Friday Bond Short StrategyStrategy: Friday Bond Short Strategy (1H Timeframe)
Objective:
This strategy aims to open short positions on a specified day and hour (Eastern Time) and close those positions on another specified day and hour. The background color of the chart will turn green when a position is active, providing a visual cue of an open trade.
Parameters:
1. Entry Day:
• Defines the day of the week on which the short position will be opened.
• Value: 6 for Friday (Pine Script’s weekday numbering: Monday = 2, Friday = 6).
2. Entry Hour:
• Specifies the hour (Eastern Time) when the short position will be opened.
• Value: 13 for 13:00 ET (1:00 PM).
3. Exit Day:
• Defines the day of the week on which the short position will be closed.
• Value: 2 for Monday.
4. Exit Hour:
• Specifies the hour (Eastern Time) when the position will be closed.
• Value: 13 for 13:00 ET (1:00 PM).
How It Works:
1. Time Adjustment to Eastern Time:
• The script converts all time references to Eastern Time (America/New_York) to ensure the strategy operates according to the desired time zone.
2. Entry Conditions:
• The strategy checks if the current day of the week matches the specified entry_day and if the current hour matches the specified entry_hour.
• If both conditions are met, a short position is opened (strategy.entry("Short", strategy.short)).
3. Exit Conditions:
• Similarly, the strategy checks if the current day of the week matches the specified exit_day and if the current hour matches the specified exit_hour.
• If both conditions are met, the open short position is closed (strategy.close("Short")).
4. Background Color:
• The background color of the chart is adjusted based on whether there is an open position:
• Green Background: If the strategy has an open position (strategy.position_size > 0), the background is set to light green.
• No Background Color: If there is no open position, the background color is not set (na).
Summary:
The Friday Bond Short Strategy is designed to enter short positions on Fridays at 1:00 PM ET and close them on Mondays at 1:00 PM ET. The chart background color turns green when a short position is active, providing a clear visual indication of when the strategy is engaged in a trade.
Cari dalam skrip untuk "the strat"
HilalimSB Strategy HilalimSB A Wedding Gift 🌙
What is HilalimSB🌙?
First of all, as mentioned in the title, HilalimSB is a wedding gift.
HilalimSB - Revealing the Secrets of the Trend
HilalimSB is a powerful indicator designed to help investors analyze market trends and optimize trading strategies. Designed to uncover the secrets at the heart of the trend, HilalimSB stands out with its unique features and impressive algorithm.
Hilalim Algorithm and Fixed ATR Value:
HilalimSB is equipped with a special algorithm called "Hilalim" to detect market trends. This algorithm can delve into the depths of price movements to determine the direction of the trend and provide users with the ability to predict future price movements. Additionally, HilalimSB uses its own fixed Average True Range (ATR) value. ATR is an indicator that measures price movement volatility and is often used to determine the strength of a trend. The fixed ATR value of HilalimSB has been tested over long periods and its reliability has been proven. This allows users to interpret the signals provided by the indicator more reliably.
ATR Calculation Steps
1.True Range Calculation:
+ The True Range (TR) is the greatest of the following three values:
1. Current high minus current low
2. Current high minus previous close (absolute value)
3. Current low minus previous close (absolute value)
2.Average True Range (ATR) Calculation:
-The initial ATR value is calculated as the average of the TR values over a specified period
(typically 14 periods).
-For subsequent periods, the ATR is calculated using the following formula:
ATRt=(ATRt−1×(n−1)+TRt)/n
Where:
+ ATRt is the ATR for the current period,
+ ATRt−1 is the ATR for the previous period,
+ TRt is the True Range for the current period,
+ n is the number of periods.
Pine Script to Calculate ATR with User-Defined Length and Multiplier
Here is the Pine Script code for calculating the ATR with user-defined X length and Y multiplier:
//@version=5
indicator("Custom ATR", overlay=false)
// User-defined inputs
X = input.int(14, minval=1, title="ATR Period (X)")
Y = input.float(1.0, title="ATR Multiplier (Y)")
// True Range calculation
TR1 = high - low
TR2 = math.abs(high - close )
TR3 = math.abs(low - close )
TR = math.max(TR1, math.max(TR2, TR3))
// ATR calculation
ATR = ta.rma(TR, X)
// Apply multiplier
customATR = ATR * Y
// Plot the ATR value
plot(customATR, title="Custom ATR", color=color.blue, linewidth=2)
This code can be added as a new Pine Script indicator in TradingView, allowing users to calculate and display the ATR on the chart according to their specified parameters.
HilalimSB's Distinction from Other ATR Indicators
HilalimSB emerges with its unique Average True Range (ATR) value, presenting itself to users. Equipped with a proprietary ATR algorithm, this indicator is released in a non-editable form for users. After meticulous testing across various instruments with predetermined period and multiplier values, it is made available for use.
ATR is acknowledged as a critical calculation tool in the financial sector. The ATR calculation process of HilalimSB is conducted as a result of various research efforts and concrete data-based computations. Therefore, the HilalimSB indicator is published with its proprietary ATR values, unavailable for modification.
The ATR period and multiplier values provided by HilalimSB constitute the fundamental logic of a trading strategy. This unique feature aids investors in making informed decisions.
Visual Aesthetics and Clear Charts:
HilalimSB provides a user-friendly interface with clear and impressive graphics. Trend changes are highlighted with vibrant colors and are visually easy to understand. You can choose colors based on eye comfort, allowing you to personalize your trading screen for a more enjoyable experience. While offering a flexible approach tailored to users' needs, HilalimSB also promises an aesthetic and professional experience.
Strong Signals and Buy/Sell Indicators:
After completing test operations, HilalimSB produces data at various time intervals. However, we would like to emphasize to users that based on our studies, it provides the best signals in 1-hour chart data. HilalimSB produces strong signals to identify trend reversals. Buy or sell points are clearly indicated, allowing users to develop and implement trading strategies based on these signals.
For example, let's imagine you wanted to open a position on BTC on 2023.11.02. You are aware that you need to calculate which of the buying or selling transactions would be more profitable. You need support from various indicators to open a position. Based on the analysis and calculations it has made from the data it contains, HilalimSB would have detected that the graph is more suitable for a selling position, and by producing a sell signal at the most ideal selling point at 08:00 on 2023.11.02 (UTC+3 Istanbul), it would have informed you of the direction the graph would follow, allowing you to benefit positively from a 2.56% decline.
Technology and Innovation:
HilalimSB aims to enhance the trading experience using the latest technology. With its innovative approach, it enables users to discover market opportunities and support their decisions. Thus, investors can make more informed and successful trades. Real-Time Data Analysis: HilalimSB analyzes market data in real-time and identifies updated trends instantly. This allows users to make more informed trading decisions by staying informed of the latest market developments. Continuous Update and Improvement: HilalimSB is constantly updated and improved. New features are added and existing ones are enhanced based on user feedback and market changes. Thus, HilalimSB always aims to provide the latest technology and the best user experience.
Social Order and Intrinsic Motivation:
Negative trends such as widespread illegal gambling and uncontrolled risk-taking can have adverse financial effects on society. The primary goal of HilalimSB is to counteract these negative trends by guiding and encouraging users with data-driven analysis and calculable investment systems. This allows investors to trade more consciously and safely.
What is HilalimSB Strategy🌙?
HilalimSB Strategy is a strategy that is supported by the HilalimSB algorithm created by the creator of HilalimSB and continues transactions with take profit and stop loss levels determined by users who strategically and automatically open transactions as a result of the data it receives and automatically closes transactions under necessary conditions. It is a first in the tradingview world with its unique take profit and stop loss markings. HilalimSB Strategy is open to users' initiatives and is a trading strategy developed on BTC.
What does the HilalimSB Strategy target?
The main purpose of HilalimSB Strategy is to reduce the transaction load of traders and to be integrated into various brokerage firms and operated by automatic trading bots, and it is aimed to serve this purpose. In addition to the strategies currently available in the markets, HilalimSB Strategy offers a useful infrastructure to traders with its useful interface. HilalimSB Strategy, which was decided to be published as a result of various calculations, was offered to the users with its unique visual effects after the completion of the testing procedures under market conditions.
HilalimSB Strategy and Heikin Ashi
HilalimSB Strategy produces data in Heikin Ashi chart types, but since Heikin Ashi chart types have their own calculation method, HilalimSB Strategy has been published in a way that cannot produce data in this chart type due to HilalimSB Strategy's ideology of appealing to all types of users, and any confusion that may arise is prevented in this way.
After the necessary conditions determined by the creator of HilalimSB are met, HilalimSB Heikin Ashi will be shared exclusively with invited users only, upon request, to users who request an invitation.
Differences between HilalimSB Strategy and HilalimSB
HilalimSB Strategy has been shared as a strategy and its features have been explained above. HilalimSB is a trading indicator and this is the main difference between them.We can explain it briefly this way.
Here are the differences between indicators and strategies:
1.Purpose and Use:
Indicators: Analyze market data to provide information about price movements and trends. They typically generate buy and sell signals and give traders clues about when to make trades in the market.
Strategies: These are plans for trading based on specific rules. They use signals from indicators and other market data to execute buy and sell transactions.
2.Features:
Indicators: Operate independently and are based on specific mathematical formulas. Examples include moving averages, RSI, and MACD.
Strategies: Combine one or more indicators and other market analysis tools to create a comprehensive trading plan. This plan determines entry and exit points, risk management, and trade size.
3.Scope:
Indicators: Are single analysis tools focusing on specific time frames or price movements.
Strategies: Are comprehensive trading plans that typically involve multiple trades over a certain period.
4.Decision Making:
Indicators: Provide information to traders and help in the decision-making process.
Strategies: Are direct decision-making mechanisms that execute trades automatically according to predetermined rules.
5.Automation:
Indicators: Are mostly interpreted manually and used based on the trader’s discretion.
Strategies: Can be used in automated trading systems and execute trades automatically according to the set rules.
The shared image is a 1-hour chart of BTCUSDC.P determined by the user as 1 percent take profit and 1 percent stop loss. And transactions were opened on Binance with the commission rate determined as 0.017 for the USDC trading pair.
HilalimSB Strategy, which presents users with completely concrete data, has proven itself in testing processes and is a project of SB that aims to reach all user profiles.🌙
Supertrend Advance Pullback StrategyHandbook for the Supertrend Advance Strategy
1. Introduction
Purpose of the Handbook:
The main purpose of this handbook is to serve as a comprehensive guide for traders and investors who are looking to explore and harness the potential of the Supertrend Advance Strategy. In the rapidly changing financial market, having the right tools and strategies at one's disposal is crucial. Whether you're a beginner hoping to dive into the world of trading or a seasoned investor aiming to optimize and diversify your portfolio, this handbook offers the insights and methodologies you need. By the end of this guide, readers should have a clear understanding of how the Supertrend Advance Strategy works, its benefits, potential pitfalls, and practical application in various trading scenarios.
Overview of the Supertrend Advance Pullback Strategy:
At its core, the Supertrend Advance Strategy is an evolution of the popular Supertrend Indicator. Designed to generate buy and sell signals in trending markets, the Supertrend Indicator has been a favorite tool for many traders around the world. The Advance Strategy, however, builds upon this foundation by introducing enhanced mechanisms, filters, and methodologies to increase precision and reduce false signals.
1. Basic Concept:
The Supertrend Advance Strategy relies on a combination of price action and volatility to determine the potential trend direction. By assessing the average true range (ATR) in conjunction with specific price points, this strategy aims to highlight the potential starting and ending points of market trends.
2. Methodology:
Unlike the traditional Supertrend Indicator, which primarily focuses on closing prices and ATR, the Advance Strategy integrates other critical market variables, such as volume, momentum oscillators, and perhaps even fundamental data, to validate its signals. This multidimensional approach ensures that the generated signals are more reliable and are less prone to market noise.
3. Benefits:
One of the main benefits of the Supertrend Advance Strategy is its ability to filter out false breakouts and minor price fluctuations, which can often lead to premature exits or entries in the market. By waiting for a confluence of factors to align, traders using this advanced strategy can increase their chances of entering or exiting trades at optimal points.
4. Practical Applications:
The Supertrend Advance Strategy can be applied across various timeframes, from intraday trading to swing trading and even long-term investment scenarios. Furthermore, its flexible nature allows it to be tailored to different asset classes, be it stocks, commodities, forex, or cryptocurrencies.
In the subsequent sections of this handbook, we will delve deeper into the intricacies of this strategy, offering step-by-step guidelines on its application, case studies, and tips for maximizing its efficacy in the volatile world of trading.
As you journey through this handbook, we encourage you to approach the Supertrend Advance Strategy with an open mind, testing and tweaking it as per your personal trading style and risk appetite. The ultimate goal is not just to provide you with a new tool but to empower you with a holistic strategy that can enhance your trading endeavors.
2. Getting Started
Navigating the financial markets can be a daunting task without the right tools. This section is dedicated to helping you set up the Supertrend Advance Strategy on one of the most popular charting platforms, TradingView. By following the steps below, you'll be able to integrate this strategy into your charts and start leveraging its insights in no time.
Setting up on TradingView:
TradingView is a web-based platform that offers a wide range of charting tools, social networking, and market data. Before you can apply the Supertrend Advance Strategy, you'll first need a TradingView account. If you haven't set one up yet, here's how:
1. Account Creation:
• Visit TradingView's official website.
• Click on the "Join for free" or "Sign up" button.
• Follow the registration process, providing the necessary details and setting up your login credentials.
2. Navigating the Dashboard:
• Once logged in, you'll be taken to your dashboard. Here, you'll see a variety of tools, including watchlists, alerts, and the main charting window.
• To begin charting, type in the name or ticker of the asset you're interested in the search bar at the top.
3. Configuring Chart Settings:
• Before integrating the Supertrend Advance Strategy, familiarize yourself with the chart settings. This can be accessed by clicking the 'gear' icon on the top right of the chart window.
• Adjust the chart type, time intervals, and other display settings to your preference.
Integrating the Strategy into a Chart:
Now that you're set up on TradingView, it's time to integrate the Supertrend Advance Strategy.
1. Accessing the Pine Script Editor:
• Located at the top-center of your screen, you'll find the "Pine Editor" tab. Click on it.
• This is where custom strategies and indicators are scripted or imported.
2. Loading the Supertrend Advance Strategy Script:
• Depending on whether you have the script or need to find it, there are two paths:
• If you have the script: Copy the Supertrend Advance Strategy script, and then paste it into the Pine Editor.
• If searching for the script: Click on the “Indicators” icon (looks like a flame) at the top of your screen, and then type “Supertrend Advance Strategy” in the search bar. If available, it will show up in the list. Simply click to add it to your chart.
3. Applying the Strategy:
• After pasting or selecting the Supertrend Advance Strategy in the Pine Editor, click on the “Add to Chart” button located at the top of the editor. This will overlay the strategy onto your main chart window.
4. Configuring Strategy Settings:
• Once the strategy is on your chart, you'll notice a small settings ('gear') icon next to its name in the top-left of the chart window. Click on this to access settings.
• Here, you can adjust various parameters of the Supertrend Advance Strategy to better fit your trading style or the specific asset you're analyzing.
5. Interpreting Signals:
• With the strategy applied, you'll now see buy/sell signals represented on your chart. Take time to familiarize yourself with how these look and behave over various timeframes and market conditions.
3. Strategy Overview
What is the Supertrend Advance Strategy?
The Supertrend Advance Strategy is a refined version of the classic Supertrend Indicator, which was developed to aid traders in spotting market trends. The strategy utilizes a combination of data points, including average true range (ATR) and price momentum, to generate buy and sell signals.
In essence, the Supertrend Advance Strategy can be visualized as a line that moves with the price. When the price is above the Supertrend line, it indicates an uptrend and suggests a potential buy position. Conversely, when the price is below the Supertrend line, it hints at a downtrend, suggesting a potential selling point.
Strategy Goals and Objectives:
1. Trend Identification: At the core of the Supertrend Advance Strategy is the goal to efficiently and consistently identify prevailing market trends. By recognizing these trends, traders can position themselves to capitalize on price movements in their favor.
2. Reducing Noise: Financial markets are often inundated with 'noise' - short-term price fluctuations that can mislead traders. The Supertrend Advance Strategy aims to filter out this noise, allowing for clearer decision-making.
3. Enhancing Risk Management: With clear buy and sell signals, traders can set more precise stop-loss and take-profit points. This leads to better risk management and potentially improved profitability.
4. Versatility: While primarily used for trend identification, the strategy can be integrated with other technical tools and indicators to create a comprehensive trading system.
Type of Assets/Markets to Apply the Strategy:
1. Equities: The Supertrend Advance Strategy is highly popular among stock traders. Its ability to capture long-term trends makes it particularly useful for those trading individual stocks or equity indices.
2. Forex: Given the 24-hour nature of the Forex market and its propensity for trends, the Supertrend Advance Strategy is a valuable tool for currency traders.
3. Commodities: Whether it's gold, oil, or agricultural products, commodities often move in extended trends. The strategy can help in identifying and capitalizing on these movements.
4. Cryptocurrencies: The volatile nature of cryptocurrencies means they can have pronounced trends. The Supertrend Advance Strategy can aid crypto traders in navigating these often tumultuous waters.
5. Futures & Options: Traders and investors in derivative markets can utilize the strategy to make more informed decisions about contract entries and exits.
It's important to note that while the Supertrend Advance Strategy can be applied across various assets and markets, its effectiveness might vary based on market conditions, timeframe, and the specific characteristics of the asset in question. As always, it's recommended to use the strategy in conjunction with other analytical tools and to backtest its effectiveness in specific scenarios before committing to trades.
4. Input Settings
Understanding and correctly configuring input settings is crucial for optimizing the Supertrend Advance Strategy for any specific market or asset. These settings, when tweaked correctly, can drastically impact the strategy's performance.
Grouping Inputs:
Before diving into individual input settings, it's important to group similar inputs. Grouping can simplify the user interface, making it easier to adjust settings related to a specific function or indicator.
Strategy Choice:
This input allows traders to select from various strategies that incorporate the Supertrend indicator. Options might include "Supertrend with RSI," "Supertrend with MACD," etc. By choosing a strategy, the associated input settings for that strategy become available.
Supertrend Settings:
1. Multiplier: Typically, a default value of 3 is used. This multiplier is used in the ATR calculation. Increasing it makes the Supertrend line further from prices, while decreasing it brings the line closer.
2. Period: The number of bars used in the ATR calculation. A common default is 7.
EMA Settings (Exponential Moving Average):
1. Period: Defines the number of previous bars used to calculate the EMA. Common periods are 9, 21, 50, and 200.
2. Source: Allows traders to choose which price (Open, Close, High, Low) to use in the EMA calculation.
RSI Settings (Relative Strength Index):
1. Length: Determines how many periods are used for RSI calculation. The standard setting is 14.
2. Overbought Level: The threshold at which the asset is considered overbought, typically set at 70.
3. Oversold Level: The threshold at which the asset is considered oversold, often at 30.
MACD Settings (Moving Average Convergence Divergence):
1. Short Period: The shorter EMA, usually set to 12.
2. Long Period: The longer EMA, commonly set to 26.
3. Signal Period: Defines the EMA of the MACD line, typically set at 9.
CCI Settings (Commodity Channel Index):
1. Period: The number of bars used in the CCI calculation, often set to 20.
2. Overbought Level: Typically set at +100, denoting overbought conditions.
3. Oversold Level: Usually set at -100, indicating oversold conditions.
SL/TP Settings (Stop Loss/Take Profit):
1. SL Multiplier: Defines the multiplier for the average true range (ATR) to set the stop loss.
2. TP Multiplier: Defines the multiplier for the average true range (ATR) to set the take profit.
Filtering Conditions:
This section allows traders to set conditions to filter out certain signals. For example, one might only want to take buy signals when the RSI is below 30, ensuring they buy during oversold conditions.
Trade Direction and Backtest Period:
1. Trade Direction: Allows traders to specify whether they want to take long trades, short trades, or both.
2. Backtest Period: Specifies the time range for backtesting the strategy. Traders can choose from options like 'Last 6 months,' 'Last 1 year,' etc.
It's essential to remember that while default settings are provided for many of these tools, optimal settings can vary based on the market, timeframe, and trading style. Always backtest new settings on historical data to gauge their potential efficacy.
5. Understanding Strategy Conditions
Developing an understanding of the conditions set within a trading strategy is essential for traders to maximize its potential. Here, we delve deep into the logic behind these conditions, using the Supertrend Advance Strategy as our focal point.
Basic Logic Behind Conditions:
Every strategy is built around a set of conditions that provide buy or sell signals. The conditions are based on mathematical or statistical methods and are rooted in the study of historical price data. The fundamental idea is to recognize patterns or behaviors that have been profitable in the past and might be profitable in the future.
Buy and Sell Conditions:
1. Buy Conditions: Usually formulated around bullish signals or indicators suggesting upward price momentum.
2. Sell Conditions: Centered on bearish signals or indicators indicating downward price momentum.
Simple Strategy:
The simple strategy could involve using just the Supertrend indicator. Here:
• Buy: When price closes above the Supertrend line.
• Sell: When price closes below the Supertrend line.
Pullback Strategy:
This strategy capitalizes on price retracements:
• Buy: When the price retraces to the Supertrend line after a bullish signal and is supported by another bullish indicator.
• Sell: When the price retraces to the Supertrend line after a bearish signal and is confirmed by another bearish indicator.
Indicators Used:
EMA (Exponential Moving Average):
• Logic: EMA gives more weight to recent prices, making it more responsive to current price movements. A shorter-period EMA crossing above a longer-period EMA can be a bullish sign, while the opposite is bearish.
RSI (Relative Strength Index):
• Logic: RSI measures the magnitude of recent price changes to analyze overbought or oversold conditions. Values above 70 are typically considered overbought, and values below 30 are considered oversold.
MACD (Moving Average Convergence Divergence):
• Logic: MACD assesses the relationship between two EMAs of a security’s price. The MACD line crossing above the signal line can be a bullish signal, while crossing below can be bearish.
CCI (Commodity Channel Index):
• Logic: CCI compares a security's average price change with its average price variation. A CCI value above +100 may mean the price is overbought, while below -100 might signify an oversold condition.
And others...
As the strategy expands or contracts, more indicators might be added or removed. The crucial point is to understand the core logic behind each, ensuring they align with the strategy's objectives.
Logic Behind Each Indicator:
1. EMA: Emphasizes recent price movements; provides dynamic support and resistance levels.
2. RSI: Indicates overbought and oversold conditions based on recent price changes.
3. MACD: Showcases momentum and direction of a trend by comparing two EMAs.
4. CCI: Measures the difference between a security's price change and its average price change.
Understanding strategy conditions is not just about knowing when to buy or sell but also about comprehending the underlying market dynamics that those conditions represent. As you familiarize yourself with each condition and indicator, you'll be better prepared to adapt and evolve with the ever-changing financial markets.
6. Trade Execution and Management
Trade execution and management are crucial aspects of any trading strategy. Efficient execution can significantly impact profitability, while effective management can preserve capital during adverse market conditions. In this section, we'll explore the nuances of position entry, exit strategies, and various Stop Loss (SL) and Take Profit (TP) methodologies within the Supertrend Advance Strategy.
Position Entry:
Effective trade entry revolves around:
1. Timing: Enter at a point where the risk-reward ratio is favorable. This often corresponds to confirmatory signals from multiple indicators.
2. Volume Analysis: Ensure there's adequate volume to support the movement. Volume can validate the strength of a signal.
3. Confirmation: Use multiple indicators or chart patterns to confirm the entry point. For instance, a buy signal from the Supertrend indicator can be confirmed with a bullish MACD crossover.
Position Exit Strategies:
A successful exit strategy will lock in profits and minimize losses. Here are some strategies:
1. Fixed Time Exit: Exiting after a predetermined period.
2. Percentage-based Profit Target: Exiting after a certain percentage gain.
3. Indicator-based Exit: Exiting when an indicator gives an opposing signal.
Percentage-based SL/TP:
• Stop Loss (SL): Set a fixed percentage below the entry price to limit potential losses.
