Custom V2 KillZone US / FVG / EMAThis indicator is designed for traders looking to analyze liquidity levels, opportunity zones, and the underlying trend across different trading sessions. Inspired by the ICT methodology, this tool combines analysis of Exponential Moving Averages (EMA), session management, and Fair Value Gap (FVG) detection to provide a structured and disciplined approach to trading effectively.
Indicator Features
Identifying the Underlying Trend with Two EMAs
The indicator uses two EMAs on different, customizable timeframes to define the underlying trend:
EMA1 (default set to a daily timeframe): Represents the primary underlying trend.
EMA2 (default set to a 4-hour timeframe): Helps identify secondary corrections or impulses within the main trend.
These two EMAs allow traders to stay aligned with the market trend by prioritizing trades in the direction of the moving averages. For example, if prices are above both EMAs, the trend is bullish, and long trades are favored.
Analysis of Market Sessions
The indicator divides the day into key trading sessions:
Asian Session
London Session
US Pre-Open Session
Liquidity Kill Session
US Kill Zone Session
Each session is represented by high and low zones as well as mid-lines, allowing traders to visualize liquidity levels reached during these periods. Tracking the price levels in different sessions helps determine whether liquidity levels have been "swept" (taken) or not, which is essential for ICT methodology.
Liquidity Signal ("OK" or "STOP")
A specific signal appears at the end of the "Liquidity Kill" session (just before the "US Kill Zone" session):
"OK" Signal: Indicates that liquidity conditions are favorable for trading the "US Kill Zone" session. This means that liquidity levels have been swept in previous sessions (Asian, London, US Pre-Open), and the market is ready for an opportunity.
"STOP" Signal: Indicates that it is not favorable to trade the "US Kill Zone" session, as certain liquidity conditions have not been met.
The "OK" or "STOP" signal is based on an analysis of the high and low levels from previous sessions, allowing traders to ensure that significant liquidity zones have been reached before considering positions in the "Kill Zone".
Detection of Fair Value Gaps (FVG) in the US Kill Zone Session
When an "OK" signal is displayed, the indicator identifies Fair Value Gaps (FVG) during the "US Kill Zone" session. These FVGs are areas where price may return to fill an "imbalance" in the market, making them potential entry points.
Bullish FVG: Detected when there is a bullish imbalance, providing a buying opportunity if conditions align with the underlying trend.
Bearish FVG: Detected when there is a bearish imbalance, providing a selling opportunity in the trend direction.
FVG detection aligns with the ICT Silver Bullet methodology, where these imbalance zones serve as probable entry points during the "US Kill Zone".
How to Use This Indicator
Check the Underlying Trend
Before trading, observe the two EMAs (daily and 4-hour) to understand the general market trend. Trades will be prioritized in the direction indicated by these EMAs.
Monitor Liquidity Signals After the Asian, London, and US Pre-Open Sessions
The high and low levels of each session help determine if liquidity has already been swept in these areas. At the end of the "Liquidity Kill" session, an "OK" or "STOP" label will appear:
"OK" means you can look for trading opportunities in the "US Kill Zone" session.
"STOP" means it is preferable not to take trades in the "US Kill Zone" session.
Look for Opportunities in the US Kill Zone if the Signal is "OK"
When the "OK" label is present, focus on the "US Kill Zone" session. Use the Fair Value Gaps (FVG) as potential entry points for trades based on the ICT methodology. The identified FVGs will appear as colored boxes (bullish or bearish) during this session.
Use ICT Methodology to Manage Your Trades
Follow the FVGs as potential reversal zones in the direction of the trend, and manage your positions according to your personal strategy and the rules of the ICT Silver Bullet method.
Customizable Settings
The indicator includes several customization options to suit the trader's preferences:
EMA: Length, source (close, open, etc.), and timeframe.
Market Sessions: Ability to enable or disable each session, with color and line width settings.
Liquidity Signals: Customization of colors for the "OK" and "STOP" labels.
FVG: Option to display FVGs or not, with customizable colors for bullish and bearish FVGs, and the number of bars for FVG extension.
-------------------------------------------------------------------------------------------------------------
Cet indicateur est conçu pour les traders souhaitant analyser les niveaux de liquidité, les zones d’opportunité, et la tendance de fond à travers différentes sessions de trading. Inspiré de la méthodologie ICT, cet outil combine l'analyse des moyennes mobiles exponentielles (EMA), la gestion des sessions de marché, et la détection des Fair Value Gaps (FVG), afin de fournir une approche structurée et disciplinée pour trader efficacement.
무빙 애버리지
Fibonacci Moving Average PlusFibonacci Moving Average Plus is a sophisticated technical indicator that employs the first 15 numbers of the Fibonacci sequence to create dynamic moving average channels. This indicator aims to capture both immediate and long-term price movements by calculating Exponential Moving Averages (EMAs) based on these Fibonacci values. By using Fibonacci-based moving averages for both high and low price points, the indicator generates a visual channel that reflects the ebb and flow of market trends, acting as potential zones of support and resistance. Additionally, the indicator provides midline, retracement, and extension levels rooted in Fibonacci ratios, which are frequently observed as key levels for reversals or trend continuation.
Ideology Behind Using Fibonacci Sequence-Based Moving Averages
The Fibonacci sequence, known for its mathematical harmony and prevalence in natural patterns, is widely utilized in technical analysis to identify potential turning points in markets. In this indicator, the first 15 Fibonacci numbers (5, 8, 13, 21, etc.) are used as the lookback periods for EMAs to capture different layers of market sentiment. These moving averages represent timeframes that are theoretically in alignment with the natural rhythms of market cycles, where key levels—often coinciding with Fibonacci numbers—can act as magnetic points for price.
The Fibonacci high and low channels aim to encapsulate price action, giving traders a sense of whether the market is trending, consolidating, or experiencing reversal pressure. These levels, grounded in both mathematics and market psychology, help traders spot areas where price might face resistance or find support.
Key Features
Fibonacci Moving Average High and Low: This indicator calculates the high and low EMAs based on Fibonacci sequence numbers (e.g., 5, 8, 13, etc.) for enhanced trend analysis.
Golden Pocket Retracement (GPR) and Extension (GPE) Bands: Displays common Fibonacci retracement and extension levels (0.618, 0.65 for retracement, and 1.618, 1.65 for extension).
Midline: Plots the average of the Fibonacci high and low to act as an additional reference level.
Stop-Loss Levels: Provides suggested stop-loss levels based on Fibonacci levels for both long and short positions.
Basic User Guide
Adjust Input Settings:
Input Timeframe: Set a specific timeframe for the Fibonacci moving average calculation, separate from the chart's primary timeframe.
Show Fibonacci MA High/Low: Toggle the visibility of the high and low Fibonacci moving averages.
Show Mid Line: Display a midline for added trend reference.
Show Golden Pocket Bands: Choose to display retracement or extension bands for potential support or resistance zones.
Show Stop-Loss Levels: Enable to visualize potential stop-loss levels for both long and short trades.
Interpretation:
Fibonacci MA High and Low: Use these lines to gauge the general trend. When the price is above both, it may indicate an uptrend; below both, a downtrend.
Golden Pocket Retracement: This zone (between 0.618 and 0.65) is often a key level for potential reversals or support/resistance.
Golden Pocket Extension: The 1.618 and 1.65 levels can indicate potential profit-taking or trend exhaustion points.
Stop-Loss Levels: The calculated stop-loss levels (long SL below and short SL above) can aid in risk management.
Customization:
You can customize the appearance and visibility of each component through the input settings to fit your specific strategy and visual preferences.
This indicator should be used alongside other technical analysis tools to provide a more comprehensive trading approach.
This Indicator would not exist without the original contributions and blessing from Sofien Kaabar
Moving Average Percentage DifferenceMoving average is a great tool to identify the asset direction. However, it's hard to see whether the moving average speeds up or slows down from just looking at it. Ideally we want it to go faster as it will show a strong trend. And if it slows down - then the trend becomes weaker. This indicator helps to identify it. Theoretically, it could be shown with an angle of the moving average, but I don't like this idea as the angle depends on the scale: you zoom in and it looks very steep, you zoom out - and it's all flat. But the percentage change is always the percentage, no matter what zoom you use.
It also allows you to set a twilight zone to filter periods when MA does nothing.
Think about this indicator from this perspective: if a normal moving average shows the speed of a trend, then this indicator shows the change of the speed or in other words - acceleration.
Multifactor Buy/Sell Strategy V2 | RSI, MACD, ATR, EMA, Boll.BITGET:1INCHUSDT
This Pine Script code for TradingView is a multifactor Buy/Sell indicator that combines several technical factors to generate trading signals based on trend, volatility, and volume conditions. Here’s a breakdown of the main components and functionality:
Indicator Name
- Multifactor Buy/Sell Strategy V2 — an overlay indicator applied directly on the price chart.
