Ichimoku with Shifted and Unshifted Senkou BIchimoku Kinko Hyo Indicator Explanation
The Ichimoku Kinko Hyo is a comprehensive technical indicator designed to provide insights into the market's trend, support/resistance levels, and momentum, all in one glance. It consists of five main components:
Tenkan-sen (Conversion Line): A fast-moving average.
Kijun-sen (Base Line): A slower-moving average.
Senkou Span A (Leading Span A): The average of Tenkan-sen and Kijun-sen, shifted forward in time.
Senkou Span B (Leading Span B): A slower moving average of the high and low price over a period of 52 periods, shifted forward in time.
Chikou Span (Lagging Line): The closing price shifted back in time by 26 periods.
The Ichimoku indicator is typically used to identify the trend direction, momentum, and support/resistance levels. The cloud formed between Senkou Span A and Senkou Span B is key in identifying the market's overall trend.
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!
EMA CHILL 9/20/50/100/200this is a ema of 9,20,50,100 and 200, ema stands for exponential moving average, which tells us price trends in the market, we can use it in any chart to find market trends,
EMA CHILL 9/20/50/100this is a ema of 9,20,50 and 100, ema stands for exponential moving average, which tells us price trends in the market, we can use it in any chart to find market trends,
Price Down from Monthly High (%)//@version=5
indicator("Price Down from Monthly High (%)", overlay=true)
// Get the highest price of the current month
monthlyHigh = request.security(syminfo.tickerid, "M", high)
// Calculate the percentage price down from the monthly high
percentageDown = ((monthlyHigh - close) / monthlyHigh) * 100
// Plot the percentage down from the monthly high
plot(percentageDown, color=color.red, title="Percentage Down from Monthly High", linewidth=2)
[ItsPS] Previous and Current Day Change screener indicator Previous and Current Day Change screener indicator
WT SETUP WITH LINES AND LABELS//@version=5
indicator("WT SETUP WITH LINES AND LABELS", "WT SETUP", overlay=true, max_lines_count=500, max_labels_count=500)
// Timeframe selection
tf = input.string("D", "Timeframe", options= )
// Level selection
level_selection = input.string("Yesterday", "Level Calculation", options= )
// Color input options
color pivotColor = input.color(color.white, "Pivot Color", group="Colors")
color highColor = input.color(color.red, "High Color", group="Colors")
color lowColor = input.color(color.green, "Low Color", group="Colors")
color closeColor = input.color(color.white, "Close Color", group="Colors")
color r1Color = input.color(color.red, "R1 Color", group="Colors")
color r2Color = input.color(color.red, "R2 Color", group="Colors")
color r3Color = input.color(color.red, "R3 Color", group="Colors")
color r4Color = input.color(color.red, "R4 Color", group="Colors")
color s1Color = input.color(color.green, "S1 Color", group="Colors")
color s2Color = input.color(color.green, "S2 Color", group="Colors")
color s3Color = input.color(color.green, "S3 Color", group="Colors")
color s4Color = input.color(color.green, "S4 Color", group="Colors")
offset = level_selection == "Yesterday" ? 1 : 0
float lowPrev = request.security(syminfo.tickerid, tf, low )
float highPrev = request.security(syminfo.tickerid, tf, high )
float closePrev = request.security(syminfo.tickerid, tf, close )
float pivot = (lowPrev + highPrev + closePrev) / 3
float s1 = (2 * pivot) - highPrev
float r1 = (2 * pivot) - lowPrev
float rangeValue = highPrev - lowPrev
float s2 = pivot - rangeValue
float r2 = pivot + rangeValue
float s3 = lowPrev - 2 * (highPrev - pivot)
float r3 = highPrev + 2 * (pivot - lowPrev)
float s4 = pivot * 3 - (3 * highPrev - lowPrev)
float r4 = pivot * 3 + (highPrev - 3 * lowPrev)
var line pivotLine = na
var line r1Line = na
var line r2Line = na
var line r3Line = na
var line r4Line = na
var line s1Line = na
var line s2Line = na
var line s3Line = na
var line s4Line = na
var line highLine = na
var line lowLine = na
var line closeLine = na
