Renko Chart EmulationRenko charts are a popular tool in technical analysis, known for their ability to filter out market noise and focus purely on price movements. Unlike traditional candlestick or bar charts, Renko charts are not time-based but are constructed using bricks that represent a fixed price movement. This makes them particularly useful for identifying trends and key levels of support and resistance. While Renko charts are commonly found on platforms with specialized charting capabilities, they can also be emulated in Pine Script as a line indicator.
The Renko emulation indicator in Pine Script calculates the movement of price based on a user-defined brick size. Whenever the price moves up or down by an amount equal to or greater than the brick size, a new level is plotted, indicating a shift in price direction. This approach helps traders visualize significant price moves without the distractions of smaller fluctuations. By plotting the Renko levels as a continuous line and coloring it based on direction, this indicator provides a clean and straightforward representation of market trends.
Traders can use this Renko emulation line to identify potential entry and exit points, as well as to confirm ongoing trends. The simplicity of Renko charts makes them a favorite among those who prefer a minimalist approach to technical analysis. However, it is essential to choose an appropriate brick size that aligns with the volatility of the trading instrument. A smaller brick size may result in frequent signals, while a larger one can smooth out the chart, focusing only on the most substantial price movements. This script offers a flexible solution for incorporating Renko-style analysis into any trading strategy.
Educational
Correlation Coefficient Master TableThe Correlation Coefficient Master Table is a comprehensive tool designed to calculate and visualize the correlation coefficient between a selected base asset and multiple other assets over various time periods. It provides traders and analysts with a clear understanding of the relationships between assets, enabling them to analyze trends, diversification opportunities, and market dynamics. You can define key parameters such as the base asset’s data source (e.g., close price), the assets to compare against (up to six symbols), and multiple lookback periods for granular analysis.
The indicator calculates the covariance and normalizes it by the product of the standard deviations. The correlation coefficient ranges from -1 to +1, with +1 indicating a perfect positive relationship, -1 a perfect negative relationship, and 0 no relationship.
You can specify the lookback periods (e.g., 15, 30, 90, or 120 bars) to tailor the calculation to their analysis needs. The results are visualized as both a line plot and a table. The line plot shows the correlation over the primary lookback period (the Chart Length), which can be used to inspect a certain length close up, or could be used in conjunction with the table to provide you with five lookback periods at once for the same base asset. The dynamically created table provides a detailed breakdown of correlation values for up to six target assets across the four user-defined lengths. The table’s cells are formatted with rounded values and color-coded for easy interpretation.
This indicator is ideal for traders, portfolio managers, and market researchers who need an in-depth understanding of asset interdependencies. By providing both the numerical correlation coefficients and their visual representation, users can easily identify patterns, assess diversification strategies, and monitor correlations across multiple timeframes, making it a valuable tool for decision-making.
Fibonacci Trend - Aynet1. Inputs
lookbackPeriod: Defines the number of bars to consider for calculating swing highs and lows. Default is 20.
fibLevel1 to fibLevel5: Fibonacci retracement levels to calculate price levels (23.6%, 38.2%, 50%, 61.8%, 78.6%).
useTime: Enables or disables time-based Fibonacci projections.
riskPercent: Defines the percentage of risk for trading purposes (currently not used in calculations).
2. Functions
isSwingHigh(index): Identifies a swing high at the given index, where the high of that candle is higher than both its previous and subsequent candles.
isSwingLow(index): Identifies a swing low at the given index, where the low of that candle is lower than both its previous and subsequent candles.
3. Variables
swingHigh and swingLow: Store the most recent swing high and swing low prices.
swingHighTime and swingLowTime: Store the timestamps of the swing high and swing low.
fib1 to fib5: Fibonacci levels based on the difference between swingHigh and swingLow.
4. Swing Point Detection
The script checks if the last bar is a swing high or swing low using the isSwingHigh() and isSwingLow() functions.
If a swing high is detected:
The high price is stored in swingHigh.
The timestamp of the swing high is stored in swingHighTime.
If a swing low is detected:
The low price is stored in swingLow.
The timestamp of the swing low is stored in swingLowTime.
5. Fibonacci Levels Calculation
If both swingHigh and swingLow are defined, the script calculates the Fibonacci retracement levels (fib1 to fib5) based on the price difference (priceDiff = swingHigh - swingLow).
6. Plotting Fibonacci Levels
Fibonacci levels (fib1 to fib5) are plotted as horizontal lines using the line.new() function.
Labels (e.g., "23.6%") are added near the lines to indicate the level.
Lines and labels are color-coded:
23.6% → Blue
38.2% → Green
50.0% → Yellow
61.8% → Orange
78.6% → Red
7. Filling Between Fibonacci Levels
The plot() function creates lines for each Fibonacci level.
The fill() function is used to fill the space between two levels with semi-transparent colors:
Blue → Between fib1 and fib2
Green → Between fib2 and fib3
Yellow → Between fib3 and fib4
Orange → Between fib4 and fib5
8. Time-Based Fibonacci Projections
If useTime is enabled:
The time difference (timeDiff) between the swing high and swing low is calculated.
Fibonacci time projections are added based on multiples of 23.6%.
If the current time reaches a projected time, a label (e.g., "T1", "T2") is displayed near the high price.
9. Trading Logic
Two placeholder variables are defined for trading logic:
longCondition: Tracks whether a condition for a long trade is met (currently not implemented).
shortCondition: Tracks whether a condition for a short trade is met (currently not implemented).
These variables can be extended to define entry/exit signals based on Fibonacci levels.
How It Works
Detect Swing Points: It identifies recent swing high and swing low points on the chart.
Calculate Fibonacci Levels: Based on the swing points, it computes retracement levels.
Visualize Levels: Plots the levels on the chart with labels and fills between them.
Time Projections: Optionally calculates time-based projections for future price movements.
Trading Opportunities: The framework provides tools for detecting potential reversal or breakout zones using Fibonacci levels.
ChrismtasMerry Christmas and Happy New Year! This magical time of year brings us together with loved ones, fills our hearts with joy, and offers us a chance to reflect on the past year and look forward to the future.
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.
Center of Candle Trendline### **Center of Candle Trendline**
This script dynamically plots a trendline through the center of each candlestick's body. The "center" is calculated as the average of the open and close prices for each candle. The trendline updates in real-time as new candles form, providing a clean and straightforward way to track the market's midline movement.
#### **Features:**
1. **Dynamic Trendline:** The trendline connects the center points of consecutive candlestick bodies, giving a clear visual representation of price movements.
2. **Accurate Center Calculation:** The center is determined as `(open + close) / 2`, ensuring the trendline reflects the true midpoint of each candlestick body.
3. **Real-Time Updates:** The trendline updates automatically as new bars form, keeping your chart up to date with the latest price action.
4. **Customization-Ready:** Adjust the line’s color, width, or style easily to fit your chart preferences.
#### **How to Use:**
- Add this script to your chart to monitor the price movement relative to the center of candlestick bodies.
- Use the trendline to identify trends, reversals, or price consolidation zones.
#### **Applications:**
- **Trend Analysis:** Visualize how the market trends around the center of candlesticks.
- **Reversal Identification:** Detect potential reversal zones when the price deviates significantly from the trendline.
- **Support and Resistance Zones:** Use the trendline as a dynamic support or resistance reference.
This tool is perfect for traders who want a clean and minimalistic approach to tracking price action. Whether you're a beginner or an experienced trader, this script provides valuable insights without overwhelming your chart.
#### **Note:**
This is not a standalone trading strategy but a visual aid to complement your analysis. Always combine it with other tools and techniques for better trading decisions.
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Feel free to tweak this description based on your preferences or style!
Position sizerPosition Sizer Indicator
The "Position Sizer" indicator is a practical tool for traders who need to quickly and accurately calculate position sizes based on their account balance, risk tolerance, and stop-loss level. It ensures real-time updates and supports multiple asset classes like Forex, Indexes, Metals, and Crypto.
Key Features
Dynamic Position Sizing: Automatically calculates position sizes based on the current market price and stop-loss level.
Stop-Loss Adjustment: Allows users to drag the stop-loss level directly on the chart, dynamically updating the position size.
Interactive Table: A single click on the table activates the draggable stop-loss level for easy adjustments.
Multi-Asset Compatibility: Fully supports Forex, Indexes, Metals, and Crypto trading pairs.
How to Use
Deactivate the Indicator:
Turn off the indicator to make it inactive.
Set the Stop-Loss Price:
Copy the stop-loss price or use a price near the current market price.
Reactivate the indicator after inserting the stop-loss price.
Adjust the Stop-Loss Level if needed:
Click once on the table to enable the stop-loss level for dragging.
Move the stop-loss line as needed—position sizes will automatically recalculate.
Important Disclaimer
Verification Required: Always verify the calculated position size before executing trades.
Broker Confirmation: Double-check the point size for your trading symbol with your broker to avoid errors in calculations.
User Responsibility: The creator assumes no responsibility for any trading decisions made based on this indicator.
This tool helps streamline position management, ensuring you can focus on executing your trades with accuracy and speed. Always confirm your calculations before trading.
Enhanced Renko Channel with Emulation and SMA by Dr DevendraThis indicator combines a dynamic Renko-based channel with emulated Renko bricks and a customizable Simple Moving Average (SMA). It provides traders with a powerful tool for identifying trends, visualizing price movement within a Renko framework, and overlaying critical moving average signals.