• Example: A 2% SL on an entry at $100 would trigger a sell at $98.
• Take Profit (TP): Set a fixed percentage above the entry price to lock in gains.
• Example: A 5% TP on an entry at $100 would trigger a sell at $105.
Supertrend-based SL/TP:
• Stop Loss (SL): Position the SL at the Supertrend line. If the price breaches this line, it could indicate a trend reversal.
• Take Profit (TP): One could set the TP at a point where the Supertrend line flattens or turns, indicating a possible slowdown in momentum.
Swing high/low-based SL/TP:
• Stop Loss (SL): For a long position, set the SL just below the recent swing low. For a short position, set it just above the recent swing high.
• Take Profit (TP): For a long position, set the TP near a recent swing high or resistance. For a short position, near a swing low or support.
And other methods...
1. Trailing Stop Loss: This dynamic SL adjusts with the price movement, locking in profits as the trade moves in your favor.
2. Multiple Take Profits: Divide the position into segments and set multiple TP levels, securing profits in stages.
3. Opposite Signal Exit: Exit when another reliable indicator gives an opposite signal.
Trade execution and management are as much an art as they are a science. They require a blend of analytical skill, discipline, and intuition. Regularly reviewing and refining your strategies, especially in light of changing market conditions, is crucial to maintaining consistent trading performance.
7. Visual Representations
Visual tools are essential for traders, as they simplify complex data into an easily interpretable format. Properly analyzing and understanding the plots on a chart can provide actionable insights and a more intuitive grasp of market conditions. In this section, we’ll delve into various visual representations used in the Supertrend Advance Strategy and their significance.
Understanding Plots on the Chart:
Charts are the primary visual aids for traders. The arrangement of data points, lines, and colors on them tell a story about the market's past, present, and potential future moves.
1. Data Points: These represent individual price actions over a specific timeframe. For instance, a daily chart will have data points showing the opening, closing, high, and low prices for each day.
2. Colors: Used to indicate the nature of price movement. Commonly, green is used for bullish (upward) moves and red for bearish (downward) moves.
Trend Lines:
Trend lines are straight lines drawn on a chart that connect a series of price points. Their significance:
1. Uptrend Line: Drawn along the lows, representing support. A break below might indicate a trend reversal.
2. Downtrend Line: Drawn along the highs, indicating resistance. A break above might suggest the start of a bullish trend.
Filled Areas:
These represent a range between two values on a chart, usually shaded or colored. For instance:
1. Bollinger Bands: The area between the upper and lower band is filled, giving a visual representation of volatility.
2. Volume Profile: Can show a filled area representing the amount of trading activity at different price levels.
Stop Loss and Take Profit Lines:
These are horizontal lines representing pre-determined exit points for trades.
1. Stop Loss Line: Indicates the level at which a trade will be automatically closed to limit losses. Positioned according to the trader's risk tolerance.
2. Take Profit Line: Denotes the target level to lock in profits. Set according to potential resistance (for long trades) or support (for short trades) or other technical factors.
Trailing Stop Lines:
A trailing stop is a dynamic form of stop loss that moves with the price. On a chart:
1. For Long Trades: Starts below the entry price and moves up with the price but remains static if the price falls, ensuring profits are locked in.
2. For Short Trades: Starts above the entry price and moves down with the price but remains static if the price rises.
Visual representations offer traders a clear, organized view of market dynamics. Familiarity with these tools ensures that traders can quickly and accurately interpret chart data, leading to more informed decision-making. Always ensure that the visual aids used resonate with your trading style and strategy for the best results.
8. Backtesting
Backtesting is a fundamental process in strategy development, enabling traders to evaluate the efficacy of their strategy using historical data. It provides a snapshot of how the strategy would have performed in past market conditions, offering insights into its potential strengths and vulnerabilities. In this section, we'll explore the intricacies of setting up and analyzing backtest results and the caveats one must be aware of.
Setting Up Backtest Period:
1. Duration: Determine the timeframe for the backtest. It should be long enough to capture various market conditions (bullish, bearish, sideways). For instance, if you're testing a daily strategy, consider a period of several years.
2. Data Quality: Ensure the data source is reliable, offering high-resolution and clean data. This is vital to get accurate backtest results.
3. Segmentation: Instead of a continuous period, sometimes it's helpful to backtest over distinct market phases, like a particular bear or bull market, to see how the strategy holds up in different environments.
Analyzing Backtest Results:
1. Performance Metrics: Examine metrics like the total return, annualized return, maximum drawdown, Sharpe ratio, and others to gauge the strategy's efficiency.
2. Win Rate: It's the ratio of winning trades to total trades. A high win rate doesn't always signify a good strategy; it should be evaluated in conjunction with other metrics.
3. Risk/Reward: Understand the average profit versus the average loss per trade. A strategy might have a low win rate but still be profitable if the average gain far exceeds the average loss.
4. Drawdown Analysis: Review the periods of losses the strategy could incur and how long it takes, on average, to recover.
9. Tips and Best Practices
Successful trading requires more than just knowing how a strategy works. It necessitates an understanding of when to apply it, how to adjust it to varying market conditions, and the wisdom to recognize and avoid common pitfalls. This section offers insightful tips and best practices to enhance the application of the Supertrend Advance Strategy.
When to Use the Strategy:
1. Market Conditions: Ideally, employ the Supertrend Advance Strategy during trending market conditions. This strategy thrives when there are clear upward or downward trends. It might be less effective during consolidative or sideways markets.
2. News Events: Be cautious around significant news events, as they can cause extreme volatility. It might be wise to avoid trading immediately before and after high-impact news.
3. Liquidity: Ensure you are trading in assets/markets with sufficient liquidity. High liquidity ensures that the price movements are more reflective of genuine market sentiment and not due to thin volume.
Adjusting Settings for Different Markets/Timeframes:
1. Markets: Each market (stocks, forex, commodities) has its own characteristics. It's essential to adjust the strategy's parameters to align with the market's volatility and liquidity.
2. Timeframes: Shorter timeframes (like 1-minute or 5-minute charts) tend to have more noise. You might need to adjust the settings to filter out false signals. Conversely, for longer timeframes (like daily or weekly charts), you might need to be more responsive to genuine trend changes.
3. Customization: Regularly review and tweak the strategy's settings. Periodic adjustments can ensure the strategy remains optimized for the current market conditions.
10. Frequently Asked Questions (FAQs)
Given the complexities and nuances of the Supertrend Advance Strategy, it's only natural for traders, both new and seasoned, to have questions. This section addresses some of the most commonly asked questions regarding the strategy.
1. What exactly is the Supertrend Advance Strategy?
The Supertrend Advance Strategy is an evolved version of the traditional Supertrend indicator. It's designed to provide clearer buy and sell signals by incorporating additional indicators like EMA, RSI, MACD, CCI, etc. The strategy aims to capitalize on market trends while minimizing false signals.
2. Can I use the Supertrend Advance Strategy for all asset types?
Yes, the strategy can be applied to various asset types like stocks, forex, commodities, and cryptocurrencies. However, it's crucial to adjust the settings accordingly to suit the specific characteristics and volatility of each asset type.
3. Is this strategy suitable for day trading?
Absolutely! The Supertrend Advance Strategy can be adjusted to suit various timeframes, making it versatile for both day trading and long-term trading. Remember to fine-tune the settings to align with the timeframe you're trading on.
4. How do I deal with false signals?
No strategy is immune to false signals. However, by combining the Supertrend with other indicators and adhering to strict risk management protocols, you can minimize the impact of false signals. Always use stop-loss orders and consider filtering trades with additional confirmation signals.
5. Do I need any prior trading experience to use this strategy?
While the Supertrend Advance Strategy is designed to be user-friendly, having a foundational understanding of trading and market analysis can greatly enhance your ability to employ the strategy effectively. If you're a beginner, consider pairing the strategy with further education and practice on demo accounts.
6. How often should I review and adjust the strategy settings?
There's no one-size-fits-all answer. Some traders adjust settings weekly, while others might do it monthly. The key is to remain responsive to changing market conditions. Regular backtesting can give insights into potential required adjustments.
7. Can the Supertrend Advance Strategy be automated?
Yes, many traders use algorithmic trading platforms to automate their strategies, including the Supertrend Advance Strategy. However, always monitor automated systems regularly to ensure they're operating as intended.
8. Are there any markets or conditions where the strategy shouldn't be used?
The strategy might generate more false signals in markets that are consolidative or range-bound. During significant news events or times of unexpected high volatility, it's advisable to tread with caution or stay out of the market.
9. How important is backtesting with this strategy?
Backtesting is crucial as it allows traders to understand how the strategy would have performed in the past, offering insights into potential profitability and areas of improvement. Always backtest any new setting or tweak before applying it to live trades.
10. What if the strategy isn't working for me?
No strategy guarantees consistent profits. If it's not working for you, consider reviewing your settings, seeking expert advice, or complementing the Supertrend Advance Strategy with other analysis methods. Remember, continuous learning and adaptation are the keys to trading success.
Other comments
Value of combining several indicators in this script and how they work together
Diversification of Signals: Just as diversifying an investment portfolio can reduce risk, using multiple indicators can offer varied perspectives on potential price movements. Each indicator can capture a different facet of the market, ensuring that traders are not overly reliant on a single data point.
Confirmation & Reduced False Signals: A common challenge with many indicators is the potential for false signals. By requiring confirmation from multiple indicators before acting, the chances of acting on a false signal can be significantly reduced.
Flexibility Across Market Conditions: Different indicators might perform better under different market conditions. For example, while moving averages might excel in trending markets, oscillators like RSI might be more useful during sideways or range-bound conditions. A mashup strategy can potentially adapt better to varying market scenarios.
Comprehensive Analysis: With multiple indicators, traders can gauge trend strength, momentum, volatility, and potential market reversals all at once, providing a holistic view of the market.
How do the different indicators in the Supertrend Advance Strategy work together?
Supertrend: This is primarily a trend-following indicator. It provides traders with buy and sell signals based on the volatility of the price. When combined with other indicators, it can filter out noise and give more weight to strong, confirmed trends.
EMA (Exponential Moving Average): EMA gives more weight to recent price data. It can be used to identify the direction and strength of a trend. When the price is above the EMA, it's generally considered bullish, and vice versa.
RSI (Relative Strength Index): An oscillator that measures the magnitude of recent price changes to evaluate overbought or oversold conditions. By cross-referencing with other indicators like EMA or MACD, traders can spot potential reversals or confirmations of a trend.
MACD (Moving Average Convergence Divergence): This indicator identifies changes in the strength, direction, momentum, and duration of a trend in a stock's price. When the MACD line crosses above the signal line, it can be a bullish sign, and when it crosses below, it can be bearish. Pairing MACD with Supertrend can provide dual confirmation of a trend.
CCI (Commodity Channel Index): Initially developed for commodities, CCI can indicate overbought or oversold conditions. It can be used in conjunction with other indicators to determine entry and exit points.
In essence, the synergy of these indicators provides a balanced, comprehensive approach to trading. Each indicator offers its unique lens into market conditions, and when they align, it can be a powerful indication of a trading opportunity. This combination not only reduces the potential drawbacks of each individual indicator but leverages their strengths, aiming for more consistent and informed trading decisions.
Backtesting and Default Settings
• This indicator has been optimized to be applied for 1 hour-charts. However, the underlying principles of this strategy are supply and demand in the financial markets and the strategy can be applied to all timeframes. Daytraders can use the 1min- or 5min charts, swing-traders can use the daily charts.
• This strategy has been designed to identify the most promising, highest probability entries and trades for each stock or other financial security.
• The combination of the qualifiers results in a highly selective strategy which only considers the most promising swing-trading entries. As a result, you will normally only find a low number of trades for each stock or other financial security per year in case you apply this strategy for the daily charts. Shorter timeframes will result in a higher number of trades / year.
• Consequently, traders need to apply this strategy for a full watchlist rather than just one financial security.
• Default properties: RSI on (length 14, RSI buy level 50, sell level 50), EMA, RSI, MACD on, type of strategy pullback, SL/TP type: ATR (length 10, factor 3), trade direction both, quantity 5, take profit swing hl 5.1, highest / lowest lookback 2, enable ATR trail (ATR length 10, SL ATR multiplier 1.4, TP multiplier 2.1, lookback = 4, trade direction = both).
[MT] Strategy Backtest Template| Initial Release | | EN |
An update of my old script, this script is designed so that it can be used as a template for all those traders who want to save time when programming their strategy and backtesting it, having functions already programmed that in normal development would take you more time to program, with this template you can simply add your favorite indicator and thus be able to take advantage of all the functions that this template has.
🔴Stop Loss and 🟢Take Profit:
No need to mention that it is a Stop Loss and a Take Profit, within these functions we find the options of: fixed percentage (%), fixed price ($), ATR, especially for Stop Loss we find the Pivot Points, in addition to this, the price range between the entry and the Stop Loss can be converted into a trailing stop loss, instead, especially for the Take Profit we have an option to choose a 1:X ratio that complements very well with the Pivot Points.
📈Heikin Ashi Based Entries:
Heikin Ashi entries are trades that are calculated based on Heikin Ashi candles but their price is executed to Japanese candles, thus avoiding false results that occur in Heikin candlestick charts, this making in certain cases better results in strategies that are executed with this option compared to Japanese candlesticks.
📊Dashboard:
A more visual and organized way to see the results and necessary data produced by our strategy, among them we can see the dates between which our operations are made regardless if you have activated some time filter, usual data such as Profit, Win Rate, Profit factor are also displayed in this panel, additionally data such as the total number of operations, how many were gains and how many losses, the average profit and loss for each operation and finally the maximum profits and losses followed, which are data that will be very useful to us when we elaborate our strategies.
Feel free to use this template to program your own strategies, if you find errors or want to request a new feature let me know in the comments or through my social networks found in my tradingview profile.
| Update 1.1 | | EN |
➕Additions: '
Time sessions filter and days of the week filter added to the time filter section.
Option to add leverage to the strategy.
5 Moving Averages, RSI, Stochastic RSI, ADX, and Parabolic Sar have been added as indicators for the strategy.
You can choose from the 6 available indicators the way to trade, entry alert or entry filter.
Added the option of ATR for Take Profit.
Ticker information and timeframe are now displayed on the dashboard.
Added display customization and color customization of indicator plots.
Added customization of display and color plots of trades displayed on chart.
📝Changes:
Now when activating the time filter it is optional to add a start or end date and time, being able to only add a start date or only an end date.
Operation plots have been changed from plot() to line creation with line.new().
Indicator plots can now be controlled from the "plots" section.
Acceptable and deniable range of profit, winrate and profit factor can now be chosen from the "plots" section to be displayed on the dashboard.
Aesthetic changes in the section separations within the settings section and within the code itself.
The function that made the indicators give inputs based on heikin ashi candles has been changed, see the code for more information.
⚙️Fixes:
Dashboard label now projects correctly on all timeframes including custom timeframes.
Removed unnecessary lines and variables to take up less code space.
All code in general has been optimized to avoid the use of variables, unnecessary lines and avoid unnecessary calculations, freeing up space to declare more variables and be able to use fewer lines of code.
| Lanzamiento Inicial | | ES |
Una actualización de mi antiguo script, este script está diseñado para que pueda ser usado como una plantilla para todos aquellos traders que quieran ahorrar tiempo al programar su estrategia y hacer un backtesting de ella, teniendo funciones ya programadas que en el desarrollo normal te tomaría más tiempo programar, con esta plantilla puedes simplemente agregar tu indicador favorito y así poder aprovechar todas las funciones que tiene esta plantilla.
🔴Stop Loss y 🟢Take Profit:
No hace falta mencionar que es un Stop Loss y un Take Profit, dentro de estas funciones encontramos las opciones de: porcentaje fijo (%), precio fijo ($), ATR, en especial para Stop Loss encontramos los Pivot Points, adicionalmente a esto, el rango de precio entre la entrada y el Stop Loss se puede convertir en un trailing stop loss, en cambio, especialmente para el Take Profit tenemos una opción para elegir un ratio 1:X que se complementa muy bien con los Pivot Points.
📈Entradas Basadas en Heikin Ashi:
Las entradas Heikin Ashi son operaciones que son calculados en base a las velas Heikin Ashi pero su precio esta ejecutado a velas japonesas, evitando así́ los falsos resultados que se producen en graficas de velas Heikin, esto haciendo que en ciertos casos se obtengan mejores resultados en las estrategias que son ejecutadas con esta opción en comparación con las velas japonesas.
📊Panel de Control:
Una manera más visual y organizada de ver los resultados y datos necesarios producidos por nuestra estrategia, entre ellos podemos ver las fechas entre las que se hacen nuestras operaciones independientemente si se tiene activado algún filtro de tiempo, datos usuales como el Profit, Win Rate, Profit factor también son mostrados en este panel, adicionalmente se agregaron datos como el número total de operaciones, cuantos fueron ganancias y cuantos perdidas, el promedio de ganancias y pérdidas por cada operación y por ultimo las máximas ganancias y pérdidas seguidas, que son datos que nos serán muy útiles al elaborar nuestras estrategias.
Siéntete libre de usar esta plantilla para programar tus propias estrategias, si encuentras errores o quieres solicitar una nueva función házmelo saber en los comentarios o a través de mis redes sociales que se encuentran en mi perfil de tradingview.
| Actualización 1.1 | | ES |
➕Añadidos:
Filtro de sesiones de tiempo y filtro de días de la semana agregados al apartado de filtro de tiempo.
Opción para agregar apalancamiento a la estrategia.
5 Moving Averages, RSI, Stochastic RSI, ADX, y Parabolic Sar se han agregado como indicadores para la estrategia.
Puedes escoger entre los 6 indicadores disponibles la forma de operar, alerta de entrada o filtro de entrada.
Añadido la opción de ATR para Take Profit.
La información del ticker y la temporalidad ahora se muestran en el dashboard.
Añadido personalización de visualización y color de los plots de indicadores.
Añadido personalización de visualización y color de los plots de operaciones mostradas en grafica.
📝Cambios:
Ahora al activar el filtro de tiempo es opcional añadir una fecha y hora de inicio o fin, pudiendo únicamente agregar una fecha de inicio o solamente una fecha de fin.
Los plots de operaciones han cambiados de plot() a creación de líneas con line.new().
Los plots de indicadores ahora se pueden controlar desde el apartado "plots".
Ahora se puede elegir el rango aceptable y negable de profit, winrate y profit factor desde el apartado "plots" para mostrarse en el dashboard.
Cambios estéticos en las separaciones de secciones dentro del apartado de configuraciones y dentro del propio código.
Se ha cambiado la función que hacía que los indicadores dieran entradas en base a velas heikin ashi, mire el código para más información.
⚙️Arreglos:
El dashboard label ahora se proyecta correctamente en todas las temporalidades incluyendo las temporalidades personalizadas.
Se han eliminado líneas y variables innecesarias para ocupar menos espacio en el código.
Se ha optimizado todo el código en general para evitar el uso de variables, líneas innecesarias y evitar los cálculos innecesarios, liberando espacio para declarar más variables y poder utilizar menos líneas de código.
Dow Theory Trend StrategyDow Theory Trend Strategy (Pine Script)
Overview
This Pine Script implements a trading strategy based on the core principles of Dow Theory. It visually identifies trends (uptrend, downtrend) by analyzing pivot highs and lows and executes trades when the trend direction changes. This script is an improved version that features refined trend determination logic and strategy implementation.
Core Concept: Dow Theory
The script uses a fundamental Dow Theory concept for trend identification:
Uptrend: Characterized by a series of Higher Highs (HH) and Higher Lows (HL).
Downtrend: Characterized by a series of Lower Highs (LH) and Lower Lows (LL).
How it Works
Pivot Point Detection:
It uses the built-in ta.pivothigh() and ta.pivotlow() functions to identify significant swing points (potential highs and lows) in the price action.
The pivotLookback input determines the number of bars to the left and right required to confirm a pivot. Note that this introduces a natural lag (equal to pivotLookback bars) before a pivot is confirmed.
Improved Trend Determination:
The script stores the last two confirmed pivot highs and the last two confirmed pivot lows.
An Uptrend (trendDirection = 1) is confirmed only when the latest pivot high is higher than the previous one (HH) AND the latest pivot low is higher than the previous one (HL).
A Downtrend (trendDirection = -1) is confirmed only when the latest pivot high is lower than the previous one (LH) AND the latest pivot low is lower than the previous one (LL).
Key Improvement: If neither a clear uptrend nor a clear downtrend is confirmed based on the latest pivots, the script maintains the previous trend state (trendDirection := trendDirection ). This differs from simpler implementations that might switch to a neutral/range state (e.g., trendDirection = 0) more frequently. This approach aims for smoother trend following, acknowledging that trends often persist through periods without immediate new HH/HL or LH/LL confirmations.
Trend Change Detection:
The script monitors changes in the trendDirection variable.
changedToUp becomes true when the trend shifts to an Uptrend (from Downtrend or initial state).
changedToDown becomes true when the trend shifts to a Downtrend (from Uptrend or initial state).
Visualizations
Background Color: The chart background is colored to reflect the currently identified trend:
Blue: Uptrend (trendDirection == 1)
Red: Downtrend (trendDirection == -1)
Gray: Initial state or undetermined (trendDirection == 0)
Pivot Points (Optional): Small triangles (shape.triangledown/shape.triangleup) can be displayed above pivot highs and below pivot lows if showPivotPoints is enabled.
Trend Change Signals (Optional): Labels ("▲ UP" / "▼ DOWN") can be displayed when a trend change is confirmed (changedToUp / changedToDown) if showTrendChange is enabled. These visually mark the potential entry points for the strategy.
Strategy Logic
Entry Conditions:
Enters a long position (strategy.long) using strategy.entry("L", ...) when changedToUp becomes true.
Enters a short position (strategy.short) using strategy.entry("S", ...) when changedToDown becomes true.
Position Management: The script uses strategy.entry(), which automatically handles position reversal. If the strategy is long and a short signal occurs, strategy.entry() will close the long position and open a new short one (and vice-versa).
Inputs
pivotLookback: The number of bars on each side to confirm a pivot high/low. Higher values mean pivots are confirmed later but may be more significant.
showPivotPoints: Toggle visibility of pivot point markers.
showTrendChange: Toggle visibility of the trend change labels ("▲ UP" / "▼ DOWN").
Key Improvements from Original
Smoother Trend Logic: The trend state persists unless a confirmed reversal pattern (opposite HH/HL or LH/LL) occurs, reducing potential whipsaws in choppy markets compared to logic that frequently resets to neutral.
Strategy Implementation: Converted from a pure indicator to a strategy capable of executing backtests and potentially live trades based on the Dow Theory trend changes.
Disclaimer
Dow Theory signals are inherently lagging due to the nature of pivot confirmation.
The effectiveness of the strategy depends heavily on the market conditions and the chosen pivotLookback setting.
This script serves as a basic template. Always perform thorough backtesting and implement proper risk management (e.g., stop-loss, take-profit, position sizing) before considering any live trading.
Volume Block Order AnalyzerCore Concept
The Volume Block Order Analyzer is a sophisticated Pine Script strategy designed to detect and analyze institutional money flow through large block trades. It identifies unusually high volume candles and evaluates their directional bias to provide clear visual signals of potential market movements.
How It Works: The Mathematical Model
1. Volume Anomaly Detection
The strategy first identifies "block trades" using a statistical approach:
```
avgVolume = ta.sma(volume, lookbackPeriod)
isHighVolume = volume > avgVolume * volumeThreshold
```
This means a candle must have volume exceeding the recent average by a user-defined multiplier (default 2.0x) to be considered a significant block trade.
2. Directional Impact Calculation
For each block trade identified, its price action determines direction:
- Bullish candle (close > open): Positive impact
- Bearish candle (close < open): Negative impact
The magnitude of impact is proportional to the volume size:
```
volumeWeight = volume / avgVolume // How many times larger than average
blockImpact = (isBullish ? 1.0 : -1.0) * (volumeWeight / 10)
```
This creates a normalized impact score typically ranging from -1.0 to 1.0, scaled by dividing by 10 to prevent excessive values.