### Input Parameters
The script includes multiple customizable parameters:
- RSI, EMA, MACD parameters — for setting periods and signals of MACD and RSI.
- ATR and Bollinger Bands — used for volatility analysis and level determination.
- Minimum Volatility Threshold — sets a minimum Bollinger Band width threshold for determining high volatility.
Core Indicators
1. RSI — calculated to identify oversold (below 30) and overbought (above 70) conditions.
2. EMA and MACD — calculates exponential moving averages and MACD histogram to determine trend direction.
3. ATR and Bollinger Bands — used to assess current volatility and establish dynamic upper and lower bands.
Volatility and Volume Analysis
- Determines the current ATR level and Bollinger Band width to evaluate high volatility.
- Calculates the volume moving average to track periods of increased volume during high volatility.
Trend Analysis
The script uses the difference between fast and slow EMAs to define strong trends:
- Uptrend — when the fast EMA is above the slow EMA, the price is above the fast EMA, and the trend is strong.
- Downtrend — when the fast EMA is below the slow EMA, the price is below the fast EMA, and the trend is strong.
Momentum Filter
- Based on the price change over the last three bars and compared against the minimum volatility threshold to identify strong momentum.
Buy and Sell Signal Generation
- Buy Signal: Uptrend with RSI oversold, positive MACD histogram, high volatility and volume, strong momentum, and sufficient Bollinger Band width.
- Sell Signal: Downtrend with RSI overbought, negative MACD histogram, high volatility and volume, strong momentum, and sufficient Bollinger Band width.
Visualization
- Buy and sell signals are displayed as green and red triangles on the chart.
- Plots for fast and slow EMAs, upper and lower bands, and Bollinger Bands.
Alerts
The script includes alert conditions for buy and sell signals, allowing notifications to be sent via email or mobile app.
Information Panel
A small table on the chart displays current volatility dataThis Pine Script code for TradingView is a multifactor Buy/Sell indicator that combines several technical factors to generate trading signals based on trend, volatility, and volume conditions. Here’s a breakdown of the main components and functionality:
Indicator Name
- Multifactor Buy/Sell Strategy V2 — an overlay indicator applied directly on the price chart.
Input Parameters
The script includes multiple customizable parameters:
- **RSI, EMA, MACD parameters** — for setting periods and signals of MACD and RSI.
- **ATR and Bollinger Bands** — used for volatility analysis and level determination.
- **Minimum Volatility Threshold** — sets a minimum Bollinger Band width threshold for determining high volatility.
Core Indicators
1. RSI — calculated to identify oversold (below 30) and overbought (above 70) conditions.
2. EMA and MACD — calculates exponential moving averages and MACD histogram to determine trend direction.
3. ATR and Bollinger Bands — used to assess current volatility and establish dynamic upper and lower bands.
Volatility and Volume Analysis
- Determines the current ATR level and Bollinger Band width to evaluate high volatility.
- Calculates the volume moving average to track periods of increased volume during high volatility.
Trend Analysis
The script uses the difference between fast and slow EMAs to define strong trends:
- Uptrend — when the fast EMA is above the slow EMA, the price is above the fast EMA, and the trend is strong.
- Downtrend — when the fast EMA is below the slow EMA, the price is below the fast EMA, and the trend is strong.
Momentum Filter
- Based on the price change over the last three bars and compared against the minimum volatility threshold to identify strong momentum.
Buy and Sell Signal Generation
- Buy Signal: Uptrend with RSI oversold, positive MACD histogram, high volatility and volume, strong momentum, and sufficient Bollinger Band width.
- Sell Signal: Downtrend with RSI overbought, negative MACD histogram, high volatility and volume, strong momentum, and sufficient Bollinger Band width.
Visualization
- Buy and sell signals are displayed as green and red triangles on the chart.
- Plots for fast and slow EMAs, upper and lower bands, and Bollinger Bands.
Alerts
The script includes alert conditions for buy and sell signals, allowing notifications to be sent via email or mobile app.
Information Panel
A small table on the chart displays current volatility
- Volatility Status — indicates high or low volatility.
- Bollinger Band Width — current width as a percentage.
- ATR Ratio — ratio of current ATR to long-term average ATR.
This script is suitable for trading in high-volatility conditions, combining multiple filters and factors to generate precise buy and sell signals.
EMA Hierarchy Score V.1.0
EMA Hierarchy Score V.1.0
Purpose
The EMA Hierarchy Score indicator assesses the relative positioning of multiple Exponential Moving Averages (EMAs) for a financial asset. This tool provides insights into trend strength by calculating ideal and non-ideal configurations of EMAs, allowing for effective interpretation when used alongside standard EMA charts.
Variables and Inputs
The indicator organizes a set of EMAs and other metrics into a hierarchy for scoring:
* Primary Variables (A–J):
A: Close price
B: Open price
C: Previous close price
D to J: EMAs of configurable periods (5, 9, 13, 21, 26, 52, 100).
* User Inputs:
* Customizable periods for each EMA, allowing users to adjust the indicator’s sensitivity.
* Customizable period and standard deviation multiplier for Bollinger Bands, enabling further control over the indicator’s analysis.
Mathematical Method
The EMA Hierarchy Score calculates how closely the current EMA structure aligns with an “ideal” configuration through a structured scoring system:
1- Hierarchy Scoring:
* Ideal Order: Defined as A > B > C > D > E > F > G > H > I > J, representing a strong upward trend where each EMA progressively increases.
* Non-Ideal Order: Defined as J > I > H > G > F > E > D > C > B > A, indicating a weak or downward trend where each EMA progressively decreases.
* Optimal Order: Calculated based on achieving maximum alignment with the ideal configuration for each EMA across the chosen period.
* Sub-Optimal Order: The least-aligned structure across the same period.
2- Score Calculation:
* The indicator calculates a score by comparing all EMA pairs in values. For each comparison, a score increment of +1 (ideal) or -1 (non-ideal) is applied.
* The final score reflects the EMA configuration’s deviation from the ideal order:
- Positive Score: Indicates closer alignment with the ideal structure.
- Negative Score: Indicates deviation toward a non-ideal structure.
3- Smoothed and Signal Lines:
* A smoothed score is created using a Simple Moving Average (SMA) of the raw hierarchy score.
* A signal line (an SMA of the smoothed score) further aids in tracking directional shifts in the score.
4- Trend Labels and Bollinger Bands:
* Trend Labels: Display "UP" or "DOWN" based on the smoothed score’s relationship to the signal line.
* Bollinger Bands: Plotted around a selected source (smoothedLine, signalLine, or score) to analyze score volatility and deviations from the mean. The period and standard deviation multiplier for Bollinger Bands are user-configurable.
Result Definition
The Ideal and Non-Ideal Scores represent the upper and lower bounds of achievable configurations, ensuring the score does not exceed these values.
1- Ideal and Non-Ideal Result:
* Calculated based on how closely the current EMA configuration follows the “ideal” ascending or descending order.
* Ideal Score: Defined as +165, representing perfect alignment with the ideal configuration.
* Non-Ideal Score: Defined as -165, indicating full alignment with the descending, non-ideal structure.
* The score is bounded by these values and will not go above or below this range.
2- Optimal and Sub-Optimal Scores:
* Optimal Score: The highest score over the selected scoring period, calculated with the same period as the Bollinger Bands. Using consistent periods reinforces the reliability of the score by aligning with the period already used to gauge volatility.
* Sub-Optimal Score: The lowest score over the same period, capturing points of minimal alignment with the ideal order.
Interpretation and Analysis
1- Use with EMA Charts:
* This indicator is designed to be used alongside EMA charts, as its results provide insights into the relative order of EMAs and their alignment with trend strength.
* The EMA Hierarchy Score interprets the underlying EMA structure, offering additional context on whether current trends are aligned with optimal or non-optimal EMA configurations.
2- Ideal and Non-Ideal Analysis:
* A positive EMA Hierarchy Score indicates an orderly, ideal upward trend, suggesting stronger alignment with the ideal structure.
* A negative score signals a potential downward trend or deviation from the ideal structure.
3 - Trend Indicators and Bands:
* Trend Labels: The "UP" and "DOWN" labels offer real-time feedback on trend direction shifts, based on the smoothed score and signal line relationship.
* Bollinger Bands: Visualize the range of score fluctuations, helping to identify breakout or breakdown points.
4 - Optimal and Sub-Optimal Scores:
* Use the Optimal Score to understand peak trend alignment and Sub-Optimal Score to spot potential reversal or correction zones.
* A consistently high score over time indicates trend stability, while variations may suggest instability.
Quick Reference Table
The table displayed at the top right provides an at-a-glance view of key metrics:
* Ideal and Non-Ideal Score: Fixed at ±165 to represent the calculated ideal and non-ideal configuration.
* Optimal and Sub-Optimal Scores: Show maximum and minimum scores over the scoring period, color-coded green for positive and red for negative values.