Features:
Renko Channel:
A Gaussian-based midline with adjustable poles and sampling periods.
True Range-based dynamic channel boundaries.
Visual trend identification with color-coded channel fills.
Renko Emulation:
Emulated Renko brick levels with adjustable brick sizes.
Dynamic brick plotting based on price action.
Simple Moving Average (SMA):
Configurable length and source (e.g., close, hlc3, etc.).
Dynamic color changes based on SMA slope (uptrend or downtrend).
Customizable Inputs:
Adjustable parameters for the channel, Renko emulation, and SMA settings.
Options for reduced lag and fast response modes in the Renko channel.
Improved RSI Trend Sniper | JeffreyTimmermansImproved RSI Trend Sniper
This indicator, the "Improved RSI Trend Sniper" is a sophisticated tool designed to enhance market trend analysis by integrating customizable RSI thresholds with advanced moving average options and refined visual enhancements.
Key Features
Advanced Moving Average Options:
The indicator now supports multiple moving average types: SMA, EMA, SMMA, WMA, VWMA, LSMA, HMA, and ALMA, offering greater flexibility in trend analysis.
Users can customize the moving average length for precise momentum detection.
Enhanced Momentum Detection:
Upgraded to allow dynamic calculation of momentum based on user-selected moving averages.
Conditions for bullish or bearish momentum now consider changes in the chosen moving average rather than a fixed EMA, improving accuracy.
Visual Upgrades:
A gradient-based trend fill with multiple opacity layers provides a visually appealing representation of bullish and bearish trends.
New dashboard integration displays key market information, including the ticker, timeframe, and current trend (bullish or bearish).
Improved Signal Customization:
Customizable colors and labels for bullish and bearish signals ensure easy identification on the chart.
Enhanced settings for showing or hiding labels and trend fills
Refined Alerts System:
Alerts are now generated for bullish and bearish conditions with customized messages for better responsiveness.
Alerts can be triggered once per bar close, making them more reliable.
What's New:
RSI and MA Customization: Users can define thresholds and moving average settings, providing more control over trend analysis.
Dashboard Integration: Displays real-time updates directly on the chart for improved situational awareness.
Visual Enhancements: Introduced gradient fills for trend regions, making trends more distinct.
Expanded Moving Average Options: Allows for tailored strategies using various MA calculation methods.
Alert Messaging: Streamlined notifications for actionable insights.
How It Works
Momentum Analysis:
Bullish momentum is detected when the RSI crosses above the bullish threshold and the moving average is increasing.
Bearish momentum is flagged when the RSI falls below the bearish threshold, and the moving average is decreasing.
Trend Visualization:
Bullish trends are highlighted with gradient shades of green, while bearish trends use shades of red.
Labels appear on the chart to mark key turning points.
Tailored for Different Trading Styles
The Improved RSI Trend Sniper is versatile and adaptable, catering to traders with various time horizons:
Long-Term Adjustments: For traders focusing on long-term trends, increasing the RSI length and moving average period allows the indicator to smooth out minor price fluctuations and highlight sustained momentum. Selecting slower-moving averages like the SMA or LSMA further filters out short-term noise, ensuring signals align with broader market trends.
Medium-Term Adjustments: Swing traders can use a balanced RSI length (e.g., 14–20) and a medium moving average period (e.g., 20–50) to capture actionable signals within the mid-range market cycles. The inclusion of options like EMA or SMMA ensures quicker reactions to price changes while maintaining moderate sensitivity to reversals.
Short-Term Adjustments: For day traders or scalpers, using a shorter RSI period (e.g., 7–10) alongside faster moving averages such as the HMA or ALMA can provide quicker signals for high-frequency trading. These adjustments enhance the ability to react swiftly to immediate market shifts, ideal for fast-paced trading environments.
By customizing the indicator’s settings to align with your trading timeframe, the Improved RSI Trend Sniper ensures accurate and relevant insights, empowering traders to optimize their strategies across any market condition.
Dashboard Details
Provides an at-a-glance view of market data for the current ticker and timeframe.
The Improved RSI Trend Sniper takes the original tool to the next level, offering a more comprehensive, customizable, and visually intuitive approach to market trend analysis. Perfect for traders looking to refine their strategies with actionable insights.
-Jeffrey
Relative Performance Indicator by ComLucro - 2025_V01The "Relative Performance Indicator by ComLucro - 2025_V01" is a powerful tool designed to analyze an asset's performance relative to a benchmark index over multiple timeframes. This indicator provides traders with a clear view of how their chosen asset compares to a market index in short, medium, and long-term periods.
Key Features:
Customizable Lookback Periods: Analyze performance across three adjustable periods (default: 20, 50, and 200 bars).
Relative Performance Analysis: Calculate and visualize the difference in percentage performance between the asset and the benchmark index.
Dynamic Summary Label: Displays a detailed breakdown of the asset's and index's performance for the latest bar.
User-Friendly Interface: Includes customizable colors and display options for clear visualization.
How It Works:
The script fetches closing prices of both the asset and a benchmark index.
It calculates percentage changes over the selected lookback periods.
The indicator then computes the relative performance difference between the asset and the index, plotting it on the chart for easy trend analysis.
Who Is This For?:
Traders and investors who want to compare an asset’s performance against a benchmark index.
Those looking to identify trends and deviations between an asset and the broader market.
Disclaimer:
This tool is for educational purposes only and does not constitute financial or trading advice. Always use it alongside proper risk management strategies and backtest thoroughly before applying it to live trading.
Chart Recommendation:
Use this script on clean charts for better clarity. Combine it with other technical indicators like moving averages or trendlines to enhance your analysis. Ensure you adjust the lookback periods to match your trading style and the timeframe of your analysis.
Additional Notes:
For optimal performance, ensure the benchmark index's data is available on your TradingView subscription. The script uses fallback mechanisms to avoid interruptions when index data is unavailable. Always validate the settings and test them to suit your trading strategy.
Crypto Market Caps / Global GDP %This indicator compares the total market capitalization of various crypto sectors to the global Gross Domestic Product (GDP), expressed as a percentage. The purpose of this indicator is to provide a visual representation of the relative size of the crypto market compared to the global economy, allowing traders and analysts to understand how the market is growing in relation to the overall economy.
Key Features
Crypto Market Caps -
TOTAL: Represents the total market capitalization of all cryptocurrencies.
TOTAL3: Represents the market capitalization of all cryptocurrencies, excluding Bitcoin and Ethereum.
OTHERS: Represents the market capitalization of all cryptocurrencies excluding the top 10.
Global GDP -
The indicator uses a combination of GDP data from multiple regions across the world, including:
GDP from the EU, North America (NA), and other regions.
GDP data from Asia, Latin America (LATAM), and the Middle East & North Africa (MENA).
Percentage Representation -
The market caps (TOTAL, TOTAL3, OTHERS) are compared to the global GDP, and the result is expressed as a percentage. This allows you to easily see how the size of the cryptocurrency market compares to the entire global economy at any given time.
Plotting and Visualization
The indicator plots the market cap to global GDP ratio for each category (TOTAL, TOTAL3, OTHERS) on the chart.
You can choose which plots to display through user inputs.
The percentage scale makes it easy to compare how much of the global GDP is represented by different parts of the crypto market.
Labels can be added for additional clarity, showing the exact percentage value on the chart.
How to Use
The indicator provides a clear view of the cryptocurrency market's relative size compared to the global economy.
Higher values indicate that the crypto market (or a segment of it) is becoming a larger portion of the global economy.
Lower values suggest the crypto market is still a smaller segment of the global economic activity.
User Inputs
TOTAL/GlobalGDP: Toggle visibility for the total market capitalization of all cryptocurrencies.
TOTAL3/GlobalGDP: Toggle visibility for the market cap of cryptocurrencies excluding Bitcoin and Ethereum.
OTHERS/GlobalGDP: Toggle visibility for the market cap of cryptocurrencies excluding the top 10.
Labels: Enable or disable the display of labels showing the exact percentage values.
Practical Use Cases
Market Sentiment: Gauge the overall market sentiment and potential growth relative to global economic conditions.
Investment Decisions: Help identify when the crypto market is becoming more or less significant in the context of the global economy.
Macro Analysis: Combine this indicator with other macroeconomic indicators to gain deeper insights into the broader economic landscape.
By providing an easy-to-understand percentage representation, this indicator offers valuable insights for anyone interested in tracking the relationship between cryptocurrency market cap and global economic activity.
GL_Prev Week HighThe GL_Prev Week High Indicator is a powerful tool designed to enhance your trading analysis by displaying the previous week's high price directly on your chart. With clear and customizable visuals, this indicator helps traders quickly identify critical price levels, enabling more informed decision-making.
Key Features:
Previous Week's High Line:
Displays the previous week's high as a red line on your chart for easy reference.
Customizable Horizontal Line:
Includes a white horizontal line for enhanced clarity, with adjustable length, color, and width settings.
All-Time High Tracking:
Automatically tracks the all-time high from the chart's history and places a dynamic label above it.
Real-Time Updates:
The indicator updates in real-time to ensure accuracy as new bars are added.
User Inputs for Personalization:
Adjust the left and right span of the horizontal line.
Customize line width and color to suit your preferences.
Use Case:
This indicator is ideal for traders looking to integrate the previous week's high as a key support or resistance level in their trading strategy. Whether you are analyzing trends, identifying breakout zones, or planning entry/exit points, this tool provides valuable insights directly on the chart.