3. Cumulative Impact with Time Decay
The key innovation is the cumulative impact calculation with decay:
```
cumulativeImpact := cumulativeImpact * impactDecay + blockImpact
```
This mathematical model has important properties:
- Recent block trades have stronger influence than older ones
- Impact gradually "fades" at rate determined by decay factor (default 0.95)
- Sustained directional pressure accumulates over time
- Opposing pressure gradually counteracts previous momentum
Trading Logic
Signal Generation
The strategy generates trading signals based on momentum shifts in institutional order flow:
1. Long Entry Signal: When cumulative impact crosses from negative to positive
```
if ta.crossover(cumulativeImpact, 0)
strategy.entry("Long", strategy.long)
```
*Logic: Institutional buying pressure has overcome selling pressure, indicating potential upward movement*
2. Short Entry Signal: When cumulative impact crosses from positive to negative
```
if ta.crossunder(cumulativeImpact, 0)
strategy.entry("Short", strategy.short)
```
*Logic: Institutional selling pressure has overcome buying pressure, indicating potential downward movement*
3. Exit Logic: Positions are closed when the cumulative impact moves against the position
```
if cumulativeImpact < 0
strategy.close("Long")
```
*Logic: The original signal is no longer valid as institutional flow has reversed*
Visual Interpretation System
The strategy employs multiple visualization techniques:
1. Color Gradient Bar System:
- Deep green: Strong buying pressure (impact > 0.5)
- Light green: Moderate buying pressure (0.1 < impact ≤ 0.5)
- Yellow-green: Mild buying pressure (0 < impact ≤ 0.1)
- Yellow: Neutral (impact = 0)
- Yellow-orange: Mild selling pressure (-0.1 < impact ≤ 0)
- Orange: Moderate selling pressure (-0.5 < impact ≤ -0.1)
- Red: Strong selling pressure (impact ≤ -0.5)
2. Dynamic Impact Line:
- Plots the cumulative impact as a line
- Line color shifts with impact value
- Line movement shows momentum and trend strength
3. Block Trade Labels:
- Marks significant block trades directly on the chart
- Shows direction and volume amount
- Helps identify key moments of institutional activity
4. Information Dashboard:
- Current impact value and signal direction
- Average volume benchmark
- Count of significant block trades
- Min/Max impact range
Benefits and Use Cases
This strategy provides several advantages:
1. Institutional Flow Detection: Identifies where large players are positioning themselves
2. Early Trend Identification: Often detects institutional accumulation/distribution before major price movements
3. Market Context Enhancement: Provides deeper insight than simple price action alone
4. Objective Decision Framework: Quantifies what might otherwise be subjective observations
5. Adaptive to Market Conditions: Works across different timeframes and instruments by using relative volume rather than absolute thresholds
Customization Options
The strategy allows users to fine-tune its behavior:
- Volume Threshold: How unusual a volume spike must be to qualify
- Lookback Period: How far back to measure average volume
- Impact Decay Factor: How quickly older trades lose influence
- Visual Settings: Labels and line width customization
This sophisticated yet intuitive strategy provides traders with a window into institutional activity, helping identify potential trend changes before they become obvious in price action alone.
[3Commas] DCA Bot TesterDCA Bot Tester
🔷What it does: A tool designed to simulate the behavior of a Dollar Cost Averaging (DCA) strategy based on input signals from a source indicator. Additionally, it enables you to send activation signals to 3Commas Bots via TradingView webhooks.
🔷Who is it for: This tool is ideal for those who want a visual representation and strategy report of how a DCA Bot would perform under specific conditions. By adjusting the parameters, you can assess whether the strategy aligns with your risk/reward expectations before implementation, helping you save time and protect your capital.
🔷How does it work: The tool leverages a pyramiding function to simulate price averaging, mimicking how a DCA Bot operates. It calculates volume-based averaging and, upon reaching the target, closes the positions. Conversely, if the target isn't reached, a Stop Loss is triggered, potentially resulting in significant losses if improperly configured.
🔷Why It’s Unique
Easy visualization of DCA Bot entry and exit points according to user preferences.
DCA Bot Summary table same as the one shown in the new 3Commas interface.
Use plots from other indicators as Entry Trigger Source, with a small modification of the code.
Option to Review message format before sending Signals to 3Commas. Compatibility with Multi-Pair, and futures contract pairs.
Option to filter signals by session and day according to the user’s timezone.
👉 Before continuing with the explanation of the tool, please take a few minutes to read this information, paying special attention to the risks of using DCA strategies.
DCA Bot: What is it, how does it work, and what are its advantages and risks?
A DCA Bot is an automated tool designed to simplify and optimize your trading operations, particularly in cryptocurrencies. Based on the concept of Dollar Cost Averaging (DCA) , this bot implements scaled strategies that allow you to distribute your investments intelligently. The key lies in dividing your capital into multiple orders, known as base orders and safety orders, which are executed at different price levels depending on market conditions.
These bots are highly customizable, meaning you can adapt them to your goals and trading style, whether you're operating Long (expecting a price increase) or Short (expecting a price decrease). Their primary purpose is to reduce the impact of entries that move against the estimated direction and ensure you achieve a more favorable average price.
🔸 Key Features of DCA Bots
Customizable configuration: DCA bots allow you to adjust the size of your initial investment, the number of safety orders, and the price levels at which these orders execute. These orders can be equal or incremental, depending on your risk tolerance.
Scaled safety orders: If the asset's price moves against your position, the bot executes safety orders at strategic levels to average your entry price and increase your chances of closing in profit.
Automatic Take Profit: When the predefined profit level is reached, the bot closes the position, ensuring net gains by averaging all entries made using the DCA strategy.
Stop Loss option: To protect your capital, you can set a stop loss level that limits losses if the market moves drastically against your position.
Flexibility: Bots can integrate with 3Commas technical indicators or external signals from TradingView, allowing you to trade in any trend, whether bullish or bearish.
Support for multiple assets: You can trade cryptocurrency pairs and exchanges compatible with 3Commas, offering a wide range of possibilities to diversify your strategies.
✅ Advantages of DCA Bots
Time-saving automation: DCA bots eliminate the need for constant market monitoring, executing your trades automatically and efficiently based on predefined settings.
Favorable averages in volatile markets: By averaging your entries, the bot can offer more competitive prices even under adverse market conditions. This increases your chances of recovering a position and closing it profitably.
Advanced capital management: With customizable settings, you can adjust the size of base and safety orders to optimize capital usage and reduce risk.
Additional protection: The ability to set a stop loss ensures your losses are limited, safeguarding your capital in extreme scenarios.
⚠️ Risks of Using a DCA Bot
Requires significant capital: Safety orders can accumulate quickly if the price moves against your position. This issue is compounded if increasing amounts are used for safety orders, which can immobilize large portions of capital in adverse markets.
Markets lacking clear direction: During consolidation periods or erratic movements, the bot may generate unrealized losses and make position recovery difficult.
Opportunity cost: Investing in an asset that doesn't show favorable behavior can prevent you from seizing opportunities in other markets.
Emotional pressure: Large investments in advanced stages of the DCA strategy can cause stress, especially if an asset takes too long to reach your take profit level.
Dependence on market recovery: DCA assumes that the price will eventually move in your favor, which does not always happen, especially in assets without solid fundamentals.
📖 Key Considerations for Effectively Using a DCA Bot
Use small amounts for your base and safety orders: Setting small initial orders not only limits capital usage but also allows you to manage multiple bots simultaneously, maximizing portfolio diversification.
Capital management: Define a clear budget and never risk more than you are willing to lose. This is essential for maintaining sustainable operations.
Select assets with strong fundamentals: Apply DCA to assets you understand and that have solid fundamentals and a proven historical growth record. Additionally, analyze each cryptocurrency's fundamentals: What problem does it solve? Does it have a clear use case? Is it viable in the long term? These questions will help you make more informed decisions.
Diversification: Do not concentrate all your capital on a single asset or strategy. Spread your risk across multiple bots or assets.
Monitor regularly: While bots are automated and eliminate the need to monitor the market constantly, it is essential to monitor the bots themselves to ensure they are performing as expected. This includes reviewing their performance and making adjustments if market conditions change. Remember, the goal is to automate trades, but active bot management is crucial to avoid surprises.
A DCA Bot is a powerful tool for traders looking to automate their strategies and reduce the impact of market fluctuations. However, like any tool, its success depends on how it is configured and used. By applying solid capital management principles, carefully selecting assets, and using small amounts in your orders, you can maximize its potential and minimize risks.
🔷FEATURES & HOW TO USE
🔸Strategy: Here you must select the type of signal you are going to analyze and send signals to the DCA Bot, either Long for buy signals or Short for sell signals. This must match the Bot created in 3Commas.
🔸Add a Source Indicator for Entry Triggers
Tradingview allows us to use indicator plots as a source in other indicators, we will use this functionality so that the buy or sell signals of an indicator are processed by the DCA Bot Tester.
In this EXAMPLE we will use a simple strategy that uses a Donchian Channel (DC) and an Exponential Moving Average (EMA).
Trigger to buy or long signal will be when: the price closes above the previous upper level and the average of the upper and lower level (basis) is greater than the EMA.
Trigger sell or short signal will be when: the price closes below the previous lower level and the average of the upper and lower level (basis) is less than the EMA.
trigger_buy = ta.crossover (close,upper ) and basis > ema and barstate.isconfirmed
trigger_sell = ta.crossunder(close,lower ) and basis < ema and barstate.isconfirmed
Then we create the plots that will be used as input source in the DCA Bot Tester indicator.
When a buy condition is given the plot "🟢 Trigger Buy" will have a value of 1 otherwise it will remain at 0.
When a sell condition is given the plot "🔴 Trigger Sell" will have a value of -1 otherwise it will remain at 0.
plot(trigger_buy ? 1 : 0 , '🟢 Trigger Buy' , color = na, display = display.data_window)
plot(trigger_sell? -1 : 0 , '🔴 Trigger Sell', color = na, display = display.data_window)
Here you have the complete code so you can use it and do tests. Basically you just have to define the buy or sell conditions of your preferred indicator or strategy and then create the plots with the same format that will be used in DCA Bot Tester.
//@version=6
indicator(title="Simple Strategy Example", overlay= false)
// Indicator and Signal Triggers
length = input.int(10, title = "DC Length" , display = display.none)
length_ema = input.int(50, title = "EMA Length", display = display.none)
lower = ta.lowest (length)
upper = ta.highest(length)
ema = ta.ema (close, length_ema)
basis = math.avg (upper, lower)
plot(basis, "Basis", color = color.orange, display = display.all-display.status_line)
plot(upper, "Upper", color = color.blue , display = display.all-display.status_line)
plot(lower, "Lower", color = color.blue , display = display.all-display.status_line)
plot(ema , "EMA" , color = color.red , display = display.all-display.status_line)
candlecol = open < close ? color.teal : color.red
plotcandle(open, high, low, close, title='Candles', color = candlecol, wickcolor = candlecol, bordercolor = candlecol, display = display.pane)
trigger_buy = ta.crossover (close,upper ) and basis > ema and barstate.isconfirmed
trigger_sell = ta.crossunder(close,lower ) and basis < ema and barstate.isconfirmed
plotshape(trigger_buy ?close:na, title="Label Buy" , style=shape.labelup , location= location.belowbar, color=color.green, text="B", textcolor=color.white, display=display.pane)
plotshape(trigger_sell?close:na, title="Label Sell", style=shape.labeldown, location= location.abovebar, color=color.red , text="S", textcolor=color.white, display=display.pane)
// ――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――
// 👇 Plots to be used in the DCA Bot Indicator as source triggers.
// ――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――
plot(trigger_buy ? 1 : 0 , '🟢 Trigger Buy' , color = na, display = display.data_window)
plot(trigger_sell? -1 : 0 , '🔴 Trigger Sell', color = na, display = display.data_window)
To use the example code
Open the Pine Editor, paste the code and then click Add to chart.
Then in the Plot Entry Trigger Source option, we will select 🟢 Trigger Buy, as the plot that will give us the buy signals when it is worth 1, otherwise for the sell signals you must change the value to -1 in the Plot Entry Trigger Value and remember to change the strategy mode to Short.
🔸DCA Settings: Here you need to configure the DCA values of the strategy, you can see the meaning of each value in the Settings Section. Once you are satisfied with the tests configure the 3Commas DCA Bot with the same values so that the Summary Table matches the 3Commas Table. Pay close attention to the Total Volume that the Bot will use, according to the amount of Safety Orders you are going to execute, and that all the values in the table adapt to your risk tolerance.
🔸DCA Bot Deal Start: Once you create the Bot in 3Commas with the same settings it will give you a Deal Start Message, you must copy and paste it in this section, verify that it is the same in the summary table, this is used to be sent through tradingview alerts to the Bot and it can process the signals.
🔸DCA Bot Multi-Pair: A Multi-Pair Bot allows you to manage several pairs with a single bot, but you must specify which pair it will run on. You must activate it if you want to use the signals in a DCA Bot Multi-pair. In the text box you must enter (using the 3Commas format) the symbol for each pair before you create the alert so that the bot understands which pair to work on.
In the following image we would be configuring the indicator to send a signal to activate the bot in the BTCUSDT pair using the given format it would be USDT_BTC, but if we wanted to send a signal in another pair we must change the pair in the chart and also in the configuration, an example with ETHUSDT would be USDT_ETH. After this we could create the alert, and the Mult-Pair Bot would detect it correctly.
🔸Strategy Tester Filters: This is useful if you want to test the strategy's result on a certain time window, the indicator will only enter this range. If disabled it will use all historical data available on the chart. If you are going to use the tool to send signals, make sure to disable the Use Custom Test Period. If you want the entries to only run at a certain time and day, in that case make sure that the timezone matches the one you are using in the chart.
🔸Properties: Adjust your initial capital and exchange commission appropriately to achieve realistic results.
🔸Create alerts to trigger the DCA Bot
Check that the message is the same as the one indicated by the DCA Bot.
In the case of Multi-Pair, enable the option to add the symbol with the correct format.
When creating an alert, select Any alert() function call.
Enter the any name of the alert.
Open the Notifications tab and enable Webhook URL
Paste Webhook URL provided by 3Commas looking in the section How to use TradingView custom signals.
Done, alerts will be sent with the correct format automatically to 3Commas.
🔷 INDICATOR SETTINGS
🔸3Commas DCA Bot Settings
Strategy: Select the direction of the strategy to test Long or Short, this must be the same as the Bot created in 3Commas, so that the signals are processed properly.
DCA Bot Deal Start: Copy and paste the message for the deal start signal of the DCA Bot you created in 3Commas. This is the message that will be sent with the alert to the Bot, you must verify that it is the same as the 3Commas bot so that it can process properly so that it executes and starts the trade.
DCA Bot Multi-Pair: A Multi-Pair Bot allows you to manage several pairs with a single bot, but you must specify which pair it will run on.
DCA Bot Summary Table: Here you can activate the display of table as well as change the size, position, text color and background color.
🔸Source Indicator Settings
Plot Entry Trigger Source: Select a Plot for Entries of the Source Indicator. This refers to the Long or Short entry signal that the indicator will use as BO (Base Order).
Plot Entry Trigger Value: Value of the Source Indicator to Deal Start Condition Trigger. The default value is 1, this means that when a signal is given for example Long in the source indicator, we will use 1 or for Short -1 if there is no signal it will be 0 so it will not execute any entry, please review the example code and adjust the indicator you are going to use in the same way.
🔸DCA Settings
Base Order: The Base Order is the first order the bot will create when starting a new deal.
Safety Order: Enter the amount of funds your safety orders will use to average the cost of the asset being traded.Safety orders are also known as Dollar Cost Averaging and help when prices move in the opposite direction to your bot's take profit target.
Safety Orders Deviation %: Enter the percentage difference in price to create the first Safety Order. All Safety Orders are calculated from the price the initial Base Order was filled on the exchange account.
Safety Orders Max Count: This is the total number of Safety Orders the bot is allowed to use per deal that is opened. All Safety Orders created by the bot are placed as Limit Orders on the exchange's order book.
Safety Orders Volume Scale: The Safety Order Volume Scale is used to multiply the amount of funds used by the last Safety Order that was created. Using a larger amount of funds for Safety Orders allows your bot to be more aggressive at Dollar Cost Averaging the price of the asset being traded.
Safety Orders Step Scale: The Safety Order Step Scale is used to multiply the Price Deviation percentage used by the last Safety Order placed on the exchange account. Using a larger value here will reduce the amount of Safety Orders your bot will require to cover a larger move in price in the opposite direction to the active deal's take profit target.
Take Profit %: The Take Profit section offers tools for flexible management of target parameters: automatic profit upon reaching one or more target levels in percentage.
Stop Loss % | Use SL: To enable Stop Loss, please check the "Use SL" box. This is the percentage that price needs to move in the opposite direction to close the deal at a loss. This must be greater than the sum of the deviations from the safety orders.
🔸Strategy Tester Filters
Use Custom Test Period: When enabled signals only works in the selected time window.. If disabled it will use all historical data available on the chart.
Test Start and End: Once the Custom Test Period is enabled, here you select the start and end date that you want to analyze.
Session Filter | Days | Background: Here you can choose a time zone in which signals will be sent or your strategy will be tested, as well as the days and a background of it. It is important that you use the same timezone as your chart so that it matches.
👨🏻💻💭 If this tool helps you, don’t forget to give it a boost! Feel free to share in the comments how you're using it or if you have any questions.
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The information and publications within the 3Commas TradingView account are not meant to be and do not constitute financial, investment, trading, or other types of advice or recommendations supplied or endorsed by 3Commas and any of the parties acting on behalf of 3Commas, including its employees, contractors, ambassadors, etc.
AlgoBuilder [Mean-Reversion] | FractalystWhat's the strategy's purpose and functionality?
This strategy is designed for both traders and investors looking to rely and trade based on historical and backtested data using automation.
The main goal is to build profitable mean-reversion strategies that outperform the underlying asset in terms of returns while minimizing drawdown.
For example, as for a benchmark, if the S&P 500 (SPX) has achieved an estimated 10% annual return with a maximum drawdown of -57% over the past 20 years, using this strategy with different entry and exit techniques, users can potentially seek ways to achieve a higher Compound Annual Growth Rate (CAGR) while maintaining a lower maximum drawdown.
Although the strategy can be applied to all markets and timeframes, it is most effective on stocks, indices, future markets, cryptocurrencies, and commodities and JPY currency pairs given their trending behaviors.
In trending market conditions, the strategy employs a combination of moving averages and diverse entry models to identify and capitalize on upward market movements. It integrates market structure-based moving averages and bands mechanisms across different timeframes and provides exit techniques, including percentage-based and risk-reward (RR) based take profit levels.
Additionally, the strategy has also a feature that includes a built-in probability function for traders who want to implement probabilities right into their trading strategies.
Performance summary, weekly, and monthly tables enable quick visualization of performance metrics like net profit, maximum drawdown, profit factor, average trade, average risk-reward ratio (RR), and more.
This aids optimization to meet specific goals and risk tolerance levels effectively.
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How does the strategy perform for both investors and traders?
The strategy has two main modes, tailored for different market participants: Traders and Investors.
Trading:
1. Trading:
- Designed for traders looking to capitalize on bullish trending markets.
- Utilizes a percentage risk per trade to manage risk and optimize returns.
- Suitable for active trading with a focus on mean-reversion and risk per trade approach.
◓: Mode | %: Risk percentage per trade
3. Investing:
- Geared towards investors who aim to capitalize on bullish trending markets without using leverage while mitigating the asset's maximum drawdown.
- Utilizes pre-define percentage of the equity to buy, hold, and manage the asset.
- Focuses on long-term growth and capital appreciation by fully investing in the asset during bullish conditions.
- ◓: Mode | %: Risk not applied (In investing mode, the strategy uses 10% of equity to buy the asset)
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What's is FRMA? How does the triple bands work? What are the underlying calculations?
Middle Band (FRMA):
The middle band is the core of the FRMA system. It represents the Fractalyst Moving Average, calculated by identifying the most recent external swing highs and lows in the market structure.
By determining these external swing pivot points, which act as significant highs and lows within the market range, the FRMA provides a unique moving average that adapts to market structure changes.
Upper Band:
The upper band shows the average price of the most recent external swing highs.
External swing highs are identified as the highest points between pivot points in the market structure.
This band helps traders identify potential overbought conditions when prices approach or exceed this upper band.
Lower Band:
The lower band shows the average price of the most recent external swing lows.
External swing lows are identified as the lowest points between pivot points in the market structure.
The script utilizes this band to identify potential oversold conditions, triggering entry signals as prices approach or drop below the lower band.
Adjustments Based on User Inputs:
Users can adjust how the upper and lower bands are calculated based on their preferences:
Upper/Lower: This method calculates the average bands using the prices of external swing highs and lows identified in the market.
Percentage Deviation from FRMA: Alternatively, users can opt to calculate the bands based on a percentage deviation from the middle FRMA. This approach provides flexibility to adjust the width of the bands relative to market conditions and volatility.
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What's the purpose of using moving averages in this strategy? What are the underlying calculations?
Using moving averages is a widely-used technique to trade with the trend.
The main purpose of using moving averages in this strategy is to filter out bearish price action and to only take trades when the price is trading ABOVE specified moving averages.
The script uses different types of moving averages with user-adjustable timeframes and periods/lengths, allowing traders to try out different variations to maximize strategy performance and minimize drawdowns.
By applying these calculations, the strategy effectively identifies bullish trends and avoids market conditions that are not conducive to profitable trades.
The MA filter allows traders to choose whether they want a specific moving average above or below another one as their entry condition.
This comparison filter can be turned on (>) or off.
For example, you can set the filter so that MA#1 > MA#2, meaning the first moving average must be above the second one before the script looks for entry conditions. This adds an extra layer of trend confirmation, ensuring that trades are only taken in more favorable market conditions.
⍺: MA Period | Σ: MA Timeframe
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What entry modes are used in this strategy? What are the underlying calculations?
The strategy by default uses two different techniques for the entry criteria with user-adjustable left and right bars: Breakout and Fractal.
1. Breakout Entries :
- The strategy looks for pivot high points with a default period of 3.
- It stores the most recent high level in a variable.
- When the price crosses above this most recent level, the strategy checks if all conditions are met and the bar is closed before taking the buy entry.
◧: Pivot high left bars period | ◨: Pivot high right bars period
2. Fractal Entries :
- The strategy looks for pivot low points with a default period of 3.
- When a pivot low is detected, the strategy checks if all conditions are met and the bar is closed before taking the buy entry.
◧: Pivot low left bars period | ◨: Pivot low right bars period
2. Hunt Entries :
- The strategy identifies a candle that wicks through the lower FRMA band.
- It waits for the next candle to close above the low of the wick candle.
- When this condition is met and the bar is closed, the strategy takes the buy entry.
By utilizing these entry modes, the strategy aims to capitalize on bullish price movements while ensuring that the necessary conditions are met to validate the entry points.
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What type of stop-loss identification method are used in this strategy? What are the underlying calculations?
Initial Stop-Loss:
1. ATR Based:
The Average True Range (ATR) is a method used in technical analysis to measure volatility. It is not used to indicate the direction of price but to measure volatility, especially volatility caused by price gaps or limit moves.
Calculation:
- To calculate the ATR, the True Range (TR) first needs to be identified. The TR takes into account the most current period high/low range as well as the previous period close.
The True Range is the largest of the following:
- Current Period High minus Current Period Low
- Absolute Value of Current Period High minus Previous Period Close
- Absolute Value of Current Period Low minus Previous Period Close
- The ATR is then calculated as the moving average of the TR over a specified period. (The default period is 14).
Example - ATR (14) * 2
⍺: ATR period | Σ: ATR Multiplier
2. ADR Based:
The Average Day Range (ADR) is an indicator that measures the volatility of an asset by showing the average movement of the price between the high and the low over the last several days.
