UJM15ReversalBotThis Strategy is specifically designed to trade on USDJPY intraday reversals on m15 time frame.
Cerca negli script per "liquidity"
AP_SessionStockFadeDeveloper: Andrew Palladino
Date: 10/23/2017
Description:
The strategy will buy over extended price conditions using the following criteria:
Suppose we are interested in capturing the total drop in points between two times during a session.
The times are defaulted to 9:30 AM and 3:45 PM.
The drop has to exceed a threshold set by the user, which is currently set to 50 cents.
If the current drop between the two time sessions exceeds 50 cents, then a buy limit is set at a multiple of the current drop of the day. For example, if the drop is 1 dollar, a buy limit is set at K*(1 dollar) away from close of the day. K is a multiple set by the user.
Once the buy limit is triggered, the strategy will have a target and stop. Current defaults are 90 cents for both.
If the order doesn't get hit before 12 PM of the following day, it will cancel. Cancel time is also set by the user.
The strategy settings will work on AAPL m15 time frame. Parameters will need to change for any other ticker/time frame combination.
AP_PatternsSysCreator: Andrew Palladino
Date: 10/22/2017
Strategy Name: Pattern Classifier System.
Description:
The strategy automatically classifies common price patterns using price fractals an trades them with an ATR based risk management strategy.
The following patterns are currently supported:
Symmetrical Triangle Breakout Long or Short
Ascending Triangle Long
Descending Triangle Short
Ascending Wedge Short
Descending Wedge Long
Future releases will include:
Rectangle Breakouts Long and Short
Head and Shoulders Patterns
The user has the ability to turn on or off any combinations of the individual patterns above.
AP_BigMoveFadeDeveloper: Andrew Palladino
Date: 10/19/2017
Description:
The setup is very basic.
Fade a Big Candle when candle size exceeds a certain number of pips defined by the user.
Target X pips defined by the user.
Stop Loss set at y pips, also defined by the user.
adx-breakout-rbDeveloper: Andrew Palladino
Creator: Rob Booker
Date: 9/29/2017
Description: Coming Soon.
ema200ct-strategyDeveloper: Andrew Palladino
Date: 9/26/2017
Description: Takes counter trend trades back to the 200 EMA when bars since an EMA 200 touch exceeds a predefined bar count and vertical distance to EMA is large. The trade is closed at the 200 EMA.
JSP-SPY-TrendSystemThis system is meant to be traded on the 60 minute chart. It buys SPY on pullbacks and sells after a fixed % gain.
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).
Payday Anomaly StrategyThe "Payday Effect" refers to a predictable anomaly in financial markets where stock returns exhibit significant fluctuations around specific pay periods. Typically, these are associated with the beginning, middle, or end of the month when many investors receive wages and salaries. This influx of funds, often directed automatically into retirement accounts or investment portfolios (such as 401(k) plans in the United States), temporarily increases the demand for equities. This phenomenon has been linked to a cycle where stock prices rise disproportionately on and around payday periods due to increased buy-side liquidity.
Academic research on the payday effect suggests that this pattern is tied to systematic cash flows into financial markets, primarily driven by employee retirement and savings plans. The regularity of these cash infusions creates a calendar-based pattern that can be exploited in trading strategies. Studies show that returns on days around typical payroll dates tend to be above average, and this pattern remains observable across various time periods and regions.
The rationale behind the payday effect is rooted in the behavioral tendencies of investors, specifically the automatic reinvestment mechanisms used in retirement funds, which align with monthly or semi-monthly salary payments. This regular injection of funds can cause market microstructure effects where stock prices temporarily increase, only to stabilize or reverse after the funds have been invested. Consequently, the payday effect provides traders with a potentially profitable opportunity by predicting these inflows.
Scientific Bibliography on the Payday Effect
Ma, A., & Pratt, W. R. (2017). Payday Anomaly: The Market Impact of Semi-Monthly Pay Periods. Social Science Research Network (SSRN).
This study provides a comprehensive analysis of the payday effect, exploring how returns tend to peak around payroll periods due to semi-monthly cash flows. The paper discusses how systematic inflows impact returns, leading to predictable stock performance patterns on specific days of the month.
Lakonishok, J., & Smidt, S. (1988). Are Seasonal Anomalies Real? A Ninety-Year Perspective. The Review of Financial Studies, 1(4), 403-425.
This foundational study explores calendar anomalies, including the payday effect. By examining data over nearly a century, the authors establish a framework for understanding seasonal and monthly patterns in stock returns, which provides historical support for the payday effect.
Owen, S., & Rabinovitch, R. (1983). On the Predictability of Common Stock Returns: A Step Beyond the Random Walk Hypothesis. Journal of Business Finance & Accounting, 10(3), 379-396.
This paper investigates predictability in stock returns beyond random fluctuations. It considers payday effects among various calendar anomalies, arguing that certain dates yield predictable returns due to regular cash inflows.
Loughran, T., & Schultz, P. (2005). Liquidity: Urban versus Rural Firms. Journal of Financial Economics, 78(2), 341-374.
While primarily focused on liquidity, this study provides insight into how cash flows, such as those from semi-monthly paychecks, influence liquidity levels and consequently impact stock prices around predictable pay dates.
Ariel, R. A. (1990). High Stock Returns Before Holidays: Existence and Evidence on Possible Causes. The Journal of Finance, 45(5), 1611-1626.
Ariel’s work highlights stock return patterns tied to certain dates, including paydays. Although the study focuses on pre-holiday returns, it suggests broader implications of predictable investment timing, reinforcing the calendar-based effects seen with payday anomalies.
Summary
Research on the payday effect highlights a repeating pattern in stock market returns driven by scheduled payroll investments. This cyclical increase in stock demand aligns with behavioral finance insights and market microstructure theories, offering a valuable basis for trading strategies focused on the beginning, middle, and end of each month.
Qullamaggie [Modified] | FractalystWhat's the purpose of this strategy?
The strategy aims to identify high-probability breakout setups in trending markets, inspired by Kristjan "Qullamaggie" Kullamägi’s approach.
It focuses on capturing explosive price moves after periods of consolidation, using technical criteria like moving averages, breakouts, trailing stop-loss and momentum confirmation.
Ideal for swing traders seeking to ride strong trends while managing risk.
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How does the strategy work?
The strategy follows a systematic process to capture high-momentum breakouts:
Pre-Breakout Criteria:
Prior Price Surge: Identifies stocks that have rallied 30-100%+ in recent month(s), signaling strong underlying momentum (per Qullamaggie’s volatility expansion principles).
Consolidation Phase: Looks for a tightening price range (e.g., flag, pennant, or tight base), indicating a potential "coiling" before continuation.
Trend Confirmation: Uses moving averages (e.g., 20/50/200 EMA) to ensure the stock is trading above key averages on the daily chart, confirming an uptrend.
Price Break: Enters when price clears the consolidation high with conviction.
Risk Management:
Initial Stop Loss: Placed below the consolidation low or a recent swing point to limit downside.
Break-Even Adjustment: Moves stop loss to breakeven once the trade reaches 1.5x risk-to-reward (RR), securing a "free trade" while letting winners run.
Trailing Stop (Unique Edge):
Market Structure Trailing: Instead of trailing via moving averages, the stop is dynamically adjusted using structural invalidation level. This adapts to price action, allowing the trade to stay open during volatile retracements while locking in gains as new structure forms.
Why This Matters: Most strategies use rigid trailing stops (e.g., below the 10EMA), which often exit prematurely in choppy markets. By trailing based on structure, this strategy avoids "noise" and captures larger trends, directly boosting overall returns.
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What markets or timeframes is this suited for?
This is a long-only strategy designed for trending markets, and it performs best in:
Markets: Stocks (especially high-growth, liquid equities), cryptocurrencies (major pairs with strong volatility), commodities (e.g., oil, gold), and futures (index/commodity futures).
Timeframes: Primarily daily charts for swing trades (1-30 day holds), though weekly charts can help confirm broader trends.
Key Advantage: The TradingView script allows instant backtesting with adjustable parameters
You can:
- Test historical performance across multiple markets to identify which assets align best with the strategy.
- Optimize settings (e.g., trailing stop sensitivity, moving averages etc.) to match a market’s volatility profile.
Build a diversified portfolio by filtering for markets that show consistent profitability in backtests.
For example, you might discover cryptos require tighter trailing stops due to volatility, while stocks thrive with wider structural stops. The script automates this analysis, letting you to trade confidently.
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What indicators or tools does the strategy use?
The strategy combines customizable technical tools with strict anti-lookahead safeguards:
Core Indicators:
Moving Averages: Adjustable periods (e.g., 20/50/200 EMA or SMA) and timeframes (daily/weekly) to confirm trend alignment. Users can test combinations (e.g., 10EMA vs. 20EMA) to optimize for specific markets.
Breakout Parameters:
Consolidation Length: Adjustable window to define the "tightness" of the pre-breakout pattern.
Entry Models: Flexible entry logics (Breakouts and fractals)
Anti-Lookahead Design:
All calculations (e.g., moving averages, consolidation ranges, volume averages) use only closed/confirmed data available at the time of the signal.
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How do I manage risk with this strategy?