How to Use:
Add the indicator to your chart.
Customize the settings (line length, width, and color) through the input panel to match your preferences.
Use the red line to track the previous week's high and the label to monitor all-time highs effortlessly.
License:
This script is shared under the Mozilla Public License 2.0. Feel free to use and adapt the script as per the license terms.
Adaptive Momentum Reversion StrategyThe Adaptive Momentum Reversion Strategy: An Empirical Approach to Market Behavior
The Adaptive Momentum Reversion Strategy seeks to capitalize on market price dynamics by combining concepts from momentum and mean reversion theories. This hybrid approach leverages a Rate of Change (ROC) indicator along with Bollinger Bands to identify overbought and oversold conditions, triggering trades based on the crossing of specific thresholds. The strategy aims to detect momentum shifts and exploit price reversions to their mean.
Theoretical Framework
Momentum and Mean Reversion: Momentum trading assumes that assets with a recent history of strong performance will continue in that direction, while mean reversion suggests that assets tend to return to their historical average over time (Fama & French, 1988; Poterba & Summers, 1988). This strategy incorporates elements of both, looking for periods when momentum is either overextended (and likely to revert) or when the asset’s price is temporarily underpriced relative to its historical trend.
Rate of Change (ROC): The ROC is a straightforward momentum indicator that measures the percentage change in price over a specified period (Wilder, 1978). The strategy calculates the ROC over a 2-period window, making it responsive to short-term price changes. By using ROC, the strategy aims to detect price acceleration and deceleration.
Bollinger Bands: Bollinger Bands are used to identify volatility and potential price extremes, often signaling overbought or oversold conditions. The bands consist of a moving average and two standard deviation bounds that adjust dynamically with price volatility (Bollinger, 2002).
The strategy employs two sets of Bollinger Bands: one for short-term volatility (lower band) and another for longer-term trends (upper band), with different lengths and standard deviation multipliers.
Strategy Construction
Indicator Inputs:
ROC Period: The rate of change is computed over a 2-period window, which provides sensitivity to short-term price fluctuations.
Bollinger Bands:
Lower Band: Calculated with a 18-period length and a standard deviation of 1.7.
Upper Band: Calculated with a 21-period length and a standard deviation of 2.1.
Calculations:
ROC Calculation: The ROC is computed by comparing the current close price to the close price from rocPeriod days ago, expressing it as a percentage.
Bollinger Bands: The strategy calculates both upper and lower Bollinger Bands around the ROC, using a simple moving average as the central basis. The lower Bollinger Band is used as a reference for identifying potential long entry points when the ROC crosses above it, while the upper Bollinger Band serves as a reference for exits, when the ROC crosses below it.
Trading Conditions:
Long Entry: A long position is initiated when the ROC crosses above the lower Bollinger Band, signaling a potential shift from a period of low momentum to an increase in price movement.
Exit Condition: A position is closed when the ROC crosses under the upper Bollinger Band, or when the ROC drops below the lower band again, indicating a reversal or weakening of momentum.
Visual Indicators:
ROC Plot: The ROC is plotted as a line to visualize the momentum direction.
Bollinger Bands: The upper and lower bands, along with their basis (simple moving averages), are plotted to delineate the expected range for the ROC.
Background Color: To enhance decision-making, the strategy colors the background when extreme conditions are detected—green for oversold (ROC below the lower band) and red for overbought (ROC above the upper band), indicating potential reversal zones.
Strategy Performance Considerations
The use of Bollinger Bands in this strategy provides an adaptive framework that adjusts to changing market volatility. When volatility increases, the bands widen, allowing for larger price movements, while during quieter periods, the bands contract, reducing trade signals. This adaptiveness is critical in maintaining strategy effectiveness across different market conditions.
The strategy’s pyramiding setting is disabled (pyramiding=0), ensuring that only one position is taken at a time, which is a conservative risk management approach. Additionally, the strategy includes transaction costs and slippage parameters to account for real-world trading conditions.
Empirical Evidence and Relevance
The combination of momentum and mean reversion has been widely studied and shown to provide profitable opportunities under certain market conditions. Studies such as Jegadeesh and Titman (1993) confirm that momentum strategies tend to work well in trending markets, while mean reversion strategies have been effective during periods of high volatility or after sharp price movements (De Bondt & Thaler, 1985). By integrating both strategies into one system, the Adaptive Momentum Reversion Strategy may be able to capitalize on both trending and reverting market behavior.
Furthermore, research by Chan (1996) on momentum-based trading systems demonstrates that adaptive strategies, which adjust to changes in market volatility, often outperform static strategies, providing a compelling rationale for the use of Bollinger Bands in this context.
Conclusion
The Adaptive Momentum Reversion Strategy provides a robust framework for trading based on the dual concepts of momentum and mean reversion. By using ROC in combination with Bollinger Bands, the strategy is capable of identifying overbought and oversold conditions while adapting to changing market conditions. The use of adaptive indicators ensures that the strategy remains flexible and can perform across different market environments, potentially offering a competitive edge for traders who seek to balance risk and reward in their trading approaches.
References
Bollinger, J. (2002). Bollinger on Bollinger Bands. McGraw-Hill Professional.
Chan, L. K. C. (1996). Momentum, Mean Reversion, and the Cross-Section of Stock Returns. Journal of Finance, 51(5), 1681-1713.
De Bondt, W. F., & Thaler, R. H. (1985). Does the Stock Market Overreact? Journal of Finance, 40(3), 793-805.
Fama, E. F., & French, K. R. (1988). Permanent and Temporary Components of Stock Prices. Journal of Political Economy, 96(2), 246-273.
Jegadeesh, N., & Titman, S. (1993). Returns to Buying Winners and Selling Losers: Implications for Stock Market Efficiency. Journal of Finance, 48(1), 65-91.
Poterba, J. M., & Summers, L. H. (1988). Mean Reversion in Stock Prices: Evidence and Implications. Journal of Financial Economics, 22(1), 27-59.
Wilder, J. W. (1978). New Concepts in Technical Trading Systems. Trend Research.
Improved Target Oscillator | JeffreyTimmermansImproved Target Oscillator
The Improved Target Oscillator is a versatile technical indicator that identifies trends, reversals, and market momentum. Designed to work effectively across various markets, this oscillator excels at capturing longer-term market trends, making it ideal for traders focused on sustained price movements. By using advanced mathematical techniques and dynamic visualization, the oscillator provides actionable insights, helping traders navigate complex market environments with confidence.
Key features include:
A dynamic oscillator line to reflect market momentum and reversals.
Clear gradient-based coloring to distinguish between bullish and bearish conditions.
Signal highlights for potential entry and exit points based on trend shifts.
This tool is particularly useful for identifying extended trends and provides a clean, intuitive interface for assessing market dynamics.
Improvements in the Improved Target Oscillator
Smoothing Feature:
Added an optional smoothing toggle, allowing the use of SMA or EMA for reducing noise.
Provides flexibility through adjustable smoothing length, enhancing clarity in choppy markets.
Alerts for Trade Opportunities:
Built-in alert conditions for bullish and bearish signals.
Allows traders to receive notifications when critical trend changes occur, ensuring they never miss an opportunity.
Customizable to integrate seamlessly into trading workflows.
Enhanced Visualization:
Introduced dynamic gradients for bullish and bearish conditions with improved customization options.
Provides clearer differentiation of momentum changes, improving interpretability.
Signal Highlights:
Improved visual cues for bullish and bearish signals with precise dot indicators.
Offers better alignment with oscillator momentum shifts, ensuring actionable insights.
Adaptability:
Tuned for use in capturing longer-term market trends, emphasizing its effectiveness in identifying sustained movements.
Adjusted oscillator sensitivity with a levels multiplier for better scalability across various market conditions.
Level Markers:
Clearer delineation of key oscillator levels, including half and full normalized levels for improved context.
A neutral line explicitly plotted for easier trend and momentum identification.
Summary
The Improved Target Oscillator combines a sophisticated mathematical foundation with practical visualization enhancements to deliver a more intuitive and precise tool for market analysis. With added flexibility, improved signals, and tailored features for longer-term trends, this oscillator is an essential resource for traders looking to refine their strategies.
-Jeffrey
Candle Counter by ComLucro - Multi-Timefram - 2025_V01Candle Counter by ComLucro - Multi-Timeframe - 2025_V01
The Candle Counter by ComLucro - Multi-Timeframe is a highly customizable tool designed to help traders monitor the number of candles across various timeframes directly on their charts. Whether you're analyzing trends or tracking specific market behaviors, this indicator provides a seamless and efficient way to enhance your technical analysis.
Key Features:
Flexible Timeframe Selection: Track candle counts on yearly, monthly, weekly, daily, or hourly intervals to suit your trading style.
Dynamic Label Positioning: Choose to display labels above or below candles, offering greater control over your chart layout.
Customizable Colors: Adjust label text colors to match your chart's aesthetics and improve visibility.
Clean and Organized Visualization: Automatically generates labels for each candle without overcrowding your chart.
How It Works:
Select a Timeframe: Choose from yearly, monthly, weekly, daily, or hourly intervals based on your analysis needs.
Automatic Counting: The indicator calculates and displays the number of candles for the selected period directly on your chart.