Calculation:
- To calculate the ADR for a particular day:
- Calculate the average of the high prices over a specified number of days.
- Calculate the average of the low prices over the same number of days.
- Find the difference between these average values.
- The default period for calculating the ADR is 14 days. A shorter period may introduce more noise, while a longer period may be slower to react to new market movements.
Example - ADR (20) * 2
⍺: ADR period | Σ: ADR Multiplier
3. PL Based:
This method places the stop-loss at the low of the previous candle.
If the current entry is based on the hunt entry strategy, the stop-loss will be placed at the low of the candle that wicks through the lower FRMA band.
Example:
If the previous candle's low is 100, then the stop-loss will be set at 100.
This method ensures the stop-loss is placed just below the most recent significant low, providing a logical and immediate level for risk management.
Application in Strategy (ATR/ADR):
- The strategy calculates the current bar's ADR/ATR with a user-defined period.
- It then multiplies the ADR/ATR by a user-defined multiplier to determine the initial stop-loss level.
By using these methods, the strategy dynamically adjusts the initial stop-loss based on market volatility, helping to protect against adverse price movements while allowing for enough room for trades to develop.
Each market behaves differently across various timeframes, and it is essential to test different parameters and optimizations to find out which trailing stop-loss method gives you the desired results and performance.
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What type of break-even and take profit identification methods are used in this strategy? What are the underlying calculations?
For Break-Even:
Percentage (%) Based:
Moves the initial stop-loss to the entry price when the price reaches a certain percentage above the entry.
Calculation:
Break-even level = Entry Price * (1 + Percentage / 100)
Example:
If the entry price is $100 and the break-even percentage is 5%, the break-even level is $100 * 1.05 = $105.
Risk-to-Reward (RR) Based:
Moves the initial stop-loss to the entry price when the price reaches a certain RR ratio.
Calculation:
Break-even level = Entry Price + (Initial Risk * RR Ratio)
Example:
If the entry price is $100, the initial risk is $10, and the RR ratio is 2, the break-even level is $100 + ($10 * 2) = $120.
FRMA Based:
Moves the stop-loss to break-even when the price hits the FRMA level at which the entry was taken.
Calculation:
Break-even level = FRMA level at the entry
Example:
If the FRMA level at entry is $102, the break-even level is set to $102 when the price reaches $102.
For TP1 (Take Profit 1):
- You can choose to set a take profit level at which your position gets fully closed or 50% if the TP2 boolean is enabled.
- Similar to break-even, you can select either a percentage (%) or risk-to-reward (RR) based take profit level, allowing you to set your TP1 level as a percentage amount above the entry price or based on RR.
For TP2 (Take Profit 2):
- You can choose to set a take profit level at which your position gets fully closed.
- As with break-even and TP1, you can select either a percentage (%) or risk-to-reward (RR) based take profit level, allowing you to set your TP2 level as a percentage amount above the entry price or based on RR.
When Both Percentage (%) Based and RR Based Take Profit Levels Are Off:
The script will adjust the take profit level to the higher FRMA band set within user inputs.
Calculation:
Take profit level = Higher FRMA band length/timeframe specified by the user.
This ensures that when neither percentage-based nor risk-to-reward-based take profit methods are enabled, the strategy defaults to using the higher FRMA band as the take profit level, providing a consistent and structured approach to profit-taking.
For TP1 and TP2, it's specifying the price levels at which the position is partially or fully closed based on the chosen method (percentage or RR) above the entry price.
These calculations are crucial for managing risk and optimizing profitability in the strategy.
⍺: BE/TP type (%/RR) | Σ: how many RR/% above the current price
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What's the ADR filter? What does it do? What are the underlying calculations?
The Average Day Range (ADR) measures the volatility of an asset by showing the average movement of the price between the high and the low over the last several days.
The period of the ADR filter used in this strategy is tied to the same period you've used for your initial stop-loss.
Users can define the minimum ADR they want to be met before the script looks for entry conditions.
ADR Bias Filter:
- Compares the current bar ADR with the ADR (Defined by user):
- If the current ADR is higher, it indicates that volatility has increased compared to ADR (DbU).(⬆)
- If the current ADR is lower, it indicates that volatility has decreased compared to ADR (DbU).(⬇)
Calculations:
1. Calculate ADR:
- Average the high prices over the specified period.
- Average the low prices over the same period.
- Find the difference between these average values in %.
2. Current ADR vs. ADR (DbU):
- Calculate the ADR for the current bar.
- Calculate the ADR (DbU).
- Compare the two values to determine if volatility has increased or decreased.
By using the ADR filter, the strategy ensures that trades are only taken in favorable market conditions where volatility meets the user's defined threshold, thus optimizing entry conditions and potentially improving the overall performance of the strategy.
>: Minimum required ADR for entry | %: Current ADR comparison to ADR of 14 days ago.
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What's the probability filter? What are the underlying calculations?
The probability filter is designed to enhance trade entries by using buyside liquidity and probability analysis to filter out unfavorable conditions.
This filter helps in identifying optimal entry points where the likelihood of a profitable trade is higher.
Calculations:
1. Understanding Swing highs and Swing Lows
Swing High: A Swing High is formed when there is a high with 2 lower highs to the left and right.
Swing Low: A Swing Low is formed when there is a low with 2 higher lows to the left and right.
2. Understanding the purpose and the underlying calculations behind Buyside, Sellside and Equilibrium levels.
3. Understanding probability calculations
1. Upon the formation of a new range, the script waits for the price to reach and tap into equilibrium or the 50% level. Status: "⏸" - Inactive
2. Once equilibrium is tapped into, the equilibrium status becomes activated and it waits for either liquidity side to be hit. Status: "▶" - Active
3. If the buyside liquidity is hit, the script adds to the count of successful buyside liquidity occurrences. Similarly, if the sellside is tapped, it records successful sellside liquidity occurrences.
5. Finally, the number of successful occurrences for each side is divided by the overall count individually to calculate the range probabilities.
Note: The calculations are performed independently for each directional range. A range is considered bearish if the previous breakout was through a sellside liquidity. Conversely, a range is considered bullish if the most recent breakout was through a buyside liquidity.
Example - BSL > 55%
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What's the range length Filter? What are the underlying calculations?
The range length filter identifies the price distance between buyside and sellside liquidity levels in percentage terms. When enabled, the script only looks for entries when the minimum range length is met. This helps ensure that trades are taken in markets with sufficient price movement.
Calculations:
Range Length (%) = ( ( Buyside Level − Sellside Level ) / Current Price ) ×100
Range Bias Identification:
Bullish Bias: The current range price has broken above the previous external swing high.
Bearish Bias: The current range price has broken below the previous external swing low.
Example - Range length filter is enabled | Range must be above 1%
>: Minimum required range length for entry | %: Current range length percentage in a (Bullish/Bearish) range
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What's the day filter Filter, what does it do?
The day filter allows users to customize the session time and choose the specific days they want to include in the strategy session. This helps traders tailor their strategies to particular trading sessions or days of the week when they believe the market conditions are more favorable for their trading style.
Customize Session Time:
Users can define the start and end times for the trading session.
This allows the strategy to only consider trades within the specified time window, focusing on periods of higher market activity or preferred trading hours.
Select Days:
Users can select which days of the week to include in the strategy.
This feature is useful for excluding days with historically lower volatility or unfavorable trading conditions (e.g., Mondays or Fridays).
Benefits:
Focus on Optimal Trading Periods:
By customizing session times and days, traders can focus on periods when the market is more likely to present profitable opportunities.
Avoid Unfavorable Conditions:
Excluding specific days or times can help avoid trading during periods of low liquidity or high unpredictability, such as major news events or holidays.
Increased Flexibility: The filter provides increased flexibility, allowing traders to adapt the strategy to their specific needs and preferences.
Example - Day filter | Session Filter
θ: Session time | Exchange time-zone
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What tables are available in this script?
Table Type:
- Summary: Provides a general overview, displaying key performance parameters such as Net Profit, Profit Factor, Max Drawdown, Average Trade, Closed Trades and more.
Avg Trade: The sum of money gained or lost by the average trade generated by a strategy. Calculated by dividing the Net Profit by the overall number of closed trades. An important value since it must be large enough to cover the commission and slippage costs of trading the strategy and still bring a profit.
MaxDD: Displays the largest drawdown of losses, i.e., the maximum possible loss that the strategy could have incurred among all of the trades it has made. This value is calculated separately for every bar that the strategy spends with an open position.
Profit Factor: The amount of money a trading strategy made for every unit of money it lost (in the selected currency). This value is calculated by dividing gross profits by gross losses.
Avg RR: This is calculated by dividing the average winning trade by the average losing trade. This field is not a very meaningful value by itself because it does not take into account the ratio of the number of winning vs losing trades, and strategies can have different approaches to profitability. A strategy may trade at every possibility in order to capture many small profits, yet have an average losing trade greater than the average winning trade. The higher this value is, the better, but it should be considered together with the percentage of winning trades and the net profit.
Winrate: The percentage of winning trades generated by a strategy. Calculated by dividing the number of winning trades by the total number of closed trades generated by a strategy. Percent profitable is not a very reliable measure by itself. A strategy could have many small winning trades, making the percent profitable high with a small average winning trade, or a few big winning trades accounting for a low percent profitable and a big average winning trade. Most mean-reversion successful strategies have a percent profitability of 40-80% but are profitable due to risk management control.
BE Trades: Number of break-even trades, excluding commission/slippage.
Losing Trades: The total number of losing trades generated by the strategy.
Winning Trades: The total number of winning trades generated by the strategy.
Total Trades: Total number of taken traders visible your charts.
Net Profit: The overall profit or loss (in the selected currency) achieved by the trading strategy in the test period. The value is the sum of all values from the Profit column (on the List of Trades tab), taking into account the sign.
- Monthly: Displays performance data on a month-by-month basis, allowing users to analyze performance trends over each month.
- Weekly: Displays performance data on a week-by-week basis, helping users to understand weekly performance variations.
- OFF: Hides the performance table.
Profit Color:
- Allows users to set the color for representing profit in the performance table, helping to quickly distinguish profitable periods.
Loss Color:
- Allows users to set the color for representing loss in the performance table, helping to quickly identify loss-making periods.
These customizable tables provide traders with flexible and detailed performance analysis, aiding in better strategy evaluation and optimization.
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User-input styles and customizations:
To facilitate studying historical data, all conditions and rules can be applied to your charts. By plotting background colors on your charts, you'll be able to identify what worked and what didn't in certain market conditions.
Please note that all background colors in the style are disabled by default to enhance visualization.
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How to Use This Algobuilder to Create a Profitable Edge and System:
Choose Your Strategy mode:
- Decide whether you are creating an investing strategy or a trading strategy.
Select a Market:
- Choose a one-sided market such as stocks, indices, or cryptocurrencies.
Historical Data:
- Ensure the historical data covers at least 10 years of price action for robust backtesting.
Timeframe Selection:
- Choose the timeframe you are comfortable trading with. It is strongly recommended to use a timeframe above 15 minutes to minimize the impact of commissions/slippage on your profits.
Set Commission and Slippage:
- Properly set the commission and slippage in the strategy properties according to your broker or prop firm specifications.
Parameter Optimization:
- Use trial and error to test different parameters until you find the performance results you are looking for in the summary table or, preferably, through deep backtesting using the strategy tester.
Trade Count:
- Ensure the number of trades is 100 or more; the higher, the better for statistical significance.
Positive Average Trade:
- Make sure the average trade value is above zero.
(An important value since it must be large enough to cover the commission and slippage costs of trading the strategy and still bring a profit.)
Performance Metrics:
- Look for a high profit factor, and net profit with minimum drawdown.
- Ideally, aim for a drawdown under 20-30%, depending on your risk tolerance.
Refinement and Optimization:
- Try out different markets and timeframes.
- Continue working on refining your edge using the available filters and components to further optimize your strategy.
Automation:
- Once you’re confident in your strategy, you can use the automation section to connect the algorithm to your broker or prop firm.
- Trade a fully automated and backtested trading strategy, allowing for hands-free execution and management.
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What makes this strategy original?
1. Incorporating direct integration of probabilities into the strategy.
2. Utilizing built-in market structure-based moving averages across various timeframes.
4. Offering both investing and trading strategies, facilitating optimization from different perspectives.
5. Automation for efficient execution.
6. Providing a summary table for instant access to key parameters of the strategy.
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How to use automation?
For Traders:
1. Ensure the strategy parameters are properly set based on your optimized parameters.
2. Enter your PineConnector License ID in the designated field.
3. Specify the desired risk level.
4. Provide the Metatrader symbol.
5. Check for chart updates to ensure the automation table appears on the top right corner, displaying your License ID, risk, and symbol.
6. Set up an alert with the strategy selected as Condition and the Message as {{strategy.order.alert_message}}.
7. Activate the Webhook URL in the Notifications section, setting it as the official PineConnector webhook address.
8. Double-check all settings on PineConnector to ensure the connection is successful.
9. Create the alert for entry/exit automation.
For Investors:
1. Ensure the strategy parameters are properly set based on your optimized parameters.
2. Choose "Investing" in the user-input settings.
3. Create an alert with a specified name.
4. Customize the notifications tab to receive alerts via email.
5. Buying/selling alerts will be triggered instantly upon entry or exit order execution.
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Terms and Conditions | Disclaimer
Our charting tools are provided for informational and educational purposes only and should not be construed as financial, investment, or trading advice. They are not intended to forecast market movements or offer specific recommendations. Users should understand that past performance does not guarantee future results and should not base financial decisions solely on historical data.
Built-in components, features, and functionalities of our charting tools are the intellectual property of @Fractalyst Unauthorized use, reproduction, or distribution of these proprietary elements is prohibited.
By continuing to use our charting tools, the user acknowledges and accepts the Terms and Conditions outlined in this legal disclaimer and agrees to respect our intellectual property rights and comply with all applicable laws and regulations.
Strategy - Plus / Connectable [Azullian]Discover the advanced capabilities of Strategy Plus, an essential component of the connectable indicator system designed for fast-paced strategy testing, visualization, and building within TradingView. This enhanced version of our foundational connectable strategy indicator seamlessly integrates with all connectable indicators . By utilizing the TradingView input source as a signal connector , it facilitates the linking of indicators to form a cohesive strategy. Each connectable indicator within the system sends signal weight to the next node, culminating in a comprehensive strategy that incorporates advanced customization options, sophisticated signal interpretation, and elaborate backtest labeling. Strategy Plus stands out by offering improved position management and extensive alert messaging capabilities, ensuring effective strategy refinement and backend integration.
█ DISTINCTIVE FEATURES
The Connectable Strategy Plus enhances risk mitigation within the connectable system through its advanced features and capabilities:
• Refined Signal Input Management: Tailor and precisely connect up to two signal filters with enhanced input flexibility, gain control, and strategic direction settings.
• Strategic Position Investment Control: Optimize positioning with versatile investment bases, custom investment percentages, and direction-specific investments for effective risk management.
• Advanced Exit Stop Loss Configuration: Implement custom stop loss tactics with diverse base modes and trailing options for tailored risk management.
• Strategic Exit Take Profit Settings: Apply precision-driven take profit strategies with various calculation modes and dynamic trailing functionality.
• Calibrated Entry Position Allocation: Optimize investment distribution for entry positions, including DCA and BRO trades, for strategic market response.
• Refined Order Setting Customization: Ensure exchange compliance with adjustable order settings, enhancing backtest accuracy and strategy reliability.
• Comprehensive Condition Settings: Define precise conditions for strategy execution, including date range filtering and order/loss limitations.
• Intuitive Visualization: Enhance strategy clarity with customizable visual elements and trade visualization features.
• Advanced Alert Configurations: Stay informed with comprehensive and customizable alerts for effective backend integration.
• Backend Integration With JSON Format: Leverage elaborate and structured data in JSON format for advanced analytics, enhancing decision-making and strategy optimization outside TradingView.
Let's review the separate parts of this indicator.
█ STRATEGY INPUTS
We've provided 2 inputs for connecting a signal filter or indicators or chains (1→, 2→) which are all set to 'Close' by default.
An input has several controls:
• Enable disable: Toggle the entire input on or off
• Input: Connect indicators or signal filter here, choose indicators with a compatible : Signal connector.
• G - Gain: Increase or reduce the strength of the incoming signal by a factor.
• SM - Signal Mode: Choose a trading direction compatible with the settings in your signal filter
• XM - Exit Mode: Determine when to allow to exit your open trade
○ Always: Doesn't take the restrictions into account, this ignores all the settings chosen in ML or MP
○ Restricted: Use both ML and MP conditions
○ Loss: Use the ML condition only, for example: Position will be exited and the exit signal will be allowed only when the loss exceeds the ML parameter
○ Profit: Use the MP condition only for example: Exits will only be allowed when the profit of the position exceeds the condition of the MP parameter
█ POSITION INVESTMENT
Determine the percentage of your trading budget you would like to use in each position based on the strategy's profit or loss.
• LINVB - Loss Investment Base: Choose which base to use to determine the investment percentage when the strategy is in a loss.
○ Equity: Use the equity as the base for percentage calculation.
○ Initial capital: Use the initial capital as the base for percentage calculation.
• LINV% - Loss Investment Percentage: Set a percentage of the chosen investment base as the investment for a new position.
○ For example, when 10% in loss, and a initial capital of $100, and the investment base is set to equity with a percentage of 50%, your investment will be 50% of $90, $45.
• PINVB - Profit Investment Base: Choose which base to use to determine the investment percentage when the strategy is in profit.
○ Equity: Use the equity as the base for percentage calculation.
○ Initial capital: Use the initial capital as the base for percentage calculation.
• PINV% - Profit Investment Percentage: Set a percentage of the chosen investment base as the investment for a new position.
○ For example, when 10% in profit, and an initial capital of $100, and the investment base is set to equity with a percentage of 100%, your investment will be 100% of $110, $110.
• XINVB - Custom Profit Investment Base: Choose which base to use to determine the investment percentage when the strategy is above a custom profit threshold (XT).
○ Equity: Use the equity as the base for percentage calculation.
○ Initial capital: Use the initial capital as the base for percentage calculation.
• XINV% - Custom Profit Investment Percentage: Set a percentage of the chosen investment base as the investment for a new position.
○ For example, when 100% in profit, exceeding the XT threshold of 50%, and an initial capital of $100, and the investment base is set to equity with a percentage of 50%, your investment will be 50% of $200, $100.
• XT% - Custom Profit Threshold: Determine how much profit triggers these custom profit investment settings.
• ELIB% - Entry Long Investment Base: Following previous settings, you can further restrict the investment according to the long trading direction.
○ For instance, if the previous calculation resulted in $45 to be used as an investment, and you've set the ELIB% to 50%, your long position will use 50% of $45, which is $22.5.
• ESIB% - Entry Short Investment Base: Following previous settings, you can further restrict the investment according to the short trading direction.
○ For example, if the previous calculation resulted in $45 to be used as an investment, and you've set the ESIB% to 50%, your short position will use 50% of $45, which is $22.5.
• RISK% - Risk Percentage:
○ Determine how much of the calculated position investment is at risk when the stop-loss is hit.
- For example, 1% of $45 represents a maximum loss of $0.45.
○ Risk percentage works together with the stop loss and the max leverage.
• MXLVG - Maximum Leverage:
○ Investigate the trading rules for your trading pair and use the maximum allowed amount of leverage.
○ To determine the number of contracts to be bought or sold, considering the stop loss and the specified risk percentage, the maximum leverage available will constrain the amount of leverage utilized to ensure that the maximum risk threshold is not exceeded. For instance, suppose the stop loss is set at 1%, and the risk percentage is defined as 10%. Initially, the calculated leverage to be used would be 10. However, if there is a maximum leverage cap set at 5, it would constrain the calculated leverage of 10 to adhere to the maximum limit of 5.
█ EXIT STOP LOSS
Determine the Stop Loss price based on your selected configuration.
As the stop loss is an integral part of the ordered contracts calculation used in conjunction with the Risk and Max leverage, you'll always need to provide a stop loss price.
• SLLB - Stop Loss Long Base: Choose a stop loss mode for calculating stop loss prices in long positions.
○ Risk: Determines the price using the Risk parameter (RISK%) and maximum leverage (MXLVG). In this case, SLLB% will not have any impact.
○ Price Entry + Offset: Calculates the stop loss price based on a offset percentage (SLLB%) from the entry price of the position.
○ Source: Computes the stop loss price based on an external indicator defined in SLLSRC.
- If this results in an invalid price, the calculation will revert to using the price entry + offset.
○ Source + Offset: Determines the stop loss price based on a positive or negative offset percentage (SLLB%) from an external indicator defined in SLLSRC.
- If this results in an invalid price, the calculation will fall back to using the price entry + offset.
• SLLB% - Stop Loss Long Base Percentage: Define an offset percentage that will be applied in the price entry + offset and source + offset stop loss modes.
• SLLSRC - Stop Loss Long Source: Connect an external indicator as the source for stop loss (only those providing price values eg: bollinger bands, moving averages...).
• SLLT - Stop Loss Long Trailing:
○ Fixed: The initial stop loss will be kept and no trailing stop loss will be applied.
○ Trail Stop: Takes into account all settings defined in SLLB and SLLB% and recalculates them with each candle.
- If a better stop loss is computed, it replaces the existing stop loss. In this mode SLLT% will be disregarded.
○ Trail Stop till BE: Similar to trailing stop mode, but it stops trailing when the stop loss reaches the break-even point.
○ Trail Stop from BE: Similar to trailing stop mode, but it starts trailing when the stop loss reaches the break-even point.
○ Trail Price: Computes the trailing stop loss price based on an offset percentage (SLLT%) from the closing price of the current candle.
- If a better stop loss price is calculated, it will be set as the new stop loss price.
○ Trail Price till BE: Similar to the Trail Price mode, but it stops trailing when the stop loss reaches the break-even point.
○ Trail Price from BE: Similar to Trail Price mode, but it starts trailing when the stop loss reaches the break-even point.
○ Trail Incr: Adapts the trailing stop loss price based on the offset percentage (SLLT%).
- Each price change in favor of your position will incrementally adapt the trailing stop loss with SLLT%.
○ Trail Incr till BE: Similar to the Trail Incr mode, but it stops trailing when the stop loss reaches the break-even point.
• SLLT% - Stop Loss Long Trailing Percentage: This percentage serves as an offset or increment depending on your chosen trailing mode.
• SLSB - Stop Loss Short Base: Functions similarly to SLLB but for short positions.
• SLSB% - Stop Loss Short Base Percentage: Functions similarly to SLLB% but for short positions.
• SLSSRC - Stop Loss Short Source: Functions similarly to SLLSRC but for short positions.
• SLST - Stop Loss Short Trailing: Functions similarly to SLLT but for short positions.
• SLST% - Stop Loss Short Trailing Percentage: Functions similarly to SLLT% but for short positions.
█ EXIT TAKE PROFIT
Determine the Take Profit price based on your selected configuration.
• TPLB - Take Profit Long Base: Choose a take profit mode for calculating take profit prices in long positions.
○ Reward: Determines the take profit price using the Risk parameter (RISK%) and the calculated Stop Loss price and the set reward percentage (TPLB%).
- For example: Risk 1%, Calculated Stop loss price: $90, Entry price: $100, Reward (TPLB%): 2%, will result in a take profit price on $120.
○ Price Entry + Offset: Calculates the take profit price based on a offset percentage (TPLB%) from the entry price of the position.
- For example: Entry price: $100, Offset (TPLB%): 2%, will result in a take profit price on $102.
○ Source: Computes the take profit price based on an external input from another indicator defined in TPLSRC.
- If this results in an invalid price, the calculation will revert to using the price entry + offset.
○ Source + Offset: Determines the take profit price based on a positive or negative offset percentage (TPLB%) from an external indicator inpuy defined in TPLSRC.
- If this results in an invalid price, the calculation will fall back to using the price entry + offset.
• TPLB% - Take Profit Long Base Percentage: Define an offset percentage that will be applied in the price entry + offset and source + offset take profit modes.
