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LOWESS (Locally Weighted Scatterplot Smoothing) [ChartPrime]LOWESS (Locally Weighted Scatterplot Smoothing) ⯁ OVERVIEW The LOWESS (Locally Weighted Scatterplot Smoothing) [ ChartPrime ] indicator is an advanced technical analysis tool that combines LOWESS smoothing with a Modified Adaptive Gaussian Moving Average. This indicator provides traders with a sophisticated method for trend analysis, pivot point identification, and breakout detection. ◆ KEY FEATURES LOWESS Smoothing: Implements Locally Weighted Scatterplot Smoothing for trend analysis. Modified Adaptive Gaussian Moving Average: Incorporates a volatility-adapted Gaussian MA for enhanced trend detection. Pivot Point Identification: Detects and visualizes significant pivot highs and lows. Breakout Detection: Tracks and optionally displays the count of consecutive breakouts. Gaussian Scatterplot: Offers a unique visualization of price movements using randomly colored points. Customizable Parameters: Allows users to adjust calculation length, pivot detection, and visualization options. ◆ FUNCTIONALITY DETAILS ⬥ LOWESS Calculation: Utilizes a weighted local regression to smooth price data. Adapts to local trends, reducing noise while preserving important price movements. ⬥ Modified Adaptive Gaussian Moving Average: Combines Gaussian weighting with volatility adaptation using ATR and standard deviation. Smooths the Gaussian MA using LOWESS for enhanced trend visualization. ⬥ Pivot Point Detection and Visualization: Identifies pivot highs and lows using customizable left and right bar counts. Draws lines and labels to mark broke pivot points on the chart. ⬥ Breakout Tracking: Monitors price crossovers of pivot lines to detect breakouts. Optionally displays and updates the count of consecutive breakouts. ◆ USAGE Trend Analysis: Use the color and direction of the smoothed Gaussian MA line to identify overall trend direction. Breakout Trading: Monitor breakouts from pivot levels and their persistence using the breakout count feature. Volatility Assessment: The spread of the Gaussian scatterplot can provide insights into market volatility. ⯁ USER INPUTS Length: Sets the lookback period for LOWESS and Gaussian MA calculations (default: 30). Pivot Length: Determines the number of bars to the left for pivot calculation (default: 5). Count Breaks: Toggle to show the count of consecutive breakouts (default: false). Gaussian Scatterplot: Toggle to display the Gaussian MA as a scatterplot (default: true). ⯁ TECHNICAL NOTES Implements a custom LOWESS function for efficient local regression smoothing. Uses a modified Gaussian MA calculation that adapts to market volatility. Employs Pine Script's line and label drawing capabilities for clear pivot point visualization. Utilizes random color generation for the Gaussian scatterplot to enhance visual distinction between different time periods. The LOWESS (Locally Weighted Scatterplot Smoothing) indicator offers traders a sophisticated tool for trend analysis and breakout detection. By combining advanced smoothing techniques with pivot point analysis, it provides a comprehensive view of market dynamics. The indicator's adaptability to different market conditions and its customizable nature make it suitable for various trading styles and timeframes.
مؤشرات Pine Script™
من ‎ChartPrime‎
19
Brooks Always In [KintsugiTrading]Brooks Always In Overview: The "Brooks Always In Indicator" by KintsugiTrading is a tool designed for traders who follow price action methodologies inspired by Al Brooks. This indicator identifies key bar patterns and breakouts, plots an Exponential Moving Average (EMA), and highlights consecutive bullish and bearish bars. It is intended to assist traders in making informed decisions based on price action dynamics. Features: Consecutive Bar Patterns: Identifies and highlights consecutive bullish and bearish bars. Differentiates between bars that are above/below the EMA and those that are not. Customizable EMA: Option to display an Exponential Moving Average (EMA) with user-defined length and offset. The EMA can be smoothed using various methods such as SMA, EMA, SMMA (RMA), WMA, and VWMA. Breakout Patterns: Recognizes bullish and bearish breakout bars and outside bars. Tracks inside bars and prior bar conditions to better understand the market context. Customizable Display: Users can display or hide the EMA, consecutive bar patterns, and consecutive bars relative to the moving average. How to Use: Customize Settings: First, I like to navigate to the top right corner of the chart (bolt icon), and change both the bull and bear body color to match the background (white/black) - this helps the user visualize the indicator far better. Next, Toggle to display EMA, consecutive bar patterns, and consecutive bars relative to the moving average using the provided input options. Adjust the EMA length, source, and offset as per your trading strategy. Select the smoothing method and length for the EMA if desired. Analyze Key Patterns: Observe the highlighted bars on the chart to identify consecutive bullish and bearish patterns. Use the plotted EMA to gauge the general trend and analyze the relationship between price bars and the moving average. Informed Decision Making: Utilize the identified bar patterns and breakouts to make informed trading decisions, such as identifying potential entry and exit points based on price action dynamics. Good luck with your trading!