Label Customization: Adjust the position (above or below the candles) and color of the labels to align with your preferences.
Why Use This Indicator?
This script is perfect for traders who need a clear and visual representation of candle counts in specific timeframes. Whether you're monitoring trends, evaluating price action, or developing strategies, the Candle Counter by ComLucro adapts to your needs and helps you make informed decisions.
Disclaimer:
This script is intended for educational and informational purposes only. It does not constitute financial advice. Always practice responsible trading and ensure this tool aligns with your strategies and risk management practices.
About ComLucro:
ComLucro is dedicated to providing traders with practical tools and educational resources to improve decision-making in the financial markets. Discover other scripts and strategies developed to enhance your trading experience.
Nen Star Harmonic Pattern [TradingFinder] NenStar Reversal Auto🔵 Introduction
The Nen-Star Harmonic Pattern is an advanced reversal pattern in technical analysis, designed to identify market trend changes and predict key price reversal points. This pattern is defined by a combination of Fibonacci ratios and critical concepts such as Potential Reversal Zones (PRZ), market structure, and corrective waves.
The key points of this pattern include X, A, B, C, and D, and it appears in both bullish and bearish forms. In its bullish form, the pattern resembles the letter M, while in its bearish form, it takes the shape of W. The critical Fibonacci ratios for this pattern are 0.382 to 0.786 for the XA wave, 1.13 to 1.414 for the AB wave, and 1.272 to 2.618 for the BC wave.
The Nen-Star Harmonic Pattern is one of the most precise tools for identifying market reversals and executing reversal trades. Traders can use it to pinpoint optimal entry and exit points and benefit from high risk-to-reward ratios.
By emphasizing Fibonacci retracement levels, XABCD waves, the formation of bullish and bearish patterns, and precise trade entry points, this pattern has become a practical tool in advanced technical analysis.
Bullish Nen-Star Pattern :
Bearish Nen-Star Pattern :
🔵 How to Use
The Nen-Star Harmonic Pattern indicator allows traders to automatically identify the bullish and bearish structures of this pattern and locate optimal entry and exit points. By accurately analyzing Fibonacci ratios and determining points X, A, B, C, and D, the indicator highlights Potential Reversal Zones (PRZ) on the chart. Traders can rely on the generated signals to manage their trades with greater precision.
🟣 Bullish Nen-Star Pattern
The bullish Nen-Star pattern begins with a price increase from point X to point A, followed by a retracement to point B, which lies between 0.382 and 0.786 of the XA wave.
After this retracement, the price moves to point C, located between 1.13 and 1.414 of the AB wave. The final movement is a price decline to point D, which is between 1.272 and 2.618 of the BC wave and 1.13 to 1.272 of the XA wave.
Point D : Serves as the key Potential Reversal Zone (PRZ).
Entry : A buy trade is initiated at point D, signaling the end of the corrective movement and the beginning of a price increase.
Price Targets :
61.8% retracement of the CD wave
Point A
Point C
1.272 and 1.618 extensions of the CD wave if resistance at point C is broken
Stop Loss : Placed slightly below point D.
🟣 Bearish Nen-Star Pattern
The bearish Nen-Star pattern starts with a price decrease from point X to point A, followed by a retracement to point B, which lies between 0.382 and 0.786 of the XA wave.
After this retracement, the price moves to point C, located between 1.13 and 1.414 of the AB wave. The final movement is a price increase to point D, which is between 1.272 and 2.618 of the BC wave and 1.13 to 1.272 of the XA wave.
Point D : Serves as the key Potential Reversal Zone (PRZ).
Entry : A sell trade is initiated at point D, signaling the end of the corrective movement and the beginning of a price decline.
Price Targets :
61.8% retracement of the CD wave
Point A
Point C
1.272 and 1.618 extensions of the CD wave if support at point C is broken
Stop Loss : Placed slightly above point D.
🔵 Setting
🟣 Logical Setting
ZigZag Pivot Period : You can adjust the period so that the harmonic patterns are adjusted according to the pivot period you want. This factor is the most important parameter in pattern recognition.
Show Valid Forma t: If this parameter is on "On" mode, only patterns will be displayed that they have exact format and no noise can be seen in them. If "Off" is, the patterns displayed that maybe are noisy and do not exactly correspond to the original pattern.
Show Formation Last Pivot Confirm : if Turned on, you can see this ability of patterns when their last pivot is formed. If this feature is off, it will see the patterns as soon as they are formed. The advantage of this option being clear is less formation of fielded patterns, and it is accompanied by the latest pattern seeing and a sharp reduction in reward to risk.
Period of Formation Last Pivot : Using this parameter you can determine that the last pivot is based on Pivot period.
🟣 Genaral Setting
Show : Enter "On" to display the template and "Off" to not display the template.
Color : Enter the desired color to draw the pattern in this parameter.
LineWidth : You can enter the number 1 or numbers higher than one to adjust the thickness of the drawing lines. This number must be an integer and increases with increasing thickness.
LabelSize : You can adjust the size of the labels by using the "size.auto", "size.tiny", "size.smal", "size.normal", "size.large" or "size.huge" entries.
🟣 Alert Setting
Alert : On / Off
Message Frequency : This string parameter defines the announcement frequency. Choices include: "All" (activates the alert every time the function is called), "Once Per Bar" (activates the alert only on the first call within the bar), and "Once Per Bar Close" (the alert is activated only by a call at the last script execution of the real-time bar upon closing). The default setting is "Once per Bar".
Show Alert Time by Time Zone : The date, hour, and minute you receive in alert messages can be based on any time zone you choose. For example, if you want New York time, you should enter "UTC-4". This input is set to the time zone "UTC" by default.
🔵 Conclusion
The Nen-Star Harmonic Pattern is a highly effective analytical tool in global financial markets, playing a crucial role in identifying reversal points and market trend changes. By leveraging Fibonacci principles and price structure, this pattern enables precise analysis across various assets, including stocks, cryptocurrencies, forex, and commodities.
Traders operating in global markets can use this pattern to identify high risk-to-reward trading opportunities. Its clear entry and exit points, defined Potential Reversal Zones (PRZ), and accurate price targets make it an excellent tool for risk management and profitability enhancement.
In the global context, the Nen-Star pattern is widely used by professional analysts in both advanced and emerging markets due to its versatility in analyzing long-term and short-term charts. Beyond trend prediction, it enhances trading strategies and optimizes investment decisions.
Combining this pattern with complementary tools such as volume analysis, technical indicators, and macroeconomic conditions can provide traders with deeper market insights, helping them capitalize on global opportunities.
Improved Trend Reconnaissance | JeffreyTimmermansImproved Trend Reconnaissance
The Improved Trend Reconnaissance indicator is a robust tool designed to help traders identify and follow trends while avoiding market noise. It is especially effective for capturing longer-term trends and sustained price movements over extended time periods. By leveraging smoothed trend analysis and volatility-based consolidation detection, this indicator provides clear and actionable insights for traders focusing on significant market trends.
What Does This Indicator Do?
At its core, this indicator calculates a Half Trend value and applies advanced smoothing techniques to emphasize longer-term trends. Additionally, it incorporates volatility analysis using the Average True Range (ATR) to detect periods of consolidation, where trend signals are muted to prevent false signals.
Key Components Explained
Half Trend Calculation:
This indicator determines a Half Trend value based on the relationship between the Exponential Moving Average (EMA) of closing prices and the highest highs and lowest lows over a specified range.
The trend is further smoothed to minimize short-term fluctuations, ensuring the focus remains on sustained price movements.
ATR-Based Consolidation Detection:
By comparing the range of price highs and lows to a multiple of ATR, the indicator detects consolidation zones where the market is range-bound. During these periods, trend signals are suppressed to avoid false positives.
Trend Visualization:
Bullish Trends: Highlighted in green with upward markers and optional trend-colored candles.
Bearish Trends: Highlighted in red with downward markers and optional trend-colored candles.
Designed for Longer-Term Trends:
The default settings are optimized to capture longer-term trends, making this indicator particularly valuable for traders looking to identify and follow substantial market movements over extended periods.
Key Features
Optimized for Capturing Longer Trends:
With the default settings, the indicator is tailored to identify and follow longer-term price trends, reducing noise from minor fluctuations. This makes it ideal for traders focused on significant trends and extended price movements.
Customizable Inputs:
Parameters such as trend range, smoothing length, ATR calculation period, and consolidation threshold are fully customizable.
Visual settings, including trend colors and signal sizes, can be adjusted for personalized trading needs.
Dynamic Signal Generation:
Bullish Signals: Generated when the smoothed Half Trend crosses upward and the market is trending.
Bearish Signals: Generated when the smoothed Half Trend crosses downward and the market is trending.
Alerts can notify traders in real time when these conditions occur.
Enhanced Visualization:
Candle coloring based on trend direction provides an immediate visual representation of market momentum.
Plotted trend lines and filled regions between them emphasize the current trend's strength and direction.
Real-Time Dashboard:
Displays essential information, including the current ticker, trend direction, and status (bullish or bearish), directly on the chart.
How to Use This Indicator
Identify Longer-Term Trends:
Use the smoothed Half Trend line and trend-colored candles to identify and follow significant price trends.
The default settings are specifically designed to focus on extended trends, making it easier to spot major market moves.
Avoid Noise in Consolidation:
Pay attention to the consolidation detection feature, which suppresses signals during range-bound market conditions, aka mean-reverting markets.