• TPLSRC - Take Profit Long Source: Choose to connect an external indicator as the source for take profit (of course only those which provide price values eg: bollinger bands, moving averages... but not oscillators).
• TPLT - Take Profit Long Trailing:
○ Fixed: The initial take profit will be kept and no trailing take profit will be applied.
○ Trail Profit: Takes into account all settings defined in TPLB and TPLB% and recalculates them with each candle.
- If an applicable take profit is computed, it replaces the existing take profit. In this mode TPLT% will be disregarded.
○ Trail Profit till BE: Similar to trailing profit mode, but it stops trailing when the take profit reaches the break-even point.
○ Trail Profit from BE: Similar to trailing profit mode, but it starts trailing when the take profit reaches the break-even point.
○ Trail Price: Computes the trailing take profit price based on an offset percentage (TPLT%) from the closing price of the current candle.
- If an applicable take profit price is calculated, it will be set as the new take profit price.
○ Trail Price till BE: Similar to the Trail Price mode, but it stops trailing when the take profit reaches the break-even point.
○ Trail Price from BE: Similar to Trail Price mode, but it starts trailing when the take profit reaches the break-even point.
○ Trail Incr: Adapts the trailing take profit price based on the offset percentage (TPLT%). Each price change against your position will incrementally adapt the trailing take profit with TPLT%.
○ Trail Incr till BE: Similar to the Trail Incr mode, but it stops trailing when the take profit reaches the break-even point.
• TPLT% - Take Profit Long Trailing Percentage: This percentage serves as an offset or increment depending on your chosen trailing mode.
• TPSB - Take Profit Short Base: Functions similarly to TPLB but for short positions.
• TPSB% - Take Profit Short Base Percentage: Functions similarly to TPLB% but for short positions.
• TPSSRC - Take Profit Short Source: Functions similarly to TPLSRC but for short positions.
• TPST - Take Profit Short Trailing: Functions similarly to TPLT but for short positions.
• TPST% - Take Profit Short Trailing Percentage: Functions similarly to TPLT% but for short positions.
█ ENTRY INVESTMENT DISTRIBUTION
Based on your position investment calculation you can distribute the position investment accross the initial opening trade of the position (SIG%) or the follow up Dollar Cost Averaging (DCA%) or Break Out (BRO%) trades.
For example: SIG%: 10%, DCA%: 45%, BRO%: 45% and the calculated Position Investment is $100, then the initial trade will receive $10, DCA will receive $45, and BRO will receive $45 to work with. Disable BRO and or DCA by setting them to 0%. Keep in mind that the sum of SIG, BRO and DCA may not exceed 100%.
• SIG% - Initial order investment percentage based on the signal: The percentage of the position investment distributed over normal trades.
• DCA% - Dollar Cost Averaging investment percentage: The percentage of the position investment distributed to DCA trades.
• BRO% - Break Out investment percentage: The percentage of the position investment distributed to BRO trades.
█ ENTRY DCA
DCA (Dollar-Cost Averaging) is a risk mitigation strategy where the allocated DCA% budget from the Entry Investment Distribution is distributed among x levels (DCA#) based on calculated prices (DPLM) and order sizes (DOSM), when prices move against your position.
• DCA# - Maximum DCA levels: Set the maximum number of DCA levels.
• DPLM - DCA Price Level Mode: Choose a price level mode that determines at which prices the additional purchases are distributed:
○ Linear: Entry prices are evenly spaced at regular intervals.
○ QuadIn: Entry prices are front-loaded, with more at the beginning and fewer later.
○ QuadOut: Entry prices are back-loaded, with fewer at the beginning and more later.
○ QuadInOut: Entry prices start front-loaded, then become back-loaded.
○ CubicIn: Similar to QuadIn but with a smoother front-loaded distribution.
○ CubicOut: Similar to QuadOut but with a smoother back-loaded distribution.
○ ExpoIn: Entry prices are exponentially increasing, starting small and growing.
○ ExpoOut: Entry prices are exponentially decreasing, starting large and reducing.
○ ExpoInOut: Entry prices start exponentially increasing, then decrease exponentially.
• DOSM - DCA Order Size Mode: Choose a DCA budget distribution mode for order sizes:
○ Linear: Order sizes are evenly spaced at regular intervals.
○ QuadIn: Order sizes are front-loaded, with larger orders at the beginning and smaller ones later.
○ QuadOut: Order sizes are back-loaded, with smaller orders at the beginning and larger ones later.
○ QuadInOut: Order sizes start front-loaded and transition to back-loaded.
○ CubicIn: Similar to QuadIn but with a smoother front-loaded distribution of order sizes.
○ CubicOut: Similar to QuadOut but with a smoother back-loaded distribution of order sizes.
○ ExpoIn: Order sizes exponentially increase, starting small and growing.
○ ExpoOut: Order sizes exponentially decrease, starting large and reducing.
○ ExpoInOut: Order sizes start exponentially increasing, then decrease exponentially.
For a visual representation of the price or order size distribution modes, refer to online easing curves.
█ ENTRY BRO
BRO (Break Out) is a risk mitigation strategy where the allocated BRO% budget from the Entry Investment Distribution is distributed among x levels (BRO#) based on calculated prices (BPLM) and order sizes (BOSM), when prices move in favor of your position.
• BRO# - Maximum BRO levels: Set the maximum number of BRO levels.
• BPLM - BRO Price Level Mode: Choose a price level mode that determines at which prices the additional purchases are distributed:
○ Distribution easing modes work similar as the DCA easing modes.
• BOSM - BRO Order Size Mode: Choose a BRO budget distribution mode for order sizes:
○ Distribution easing modes work similar as the DCA easing modes.
█ ORDER SETTINGS
Fine-tune accuracy to match your exchange's trading constraints, enhancing backtest precision with these settings, default settings are least restrictive for crypto trading pairs.
• MINP - Mininmum Position Notional Value: Exchange-defined minimum notional value for positions:
○ Calculated based on your exchange's rules and is the minimum total value your position must hold to meet their requirements It is calculated by multiplying Quantity with price and leverage.
○ It helps ensure your trades align with your exchange's standards.
• MAXP - Maximum Position Notional Value: Exchange-defined maximum notional value for positions:
○ Similar to MINP, this value is calculated based on your exchange's rules and represents the maximum total value allowed for your position.
• MINQ - Mininmum Order Quantity: Least permissible order quantity based on exchange rules:
○ This is the smallest quantity of an asset that your exchange allows you to trade in a single order.
• MAXQ - Maximum Order Quantity: Highest permissible order quantity according to exchange rules:
○ Opposite of MINQ, this is the largest quantity of an asset you can trade in a single order as defined by your exchange.
• DECP - Decimals in Order Price: Allowed decimal places in order prices as per exchange specifications:
○ This value specifies the number of decimal places you can use when specifying the price of an order.
• DECQ - Decimals in Order Quantity: Permitted decimal places in order quantities according to exchange specifications:
○ Similar to DECP, this value indicates the number of decimal places you can use when specifying the quantity of an asset in an order.
█ STRATEGY CONDITIONS
Specify when the strategy is permitted to execute trades.
• DATE: Enable the Date Range filter to restrict entries to a specific date range.
○ START: Set a start date and hour to commence trading.
○ END: Set an end date and hour to conclude trading within the defined range.
• IDO - Maximum Intraday Orders: Limit the number of orders the strategy can place within a single trading day. Upon reaching this limit, the strategy temporarily halts further entries for the day.
• DL% - Maximum Intraday Loss%: Set a threshold for the maximum allowable intraday loss as a percentage of equity. When exceeded, the strategy temporarily suspends trading for the day.
• CLD - Maximum Consecutive Loss Days: Define the maximum number of consecutive days the strategy can incur losses. Upon reaching this limit, the strategy halts trading and avoids new entries.
• DD% - Maximum Drawdown: Specify the maximum permissible drawdown as a percentage of equity. If this limit is met, the strategy halts trading and refrains from placing additional entries.
• TP% - Total Profit %: Establish a target for the total profit percentage the strategy aims to achieve. Once this target is attained, the strategy halts trading and refrains from initiating new entries.
• TL% - Total Loss %: Define a limit for the total loss percentage relative to the initial capital. If this limit is exceeded, the strategy discontinues trading and refrains from placing further entries.
■ VISUALS
• LINE: Activate a colored dashed diagonal line to visually connect the entry and exit points of positions.
• SLTP: Enable visualization of stop loss, take profit, and break-even levels.
• PNL: Enable Break-Even and Close Lines along with a colored area in between to visualize profit and loss.
• ☼: Brightness % : Adjust the opacity of the plotted trading visuals.
• P - Profit Color : Choose the color for profit-related elements.
• L - Loss Color: Choose the color for loss-related elements.
• B - Breakeven Color : Select the color for break-even points.
• EL - Long Color: Specify the color for long positions.
• ES - Short Color: Specify the color for short positions.
• TRADE LABELING: For better analysis we've labeled all entries and exits conform with the type of order your strategy has executed, some examples:
○ EL-SIG0-124: Enter Long - Signal 0 - Position 124
○ EL-BRO1-130: Enter Long - BRO1 - Position 130
○ EL-BRO2-130: Enter Long - BRO2 - Position 130
○ ES-DCA1-140: Enter Short - DCA1 - Position 140
○ XS-DCA2-140: Exit Short - DCA2 - Position 140
○ XL-TP-150: Exit Long - Take Profit - Position 150
○ XS-TP-154: Exit Short - Take Profit - Position 154
○ XL-SL-160: Exit Long - Stop Loss - Position 160
○ XS-SL-164: Exit Short - Stop Loss - Position 164
○ XS-CND-165: Exit Short - Strategy Condition - Max intraday loss - Position 165
■ ALERT SETTINGS
For developers and those who wish to integrate TradingView alerts into their backend systems, we offer comprehensive labeling options.
• ALID: A unique identifier you've assigned to your alert.
• NAME: A structured name you've given to this strategy.
• LAYOUT: The layout key of the strategy, allowing direct chart linking from your backend.
• SYMBOL: The symbol on which the strategy operates.
○ ONCE: You can choose to include this information only in the first message to reduce message size and repetition in follow-up messages. (max. 4096 characters)
• TICK: The ticker for the strategy.
• CHART: The chart parameter containing the timeframe.period and timeframe.multiplier.
○ ONCE: You can choose to include this information only in the first message to reduce message size and repetition in follow-up messages. (max. 4096 characters)
• BAR: Includes bar information in the alert message.
• STRATEGY: Adds strategy inputs to the alert message.
○ ONCE: You can choose to include this information only in the first message to reduce message size and repetition in follow-up messages. (max. 4096 characters)
• PERFORMANCE: Incorporates strategy performance data into the alert message.
• SIGNAL: Appends received signal weights (EL, XL, ES, XS) to the alert message.
• ORDERS: Includes order details in the alert message.
• TAGS: Adds up to 6 tags and their corresponding values to the alert message.
○ ONCE: You can choose to include this information only in the first message to reduce message size and repetition in follow-up messages. (max. 4096 characters)
Of course we can't neglect letting you in on how this juicy JSON would look (without the // comments):
{
"id": 20726, // Message Id
"t": "2023-11-01T10:35:00Z", // Message Time
"al": { // Alert
"id": "639bfa9a-5f01-4031-8880-7ec01e972055", // Alert Id
"n": "TEST04", // Name
"l": "ABC123" // Layout
},
"sym": { // Symbol
"typ": "crypto", // Type
"r": "DOGEUSD.PM", // Root
"pre": "KRAKEN", // Prefix
"tc": "DOGEUSD.PM", // Ticker
"bc": "DOGE", // BaseCurrency
"c": "USD", // Currency
"d": "DOGEUSD Multi Collateral Perpetual Futures Contract", // Description
"mtc": 0.000001, // MinTick
"pv": 1, // PointValue
"ct": "PF_DOGEUSD" // CustomTicker
},
"ch": { // Chart
"pd": "1", // Period
"mul": 1 // Multiplier
},
"bar": { // Bar
"id": 20725, // Index
"t": "2023-11-01T10:33:00Z", // Time
"o": 0.066799, // Open
"h": 0.066799, // High
"l": 0.066799, // Low
"c": 0.066799, // Close
"v": 2924 // Vol
},
"strat": { // Strategy
"n": "Strategy - Plus / Connectable ", // Name
"sig": { // Signal
"c1e": true, // Connector1Enabled
"c1s": 500500.500501, // Connector1Source
"c1g": 1, // Connector1Gain
"c2e": false, // Connector2Enabled
"c2s": 0.067043, // Connector2Source
"c2g": 1, // Connector2Gain
"sm": "Swing (EL, ES)", // SignalMode
"xm": "Always", // ExitMode
"mlp": 0.01, // ExitModeMinPercLoss
"mpp": 0.01 // ExitModeMinPercProfit
},
"inv": { // Investment
"lb": "Equity", // LossBase
"lp": 50, // LossPerc
"pb": "Equity", // ProfitBase
"pp": 100, // ProfitPerc
"pcb": "Equity", // ProfitCustomBase
"pcp": 100, // ProfitCustomPerc
"pct": 10000, // ProfitCustomThreshold
"elp": 100, // LongPerc
"esp": 100, // ShortPerc
"rsk": 1, // MaxRisk
"lvg": 10 // MaxLeverage
},
"sl": { // StopLoss
"lb": "Price Entry + Offset", // LongBase
"lp": 0.2, // LongPerc
"lsrc": 0.067043, // LongSource
"lt": "Trail Stop", // LongTrailMode
"ltp": 0.2, // LongTrailPerc
"sb": "Price Entry + Offset", // ShortBase
"sp": 0.2, // ShortPerc
"ssrc": 0.067043, // ShortSource
"st": "Trail Stop", // ShortTrailMode
"stp": 0.2 // ShortTrailPerc
},
"tp": { // TakeProfit
"lb": "Price Entry + Offset", // LongBase
"lp": 1, // LongPerc
"lsrc": 0.067043, // LongSource
"lt": "Fixed", // LongTrailMode
"ltp": 1, // LongTrailPerc
"sb": "Price Entry + Offset", // ShortBase
"sp": 1, // ShortPerc
"ssrc": 0.067043, // ShortSource
"st": "Fixed", // ShortTrailMode
"stp": 1 // ShortTrailPerc
},
"dis": { // Distribution
"sigp": 10, // SignalPerc
"dcap": 0, // DCAPerc
"brop": 90 // BROPerc
},
"dca": { // DCA
"lvl": 3, // Levels
"pl": "linear", // ModePriceLevel
"os": "linear" // ModeOrderSize
},
"bro": { // BRO
"lvl": 3, // Levels
"pl": "expoIn", // ModePriceLevel
"os": "cubicOut" // ModeOrderSize
},
"ord": { // OrderSettings
"pmin": 5, // PNVMin
"pmax": 30000000, // PNVMax
"qmin": 0, // QtyMin
"qmax": 1000000000, // QtyMax
"dp": 6, // DecPrice
"dq": 6 // DecQty
},
"cnd": { // Conditions
"de": true, // DateRangeEnabled
"start": "2023-11-01T10:30:00Z", // StartTime
"end": "2024-12-31T23:30:00Z", // EndTime
"idoe": false, // MaxIntradayOrdersEnabled
"ido": 100, // MaxIntradayOrders
"dle": false, // MaxIntradayLossEnabled
"dl": 10, // MaxIntradayLossPerc
"clde": false, // MaxConsLossDaysEnabled
"cld": false, // MaxConsLossDays
"dde": false, // MaxDrawdownEnabled
"dd": 100, // MaxDrawdownPerc
"mpe": false, // MaxProfitEnabled
"mp": 200, // MaxProfitPerc
"mle": false, // MaxLossEnabled
"ml": -50 // MaxLossPerc
}
},
"perf": { // Performance
"ic": 1000, // InitialCapital
"eq": 1000, // Equity
"np": 0, // NetProfit
"op": 0, // OpenProfit
"ct": 0, // ClosedTrades
"ot": 0, // OpenTrades
"p": "FLAT", // MarketPosition
"ps": 0, // MarketPositionSize
"pp": "FLAT", // PreviousMarketPosition
"pps": 0 // PreviousMarketPositionSize
},
"sig": { // Signal
"el": 0, // EL
"xl": 0, // XL
"es": 6, // ES
"xs": 0 // XS
},
"ord": ,
"tag":
}
█ USAGE OF CONNECTABLE INDICATORS
■ Connectable chaining mechanism
Connectable indicators can be connected directly to the signal monitor, signal filter or strategy , or they can be daisy chained to each other while the last indicator in the chain connects to the signal monitor, signal filter or strategy. When using a signal filter you can chain the filter to the strategy input to make your chain complete.
• Direct chaining: Connect an indicator directly to the signal monitor, signal filter or strategy through the provided inputs (→).
• Daisy chaining: Connect indicators using the indicator input (→). The first in a daisy chain should have a flow (⌥) set to 'Indicator only'. Subsequent indicators use 'Both' to pass the previous weight. The final indicator connects to the signal monitor, signal filter, or strategy.
■ Set up this indicator with signals and a signal filter
The indicator provides visual cues based on signal conditions. However, its weight system is best utilized when paired with a connectable signal filter, monitor, or strategy .
Let's connect the Strategy - Plus to a connectable signal filter and connectable indicators :
1. Load all relevant indicators
• Load MA - Plus / Connectable
• Load Signal filter - Plus / Connectable
• Load Strategy - Plus / Connectable
2. Signal Filter Plus: Connect the MA - Plus to the Signal Filter
• Open the signal filter settings
• Choose one of the five input dropdowns (1→, 2→, 3→, 4→, 5→) and choose : MA - Plus / Connectable: Signal Connector
• Toggle the enable box before the connected input to enable the incoming signal
3. Signal Filter: Update the filter settings if needed
• The default filter mode for the trading direction is SWING, and is compatible with the default settings in the strategy and indicators.
4. Signal Filter: Update the weight threshold settings if needed
• All connectable indicators load by default with a score of 6 for each direction (EL, XL, ES, XS)
• By default, weight threshold is 'ABOVE' Threshold 1 (TH1) and Threshold 2 (TH2), both set at 5. This allows each occurrence to score, as the default score is 1 point above the threshold.
5. Strategy Plus: Connect one of the strategy plus inputs to the signal filters signal connector in the strategy settings
• Select a strategy input → and select the Signal filter - Plus: Signal connector
6. Strateg Plus: Enable filter compatible directions
• As the default setting of the filter is SWING, we should also set the SM (Strategy mode) to SWING.
7. Strateg Plus: You're ready to start optimizing
• Dive into all parameters and start optimizing your backtesting results.
█ BENEFITS
• Adaptable Modular Design: Arrange indicators in diverse structures via direct or daisy chaining, allowing tailored configurations to align with your analysis approach.
• Streamlined Backtesting: Simplify the iterative process of testing and adjusting combinations, facilitating a smoother exploration of potential setups.
• Intuitive Interface: Navigate TradingView with added ease. Integrate desired indicators, adjust settings, and establish alerts without delving into complex code.
• Signal Weight Precision: Leverage granular weight allocation among signals, offering a deeper layer of customization in strategy formulation.
• Advanced Signal Filtering: Define entry and exit conditions with more clarity, granting an added layer of strategy precision.
• Clear Visual Feedback: Distinct visual signals and cues enhance the readability of charts, promoting informed decision-making.
• Standardized Defaults: Indicators are equipped with universally recognized preset settings, ensuring consistency in initial setups across different types like momentum or volatility.
• Reliability: Our indicators are meticulously developed to prevent repainting. We strictly adhere to TradingView's coding conventions, ensuring our code is both performant and clean.
█ COMPATIBLE INDICATORS
Each indicator that incorporates our open-source 'azLibConnector' library and adheres to our conventions can be effortlessly integrated and used as detailed above.
For clarity and recognition within the TradingView platform, we append the suffix ' / Connectable' to every compatible indicator.
█ COMMON MISTAKES, CLARIFICATIONS AND TIPS
• Removing an indicator from a chain: Deleting a linked indicator and confirming the "remove study tree" alert will also remove all underlying indicators in the object tree. Before removing one, disconnect the adjacent indicators and move it to the object stack's bottom.
• Point systems: The azLibConnector provides 500 points for each direction (EL: Enter long, XL: Exit long, ES: Enter short, XS: Exit short) Remember this cap when devising a point structure.
• Flow misconfiguration: In daisy chains the first indicator should always have a flow (⌥) setting of 'indicator only' while other indicator should have a flow (⌥) setting of 'both'.
• Hide attributes: As connectable indicators send through quite some information you'll notice all the arguments are taking up some screenwidth and cause some visual clutter. You can disable arguments in Chart Settings / Status line.
• Layout and abbreviations: To maintain a consistent structure, we use abbreviations for each input. While this may initially seem complex, you'll quickly become familiar with them. Each abbreviation is also explained in the inline tooltips.
• Inputs: Connecting a connectable indicator directly to the strategy delivers the raw signal without a weight threshold, meaning every signal will trigger a trade.
• Layout and Abbreviations: Abbreviations streamline structure and input identification. Although they may seem complex initially, inline tooltips provide explanations, facilitating quick acclimatization.
• Total Trade Limit Error & Date-Time Filter: For deep backtesting, be mindful of the total trade limit. Utilize the date-time filter to narrow the test scope and avoid TradingView order limits.
• Calculation Timeout: Encounter a timeout? Adjust any parameter slightly to restart the calculation process.
• Message Character Limit: To stay within message character limits, consider turning off certain features or setting some to 'once'.
• Direct Indicator-to-Strategy Connection: When connecting an indicator directly to a strategy without thresholds, the strategy will default to long if weights are equally assigned.
• Pyramid Enabling with DCA and BRO: Activate pyramid orders, enabling you to optimize your strategy during Dollar Cost Averaging and Break Out trades.
• Recalculate & Fill Orders Properties: Adjusting these default settings in strategy properties tab may lead to unexpected behavior when backtesting. Approach with caution.
• Optimized for Crypto: Our indicators have been optimized and tested primarily on cryptocurrency markets. Results in other markets may vary.
• Inline Tooltips Documentation: Detailed documentation and guidance are available via inline tooltips for immediate assistance.
• Strategy Settings Margin: Set margin to 1 to be able to apply leverage.
• Styling Panel: Explore the styling panel to disable labels or any other visual cues to reduce clutter on busy charts, enhancing visual clarity and personalization.
• Applying Leverage on Spot Markets: Ensure that maximum leverage on spot markets is configured to 1.
• Unrealistic Order Sizes: Verify that the order book can accommodate your backtested order sizes.
█ A NOTE OF GRATITUDE
Through years of exploring TradingView and Pine Script, we've drawn immense inspiration from the community's knowledge and innovation. Thank you for being a constant source of motivation and insight.
█ RISK DISCLAIMER
Azullian's content, tools, scripts, articles, and educational offerings are presented purely for educational and informational uses. Please be aware that past performance should not be considered a predictor of future results.
FreedX Backtest█ Our strategy template empowers TradingView users to effortlessly backtest any indicator, enhancing their trading strategy's effectiveness. In addition, users can create automated webhook alerts from the template. This document details our template's features and how to utilize them effectively.
█ TRADE DATE SETTINGS
The Trading Date Settings feature in our TradingView script allows you to refine their backtesting parameters by specifying trading dates and hours. This feature enhances the accuracy of the backtest by aligning it with specific time frames and days, ensuring that the strategy is tested under relevant market conditions.
Features:
⚙️ Enable Trading Between Specific Dates:
🎯 Purpose:
→ Allows you to limit the backtesting of their strategy to a specific date range.
💡 How to Use:
→ Input the Start Date and End Date for the backtest period.
→ The script will execute the strategy only within this specified date range.
⚙️ Enable Trading Between Specific Hours:
🎯 Purpose:
→ Allows you to limit the backtesting of their strategy to a specific hour range.
💡 How to Use:
→ Input the start and end hour for in Trading Session section.
→ The script will execute the strategy only within this specified hour range.
⚙️ Enable Trading on Specified Days of the Week:
🎯 Purpose:
→ Gives you the option to conduct backtesting on selected days of the week, tailoring the strategy to particular market behaviours that may occur on these days.