The strategy prioritizes customizable risk controls to align with your trading style and account size:
User-Defined Risk Inputs:
Risk Per Trade: Set a % of Equity (e.g., 1-2%) to determine position size. The strategy auto-calculates shares/contracts to match your selected risk per trade.
Flexibility: Choose between fixed risk or equity-based scaling.
The script adjusts position sizing dynamically based on your selection.
Pyramiding Feature:
Customizable Entries: Adjust the number of pyramiding trades allowed (e.g., 1-3 additional positions) in the strategy settings. Each new entry is triggered only if the prior trade hits its 1.5x RR target and the trend remains intact.
Risk-Scaled Additions: New positions use profits from prior trades, compounding gains without increasing initial risk.
Risk-Free Trade Mechanic:
Once a trade reaches 1.5x RR, the stop loss is moved to breakeven, eliminating downside risk.
The strategy then opens a new position (if pyramiding is enabled) using a portion of the locked-in profit. This "snowballs" winners while keeping total capital exposure stable.
Impact on Net Profit & Drawdown:
Net Profit Boost: Pyramiding lets you ride multi-leg trends aggressively. For example, a 100% runner could generate 2-3x more profit vs. a single-entry approach.
Controlled Drawdowns: Since new positions are funded by profits (not initial capital), max drawdown stays anchored to your original risk per trade (e.g., 1-2% of account). Even if later entries fail, the breakeven stop on prior trades protects overall equity.
Why This Works: Most strategies either over-leverage (increasing drawdowns) or exit too early. By recycling profits into new positions only after securing risk-free capital, this approach mimics hedge fund "scaling in" tactics while staying retail-trader friendly.
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How does the strategy identify market structure for its trailing stoploss?
The strategy identifies market structure by utilizing an efficient logic with for loops to pinpoint the first swing candle that features a pivot of 2. This marks the beginning of the break of structure, where the market's previous trend or pattern is considered invalidated or changed.
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What are the underlying calculations?
The underlying calculations involve:
Identifying Swing Points: The strategy looks for swing highs (marked with blue Xs) and swing lows (marked with red Xs). A swing high is identified when a candle's high is higher than the highs of the candles before and after it. Conversely, a swing low is when a candle's low is lower than the lows of the candles before and after it.
Break of Structure (BOS):
Bullish BOS: This occurs when the price breaks above the swing high level of the previous structure, indicating a potential shift to a bullish trend.
Bearish BOS: This happens when the price breaks below the swing low level of the previous structure, signaling a potential shift to a bearish trend.
Structural Liquidity and Invalidation:
Structural Liquidity: After a break of structure, liquidity levels are updated to the first swing high in a bullish BOS or the first swing low in a bearish BOS.
Structural Invalidation: If the price moves back to the level of the first swing low before the bullish BOS or the first swing high before the bearish BOS, it invalidates the break of structure, suggesting a potential reversal or continuation of the previous trend.
This method provides users with a technical approach to filter market regimes, offering an advantage by minimizing the risk of overfitting to historical data, which is often a concern with traditional indicators like moving averages.
By focusing on identifying pivotal swing points and the subsequent breaks of structure, the strategy maintains a balance between sensitivity to market changes and robustness against historical data anomalies, ensuring a more adaptable and potentially more reliable market analysis tool.
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What entry criteria are used in this script?
The script uses two entry models for trading decisions: BreakOut and Fractal.
Underlying Calculations:
Breakout: The script records the most recent swing high by storing it in a variable. When the price closes above this recorded level, and all other predefined conditions are satisfied, the script triggers a breakout entry. This approach is considered conservative because it waits for the price to confirm a breakout above the previous high before entering a trade. As shown in the image, as soon as the price closes above the new candle (first tick), the long entry gets taken. The stop-loss is initially set and then moved to break-even once the price moves in favor of the trade.
Fractal: This method involves identifying a swing low with a period of 2, which means it looks for a low point where the price is lower than the two candles before and after it. Once this pattern is detected, the script executes the trade. This is an aggressive approach since it doesn't wait for further price confirmation. In the image, this is represented by the 'Fractal 2' label where the script identifies and acts on the swing low pattern.
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What type of stop-loss identification method are used in this strategy?
This strategy employs two types of stop-loss methods: Initial Stop-loss and Trailing Stop-Loss.
Underlying Calculations:
Initial Stop-loss:
ATR Based: The strategy uses the Average True Range (ATR) to set an initial stop-loss, which helps in accounting for market volatility without predicting price direction.
Calculation:
- First, the True Range (TR) is calculated for each period, which is the greatest of:
- Current Period High - Current Period Low
- Absolute Value of Current Period High - Previous Period Close
- Absolute Value of Current Period Low - Previous Period Close
- The ATR is then the moving average of these TR values over a specified period, typically 14 periods by default. This ATR value can be used to set the stop-loss at a distance from the entry price that reflects the current market volatility.
Swing Low Based:
For this method, the stop-loss is set based on the most recent swing low identified in the market structure analysis. This approach uses the lowest point of the recent price action as a reference for setting the stop-loss.
Trailing Stop-Loss:
The strategy uses structural liquidity and structural invalidation levels across multiple timeframes to adjust the stop-loss once the trade is profitable. This method involves:
Detecting Structural Liquidity: After a break of structure, the liquidity levels are updated to the first swing high in a bullish scenario or the first swing low in a bearish scenario. These levels serve as potential areas where the price might find support or resistance, allowing the stop-loss to trail the price movement.
Detecting Structural Invalidation: If the price returns to the level of the first swing low before a bullish break of structure or the first swing high before a bearish break of structure, it suggests the trend might be reversing or invalidating, prompting the adjustment of the stop-loss to lock in profits or minimize losses.
By using these methods, the strategy dynamically adjusts the initial stop-loss based on market volatility, helping to protect against adverse price movements while allowing for enough room for trades to develop. The ATR-based stop-loss adapts to the current market conditions by considering the volatility, ensuring that the stop-loss is not too tight during volatile periods, which could lead to premature exits, nor too loose during calm markets, which might result in larger losses. Similarly, the swing low based stop-loss provides a logical exit point if the market structure changes unfavorably.
Each market behaves differently across various timeframes, and it is essential to test different parameters and optimizations to find out which trailing stop-loss method gives you the desired results and performance. This involves backtesting the strategy with different settings for the ATR period, the distance from the swing low, and how the trailing stop-loss reacts to structural liquidity and invalidation levels.
Through this process, you can tailor the strategy to perform optimally in different market environments, ensuring that the stop-loss mechanism supports the trade's longevity while safeguarding against significant drawdowns.
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What type of break-even method is used in this strategy? What are the underlying calculations?
Moves the initial stop-loss to the entry price when the price reaches a certain RR ratio.
Calculation:
Break-even level = Entry Price + (Initial Risk * RR Ratio)
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What tables are available in this script?
- Summary: Provides a general overview, displaying key performance parameters such as Net Profit, Profit Factor, Max Drawdown, Average Trade, Closed Trades and more.
Total Commission: Displays the cumulative commissions incurred from all trades executed within the selected backtesting window. This value is derived by summing the commission fees for each trade on your chart.
Average Commission: Represents the average commission per trade, calculated by dividing the Total Commission by the total number of closed trades. This metric is crucial for assessing the impact of trading costs on overall profitability.
Avg Trade: The sum of money gained or lost by the average trade generated by a strategy. Calculated by dividing the Net Profit by the overall number of closed trades. An important value since it must be large enough to cover the commission and slippage costs of trading the strategy and still bring a profit.
MaxDD: Displays the largest drawdown of losses, i.e., the maximum possible loss that the strategy could have incurred among all of the trades it has made. This value is calculated separately for every bar that the strategy spends with an open position.
Profit Factor: The amount of money a trading strategy made for every unit of money it lost (in the selected currency). This value is calculated by dividing gross profits by gross losses.
Avg RR: This is calculated by dividing the average winning trade by the average losing trade. This field is not a very meaningful value by itself because it does not take into account the ratio of the number of winning vs losing trades, and strategies can have different approaches to profitability. A strategy may trade at every possibility in order to capture many small profits, yet have an average losing trade greater than the average winning trade. The higher this value is, the better, but it should be considered together with the percentage of winning trades and the net profit.
Winrate: The percentage of winning trades generated by a strategy. Calculated by dividing the number of winning trades by the total number of closed trades generated by a strategy. Percent profitable is not a very reliable measure by itself. A strategy could have many small winning trades, making the percent profitable high with a small average winning trade, or a few big winning trades accounting for a low percent profitable and a big average winning trade. Most mean-reversion successful strategies have a percent profitability of 40-80% but are profitable due to risk management control.
BE Trades: Number of break-even trades, excluding commission/slippage.
Losing Trades: The total number of losing trades generated by the strategy.
Winning Trades: The total number of winning trades generated by the strategy.
Total Trades: Total number of taken traders visible your charts.
Net Profit: The overall profit or loss (in the selected currency) achieved by the trading strategy in the test period. The value is the sum of all values from the Profit column (on the List of Trades tab), taking into account the sign.
- Monthly: Displays performance data on a month-by-month basis, allowing users to analyze performance trends over each month and year.
- Weekly: Displays performance data on a week-by-week basis, helping users to understand weekly performance variations.