var label pivotLabel = na
var label r1Label = na
var label r2Label = na
var label r3Label = na
var label r4Label = na
var label s1Label = na
var label s2Label = na
var label s3Label = na
var label s4Label = na
var label highLabel = na
var label lowLabel = na
var label closeLabel = na
if barstate.islast
pivotLine := line.new(bar_index, pivot, bar_index + 1, pivot, extend=extend.right, color=pivotColor, width=1)
r1Line := line.new(bar_index, r1, bar_index + 1, r1, extend=extend.right, color=r1Color, width=1)
r2Line := line.new(bar_index, r2, bar_index + 1, r2, extend=extend.right, color=r2Color, width=1)
r3Line := line.new(bar_index, r3, bar_index + 1, r3, extend=extend.right, color=r3Color, width=1)
r4Line := line.new(bar_index, r4, bar_index + 1, r4, extend=extend.right, color=r4Color, width=1)
s1Line := line.new(bar_index, s1, bar_index + 1, s1, extend=extend.right, color=s1Color, width=1)
s2Line := line.new(bar_index, s2, bar_index + 1, s2, extend=extend.right, color=s2Color, width=1)
s3Line := line.new(bar_index, s3, bar_index + 1, s3, extend=extend.right, color=s3Color, width=1)
s4Line := line.new(bar_index, s4, bar_index + 1, s4, extend=extend.right, color=s4Color, width=1)
highLine := line.new(bar_index, highPrev, bar_index + 1, highPrev, extend=extend.right, color=highColor, width=1)
lowLine := line.new(bar_index, lowPrev, bar_index + 1, lowPrev, extend=extend.right, color=lowColor, width=1)
closeLine := line.new(bar_index, closePrev, bar_index + 1, closePrev, extend=extend.right, color=closeColor, width=1)
tfString = tf == "D" ? "Daily" : (tf == "W" ? "Weekly" : "Monthly")
levelString = level_selection == "Yesterday" ? "Yesterday's" : "Latest"
pivotLabel := label.new(bar_index, pivot, tfString + " " + levelString + " Pivot " + str.tostring(pivot, "(#.##)"), color=color.gray, style=label.style_label_down, textcolor=color.white)
r1Label := label.new(bar_index, r1, "R1 " + str.tostring(r1, "(#.##)"), color=r1Color, style=label.style_label_down, textcolor=color.white)
r2Label := label.new(bar_index, r2, "R2 " + str.tostring(r2, "(#.##)"), color=r2Color, style=label.style_label_down, textcolor=color.white)
r3Label := label.new(bar_index, r3, "R3 " + str.tostring(r3, "(#.##)"), color=r3Color, style=label.style_label_down, textcolor=color.white)
r4Label := label.new(bar_index, r4, "R4 " + str.tostring(r4, "(#.##)"), color=r4Color, style=label.style_label_down, textcolor=color.white)
s1Label := label.new(bar_index, s1, "S1 " + str.tostring(s1, "(#.##)"), color=s1Color, style=label.style_label_up, textcolor=color.white)
s2Label := label.new(bar_index, s2, "S2 " + str.tostring(s2, "(#.##)"), color=s2Color, style=label.style_label_up, textcolor=color.white)
s3Label := label.new(bar_index, s3, "S3 " + str.tostring(s3, "(#.##)"), color=s3Color, style=label.style_label_up, textcolor=color.white)
s4Label := label.new(bar_index, s4, "S4 " + str.tostring(s4, "(#.##)"), color=s4Color, style=label.style_label_up, textcolor=color.white)
highLabel := label.new(bar_index, highPrev, "High " + str.tostring(highPrev, "(#.##)"), color=highColor, style=label.style_label_down, textcolor=color.white)
lowLabel := label.new(bar_index, lowPrev, "Low " + str.tostring(lowPrev, "(#.##)"), color=lowColor, style=label.style_label_up, textcolor=color.white)
closeLabel := label.new(bar_index, closePrev, "Close " + str.tostring(closePrev, "(#.##)"), color=color.gray, style=label.style_label_down, textcolor=color.white)
else
line.delete(pivotLine)
line.delete(r1Line)
line.delete(r2Line)
line.delete(r3Line)
line.delete(r4Line)
line.delete(s1Line)
line.delete(s2Line)
line.delete(s3Line)
line.delete(s4Line)
line.delete(highLine)
line.delete(lowLine)
line.delete(closeLine)
label.delete(pivotLabel)
label.delete(r1Label)
label.delete(r2Label)
label.delete(r3Label)
label.delete(r4Label)
label.delete(s1Label)
label.delete(s2Label)
label.delete(s3Label)
label.delete(s4Label)
label.delete(highLabel)
label.delete(lowLabel)
label.delete(closeLabel)
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.