This concise table helps users quickly assess indicator values, reducing the need to interpret multiple chart lines and making it easier to understand overall trend strength.
Disclaimer
The EMA Hierarchy Score V.1.0 is a technical analysis tool designed to assist in understanding the alignment and strength of trends as defined by EMA configurations. This indicator does not constitute investment advice, nor does it make specific recommendations for buying or selling assets. Users should consult with a financial advisor before making any trading decisions, as past performance or technical signals do not guarantee future results. The developers of this indicator disclaim all liability for potential financial losses arising from reliance on this tool. Users assume full responsibility for interpreting and applying the indicator’s outputs in their investment decisions.
Frosty the Trendman: A Gift to Brighten Your Christmas TradesFrosty the Trendman: A Gift to Brighten Your Christmas Trades 🎁
This festive indicator we bring to you as a Christmas gift in the form of a snowman ☃️, to light up your chart with joy and the Christmas spirit. 🎄✨
Frosty is not just a festive snowman, he's also a market expert! 📈
And he’s useful as a trading indicator. 🤑
Key Features:
• Frosty changes color based on the trend! ❄️🎨
When the trend is bullish 💹, that is, when the price is above the 200-period simple moving average (SMA 200), Frosty turns a light green 🌱, reflecting a positive, growing atmosphere. This color activates when the price is above the SMA 200, indicating a bullish trend. 📈
• When the trend is bearish 📉, that is, when the price is below the SMA 200, Frosty changes to a light red 🔴, reflecting a negative market trend and a more pessimistic sentiment. 😔
See it here!
• Interactive elements 🤖: With buttons, eyes 👀, and a nose (in the shape of a triangle), Frosty even has a dollar sign 💵 on his hat because we all like a little Christmas cheer in our trades! 💰
• Christmas cheer 🎅🏼: The snowman not only represents festive fun, but also includes a label that says "Merry Christmas" 🎄 to remind you to enjoy the Christmas spirit in your trading. 🎉
• Perfect for the holiday season! 🎁
Although Frosty is a snowman, the purpose of this indicator is to bring warmth and joy 🌟 to your trading experience. Whether for fun or simply to add some Christmas magic to your charts, Frosty is here to guide your holiday trades with a festive touch! 🎅🎄✨
Enjoy the holiday spirit while trading with Frosty! ❄️
Español
Frosty the Trendman: Un regalo para alegrar tus trades navideños 🎁
Este indicador festivo que traemos para ti como un regalo navideño en forma de un muñeco de nieve ☃️, para iluminar tu gráfico con alegría y el espíritu navideño. 🎄✨
Frosty no solo es un muñeco de nieve festivo, ¡también es un experto en el mercado! 📈 Y tiene utilidad como indicador de trading. 🤑
Características clave:
• ¡Frosty cambia de color según la tendencia! ❄️🎨
Cuando la tendencia es alcista 💹, es decir, cuando el precio se encuentra por encima de la media móvil simple de 200 periodos (SMA 200), Frosty adquiere un color verde claro 🌱, que refleja un ambiente positivo y de crecimiento.
Este color se activa cuando el precio está por encima del SMA 200, indicando que la tendencia es alcista. 📈
• Cuando la tendencia es bajista 📉, es decir, cuando el precio se encuentra por debajo del SMA 200, Frosty cambia a un color rojo claro 🔴, lo que refleja una tendencia negativa en el mercado y un sentimiento más pesimista. 😔
• Elementos interactivos 🤖: Con botones, ojos 👀 y una nariz (en forma de triángulo), ¡Frosty incluso lleva un signo de dólar 💵 en su sombrero, porque a todos nos gusta un poco de alegría navideña en nuestras operaciones! 💰
• Ánimo navideño 🎅🏼: El muñeco de nieve no solo representa diversión festiva, sino que también incluye una etiqueta que dice "Merry Christmas" 🎄 para recordarte disfrutar del espíritu navideño en tu trading. 🎉
• ¡Perfecto para la temporada navideña! 🎁: Aunque Frosty sea un muñeco de nieve, el propósito de este indicador es traer calor y alegría 🌟 a tu experiencia de trading. Ya sea para divertirte o simplemente añadir un poco de magia navideña a tus gráficos,
¡Frosty está aquí para guiar tus operaciones navideñas con un toque festivo! 🎅🎄✨
BTCUSD Price Overextension from Configurable SMAsBTCUSD Price Overextension Indicator with Configurable SMAs
This indicator helps identify potential correction points for BTCUSD by detecting overextended conditions based on customizable short-term and long-term SMAs, average price deviation, and divergence.
Key Features:
Customizable SMAs: Set your own lengths for short-term (default 20) and long-term (default 50) SMAs, allowing you to tailor the indicator to different market conditions.
Overextension Detection: Detects when the average price over a set period (default 10 bars) is overextended above the short-term SMA by a configurable adjustment factor.
Divergence Threshold: Highlights when the short-term and long-term SMAs diverge beyond a specified threshold, signaling potential trend continuation.
Conditional Highlight: Displays a red background only when all conditions are met, and the current candle closes at or above the previous candle. A label "Overextended" appears only on the first bar of each overextended sequence for clear identification.
How to Use:
Identify Correction Signals: Look for red background highlights, which indicate a potential overextension based on the configured SMA and divergence thresholds.
Adjust Parameters: Use the adjustment factor, divergence threshold, and SMA lengths to fine-tune the indicator for different market environments or trading strategies.
This tool is ideal for BTCUSD traders looking to spot potential pullback areas or continuation zones by analyzing trend strength and overextension relative to key moving averages.
Bollinger Bands + RSI StrategyThe Bollinger Bands + RSI strategy combines volatility and momentum indicators to spot trading opportunities in intraday settings. Here’s a concise summary:
Components:
Bollinger Bands: Measures market volatility. The lower band signals potential buying opportunities when the price is considered oversold.
Relative Strength Index (RSI): Evaluates momentum to identify overbought or oversold conditions. An RSI below 30 indicates oversold, suggesting a buy, and above 70 indicates overbought, suggesting a sell.
Strategy Execution:
Buy Signal : Triggered when the price falls below the lower Bollinger Band while the RSI is also below 30.
Sell Signal : Activated when the price exceeds the upper Bollinger Band with an RSI above 70.
Exit Strategy : Exiting a buy position is considered when the RSI crosses back above 50, capturing potential rebounds.
Advantages:
Combines price levels with momentum for more reliable signals.
Clearly defined entry and exit points help minimize emotional trading.
Considerations:
Can produce false signals in very volatile or strongly trending markets.
Best used in markets without a strong prevailing trend.
This strategy aids traders in making decisions based on technical indicators, enhancing their ability to profit from short-term price movements.
Moving Average Pullback Signals [UAlgo]The "Moving Average Pullback Signals " indicator is designed to identify potential trend continuation or reversal points based on moving average (MA) pullback patterns. This tool combines multiple types of moving averages, customized trend validation parameters, and candlestick wick patterns to provide reliable buy and sell signals. By leveraging several advanced MA methods (such as TEMA, DEMA, ZLSMA, and McGinley-D), this script can adapt to different market conditions, providing traders with flexibility and more precise trend-based entries and exits. The addition of a gradient color-coded moving average line and wick validation logic enables traders to visualize market sentiment and trend strength dynamically.
🔶 Key Features
Multiple Moving Average (MA) Calculation Methods: This indicator offers various MA calculation types, including SMA, EMA, DEMA, TEMA, ZLSMA, and McGinley-D, allowing traders to select the MA that best fits their strategy.
Trend Validation and Pattern Recognition: The indicator includes a customizable trend validation length, ensuring that the trend is consistent before buy/sell signals are generated. The "Trend Pattern Mode" setting provides flexibility between "No Trend in Progress," "Trend Continuation," and "Both," tailoring signals to the trader’s preferred style.
Wick Validation Logic: To enhance the accuracy of entries, this indicator identifies specific wick patterns for bullish or bearish pullbacks, which signal potential trend continuation or reversal. Wick length and validation factor are adjustable to suit various market conditions and timeframes.
Gradient Color-coded MA Line: This feature provides a quick visual cue for trend strength, with color changes reflecting relative highs and lows of the MA, enhancing market sentiment interpretation.
Alerts for Buy and Sell Signals: Alerts are triggered when either a bullish or bearish pullback is detected, allowing traders to receive instant notifications without continuously monitoring the chart.
Visual Labels for Reversal Points: The indicator plots labels ("R") at potential reversal points, with color-coded labels for bullish (green) and bearish (red) pullbacks, highlighting pullback opportunities that align with the trend or reversal potential.
🔶 Disclaimer
Use with Caution: This indicator is provided for educational and informational purposes only and should not be considered as financial advice. Users should exercise caution and perform their own analysis before making trading decisions based on the indicator's signals.
Not Financial Advice: The information provided by this indicator does not constitute financial advice, and the creator (UAlgo) shall not be held responsible for any trading losses incurred as a result of using this indicator.
