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
Adaptive Sentiment-Volume MomentumThis is a simple breakout approach using ATR bands and an EMA filter. Test this strategy and let me know how it performs!
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.
AVP 259 alertsits a mixture of indicators that merges the famous indicators in one single form to easily get explained with their study and mastery
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.
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!
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.
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.
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.
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.
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.
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.
EMA Crossover Strategy with Take Profit and Candle HighlightingStrategy Overview:
This strategy is based on the Exponential Moving Averages (EMA), specifically the EMA 20 and EMA 50. It takes advantage of EMA crossovers to identify potential trend reversals and uses multiple take-profit levels and a stop-loss for risk management.
Key Components:
EMA Crossover Signals:
Buy Signal (Uptrend): A buy signal is generated when the EMA 20 crosses above the EMA 50, signaling the start of a potential uptrend.
Sell Signal (Downtrend): A sell signal is generated when the EMA 20 crosses below the EMA 50, signaling the start of a potential downtrend.
Take Profit Levels:
Once a buy or sell signal is triggered, the strategy calculates multiple take-profit levels based on the range of the previous candle. The user can define multipliers for each take-profit level.
Take Profit 1 (TP1): 50% of the previous candle's range above or below the entry price.
Take Profit 2 (TP2): 100% of the previous candle's range above or below the entry price.
Take Profit 3 (TP3): 150% of the previous candle's range above or below the entry price.
Take Profit 4 (TP4): 200% of the previous candle's range above or below the entry price.
These levels are adjusted dynamically based on the previous candle's high and low, so they adapt to changing market conditions.
Stop Loss:
A stop-loss is set to manage risk. The default stop-loss is 3% from the entry price, but this can be adjusted in the settings. The stop-loss is triggered if the price moves against the position by this amount.
Trend Direction Highlighting:
The strategy highlights the bars (candles) with colors:
Green bars indicate an uptrend (when EMA 20 crosses above EMA 50).
Red bars indicate a downtrend (when EMA 20 crosses below EMA 50).
These visual cues help users easily identify the market direction.
Strategy Entries and Exits:
Entries: The strategy enters a long (buy) position when the EMA 20 crosses above the EMA 50 and a short (sell) position when the EMA 20 crosses below the EMA 50.
Exits: The strategy exits the positions at any of the defined take-profit levels or the stop-loss. Multiple exit levels provide opportunities to take profit progressively as the price moves in the favorable direction.
Entry and Exit Conditions in Detail:
Buy Entry Condition (Uptrend):
A buy position is opened when EMA 20 crosses above EMA 50, signaling the start of an uptrend.
The strategy calculates take-profit levels above the entry price based on the previous bar's range (high-low) and the multipliers for TP1, TP2, TP3, and TP4.
Sell Entry Condition (Downtrend):
A sell position is opened when EMA 20 crosses below EMA 50, signaling the start of a downtrend.
The strategy calculates take-profit levels below the entry price, similarly based on the previous bar's range.
Exit Conditions:
Take Profit: The strategy attempts to exit the position at one of the take-profit levels (TP1, TP2, TP3, or TP4). If the price reaches any of these levels, the position is closed.
Stop Loss: The strategy also has a stop-loss set at a default value (3% below the entry for long trades, and 3% above for short trades). The stop-loss helps to protect the position from significant losses.
Backtesting and Performance Metrics:
The strategy can be backtested using TradingView's Strategy Tester. The results will show how the strategy would have performed historically, including key metrics like:
Net Profit
Max Drawdown
Win Rate
Profit Factor
Average Trade Duration
These performance metrics can help users assess the strategy's effectiveness over historical periods and optimize the input parameters (e.g., multipliers, stop-loss level).
Customization:
The strategy allows for the adjustment of several key input values via the settings panel:
Take Profit Multipliers: Users can customize the multipliers for each take-profit level (TP1, TP2, TP3, TP4).
Stop Loss Percentage: The user can also adjust the stop-loss percentage to a custom value.
EMA Periods: The default periods for the EMA 50 and EMA 20 are fixed, but they can be adjusted for different market conditions.
Pros of the Strategy:
EMA Crossover Strategy: A classic and well-known strategy used by traders to identify the start of new trends.
Multiple Take Profit Levels: By taking profits progressively at different levels, the strategy locks in gains as the price moves in favor of the position.
Clear Trend Identification: The use of green and red bars makes it visually easier to follow the market's direction.
Risk Management: The stop-loss and take-profit features help to manage risk and optimize profit-taking.
Cons of the Strategy:
Lagging Indicators: The strategy relies on EMAs, which are lagging indicators. This means that the strategy might enter trades after the trend has already started, leading to missed opportunities or less-than-ideal entry prices.