This ensures that signals generated are more reliable and actionable.
Confirm Trend Signals:
Use the visual markers (flags) and dashboard status to validate bullish or bearish trends before making trading decisions.
Set Alerts:
Set alerts for bullish or bearish signals to stay informed about key market movements without constantly monitoring the charts.
Adapt for Your Strategy:
While optimized for longer-term trends, the customizable settings allow you to adapt the indicator for shorter-term strategies if needed.
What Makes This Indicator Unique?
Focus on Longer-Term Trends:
Unlike many indicators that respond to short-term fluctuations, this tool is tailored for longer-term trend-following systems, ensuring that traders capture the most meaningful price movements.
Noise Reduction:
By combining smoothing techniques and ATR-based consolidation detection, the indicator reduces market noise and focuses on actionable insights.
Clear Visual Representation:
The combination of trend-colored candles, plotted lines, and dashboard information simplifies the analysis of complex market trends.
Customizability:
Fully adjustable parameters ensure the indicator meets the specific needs of a wide range of trading styles.
Real-Time Feedback:
Alerts and dashboard integration keep traders informed, enabling timely and well-informed decision-making.
The Improved Trend Reconnaissance indicator is an essential tool for traders looking to focus on longer-term trends and sustained market movements. With its default settings optimized for capturing significant trends over extended periods, it offers clarity, precision, and actionable insights for successful trend-following trading.
-Jeffrey
Machine Learning RSI Bands V3The Machine Learning RSI Bands V3 is a cutting-edge trading tool designed to provide actionable insights by combining the strength of machine learning with a traditional RSI framework. It adapts dynamically to changing market conditions, offering traders a robust, data-driven approach to identifying opportunities.
Let’s break down its functionality and the logic behind each input to give you a clear understanding of how it works and how you can use it effectively.
RSI Parameters RSI Source (rsisrc): Choose the data source for RSI calculation, such as the closing price. This allows you to focus on the specific price data that aligns with your trading strategy. RSI Length (rsilen): Set the number of periods used for RSI calculation. A shorter length makes the RSI more reactive to price changes, while a longer length smooths out volatility. These inputs allow you to customize the foundational RSI calculations, ensuring the indicator fits your style of trading.
Band Limits Lower Band Limit (lb): Defines the RSI value below which the market is considered oversold. Upper Band Limit (ub): Defines the RSI value above which the market is considered overbought. These settings give you control over the thresholds for market conditions. By adjusting the band limits, you can tailor the indicator to be more or less sensitive to market movements.
Sampling and Reaction Settings Target Reaction Size (l): Determines the number of bars used to define pivot points. Smaller values react to shorter-term price movements, while larger values focus on broader trends. Backtesting Reaction Size (btw): Sets the number of bars used to validate signal performance. This ensures signals are only considered valid if they perform consistently within the specified range. Data Format (version): Choose between Absolute (ignoring direction) and Directional (incorporating directional price changes). Sampling Method (sm): Select how the data is analyzed—options include Price Movement, Volume Movement, RSI Movement, Trend Movement, or a Hybrid approach. These settings empower you to refine how the indicator processes and interprets data, whether focusing on short-term price shifts or broader market trends.
Signal Settings Signal Confidence Method (cm): Choose between: Threshold: Signals must meet a confidence limit before being generated. Voting: Requires a majority of 5 signal components to confirm a trade. Confidence Limit (cl): Defines the confidence threshold for generating signals when using the Threshold method. Votes Needed (vn): Sets the number of votes required to confirm a trade when using the Voting method. Use All Outputs (fm): If enabled, signals are generated without filtering, providing an unfiltered view of potential opportunities. This section offers a balance between precision and flexibility, enabling you to control the rigor applied to signal generation.
How It Works
The script uses machine learning models to adaptively calculate dynamic RSI bands. These bands adjust based on market conditions, providing a more responsive and nuanced interpretation of overbought and oversold levels.
Dynamic Bands: The lower and upper RSI bands are recalibrated using machine learning to reflect current market conditions. Signals: Long and short signals are generated when RSI crosses these bands, with additional filters applied based on your chosen confidence method and sampling settings. Transparency: Real-time success rates and profit factors are displayed on the chart, giving you clear feedback on the indicator's performance.
Why Use Machine Learning RSI Bands V3?
This indicator is built for traders who want more than static thresholds and generic signals. It offers:
Adaptability: Machine learning dynamically adjusts the indicator to market conditions. Customizability: Each input serves a specific purpose, giving you full control over its behavior. Accountability: With built-in performance metrics, you always know how the tool is performing.
This is a tool designed for those who value precision and adaptability in trading.
Fibonacci Trading Strategy (Auto Levels)How It Works
Swing Highs and Lows Detection:
The script identifies the highest high and lowest low over a specified lookback period (default: 50 candles). These points are used as the basis for Fibonacci calculations.
Fibonacci Levels:
Fibonacci retracement levels: 0%, 38.2%, 50%, 61.8%, 78.6%, and 100%.
Fibonacci extension levels: 127.2%, 161.8%, 200%, 261.8%, and 361.8%.
Each level is plotted on the chart with a specific color and labeled with the corresponding price.
Entry Zones:
Pullback Area: Between the 50% and 61.8% retracement levels. This area is highlighted in green, indicating a potential entry for conservative traders.
Full Margin Area: Between the 61.8% and 78.6% retracement levels. This area is highlighted in red, suggesting a higher-risk entry for aggressive traders.
Stop Loss (SL):
The Stop Loss is placed at the 78.6% Fibonacci retracement level. A dotted red line is drawn at this level to provide a visual reference for risk management.
Entry labels include the Stop Loss price for clarity.
Take Profit (TP) Levels:
Multiple take-profit targets are identified using Fibonacci extension levels (127.2%, 161.8%, 200%, 261.8%, and 361.8%).
Each level is labeled with the price and target percentage.
Visual Aids:
The script dynamically labels each Fibonacci level with its corresponding price.
Entry points (Pullback and Full Margin) are marked with clear labels, including the recommended Stop Loss.
Background highlights help distinguish the Pullback and Full Margin areas.
Strategy Highlights
Risk Management:
Incorporates a well-defined Stop Loss at the 78.6% level to limit downside risk.
Multiple take-profit levels help traders scale out of positions gradually.
Automation:
Automatically recalculates levels when new swing highs or lows are detected, ensuring accuracy in dynamic markets.
Customizability:
Users can adjust the lookback period to suit different timeframes or trading styles.
Clarity:
Clean visuals and detailed labels ensure the strategy is easy to interpret and apply.
When to Use
The strategy is suitable for trend-following traders looking to enter during pullbacks in an established trend.
It works best in trending markets where Fibonacci levels often act as strong support or resistance.
Example Scenario
Bullish Setup:
Price retraces to the 50%-61.8% area (Pullback Area) after a swing high.
A buy order is placed in this zone, with the Stop Loss at the 78.6% level.
Profit targets are set at the 127.2%, 161.8%, and higher Fibonacci extensions.
Bearish Setup:
In a downtrend, price retraces upward to the 50%-61.8% zone.
A sell order is placed, with the Stop Loss at the 78.6% level and take-profit levels below.
STH MVRV + Double MA | JeffreyTimmermansSTH MVRV + Double MA
This indicator combines blockchain analytics and technical analysis to provide traders with insights into market trends and cycles. At its core, it utilizes the Short-Term Holder (STH) Market Value to Realized Value (MVRV) ratio, a powerful metric in blockchain analysis, alongside Moving Averages (MA's) to offer a comprehensive view of market dynamics.
What Is the STH-MVRV Ratio?
The STH-MVRV ratio is a blockchain-based metric that compares the market value of Bitcoin held by short-term holders to its realized value.
Market Value: The current price of Bitcoin multiplied by the number of coins held by short-term holders.
Realized Value : The average price at which short-term holders acquired their Bitcoin, based on blockchain transaction data.
This ratio provides a unique perspective on market sentiment:
Above 1: Short-term holders, on average, are in profit. This often signals a bullish market.
Below 1: Short-term holders are, on average, at a loss, which can indicate bearish sentiment.
The STH-MVRV is particularly useful for identifying potential market tops or bottoms, as short-term holder behavior often reflects broader market trends.
How Does This Indicator Work?
The STH MVRV + Double MA indicator builds on the STH-MVRV ratio by integrating it with additional data and tools to enhance its practical use:
STH-MVRV Variations:
STH-MVRV (MVRV): The traditional ratio as described above.
Price-Based MVRV: A variation using Bitcoin price to measure similar dynamics.
Average MVRV: A hybrid metric combining the two for balanced insights.
Dynamic Moving Averages (MA's):
Primary SMA (STH-MVRV): Smooths out fluctuations in the STH-MVRV ratio over a default period of 155 days.
Extra MA: A faster-moving average for shorter-term trends (default: 50 days).
Second MA: A slower-moving average for longer-term trends (default: 200 days).
Visual and Alert Features:
Color-coded plots to highlight bullish or bearish conditions.
Alerts for key crossover events, such as when STH-MVRV crosses above/below critical levels or Moving Averages.
Key Features
STH-MVRV as a Sentiment Gauge:
Use the ratio to determine whether short-term holders are profiting (bullish) or losing (bearish).
Moving Average Integration:
Identify trends and reversals with customizable Moving Averages.
Crossovers between MA's and the STH-MVRV indicate actionable trading signals.