مؤشرات Pine Script™
من ‎KintsugiTrading‎
Trend LinesThis script, titled "Trend Lines," is designed to detect and plot significant trend lines on a TradingView chart, based on pivot points. It highlights both uptrend and downtrend lines using different colors and allows customization of line styles, including color and thickness. Here's a breakdown of how the script works: Inputs Left Bars (lb) and Right Bars (rb): These inputs determine the number of bars to the left and right of a pivot point used to identify significant highs and lows. Show Pivot Points: A boolean input to display markers at detected pivot points on the chart. Show Old Line as Dashed: A boolean input to display older trend lines as dashed for visual distinction. Uptrend Line Color (ucolor) and Downtrend Line Color (dcolor): Color inputs to customize the appearance of uptrend and downtrend lines. Uptrend Line Thickness (uthickness) and Downtrend Line Thickness (dthickness): Inputs to adjust the thickness of the trend lines. Calculations Pivot Highs and Lows: The script calculates potential pivot highs and lows by looking at lb bars to the left and rb bars to the right. If a bar's high is the highest (or low is the lowest) within this window, it is considered a pivot point. Trend Lines: The script connects the most recent and previous pivot highs to form downtrend lines, and the most recent and previous pivot lows to form uptrend lines. These lines are drawn with the specified color and thickness. Angles: The angle of each trend line is calculated to determine whether the trend is strengthening or weakening. If the trend changes significantly, the line's extension is adjusted accordingly. Plotting Pivot Point Markers: If Show Pivot Points is enabled, markers labeled "H" for highs and "L" for lows are plotted at the pivot points. Trend Lines: The script draws lines between pivot points, coloring them according to the trend direction (uptrend or downtrend). If Show Old Line as Dashed is enabled, the script sets older lines to a dashed style to indicate they are no longer the most recent trend lines. This script is useful for traders who want to visually identify key support and resistance levels based on historical price action, helping them to make more informed trading decisions. The customization options allow traders to tailor the appearance of the trend lines to suit their personal preferences or charting style.
