pinescript. There are strategy.orders set at the outer boundaries of the script to hedge against that risk. These get deleted bar after the first order is filled. Purely to counteract news bars or huge spikes in price messing up backtest.
🟦 VISUAL GOODIES
I've added a market profile feature to the edge of the grid. This so you can see in which grid zone market has been the most over X bars in the past. Some traders may wish to only turn on the strategy whenever the market profile displays specific characteristics (ranging market for instance).
These simply count how many times a high, low, or close price has been in each zone for X bars in the past. it's these purple boxes at the right side of the chart.
🟦 Script can be fully automated to MT5
There are risk settings in lot sizes or % for alerts and symbol settings provided at the bottom of the indicator. The script will send alert to MT5 broker trying to mimic the execution that happens on tradingview. There are always delays when using a bridge to MT5 broker and there could be errors so be mindful of that. This script sends alerts in format so they can be read by tradingview.to which is a bridge between the platforms.
Use the all alert function calls feature when setting up alerts and make sure you provide the right webhook if you want to use this approach.
Almost every setting in this indicator has a tooltip added to it. So if any setting is not clear hover over the (?) icon on the right of the setting.
Bollinger Bands + RSI StrategyThe Bollinger Bands + RSI strategy combines volatility and momentum indicators to spot trading opportunities in intraday settings. Here’s a concise summary:
Components:
Bollinger Bands: Measures market volatility. The lower band signals potential buying opportunities when the price is considered oversold.
Relative Strength Index (RSI): Evaluates momentum to identify overbought or oversold conditions. An RSI below 30 indicates oversold, suggesting a buy, and above 70 indicates overbought, suggesting a sell.
Strategy Execution:
Buy Signal : Triggered when the price falls below the lower Bollinger Band while the RSI is also below 30.
Sell Signal : Activated when the price exceeds the upper Bollinger Band with an RSI above 70.
Exit Strategy : Exiting a buy position is considered when the RSI crosses back above 50, capturing potential rebounds.
Advantages:
Combines price levels with momentum for more reliable signals.
Clearly defined entry and exit points help minimize emotional trading.
Considerations:
Can produce false signals in very volatile or strongly trending markets.
Best used in markets without a strong prevailing trend.
This strategy aids traders in making decisions based on technical indicators, enhancing their ability to profit from short-term price movements.
VWAP Stdev Bands Strategy (Long Only)The VWAP Stdev Bands Strategy (Long Only) is designed to identify potential long entry points in trending markets by utilizing the Volume Weighted Average Price (VWAP) and standard deviation bands. This strategy focuses on capturing upward price movements, leveraging statistical measures to determine optimal buy conditions.
Key Features:
VWAP Calculation: The strategy calculates the VWAP, which represents the average price a security has traded at throughout the day, weighted by volume. This is an essential indicator for determining the overall market trend.
Standard Deviation Bands: Two bands are created above and below the VWAP, calculated using specified standard deviations. These bands act as dynamic support and resistance levels, providing insight into price volatility and potential reversal points.
Trading Logic:
Long Entry Condition: A long position is triggered when the price crosses below the lower standard deviation band and then closes above it, signaling a potential price reversal to the upside.
Profit Target: The strategy allows users to set a predefined profit target, closing the long position once the specified target is reached.
Time Gap Between Orders: A customizable time gap can be specified to prevent multiple orders from being placed in quick succession, allowing for a more controlled trading approach.
Visualization: The VWAP and standard deviation bands are plotted on the chart with distinct colors, enabling traders to visually assess market conditions. The strategy also provides optional plotting of the previous day's VWAP for added context.
Use Cases:
Ideal for traders looking to engage in long-only positions within trending markets.
Suitable for intraday trading strategies or longer-term approaches based on market volatility.
Customization Options:
Users can adjust the standard deviation values, profit target, and time gap to tailor the strategy to their specific trading style and market conditions.
Note: As with any trading strategy, it is important to conduct thorough backtesting and analysis before live trading. Market conditions can change, and past performance does not guarantee future results.
PTS - Bollinger Bands with Trailing StopPTS - Bollinger Bands with Trailing Stop Strategy
Overview
The "PTS - Bollinger Bands with Trailing Stop" strategy is designed to capitalize on strong bullish market movements by combining the Bollinger Bands indicator with a dynamic trailing stop based on the Average True Range (ATR). This strategy aims to enter long positions during upward breakouts and protect profits through an adaptive exit mechanism.
Key Features
1. Bollinger Bands Indicator
Basis Moving Average Type: Choose from SMA, EMA, SMMA, WMA, or VWMA for the Bollinger Bands' basis line. Length: Adjustable period for calculating the moving average and standard deviation (default is 20). Standard Deviation Multiplier (StdDev): Determines the width of the bands (default is 2.0). Source: Select the price data used for calculations (default is the closing price).