Customizable Parameters:
Tailor SMA and MA settings to align with your strategy.
Adjust colors and labels for clearer insights.
Real-Time Updates:
Dynamic labels display the current values of STH-MVRV, Price-based MVRV, or the Average, providing instant clarity.
How to Use This Indicator
Gauge Market Sentiment:
Use the STH-MVRV to understand whether the market is overvalued or undervalued based on short-term holder behavior.
Trend Identification with MA's:
Monitor crossovers between STH-MVRV and Moving Averages for potential buy or sell signals.
Analyze Market Cycles:
Use the Average MVRV to gain a broader view of market conditions, balancing short-term and long-term insights.
What Makes This Indicator Unique?
In-Depth Blockchain Metric: Builds directly on the STH-MVRV ratio, a key metric in blockchain analysis.
Integrated Analysis: Combines the STH-MVRV with Moving Averages for enhanced functionality.
Customizability and Practicality: Users can adapt the settings to fit their unique trading style, ensuring the tool is both flexible and powerful.
This combination of blockchain insights and technical tools makes the STH MVRV + Double MA indicator an essential addition to any trader’s arsenal. Use it to stay ahead of market trends and make informed decisions with confidence.
-Jeffrey
Strategy Development Environment [BerlinCode42]Happy Trade,
Intro
What is New
Algebraic/Boolean Equation
Instruction Set for The Algebraic/Boolean Equation
Example
Usage
Settings Menu
Declaration for Tradingview House Rules on Script Publishing
Disclaimer
Conclusion
1. Intro
This is a rich equipped fork of my previous "Backtest any Indicator v5". And serves as the fitting backtester and trade strategy creation tool for my upcoming ANN Indicators (artificial neural network).
As the previous version this script has no trade signal generating code. The trade signals comes in by the five user settable input slots where the user plug-in external indicators. The final trade siganls go long etc are defined by a algebraic/boolean equation typed in as text in 4 terminals as shown in Image 0 . With this algebraic/boolean equations input the user can setup any trade logic as complex and fast and easy as never seen before here on TradingView.
Image 0
2. What is new
Input algebraic/boolean equations in text-form for go long, go short, exit long & exit short
Five input slots for external indicator signals
Equation tester
User settable signal delay for enter and exit trades
User selectable alternating trades filter
User settable exit long = enter short
Intrabar or trade only on bar closing
Time filter with duration input
User settable UTC Adjustment
Long and short trades possible
Two Take Profits with quantity setting
Trailing Stop
Webhook connection
3. Algebraic/Boolean Equation
This is where the magic happens. Unlike other backtesters that rely on drop-down menus to define trade signal equations—thus limiting the number of input signals and the complexity of logic—this script uses a string interpreter to solve equations. With this, you can develop your trade logic equations and add signals or conditions simply by writing them down in algebraic/boolean form.
The instruction set for this interpreter includes not only external input signals but also several internal values. These include BarTime, BarIndex, Open, High, Low, Close, True Range, Minimal Tick, Volume, and a signal that indicates whether there is an open trade (long, short, or none). You can also reference the values of past bars for all these inputs and, of course, use constant values in your equations. There is a sad limitation: Only one past bar value per equation is practicable. If you use more, errors can occur. It seems to be caused by the pipe line architecture of the parallel computing. In any attempt to solve this issue an older function call result was hand over.
The implemented functions cover a wide range of algebraic and boolean operations. A boolean "true" is represented by all values greater than zero, while "false" is represented by zero or values less than zero.
4. Instruction set for the Algebraic/Boolean Equation
There are functions that accept either two input values or one input value. The general form is (XandY) or (notX), where X and Y can be any input slot, predefined value, constant, or another sub-equation. Functions are always written in lowercase, while input slots and predefined values use uppercase letters.
Each sub-equation must be enclosed in parentheses, e.g., (A+B). Without proper use of parentheses, the interpreter cannot determine which function to calculate first. Negative constants must be expressed by subtracting from zero (e.g., (0-3.14)), so careful attention is required.
Here are some examples that demonstrate both incorrect and correct notations:
incorrect correct
(A+B*C) (A+(B*C))
(A+B+D+E) (A+(B+(D+E)))
(-20>A) ((0-20)>A)
(A*-B) (A*(0-B))
(AnotB) (Aand(notB))
ABS(a-b) (abs(A-B))
The correct usage ensures the interpreter calculates in the intended order.
And here comes the complete Instruction Set:
Addition: (A+B)
Subtraction: (A-B)
Multiplication: (A*B)
Division: (A/B)
Absolut value: (absA)
Power of: (A^B)
Natural Logarithm: (logA)
Lowest value of Low of last x bars: (lotx)
Highest value of High of last x bars: (hotx)
Modulo, Remainder of a Division: (A%B)
Round: (rndA)
round to ceil: (ceiA)
Round to floor: (floA)
Round to next minimal tick: (mitA)
EMA of A of last 3 bars: (e03A)
EMA of A of last 7 bars: (e07A)
EMA of A of last 10 bars: (e10A)
EMA of A of last 20 bars: (e20A)
EMA of A of last 50 bars: (e50A)
Smaller then: (AB)
Equal to: (A==B)
Unequal to: (A!=B)
And: (AandB)
Or: (AorB)
Exclusive Or: (AxorB)
Not: (notA)
Past bar value: (A ) ,whereby x can be 1,2,3,...,barIndex-1
Bar time: (T)
Bar index: (I)
Opening Price of Bar: (O)
Highest Price of Bar: (H)
Lowest Price of Bar: (L)
Closing Price of Bar: (C)
Min tick value for the current symbol: (K)
Trade Volume: (V)
True Range: (R)
Is Money invested: (M) ,Long position: M=1,
Short position: M=-1,
No position: M=0
Reminder: if you wanna replace A or B above don't forget the parentheses. So if you have (logA) and wanna replace A with D+F so the correct replacement would be (log(D+F)).
In the following there are some examples of popular bar patterns and useful filters:
Doji: ((abs(O-C))<(10*K))and((H-L)>(100*K))
green Hammer: (((H-C)<(5000*K))and(((O-L)/2)>(abs(O-C)))
Up trend: (C>(e10H))
Down trend: (C<(e10L))
cool down 7 bars: (( any buy condition )and((e07(absM))==0))
possible Pivot High: (H==(hot30))and((CC))
possible Pivot Low: (L==(lot30))and((C>H )or(O0)), goShort ((A>0)and((A )<0)), Enter Signal delay=0, Exit Signal delay=0, Alternate Trades=true
take profit 1 =0.4% (30%), take profit 2 =0.7%, trailing stop loss=0.2%, intrabar, start capital=1000$, qty=5%, fee=0.05%, no Session Filter
Image 1
6. Usage
First you need to attach some signals from external Indicators. In the example above we use the Stochastic RSI indicator from TradingView. Load the Stochastic RSI indicator to the chart. Then you go to the settings menu of this script, choose in the drop-down menu of Input A the signal .
In case you wanna use a signal which is not in the drop-down menu of Input A do the following:
1) You need to know the name of the boolean (or integer) variable of your indicator which hold the desired signal. Lets say that this boolean variable is called BUY. If this BUY variable is not plotted on the chart you simply add the following code line at the end of your pine script.
For boolean (true/false) BUY variables use this:
plot(BUY ? 1:0,'Your buy condition hold in that variable BUY',display = display.data_window)
And in case your script's BUY variable is an integer or float then use instate the following code line:
plot(BUY ,'Your buy condition hold in that variable BUY',display = display.data_window)
2) Probably the name of this BUY variable in your indicator is not BUY. Simply replace in the code line above the BUY with the name of your script's trade condition variable.
3) Do the same procedure for your SELL variable. Then save your changed Indicator script.
4) Then add the changed Indicator script from step before and this backtester script to the chart ...
5) and go to the settings of it. Choose under "Settings -> Input A " your Indicator. So in the example above choose .
The form is usually: ' : BUY'. Then you see something like Image 1
6) Decide about each trade logic for Go Long and Go Short . In this Example we use for GoLong if "Stoch RSI: K" is smaller then 20. The "Stoch RSI: K" we already loaded it in input A. So we set under Go Long (A<20) and set Enter Signal Delay to 0.
Now we setup Go Short if "Stoch RSI: K" is bigger then 80. So we set under Go Short A>80. Enter Signal Delay is already set.
7) For the Exit conditions you can choose (trailing) Stop loss or Take Profit or Exit by Indicator Signal. What ever comes first triggers the exit. If you like to use an EMA Indicator for the Exit by Indicator just load it in a free input slot B, D, E, F or use the inbuild EMA. For this example we use the inbuild EMA of the last 7 values of close. It is called by the following equation: (e07C). So to exit a long trade when the close price crossunder this EMA you have to type in Exit Long ((e07C)>C). For exit a short trade enter in Exit Short ((e07C)<C).
You can choose detailed time- and session filters. You can setup two take profit levels with quantity and stop loss, trailing, initial capital, quantity per trade and set the exchange fees. You get an overall result table and even a detailed, scroll-able table with all trades.