- UI Table: A user-friendly table that allows users to view and save the selected strategy parameters from user inputs. This table enables easy access to key settings and configurations, providing a straightforward solution for saving strategy parameters by simply taking a screenshot with Alt + S or ⌥ + S.
User-input styles and customizations:
Please note that all background colors in the style are disabled by default to enhance visualization.
How to Use This Strategy to Create a Profitable Edge and Systems?
Choose Your Strategy mode:
- Decide whether you are creating an investing strategy or a trading strategy.
Select a Market:
- Choose a one-sided market such as stocks, indices, or cryptocurrencies.
Historical Data:
- Ensure the historical data covers at least 10 years of price action for robust backtesting.
Timeframe Selection:
- Choose the timeframe you are comfortable trading with. It is strongly recommended to use a timeframe above 15 minutes to minimize the impact of commissions/slippage on your profits.
Set Commission and Slippage:
- Properly set the commission and slippage in the strategy properties according to your broker/prop firm specifications.
Parameter Optimization:
- Use trial and error to test different parameters until you find the performance results you are looking for in the summary table or, preferably, through deep backtesting using the strategy tester.
Trade Count:
- Ensure the number of trades is 200 or more; the higher, the better for statistical significance.
Positive Average Trade:
- Make sure the average trade is above zero.
(An important value since it must be large enough to cover the commission and slippage costs of trading the strategy and still bring a profit.)
Performance Metrics:
- Look for a high profit factor, and net profit with minimum drawdown.
- Ideally, aim for a drawdown under 20-30%, depending on your risk tolerance.
Refinement and Optimization:
- Try out different markets and timeframes.
- Continue working on refining your edge using the available filters and components to further optimize your strategy.
What Makes This Strategy Unique?
This strategy combines flexibility, smart risk management, and momentum focus in a way that’s rare and practical:
1. Adapts to Any Market Rhythm
Works on daily, weekly, or intraday charts without code changes.
Uses two entry types: classic breakouts (like trending stocks) or fractal patterns (to avoid false starts).
2. Smarter Stop-Loss System
No rigid rules: Stops adjust based on price structure (e.g., new “higher lows”), not fixed percentages.
Avoids whipsaws: Tightens stops only when the trend strengthens, not in choppy markets.
3. Safe Profit-Boosting Pyramiding
Adds new positions only after prior trades are risk-free (stops moved above breakeven).
Scales up using locked-in profits, not new capital, to grow gains safely.
4. Built-In Momentum Check
Tracks 1/3/6-month price growth to spotlight stocks with strong, lasting momentum.
Terms and Conditions | Disclaimer
Our charting tools are provided for informational and educational purposes only and should not be construed as financial, investment, or trading advice. They are not intended to forecast market movements or offer specific recommendations. Users should understand that past performance does not guarantee future results and should not base financial decisions solely on historical data.
Built-in components, features, and functionalities of our charting tools are the intellectual property of @Fractalyst Unauthorized use, reproduction, or distribution of these proprietary elements is prohibited.
- By continuing to use our charting tools, the user acknowledges and accepts the Terms and Conditions outlined in this legal disclaimer and agrees to respect our intellectual property rights and comply with all applicable laws and regulations.
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.
-----
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.
-----
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.
-----
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.
-----
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.
Classic Nacked Z-Score ArbitrageThe “Classic Naked Z-Score Arbitrage” strategy employs a statistical arbitrage model based on the Z-score of the price spread between two assets. This strategy follows the premise of pair trading, where two correlated assets, typically from the same market sector, are traded against each other to profit from relative price movements (Gatev, Goetzmann, & Rouwenhorst, 2006). The approach involves calculating the Z-score of the price spread between two assets to determine market inefficiencies and capitalize on short-term mispricing.
Methodology
Price Spread Calculation:
The strategy calculates the spread between the two selected assets (Asset A and Asset B), typically from different sectors or asset classes, on a daily timeframe.
Statistical Basis – Z-Score:
The Z-score is used as a measure of how far the current price spread deviates from its historical mean, using the standard deviation for normalization.
Trading Logic:
• Long Position:
A long position is initiated when the Z-score exceeds the predefined threshold (e.g., 2.0), indicating that Asset A is undervalued relative to Asset B. This signals an arbitrage opportunity where the trader buys Asset B and sells Asset A.
• Short Position:
A short position is entered when the Z-score falls below the negative threshold, indicating that Asset A is overvalued relative to Asset B. The strategy involves selling Asset B and buying Asset A.
Theoretical Foundation
This strategy is rooted in mean reversion theory, which posits that asset prices tend to return to their long-term average after temporary deviations. This form of arbitrage is widely used in statistical arbitrage and pair trading techniques, where investors seek to exploit short-term price inefficiencies between two assets that historically maintain a stable price relationship (Avery & Sibley, 2020).
Further, the Z-score is an effective tool for identifying significant deviations from the mean, which can be seen as a signal for the potential reversion of the price spread (Braucher, 2015). By capturing these inefficiencies, traders aim to profit from convergence or divergence between correlated assets.
Practical Application
The strategy aligns with the Financial Algorithmic Trading and Market Liquidity analysis, emphasizing the importance of statistical models and efficient execution (Harris, 2024). By utilizing a simple yet effective risk-reward mechanism based on the Z-score, the strategy contributes to the growing body of research on market liquidity, asset correlation, and algorithmic trading.
The integration of transaction costs and slippage ensures that the strategy accounts for practical trading limitations, helping to refine execution in real market conditions. These factors are vital in modern quantitative finance, where liquidity and execution risk can erode profits (Harris, 2024).
References
• Gatev, E., Goetzmann, W. N., & Rouwenhorst, K. G. (2006). Pairs Trading: Performance of a Relative-Value Arbitrage Rule. The Review of Financial Studies, 19(3), 1317-1343.
• Avery, C., & Sibley, D. (2020). Statistical Arbitrage: The Evolution and Practices of Quantitative Trading. Journal of Quantitative Finance, 18(5), 501-523.
• Braucher, J. (2015). Understanding the Z-Score in Trading. Journal of Financial Markets, 12(4), 225-239.
• Harris, L. (2024). Financial Algorithmic Trading and Market Liquidity: A Comprehensive Analysis. Journal of Financial Engineering, 7(1), 18-34.
Easy Trade Pro [Buy and Sell Strategy + Backtesting System]Hello Traders,
Easy Trade Pro is a comprehensive tool that combines multiple technical indicators into a single customizable one. This tool is the culmination of an extensive trading career, it is designed to help traders navigate the markets in any timeframe and financial asset, like Equities, Futures, Crypto, Forex and Commodities.
Before we deep dive into the comprehensive guide on what Easy Trade Pro is, let's kick off by showcasing the strategy used in this example. Please note, we have adopted an extremely conservative approach strictly following the Tradingview House Rules, which you can review here: www.tradingview.com
The backtest strategy parameters:
Currency pair: EUR USD
Timeframe: 15-min chart
Market: Spot, no leverage
Broker: FXCM
Trading range: 2022-09-01 07:30 — 2023-06-26 20:00
Backtesting range: 2022-08-31 23:00 — 2023-06-26 20:00
Initial Capital: $10,000
Buy Order Size: 20% of the capital, $2,000
Stop Loss: 0.50%
Sell orders: Four different take profits where we unload the position by 25% each time
Broker Fees: Commission set at 0.08$
Slippage: 10 ticks
Understanding FXCM Commissions and Setting Realistic Slippage for EUR/USD Spot Trading:
◉I would like to provide some clarity on the commission structure and slippage setting used in the study for trading the EUR/USD pair on the FXCM spot market. Based on the information available, FXCM charges a commission of $4.00 per standard lot (100,000) on both sides of the trade (meaning at open and close) for the EUR/USD pair. Since the study involve an order size of $2,000 USD, which is equivalent to 0.02 lots, the commission fee for one side of the trade (either buying or selling) would be calculated as $4.00 multiplied by 0.02, which is $0.08. This means that for each individual trade, whether it be a buy or sell, the commission fee would be $0.08.
◉As for slippage, it is crucial to account for the inherent uncertainty in the execution price due to market fluctuations. In the forex market, the EUR/USD pair is quoted with a precision of five decimal places, with the smallest price change being a "pipette" (0.00001). Given that slippage can vary based on market conditions, it is considered fair practice to use a slippage of around 10 ticks under normal market conditions for the EUR/USD pair. This allows for a more realistic representation of the execution price, especially in a liquid and fast-moving market such as forex.
More detailed information about FXCM fees structure in the link below:
docs.fxcorporate.com
Enter a Trade conditions:
For our buy order, we utilize a custom buy signal called 'Bullish Reversal'. A detailed explanation of this and other buy orders can be found later in the guide, specifically in section 1).
To enhance realism in our trading strategy, we have implemented a confirmation mechanism. When utilizing the strategy tester, you have the option to input a value to determine the number of confirmation candles to consider.
For example, if you set the input to 1, the system will check if the next candle following the signal meets the criteria for confirmation. If set to 2, the system will evaluate the second candle, and so on for higher values. The confirmation is determined by comparing the closing or opening price of the selected buy signal candle with the corresponding closing price of the confirmation candle.