مؤشرات Pine Script™
من ‎TommyCarey‎
4
OrderBlock Trend (CISD)OrderBlock Trend (CISD) Indicator Overview: The "OrderBlock Trend (CISD)" AKA: change in state of delivery by ICT inner circle trader this indicator is designed to help traders identify and visualize market trends based on higher timeframe candle behavior. This script leverages the concept of order blocks, which are price levels where significant buying or selling activity has occurred, to signal potential trend reversals or continuations. By analyzing bullish and bearish order blocks on a higher timeframe, the indicator provides visual cues and statistical insights into the market's current trend dynamics. Key Features: Higher Timeframe Analysis: The indicator uses a higher timeframe (e.g., Daily) to assess the trend direction based on the open and close prices of candles. This approach helps in identifying more significant and reliable trend changes, filtering out noise from lower timeframes. Bullish and Bearish Order Blocks: The script detects the first bullish or bearish candle on the selected higher timeframe and uses these candles as reference points (order blocks) to determine the trend direction. A bullish trend is indicated when the current price is above the last bearish order block's open price, and a bearish trend is indicated when the price is below the last bullish order block's open price. Visual Trend Indication: The indicator visually represents the trend using background colors and plot shapes: A green background and a square shape above the bars indicate a bullish trend. A red background and a square shape above the bars indicate a bearish trend. Candle Count and Statistics: The script keeps track of the number of up and down candles during bullish and bearish trends, providing percentages of up and down candles in each trend. This data is displayed in a table, giving traders a quick overview of market sentiment during each trend phase. User Customization: The higher timeframe can be adjusted according to the trader's preference, allowing flexibility in trend analysis based on different time horizons. Concepts and Calculations: The "OrderBlock Trend (CISD)" indicator is based on the concept of order blocks, a key area where institutional traders are believed to place large orders, creating significant support or resistance levels. By identifying these blocks on a higher timeframe, the indicator aims to highlight potential trend reversals or continuations. The use of higher timeframe data helps filter out minor fluctuations and focus on more meaningful price movements. The candle count and percentage calculations provide additional context, allowing traders to understand the proportion of bullish or bearish candles within each trend. This information can be useful for assessing the strength and consistency of a trend. How to Use: Select the Higher Timeframe: Choose the higher timeframe (e.g., Daily) that best suits your trading strategy. The default setting is "D" (Daily), but it can be adjusted to other timeframes as needed. Interpret the Trend Signals: A green background indicates a bullish trend, while a red background indicates a bearish trend. The corresponding square shapes above the bars reinforce these signals. Use the information on the proportion of up and down candles during each trend to gauge the trend's strength and consistency. Trading Decisions: The indicator can be used in conjunction with other technical analysis tools and indicators to make informed trading decisions. It is particularly useful for identifying trend reversals and potential entry or exit points based on the behavior of higher timeframe order blocks. Customization and Optimization: Experiment with different higher timeframes and settings to optimize the indicator for your specific trading style and preferences. Conclusion: The "OrderBlock Trend (CISD)" indicator offers a comprehensive approach to trend analysis, combining the power of higher timeframe order blocks with clear visual cues and statistical insights. By understanding the underlying concepts and utilizing the provided features, traders can enhance their trend detection and decision-making processes in the markets. Disclaimer: This indicator is intended for educational purposes and should be used in conjunction with other analysis methods. Always perform your own research and risk management before making trading decisions. Some known bugs when you switch to lower timeframe while using daily timeframe data it didn't use the daily candle close to establish the trend change but your current time frame If some of you know how to fix it that would be great if you help me to I would try my best to fix this in the future :) credit to ChatGPT 4o
مؤشرات Pine Script™
من ‎AGENT-X‎
2