💡 How to Use:
→ Select the days of the week for the backtest.
→ The script will activate the trading strategy only on these chosen days.
█ BUY/SELL TRIGGER SETTINGS
The Buy/Sell Trigger Settings feature is designed to provide users with flexibility in defining the conditions for 'LONG' and 'SHORT' signals based on various indicator types. This customization is crucial for tailoring strategies to different trading styles and market conditions.
Features:
⚙️ Single-Line Plotted Indicators :
🎯 Purpose:
→ Enables you to select a single-line plotted indicator as a source for backtesting. You can define specific levels to trigger 'LONG' or 'SHORT' signals.
💡 How to Use:
→ Choose a Single-Line Plotted indicator as the source.
→ Set the top and bottom levels for the indicator.
→ The script triggers 'LONG' signals at the bottom level and 'SHORT' signals at the top level.
⚙️ Two-Line Plotted Indicators :
🎯 Purpose:
→ Allows backtesting with two-line cross plot sources. Signals are generated based on the crossover of these lines.
💡 How to Use:
→ Select two lines as 'Source 1' and 'Source 2' for the indicator.
→ The script triggers a 'LONG' signal when 'Source 1' crosses above 'Source 2'.
→ Conversely, a 'SHORT' signal is triggered when 'Source 2' crosses above 'Source 1'.
⚙️ Custom Signals :
🎯 Purpose:
→ This setting enables users to define their own criteria for LONG, SHORT, and CLOSE signals based on custom indicator outputs.
💡 How to Use:
→ Select the custom source for your signals.
→ Define the output values that correspond to each signal type (e.g., “1” for 'LONG', “-1” for SHORT, and “0” for CLOSE).
→ The script will trigger signals according to these custom-defined values.
█ TP/SL SETTINGS
The TP/SL (Take Profit/Stop Loss) Settings feature is designed to give users control over their profit securing and risk mitigation strategies. This feature allows for setting custom TP and SL levels, which can be critical in managing trades effectively.
Features:
Custom TP/SL Levels for Long/Short Signals:
🎯 Purpose:
→ Enables users to set specific percentage levels for Take Profit and Stop Loss on long and short signals.
💡 How to Use:
→ In the TP/SL Settings, input the desired percentage for Take Profit (TP) and Stop Loss (SL).
→ For example, to secure a profit at a 10% price increase on LONG signals, set the “Long TP Percentage” to “10”.
█ STRATEGY SETTINGS
Strategy Settings provide a range of options to customize the trading strategy. These settings include leverage, drawdown limits, position direction changes, and more, allowing users to tailor their strategy to their risk tolerance and market view.
Features:
⚙️ Enable Leverage :
🎯 Purpose:
→ Allows users to apply leverage to their trades.
☢️ Caution:
→ High leverage can significantly increase the risk of liquidation.
→ High leverage and a high stop-loss price may override your fixed stoploss percentage, adjusting the stop-loss to the liquidation price.
💡 How to Use:
→ Set the desired leverage ratio in the Strategy Settings.
⚙️ Enable Drawdown Limit:
🎯 Purpose:
→ Sets a maximum drawdown limit, automatically halting the strategy if this limit is reached, thereby controlling risk.
💡 How to Use:
→ Input the maximum drawdown limit (default: 100, min: 0, max: 100).
⚙️ Enable Reverse Position:
🎯 Purpose:
→ Automatically closes a current position and opens a new one in the opposite direction upon detecting a signal for a market trend change.
🎯 Example:
→ If a LONG signal is received while in a SHORT position, the script will close the SHORT position and open a LONG position.
💡 How to Use:
→ Activate this feature in the Strategy Settings.
⚙️ Enable Spot Mode:
🎯 Purpose:
→ Disables short orders, using short signals only for closing long positions.
💡 How to Use:
→ Select the 'Spot Mode' option in the Strategy Settings.
⚙️ Enable Invert Signals:
🎯 Purpose:
→ Inverts all indicator signals, changing LONG signals to SHORT and vice versa.
💡 How to Use:
→ Opt for the 'Invert Signals' feature in the Strategy Settings.
⚙️ Enable Trailing Stop:
🎯 Purpose:
→ Triggers a trailing stop order on the exchange instead of a standard stop market order.
☢️ Caution:
→ The backtesting of this feature on TradingView may not accurately reflect actual strategy performance due to discrepancies between TradingView and exchange mechanisms.
💡 How to Use:
→ Select 'Trailing Stop' in the Strategy Settings.
█ ADVANCED STRATEGY SETTINGS
Advanced Strategy Settings offer sophisticated methods for managing Stop Loss (SL) and Take Profit (TP) using the Average True Range (ATR). These settings are ideal for traders who want to incorporate volatility into their exit strategies.
Features:
⚙️ Enable ATR Stop Loss:
🎯 Purpose:
→ Automatically sets the Stop Loss price using the Average True Range at the time of entry.
💡 How to Use:
→ Activate 'ATR Stop Loss' to have the SL price calculated based on the current ATR.
⚙️ Enable ATR Take Profit:
🎯 Purpose:
→ Sets the Take Profit price based on the Average True Range at the time of entry.
💡 How to Use:
→ Choose 'ATR Take Profit' for TP price determination using ATR.
⚙️ Enable ATR Trailing Stop:
🎯 Purpose:
→ Dynamically updates the Stop Loss price with each new bar, according to the Average True Range.
💡 How to Use:
→ Activate 'ATR Trailing Stop'.
→ Set the ATR Period to define the number of bars for ATR calculation.
→ Adjust the ATR SL Multiplier to determine the stop loss distance.
→ Modify the ATR TP Multiplier for setting the take profit distance.
█ TREND FILTERING SETTINGS
Trend Filtering Settings are designed to align trading strategies with the prevailing market trend, enhancing the precision of trade entries and exits. These settings utilize moving averages for trend analysis and decision-making.
Features:
⚙️ Enable Trend Filtering:
🎯 Purpose:
→ Limits trades based on moving average trends, blocking short trades in an uptrend and vice versa.
💡 How to Use:
→ Enable 'Trend Filtering'.
→ Set Fast and Slow MA Lengths for trend analysis.
→ Select the Timeframe for moving averages.
→ Choose the Moving Average Type for trend filtering.
🎯 Note:
→ Be cautious with timeframe selections; lower timeframes than the base may cause inconsistencies.
⚙️ Enable Exit on Trend Reversal:
🎯 Purpose:
→ Automatically closes a position when a market trend reversal is detected.
💡 How to Use:
→ Turn on 'Exit on Trend Reversal' in the settings.
⚙️ Enable Trend Drawing On Chart:
🎯 Purpose:
→ Visually represents the trend filter directly on the chart for easy reference.
💡 How to Use:
→ Activate 'Trend Drawing On Chart' to see the trend filter overlaid on the trading chart.
█ AUTOMATED ALERT SETTINGS
Automated Alert Settings are designed to integrate your TradingView script with webhook alerts. These settings allow for enhanced strategy execution and management.
Features:
Enable Webhook Alerts:
🎯 Purpose:
→ Trigger BUY, SELL, CHANGE_DIRECTION or MOVE_STOP_LOSS .
💡 How to Use:
→ Enable 'Webhook Alerts' in the settings.
→ Enter your Strategy ID.
→ Optionally, activate 'Override Allocation Percentage' to bypass the preset allocation percentage.
☢️ Caution:
→ Overriding the allocation percentage may result in trade entry errors due to misalignment between entry cost and available balance.
█ DEBUGGING SETTINGS
Debugging Settings are crucial for users who want to analyze and optimize their strategies. These settings provide tools for visualizing alerts on charts and accessing detailed data outputs.
Features:
⚙️ Enable Alert Plotting:
🎯 Purpose:
→ Allows users to visualize trading alerts directly on the chart, aiding in strategy analysis and refinement.
💡 How to Use:
→ Activate 'Alert Plotting' to draw alerts on the chart.
☢️ Caution:
→ It is recommended to disable this feature when creating actual trading alerts, as it can cause latency in signal processing.
⚙️ Enable Debugger Mode:
🎯 Purpose:
→ Facilitates strategy debugging by providing detailed data output in the TradingView Data Window.
💡 How to Use:
→ Turn on 'Debugger Mode' to access real-time data and metrics relevant to your strategy.
█ ADDITIONAL SETTINGS
⚙️ Enable Bar Magnifier
⚙️ Enable Using standard OHLC
PresentTrend - Strategy [presentTrading]- Introduction and how it is different
The PresentTrend strategy is a unique custom trend-following strategy. This combination allows the strategy to take advantage of both short-term and long-term market trends, making it suitable for various market conditions.
BTCUSDT 4hr chart
(700.hk) 3D chart
- Strategy, How it Works
RSI or MFI: The first part uses a custom indicator based on either the Relative Strength Index (RSI) or the Money Flow Index (MFI). The indicator calculates a PresentTrend value, which generates buy and sell signals based on its crossover and crossunder, indicating potential trend reversals.
ATR: The second part is a popular trend-following indicator that uses the Average True Range (ATR).
The strategy enters a long position when all buy signals from both strategies are true, and a short position when all sell signals are true. This ensures trades are entered when both short-term and long-term trends align, potentially increasing the strategy's reliability.
- Trade direction
The strategy also includes a trade direction parameter, allowing the user to choose whether to enter long trades, short trades, or both. This makes the strategy adaptable to different market conditions and trading styles.
- Usage
1. Set the input parameters for the custom trend-following strategy.
2. Choose whether to use the RSI or MFI for the custom strategy.
3. Choose the trade direction: long, short, or both.
4. The strategy will generate buy and sell signals based on the conditions of both strategies.
5. Enter a trade when a buy or sell signal is generated, depending on the chosen trade direction.
Please note that this strategy is meant to be a tool to aid in your trading decisions and not a standalone trading system. Always use proper risk management and make sure to test the strategy thoroughly before using it in live trading.
- Default settings
1. Source: 'hlc3', a balanced price level for calculations.
2. Length: 14, a common setting for many technical indicators.
3. Multiplier: 1.618 (the golden ratio), used in calculating the upper and lower thresholds.
4. RSI or MFI: Set to use MFI by default, both are momentum indicators.
5. Trade Direction: 'Both', allowing for both long and short trades.
The default settings are designed to provide a balanced approach to trend detection. However, these can be adjusted based on the user's preferences and the specific characteristics of the market being traded.
- Strategy's default Properties
1. Default Quantity Type: 'strategy.percent_of_equity'
2. commission_value= 0.1, commission_type=strategy.commission.percent, slippage= 1: These parameters set the commission and slippage for the strategy. The commission is set to 0.1% of the trade value, and the slippage (the difference between the expected price of a trade and the price at which the trade is executed) is set to 1.
3. default_qty_type = strategy.percent_of_equity, default_qty_value = 10: These parameters set the default quantity for trades. The default_qty_type is set to strategy.percent_of_equity, which means that the size of each trade will be a percentage of the account equity. The default_qty_value is set to 10, which means that each trade will be 10% of the account equity.
4. initial_capital= 10000: This parameter sets the initial capital for the strategy to $10,000.
3Commas BotBjorgum 3Commas Bot
A strategy in a box to get you started today
With 3rd party API providers growing in popularity, many are turning to automating their strategies on their favorite assets. With so many options and layers of customization possible, TradingView offers a place no better for young or even experienced coders to build a platform from to meet these needs. 3Commas has offered easy access with straight forward TradingView compatibility. Before long many have their brokers hooked up and are ready to send their alerts (or perhaps they have been trying with mixed success for some time now) only they realize there might just be a little bit more to building a strategy that they are comfortable letting out of their sight to trade their money while they eat, sleep, etc. Many may have ideas for entry criteria they are excited to try, but further questions arise... "What about risk mitigation?" "How can I set stop or limit orders?" "Is there not some basic shell of a strategy that has laid some of this out for me to get me going?"
Well now there is just that. This strategy is meant for those that have begun to delve into the world of algorithmic trading providing a template that offers risk defined positions complete with stops, limit orders, and even trailing stops should one so choose to employ any of these criteria. It provides a framework that is easily manipulated (with some basic working knowledge of pine coding) to encompass ones own ideas and entry criteria, while also providing an already functioning strategy.
The default settings have a basic 1:1 risk to reward ratio, which sets a limit and a stop equal distance from the entry. The entry is a simple MA cross (up for long, down for short). There a variety of MA's to choose from and the user can define the lengths of the averages. The ratio can be adjusted from the menu along with a volatility based adder (ATR) that helps to distance a stop from support or resistance. These values are calculated off the swing low/high of the user defined lookback period. Risk is calculated from position entry to stop, and projected upwards to the limit as a function of the desired risk to reward ratio. Of note: the default settings include 0.05% commissions. Competitive commissions of the leading cryptocurrency exchanges are .1% round trip (one buy and one sell) for market orders. There is also some slippage to allow time for alerts to be sent and orders to fill giving the back test results a more accurate representation of real time conditions. Its recommended to research the going rates for your exchange and set them to default for the strategy you use or build.
To get started a user would:
1) Make a copy of the code and paste in their bot keys in the area provided under the "3Comma Keys" section
- eg. Long bot "start deal" copied from 3commas in to define "Long" etc. (code is commented)
2) Place alert on desired asset with desired settings ensuring to select "Order fills and alert() function calls"
3) Paste webhook into the webhook box and select webhook URL alerts (3rd party provided webhook)
3) Delete contents of alert message box and replace with {{strategy.order.alert_message}} and nothing else
- the codes will be sent to the webhook appropriately as the strategy enters and exits positions. Only 1 alert is needed
settings used for the display image:
1hr chart on BTCUSD
-ATR stop
-Risk adjustment 1.2
-ATR multiplier 1.3
-RnR 0.6
-MAs HEMA/SMA
-MA Length 50/100
-Order size percent of equity
-Trail trigger 60% of target
Experiment with your own settings on your crypto of choice or implement your own code!
Implementing your trailing stop (optional)
Among the options for possible settings is a trailing stop. This stop will ratchet higher once triggered as a function of the Average True Range (ATR). There is a variable level to choose where the user would like to begin trailing the stop during the trade. The level can be assigned with a decimal between 0 and 1 (eg. 0.5 = 50% of the distance between entry and the target which must be exceeded before the trail triggers to begin). This can allow for some dips to occur during the trade possibly keeping you in the trade for longer, while potentially reducing risk of drawdown over time. The default for this setting is 0 meaning unless adjusted, the trail will trigger on entry if the trailing stop exit method is selected. An example can be seen below:
Again, optional as well is the choice to implement a limit order. If one were to select a trailing stop they could choose not to set a limit, which could allow a trail to run further until hit. Drawdowns of this strategy would be foregoing locking gains at highs on target on other trades. This is a trade-off the user can decide on and test. An example of this working in favor can be observed below:
Conclusion
Although a simple strategy is implemented here, the benefits of this script allow a user a starting platform to build their strategies from with built in risk mitigation. This allows the user to sidestep some of the potential difficulties' that can arise while learning Pine and taking on the endeavor of automating their trading strategies. It is meant as an aid, a structure, and an educational piece that can be seen as a "pick-up-and-go" strategy with easy 3Commas compatibility. Additionally, this can help users become more comfortable with strategy alert messages and sending strings in the form of alerts from Pine. As well, FAQs are often littered with questions regarding "strategy.exit" calls, how to implement stops. how to properly set a trailing stop based on ATR, and more. The time this can save an individual to get started is likely of the best "take-aways" here.
Happy trading
Strategy Stats [presentTrading]Hello! it's another weekend. This tool is a strategy performance analysis tool. Looking at the TradingView community, it seems few creators focus on this aspect. I've intentionally created a shared version. Welcome to share your idea or question on this.
█ Introduction and How it is Different
Strategy Stats is a comprehensive performance analytics framework designed specifically for trading strategies. Unlike standard strategy backtesting tools that simply show cumulative profits, this analytics suite provides real-time, multi-timeframe statistical analysis of your trading performance.
Multi-timeframe analysis: Automatically tracks performance metrics across the most recent time periods (last 7 days, 30 days, 90 days, 1 year, and 4 years)
Advanced statistical measures: Goes beyond basic metrics to include Information Coefficient (IC) and Sortino Ratio
Real-time feedback: Updates performance statistics with each new trade
Visual analytics: Color-coded performance table provides instant visual feedback on strategy health
Integrated risk management: Implements sophisticated take profit mechanisms with 3-step ATR and percentage-based exits
BTCUSD Performance
The table in the upper right corner is a comprehensive performance dashboard showing trading strategy statistics.
Note: While this presentation uses Vegas SuperTrend as the underlying strategy, this is merely an example. The Stats framework can be applied to any trading strategy. The Vegas SuperTrend implementation is included solely to demonstrate how the analytics module integrates with a trading strategy.
⚠️ Timeframe Limitations
Important: TradingView's backtesting engine has a maximum storage limit of 10,000 bars. When using this strategy stats framework on smaller timeframes such as 1-hour or 2-hour charts, you may encounter errors if your backtesting period is too long.
Recommended Timeframe Usage:
Ideal for: 4H, 6H, 8H, Daily charts and above
May cause errors on: 1H, 2H charts spanning multiple years
Not recommended for: Timeframes below 1H with long history
█ Strategy, How it Works: Detailed Explanation
The Strategy Stats framework consists of three primary components: statistical data collection, performance analysis, and visualization.
🔶 Statistical Data Collection
The system maintains several critical data arrays:
equityHistory: Tracks equity curve over time
tradeHistory: Records profit/loss of each trade
predictionSignals: Stores trade direction signals (1 for long, -1 for short)
actualReturns: Records corresponding actual returns from each trade
For each closed trade, the system captures:
float tradePnL = strategy.closedtrades.profit(tradeIndex)
float tradeReturn = strategy.closedtrades.profit_percent(tradeIndex)
int tradeType = entryPrice < exitPrice ? 1 : -1 // Direction
🔶 Performance Metrics Calculation
The framework calculates several key performance metrics:
Information Coefficient (IC):
The correlation between prediction signals and actual returns, measuring forecast skill.
IC = Correlation(predictionSignals, actualReturns)
Where Correlation is the Pearson correlation coefficient:
Correlation(X,Y) = (nΣXY - ΣXY) / √
Sortino Ratio:
Measures risk-adjusted return focusing only on downside risk:
Sortino = (Avg_Return - Risk_Free_Rate) / Downside_Deviation
Where Downside Deviation is:
Downside_Deviation = √
R_i represents individual returns, T is the target return (typically the risk-free rate), and n is the number of observations.
Maximum Drawdown:
Tracks the largest percentage drop from peak to trough:
DD = (Peak_Equity - Trough_Equity) / Peak_Equity * 100
🔶 Time Period Calculation
The system automatically determines the appropriate number of bars to analyze for each timeframe based on the current chart timeframe:
bars_7d = math.max(1, math.round(7 * barsPerDay))
bars_30d = math.max(1, math.round(30 * barsPerDay))
bars_90d = math.max(1, math.round(90 * barsPerDay))
bars_365d = math.max(1, math.round(365 * barsPerDay))
bars_4y = math.max(1, math.round(365 * 4 * barsPerDay))
Where barsPerDay is calculated based on the chart timeframe:
barsPerDay = timeframe.isintraday ?
24 * 60 / math.max(1, (timeframe.in_seconds() / 60)) :
timeframe.isdaily ? 1 :
timeframe.isweekly ? 1/7 :
timeframe.ismonthly ? 1/30 : 0.01
🔶 Visual Representation
The system presents performance data in a color-coded table with intuitive visual indicators:
Green: Excellent performance
Lime: Good performance
Gray: Neutral performance
Orange: Mediocre performance
Red: Poor performance
█ Trade Direction
The Strategy Stats framework supports three trading directions:
Long Only: Only takes long positions when entry conditions are met
Short Only: Only takes short positions when entry conditions are met
Both: Takes both long and short positions depending on market conditions
█ Usage
To effectively use the Strategy Stats framework:
Apply to existing strategies: Add the performance tracking code to any strategy to gain advanced analytics
Monitor multiple timeframes: Use the multi-timeframe analysis to identify performance trends
Evaluate strategy health: Review IC and Sortino ratios to assess predictive power and risk-adjusted returns
Optimize parameters: Use performance data to refine strategy parameters
Compare strategies: Apply the framework to multiple strategies to identify the most effective approach
For best results, allow the strategy to generate sufficient trade history for meaningful statistical analysis (at least 20-30 trades).
█ Default Settings
The default settings have been carefully calibrated for cryptocurrency markets:
Performance Tracking:
Time periods: 7D, 30D, 90D, 1Y, 4Y
Statistical measures: Return, Win%, MaxDD, IC, Sortino Ratio
IC color thresholds: >0.3 (green), >0.1 (lime), <-0.1 (orange), <-0.3 (red)
Sortino color thresholds: >1.0 (green), >0.5 (lime), <0 (red)
Multi-Step Take Profit:
ATR multipliers: 2.618, 5.0, 10.0
Percentage levels: 3%, 8%, 17%
Short multiplier: 1.5x (makes short take profits more aggressive)
Stop loss: 20%
RSI + Stochastic + WMA StrategyThis script is designed for TradingView and serves as a trading strategy (not just a visual indicator). It's intended for backtesting, strategy optimization, or live trading signal generation using a combination of popular technical indicators.
📊 Indicators Used in the Strategy:
Indicator Description
RSI (Relative Strength Index) Measures momentum; identifies overbought (>70) or oversold (<30) conditions.
Stochastic Oscillator (%K & %D) Detects momentum reversal points via crossovers. Useful for timing entries.
WMA (Weighted Moving Average) Identifies the trend direction (used as a trend filter).
📈 Trading Logic / Strategy Rules:
📌 Long Entry Condition (Buy Signal):
All 3 conditions must be true:
RSI is Oversold → RSI < 30
Stochastic Crossover Upward → %K crosses above %D
Price is above WMA → Confirms uptrend direction
👉 Interpretation: Market was oversold, momentum is turning up, and price confirms uptrend — bullish entry.
📌 Short Entry Condition (Sell Signal):
All 3 conditions must be true:
RSI is Overbought → RSI > 70
Stochastic Crossover Downward → %K crosses below %D
Price is below WMA → Confirms downtrend direction
👉 Interpretation: Market is overbought, momentum is turning down, and price confirms downtrend — bearish entry.
🔄 Strategy Execution (Backtesting Logic):
The script uses:
pinescript
Copy
Edit
strategy.entry("LONG", strategy.long)
strategy.entry("SHORT", strategy.short)
These are Pine Script functions to place buy and sell orders automatically when the above conditions are met. This allows you to:
Backtest the strategy
Measure win/loss ratio, drawdown, and profitability
Optimize indicator settings using TradingView Strategy Tester
📊 Visual Aids (Charts):
Plots WMA Line: Orange line for trend direction
Overbought/Oversold Zones: Horizontal lines at 70 (red) and 30 (green) for RSI visualization
⚡ Strategy Type Summary:
Category Setting
Strategy Type Momentum Reversal + Trend Filter
Timeframe Flexible (Works best on 1H, 4H, Daily)
Trading Style Swing/Intraday
Risk Profile Medium to High (due to momentum triggers)
Uses Leverage Possible (adjust risk accordingly)
MA Crossover with Demand/Supply Zones + Stop Loss/Take ProfitStop Loss and Take Profit Inputs:
Added stopLossPerc and takeProfitPerc as inputs to allow the user to define the stop loss and take profit levels as a percentage of the entry price.
Stop Loss and Take Profit Calculation:
For long positions, the stop loss is calculated as strategy.position_avg_price * (1 - stopLossPerc), and the take profit is calculated as strategy.position_avg_price * (1 + takeProfitPerc).
For short positions, the stop loss is calculated as strategy.position_avg_price * (1 + stopLossPerc), and the take profit is calculated as strategy.position_avg_price * (1 - takeProfitPerc).
Exit Strategy:
Added strategy.exit to define the stop loss and take profit levels for each trade. The from_entry parameter ensures that the exit is tied to the specific entry order.