Backtesting Recommended: Traders are encouraged to backtest the indicator thoroughly on historical data before using it in live trading to assess its performance and suitability for their trading strategies.
Risk Management: Trading involves inherent risks, and users should implement proper risk management strategies, including but not limited to stop-loss orders and position sizing, to mitigate potential losses.
No Guarantees: The accuracy and reliability of the indicator's signals cannot be guaranteed, as they are based on historical price data and past performance may not be indicative of future results.
Machine Learning RSI [BackQuant]Machine Learning RSI
The Machine Learning RSI is a cutting-edge trading indicator that combines the power of Relative Strength Index (RSI) with Machine Learning (ML) clustering techniques to dynamically determine overbought and oversold thresholds. This advanced indicator adapts to market conditions in real-time, offering traders a robust tool for identifying optimal entry and exit points with increased precision.
Core Concept: Relative Strength Index (RSI)
The RSI is a well-known momentum oscillator that measures the speed and change of price movements, oscillating between 0 and 100. Typically, RSI values above 70 are considered overbought, and values below 30 are considered oversold. However, static thresholds may not be effective in all market conditions.
This script enhances the RSI by integrating a dynamic thresholding system powered by Machine Learning clustering, allowing it to adapt thresholds based on historical RSI behavior and market context.
Machine Learning Clustering for Dynamic Thresholds
The Machine Learning (ML) component uses clustering to calculate dynamic thresholds for overbought and oversold levels. Instead of relying on fixed RSI levels, this indicator clusters historical RSI values into three groups using a percentile-based initialization and iterative optimization:
Cluster 1: Represents lower RSI values (typically associated with oversold conditions).
Cluster 2: Represents mid-range RSI values.
Cluster 3: Represents higher RSI values (typically associated with overbought conditions).
Dynamic thresholds are determined as follows:
Long Threshold: The upper centroid value of Cluster 3.
Short Threshold: The lower centroid value of Cluster 1.
This approach ensures that the indicator adapts to the current market regime, providing more accurate signals in volatile or trending conditions.
Smoothing Options for RSI
To further enhance the effectiveness of the RSI, this script allows traders to apply various smoothing methods to the RSI calculation, including:
Simple Moving Average (SMA)
Exponential Moving Average (EMA)
Weighted Moving Average (WMA)
Hull Moving Average (HMA)
Linear Regression (LINREG)
Double Exponential Moving Average (DEMA)
Triple Exponential Moving Average (TEMA)
Adaptive Linear Moving Average (ALMA)
T3 Moving Average
Traders can select their preferred smoothing method and adjust the smoothing period to suit their trading style and market conditions. The option to smooth the RSI reduces noise and makes the indicator more reliable for detecting trends and reversals.
Long and Short Signals
The indicator generates long and short signals based on the relationship between the RSI value and the dynamic thresholds:
Long Signals: Triggered when the RSI crosses above the long threshold, signaling bullish momentum.
Short Signals: Triggered when the RSI falls below the short threshold, signaling bearish momentum.
These signals are dynamically adjusted to reflect real-time market conditions, making them more robust than static RSI signals.
Visualization and Clustering Insights
The Machine Learning RSI provides an intuitive and visually rich interface, including:
RSI Line: Plotted in real-time, color-coded based on its position relative to the dynamic thresholds (green for long, red for short, gray for neutral).
Dynamic Threshold Lines: The script plots the long and short thresholds calculated by the ML clustering process, providing a clear visual reference for overbought and oversold levels.
Cluster Plots: Each RSI cluster is displayed with distinct colors (green, orange, and red) to give traders insights into how RSI values are grouped and how the dynamic thresholds are derived.
Customization Options
The Machine Learning RSI is highly customizable, allowing traders to tailor the indicator to their preferences:
RSI Settings : Adjust the RSI length, source price, and smoothing method to match your trading strategy.
Threshold Settings : Define the range and step size for clustering thresholds, allowing you to fine-tune the clustering process.
Optimization Settings : Control the performance memory, maximum clustering steps, and maximum data points for ML calculations to ensure optimal performance.
UI Settings : Customize the appearance of the RSI plot, dynamic thresholds, and cluster plots. Traders can also enable or disable candle coloring based on trend direction.
Alerts and Automation
To assist traders in staying on top of market movements, the script includes alert conditions for key events:
Long Signal: When the RSI crosses above the long threshold.
Short Signal: When the RSI crosses below the short threshold.
These alerts can be configured to notify traders in real-time, enabling timely decisions without constant chart monitoring.
Trading Applications
The Machine Learning RSI is versatile and can be applied to various trading strategies, including:
Trend Following: By dynamically adjusting thresholds, this indicator is effective in identifying and following trends in real-time.
Reversal Trading: The ML clustering process helps identify extreme RSI levels, offering reliable signals for reversals.
Range-Bound Trading: The dynamic thresholds adapt to market conditions, making the indicator suitable for trading in sideways markets where static thresholds often fail.
Final Thoughts
The Machine Learning RSI represents a significant advancement in RSI-based trading indicators. By integrating Machine Learning clustering techniques, this script overcomes the limitations of static thresholds, providing dynamic, adaptive signals that respond to market conditions in real-time. With its robust visualization, customizable settings, and alert capabilities, this indicator is a powerful tool for traders seeking to enhance their momentum analysis and improve decision-making.
As always, thorough backtesting and integration into a broader trading strategy are recommended to maximize the effectiveness!
Auto Fibonacci ModePurpose of the Code:
This Pine Script™ code defines an indicator called "Auto Fibonacci Mode" that automatically plots Fibonacci retracement and extension levels based on recent price data, providing traders with reference levels for potential support and resistance. It also offers an "Auto" mode that determines levels based on the selected moving average type (e.g., EMA, SMA) for added flexibility in trend identification.
Key Components and Functionalities:
Inputs:
lookback (Lookback): Determines how many bars back to look when identifying the highest and lowest prices.
reverse: Reverses the direction of Fibonacci calculations, which is helpful for analyzing both uptrends and downtrends.
auto: When enabled, this option automatically adjusts Fibonacci levels based on a moving average.
mod: Allows the user to select a specific moving average type (EMA, SMA, RMA, HMA, or WMA) for use in "Auto" mode.
Label and Color Options: Customize the display of Fibonacci labels, colors, and whether to show the highest and lowest levels on the chart.
Fibonacci Levels:
Sixteen Fibonacci levels are configurable in the input options, allowing users to choose traditional retracement levels (e.g., 0.236, 0.5, 1.618) as well as custom levels.
These levels are calculated dynamically and adjusted based on the highest and lowest price range within the lookback period.
Calculation of Direction and Fibonacci Levels:
Moving Average Direction: Using the specified moving average, the code evaluates the price direction to determine the trend (upward or downward). This direction can be reversed if the user selects the reverse option.
Fibonacci Level Calculation: Each level is computed based on the highest and lowest prices over the lookback range and adjusted according to the selected trend direction and moving average type.
Plotting Fibonacci Levels:
The script generates lines on the chart to represent each Fibonacci level, with customizable gradient colors.
Labels displaying level values and prices can be enabled, providing easy identification of each level on the chart.
Additional Lines:
Lines representing the highest and lowest prices within the lookback range can also be displayed, highlighting recent support and resistance levels for added context.
Usage:
The Auto Fibonacci Mode indicator is designed for traders interested in Fibonacci retracement and extension levels, particularly those seeking automatic trend detection based on moving averages.
This indicator enables:
Automatic adjustment of Fibonacci levels based on selected moving average type.
Quick visualization of support and resistance areas without manual adjustments.
Analysis flexibility with customizable levels and color gradients for easier trend and reversal identification.
This tool is valuable for traders who rely on Fibonacci analysis and moving averages as part of their technical analysis strategy.
Important Note:
This script is provided for educational purposes and does not constitute financial advice. Traders and investors should conduct their research and analysis before making any trading decisions.
- Trading Bot – TopBot Anomaly LITE Robot Strategy -- Trading Bot - TopBot Anomaly LITE -
- Ready to use and automate robot strategy -
1 - Introduction
This strategy is based on a search for abnormal market price movements relative to a time-shifted basic moving average. Different variations of the basic moving average are created and shifted proportionally rather than linearly, giving the strategy greater reactivity to serve as position entry points. What's more, this strategy stands out with a major innovation, allowing position exits to be set on moving average variations (and not on the moving average itself, like all strategies that close positions on return to the moving average), which greatly improves actual results.
2 - Detailed operation of the strategy
It defines a function that calculates various moving averages (depending on the type of moving average defined by the user) and the length chosen. The function takes into account different types of moving averages: SMA, PCMA, EMA, WMA, DEMA, ZLEMA and HMA, and is offset in time so that it can be an entry or exit condition in real time. To do this, it sets up LIMIT positions which it monitors to place an order the instant the price is crossed (otherwise it would have to wait for the next candle for the moving average to be calculated).