Exponential Moving Averages by ComLucro - A/B/C/D/E - 2025_V01This script, "Exponential Moving Averages by ComLucro: A/B/C/D/E - 2025_V01", offers a customizable tool for traders to visualize five exponential moving averages (EMAs) on their charts.
Key Features:
Customizable Lengths: Adjust the lengths for each EMA (A, B, C, D, E) to fit your trading strategy, ranging from short-term (10 periods) to long-term (200 periods).
Color Customization: Choose colors for each EMA line to differentiate and organize your chart effectively.
Visibility Options: Toggle individual EMAs on or off for a cleaner and more focused analysis.
Intuitive Design: Streamlined user interface ensures easy integration and quick adjustments directly on your TradingView chart.
How It Works:
The script calculates five EMAs based on the closing price and plots them directly on your chart.
Use these EMAs to identify trends, potential reversals, and areas of confluence in price action.
Ideal For:
Traders seeking to incorporate multiple EMA signals into their trading strategy.
Analyzing trends across various timeframes with an easy-to-use, customizable indicator.
Chart Recommendation:
Use this script on clean charts with clear price action to avoid clutter. It works well in combination with other trend-following tools or oscillators.
Disclaimer:
This tool is for educational purposes only and does not constitute financial or trading advice. Use it as part of a well-rounded trading strategy with proper risk management.
Additional Notes:
For best results, combine this indicator with strong risk management practices and a detailed understanding of market conditions. Always backtest the settings to ensure compatibility with your trading strategy.
Simple Moving Averages by ComLucro - A/B/C/D/E - 2025_V03This script provides an easy-to-use tool for plotting Simple Moving Averages (SMA) on your TradingView chart. With customizable lengths, colors, and visibility options, you can tailor the script to fit your trading strategy and chart preferences.
Key Features:
Five Simple Moving Averages (SMA): A, B, C, D, and E, with default lengths of 10, 20, 50, 100, and 200 periods, respectively.
Fully Customizable:
Adjust SMA lengths to match your trading needs.
Customize line colors for easy identification.
Toggle visibility for each SMA on or off.
Clear and Intuitive Design: This script overlays directly on your chart, providing a clean and professional look.
Educational Purpose: Designed to support traders in analyzing market trends and identifying key price levels.
How to Use:
Add the indicator to your chart.
Configure the SMA lengths under the input settings. Default settings are optimized for common trading strategies.
Customize the colors to differentiate between the moving averages.
Toggle the visibility of specific SMAs to focus on what's important for your analysis.
Best Practices:
Use shorter SMAs (e.g., A and B) to identify short-term trends and momentum.
Use longer SMAs (e.g., D and E) to evaluate medium- to long-term trends and support/resistance levels.
Combine with other tools like RSI, MACD, or volume analysis for a more comprehensive trading strategy.
Disclaimer:
This script is for educational purposes only and does not constitute financial or trading advice. Always backtest your strategies and use proper risk management before applying them in live markets.
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.
Buy the Close, Sell the OpenScript de prueba para la estrategia de "Buy the Close, Sell the Open" sugerida por el master HC.
EMA Crossover Short-Only Strategy5 min timeframe for best results
and best for index only first analyse then implement your own strategy for better optimisation
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.
SMA MTF Difference %Indicador que calcula y muestra la diferencia porcentual entre la SMA 200 en timeframe de 1 minuto y la SMA 50 en timeframe de 5 minutos.
Un valor positivo indica que la SMA 200 1m está por encima de la SMA 50 5m.
Ejemplo: Un valor de 5 significa que la SMA 200 1m está 5% por encima de la SMA 50 5m.
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.
GeometricProgressionPriceLevelsThis indicator plots horizontal lines at values which are terms of a Geometric Progression. 'Base Price' could be any number (use a number nearest to the price of the Symbol/Stock). 'Multiplier For Geometric Progression' is the Multiplication Factor to calculate values between terms. 30 Horizontal lines will be plotted above and 30 Horizontal lines will be plotted below the 'Base Price' number value.