In this case we choose as buy signal: 'Bullish Reversal' + 2 candle of confirmation
Exit a trade conditions:
On the sell side, we exit a trade in four different types of sell orders where we take profits. Inside '', you will encounter unique labels attributed to our custom sell signals. A detailed explanation of these sell orders can be found later in the guide, specifically in section 1). We used custom order called:
1TP 'Good Sell'
2TP 'Good Sell'
3TP 'Good Sell'
4TP 'Bearish Reversal' + 4 confirmation candles
Our confirmation logic, for sell signals, is applied only to 'Bearish Reversal' signal. The confirmation is determined by comparing the closing or opening price of the selected 'Bearish Reversal' candle with the corresponding closing price of the confirmation candle. In this case, we wait for the fourth candle from the 'Bearish Reversal' signal to confirm the sell trade.
Protect your capital:
This super-conservative study involves a clear low risk, with the use of $2,000, 20% of our capital. If the stop loss of 0.5% were triggered, we lose 10$, equating to 0.10% of $10,000 - thus affecting only 0.10% of our capital.
Super Conservative Approach & Results:
With 353 closed trades, we achieved a net profit of 2.03%, or $203.34$ relative to our initial $10,000 capital, and a win rate of 73.37%.
Less Conservative Approach & Results:
We could also consider increasing our risk to 0.5% of our capital per trade. We would maintain our stop loss at 0.50%, but we would need to use all our capital to enter the market. If the stop loss of 0.5% will be triggered, we would lose 50$, equating to 0.5% of $10,000.
In this scenario, our net profit would have increased to 10.15%, equivalent to $1015.
Please be aware:
While fully automated strategies can bring considerable advantages, they are not without their cons. For one, relying solely on an automated system may not take into account the potential confluence of other strategies or indicators, such as the significance of support and resistance zones. These elements often require a more nuanced, human understanding of the markets and cannot always be perfectly replicated by an algorithm.
Additionally, it's essential to remember that a significant percentage of traders are not consistently profitable. As such, prudent risk management, a conservative approach, and acceptance of a reasonable profit are crucial aspects of successful trading. While the allure of high returns can be tempting, the sustainability of your trading strategy should always take precedence. Achieving steady, reliable profits over time often outweighs the appeal of a risky, high-return strategy that could potentially lead to substantial losses.
So, while automation can be a powerful tool in your trading arsenal, it's also important to consider other strategies and factors. Always ensure you're managing your risk effectively and approaching trading with a realistic and informed perspective.
------------------------------------------------------------------------ Why Easy Trade Pro is Original? ----------------------------------------------------------------------------------
We developed Easy Trade Pro as a unique and comprehensive solution, and we decided to protect our code to preserve its originality. We invested significant time and effort into making it a realistic trading strategy simulator. The standout features that set Easy Trade Pro apart include:
☀ Versatile Stop Loss Mechanisms: Stop loss execution can be complex and often requires careful coding to work as intended. In most freely available open-source codes, stop losses are implemented using the Average True Range (ATR). ATR can be beneficial but has limitations:
☁ Lagging Indicator - Like most technical indicators, the ATR is a lagging indicator. This means it is based on past data, and so it may not accurately reflect future market volatility. If market conditions change rapidly, the ATR may not adjust quickly enough, potentially leading to suboptimal stop loss levels.
☁ No Directional Information - The ATR measures volatility, but it does not provide any indication of the direction of the trend. Therefore, it should not be used as a standalone tool for making trading decisions, but should be used in conjunction with other technical analysis tools that can provide directional cues.
☁ Inefficiency in Trending Markets - In strongly trending markets, ATR-based stops can sometimes be too far from the current price level. This could lead to larger losses if the price moves against your trade before hitting the stop loss. On the flip side, in less volatile, sideways markets, an ATR-based stop might be set too close to the entry point, leading to premature stop outs.
☁ Overoptimization Risk - If you're backtesting a trading strategy, there's a risk of overoptimizing your stop loss settings by fine-tuning them to past data. The best ATR multiplier that worked in the past might not necessarily work in the future, leading to potential performance issues.
☀ We countered these by implementing four different types of 'protect the trade' mechanisms:
✔ Fixed Percentage Stop Loss
✔ Trailing Stop Loss
✔ Stop Loss Moved to Entry Upon Reaching Certain Gain
✔ Stop Loss Moved to Entry Upon Reaching First Take Profit Order ("Custom Order").
☀ Dual Exit Strategy: We incorporated two distinct methods of exiting a trade. The first uses our custom signals, while the second triggers exit at a certain percentage of gain.
☀ Multiple Take Profit Orders: You have the flexibility to establish up to four different sell orders. This feature enables you to fractionate your exit strategy according to your needs. You can choose to trigger these fractions based on our custom signals or determine your own exit points by setting targeted gains at a fixed percentage.
☀ Confirmation Candle System: This feature enhances trade precision by requiring confirmation candles after a buy or sell signal. This confirmation, dependent on the next candle's closing price, helps reduce false signals and improves entry and exit points. While our confirmation system is applicable to all custom buy signals, it's solely dedicated for the bearish reversal when it comes to sell signals.
☀ Universal Compatibility: Easy Trade Pro's Strategy Tester works perfectly with any asset class. The code can handle different contract types, including the SPX contracts and fractional assets like Bitcoin. It's optimized to ensure proper execution of trades without rounding issues.
☀ Bullish and Bearish Reversal candles: Our method of detecting these pivotal candles combines conditions from buy and sell signals with pertinent divergences in Price, RSI, and Volume (OBV). The distinguishing factor, however, lies in recognizing significant shifts in market structure and liquidity grabs. To further enhance the credibility of our indicator, we've incorporated Bollinger Bands, serving as an additional layer in spotting potential trend reversals, particularly when aligned with long-wick candlesticks, engulfing patterns, and morning or evening star formations.
☀ Non-Repainting Indicator: Our indicator signals are designed not to repaint. Once a signal appears, it stays fixed, offering a reliable tool for your trading decisions.
================================================== EXTENSIVE TECHNICAL DESCRIPTION ====================================================
Easy Trade Pro is versatile, allowing you to analyze market trends across any financial asset. With its rigorous testing, our tool can be used confidently on any timeframe, from 1D to 1min, whether you prefer longer-term or shorter-term trades.
Although we recommend trading on timeframes between 1D and 1min, higher timeframes like 1W chart, can also provide broader insights.
Our study combines a variety of popular technical indicators, such as RSI, Stochastic RSI, MACD, DMI, Bollinger Bands as well as relevant EMAs. On the volume side OBV and MFI. Using a data-driven approach, “Easy Trade Pro” analyzes historical market trends to identify optimal ways to combine these indicators with significant divergences between price and oscillators. On top of that the code considers relevant changes in market structure and liquidity grabs, to generate reliable and accurate signals for potential buy and sell opportunities.
* ☎ --> Please not that MACD, BBs, and EMAs account for a minimal part of our script <--- ☎, If you're looking for a simpler tool, consider checking out our open-source indicator, 'RSI, SRSI, MACD, and DMI cross - Open source code'. You can find it here:
With our customizable system, traders will be able to identify:
1) Three types of buy signals🐂,💰,💎 and sell signals 🐻,🔨,💀
2) Bullish and bearish reversal candles with support and resistance lines
3) Bull and bear momentum signals
4) A function that utilizes Color bars to identify the strength of the trend
5) Three customizable moving averages
6) Alerts direct to your email or phone
7) Advanced and customizable settings menu
8) Our software also includes a backtesting system that that allows users to test their trading strategies on historical data, to check how they would have performed in real-world market conditions. This can help refine a trading strategy and make more informed decisions.
------------------------------------------------------------------------------ 1) BUY AND SELL SIGNALS ---------------------------------------------------------------------------------
Our buy and sell signals are generated using a custom combination of RSI, MFI, and Stochastic RSI levels, as well as relevant MACD and Stochastic RSI crosses. These indicators are carefully analyzed to identify potential trading opportunities and determine optimal entry and exit points for trades.
RSI (Relative strength index) measures the strength of a security's price action, while the SRSI (Stochastic Relative Strength Index) is a momentum oscillator that measures the current price relative to its high and low range over a set period. The Money Flow Index (MFI) is another momentum indicator that uses both price and volume data to measure buying and selling pressure. MACD (Moving Average Convergence Divergence) is a popular technical indicator used in financial markets to analyze price trends and momentum.
▶ With our system, you'll be able to identify three different levels of buy signals:
◉ The first level of buy signal is represented by a 🐂 emoji and is a "Good Buy". This signal indicates a possible buying opportunity. It indicates that could be a good opportunity to enter in a long trade. It's important to note that, the "Good Buy" signal can sometimes be supplemented with a green "Bull" text and a flag plotshape positioned beneath the signal. In these scenarios, we categorize this as a "Good Buy Bull" signal.
◉ The second level of buy signal is represented by a 💰 emoji and is a "Great Buy". This signal indicates a stronger buying opportunity than the "Good Buy" signal.
◉ The third and strongest buy signal is represented by a 💎 emoji and is an "Incredible Buy". This signal indicates a stronger buying opportunity than the "Good Buy" and "Great Buy" signals
▶ With our system, you'll be able to identify three different levels of sell signals:
◉ On the sell side, the first level is represented by a 🐻 emoji and is a "Good Sell". This signal indicates a possible selling opportunity. It indicates that could be a good opportunity to exit a trade or open a short position. It's important to note that, the "Good Sell" signal can occasionally be accompanied by a red "Bear" text and a flag plotshape positioned beneath the signal. In such instances, we refer to this as a "Good Sell Bear" signal.