It calculates shifted variants (“semi” parallels) as a percentage of this basic moving average, high and low, to define position entry points (depending on user settings, up to 2 shifted levels for 2 Long position entries). Because the offset is calculated as a percentage rather than a fixed value, the resulting deviations are not parallel to the basic moving average, but enable the detection of a sudden price contraction. By adjusting these deviations proportionally, we can more clearly observe variations relative to the basic moving average, enabling us to detect dynamic support and resistance zones that adapt to market fluctuations. The fact that they are not strictly parallel avoids too rigid an interpretation and gives a more nuanced reading of trends, capturing small divergences that could indicate more subtle changes in market dynamics.
The most distinctive feature of this strategy concerns position exits: the script calculates a new moving average shifted proportionally to the base moving average (adjustable) to define the position exit price level. A classic moving-average exit can also be used, leaving the deviation value at 0.
The strategy enters the position when one of the deviations from the position entry moving average is crossed, and exits the position when the deviation from the position exit moving average is crossed.
3 - “Ready to use” anduser-adjustable parameters
The strategy interface has been optimized for easy creation of trading robots, with all settings underlying the calculations and numerous options for optimization.
Here are the contents of the strategy settings interface:
Visually show/hide entry zones on the chart
Define position output deviation level (0 - 0.4%)
Define position entry deviation levels (up to 2 levels)
Define type of capital management (% available balance, % total capital or fixed amount in $)
Define the amount of each position entry (in % or $)
Define the leverage used
Define source of data used (ohlc4, open, high, low, close, hl2, hlc3, ohlc4, hlcc4)
Define type of moving average used for calculations (SMA, PCMA, EMA, WMA, DEMA, ZLEMA, HMA)
Define moving average length (period)
Define a message to be sent to a bot via the webhook for a LONG entry
Define a message to be sent to a bot via the webhook for a LONG output
Define a stoploss (optional for this type of strategy)
In addition, important information about strategy settings and results is displayed directly on the chart. The percentage profit displayed may differ slightly from that of the backtest, as it includes potential profits from open trades (strategy.openprofit) in its calculation.
4 - Chart and backtest display conditions, options and settings
Here are the conditions and settings of the graph presented on the screen:
Its result is obtained over 2 months. Position entry is in cash to balance the two entries, with 50% of capital per entry leveraged x2
L3USDT.P - BITGET - 5M - LONG - Backtest : 03/09/2024 - 09/11/2024 - CASH : 500 (1/2 Equity By Entry - x2 Leverage) - SMA Lenght : 33 – Exit Deviation : 0.004 - LONGS : 0.029 - 0.04 : Stop-Loss - 100% (none)
5 - How to adjust and apply the strategy?
Generally speaking, the strategy works well on a large proportion of cryptocurrencies. The recommended timeframes are: 5M - 15M - 30M - 45M - 1H - 2H - 3H - 4H and the most appropriate timeframe will vary according to the crypto-currency. It is also possible, with certain assets, to run the strategy on shorter timeframes such as 5M or 15M with success.
Generally speaking, if set “wide”, the winrate is usually very high and most result curves are nice and progressive, with good stability over time.
The strategy can be used with a single position entry level, maximizing the use of capital on each trade and/or having several strategies active on a single account at the same time.
It can also be used on a “safe” basis, using up to 2 successive entries to smooth out unforeseen market movements and minimize risk.
Recommended leverage is x1 or x2 for controlled long-term trading, especially with 2 levels of entries used, although sometimes higher leverage could be considered with controlled risk.
Here's how to set up the strategy:
Start by finding a cryptocurrency displaying a nice curve with the default settings. The SMA Lenght setting is very important and can vary greatly from asset to asset (between SMA 2 and SMA 80).
Then try the default settings on all timesframes, and select the timeframe with the best curve or the best result.
Set the first triggerlevel to the value that gives the best result
(optional): Change the moving average type, period and data source to find the most optimized setting before proceeding to the next step.
Set the 2nd inputlevel to the last value modifying the result.
Then set the output level, which can greatly improve the results.
Enter your bot's Enter_Long and Exit_Long commands
Create an alarm linked via webhook to your bot or trading intermediary (info below)
6 - How to program robots for automated trading using this strategy
If you want to use this strategy for automated trading, it's very simple. All you need is an account with a cryptocurrency broker that allows APIs, and an intermediary between TradinView and your broker who will manage your orders.
Here's how it works:
On your intermediary, create a bot that will manage the details of your orders (amount, single or multiple entries, exit conditions). This bot is linked to the broker via an API and will be able to place real orders. Each bot has four different signals that enable it to be activated via a webhook. When one of the signals is received, it executes the orders for you.
On TradingView, set the strategy to a suitable asset and timeframe. Once set, enter in the strategy parameters the signals specific to the bot you've created. Confirm and close the parameters.
Still on TradingView, create an alarm based on your set strategy (on the strategy tester). Give the alarm the name of your choice and in “Message” enter only{{strategy.order.comment}}.
In alarm notifications, activate the webhook and enter the webhook of your trading intermediary. Confirm the alarm.
As long as the alarm is activated in TradingView, the strategy will monitor the market and send an order to enter or exit a position as soon as the conditions are met. Your bot will receive the instruction and place orders with your broker. Subsequent changes to the strategy settings do not change those stored in the alarm. If you wish to change the settings for one of your bots, simply delete the old alarm and create a new one.
Note: In your bot settings, on your intermediary, make sure to allow: - Multiple entries - A single exit signal to close all positions - Stoploss disabled (if necessary, use the strategy one)
Happy automated trading!
ATAMOKU: A Hierarchical Scoring Tool Based on Ichimoku Principle
Overview and Purpose of ATAMOKU
The name "ATAMOKU" combines “Ata” (meaning “ancestor” in Turkish) and “Moku” (meaning “cloud” in Japanese). ATAMOKU is built on Ichimoku principles, designed to assist traders in analyzing trend direction and strength. By providing a structured, score-based approach, ATAMOKU aims to make Ichimoku data more accessible for identifying potential entry and exit points.
How ATAMOKU Works
ATAMOKU uses Ichimoku’s essential elements—including the Conversion Line (Tenkan-sen), Base Line (Kijun-sen), and Leading Spans A and B—and applies a scoring hierarchy to assess market conditions. The scoring system measures trend strength and alignment by comparing the relationships between these elements. This method allows ATAMOKU to produce an objective score that reflects whether the market is in an “ideal” or “non-ideal” state.
Key Features of ATAMOKU
1 - Hierarchy-Based Scoring System:
ATAMOKU calculates a score that represents the strength and direction of the current trend. Each component of Ichimoku is assigned a weight, and the indicator scores these components based on their hierarchical position. When all components align for an upward trend, ATAMOKU’s score will approach +364 (representing an ideal state). In contrast, a score of -364 indicates a non-ideal or bearish alignment.
2 - Optimal and Suboptimal Tracking:
ATAMOKU includes Optimal and Suboptimal markers to track the highest and lowest scores over a specific period, with a default of 52 periods. The Optimal score captures the highest recorded value within the period, while the Suboptimal score captures the lowest. These markers help traders gauge how current conditions compare to recent peaks and troughs, indicating market stability or volatility.
3 - Real-Time Scoring Display (Hierarchy Table):
ATAMOKU uses a Hierarchy Table adjacent to the main chart to present real-time scoring data for each Ichimoku component. This table displays values for Conversion Line, Base Line, Leading Spans, and Lagging Span, providing traders with a detailed view of each component’s contribution to the total score. By referencing the table, traders can understand the weight and impact of each Ichimoku element on the overall score.
4 - Histogram Visualization:
ATAMOKU’s scores are displayed on a histogram with green and red bars to indicate market sentiment. Green bars represent bullish conditions, while red bars indicate bearish conditions. This visual format allows traders to quickly assess trend direction and strength at a glance, providing context for decision-making.
5 - Signal and Smoothing Lines:
To help reduce noise, ATAMOKU features Signal and Smooth lines, which can be customized using different smoothing methods (such as SMA, EMA, or WMA). When the Signal and Smooth lines cross, the indicator will label the trend as UP or DOWN based on the direction of the crossover. This feature helps traders detect potential reversals or trend confirmations.
6 - Adjustable Settings:
* Scoring Weights: Traders can configure the relative weights of each Ichimoku component to match their analysis preferences.
* Smoothing Techniques: Users may choose from SMA, EMA, and WMA smoothing methods to adjust signal sensitivity.
* Period Adjustments: Scoring and smoothing period lengths can be customized to fit various trading styles and time frames.
Intended Use and Practical Application
ATAMOKU is best used alongside the Ichimoku Cloud, as its scoring and signal features complement the visual data provided by Ichimoku. The Hierarchy Score, combined with Optimal/Suboptimal markers, gives traders insight into the current market conditions and allows for comparisons across time. ATAMOKU is adaptable to any time frame and provides both trend analysis and potential entry/exit signals based on Ichimoku principles.