Multi-Regression StrategyIntroducing the "Multi-Regression Strategy" (MRS) , an advanced technical analysis tool designed to provide flexible and robust market analysis across various financial instruments. This strategy offers users the ability to select from multiple regression techniques and risk management measures, allowing for customized analysis tailored to specific market conditions and trading styles. Core Components: Regression Techniques: Users can choose one of three regression methods: 1 - Linear Regression: Provides a straightforward trend line, suitable for steady markets. 2 - Ridge Regression: Offers a more stable trend estimation in volatile markets by introducing a regularization parameter (lambda). 3 - LOESS (Locally Estimated Scatterplot Smoothing): Adapts to non-linear trends, useful for complex market behaviors. Each regression method calculates a trend line that serves as the basis for trading decisions. Risk Management Measures: The strategy includes nine different volatility and trend strength measures. Users select one to define the trading bands: 1 - ATR (Average True Range) 2 - Standard Deviation 3 - Bollinger Bands Width 4 - Keltner Channel Width 5 - Chaikin Volatility 6 - Historical Volatility 7 - Ulcer Index 8 - ATRP (ATR Percentage) 9 - KAMA Efficiency Ratio The chosen measure determines the width of the bands around the regression line, adapting to market volatility. How It Works: Regression Calculation: The selected regression method (Linear, Ridge, or LOESS) calculates the main trend line. For Ridge Regression, users can adjust the lambda parameter for regularization. LOESS allows customization of the point span, adaptiveness, and exponent for local weighting. Risk Band Calculation: The chosen risk measure is calculated and normalized. A user-defined risk multiplier is applied to adjust the sensitivity. Upper and lower bounds are created around the regression line based on this risk measure. Trading Signals: Long entries are triggered when the price crosses above the regression line. Short entries occur when the price crosses below the regression line. Optional stop-loss and take-profit mechanisms use the calculated risk bands. Customization and Flexibility: Users can switch between regression methods to adapt to different market trends (linear, regularized, or non-linear). The choice of risk measure allows adaptation to various market volatility conditions. Adjustable parameters (e.g., regression length, risk multiplier) enable fine-tuning of the strategy. Unique Aspects: Comprehensive Regression Options: Unlike many indicators that rely on a single regression method, MRS offers three distinct techniques, each suitable for different market conditions. Diverse Risk Measures: The strategy incorporates a wide range of volatility and trend strength measures, going beyond traditional indicators to provide a more nuanced view of market dynamics. Unified Framework: By combining advanced regression techniques with various risk measures, MRS offers a cohesive approach to trend identification and risk management. Adaptability: The strategy can be easily adjusted to suit different trading styles, timeframes, and market conditions through its various input options. How to Use: Select a regression method based on your analysis of the current market trend (linear, need for regularization, or non-linear). Choose a risk measure that aligns with your trading style and the market's current volatility characteristics. Adjust the length parameter to match your preferred timeframe for analysis. Fine-tune the risk multiplier to set the desired sensitivity of the trading bands. Optionally enable stop-loss and take-profit mechanisms using the calculated risk bands. Monitor the regression line for potential trend changes and the risk bands for entry/exit signals. By offering this level of customization within a unified framework, the Multi-Regression Strategy provides traders with a powerful tool for market analysis and trading decision support. It combines the robustness of regression analysis with the adaptability of various risk measures, allowing for a more comprehensive and flexible approach to technical trading.
استراتيجيات Pine Script™
من ‎gotbeatz26107‎
3
Momentum Trend [MT]The Momentum Trend indicator is an innovative technical analysis tool designed to capture and visualize momentum trends in financial markets. This advanced indicator goes beyond traditional momentum measures, offering a unique perspective on price action and trend strength. Core Functionality: Trend Momentum Index (TMI) Calculation: At the heart of this indicator is the Trend Momentum Index (TMI), a proprietary algorithm that combines moving averages with price action analysis to gauge momentum. The TMI is calculated using a user-defined source, length, and moving average type. Dynamic Trend Visualization: The indicator uses a color-coded column plot to represent the TMI values, providing an intuitive visual representation of trend strength and direction. The colors change based on specific conditions, offering instant insights into the current market state. Adaptive Momentum Analysis: The TMI adapts to changing market conditions by comparing current values to historical ones, allowing for a more nuanced understanding of momentum shifts. Key Inputs and Their Significance: TMI Source: Allows users to select the price data for TMI calculations. The default is the closing price, but users can choose alternative sources for different analytical perspectives. TMI Length: Defines the lookback period for the