Flexibility:
The stop loss and take profit levels are dynamic and adjust based on the entry price of the trade.
How It Works:
When a buy signal is generated (MA crossover near a demand zone), the strategy enters a long position and sets a stop loss and take profit level based on the input percentages.
When a sell signal is generated (MA crossunder near a supply zone), the strategy enters a short position and sets a stop loss and take profit level based on the input percentages.
The trade will exit automatically if either the stop loss or take profit level is hit.
Example:
If the entry price for a long position is $100, and the stop loss is set to 1% while the take profit is set to 2%:
Stop loss level =
100
∗
(
1
−
0.01
)
=
100∗(1−0.01)=99
Take profit level =
100
∗
(
1
+
0.02
)
=
100∗(1+0.02)=102
Notes:
You can adjust the stopLossPerc and takeProfitPerc inputs to suit your risk management preferences.
Always backtest the strategy to ensure the stop loss and take profit levels are appropriate for your trading instrument and timeframe.
Martingale + Grid DCA Strategy [YinYangAlgorithms]This Strategy focuses on strategically Martingaling when the price has dropped X% from your current Dollar Cost Average (DCA). When it does Martingale, it will create a Purchase Grid around this location to likewise attempt to get you a better DCA. Likewise following the Martingale strategy, it will sell when your Profit has hit your target of X%.
Martingale may be an effective way to lower your DCA. This is due to the fact that if your initial purchase; or in our case, initial Grid, all went through and the price kept going down afterwards, that you may purchase more to help lower your DCA even more. By doing so, you may bring your DCA down and effectively may make it easier and quicker to reach your target profit %.
Grid trading may be an effective way of reducing risk and lowering your DCA as you are spreading your purchases out over multiple different locations. Likewise we offer the ability to ‘Stack Grids’. What this means, is that if a single bar was to go through 20 grids, the purchase amount would be 20x what each grid is valued at. This may help get you a lower DCA as rather than creating 20 purchase orders at each grid location, we create a single purchase order at the lowest grid location, but for 20x the amount.
By combining both Martingale and Grid DCA techniques we attempt to lower your DCA strategically until you have reached your target profit %.
Before we start, we just want to make it known that first off, this Strategy features 8% Commission Fees, you may change this in the Settings to better reflect the Commission Fees of your exchange. On a similar note, due to Commission Fees being one of the number one profit killers in fast swing trade strategies, this strategy doesn’t focus on low trades, but the ideology of it may result in low amounts of trades. Please keep in mind this is not a bad thing. Since it has the ability to ‘Stack Grid Purchases’ it may purchase more for less and result in more profit, less commission fees, and likewise less # of trades.
Tutorial:
In this example above, we have it set so we Martingale twice, and we use 100 grids between the upper and lower level of each martingale; for a total of 200 Grids. This strategy will take total capital (initial capital + net profit) and divide it by the amount of grids. This will result in the $ amount purchased per grid. For instance, say you started with $10,000 and you’ve made $2000 from this Strategy so far, your total capital is $12,000. If you likewise are implementing 200 grids within your Strategy, this will result in $12,000 / 200 = $60 per grid. However, please note, that the further down the grid / martingale is, the more volume it is able to purchase for $60.
The white line within the Strategy represents your DCA. As the Strategy makes purchases, this will continue to get lower as will your Target Profit price (Blue Line). When the Close goes above your Target Profit price, the Strategy will close all open positions and claim the profit. This profit is then reinvested back into the Strategy, which may exponentially help the Strategy become more profitable the longer it runs for.
In the example above, we’ve zoomed in on the first example. In this we want to focus on how the Strategy got back into the trades shortly after it sold. Currently within the Settings we have it set so our entry is when the Lowest with a length of 3 is less than the previous Lowest with a length of 3. This is 100% customizable and there are multiple different entry options you can choose from and customize such as:
EMA 7 Crossover EMA 21
EMA 7 Crossunder EMA 21
RSI 14 Crossover RSI MA 14
RSI 14 Crossunder RSI MA 14
MFI 14 Crossover MFI MA 14
MFI 14 Crossunder MFI MA 14
Lowest of X Length < Previous Lowest of X Length
Highest of X Length > Previous Highest of X Length
All of these entry options may be tailored to be checked for on a different Time Frame than the one you are currently using the Strategy on. For instance, you may be running the Strategy on the 15 minute Time Frame yet decide you want the RSI to cross over the RSI MA on the 1 Day to be a valid entry location.
Please keep in mind, this Strategy focuses on DCA, this means you may not want the initial purchase to be the best location. You may want to buy when others think it is a good time to sell. This is because there may be strong bearish momentum which drives the price down drastically and potentially getting you a good DCA before it corrects back up.
We will continue to add more Entry options as time goes on, and if you have any in mind please don’t hesitate to let us know.
Now, back to the example above, if we refer to the Yellow circle, you may see that the Lowest of a length of 3 was less than its previous lowest, this triggered the martingales to create their grids. Only a few bars later, the price went into the first grid and went a little lower than its midpoint (Yellow line). This caused about 60% of the first grid to be purchased. Shortly after the price went even lower into this grid and caused the entire first martingale grid to be purchased. However, if you notice, the white line (your DCA) is lower than the midpoint of the first grid. This is due to the fact that we have ‘Stack Grid Purchases’ enabled. This allows the Strategy to purchase more when a single bar crosses through multiple grid locations; and effectively may lower your average more than if it simply executed a purchase order at each grid.
Still looking at the same location within our next example, if we simply increase the Martingale amount from 2 to 3 we can see something strange happens. What happened is our Target Profit price was reached, then our entry condition was met, which caused all of the martingale grids to be formed; however, the price continued to increase afterwards. This may not be a good thing, sure the price could correct back down to these grid locations, but what if it didn’t and it just kept increasing? This would result in this Strategy being stuck and unable to make any trades. For this reason we have implemented a Failsafe in the Settings called ‘Reset Grids if no purchase happens after X bars’.
We have enabled our Failsafe ‘Reset Grids if no purchase happens after X bars’ in this example above. By default it is set to 100 bars, but you can change this to whatever works best for you. If you set it to 0, this Failsafe will be disabled and act like the example prior where it is possible to be stuck with no trades executing.
This Failsafe may be an important way to ensure the Strategy is able to make purchases, however it may also mean the Grids increase in price when it is used, and if a massive correction were to occur afterwards, you may lose out on potential profit.
This Strategy was designed with WebHooks in mind. WebHooks allow you to send signals from the Strategy to your exchange. Simply set up a Custom TradingView Bot within the OKX exchange or 3Commas platform (which has your exchange API), enter the data required from the bot into the settings here, select your bot type in ‘Webhook Alert Type’, and then set up the alert. After that you’re good to go and this Strategy will fully automate all of its trades within your exchange for you. You need to format the Alert a certain way for it to work, which we will go over in the next example.
Add an alert for this Strategy and simply modify the alert message so all it says is:
{{strategy.order.alert_message}}
Likewise change from the Alert ‘Settings’ to Alert ‘Notifications’ at the top of the alert popup. Within the Notifications we will enable ‘Webhook URL’ and then we will pass the URL we are sending the Webhook to. In this example we’ve put OKX exchange Webhook URL, however if you are using 3Commas you’ll need to change this to theirs.
OKX Webhook URL:
www.okx.com
3Commas Webhook URL:
app.3commas.io
Make sure you click ‘Create’ to actually create this alert. After that you’re all set! There are many Tutorials videos you can watch if you are still a little confused as to how Webhook trading works.
Due to the nature of this Strategy and how it is designed to work, it has the ability to never sell unless there it will make profit. However, because of this it also may be stuck waiting in trades for quite a long period of time (usually a few months); especially when your Target Profit % is 15% like in the example above. However, this example above may be a good indication that it may maintain profitability for a long period of time; considering this ‘Deep Backtest’ is from 2017-8-17.
We will conclude the tutorial here. Hopefully you understand how this Strategy has the potential to make calculated and strategic DCA Grid purchases for you and then based on a traditional Martingale fashion, bulk sell at the desired Target Profit Percent.
Settings:
Purchase Settings:
Only Purchase if its lower than DCA: Generally speaking, we want to lower our Average, and therefore it makes sense to only buy when the close is lower than our current DCA and a Purchase Condition is met.
Purchase Condition: When creating the initial buy location you must remember, you want to Buy when others are Fearful and Sell when others are Greedy. Therefore, many of the Buy conditions involve times many would likewise Sell. This is one of the bonuses to using a Strategy like this as it will attempt to get you a good entry location at times people are selling.
Lower / Upper Change Length: This Lower / Upper Length is only used if the Purchase Condition is set to 'Lower Changed' or 'Upper Changed'. This is when the Lowest or Highest of this length changes. Lowest would become lower or Highest would become higher.
Purchase Resolution: Purchase Resolution is the Time Frame that the Purchase Condition is calculated on. For instance, you may only want to start a new Purchase Order when the RSI Crosses RSI MA on the 1 Day, but yet you run this Strategy on the 15 minutes.
Sell Settings:
Trailing Take Profit: Trailing Take Profit is where once your Target Profit Percent has been hit, this will trail up to attempt to claim even more profit.
Target Profit Percent: What is your Target Profit Percent? The Strategy will close all positions when the close price is greater than your DCA * this Target Profit Percent.
Grid Settings:
Stack Grid Purchases: If a close goes through multiple Buy Grids in one bar, should we amplify its purchase amount based on how many grids it went through?
Reset Grids if no purchase happens after X Bars: Set this to 0 if you never want to reset. This is very useful in case the price is very bullish and continues to increase after our Target Profit location is hit. What may happen is, Target Profit location is hit, then the Entry condition is met but the price just keeps increasing afterwards. We may not want to be sitting waiting for the price to drop, which may never happen. This is more of a failsafe if anything. You may set it very large, like 500+ if you only want to use it in extreme situations.
Grid % Less than Initial Purchase Price: How big should our Buy Grid be? For instance if we bought at 0.25 and this value is set to 20%, that means our Buy Grid spans from 0.2 - 0.25.
Grid Amounts: How many Grids should we create within our Buy location?
Martingale Settings:
Amount of Times 'Planned' to Martingale: The more Grids + the More Martingales = the less $ spent per grid, however the less risk. Remember it may be better to be right and take your time than risk too much and be stuck too long.
Martingale Percent: When the current price is this percent less than our DCA, lets create another Buy Grid so we can lower our average more. This will make our profit location less.
Webhook Alerts:
Webhook Alert Type: How should we format this Alert? 3Commas and OKX take their alerts differently, so please select the proper one or your webhooks won't work.
3Commas Webhook Alerts:
3Commas Bot ID: The 3Commas Bot ID is needed so we know which BOT ID we are sending this webhook too.
3Commas Email Token: The 3Commas Email Token is needed for your webhooks to work properly as it is linked to your account.
OKX Webhook Alerts:
OKX Signal Token: This Signal Token is attached to your OKX bot and will be used to access it within OKX.
If you have any questions, comments, ideas or concerns please don't hesitate to contact us.
HAPPY TRADING!
Previous Day High Low Strategy only for LongWelcome to the "Previous Day High Low Strategy only for Long"!.
This strategy aims to identify potential long trading opportunities based on the previous day's high and low prices, along with certain market strength conditions.
Key Features:
Entry Conditions: The strategy triggers a long position when the current day's closing price crosses above the previous day's high or low.
Market Strength Filter: The strategy incorporates a market strength filter using the Average Directional Index (ADX). It only takes long positions when the ADX value is above a specific threshold and when there is a predominance of upward movement.
Trade Timing: The strategy operates within a specified trade window, starting at 09:30 and ending at 15:10. Positions are closed at 15:15 if still active.
Risk Management: The strategy employs dynamic stop-loss and profit-taking levels based on a user-defined Max Profit value. It has three profit targets (T1, T2, T3) and a stop-loss level to manage risk effectively.
Rules:
Ensure that the strategy idea is clearly understandable. Provide an easy-to-read title and a thoughtful description explaining the reasoning behind the strategy.
All content should be ad-free. Avoid any form of promotion, advertising, or solicitation.
No fundraising requests or money solicitation is allowed on TradingView.
Publish in the same language as the TradingView subdomain you're on, except for script titles, which must be in English.
Don't plagiarize. Create and share only unique content, and always give credit when using someone else's work.
Be respectful, kind, and constructive when engaging with others.
Zero tolerance for contentious political discourse, defamatory, threatening, or discriminatory remarks.
Avoid sharing harmful, misleading, or inappropriate content.
Respect the moderators' work and address complaints privately.
Use only your original account and avoid creating duplicate or fake accounts.
Do not attempt to manipulate the reputation system or engage in like-for-like schemes.
Explanation of how the strategy works
1. Previous Day's High and Low (HH, LL):
In this strategy, we start by obtaining the high and low prices of the previous day (not the current day) using the request.security function. This function allows us to access historical data for a specific time frame. The high and low prices are stored in the variables HH and LL, respectively.
2. Entry Conditions:
The strategy uses two conditions to trigger a long position:
Condition 1 (Long Condition 1): If the closing price of the current day crosses above the previous day's high (HH), it generates a long signal. This is achieved using the ta.crossover function, which detects when a crossover occurs.
Condition 2 (Long Condition 2): Similarly, if the closing price of the current day crosses above the previous day's low (LL), it also generates a long signal.
Combined Condition: To take long positions, the strategy combines both long conditions using the logical OR operator (or). This means that if either of the two conditions is met, a long position will be initiated.
3. Market Strength Filter:
The strategy also includes a filter based on the Average Directional Index (ADX) to gauge the market's strength before taking long positions. The ADX measures the strength of a trend in the market. The higher the ADX value, the stronger the trend.
Calculation of ADX: The ADX is calculated using the adx function, which takes two parameters: LWdilength (DMI Length) and LWadxlength (ADX period).
Strength Condition (strength_up): The strategy requires that the ADX value should be above a threshold (11 in this case) and that there is a predominance of upward movement (up > down) before initiating a long position. The LWADX value is multiplied by 2.5 and compared to the highest value of LWADX from the last 4 periods using ta.highest(LWADX , 4). If these conditions are met, the variable strength_up is set to true.
Combined Condition: The strength_up condition is then combined with the long conditions using the logical AND operator (and). This means that the strategy will only take a long position if both the long conditions and the market strength condition are met.
4. Trade Timing:
The strategy sets a specific trade window between 09:30 and 15:10. It will only execute trades within this time frame (TradeTime).
5. Risk Management:
The strategy implements dynamic stop-loss (SL) and profit-taking levels (T1, T2, T3) based on a user-defined Max Profit value. The stop-loss is set as a percentage of the Max Profit value. As the position moves in favor of the trader, the profit targets are adjusted accordingly.
6. Position Management:
The strategy uses the strategy.entry function to enter long positions based on the combined entry conditions. Once a position is open, the script uses strategy.exit to define the exit condition when either the profit target or stop-loss level is hit. The strategy.close function is used to close any open position at the end of the trade window (15:15).
7. Plotting:
The strategy uses the plot function to visualize the previous day's high and low prices, as well as the stop-loss (SL) and profit-taking (T1, T2, T3) levels on the chart.
Overall, the "Previous Day High Low Strategy only for Long" aims to identify potential long trading opportunities based on the previous day's price action and market strength conditions. However, as with any trading strategy, it's essential to thoroughly test it and consider risk management before applying it to real-world trading scenarios.
Disclaimer:
The information presented by this strategy is for educational purposes only and should not be considered as investment advice. The strategy is not designed for qualified investors. Always conduct your own research and consult with a financial advisor before making any trading decisions.
Remember, the success of any trading strategy depends on various factors, including market conditions, risk management, and individual trading skills. Past performance is not indicative of future results.
[pAulseperformance] PSStrategyX█ OVERVIEW
This script reduces the amount of time it takes to turn your indicator into a live trading bot.
It will convert your signals into alerts that will be sent to your exchange for trading.
The script features a broker connector to automate alert syntax and connect with third-party exchanges to live trade strategies with minimal setup.
It also includes an enhanced version of the built-in backtester with customizable options to speed up backtesting, trade-by-trade statistics, and a chart strategy summary to help traders make informed decisions.
The PSStrategyX trading tool is designed to provide traders with a range of benefits, including:
Increased confidence in their strategies.
Better understanding of the accuracy of indicator signals.
Simplified automated trading through third-party broker connections.
Reduced time to develop strategies by focusing on signal development only. No need to work with complicated strategy testing code and 3rd party automation.
█ FEATURES
Broker Connector
— Supports Autoview (More Connectors added in the future)
— Connects and auto trades with most exchanges
— No need for Webhooks (AutoView)
— Can forward test live strategies on Testnets before using real money.
Built in Backtester loaded with options to speed up backtesting
— Standard strategy features including stop loss, take profit, and various filters reduce the time and complexity involved in building a working strategy.
Trade By Trade Statistics
— Gain insight on every trade with additional trade-by-trade statistics.
Strategy Summary
— Get instant feedback on your chart of your strategies performance. Visual cues and feedback give you hints on where to look and what to improve.
Strategy Tester Enhancements
— Take the max trades allowed in the strategy tester without errors.
— Take the largest or smallest trade allowed without errors.
█ WHY?
The PSStrategyX tool was developed to solve a common problem faced by traders who use Pine Script on TradingView: the inability to integrate Pine Script with exchanges through TradingView.
Without this integration, traders need to go through several extra steps to live trade their Pine Script strategies on a real exchange with real money. This includes finding a broker, learning the new syntax for the broker, and placing that syntax correctly in the strategy.
These steps can be time-consuming and add complexity to the codebase.
The PSStrategyX tool simplifies this process by automatically configuring the correct alert syntax to connect to third-party exchanges, allowing traders to live trade their strategies with minimal setup. This saves traders time and effort, allowing them to focus on signal development rather than complicated strategy testing code and 3rd party automation.
Additionally, the tool was developed to address the time-consuming task of converting any one of the thousands of great free indicators on TradingView to strategies through hours of coding.
Overall, I built the PSStrategyX to streamline the auto trading process and make auto trading more accessible to traders of all levels.
█ HOW TO USE THIS?
Using the PSStrategyX trading tool is a straightforward process that requires a few key steps:
1 — Generate trading signals: You need a signal generator that can provide buy and sell signals for your preferred trading instrument(s).
You can use TradingView's indicators or create your own custom indicators using TradingView's Pine programming language.
2 — Connect trading signals to PSStrategyX: You will use 2 scripts on your chart. One generates buy/sell/exit signals, and the other is the PSStrategyX script executing those signals as trades.
To set this up you will need to make sure that your signal generator is an indicator, NOT a strategy.
Make sure the signals are being plotted buy = 1; sell = -1; exit = 0; signals in one plot. Exits are optional.
Example plot(buy ? 1 : sell ? -1 : exit ? 0 : na)
You will choose the plot with buy/sell/exit signals inside the PSStrategyX tool to execute trades. If you need help, check out the docs for more details.
3 — Set up the broker connector (optional): If you want to take live trades with this tool, you will need to set up a third party connecter. Once set up, everything is automated. See more details in the "authors instructions." at the bottom of this post.
4 — Set up an exchange account (optional): If you want to trade on an exchange, you will need to set up an account with the exchange you plan to use.
The Broker Connector supports a range of popular exchanges, including Binance, Bitfinex, Kraken, Oanda and more.
Once you have generated your trading signals, set up the Broker connecter (optional) and set up an exchange account (optional), you can start using the PSStrategyX trading tool to execute trades automatically based on your trading signals.
█ LIMITATIONS
Here are some important limitations to keep in mind when using the PSStrategyX trading tool:
General:
— Once the alert is sent, there is no way to monitor positions on any exchange. The order will be processed by the broker connector and sent to the exchange.
While this usually works fine, it's important to check the log for errors.
Sometimes the broker connector may fail to process the order, or the exchange may not process it for various reasons.
— The tool sends TP/SL orders with the entry order when possible to protect your order in case of errors or if you lose a connection.
However, not all exchanges accept TP/SL orders, and sometimes your entry order will be left unprotected.
FIFO:
— This tool DOES NOT support the First In First Out (FIFO) method for closing positions.
— Instead, it uses the ANY method. There currently is no way to make this variable.
█ FAQ
What does PSStrategyX do exactly?
PSStrategyX is a strategy enhancing, backtester, forwardtester, automation and simulation tool. It's NOT a signal generator, and does not produce buy/sell signals by itself. You provide buy/sell signals, and PSStrategyX will put those signals on steroids...basically.
PSStrategyX helps you figure out what indicators actually work. Without wasting time learning how to code.
Why did you choose AutoView for this tool?
AutoView offered the best integration I could find. They allow you to connect to test exchanges for free, which is great for practicing without using real money. They also work without using webhooks, which means you can live trade without paying for Tradingview pro. Additionally, AutoView supports many different exchanges. I don't work for AutoView, but if you sign up through my referral link and purchase a paid version, I earn a commission.
Why doesn't Tradingview automatically connect Pine Script to exchanges?
This is a great question, but unfortunately I don't have the answer. It would definitely be helpful if Tradingview provided this feature, but it might also put some brokers out of business.
How do I get access?
DON'T ask for access in the comments.
DO review the "Authors Instructions" on this page for details.
Rsi strategy for BTC with (Rsi SPX)
I hope this strategy is just an idea and a starting point, I use the correlation of the Sp500 with the Btc, this does not mean that this correlation will exist forever!. I love Trading view and I'm learning to program, I find correlations very interesting and here is a simple strategy.
This is a trading strategy script written in Pine Script language for use in TradingView. Here is a brief overview of the strategy:
The script uses the RSI (Relative Strength Index) technical indicator with a period of 14 on two securities: the S&P 500 (SPX) and the symbol corresponding to the current chart (presumably Bitcoin, based on the variable name "Btc_1h_fixed"). The RSI is plotted on the chart for both securities.
The script then sets up two trading conditions using the RSI values:
A long entry condition: when the RSI for the current symbol crosses above the RSI for the S&P 500, a long trade is opened using the "strategy.entry" function.
A short entry condition: when the RSI for the current symbol crosses below the RSI for the S&P 500, a short trade is opened using the "strategy.entry" function.
The script also includes a take profit input parameter that allows the user to set a percentage profit target for closing the trade. The take profit is set using the "strategy.exit" function.
Overall, the strategy aims to take advantage of divergences in RSI values between the current symbol and the S&P 500 by opening long or short trades accordingly. The take profit parameter allows the user to set a specific profit target for each trade. However, the script does not include any stop loss or risk management features, which should be considered when implementing the strategy in a real trading scenario.
Kioseff Trading - AI-Powered Strategy Optimizer Introducing the Kioseff Trading AI-Powered Strategy Optimizer
Optimize and build your trading strategy with ease, no matter your experience level. The Kioseff Trading AI-Powered Strategy Optimizer allows traders to efficiently test and refine strategies with thousands of different profit targets and stop loss settings. Integrated with TradingView's backtester, this tool simplifies strategy optimization, strategy testing, and alert setting, enabling you to enhance your strategy with AI-driven insights.
Key Features:
Comprehensive Testing : Simultaneously test thousands of profit targets and stop losses to fine-tune your strategy.
Dual Strategy Optimization : Adjust and optimize both long and short strategies for balanced performance.
AI Integration : Elevate your strategy with heuristic-based adaptive learning, turning it into a smart, AI-assisted system.
Detailed Analysis : View critical metrics like profit factor, win rate, max drawdown, and equity curve, presented in a strategy script format.
Customizable Alerts : Set alerts for the best version of your strategy.
Flexible Risk Management : Optimize various stop loss types, including profit targets, limit orders, OCO orders, trailing stops, and fixed stops.
Targeted Goals : Choose optimization goals like highest win rate, maximum net profit, or most efficient profit.
Indicator Compatibility : Integrate any strategy/indicator, whether it’s your creation, a favorite author’s, or any public TradingView indicator.
Accessible Design : Navigate a user-friendly interface suitable for traders of all skill levels. No code required.
Precision Lock-In : “Lock” your optimal profit target or stop loss to drill down into precision testing of other variables.