Legal Disclaimer
ATAMOKU is a technical analysis tool and does not guarantee profitability. It is designed to aid in decision-making by providing additional market insights. Traders are encouraged to exercise their judgment and assume responsibility for their trading actions.
Anchored Average Trading PriceThis "Anchored Average Trading Price" indicator allows users to anchor the calculation of the average trading price to a specific candle. By selecting an anchor date and time, the indicator begins calculating the average trading price from that point forward. This tool is particularly helpful for traders who want to analyze the price action relative to a key event or a particular point in time on the chart.
Key Features:
1. Flexible Anchoring: The indicator lets you set an anchor time, which determines the specific candle from which the average trading price calculation starts.
2. Customizable Calculation Method: You have the option to choose the basis of the average calculation:
- Open Price
- Close Price
- Average Daily Traded Price (calculated as `(Open + High + Low + Close) / 4`)
3. Automatic Updating: Once the anchor is set, the indicator dynamically updates on each new candle to continuously reflect the average trading price since the anchor point.
Potential Uses and Functionality Expansions:
- Trend Analysis: By observing the average trading price over time, you can gauge market sentiment and track trends from a particular event or time in the market.
- Support and Resistance: Anchoring this indicator to major highs, lows, or significant events could help identify dynamic support and resistance levels as the market interacts with the average price line.
- Customization Options: Future updates could allow additional flexibility, such as:
- A reset feature for users to easily re-anchor without changing the timestamp.
- Additional price calculation methods, like VWAP (Volume Weighted Average Price) for volume-based insights.
- Alerts when price crosses above or below the anchored average, signaling potential entry or exit points.
MERCURY by DrAbhiramSivprasad"MERCURY by DrAbhiramSivprasad"
Developed from over 10 years of personal trading experience, the Mercury Indicator is a strategic tool designed to enhance accuracy in trading decisions. Think of it as a guiding light—a supportive tool that helps traders refine and build more robust strategies by integrating multiple powerful elements into a single indicator. I’ll be sharing some examples to illustrate how I use this indicator in my own trading journey, highlighting its potential to improve strategy accuracy.
Reason behind the combination of emas , cpr and vwap is it provides very good support and resistance in my trading carrier so now i brought them together in one plate
How It Works:
Mercury combines three essential elements—EMA, VWAP, and CPR—each of which plays a vital role in detecting support and resistance:
Exponential Moving Averages (EMAs): Known for their strength in providing dynamic support and resistance levels, EMAs help in identifying trends and shifts in momentum. This indicator includes a dashboard with up to nine customizable EMAs, showing whether each is acting as support or resistance based on real-time price movement.
Volume Weighted Average Price (VWAP): VWAP also provides valuable support and resistance, often regarded as a fair price level by institutional traders. Paired with EMAs, it forms a dual-layered support/resistance system, adding an additional level of confirmation.
Central Pivot Range (CPR): By combining CPR with EMAs and VWAP, Mercury highlights “traffic blocks” in your target journey. This means it identifies zones where price is likely to stall or reverse, providing additional guidance for navigating entries and exits.
Why This Combination Matters:
Using these three tools together gives you a more complete view of the market. VWAP and EMAs offer dynamic trend direction and support/resistance, while CPR pinpoints critical price zones. This combination helps you find high-probability trades, adding clarity to complex market situations and enabling stronger confirmation on trend or reversal decisions.
How to Use:
Trend Confirmation: Check if all EMAs are aligned (green for uptrend, red for downtrend), which is visible in the EMA dashboard. An alignment across VWAP, CPR, and EMAs signifies high confidence in trend direction.
Breakouts & Breakdowns: Mercury has an alert system to signal when a price breakout or breakdown occurs across VWAP, EMA1, and EMA2. This can help in spotting strong directional moves.
Example Application: In my trading, I use Mercury to identify support/resistance zones, confirming trends with EMA/VWAP alignment and using CPR as a checkpoint. I find this especially useful for day trading and swing setups.
Recommended Timeframes:
Day Trading: 5 to 15-minute charts for swift, actionable insights.
Swing Trading: 1-hour or 4-hour charts for broader trend analysis.
Note:
The Mercury Indicator should be used as a supportive tool rather than a standalone strategy, guiding you toward informed decisions in line with your trading style and goals.
EXAMPLE OF TRADE
you can see the cart of XAUUSD on 11th nov 2024
1.SHORT POSITION - TIME FRAME 15 MIN
So here for a short position you need to wait for a breakdown candle which will print in orange post the candle you need to check ema dashboard is completly red that indicates no traffic blocks in your journey to destiny target from ema's and you can take the target from nearest cpr support line
TAKEN IN XAUUSD you can see in chart of XAUUSD on 7th nov
2.LONG POSITION - TIME FRAME 15 MIN -
So here for long position you need to wait for a breakout candle from indicator thats here is blue and check all ema boxes are green and candle body should close above all the 3 lines here it is the both ema 1 and 2 and the vwap line then you can take and entry and your target will be the nearest resistance from the daily cpr
3. STOP LOSS CRITERIA
After the entry any candle close below any of the last line from entry for example we have 3 lines vwap and ema 1 and 2 lines and u have made an entry and the last line before the entry is vwap then if any candle closes below vwap can be considered as stoploss like wise in any lines
The MERCURY indicator is a comprehensive trading tool designed to enhance traders' ability to identify trends, breakouts, and reversals effectively. Created by Dr. Abhiram Sivprasad, this indicator integrates several technical elements, including Central Pivot Range (CPR), EMA crossovers, VWAP levels, and a table-based EMA dashboard, to offer a holistic trading view.
Core Components and Functionality:
Central Pivot Range (CPR):
The CPR in MERCURY provides a central pivot level along with Below Central (BC) and Top Central (TC) pivots. These levels act as potential support and resistance, useful for identifying reversal points and zones where price may consolidate.
Exponential Moving Averages (EMAs):
MERCURY includes up to nine EMAs, with a customizable EMA crossover alert system. This feature enables traders to see shifts in trend direction, especially when shorter EMAs cross longer ones.
VWAP (Volume-Weighted Average Price):
VWAP is incorporated as a dynamic support/resistance level and, combined with EMA crossovers, helps refine entry and exit points for higher probability trades.
Breakout and Breakdown Alerts:
MERCURY monitors conditions for upside and downside breakouts. For an upside breakout, all EMAs turn green and a candle closes above VWAP, EMA1, and EMA2. Similarly, all EMAs turning red, combined with a close below VWAP and EMA1/EMA2, signals a downside breakdown. Continuous alerts are available until the trend shifts.
Real-Time EMA Dashboard:
A table displays each EMA’s relative position (Above or Below), helping traders quickly gauge trend direction. Colors in the table adjust to long/short conditions based on EMA alignment.
Usage Recommendations:
Trend Confirmation:
Use the CPR, EMA alignments, and VWAP to confirm uptrends and downtrends. The table highlights trends, making it easy to spot long or short setups at a glance.
Breakout and Breakdown Alerts:
The alert system is customizable for continuous notifications on critical price levels. When all EMAs align in one direction (green for long, red for short) and the close is above or below VWAP and key EMAs, the indicator confirms a breakout/breakdown.
Adaptable for Different Styles:
Day Trading: Traders can set shorter EMAs for quick insights.
Swing Trading: Longer EMAs combined with CPR offer insights into sustained trends.
Recommended Settings:
Timeframes: MERCURY is suitable for timeframes as low as 5 minutes for intraday traders, up to daily charts for trend analysis.
Symbols: Works across forex, stocks, and crypto. Adjust EMA lengths for asset volatility.
Example Strategy:
Long Entry: When the price crosses above CPR and closes above both EMA1 and EMA2.
Short Entry: When the price falls below CPR with a close below both EMA1 and EMA2.
GeoMean+The Geometric Moving Average (GMA) with Sigma Bands is a technical indicator that combines trend following and volatility measurement. The blue center line represents the GMA, while the upper and lower bands (light blue) show price volatility using standard deviations (sigma). Traders can use this indicator for both trend following and mean reversion strategies. For trend following, enter long when price crosses above the GMA and short when it crosses below, using the bands as profit targets. For mean reversion, look for buying opportunities when price touches the lower band and selling opportunities at the upper band, with the GMA as your profit target. The indicator includes alerts for band touches and crosses, providing real-time notifications with symbol, timeframe, current price, and band level information. The default 100-period setting works well for daily charts, but can be adjusted shorter (20-50) for intraday trading or longer (200+) for position trading. Wider bands indicate higher volatility (use smaller positions), while narrower bands suggest lower volatility (larger positions possible). For best results, confirm signals with volume and avoid trading against strong trends. Stop losses can be placed beyond the touched band or at the GMA line, depending on your risk tolerance.