◉ The second sell signal is represented by a 🔨 emoji and is a "Great Sell". This signal indicates a stronger selling opportunity than the "Good Sell" signal.
◉ The third and strongest sell signal is represented by a 💀 emoji and is an "Incredible Sell". This signal indicates a stronger selling opportunity than the "Good Sell" and "Great Sell" signals.
------------------------------------------2) "BULLISH AND BEARISH REVERSAL CANDLES PLUS SUPPORT AND RESISTANCE LINES" ------------------------------------------------
Bullish and bearish reversal candles are specific candles that have more probability to reverse the trend.
Our trading indicator is designed to identify bullish and bearish reversal candles. Our method of detecting these pivotal candles combines conditions from buy and sell signals with pertinent divergences in Price, RSI, and Volume (OBV). The distinguishing factor, however, lies in recognizing significant shifts in market structure and liquidity grabs. To further enhance the credibility of our indicator, we've incorporated Bollinger Bands, serving as an additional layer in spotting potential trend reversals, particularly when aligned with long-wick candlesticks, engulfing patterns, and morning or evening star formations.
These candles are represented by blue and orange colors respectively by default. Additionally, the indicator also uses lines that are drawn at either the opening or closing of candles to help identify pivot points of support or resistance. These candles, lines color or shape are customizable in the settings menu.
How can I benefit the most from bullish reversal candles? To make the most of bullish reversal candles, a powerful strategy is:
E.g, 1D chart - Wait for the next 1 or 2 candles to close above the support line linked to the bullish reversal candle. For lower timeframes, it is recommended to wait for 2 or 3 candles before making a trading decision. A good tip is also to look for other signals (confluence), like a buy signal. Traders should decide based on their risk tolerance.
Here below we can see an example of a bullish reversal candle in the BTC/USDT, 1D, chart. The system identify a bullish reversal candle (blue color), the next 2 candles are green and closed above the support blue line, in addition we have other bullish signals (confluence).
How can I benefit the most from bullish reversal lines? Bullish reversal lines can help traders to identify key level of support and maintain control of their position until a clear break below occurs.
In the example below we se how the price retrace to the support line:
After touching the price bounce up.
How can I benefit the most from bearish reversal candles? To make the most of bearish reversal candles, a powerful strategy is:
E.g, 1D chart - Wait for the next 1 or 2 candles to close below the resistance line linked to the bearish reversal candle. For lower timeframes, it is recommended to wait for 2 or 3 candles before making a trading decision. Traders should decide based on their risk tolerance.
Here below we can see an example of a bearish reversal candle in the ETH/USDT, 1D, chart. The system identify a bearish reversal candle (orange color), the next candle is red and closes below the resistance orange line. A good tip is also to look for other signals (confluence), like a sell signal.
How can I benefit the most from bearish reversal lines? Bearish reversal lines can help traders to identify key level of resistance and maintain control of their position until a clear break above occurs.
In the example below we se how the price bounce back to the resistance line and get rejected.
------------------------------------------------------------------------- 3) BULL AND BEAR MOMENTUM SIGNALS -----------------------------------------------------------------------
We analyzed factors such as buy or sell signals, long or short confirmation signals, DMI crossup or crossdown and breaks of market structure (BOS) or change of character (CHoCh) to determine the strength and direction of the trend. These study give us bull trend or bear trend signals that can help traders identify potential trading opportunities and make informed decisions.
These conditions are represented by a green word "BULL" and a flag shape below (bull momentum) and by a red word "BEAR" and a flag shape above (bear momentum) respectively by default. These plots shapes are customizable in the settings menu.
How can I benefit the most from bull momentum signals? To make the most of bull momentum signals, a powerful strategy is:
E.g, 1D chart - Look for confluence. If bull signal comes with a "Good Buy 🐂" in the same candle the signal is more strong. Another good combo is to look for a bullish reversal candle prior or after this signal, usually within a range of 1/2 candles. For lower timeframes, it is recommended to wait 2/3 candles before making a trading decision.
In the picture below we can see an example of a bull momentum signal in the US500, 1D, chart.
How can I benefit the most from bear momentum signals? To make the most of bear momentum signals, a powerful strategy is:
E.g, 1D chart - Look for confluence. If bear signal comes with a "Good Sell 🐻" in the same candle the signal is more strong. Another good combo is to look for a bearish reversal candle prior or after this signal, usually within a range of 1/2 candles. For lower timeframes, it is recommended to wait 2/3 candles before making a trading decision.
In the picture below we can see an example of a bear momentum signal in combo with a sell signal, NETFLIX, 1D, chart.
-------------------------------------------------------------- 4) "COLOR BARS THAT INDICATE THE STRENGTH OF THE TREND -----------------------------------------------------
This code is responsible for changing the color of the bars on a chart based on certain conditions. The gradient colors are defined for green and red, and the algorithm checks if the current bar is within a certain range of either a bearish reversal or bullish reversal candle and whether the price is above or below certain exponential moving averages or if important break of market structure occurs.
Ultimately, this feature helps traders visually identify potential trends and market shifts and avoid getting distracted by price fluctuations. Please note that every gradient of color can be customize by the user. We set 3 different bullish colors and 3 different bearish colors.
Below the picture of the settings menu related to the bar color.
----------------------------------------------------------------------5)THREE CUSTOMIZABLE MOVING AVERAGES ----------------------------------------------------------------------
You can choose up to three moving averages, any length and any type like SMA, EMA, WMA, HMA, RMA, SWMA and VWMA. Furthermore, you have the freedom to adjust the color and width of the lines to your preference.
Below the picture of the settings menu related to the moving averages.
----------------------------------------------------------------------6) ALERTS DIRECT TO YOUR EMAIL OR PHONE --------------------------------------------------------------------
Our alert feature sends real-time notifications directly to your email or phone when a signal is generated, allowing you to take immediate action and stay ahead of the market.
With our system, you first establish your own rules for trading in the strategy tester - this includes your criteria for entering and exiting trades.
Once you've defined these conditions, our system will start sending you alerts. These alerts will be triggered whenever your specified conditions are met. So, if the market matches your 'enter trade' conditions, you'll receive an alert prompting. Similarly, when your 'exit trade' conditions are met, you'll receive another alert.
Remember, these alerts are purely based on the conditions you set.
Once the condition is met, you will receive alerts directly to your email or phone when enter and exit a trade based on your custom conditions. To make sure you receive these notifications click on notifications tab.
---------------------------------------------------------------7) ADVANCED AND CUSTOMIZABLE SETTINGS MENU----------------------------------------------------------------------
We designed Easy Trade indicators with traders in mind, so it's user-friendly, easy to navigate and users can customize inputs, style, and colors of every feature in the indicator's settings menu.
-----------------------------------------------------------------------8) EASY TRADE PRO - BACKTESTING SYSTEM----------------------------------------------------------------------
Easy Trade Pro features a highly effective and realistic backtesting system, designed to mirror as closely as possible the real-world scenarios of entering and exiting trades.
Step 1:
Open the settings menu of the Indicator.
Once opened the settings menu click on properties.
Decide on the capital you wish to invest. Choose whether to use contracts or USD and determine the size of your orders. For the sake of realism, we recommend not exceeding 25% of your capital per order. However, if you decide to utilize your entire capital, make sure to adjust your stop loss accordingly. For instance, if you have a capital of 10K and use 10K with a stop loss at 2%, your potential loss would be $200. Conversely, if you use only 2K of your 10K capital with a stop loss at 10%, you would still lose the same 2% of your capital. To make your simulation even more authentic, consider incorporating broker fees or commissions into your calculations. For example, spot market fees are typically around 0.10%. If you're backtesting markets with low liquidity, consider factoring in slippage as well.
Step 2:
Navigate to the 'Inputs' section and scroll down until you come across 'Backtesting System - Strategy Test'. Once you locate this, click on the box and activate the 'USE STRATEGY SYSTEM' option by checking the tick box.
Also You will then need to set a 'Start Date' and 'End Date', establishing a specific time period during which you wish to test your strategy.
Otherwise you can consider to use the deep backtesting feature.
Step 3:
It's now time to establish the conditions for entering a trade. You can choose from five different types of custom buy signals: Good Buy, Good Buy Bull, Great Buy, Incredible Buy, and Bullish Reversal. Note that 'Great Buy' and 'Incredible Buy' are rare signals, so we advise against using them frequently in mechanical strategy tests; instead, consider them more for manual live tests. For more consistent results, we recommend using the other buy signals.
After determining your preferred buy signal, you can choose how many confirmation candles you wish to wait for before entering a trade. A 'confirmation' means that if the next candle closes above the opening or closing price of the chosen buy signal, it's considered a confirmation. This could be the opening or closing price, depending on whether the candle is green (close > open) or red.
You can set the number of confirmation candles in different time frames: below 2h, between 2h and 10h, and above 10h.
Step 4:
It's now time to safeguard your trade by managing risk. You can choose to implement a stop loss, expressed in percentage terms, or opt for a trailing stop. A trailing stop is a type of stop loss order that moves with the market price. It is designed to protect gains by enabling a trade to remain open and continue to profit as long as the market price is moving in a favorable direction. However, the trade closes if the market price changes direction by a specified amount (the 'trailing stop distance').