No Confirmation Indicators: The strategy purely depends on the crossover of two EMAs and does not use other confirming indicators (e.g., RSI, MACD), which might lead to false signals in volatile markets.
How to Use in Real-Time Trading:
Use for Backtesting: Initially, use this strategy in backtest mode to understand how it would have performed historically with your preferred settings.
Paper Trading: Once comfortable, you can use paper trading to test the strategy in real-time market conditions without risking real money.
Live Trading: After testing and optimizing the strategy, you can consider using it for live trading with proper risk management in place (e.g., starting with a small position size and adjusting parameters as needed).
Summary:
This strategy is designed to identify trend reversals using EMA crossovers, with customizable take-profit levels and a stop-loss to manage risk. It's well-suited for traders looking for a systematic way to enter and exit trades based on clear market signals, while also providing flexibility to adjust for different risk profiles and trading styles.
Candle % Close with Bullish/Bearish EvaluationI created the indicator to more quickly define the polarity of candles. For a large number of candles, it is straightforward to determine whether a candle is bullish or bearish. However, candles with long wicks often appear, making it uncertain whether the candle is bullish or bearish from a price action perspective. It is not a rule that a red candle is bearish and a green candle is bullish.
From a more advanced price action standpoint, how these candles close is important. Therefore, I created the 'Percent range' input. By default, it is set to 50% (high-low)/2. This way, the indicator precisely determines 50% of the candle's entire range. This allows us to determine whether a bearish candle truly closed below 50% of its range. If not, such a candle is considered bullish, even if it is a negative candle. The same applies to bullish candles, but conversely. If a positive candle closes below 50% of its range, from a price action perspective, it is considered a bearish candle.
Since in price action it is common for the price to return to 50% of the previous candle and, after filling, to continue in the established trend, I added the line extension option. Whatever high value you enter, the line extension follows the current candle. This option works only when the stop line checkbox is enabled. This way, you can plot 50% of the candle's range that the market has historically not returned to due to a strong trend. Often, this line is plotted on a candle where there is also an FVG, which can help you more easily find a point of interest.
Stop line extension : Ensures the interruption of line plotting when the candle is touched by the body or wick.
Dynamic Risk-Adjusted Performance Ratios with TableWith this indicator, you have everything you need to monitor and compare the Sharpe ratio, Sortino ratio, and Omega ratio across multiple assets—all in one place. This tool is designed to help save time and improve efficiency by letting you track up to 15 assets simultaneously in a fully customizable table. You can adjust the lookback period to fit your trading strategy and get a clearer picture of how your assets perform over time. Instead of switching between charts, this indicator puts all the critical information you need at your fingertips.
Sharpe Ratio -
Helps evaluate the overall efficiency of investments by comparing the average return to the total risk (measured by the standard deviation of all returns). Essentially, it tells you how much excess return you’re getting for each unit of risk you’re taking. A higher Sharpe ratio means you’re getting better risk-adjusted performance—something you’ll want to aim for in your portfolio.
Sortino Ratio -
Goes a step further by focusing only on downside risk—because let’s face it, no one worries about positive volatility. This ratio is calculated by dividing the average return by the standard deviation of only the negative returns. Perfect for those concerned about avoiding losses rather than chasing extreme gains. It gives you a sharper view of how well your assets are performing relative to the risks you’re trying to avoid.
Omega Ratio -
Offers a unique perspective by comparing the sum of positive returns to the absolute sum of negative returns. It’s a straightforward way to see if your wins outweigh your losses. A higher Omega ratio means your positive returns significantly exceed the downside, which is exactly what you want when building a strong, reliable portfolio.
This indicator is perfect for traders who want to streamline their decision-making process and gain an edge. Bringing together these three critical ratios into a single user-defined table makes it easy to compare and rank assets at a glance. Whether optimizing a portfolio or looking for the best opportunities, this tool helps you stay ahead by focusing on risk-adjusted returns. The customizable lookback period lets you tailor the analysis to fit your unique trading approach, giving you insights that align with your goals. If you’re serious about making data-driven decisions and improving your trading outcomes, this indicator is a game-changer for your toolkit.
CandelaCharts - Equal Highs/Lows (EQH/EQL) 📝 Overview
The Equal Highs/Lows indicator is a specialized tool for detecting equal highs and lows within price movements.
These levels hold importance as they frequently signal possible reversal zones or consolidation phases in the market. By leveraging Average True Range (ATR) thresholds, the indicator employs tailored settings to pinpoint these critical price levels with precision.
Visual Markings: Lines and labels highlight equal highs and lows directly on the chart.
Dynamic Adaptability: It adjusts in real time to market volatility, ensuring accurate level identification through ATR-based thresholds.
Equal Highs are not used as entry and exit points; instead, they are used as confirmation that the current market trend will reverse. This means that when an EQH is formed on a chart, traders can adapt a bearish bias and look for only short entries.