Advanced Bitcoin Trend Following StrategyTitle: Bitcoin Multi-Factor Trend Following Strategy
Description:
The Bitcoin Multi-Factor Trend Following Strategy is designed for traders seeking a robust, multi-factor approach to trend following in Bitcoin markets. This script combines technical indicators and statistical methods to identify trend directions, optimize entry and exit points, and manage position sizing based on volatility and leverage constraints. Key features of the strategy include:
Multi-Indicator Trend Forecasting:
This strategy employs three trend forecasting methods: range, exponential moving average (EMA), and Bollinger Bands. Each method can be independently enabled or disabled, giving traders flexibility in how trends are identified and followed.
Range Forecast : Calculates forecast based on the range (high and low) of recent prices, with optional smoothing via a Kalman filter to reduce noise.
EMA Spread Forecast : Utilizes the spread between fast and slow EMAs to gauge the trend’s strength, adjusted for volatility.
Bollinger Band Forecast : Measures the proximity of price to Bollinger Band levels to assess trend intensity.
Kalman Filter for Smoothing:
The Kalman filter is applied to price data for smoother trend estimation, particularly within the range forecast. This allows the strategy to reduce noise and focus on more reliable price signals.
Volatility-Adjusted Position Sizing:
The strategy incorporates volatility targeting to dynamically adjust position sizes based on current market conditions. Traders can set an annualized volatility target to control the risk level, with position size scaled accordingly to maintain consistent risk exposure. A maximum leverage cap ensures that position sizes do not exceed a user-defined threshold, offering an additional layer of risk control.
Dynamic Entry and Exit Points:
Entry and exit points are based on customizable thresholds that determine trend strength and are sensitive to market volatility. The script monitors changes in forecast values and automatically adjusts trades to capitalize on emerging trends or exit weakening ones. The strategy includes an option to close all open positions when trend forecasts fall below defined thresholds, ensuring an automated approach to risk management.
Backtesting and Performance Metrics:
To support strategy optimization, the script includes a backtest mode that calculates key performance metrics such as Sharpe Ratio, Buy & Hold profit, Strategy profit, Win rate, and other metrics. These metrics are displayed in a summary table directly on the chart, providing real-time insight into the strategy’s historical performance compared to a buy-and-hold approach.
Configurable Time and Date Range:
Users can specify start and end dates for the backtest period, allowing for focused backtesting over any desired timeframe. This feature enables in-depth analysis of performance across varying market conditions.
Use Case:
This strategy is best suited for experienced traders who wish to apply a structured trend-following approach in Bitcoin or other high-volatility assets. It is highly customizable, making it adaptable to various market conditions and trading styles. The combination of trend forecasting methods, volatility targeting, and automatic leverage control offers a balanced approach to capturing long-term trends while managing risk.
Parameters:
Entry Threshold: Adjusts the sensitivity of the entry point for trends. Lower values make the strategy more reactive.
Annual Volatility Target: Controls the risk level by targeting a specific annualized volatility percentage.
Max Leverage: Caps the allowable leverage for each trade.
Forecast Activations: Toggles to enable or disable the use of range, EMA, and Bollinger forecasts.
Date Range: Allows users to define the start and end dates for testing the strategy.
Notes:
This strategy is designed for educational purposes and requires thorough backtesting and optimization before live trading. Real-time performance may vary, and additional risk management practices are advised.
License:
This script is subject to the terms of the Mozilla Public License 2.0.
TrigWave Suite [InvestorUnknown]The TrigWave Suite combines Sine-weighted, Cosine-weighted, and Hyperbolic Tangent moving averages (HTMA) with a Directional Movement System (DMS) and a Relative Strength System (RSS).
Hyperbolic Tangent Moving Average (HTMA)
The HTMA smooths the price by applying a hyperbolic tangent transformation to the difference between the price and a simple moving average. It also adjusts this value by multiplying it by a standard deviation to create a more stable signal.
// Function to calculate Hyperbolic Tangent
tanh(x) =>
e_x = math.exp(x)
e_neg_x = math.exp(-x)
(e_x - e_neg_x) / (e_x + e_neg_x)
// Function to calculate Hyperbolic Tangent Moving Average
htma(src, len, mul) =>
tanh_src = tanh((src - ta.sma(src, len)) * mul) * ta.stdev(src, len) + ta.sma(src, len)
htma = ta.sma(tanh_src, len)
Sine-Weighted Moving Average (SWMA)
The SWMA applies sine-based weights to historical prices. This gives more weight to the central data points, making it responsive yet less prone to noise.
// Function to calculate the Sine-Weighted Moving Average
f_Sine_Weighted_MA(series float src, simple int length) =>
var float sine_weights = array.new_float(0)
array.clear(sine_weights) // Clear the array before recalculating weights
for i = 0 to length - 1
weight = math.sin((math.pi * (i + 1)) / length)
array.push(sine_weights, weight)
// Normalize the weights
sum_weights = array.sum(sine_weights)
for i = 0 to length - 1
norm_weight = array.get(sine_weights, i) / sum_weights
array.set(sine_weights, i, norm_weight)
// Calculate Sine-Weighted Moving Average
swma = 0.0
if bar_index >= length
for i = 0 to length - 1
swma := swma + array.get(sine_weights, i) * src
swma
Cosine-Weighted Moving Average (CWMA)
The CWMA uses cosine-based weights for data points, which produces a more stable trend-following behavior, especially in low-volatility markets.
f_Cosine_Weighted_MA(series float src, simple int length) =>
var float cosine_weights = array.new_float(0)
array.clear(cosine_weights) // Clear the array before recalculating weights
for i = 0 to length - 1
weight = math.cos((math.pi * (i + 1)) / length) + 1 // Shift by adding 1
array.push(cosine_weights, weight)
// Normalize the weights
sum_weights = array.sum(cosine_weights)
for i = 0 to length - 1
norm_weight = array.get(cosine_weights, i) / sum_weights
array.set(cosine_weights, i, norm_weight)
// Calculate Cosine-Weighted Moving Average
cwma = 0.0
if bar_index >= length
for i = 0 to length - 1
cwma := cwma + array.get(cosine_weights, i) * src
cwma
Directional Movement System (DMS)
DMS is used to identify trend direction and strength based on directional movement. It uses ADX to gauge trend strength and combines +DI and -DI for directional bias.
// Function to calculate Directional Movement System
f_DMS(simple int dmi_len, simple int adx_len) =>
up = ta.change(high)
down = -ta.change(low)
plusDM = na(up) ? na : (up > down and up > 0 ? up : 0)
minusDM = na(down) ? na : (down > up and down > 0 ? down : 0)
trur = ta.rma(ta.tr, dmi_len)
plus = fixnan(100 * ta.rma(plusDM, dmi_len) / trur)
minus = fixnan(100 * ta.rma(minusDM, dmi_len) / trur)
sum = plus + minus
adx = 100 * ta.rma(math.abs(plus - minus) / (sum == 0 ? 1 : sum), adx_len)
dms_up = plus > minus and adx > minus
dms_down = plus < minus and adx > plus
dms_neutral = not (dms_up or dms_down)
signal = dms_up ? 1 : dms_down ? -1 : 0
Relative Strength System (RSS)
RSS employs RSI and an adjustable moving average type (SMA, EMA, or HMA) to evaluate whether the market is in a bullish or bearish state.
// Function to calculate Relative Strength System
f_RSS(rsi_src, rsi_len, ma_type, ma_len) =>
rsi = ta.rsi(rsi_src, rsi_len)
ma = switch ma_type
"SMA" => ta.sma(rsi, ma_len)
"EMA" => ta.ema(rsi, ma_len)
"HMA" => ta.hma(rsi, ma_len)
signal = (rsi > ma and rsi > 50) ? 1 : (rsi < ma and rsi < 50) ? -1 : 0
ATR Adjustments
To minimize false signals, the HTMA, SWMA, and CWMA signals are adjusted with an Average True Range (ATR) filter:
// Calculate ATR adjusted components for HTMA, CWMA and SWMA
float atr = ta.atr(atr_len)
float htma_up = htma + (atr * atr_mult)
float htma_dn = htma - (atr * atr_mult)
float swma_up = swma + (atr * atr_mult)
float swma_dn = swma - (atr * atr_mult)
float cwma_up = cwma + (atr * atr_mult)
float cwma_dn = cwma - (atr * atr_mult)
This adjustment allows for better adaptation to varying market volatility, making the signal more reliable.
Signals and Trend Calculation
The indicator generates a Trend Signal by aggregating the output from each component. Each component provides a directional signal that is combined to form a unified trend reading. The trend value is then converted into a long (1), short (-1), or neutral (0) state.
Backtesting Mode and Performance Metrics
The Backtesting Mode includes a performance metrics table that compares the Buy and Hold strategy with the TrigWave Suite strategy. Key statistics like Sharpe Ratio, Sortino Ratio, and Omega Ratio are displayed to help users assess performance. Note that due to labels and plotchar use, automatic scaling may not function ideally in backtest mode.