TMI calculation. The default of 8 provides a balance between responsiveness and stability, but users can adjust this to suit their trading style. Moving Average Type: Users can select from various moving average types (SMA, EMA, SMMA, WMA, VWMA) for the base calculation, allowing for customization based on trading preferences. What Makes It Unique: Comprehensive Momentum Analysis: The TMI combines elements of trend following and momentum, providing a more holistic view of market dynamics than traditional momentum indicators. Multi-Faceted Trend Identification: The color-coding system doesn't just show bullish or bearish trends, but also identifies accelerating and decelerating momentum in both directions. Flexible Moving Average Integration: The ability to choose different moving average types allows traders to fine-tune the indicator's responsiveness and smoothness. Visual Clarity: The column-style plot with color changes offers clear, at-a-glance insights into trend strength and direction. Momentum Comparison Logic: The indicator incorporates logic to compare current momentum changes with recent historical changes, providing context for the current market state. The Momentum Trend indicator represents a sophisticated approach to momentum and trend analysis. By combining moving averages, price action, and comparative momentum logic, it offers traders a powerful tool for identifying potential trend continuations, reversals, and momentum shifts. This indicator is particularly valuable for traders looking to: - Identify the start of new trends - Spot potential trend reversals - Gauge the strength of ongoing trends - Time entries and exits based on momentum shifts
مؤشرات Pine Script™
من ‎Future_2x‎
Crab Harmonic Pattern [TradingFinder] Harmonic Chart patterns🔵 Introduction The Crab pattern is recognized as a reversal pattern in technical analysis, utilizing Fibonacci numbers and percentages for chart analysis. This pattern can predict suitable price reversal areas on charts using Fibonacci ratios. The structure of the Crab pattern can manifest in both bullish and bearish forms on the chart. By analyzing this structure, traders can identify points where the price direction changes, which are essential for making informed trading decisions. The pattern's structure is visually represented on charts as shown below. To gain a deeper understanding of the Crab pattern's functionality, it is beneficial to become familiar with its various harmonic forms. 🟣 Types of Crab Patterns The Crab pattern is categorized into two types based on its structure: bullish and bearish. The bullish Crab is denoted by the letter M, while the bearish Crab is indicated by the letter W in technical analysis. Typically, a bullish Crab pattern signals a potential price increase, whereas a bearish Crab pattern suggests a potential price decrease on the chart. The direction of price movement depends significantly on the price's position within the chart. By identifying whether the pattern is bullish or bearish, traders can determine the likely direction of the price reversal. Bullish Crab : Bearish Crab : 🔵 How to Use When trading using the Crab pattern, crucial parameters include the end time of the correction and the point at which the chart reaches its peak. Generally, the best time to buy is when the chart nears the end of its correction, and the best time to sell is when it approaches the peak price. As we discussed, the end of the price correction and the time to reach the peak are measured using Fibonacci ratios. By analyzing these levels, traders can estimate the end of the correction in the chart waves and select a buying position for their stock or asset upon reaching that ratio. 🟣 Bullish Crab Pattern In this pattern, the stock price is expected to rise at the pattern's completion, transitioning into an upward trend. The bullish Crab pattern usually begins with an upward trend, followed by a price correction, after which the stock resumes its upward movement. If a deeper correction occurs, the price will change direction at some point on the chart and rise again towards its target price. Price corrections play a critical role in this pattern, as it aims to identify entry and exit points using Fibonacci ratios, allowing traders to make purchases at the end of the corrections. When the price movement lines are connected on the chart, the bullish Crab pattern resembles the letter M. 🟣 Bearish Crab Pattern In this pattern, the stock price is expected to decline at the pattern's completion, leading to a strong downward trend. The bearish Crab pattern typically starts with a price correction in a downward trend and, after several fluctuations, reaches a peak where the direction changes downward, resulting in a significant price drop. This pattern uses Fibonacci ratios to identify points where the price movement is likely to change direction, enabling traders to exit their positions at the chart's peak. When the price movement lines are connected on the chart, the bearish Crab pattern resembles the letter W. 🔵 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 Format : 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.