Image 2
In the Image 2 you see the provided info tables about all Trades and the Result Summary. Further more every trade is marked by a background color, labels and levels. An opening Label with the trade direction and trade number. A closing Label again with the trade number, the trade profit in %, the trade gain in $ and the total amount of $ after all past trades. A green line for each take profit levels and an orange line for the (trail) stop loss. This summary table down left gives you an insign about how good or not so good the trade strategy is and with the trade list you can find those trade which should be avoided. Found those bad trades on the chart by the time or trade number. By seeing a big number of bad trades you may find a pattern and can formulate conditions to avoid those bad trades. Those new conditions you can easily add to the equations for enter or exit trades.
Now you have a backtest with the oppotunity to develope and envolve your trading strategy more and more. And for any iteration from general to detailed you can do it with this backtester. You can add more and more filter signals or may change the setting of your Indicator to the best results and setup the following strategy settings like Time- and Session Filter, Stop Loss, Take Profit etc. With it you find a profitable strategy and it's settings.
7. Settings Menu
In the settings menu you will find the following high-lighted sections. Most of the settings have a attention mark on their right side. Move over it with the cursor to read specific explanation.
Input Signals: This are five input slots A, B, D, E & F which you can load up with your preferred Indicators.
Algebraic Equation for the Trade Signals: Here you setup the definitions for Go Long , Go Short , Ex Long & Ex Short . As shown in Image 3 you can combine the input slots A, B, D, E, F with predefined Variables O, H, L, C, T, I, V, K, M, R or any constant value with the in-build function in the instruction set.
Image 3
Additionally, you have the option to delay entry and exit signals. This feature is particularly useful when trade signals exhibit noise and require smoothing.
You can also enable the script to perform alternating trading . In this mode, trades alternate sequentially—after a long trade, a short trade follows, and then another long trade, and so on.
Image 4
As shown in Image 4 , you can configure the script so that an "exit by signal" also acts as the next entry in the opposite trade direction. To enable this, check the option Exit = Enter Next and set the exit condition as the opposite of the entry condition. With this setting, only one occurrence of the signal is needed to trigger both the exit and the new entry, making the transition seamless.
Equation Tester: Each equation is assigned a checkmark and a color. Activate one like in Image 5 and the chart will highlight bars with a colored background where the corresponding equation result is greater than zero (interpreted as true). At the last bar, a label is displayed showing each equation’s result value. This feature allows you to build your equations and test sub-equations to ensure their results are correct.
Image 5
Backtest Results: Check mark the List of Trades to see any single trade with their stats. If there are more trades than can fit in the list, you can scroll down by decreasing the Scroll value.
Timezone Adjustment: In case you wanna use an Chart-UTC that differs from the time scale you can activate Timezone Adjustment . Then you have to setup your location UTC correctly! The Exchange UTC will be set in most cases automatically. Known Exchanges include Amsterdam, Chicago, New_York, Los_Angeles, Calcutta, Colombo, Moscow, St_Petersburg, Tokyo, Shanghai, Hongkong, Berlin, London, Paris, Madrid. Only if you have other exchanges you need to setup it by hand.
Time Filter: You can set a Start time or deactivate it by leave it unhooked. The same with End Time and Duration Days . Duration Days can also count from End time in case you deactivate Start time.
Session Filter: Here, you can choose to activate trading on a weekly basis, specifying which days of the week trading is allowed and which are excluded. Additionally, you can configure trading on a daily basis, setting the start and end times for when trades are permitted. If activated, no new trades will be initiated outside the defined times and sessions.
Long & Short: Here you can enable Longs or Shorts or both trades.
TP & SL Settings: Take Profit 1&2 set the target prices of any trade in relation to the entry price. The TP1 exit a part of the position defined by the quantity value. Stop Loss set the price to step out when a trade goes the wrong direction. You can activate also a trailing SL.
Additionally, you can specify whether trades should be executed intrabar or at the bar's closing.
Hedging: The Hedging is basic as shown in the following Image 6 and serves as a catch if price moves fast in the wrong direction.
Image 6
You can activate a hedging mechanism, which opens a trade in the opposite direction if the price moves x% against the entry price. If both the Stop Loss and Hedging are triggered within the same bar, the hedging action will always take precedence.
Invest Settings: Here, you can set the initial amount of cash to start with. The Quantity Percentage determines how much of the available cash is allocated to each trade, while the Fee Percentage specifies the trading fee applied to both opening and closing positions.
Webhooks: Here, you configure the License ID and the Comment. This is particularly useful if you plan to use multiple instances of the script, ensuring the webhooks target the correct positions. The Take Profit and Stop Loss values are displayed as prices.
8. Declaration for Tradingview House Rules on Script Publishing
This Backtester also serves as Strategy Development Tool by offering the user a fast and easy opportunity to test, enhance and manipulate the definitions for enter and exit trades. The unique feature "algebraic/boolean equation input" provides users with a significant edge over other backtest scripts. Unlike any other backtesting tool available with few drop-down menus for enter the equation, this script allows users to define an extensive range of trade equation definitions without setup of numerous specific parameters. This is reached by four terminals where the user type in the equation as text. Those equations in text-form are send intern to a context-depending touring machine that interprets the string. So with this tool, users can implement their trading ideas—even those involving complex definitions for trade entries and exits based on huge number of variables and indicators—without hiring a developer.
This script is closed-source and invite-only to support and compensate for over a year of development work. Unlike traditional backtest scripts, this one does not rely on TradingView's strategy functions. Instead, it is designed as an indicator, utilizing TradingView's "Indicator-on-Indicator" functionality.
9. Disclaimer
Trading is risky, and traders do lose money, eventually all. This script is for informational and educational purposes only. All content should be considered hypothetical, selected post-factum to demonstrate the upcoming ANN scripts and is not to be construed as financial advice. Decisions to buy, sell, hold, or trade in securities, commodities, and other investments involve risk and are best made based on the advice of qualified financial professionals. Past performance does not guarantee future results. Using this script on your own risk. This script may have bugs and I declare don't be responsible for any losses.
10. Conclusion
Now it’s your turn! Connect your promising Artificial Neural Networks (ANN) and standard indicators to this feature-rich Backtest/Strategy script. This tool allows you to quickly evaluate how well your indicators perform in trading scenarios and easily compare different trading logics defined by algebraic/boolean equations. You can refine your trading strategy step by step without needing a coder. Let it incorporate numerous variables and indicators—simply write the algebraic/boolean equations for trade entries and exits directly into the script’s settings.
Additionally, you can utilize the Time Filter to identify the market conditions where your setups perform best—or where they fall short. The Session Filter helps you isolate recurring favorable conditions to optimize your strategy further. Once you find a promising configuration, you can set up alerts to send webhooks directly. Configure all parameters, test and validate them in paper trading, and if results align with your expectations, deploy the script as your trading bit.
Cheers
Volatility IndicatorThe volatility indicator presented here is based on multiple volatility indices that reflect the market’s expectation of future price fluctuations across different asset classes, including equities, commodities, and currencies. These indices serve as valuable tools for traders and analysts seeking to anticipate potential market movements, as volatility is a key factor influencing asset prices and market dynamics (Bollerslev, 1986).
Volatility, defined as the magnitude of price changes, is often regarded as a measure of market uncertainty or risk. Financial markets exhibit periods of heightened volatility that may precede significant price movements, whether upward or downward (Christoffersen, 1998). The indicator presented in this script tracks several key volatility indices, including the VIX (S&P 500), GVZ (Gold), OVX (Crude Oil), and others, to help identify periods of increased uncertainty that could signal potential market turning points.
Volatility Indices and Their Relevance
Volatility indices like the VIX are considered “fear gauges” as they reflect the market’s expectation of future volatility derived from the pricing of options. A rising VIX typically signals increasing investor uncertainty and fear, which often precedes market corrections or significant price movements. In contrast, a falling VIX may suggest complacency or confidence in continued market stability (Whaley, 2000).
The other volatility indices incorporated in the indicator script, such as the GVZ (Gold Volatility Index) and OVX (Oil Volatility Index), capture the market’s perception of volatility in specific asset classes. For instance, GVZ reflects market expectations for volatility in the gold market, which can be influenced by factors such as geopolitical instability, inflation expectations, and changes in investor sentiment toward safe-haven assets. Similarly, OVX tracks the implied volatility of crude oil options, which is a crucial factor for predicting price movements in energy markets, often driven by geopolitical events, OPEC decisions, and supply-demand imbalances (Pindyck, 2004).
Using the Indicator to Identify Market Movements
The volatility indicator alerts traders when specific volatility indices exceed a defined threshold, which may signal a change in market sentiment or an upcoming price movement. These thresholds, set by the user, are typically based on historical levels of volatility that have preceded significant market changes. When a volatility index exceeds this threshold, it suggests that market participants expect greater uncertainty, which often correlates with increased price volatility and the possibility of a trend reversal.
For example, if the VIX exceeds a pre-determined level (e.g., 30), it could indicate that investors are anticipating heightened volatility in the equity markets, potentially signaling a downturn or correction in the broader market. On the other hand, if the OVX rises significantly, it could point to an upcoming sharp movement in crude oil prices, driven by changing market expectations about supply, demand, or geopolitical risks (Geman, 2005).
Practical Application
To effectively use this volatility indicator in market analysis, traders should monitor the alert signals generated when any of the volatility indices surpass their thresholds. This can be used to identify periods of market uncertainty or potential market turning points across different sectors, including equities, commodities, and currencies. The indicator can help traders prepare for increased price movements, adjust their risk management strategies, or even take advantage of anticipated price swings through options trading or volatility-based strategies (Black & Scholes, 1973).