How it works
It's important to remember that merely having the AI-Powered Strategy Optimizer on your chart doesn't automatically provide you with the best strategy. You need to follow the AI's guidance through an iterative process to discover the optimal settings for your strategy.
The Trading Strategy Optimizer is a versatile tool tailored for both non-coding traders and seasoned algorithmic trading professionals. Let's start with no-code-required instructions on how to use the optimizer.
Instructions: How To Optimize Your Strategy Without Code
1. Build your strategy in the settings
The image above shows explanations for each key setting.
Note: This example uses the RSI indicator to initiate a long trade whenever it dips below the 30 mark.
Ensure that the indicator you wish to optimize is already applied to your chart . This enables the Trading Strategy Optimizer to interact with the indicator and finetune profit targets and stop losses effectively.
Because the indicator is plotted on the chart I can access the indicator with the Trading Strategy Optimizer and optimize profit targets and stop losses for it.
2. Leverage AI Recommendations
Optimization Prompt: After you load your strategy, the tool advises you on new TP and SL levels that could be more profitable.
When your strategy is set, the tool gives you tips for where to set your profit goal (TP) and your stop loss to help you optimize your strategy. It'll tell you if there's a better range for these settings based on past results.
Follow Suggestions: Keep updating your TP and SL according to the tool's suggestions until it says "Best Found".
Final Result: The last image shows the best settings found by the indicator.
(Optional Step 3)
3. Lock the profit target or stop loss to further fine tune your strategy
Continue following the AI’s suggestion until “Best Found” is displayed.
Note: you can select lock either your stop loss or profit target for fine tuning. For this demonstration we will lock our profit target.
Code-Required Instructions (Optional)
You can backtest more code-intensive strategies, such as harmonic patterns, traditional chart patterns, candlestick patterns, Elliot wave, etc., by coding the entry condition in your own script and loading it into the Trading Strategy Optimizer. Let's dial in on how to achieve this!
1. You must create an integer variable in your script with an initial value of "0".
2. Define your entry condition in the code. Once complete, assign the value "1" to the variable you created if the entry condition is fulfilled.
3. Plot your variable.
4. Select the plotted variable in the settings for the Trading Strategy Optimizer
The image above shows a coded entry condition for the linear regression channel (which can be any indicator). When price crosses under and closes below the lower line our variable "strategyEntryVariable" is assigned the value "1".
The Trading Strategy Optimizer will treat this change in value from "0" to "1" as an entry signal and enter long/short up to 1000 times at the price where the entry condition was fulfilled.
5. Test Your Strategy
The image above shows the completion of the process! Keep applying the steps we described. Stick with the AI's recommendations until you see “Best Found” show up.
By following these instructions, you can build, test, and optimize almost any trading indicator or strategy!
So, just note that the Trading Strategy Optimizer considers a change in value of a plotted variable from "0" to "1" as an entry signal! So long as you follow this rule you should be able to test and optimize any conceivable, Pine Script compatible strategy!
AI Mode
AI Mode incorporates Heuristic-Based Adaptive Learning to fine-tune trading strategies in a continuous manner. This feature consists of two main components:
Heuristic-Based Decision Making: The algorithm evaluates multiple versions of your strategy using specific metrics such as Profit and Loss (PNL), Win Rate, and Most Efficient Profit. These metrics act as heuristics to assist the algorithm in identifying suitable profit targets and stop losses for trade execution.
Online Learning: The algorithm updates the performance evaluations of each strategy based on incoming market data. This enables the system to adapt to current market conditions.
Incorporating both heuristic-based decision-making and online learning, this feature aims to provide a framework for trading strategy optimization.
Settings
AI Mode Aggressiveness:
Description: The "AI Mode Aggressiveness" setting allows you to fine-tune the AI's trading behavior. This setting ranges from "Low" To "High, with higher aggressiveness indicating a more assertive trading approach.
Functionality: This feature filters trading strategies based on a proprietary evaluation method. A higher setting narrows down the strategies that the AI will consider, leaning towards more aggressive trading. Conversely, a lower setting allows for a more conservative approach by broadening the pool of potential strategies.
Adaptive Learning Aggressiveness:
Description: When Adaptive Learning is enabled, the "Adaptive Learning Aggressiveness" setting controls how dynamically the AI adapts to market conditions using selected performance metrics.
Functionality: This setting impacts the AI's responsiveness to shifts in strategy performance. By adjusting this setting, you can control how quickly the AI moves away from strategies that may have been historically successful but are currently underperforming, towards strategies that are showing current promise.
Additional Settings
Optimization
Trading system optimization is immensely advantageous when executed with prudence.
Technical-oriented, mechanical trading systems work when a valid correlation is methodical to the extent that an objective, precisely-defined ruleset can consistently exploit it. If no such correlation exists, or a technical-oriented system is erroneously designed to exploit an illusory correlation (absent predictive utility), the trading system will fail.
Evaluate results practically and test parameters rigorously after discovery. Simply mining the best-performing parameters and immediately trading them is unlikely a winning strategy. Put as much effort into testing strong-performing parameters and building an accompanying system as you would any other trading strategy. Automated optimization involves curve fitting - it's the responsibility of the trader to validate a replicable sequence or correlation and the trading system that exploits it.
Kioseff Trading - AI-Optimized RSIAI-Optimized RSI
Introducing AI-Optimized RSI: a streamlined solution for traders of any skill level seeking to rapidly test and optimize RSI. Capable of analyzing thousands of strategies, this tool cuts through the complexity to identify the most profitable, reliable, or efficient approaches.
Paired with TradingView's native backtesting capabilities, the AI-Optimized RSI learns from historical performance data. Set up is easy for all skill levels, and it makes fine-tuning trading alerts and RSI straightforward.
Features
Purpose : Uncover optimal RSI settings and entry levels with precision. Say goodbye to random guesses and arbitrary indicator use—this tool provides clear direction based on data.
Target Performance : You set the goal, and AI-RSI seeks it out, whether it's maximizing profits, efficient trading, or achieving the highest win rate.
AI-Powered : With intelligent AI recommendations, the tool dynamically fine-tunes your RSI approach, steering you towards ideal strategy performance.
Rapid Testing : Evaluate thousands of RSI strategies.
Dual Direction : Perfect both long and short RSI strategies with equal finesse.
Deep Insights : Access detailed metrics including profit factor, PnL, win rate, trade counts, and more, all within a comprehensive strategy script.
Instant Alerts : Set alerts and trade.
Full Customization : Test and optimize all RSI settings, including cross levels, profit targets and stop losses.
Simulated Execution : Explore the impact of limit orders and other trade types through simulation.
Integrative Capability : Combine your own custom indicators or others from the TradingView community for a personalized optimization experience.
Flexible Timeframes : Set your optimization and backtesting to any date range.
Key Settings
The image above shows explanations for a list of key settings for the optimizer.
Direction : This setting controls trade direction: Long or Short.
Entry Condition : Define RSI entry: Select whether to trigger trades on RSI crossunders or crossovers.
RSI Lengths Range : Choose the range of RSI periods to test and find the best one.The AI will find the best RSI period for you.
RSI Cross Range : Set the range for RSI levels where crosses trigger trade signals. The AI will find the best level for you.
Combinations : Select how many RSI strategies to compare.
Optimization Type : Choose the goal for optimization and the AI: profit, win rate, or efficiency.
Profit Target : Set your profit target with this setting.
Stop Loss : Decide your maximum allowable loss (stop loss) per trade.
Limit Order : Specify whether to include limit orders in the strategy.
Stop Type : Choose your stop strategy: a fixed stop loss or a trailing stop.
How to: Find the best RSI for trading
It's important to remember that merely having the AI-Optimized RSI on your chart doesn't automatically provide you with the best strategy. You need to follow the AI's guidance through an iterative process to discover the optimal RSI settings and strategy.
1.Starting Your Strategy Setup
Begin by deciding your goals for each trade: your profit target and stop loss. You'll also choose how to manage your stops – whether they stay put (fixed) or move with the price (trailing), and whether you want to exit trades at a specific price (limit orders). Keep the initial settings for RSI lengths and cross ranges at their default to give the tool a broad testing field. The AI's guidance will refine these settings to pinpoint the most effective ones through a process of comprehensive testing.
The image above shows our chart prior to any optimization efforts.
Note: the settings shown above in the key settings section will be used to start our demonstration.
2. Follow AI’s suggestions
Optimization Prompt: After loading your strategy, the indicator will prompt you to change the RSI length range and RSI level range to a better performing range.
Continue changing the RSI length range and RSI level range to match the indicator's suggestions until "Best Found" is displayed!
The image above shows results after we applied the tool’s suggestions. New suggestions have appeared, and we will continue to apply them.
Continue to adjust settings as recommended by the optimizer. If no better options are found, the optimizer will suggest increasing the number of combinations. Repeat this process until the optimizer indicates that the optimal setting has been identified.
Success! With the "Best Found" notification, an optimized RSI is now active. The AI will keep refining the strategy based on ongoing performance, ensuring continuous optimization.
AI Mode
AI Mode incorporates Heuristic-Based Adaptive Learning to fine-tune trading strategies in a continuous manner. This feature consists of two main components:
Heuristic-Based Decision Making: The algorithm evaluates multiple RSI-based trading strategies using specific metrics such as Profit and Loss (PNL), Win Rate, and Most Efficient Profit. These metrics act as heuristics to assist the algorithm in identifying suitable strategies for trade execution.
Online Learning: The algorithm updates the performance evaluations of each strategy based on incoming market data. This enables the system to adapt to current market conditions.
Incorporating both heuristic-based decision-making and online learning, this feature aims to provide a framework for trading strategy optimization.
Settings
AI Mode Aggressiveness:
Description: The "AI Mode Aggressiveness" setting allows you to fine-tune the AI's trading behavior. This setting ranges from “Low” to “High”, with “High” indicating a more assertive trading approach.
Functionality: This feature filters trading strategies based on a proprietary evaluation method. A higher setting narrows down the strategies that the AI will consider, leaning towards more aggressive trading. Conversely, a lower setting allows for a more conservative approach by broadening the pool of potential strategies.
Adaptive Learning Aggressiveness:
Description: When Adaptive Learning is enabled, the "Adaptive Learning Aggressiveness" setting controls how dynamically the AI adapts to market conditions using selected performance metrics.
Functionality: This setting impacts the AI's responsiveness to shifts in strategy performance. By adjusting this setting, you can control how quickly the AI moves away from strategies that may have been historically successful but are currently underperforming, towards strategies that are showing current promise.
Optimization
Trading system optimization is immensely advantageous when executed with prudence.
Technical-oriented, mechanical trading systems work when a valid correlation is methodical to the extent that an objective, precisely-defined ruleset can consistently exploit it. If no such correlation exists, or a technical-oriented system is erroneously designed to exploit an illusory correlation (absent predictive utility), the trading system will fail.
Evaluate results practically and test parameters rigorously after discovery. Simply mining the best-performing parameters and immediately trading them is unlikely a winning strategy. Put as much effort into testing strong-performing parameters and building an accompanying system as you would any other trading strategy. Automated optimization involves curve fitting - it's the responsibility of the trader to validate a replicable sequence or correlation and the trading system that exploits it.
3LS | 3 Line Strike Strategy [Kintsugi Trading]What is the 3LS | 3 Line Strike Strategy?
Incorporating the 3 Line Strike candlestick pattern into our strategy was inspired by Arty at The Moving Average and the amazing traders at TheTrdFloor .
The Three Line Strike is a trend continuation candlestick pattern consisting of four candles. Depending on their heights and collocation, a bullish or a bearish trend continuation can be predicted.
In a symphony of trend analysis, price action, and volume we can find and place high-probability trades with the 3LS Strategy.
How to use it!
----- First, start by choosing a Stop-Loss Strategy, Stop PIP Size, and Risk/Reward Ratio -----
- Stop-Loss Strategy
Fixed PIP Size – This uses the top/bottom of the indicator candle and places a TP based on the chosen Risk:Reward ratio.
ATR Trail (No set Target Profit, only uses ATR Stop)
ATR Trail-Stop (Has set Target Profit, however, stop is based on ATR inputs)
**If you choose an ATR Stop-Loss Strategy - input the desired ATR period and Multiple you would like the stop to be calculated at**
**ATR Stop-Loss Strategies have a unique alert setup for Auto-Trading. See Auto-Trading Section**
- Risk/Reward Ratio = If you have a .5 risk/reward, it means you are risking $100 to make $50.
- Additional Stop PIP Size = Number of PIPs over the default stop location of the top or bottom of the indicator candle.
----- Next, we set the Session Filter -----
Set the Timezone and Trade Session you desire. If no specific session is desired, simply set the Trade Session to 00:00 - 00:00.
----- Next, we set the Moving Average Cloud Fill -----
Enter the Fast and Slow Moving Average Length used to calculate trend direction:
MA Period Fast
MA Period Slow
These inputs will determine whether the strategy looks for Long or Short positions.
----- Next, we set the VSA – Volume Spread Analysis Settings -----
Check the box to show the indicator at the bottom of the chart if desired.
This is just a different visual output of the VSA | Volume Spread Analysis indicator available for free under the community indicators tab. You can add that indicator to your chart and see the same output in candle format.
In combination with the Moving Average Cloud, the Volume Spread Analysis will help us determine when to take a trade and in what direction.
The strategy is essentially looking for small reversals going against the overall trend and placing a trade once that reversal ends and the price moves back in the direction of the overall trend.
The 3LS Strategy utilizes confirmation between trend, volume, and price action to place high probability trades.
The VSA is completely customizable by:
Moving Average Length
MA-1 Multiplier
MA-2 Multiplier
MA-3 Multiplier
Check out the VSA | Volume Spread Analysis indicator in the community scripts section under the indicators tab to use this awesome resource on other strategies.
----- Next, we have the option to view the automated KT Bull/Bear Signals -----
Check the boxes to show the buy-sell signal on the chart if desired.
----- Next, we set the risk we want to use if Auto Trading the strategy -----
I always suggest using no more than 1-3% of your total account balance per trade. Remember, if you have multiple strategies triggering per day with each using 1%, the total percent at risk will be much larger.
For Example – if you have 10 strategies each risking 1% your total risk is 10% of your account, not 1%! Be mindful to only use 1-3% of your total account balance across all strategies, not just each individual one.
----- Finally, we backtest our ideas -----
After using the 'Strategy Tester' tab on TradingView to thoroughly backtest your predictions you are ready to take it to the next level - Automated Trading!
This was my whole reason for creating the script. If you work a full-time job, live in a time zone that is hard to trade, or just don't have the patience, this will be a game-changer for you as it was for me.
Auto-Trading
When it comes to auto-trading this strategy I have included two options in the script that utilize the alert messages generated by TradingView.
*Note: Please trade on a demo account until you feel comfortable enough to use real money, and then please stick to 1%-2% of your total account value in risk per trade.*
AutoView
PineConnector
**ATR Auto-Trading Alert Setup**
How to create alerts on 3 Line Strike Strategy
For Trailing Stops:
1) Adjust autoview/pineconnector settings
2) Click "add alert"
3) Select "Condition" = Strategy Name
4) Select "Order Fills Only" from the drop-down
3) Remove template message text from "message" box and place the exact text. '{{strategy.order.alert_message}}'
4) Click "create"
For Fixed Pip Stop:
1) Adjust autoview/pineconnector settings
2) Click "add alert"
3) Select "Condition" = Strategy Name
4) Select "alert() function calls only"
5) I like to title my Alert Name the same thing I named it as an Indicator Template to keep track
Good luck with your trading!
Bjorgum Double Tap█ OVERVIEW
Double Tap is a pattern recognition script aimed at detecting Double Tops and Double Bottoms. Double Tap can be applied to the broker emulator to observe historical results, run as a trading bot for live trade alerts in real time with entry signals, take profit, and stop orders, or to simply detect patterns.
█ CONCEPTS
How Is A Pattern Defined?
Doubles are technical formations that are both reversal patterns and breakout patterns. These formations typically have a distinctive “M” or a “W” shape with price action breaking beyond the neckline formed by the center of the pattern. They can be recognized when a pivot fails to break when tested for a second time and the retracement that follows breaks beyond the key level opposite. This can trap entrants that were playing in the direction of the prior trend. Entries are made on the breakout with a target projected beyond the neckline equal to the height of the pattern.
Pattern Recognition
Patterns are recognized through the use of zig-zag; a method of filtering price action by connecting swing highs and lows in an alternating fashion to establish trend, support and resistance, or derive shapes from price action. The script looks for the highest or lowest point in a given number of bars and updates a list with the values as they form. If the levels are exceeded, the values are updated. If the direction changes and a new significant point is made, a new point is added to the list and the process starts again. Meanwhile, we scan the list of values looking for the distinctive shape to form as previously described.
█ STRATEGY RESULTS
Back Testing
Historical back testing is the most common method to test a strategy due in part to the general ease of gathering quick results. The underlying theory is that any strategy that worked well in the past is likely to work well in the future, and conversely, any strategy that performed poorly in the past is likely to perform poorly in the future. It is easy to poke holes in this theory, however, as for one to accept it as gospel, one would have to assume that future results will match what has come to pass. The randomness of markets may see to it otherwise, so it is important to scrutinize results. Some commonly used methods are to compare to other markets or benchmarks, perform statistical analysis on the results over many iterations and on differing datasets, walk-forward testing, out-of-sample analysis, or a variety of other techniques. There are many ways to interpret the results, so it is important to do research and gain knowledge in the field prior to taking meaningful conclusions from them.
👉 In short, it would be naive to place trust in one good backtest and expect positive results to continue. For this reason, results have been omitted from this publication.
Repainting
Repainting is simply the difference in behaviour of a strategy in real time vs the results calculated on the historical dataset. The strategy, by default, will wait for confirmed signals and is thus designed to not repaint. Waiting for bar close for entires aligns results in the real time data feed to those calculated on historical bars, which contain far less data. By doing this we align the behaviour of the strategy on the 2 data types, which brings significance to the calculated results. To override this behaviour and introduce repainting one can select "Recalculate on every tick" from the properties tab. It is important to note that by doing this alerts may not align with results seen in the strategy tester when the chart is reloaded, and thus to do so is to forgo backtesting and restricts a strategy to forward testing only.
👉 It is possible to use this script as an indicator as opposed to a full strategy by disabling "Use Strategy" in the "Inputs" tab. Basic alerts for detection will be sent when patterns are detected as opposed to complex order syntax. For alerts mid-bar enable "Recalculate on every tick" , and for confirmed signals ensure it is disabled.
█ EXIT ORDERS
Limit and Stop Orders
By default, the strategy will place a stop loss at the invalidation point of the pattern. This point is beyond the pattern high in the case of Double Tops, or beneath the pattern low in the case of Double Bottoms. The target or take profit point is an equal-legs measurement, or 100% of the pattern height in the direction of the pattern bias. Both the stop and the limit level can be adjusted from the user menu as a percentage of the pattern height.
Trailing Stops
Optional from the menu is the implementation of an ATR based trailing stop. The trailing stop is designed to begin when the target projection is reached. From there, the script looks back a user-defined number of bars for the highest or lowest point +/- the ATR value. For tighter stops the user can look back a lesser number of bars, or decrease the ATR multiple. When using either Alertatron or Trading Connector, each change in the trail value will trigger an alert to update the stop order on the exchange to reflect the new trail price. This reduces latency and slippage that can occur when relying on alerts only as real exchange orders fill faster and remain in place in the event of a disruption in communication between your strategy and the exchange, which ensures a higher level of safety.
👉 It is important to note that in the case the trailing stop is enabled, limit orders are excluded from the exit criteria. Rather, the point in time that the limit value is exceeded is the point that the trail begins. As such, this method will exit by stop loss only.
█ ALERTS
Five Built-in 3rd Party Destinations
The following are five options for delivering alerts from Double Tap to live trade execution via third party API solutions or chat bots to share your trades on social media. These destinations can be selected from the input menu and alert syntax will automatically configure in alerts appropriately to manage trades.
Custom JSON
JSON, or JavaScript Object Notation, is a readable format for structuring data. It is used primarily to transmit data between a server and a web application. In regards to this script, this may be a custom intermediary web application designed to catch alerts and interface with an exchange API. The JSON message is a trade map for an application to read equipped with where its been, where its going, targets, stops, quantity; a full diagnostic of the current state and its previous state. A web application could be configured to follow the messages sent in this format and conduct trades in sync with alerts running on the TV server.
Below is an example of a rendered JSON alert:
{
"passphrase": "1234",
"time": "2022-05-01T17:50:05Z",
"ticker": "ETHUSDTPERP",
"plot": {
"stop_price": 2600.15,
"limit_price": 3100.45
},
"strategy": {
"position_size": 0.1,
"order_action": "buy",
"market_position": "long",
"market_position_size": 0,
"prev_market_position": "flat",
"prev_market_position_size": 0
}
}
Trading Connector
Trading Connector is a third party fully autonomous Chrome extension designed to catch alert webhooks from TradingView and interface with MT4/MT5 to execute live trades from your machine. Alerts to Trading Connector are simple; just select the destination from the input drop down menu, set your ticker in the "TC Ticker" box in the "Alert Strings" section and enter your URL in the alert window when configuring your alert.
Alertatron
Alertatron is an automated algo platform for cryptocurrency trading that is designed to automate your trading strategies. Although the platform is currently restricted to crypto, it offers a versatile interface with high flexibility syntax for complex market orders and conditions. To direct alerts to Alertatron, select the platform from the 3rd party drop down, configure your API key in the ”Alertatron Key” box and add your URL in the alert message box when making alerts.
3 Commas
3 Commas is an easy and quick to use click-and-go third party crypto API solution. Alerts are simple without overly complex syntax. Messages are simply pasted into alerts and executed as alerts are triggered. There are 4 boxes at the bottom of the "Inputs" tab where the appropriate messages to be placed. These messages can be copied from 3 Commas after the bots are set up and pasted directly into the settings menu. Remember to select 3 Commas as a destination from the third party drop down and place the appropriate URL in the alert message window.
Discord
Some may wish to share their trades with their friends in a Discord chat via webhook chat bot. Messages are configured to notify of the pattern type with targets and stop values. A bot can be configured through the integration menu in a Discord chat to which you have appropriate access. Select Discord from the 3rd party drop down menu and place your chat bot URL in the alert message window when configuring alerts.
👉 For further information regarding alert setup, refer to the platform specific instructions given by the chosen third party provider.
█ IMPORTANT NOTES
Setting Alerts
For alert messages to be properly delivered on order fills it is necessary to place the following placeholder in the alert message box when creating an alert.
{{strategy.order.alert_message}}
This placeholder will auto-populate the alert message with the appropriate syntax that is designated for the 3rd party selected in the user menu.
Order Sizing and Commissions
The values that are sent in alert messages are populated from live metrics calculated by the strategy. This means that the actual values in the "Properties" tab are used and must be set by the user. The initial capital, order size, commission, etc. are all used in the calculations, so it is important to set these prior to executing live trades. Be sure to set the commission to the values used by the exchange as well.
👉 It is important to understand that the calculations on the account size take place from the beginning of the price history of the strategy. This means that if historical results have inflated or depleted the account size from the beginning of trade history until now, the values sent in alerts will reflect the calculated size based on the inputs in the "Properties" tab. To start fresh, the user must set the date in the "Inputs" tab to the current date as to remove trades from the trade history. Failure to follow this instruction can result in an unexpected order size being sent in the alert.
█ FOR PINECODERS
• With the recent introduction of matrices in Pine, the script utilizes a matrix to track pivot points with the bars they occurred on, while tracking if that pivot has been traded against to prevent duplicate detections after a trade is exited.
• Alert messages are populated with placeholders ; capability that previously was only possible in alertcondition() , but has recently been extended to `strategy.*()` functions for use in the `alert_message` argument. This allows delivery of live trade values to populate in strategy alert messages.
• New arguments have been added to strategy.exit() , which allow differentiated messages to be sent based on whether the exit occurred at the stop or the limit. The new arguments used in this script are `alert_profit` and `alert_loss` to send messages to Discord