Additionally, you can minimize losses and move the stop loss to your entry point once the price reaches a certain percentage of profit. This strategy can help secure potential gains while limiting the potential for losses.
Step 5:
Now it's time to set the conditions for exiting the trade. You have the option to divide your exit into a maximum of four parts, with each part representing 25% of the position size. For each take profit point, you can choose from three different custom sell signals: Good Sell, Good Sell Bear, and Bearish Reversal.
Similarly, the concept of confirmation candles also applies here, but in this case, the candles are not closing above. A 'confirmation' for a sell signal means that if the next candle closes below the opening or closing price of the selected sell signal, it's considered a confirmation. This could be the opening or closing price, depending on whether the candle is green (open > close) or red (close < open).
So, when you're looking to sell, a confirmation would occur if the next candlestick's closing price is lower than the opening or closing price of the candlestick that triggered the sell signal. This indicates a potential bearish trend, providing the confirmation to execute the sell order.
Additionally, we've introduced a feature that allows you to move your stop loss to the entry point whenever the first take profit (1TP) is reached, which equates to hitting one custom sell signal.
Step 6:
We've also designed an alternative method for taking profits. With this approach, you can choose to exit your position once a fixed percentage gain from the entry point is reached. For instance, you might decide to exit when a 10% profit is achieved. Similarly to the previous method, this approach allows you to choose up to four exit points and determine the proportion of your position you want to close at each stage.
Conclusion:
Easy Trade Pro provides users with various options for entering and exiting trades. To effectively utilize the indicator, we strongly recommend conducting thorough backtesting and considering the results across your preferred trading pairs. It is advisable to analyze a substantial number of trades, ideally exceeding 100 trades, to obtain reliable insights into the indicator's performance. This approach will help you gain a better understanding of how Easy Trade Pro aligns with your trading strategy and objectives.
❗Keep attention❗
It is important to note that no trading indicator or strategy is foolproof, and there is always a risk of losses in trading. While this indicator may provide useful information for making conclusions, it should not be used as the sole basis for making trading decisions. Traders should always use proper risk management techniques and consider multiple factors when making trading decisions.
It is also important to be aware of the limitations of simulated performance results. Hypothetical or simulated results do not represent actual trading, and since trades have not been executed, results may be over- or under-compensated for market factors such as lack of liquidity. Simulated trading programs are also designed with the benefit of hindsight, and no representation is being made that any account will achieve profits or losses similar to those shown. Therefore, our indicators are for informative purposes only and not intended to be used as financial advice.
We encourage traders to use our indicators as part of a well-rounded trading strategy and to always be aware of the risks involved in trading. Remember that past performance is not indicative of future results and always trade responsibly.
Fair Value Strategy - ekmllThis is a strategy using SPX's Fair Value derived from Net Liquidity.
The main difference between this one and calebsandfort's one is net liquidity values in this one are calculated in TradingView and doesn't need author's daily library updates to function.
Net Liquidity function is simply: Fed Balance Sheet - Treasury General Account - Reverse Repo Balance
Formula for calculating the fair value of and Index using Net Liquidity looks like this: (WALCL - WTREGEN - RRPONTSYD)/1000000000/scalar - subtractor
The Index Fair Value is then subtracted from the Index value which creates an oscillating diff value.
When diff is greater than the overbought threshold, Index is considered overbought and we go short/sell.
When diff is less than the oversold signal, Index is considered oversold and we cover/buy.
Parameters:
Index: SPX, NDX, RUT
Strategy: Short Only, Long Only, Long/Short
Inverse (bool): check if using an inverse ETF to go long instead of short.
Scalar (float)
Subtractor (int)
Overbought Threshold (int)
Oversold Threshold (int)
Start After Date: When the strategy should start trading
Close Date: Day to close open trades. I just like it to get complete results rather than the strategy ending with open trades.
I've optimized the parameters for SPX.
Fair Value Strategy UltimateThis is a strategy using an index's (SPX, NDX, RUT) Fair Value derived from Net Liquidity.
Net Liquidity function is simply: Fed Balance Sheet - Treasury General Account - Reverse Repo Balance
Formula for calculating the fair value of and Index using Net Liquidity looks like this: net_liquidity/1000000000/scalar - subtractor
The Index Fair Value is then subtracted from the Index value which creates an oscillating diff value.
When diff is greater than the overbought threshold, Index is considered overbought and we go short/sell.
When diff is less than the oversold signal, Index is considered oversold and we cover/buy.
The net liquidity values I calculate outside of TradingView. If you'd like the strategy to work for future dates, you'll need to update the reference to my NetLiquidityLibrary , which I update daily.
Parameters:
Index: SPX, NDX, RUT
Strategy: Short Only, Long Only, Long/Short
Inverse (bool): check if using an inverse ETF to go long instead of short.
Scalar (float)
Subtractor (int)
Overbought Threshold (int)
Oversold Threshold (int)
Start After Date: When the strategy should start trading
Close Date: Day to close open trades. I just like it to get complete results rather than the strategy ending with open trades.
Optimal Parameters:
I've optimized the parameters for each index using the python backtesting library and they are as follows =>
SPX
Scalar: 1.1
Subtractor: 1425
OB Threshold: 0
OS Threshold: -175
NDX
Scalar: 0.5
Subtractor: 250
OB Threshold: 0
OS Threshold: -25
RUT
Scalar: 3.2
Subtractor: 50
OB Threshold: 25
OS Threshold: -25
3Commas Bot DCA Backtester & Signals FREEThis is a DCA Strategy backtester + signals, built to emulate the 3Commas DCA bots. It uses your choice of 4 different buy signals, 2 of which can be adjusted in the settings. Everything is customizable so you can backtest specific settings with different buy signals and find the best performing strategy for your risk tolerance and capital. It can be used to backtest strategies on stocks as well, but just make sure your base order is larger than the share price for the entire backtesting range or it will not calculate properly.
You can use this template to code your own buy signals and then backtest them as a DCA strategy if you know some basic pine script.
The indicator shows all of your backtesting orders on the chart. The red line is your take profit level, the blue line is your average price level, the white line is your first order and the green lines are your average down orders. If you enable a stop loss in the settings your stop loss will be shown as an orange line once all of your average down orders have been hit, it will not be set until price has dipped below your covered trading range.
These levels update when things change during backtesting so you can visualize your strategy and how it would perform as well as see if your percentage deviation is large enough to cover dips. When backtesting trades are taken, the chart will show where they were taken(in backtesting) along with info on those trades such as the number each order is, the size of that order and the percentage deviation that order is from the initial buy.
SENDING SIGNALS TO 3COMMAS
Tradingview cannot sync this backtester to 3Commas and with the way alerts are setup for strategies on Tradingview, the best option for you to give signals to your bot would be to use this backtester to figure out what trigger you want to use and then setup that indicator separately to send alerts to your bot. All of the indicators used for signals in this backtester are available for free and can be configured to match this backtester and send alerts to 3Commas for you. Just make sure you set your alerts to once per bar close and don’t use less than a 15 second timeframe because then you could trigger the Tradingview threshold for alerts and get your alerts shut off.
You can also use this backtester with your own buy triggers if you know a little pine script. Just make copy of the script and code in your own buy signals and see how it backtests.
INFO PANEL FOR ANALYZING YOUR STRATEGY
The right hand side of the screen will show an info panel that shows a lot of different information so you can quickly see your bot settings and how it performed right on the screen.
In the top right corner you will see in purple your bot settings. These include your stoploss % if turned on, take profit %, average down order %, average down order % multiplier, volume multiplier, max number of orders allowed and size of your base order.
The top section of the first column “Current Trade” shows these stats: the open trade’s average price, the open trade’s take profit price, the open trade’s PNL, how far price is from your open tarde’s take profit level in percentage, your open position size and number of open orders.
The bottom section of the first column “Overall Performance” shows these stats: total number of trades taken during backtesting range, the largest amount of trades that were open at one time during backtesting, the max drawdown, the average number of bars per trade, gross profit, net profit, percent profit from your initial capital, current portfolio value and your initial capital.
CUSTOMIZABLE OPTIONS TO FIND THE PERFECT STRATEGY
Stoploss On/Off
This will turn your stoploss on or off. By default it is set to off and will not affect anything unless turned on.
Stoploss Percentage
This is the percentage below your final average down order price that will be set as a stoploss to keep your account from going too far in the red on big dips.
Take Profit Percentage - This is the percentage of profit you want the trade to hit before taking profit on your entire DCA trade. This level updates everytime you average down.
Average Down Percentage - This is the percentage that price has to drop from your initial order to initiate your first safety order. If the Average Down Percent Multiplier is set to 1 then this percentage will be the same for every average down order.
Average Down Percentage Multiplier - This multiplies your Average Down Percentage so each safety order needs a larger percentage deviation than the previous one. This keeps your buys closer together at the beginning and further apart when you hit more orders so you can extend your trading range but still be aggressive when price is going sideways.
Volume Multiplier Per New Order - This multiplies the size of each trade based on your base order. If you set it to a 2x multiplier then each average down order will be 2 times the size of the last one. So for example, a $100 base order with a 2x multiplier would have these values for the first 3 average down orders: 200, 400, 800.