Traders may also use this indicator in conjunction with other technical analysis tools to validate the potential for significant market movements. For example, if the VIX exceeds its threshold and the market is simultaneously approaching a critical technical support or resistance level, the trader might consider entering a position that capitalizes on the anticipated price breakout or reversal.
Conclusion
This volatility indicator is a robust tool for identifying market conditions that are conducive to significant price movements. By tracking the behavior of key volatility indices, traders can gain insights into the market’s expectations of future price fluctuations, enabling them to make more informed decisions regarding market entries and exits. Understanding and monitoring volatility can be particularly valuable during times of heightened uncertainty, as changes in volatility often precede substantial shifts in market direction (French et al., 1987).
References
• Bollerslev, T. (1986). Generalized Autoregressive Conditional Heteroskedasticity. Journal of Econometrics, 31(3), 307-327.
• Christoffersen, P. F. (1998). Evaluating Interval Forecasts. International Economic Review, 39(4), 841-862.
• Whaley, R. E. (2000). Derivatives on Market Volatility. Journal of Derivatives, 7(4), 71-82.
• Pindyck, R. S. (2004). Volatility and the Pricing of Commodity Derivatives. Journal of Futures Markets, 24(11), 973-987.
• Geman, H. (2005). Commodities and Commodity Derivatives: Modeling and Pricing for Agriculturals, Metals and Energy. John Wiley & Sons.
• Black, F., & Scholes, M. (1973). The Pricing of Options and Corporate Liabilities. Journal of Political Economy, 81(3), 637-654.
• French, K. R., Schwert, G. W., & Stambaugh, R. F. (1987). Expected Stock Returns and Volatility. Journal of Financial Economics, 19(1), 3-29.
Z-Score Financial Market Conditions | JeffreyTimmermansZ-Score Financial Market Conditions
The Z-Score Financial Market Conditions indicator is a cutting-edge tool for measuring financial market stress and relaxation by combining eight critical financial metrics into a single composite Z-score. This dynamic indicator provides traders and analysts with actionable insights into the overall state of the financial markets, enabling informed decision-making across various trading and investment systems.
Purpose of the Indicator
This indicator serves as a comprehensive gauge of financial market conditions, offering a clear visualization of whether the markets are in a state of stress (elevated risks) or relaxation (normalized conditions). The Z-Score Financial Market Conditions tool is particularly effective for:
Macro-Level Risk Assessment: Identifying periods of high market stress or calmness.
Trend Following Systems: Gauging the market's underlying conditions to validate trends.
Mean Reversion Strategies: Using extreme Z-score levels to detect potential reversals.
Portfolio Risk Management: Adjusting asset exposure based on market-wide financial conditions.
This indicator works exclusively on the 1-day timeframe, as it is calibrated to analyze daily changes in the financial metrics that drive market behavior.
The Eight Key Components and Their Importance
The composite Z-score integrates the Z-scores of the following eight financial metrics. These metrics have been selected for their complementary insights into various aspects of financial market conditions:
VIX (S&P 500 Volatility Index)
Reflects implied volatility in the U.S. equity market.
High VIX values indicate increased uncertainty and risk aversion among market participants.
MOVE (US Treasury Bond Volatility Index)
Captures volatility in U.S. Treasury bonds.
Essential for understanding risk in fixed-income markets, which significantly impact broader economic conditions.
ICE BofA High Yield Option Adjusted Spread (BAMLH0A0HYM2)
Measures the risk premium for high-yield corporate bonds.
Rising spreads suggest increased credit risk and potential economic stress.
ICE BofA Corporate Index Option Adjusted Spread (BAMLC0A0CM)
Tracks credit spreads in the investment-grade bond market.
Helps evaluate the health of higher-quality corporate debt, a key indicator of financial stability.
ICE BofA US High Yield Index Spread (BAMLH0A0HYM2)
Focuses on high-yield U.S. corporate bonds.
Provides localized insights into U.S. credit conditions and risk levels.
CDS (Credit Default Swap Spreads)
Measures the cost of insuring against bond defaults.
Rising CDS spreads signal growing concern over creditworthiness, often a leading indicator of financial stress.
Global Bond Spread (AGG)
Represents global fixed-income spreads.
Offers a broader perspective on international financial conditions beyond the U.S. market.
TED Spread (Treasury-EuroDollar Spread)
The difference between interbank lending rates and short-term U.S. Treasury yields.
Widely regarded as an indicator of systemic risk in the banking sector.
Features and Improvements
This script builds upon the original concept by introducing advanced features to enhance its precision and usability:
Lookback Period Adjustment
A customizable lookback period for Z-score calculations (default: 160 days).
Allows for greater flexibility in adapting to different market conditions.
Moving Average (MA) Smoothing
Optional smoothing of Z-scores using an exponential moving average (EMA) for enhanced clarity.
Default smoothing length: 8 days.
Individual Component Visibility
Plots for individual Z-scores can be enabled or disabled to focus on specific metrics.
Dynamic Background Coloring
Visual cues to indicate bullish (green) or bearish (red) financial conditions based on the composite Z-score.
Custom Inputs
Toggle on/off for each financial metric to tailor the indicator to specific use cases.
Customizable parameters for smoothing and moving averages.
Applications
This indicator is versatile and can be effectively used in various trading systems and strategies:
Long-Term Investment Decision-Making: Assess macroeconomic trends for portfolio rebalancing.
Systematic Trading: Incorporate market conditions into algorithmic models to enhance robustness.
Volatility-Based Strategies: Use Z-score fluctuations to anticipate periods of market turbulence or calm.
Credits
This indicator was inspired by and builds upon the work of TomasOnMarkets . While incorporating significant enhancements, it acknowledges the foundational concepts provided by this original source. Thank you for sharing your input on this important indicator. We are honored to use it and to further improve upon it.
-Jeffrey
Follow Through Day (FTD) + Sweep [TrendX_]The Follow Through Day (FTD) + Sweep indicator is a Trend-following tool mixing William O'Neil's original FTD concept and Liquidity concept. This indicator helps you identify potential subsequent bullish trends with greater precision by combining volume analysis, price action, and liquidity concepts.
💎 FEATURES
Follow Through Day Candle (FTD Candle)
The FTD, pioneered by William O'Neil, serves as a reliable signal for identifying the beginning of new bull markets. It's particularly valuable because it combines multiple market factors - price action, volume, and timing - to confirm genuine market reversals rather than temporary bounces.
The power of the FTD lies in its ability to distinguish between ordinary market fluctuations and significant trend changes. By requiring specific criteria to be met across multiple sessions, it helps filter out false signals and identifies high-probability reversal points where institutional investors are likely beginning to accumulate positions.
Sweep Area
The Sweep area feature enhances the traditional FTD concept by incorporating modern liquidity analysis. This overlay identifies zones where large market participants are likely to trigger stop losses before continuing the trend. These areas often represent optimal entry points for traders looking to join the new uptrend with reduced risk.
🔎 BREAKDOWN
FTD Candle
The FTD formation process occurs in two distinct phases: Setup and Completion.
Setup Phase
Strong Market Decline
The market must first experience a significant downtrend
This selling pressure helps clear out weak hands and creates oversold conditions
The decline creates the potential energy for a powerful reversal
First Recovery Session
Marks the initial sign of buying pressure emerging
Often characterized by a strong reversal candle
Represents the first indication that selling pressure may be exhausting
Recovery Confirmation
The second and third days must maintain prices above the new pivot low
This consolidation period helps confirm the validity of the initial bounce
Shows that sellers are no longer in control of price action
Completion Phase:
Supply Test Session
Low volume indicates diminishing selling pressure
Price remains above the pivot low
Creates the foundation for institutional buyers to begin accumulating
Breakout Day
Price increase exceeds average profit of bullish candles
Volume increases by at least 15% compared to previous session
Shows strong institutional commitment to the new uptrend
Timing Window
Must occur between the 4th and 8th candle after First Recovery Session
This specific timing helps confirm the sustainability of the reversal
Based on O'Neil's research of historical market bottoms
FTD Sweep
The Post-FTD Phase introduces the Sweep concept, which is crucial for understanding how large market participants operate. This feature leverages the liquidity concept because institutional traders often need to trigger stop losses to accumulate larger positions at better prices. This helps:
Create liquidity pools for large position entries
Shake out weak hands before continuing the trend
Test the strength of the new trend by absorbing selling pressure
⚙️ USAGE
Sweep + TP & SL Strategy
Example: BTCUSDT (1D) - Replay back to 9th November 2024
After an FTD candle forms, traders can adopt a systematic approach to enhance their trading strategy. First, they should determine the swing range and convert the post-FTD zone into concrete stop loss and take profit levels, which are based on the price action during the FTD formation. Next, traders should wait for a sweep formation, as this indicates that institutional players are accumulating positions. A quick price rejection from the sweep level should be observed before executing an entry.
The reasoning behind this strategy is rooted in market microstructure. By waiting for the sweep, traders position themselves alongside institutional players who need to build large positions without causing adverse price movement. The sweep creates the liquidity they need, and the subsequent move often represents the true trend continuation.
DISCLAIMER
This indicator is not financial advice, it can only help traders make better decisions. There are many factors and uncertainties that can affect the outcome of any endeavor, and no one can guarantee or predict with certainty what will occur. Therefore, one should always exercise caution and judgment when making decisions based on past performance.