📦 Features
Key features of the indicator include:
Visual Markings: Lines and labels highlight equal highs and lows directly on the chart.
Dynamic Adaptability: It adjusts in real time to market volatility, ensuring accurate level identification through ATR-based thresholds.
Styling
⚙️ Settings
Show: Controls whether EQH/EQL are displayed on the chart.
Line Style: Controls the line type and line width
Bullish Color: Color of the bullish EQH/EQL
Bearish Color: Color of the bearish EQH/EQL
⚡️ Showcase
Short Term
Intermediate Term
Long Term
🚨 Alerts
This script provides alert options for all signals.
Bearish Signal
A bearish signal is triggered when the price forms an EQH.
Bullish Signal
A bullish signal is triggered when the price forms an EQL.
⚠️ Disclaimer
Trading involves significant risk, and many participants may incur losses. The content on this site is not intended as financial advice and should not be interpreted as such. Decisions to buy, sell, hold, or trade securities, commodities, or other financial instruments carry inherent risks and are best made with guidance from qualified financial professionals. Past performance is not indicative of future results.
Price Action Health CheckThis is a price action indicator that measures market health by comparing EMAs, adapting automatically to different timeframes (Weekly/Daily more reliable) and providing context-aware health status.
Key features:
Automatically adjusts EMA periods based on timeframe
Measures price action health through EMA separation and historical context
Provides visual health status with clear improvement/deterioration signals
Projects a 13-period trend line for directional context
Trading applications:
Identify shifts in market health before major trend changes
Validate trend strength by comparing current readings to historical averages
Time entries/exits based on health status transitions
Filter trades using timeframe-specific health readings
I like to use it to keep SPX in check before deciding the market is going down.
Note: For optimal analysis, use primarily on Weekly and Daily timeframes where price action patterns are more significant.
Snipe 1-Minute IntradayPurpose
This script demonstrates a simple intraday approach using RSI, EMAs, VWAP, and an optional volume filter. It plots visual buy (bullish) and sell (bearish) signals on the chart under certain conditions. You can use it as a starting point to explore or develop your own intraday strategies.
Key Features
1. VWAP (Volume Weighted Average Price)
Plots the built-in VWAP for additional context on intraday price action.
2. EMA Crossover
Uses two EMAs (fast and slow). A bullish signal triggers when the fast EMA is above the slow EMA, and a bearish signal triggers when the fast EMA is below the slow EMA.
3. RSI Momentum Filter
An RSI reading above 50 indicates bullish momentum; below 50 indicates bearish momentum.
4. Volume Filter (Optional)
Compares the current bar’s volume against the average volume (over a user-defined period). When enabled, signals only appear if the current volume exceeds the average.
5. Time Window (Optional)
Allows you to define a specific time window (e.g., the first hour of trading) for valid signals. You can enable or disable this filter and set your preferred time zone.
How the Signals Are Generated
• Bullish Signal
o Occurs when:
1. Price is above VWAP.
2. Fast EMA is above Slow EMA.
3. RSI is above 50.
4. (Optional) Current volume exceeds the average volume if the volume filter is enabled.
5. (Optional) The chart’s timestamp is within the specified session if the time filter is enabled.
A green triangle is plotted below the bar, and an optional background highlight is shown.
• Bearish Signal
Occurs when the conditions are inverted (price below VWAP, fast EMA below slow EMA, RSI below 50, volume filter and time window—if enabled—are satisfied).
A red triangle is plotted above the bar, and an optional background highlight is shown.
How to Use
1. Load on a 1-Minute Chart (Recommended)
This script is intended for intraday timeframes (specifically 1-minute). Feel free to experiment with other timeframes.
2. Adjust Inputs
You can modify the RSI length, EMA lengths, and volume lookback to suit your preferences or trading style.
If you prefer signals outside the default session hours, turn off “Use Time Filter for Signals?” or change the session window and time zone.
3. Enable or Disable Volume Filter
Turn this on if you only want signals during higher-than-average volume bars.
4. Combine with Other Analysis
This script can be used as a visual tool; however, it is not a complete trading system by itself. Consider additional technical or fundamental analysis to validate your trading decisions.
5. Risk Management
Always practice sound risk management. Setting appropriate stop-losses or using position sizing techniques can help manage potential losses.
Important Notes and Disclaimers
• Educational Only: This script is for demonstration and educational purposes and does not guarantee future results.
• No Financial Advice: Nothing here should be construed as financial or investment advice. Always do your own research and consider consulting a qualified financial professional.
• Test Before Using Live: If you plan to incorporate this script into a strategy, backtest it on historical data and consider forward-testing on a demo account.
• License: This code is subject to the Mozilla Public License 2.0.