Size Of Base Order - This is the size of your first position entry and will be used as a starting point for the volume multiplier. If your base order is $100 then it will buy $100 worth of whatever crypto you are backtesting this on. If you are looking at stock charts, you need to make sure your base order is higher than the share price across the entire backtesting range or it will not perform correctly.
Max Number Of Orders - This is the maximum number of orders the bot can take, including your base order. Adjust this to suit the amount of capital you are willing to allocate to your bot based on how much money it will require to run according to your bot settings.
TIPS ON HOW TO USE FOR BEST RESULTS
If you don’t have a lot of capital to work with, then use longer timeframes with a reasonable take profit percentage so that you don’t need a lot of average down orders. You can also try keeping the volume multiplier close to 1.
You can use the 3Commas dca bot settings page to see how much capital you will need for your strategy if you match it to the settings you have on this indicator. You can also check to see how much of a percentage deviation your bot is covering to make sure you have a reasonable range to trade in and orders to cover big dips. You can also check your coverage by seeing how far down the chart the green lines cover, which are your average down orders.
Make sure the initial capital in the properties tab of the settings has enough to cover all of your orders otherwise you will get unrealistic backtesting results. Also, make sure you leave the order size in the properties tab on contracts so it calculates your trades correctly. The only settings you need to touch in the properties tab is the initial capital. Unless you are trading somewhere that has lower commission fees, then you can change that to match, but leave all the other settings as is for it to function properly.
Increasing the volume multiplier will make your average price and take profit target follow the price action a lot closer as price falls, but it can also lead to having very large orders very quickly once you get into the 1.5-3x multiple range. Try using a high volume multiplier with less safety orders and you will get better results, however you need to have money on the sidelines to add on major dips to keep your bot turning a profit. Be very careful with this as greed and impatience will hurt your overall performance. This bot is meant to make money with lots of small wins so don’t get greedy and make sure you have enough money to cover large dips. If you are being aggressive with your bot, then I recommend only using 25% or less of your portfolio to trade aggressively and then use the smart trade feature on 3commas to add chunks of funds to your trades when price dips below your last safety order. Or if you want it to run without any supervision, then use lower volume multipliers and have lots of safety orders that can cover entire bear markets and still keep buying lower.
It’s a good idea to have some capital on the sidelines that you can add in when price dips quickly. This will help lower your average price and allow your bot to get out in profit quicker. 3Commas bot has a smart trade feature that will allow you to track your average price when adding extra funds and it will automatically update your other orders which is very convenient. Look at the longer timeframes when price dips and only add chunks at major areas where price is very likely to bounce. Or you can be aggressive when trading and add to your position when price dips and is at a likely bounce zone to maximize profits.
Only trade coins that have a good amount of liquidity as the larger your orders get, the harder it will be to sell if there isn’t much liquidity. Also, beware of how large your first order is as it will usually be a market order and can move the market if there is not much liquidity.
Since this bot takes a lot of trades and performs best when taking small profits consistently, you will need to factor in exchange fees. The bot is set to .5% commission(you can change this) on the buy and sell orders as most exchanges charge that amount. Some exchanges offer no fee trading on certain coins so be sure to look around for those so you can keep the commissions and maximize profits.
I strongly encourage you to try out a lot of different setting combinations across multiple different coins and do it across a few months to see how it would have performed under various market conditions. This will help you get a better idea of how much of a percentage deviation you’ll need to be able to cover to keep your bot running and making constant profits. You can also use the deep backtesting feature of the strategy panel to see how it would have done, but just beware that the info panel of the indicator will not reflect deep backtesting results, only the normal backtesting range.
MARKETS
This backtester can be used on any market including crypto, stocks, forex & futures. You just need to make sure your base order is larger than the share price when using this on things besides crypto.
TIMEFRAMES
This backtester can be used on all timeframes.
SPX Fair Value Strategy UltimateThis is a strategy using the SPX Fair Value derived from Net Liquidity.
Net Liquidity function is simply: Fed Balance Sheet - Treasury General Account - Reverse Repo Balance
Formula for calculating the fair value of SPX using Net Liquidity looks like this: net_liquidity/1000000000/1.1 -1625
The SPX Fair Value is then subtracted from the SPX value which creates an oscillating diff value.
When diff is greater than 350, SPX is considered overbought and we go short/sell.
When diff is less than -150, SPX is considered oversold and we cover/buy.
The net liquidity values I calculate outside of TradingView. If you'd like the strategy to work for future dates, you'll need to update them.
Paremeters:
Strategy: Short Only, Long Only, Long/Short
Inverse (bool): check if using an inverse ETF to go long instead of short.
Start After Date: When the strategy should start trading
Close Date: Day to close open trades. I just like it to get complete results rather than the strategy ending with open trades.
Supertrend pro+ (Adaptive ATR) Supertrend Pro+ (Adaptive ATR) - Param Approach
By SKP
Overview
This advanced Supertrend Pro+ strategy improves on the classic Supertrend indicator by integrating an Adaptive ATR, ensuring dynamic volatility adjustments for more accurate trend detection. This strategy filters out false signals using ADX trend strength validation and volume confirmation, making it a powerful tool for trend-following traders.
Key Features
✔ Adaptive ATR Calculation - Dynamically adjusts to market volatility for more reliable Supertrend signals.
✔ ADX Trend Filter - Ensures trades occur only in strong trending markets, avoiding false breakouts.
✔ Volume Confirmation - Prevents trading in low-liquidity conditions by verifying volume strength.
✔ Multi-Timeframe Analysis - Displays Supertrend trends from different timeframes for enhanced trade confidence.
✔ Trailing Stop & Take Profit Options - Allows flexible risk management with stop-loss and profit-targeting mechanisms.
✔ Custom Alerts for Trade Signals - Alerts trigger on confirmed Supertrend buy/sell signals and potential trend shifts.
✔ Max Drawdown Protection - Automatically closes trades if equity drops beyond a set percentage, preventing excessive losses.
How It Works
Adaptive ATR Calculation
Instead of using a fixed ATR, this strategy calculates an adaptive ATR based on a longer-term ATR baseline.
If volatility increases, the ATR expands dynamically, ensuring stop-losses and Supertrend calculations adjust accordingly.
Supertrend Confirmation
Uses an enhanced Supertrend algorithm with adaptive ATR to determine trend direction.
If price crosses above the trendline, it signals a bullish reversal (Buy Signal).
If price crosses below the trendline, it signals a bearish reversal (Sell Signal).
ADX Trend Strength Filter
Trades are only taken when ADX is above the threshold, ensuring entry in strong trending markets.
Volume Confirmation
Uses a relative volume filter to ensure sufficient liquidity before entering trades.
Helps avoid false breakouts in low-volume conditions.
Risk Management
Trailing Stop Loss - Automatically moves the stop as price moves in favor of the trade.
Manual Stop Loss & Take Profit - Allows precise percentage-based exit points.
Max Drawdown Protection - Closes all trades if equity falls below a set threshold, reducing risk.
Multi-Timeframe Supertrend Table
Displays Supertrend signals across different timeframes (1 min, 5 min, 15 min, 1 hour, Daily)
Helps traders align their entries with higher timeframe trends for better accuracy.
Custom Alerts
Alerts notify when a new buy/sell signal appears.
Extra early warning alerts indicate potential trade setups before confirmation.
How to Use
📌 For trend-following traders:
Focus on entries in the direction of the higher timeframes.
Only enter when ADX is trending and volume confirms liquidity.
📌 For scalpers:
Use shorter timeframes (1m, 5m, 15m) for quick trades.
Adjust the ATR multiplier and Adaptive ATR sensitivity for tighter stops.
📌 For swing traders:
Use longer timeframes (1H, Daily) for more stable trends.
Enable trailing stop loss to lock in profits as the trend progresses.
Inputs & Customization
ATR Period & Adaptive ATR Sensitivity
Supertrend Multiplier
ADX Filter & Threshold
Volume Confirmation Settings
Stop Loss & Take Profit Options
Multi-Timeframe Supertrend Display
Custom Alerts
Forex Hammer and Hanging Man StrategyThe strategy is based on two key candlestick chart patterns: Hammer and Hanging Man. These chart patterns are widely used in technical analysis to identify potential reversal points in the market. Their relevance in the Forex market, known for its high liquidity and volatile price movements, is particularly pronounced. Both patterns provide insights into market sentiment and trader psychology, which are critical in currency trading, where short-term volatility plays a significant role.
1. Hammer:
• Typically occurs after a downtrend.
• Signals a potential trend reversal to the upside.
• A Hammer has:
• A small body (close and open are close to each other).
• A long lower shadow, at least twice as long as the body.
• No or a very short upper shadow.
2. Hanging Man:
• Typically occurs after an uptrend.
• Signals a potential reversal to the downside.
• A Hanging Man has:
• A small body, similar to the Hammer.
• A long lower shadow, at least twice as long as the body.
• A small or no upper shadow.
These patterns are a manifestation of market psychology, specifically the tug-of-war between buyers and sellers. The Hammer reflects a situation where sellers tried to push the price down but were overpowered by buyers, while the Hanging Man shows that buyers failed to maintain the upward movement, and sellers could take control.