Alerts and Visualization
Trend Direction Alerts: Set up alerts for long and short signals
Color Bars and Gradient Option: Bars are colored based on the trend direction, with an optional gradient for smoother visual feedback.
Important Notes
Customization: Default settings are experimental and not intended for trading/investing purposes. Users are encouraged to adjust and calibrate the settings to optimize results according to their trading style.
Backtest Results Disclaimer: Please note that backtest results are not indicative of future performance, and no strategy guarantees success.
Cross-Asset Correlation Trend IndicatorCross-Asset Correlation Trend Indicator
This indicator uses correlations between the charted asset and ten others to calculate an overall trend prediction. Each ticker is configurable, and by analyzing the trend of each asset, the indicator predicts an average trend for the main asset on the chart. The strength of each asset's trend is weighted by its correlation to the charted asset, resulting in a single average trend signal. This can be a rather robust and effective signal, though it is often slow.
Functionality Overview :
The Cross-Asset Correlation Trend Indicator calculates the average trend of a charted asset based on the correlation and trend of up to ten other assets. Each asset is assigned a trend signal using a simple EMA crossover method (two customizable EMAs). If the shorter EMA crosses above the longer one, the asset trend is marked as positive; if it crosses below, the trend is negative. Each trend is then weighted by the correlation coefficient between that asset’s closing price and the charted asset’s closing price. The final output is an average weighted trend signal, which combines each trend with its respective correlation weight.
Input Parameters :
EMA 1 Length : Sets the period of the shorter EMA used to determine trends.
EMA 2 Length : Sets the period of the longer EMA used to determine trends.
Correlation Length : Defines the lookback period used for calculating the correlation between the charted asset and each of the other selected assets.
Asset Tickers : Each of the ten tickers is configurable, allowing you to set specific assets to analyze correlations with the charted asset.
Show Trend Table : Toggle to show or hide a table with each asset’s weighted trend. The table displays green, red, or white text for each weighted trend, indicating positive, negative, or neutral trends, respectively.
Table Position : Choose the position of the trend table on the chart.
Recommended Use :
As always, it’s essential to backtest the indicator thoroughly on your chosen asset and timeframe to ensure it aligns with your strategy. Feel free to modify the input parameters as needed—while the defaults work well for me, they may need adjustment to better suit your assets, timeframes, and trading style.
As always, I wish you the best of luck and immense fortune as you develop your systems. May this indicator help you make well-informed, profitable decisions!
Supertrend EMA & KNNSupertrend EMA & KNN
The Supertrend EMA indicator cuts through the noise to deliver clear trend signals.
This tool is built using the good old Exponential Moving Averages (EMAs) with a novel of machine learning; KNN (K Nearest Neighbors) breakout detection method.
Key Features:
Effortless Trend Identification: Supertrend EMA simplifies trend analysis by automatically displaying a color-coded EMA. Green indicates an uptrend, red signifies a downtrend, and the absence of color suggests a potential range.
Dynamic Breakout Detection: Unlike traditional EMAs, Supertrend EMA incorporates a KNN-based approach to identify breakouts. This allows for faster color changes compared to standard EMAs, offering a more dynamic picture of the trend.
Customizable Parameters: Fine-tune the indicator to your trading style. Adjust the EMA length for trend smoothing, KNN lookback window for breakout sensitivity, and breakout threshold for filtering noise.
A Glimpse Under the Hood:
Dual EMA Power: The indicator utilizes two EMAs. A longer EMA (controlled by the "EMA Length" parameter) provides a smooth trend direction, while a shorter EMA (controlled by the "Short EMA Length" parameter) triggers color changes, aiming for faster response to breakouts.
KNN Breakout Detection: This innovative feature analyzes price action over a user-defined lookback period (controlled by the "KNN Lookback Length" parameter) to identify potential breakouts. If the price surpasses a user-defined threshold (controlled by the "Breakout Threshold" parameter) above the recent highs, a green color is triggered, signaling a potential uptrend. Conversely, a breakdown below the recent lows triggers a red color, indicating a potential downtrend.
Trading with Supertrend EMA:
Ride the Trend: When the indicator displays green, look for long (buy) opportunities, especially when confirmed by bullish price action patterns on lower timeframes. Conversely, red suggests potential shorting (sell) opportunities, again confirmed by bearish price action on lower timeframes.
Embrace Clarity: The color-coded EMA provides a clear visual representation of the trend, allowing you to focus on price action and refine your entry and exit strategies.
A Word of Caution:
While Supertrend EMA offers faster color changes than traditional EMAs, it's important to acknowledge a slight inherent lag. Breakout detection relies on historical data, and there may be a brief delay before the color reflects a new trend.
To achieve optimal results, consider:
Complementary Tools: Combine Supertrend EMA with other indicators or price action analysis for additional confirmation before entering trades.
Solid Risk Management: Always practice sound risk management strategies such as using stop-loss orders to limit potential losses.
Supertrend EMA is a powerful tool designed to simplify trend identification and enhance your trading experience. However, remember, no single indicator guarantees success. Use it with a comprehensive trading strategy and disciplined risk management for optimal results.
Disclaimer:
While the Supertrend EMA indicator can be a valuable tool for identifying potential trend changes, it's important to note that it's not infallible. Market conditions can be highly dynamic, and indicators may sometimes provide false signals. Therefore, it's crucial to use this indicator in conjunction with other technical analysis tools and sound risk management practices. Always conduct thorough research and consider consulting with a financial advisor before making any investment decisions.
Power Core MAThe Power Core MA indicator is a powerful tool designed to identify the most significant moving average (MA) in a given price chart. This indicator analyzes a wide range of moving averages, from 50 to 400 periods, to determine which one has the strongest influence on the current price action.
The blue line plotted on the chart represents the "Current Core MA," which is the moving average that is most closely aligned with other nearby moving averages. This line indicates the current trend and potential support or resistance levels.
The table displayed on the chart provides two important pieces of information. The "Current Core MA" value shows the length of the moving average that is currently most influential. The "Historical Core MA" value represents the average length of the most influential moving averages over time.
This indicator is particularly useful for traders and analysts who want to identify the most relevant moving average for their analysis. By focusing on the moving average that has the strongest historical significance, users can make more informed decisions about trend direction, support and resistance levels, and potential entry or exit points.
The Power Core MA is an excellent tool for those interested in finding the strongest moving average in the price history. It simplifies the process of analyzing multiple moving averages by automatically identifying the most influential one, saving time and providing valuable insights into market dynamics.
By combining current and historical data, this indicator offers a comprehensive view of the market's behavior, helping traders to adapt their strategies to the most relevant timeframes and trend strengths.
Trade Mavrix: Elite Trade NavigatorYour ultimate trading companion that helps you spot profitable breakouts, perfect pullbacks, and crucial support & resistance levels. Ready to take your trading to the next level? Let's dive in!
Adaptive ema Cloud v1 Trend & Trade Signals"adaptive ema cloud v1 trend & trade signals" is a comprehensive technical indicator aimed at assisting traders in identifying market trends, trade entry points, and potential take profit (tp) and stop-loss (sl) levels. this indicator combines adaptive exponential moving average (ema) clouds with standard deviation bands to create a visual trend and signal system, enabling users to better analyze price action.
key features:
adaptive ema cloud: calculates a dynamic ema-based cloud using a simple moving average (sma) line, with upper and lower deviation bands based on standard deviations. users can adjust the standard deviation multiplier to modify the cloud's width.
trend direction detection: the indicator determines trend direction by comparing the close price to the ema cloud and signals bullish or bearish trends when the price crosses key levels.
take profit (tp) and stop-loss (sl) points: adaptive tp and sl levels are calculated based on the deviation bands, providing users with suggested exit points when a trade is triggered.
peak and valley detection: detects peaks and valleys in price, aiding traders in spotting potential support and resistance areas.
gradient-based cloud fill: dynamically fills the cloud with a gradient color based on trend strength, helping users visually gauge trend intensity.
trade tracking: tracks recent trades and records them in an internal memory, allowing users to view the last 20 trade outcomes, including whether tp or sl was hit.
how to use:
trend signals: look for green arrows (bullish trend) or red arrows (bearish trend) to identify potential entries based on trend crossovers.
tp/sl management: tp and sl levels are automatically calculated and displayed, with alerts available to notify users when these levels are reached.
adjustable settings: customize period length, standard deviation multiplier, and color preferences to match trading preferences and chart style.
inputs-
period: defines the look-back period for ema calculations.
standard deviation multiplier: adjusts cloud thickness by setting the multiplier for tp and sl bands.
gauge size: scales the gradient intensity for trend cloud visualization.
up/down colors: allows users to set custom colors for bullish and bearish bars.
alert conditions: this script has built-in alerts for trend changes, tp, and sl levels, providing users with automated notifications of important trading signals.