2. Entry Conditions
The strategy enters a long position when the closing price crosses above the upper Bollinger Band , indicating strong upward momentum.
3. Exit Conditions
Trailing Stop Loss: Implemented using ATR to adjust dynamically with market volatility. ATR Length: Period for calculating ATR (default is 14). ATR Multiplier for Trailing Stop: Determines how closely the trailing stop follows the price (default is 2.0). Close Below Lower Bollinger Band: The strategy exits the long position if the closing price crosses below the lower Bollinger Band .
4. Risk Management
Commission and Slippage: Commission is set at 0.1%; slippage is set to 3. Position Sizing: Uses 100% of equity per trade (adjustable).
5. Date Range Filter
Specify the time period during which the strategy is active. Start Date: January 1, 2018. End Date: December 31, 2069.
Customizable Inputs
BB Length: Adjust the period for Bollinger Bands calculation. BB StdDev: Modify the standard deviation multiplier. Basis MA Type: Select the moving average type. Source: Choose the price data source. Offset: Shift the Bollinger Bands on the chart. ATR Length: Set the period for ATR calculation. ATR Multiplier for Trailing Stop: Adjust the trailing stop sensitivity.
Thought for 1m 7s
Description for the "PTS - Bollinger Bands with Trailing Stop" Strategy
PTS - Bollinger Bands with Trailing Stop Strategy
Overview
The "PTS - Bollinger Bands with Trailing Stop" strategy is designed to capitalize on strong bullish market movements by combining the Bollinger Bands indicator with a dynamic trailing stop based on the Average True Range (ATR). This strategy aims to enter long positions during upward breakouts and protect profits through an adaptive exit mechanism.
Key Features
1. Bollinger Bands Indicator
Basis Moving Average Type: Choose from SMA, EMA, SMMA, WMA, or VWMA for the Bollinger Bands' basis line. Length: Adjustable period for calculating the moving average and standard deviation (default is 20). Standard Deviation Multiplier (StdDev): Determines the width of the bands (default is 2.0). Source: Select the price data used for calculations (default is the closing price).
2. Entry Conditions
The strategy enters a long position when the closing price crosses above the upper Bollinger Band , indicating strong upward momentum.
3. Exit Conditions
Trailing Stop Loss: Implemented using ATR to adjust dynamically with market volatility. ATR Length: Period for calculating ATR (default is 14). ATR Multiplier for Trailing Stop: Determines how closely the trailing stop follows the price (default is 2.0). Close Below Lower Bollinger Band: The strategy exits the long position if the closing price crosses below the lower Bollinger Band .
4. Risk Management
Commission and Slippage: Commission is set at 0.1%; slippage is set to 3. Position Sizing: Uses 100% of equity per trade (adjustable).
5. Date Range Filter
Specify the time period during which the strategy is active. Start Date: January 1, 2018. End Date: December 31, 2069.
Customizable Inputs
BB Length: Adjust the period for Bollinger Bands calculation. BB StdDev: Modify the standard deviation multiplier. Basis MA Type: Select the moving average type. Source: Choose the price data source. Offset: Shift the Bollinger Bands on the chart. ATR Length: Set the period for ATR calculation. ATR Multiplier for Trailing Stop: Adjust the trailing stop sensitivity.
How the Strategy Works
1. Initialization
Calculates Bollinger Bands and ATR based on selected parameters.
2. Entry Logic
Opens a long position when the closing price exceeds the upper Bollinger Band.
3. Exit Logic
Uses a trailing stop loss based on ATR. Exits if the closing price drops below the lower Bollinger Band.
4. Date Filtering
Executes trades only within the specified date range.
Advantages
Adaptive Risk Management: Trailing stop adjusts to market volatility. Simplicity: Clear entry and exit signals. Customizable Parameters: Tailor the strategy to different assets or conditions.
Considerations
Aggressive Position Sizing: Using 100% equity per trade is high-risk. Market Conditions: Best in trending markets; may produce false signals in sideways markets. Backtesting: Always test on historical data before live trading.
Disclaimer
This strategy is intended for educational and informational purposes only. Trading involves significant risk, and past performance is not indicative of future results. Assess your financial situation and consult a financial advisor if necessary.
Usage Instructions
1. Apply the Strategy: Add it to your TradingView chart. 2. Configure Inputs: Adjust parameters to suit your style and asset. 3. Analyze Backtest Results: Use the Strategy Tester. 4. Optimize Parameters: Experiment with input values. 5. Risk Management: Evaluate position sizing and incorporate risk controls.
Final Notes
The "PTS - Bollinger Bands with Trailing Stop" strategy provides a framework to leverage momentum breakouts while managing risk through adaptive trailing stops. Customize and test thoroughly to align with your trading objectives.