مؤشرات Pine Script™
من ‎TFlab‎
2
TrendMaster ProTrendMaster Pro: A Comprehensive Trend Analysis Tool for Long-Term Investors TrendMaster Pro is an advanced technical indicator designed to provide long-term investors with a robust and comprehensive analysis of market trends. This sophisticated tool operates exclusively on daily timeframes, making it ideal for those focused on long-term investment strategies. By combining multiple analytical approaches, TrendMaster Pro offers investors a powerful means to assess trend quality and make informed decisions. Automatic Trend Detection At the heart of TrendMaster Pro lies its ability to automatically identify the most statistically significant trend. The indicator analyzes various timeframes ranging from 1000 to 5000 days, selecting the one that exhibits the highest correlation. This feature ensures that investors are always working with the most relevant trend data, eliminating the subjectivity often associated with manual trend identification. The trend detection algorithm employs a regression analysis approach, evaluating approximately 80,000 different trend alternatives each day. Each potential trend is assigned a score based on criteria such as trend density, deviation from regression, and the number of price points near the trend's floor and ceiling. The trend with the highest score is then selected and displayed on the chart. Comprehensive Scoring System TrendMaster Pro employs a multi-faceted scoring system that evaluates four key aspects of a trend, providing a holistic view of its quality and potential. Each aspect is scored on a scale of 0 to 10, with the overall trend quality score being a weighted average of these individual scores. 1. Length Score The Length Score measures the duration of the detected trend. Longer trends receive higher scores, reflecting increased reliability and significance. This score is calculated by normalizing the auto-selected period (which ranges from 1000 to 5000 days) to a scale of 5 to 10. For example, if the auto-selected period is 3000 days, it would receive a score of around 7.5. This emphasizes the importance of long-term trends in investment decision-making, as they tend to be more stable and indicative of underlying market forces. 2. Strength Score The Strength Score utilizes Pearson's Correlation Coefficient to assess trend strength. This statistical measure gauges the linear relationship between price and trend projection. A value closer to 1 indicates a strong positive correlation, reinforcing confidence in the trend direction based on historical price movements. The indicator translates the Pearson's Correlation Coefficient into a score from 0 to 10. For instance, a correlation coefficient of 0.95 might translate to a Strength Score of 8, indicating a strong and reliable trend. 3. Performance Score The Performance Score compares the asset's Compound Annual Growth Rate (CAGR) to a chosen benchmark, typically a major index like the S&P 500. This score provides insight into how well the asset is performing relative to the broader market. The CAGR is calculated using the formula: CAGR = (Ending Value / Beginning Value)^(1/n) - 1, where n is the number of years. The Performance Score is then determined by comparing this CAGR to the benchmark's CAGR over the same period. A higher score indicates outperformance relative to the benchmark. 4. Level Score The Level Score evaluates the current price position within the trend channel. Lower prices within the channel receive higher scores, suggesting potential value or buying opportunities. This score helps identify possible entry points based on historical trend behavior. For example, if the current price is near the lower boundary of the trend channel, it might receive a Level Score of 9, indicating a potentially attractive entry point. Visual Representation TrendMaster Pro provides a clear visual representation of the detected trend by displaying a regression channel on the chart. This channel consists of three lines: a middle line representing the main trend, and upper and lower lines representing standard deviations from the main trend. The channel offers a quick visual reference for support and resistance levels, helping investors identify potential entry and exit points. The color and style of these lines can be customized to suit individual preferences. Detailed Information Table A comprehensive table presents all scores and relevant data, allowing for quick and easy interpretation of the trend analysis. This table includes: The auto-selected trend length The Pearson's Correlation Coefficient The asset's CAGR and the benchmark's CAGR Individual scores for Length, Strength, Performance, and Level The overall Trend Quality Score This table provides investors with a clear, at-a-glance summary of the trend's key characteristics and quality. Practical Application To use TrendMaster Pro effectively, investors should consider the following: Focus on the overall Trend Quality Score as a primary indicator of trend strength and reliability. Use the Length Score to gauge the trend's longevity and potential stability. Pay attention to the Strength Score to assess how well the price action aligns with the identified trend. Utilize the Performance Score to compare the asset's performance against the broader market. Consider the Level Score when timing entries, looking for opportunities when prices are relatively low within the trend channel. Use the visual trend channel as a guide for potential support and resistance levels. Limitations and Considerations While TrendMaster Pro offers powerful insights, it's important to remember that no indicator can predict future market movements with certainty. The tool should be used in conjunction with fundamental analysis and other market information. Additionally, as the indicator is designed for daily charts and long-term analysis, it may not be suitable for short-term trading strategies. Users should also be aware that past performance does not guarantee future results, even with strong trend indications. Conclusion TrendMaster Pro represents a significant advancement in trend analysis for long-term investors. By combining automatic trend detection, comprehensive scoring, and benchmark comparison, it offers a powerful tool for those seeking to make informed, data-driven investment decisions. Its ability to objectively assess trend quality across multiple dimensions provides investors with a valuable edge in navigating complex market conditions. For investors looking to deepen their understanding of market trends and enhance their long-term investment strategies, TrendMaster Pro offers a sophisticated yet accessible solution. As with any investment tool, users are encouraged to thoroughly familiarize themselves with its features and interpret its outputs in the context of their overall investment approach.