Relevance of Chart Patterns in Forex
In the Forex market, chart patterns are vital tools because they offer insights into price action and market sentiment. Since Forex trading often involves large volumes of trades, chart patterns like the Hammer and Hanging Man are important for recognizing potential shifts in market momentum. These patterns are a part of technical analysis, which aims to forecast future price movements based on historical data, relying on the psychology of market participants.
Scientific Literature on the Relevance of Candlestick Patterns
1. Behavioral Finance and Candlestick Patterns:
Research on behavioral finance supports the idea that candlestick patterns, such as the Hammer and Hanging Man, are relevant because they reflect shifts in trader psychology and sentiment. According to Lo, Mamaysky, and Wang (2000), patterns like these could be seen as representations of collective investor behavior, influenced by overreaction, optimism, or pessimism, and can often signal reversals in market trends.
2. Statistical Validation of Chart Patterns:
Studies by Brock, Lakonishok, and LeBaron (1992) explored the profitability of technical analysis strategies, including candlestick patterns, and found evidence that certain patterns, such as the Hammer, can have predictive value in financial markets. While their study primarily focused on stock markets, their findings are generally applicable to the Forex market as well.
3. Market Efficiency and Candlestick Patterns:
The efficient market hypothesis (EMH) posits that all available information is reflected in asset prices, but some studies suggest that markets may not always be perfectly efficient, allowing for profitable exploitation of certain chart patterns. For instance, Jegadeesh and Titman (1993) found that momentum strategies, which often rely on price patterns and trends, could generate significant returns, suggesting that patterns like the Hammer or Hanging Man may provide a slight edge, particularly in short-term Forex trading.
Testing the Strategy in Forex Using the Provided Script
The provided script allows traders to test and evaluate the Hammer and Hanging Man patterns in Forex trading by entering positions when these patterns appear and holding the position for a specified number of periods. This strategy can be tested to assess its performance across different currency pairs and timeframes.
1. Testing on Different Timeframes:
• The effectiveness of candlestick patterns can vary across different timeframes, as market dynamics change with the level of detail in each timeframe. Shorter timeframes may provide more frequent signals, but with higher noise, while longer timeframes may produce more reliable signals, but with fewer opportunities. This multi-timeframe analysis could be an area to explore to enhance the strategy’s robustness.
2. Exit Strategies:
• The script incorporates an exit strategy where positions are closed after holding them for a specified number of periods. This is useful for testing how long the reversal patterns typically take to play out and when the optimal exit occurs for maximum profitability. It can also help to adjust the exit logic based on real-time market behavior.
Conclusion
The Hammer and Hanging Man patterns are widely recognized in technical analysis as potential reversal signals, and their application in Forex trading is valuable due to the market’s high volatility and liquidity. This strategy leverages these candlestick patterns to enter and exit trades based on shifts in market sentiment and psychology. Testing and optimization, as offered by the script, can help refine the strategy and improve its effectiveness.
For further refinement, it could be valuable to consider combining candlestick patterns with other technical indicators or using multi-timeframe analysis to confirm patterns and increase the probability of successful trades.
References:
• Lo, A. W., Mamaysky, H., & Wang, J. (2000). Foundations of Technical Analysis: Computational Algorithms, Statistical Inference, and Empirical Implementation. The Journal of Finance, 55(4), 1705-1770.
• Brock, W., Lakonishok, J., & LeBaron, B. (1992). Simple Technical Trading Rules and the Stochastic Properties of Stock Returns. The Journal of Finance, 47(5), 1731-1764.
• Jegadeesh, N., & Titman, S. (1993). Returns to Buying Winners and Selling Losers: Implications for Stock Market Efficiency. The Journal of Finance, 48(1), 65-91.
This provides a theoretical basis for the use of candlestick patterns in trading, supported by academic literature and research on market psychology and efficiency.
Powertrend - Volume Range Filter Strategy [wbburgin]The Powertrend is a range filter that is based off of volume, instead of price. This helps the range filter capture trends more accurately than a price-based range filter, because the range filter will update itself from changes in volume instead of changes in price. In certain scenarios this means that the Powertrend will be more profitable than a normal range filter.
Essentials of the Strategy
This is a breakout strategy which works best on trending assets with high volume and liquidity. It should be used on middle to higher timeframes and can be used on all assets that have volume provided by the data source (stocks, crypto, forex). It is long-only as of now. It can work on lower timeframes if you optimize the strategy filters to make less trades or if your exchange/broker is low/no fees, provided that your exchange/broker has high liquidity and volume.
The strategy enters a long position if the range filter is trending upwards and the price crosses over the upper range band, which signifies a price-volume breakout. The strategy closes the long position if the range filter is trending downwards and the price crosses under the lower range band, which signifies a breakdown. Both these conditions can be altered by the three filter options in the settings. The default trend filter is not alterable because it helps prevent false entries and exits that are against the trend.
Settings
The Length setting is the lookback period for the range smoothing.
The ADX Filter setting enables you to turn on an ADX filter, which will halt entries and exits unless the ADX of your customizable length is above a ADX VWMA of that length.
The Range Supertrend setting creates a supertrend from the top and bottom ranges, which can be used to filter entries and exits. The length is customizable. The filter can show you whether the range is making higher highs and lower lows. Below is an example of the Range Supertrend being used as a filter and plotted on-chart:
The VWMA setting halts entries if they are below a customizable length VWMA.
Both the Range Supertrend and the VWMA can also be plotted separately without actually filtering the strategy, so that you can use them independently if you wish. You can turn off the bar color, the highlighting, and the labels if you wish in the settings. A note about the bar color: if the color changes but the strategy does not signal an exit or entry this means that the crossover was against the trend. In these circumstances it may be indicative of a pullback to enter or exit or to add onto your position.
About the Strategy Results Below
A range filter is normally composed of two components - the range filter itself and a smoothing function. In the development of this script I tested both normal and volume-based varieties of the range filter and the smoothing function:
Tests Performed
Volume-based Range x VWMA smoothing
Price-based Range x VWMA smoothing
Price-based Range x EMA smoothing
Volume-based Range x EMA smoothing (final result)
The highest-performing was a volume-based range filter and a normal EMA-based smoothing function, but that does not mean that this strategy will be profitable - exits are based off of signal reversion so I strongly encourage you to develop your own take profits/stop losses for the strategy if you think it may be a good fit for you. The results below are with a commission value of 0.05% (because I built the strategy first for equities), slippage of 3, so if your exchange/broker has a higher fee schedule, I recommend adding filters and/or moving to higher timeframes for the strategy. Additionally, I used 10% of equity in each trade, while using the Range Supertrend filter (the previous upload was unrealistic because it used 100% of equity - missed a 0, apologies, and added in slippage).
DLX-NationThis Strategy is based on 8 EMAs and the RSI ( 14 Length )
Its algorism check for the trend of the market using crossover EMAs, then it waits for a 38% - 50% pullback. During this Pullback it checks the behaviour of the EMAs by making sure consolidation is coming to and end by checking if the red EMA cuts through certain candle bodies. Then it detects a takeover in the market, meaning during a pullback ( in case of a buy ) it calculates the selling volume and waits to confirm that buyers retake over the Market by calculating the candle sizes making sure the current candle is bigger than the previous candle using the 3rd EMA (if 50 EMA is below market price) then finally It checks if there is enough buying Strength ( in case of a buy ) or enough selling strength ( in case of a sell) by checking the RSI level over a certain period of time. When all these confirmations are done, it then analyses previous supports and resistence, and only sends a signal if there is not resistance for a buy and no support for a sell.
Its best for a strong bullish or bearish 1min, 5mins and 15mins market, thats why it only available on US30 and NAS100 for now. Its best when all the EMAs are spreading out or in other words the distance between the EMAs are increasing.
In case of a consolidation, you will see all EMAs moving together and in this case you shouldnt take any signal called. Following EMAs should guide you identifying a consilidation
50 EMA = Aqua
90 EMA = Green
150 EMA = Purple
200 EMA = Gray
400 EMA = Orange
800 EMA = Blue
Note: If you see all these EMA coming closer to each other, it indicates a long going consolidation and during these moments you shouldnt execute any signal. These is the reason why we decided to plot them on the Chart. We understand trading with a clean Chart is important, moreover using certain tools to be more profitable is essential. In case the 50 EMA ( Aqua ) Crosses over or below the 150 EMA ( Green ) and 200 EMA (Gray), this will indicate end of the consolidation and the signals will have more liquidity and movement.
Lastly when a signal is being called make sure the last candle is clearly bigger than the previous candles, this indicates that the buyer ( in case of a buy candle ) are clearly taking over the market or the sellers ( in case of a sell candle ) are clearly taking over the market giving you more volume and liquidity.
To optain the max Profit:
After adding the Strategy / Indicator on your Chart go to Settings -> Properties and set the Pyramiding to 30. These implies that we can have 30 consecutive buy signals in a row or sell signals in a row. We recommend an initail Balance of 2000$, but mininum 1000% and a lotsize of 10cent per pip (0.1). Strickly follow the Take Profit (100pips) and StopLoss (500pips) level that will be provided in this case also risk only 1% of your account per trade and maximun 5% per running trades.
Keep in mind, the smaller the TImeframe the more trades you will recieve and the stronger the momentum the more profitable the trade will be.