مؤشرات Pine Script™
من ‎Julien_Eche‎
1
CofG Oscillator w/ Added Normalizations/TransformationsThis indicator is a unique study in normalization/transformation techniques, which are applied to the CG (center of gravity) Oscillator, a popular oscillator made by John Ehlers. The idea to transform the data from this oscillator originated from observing the original indicator, which exhibited numerous whips. Curious about the potential outcomes, I began experimenting with various normalization/transformation methods and discovered a plethora of interesting results. The indicator offers 10 different types of normalization/transformation, each with its own set of benefits and drawbacks. My personal favorites are the Quantile Transformation , which converts the dataset into one that is mostly normally distributed, and the Z-Score , which I have found tends to provide better signaling than the original indicator. I've also included the option of showing the mean, median, and mode of the data over the period specified by the transformation period. Using this will allow you to gather additional insights into how these transformations effect the distribution of the data series. I've also included some notes on what each transformation does, how it is useful, where it fails, and what I've found to be the best inputs for it (though I'd encourage you to play around with it yourself). Types of Normalization/Transformation: 1. Z-Score Overview: Standardizes the data by subtracting the mean and dividing by the standard deviation. Benefits: Centers the data around 0 with a standard deviation of 1, reducing the impact of outliers. Disadvantages: Works best on data that is normally distributed Notes: Best used with a mid-longer transformation period. 2. Min-Max Overview: Scales the data to fit within a specified range, typically 0 to 1. Benefits: Simple and fast to compute, preserves the relationships among data points. Disadvantages: Sensitive to outliers, which can skew the normalization. Notes: Best used with mid-longer transformation period. 3. Decimal Scaling Overview: Normalizes data by moving the decimal point of values. Benefits: Simple and straightforward, useful for data with varying scales. Disadvantages: Not commonly used, less intuitive, less advantageous. Notes: Best used with a mid-longer transformation period. 4. Mean Normalization Overview: Subtracts the mean and divides by the range (max - min). Benefits: Centers data around 0, making it easier to compare different datasets. Disadvantages: Can be affected by outliers, which influence the range. Notes: Best used with a mid-longer transformation period. 5. Log Transformation Overview: Applies the logarithm function to compress the data range. Benefits: Reduces skewness, making the data more normally distributed. Disadvantages: Only applicable to positive data, breaks on zero and negative values. Notes: Works with varied transformation period. 6. Max Abs Scaler Overview: Scales each feature by its maximum absolute value. Benefits: Retains sparsity and is robust to large outliers. Disadvantages: Only shifts data to the range , which might not always be desirable. Notes: Best used with a mid-longer transformation period. 7. Robust Scaler Overview: Uses the median and the interquartile range for scaling. Benefits: Robust to outliers, does not shift data as much as other methods. Disadvantages: May not perform well with small datasets. Notes: Best used with a longer transformation period. 8. Feature Scaling to Unit Norm Overview: Scales data such that the norm (magnitude) of each feature is 1. Benefits: Useful for models that rely on the magnitude of feature vectors. Disadvantages: Sensitive to outliers, which can disproportionately affect the norm. Not normally used in this context, though it provides some interesting transformations. Notes: Best used with a shorter transformation period. 9. Logistic Function Overview: Applies the logistic function to squash data into the range . Benefits: Smoothly compresses extreme values, handling skewed distributions well. Disadvantages: May not preserve the relative distances between data points as effectively. Notes: Best used with a shorter transformation period. This feature is actually two layered, we first put it through the mean normalization to ensure that it's generally centered around 0. 10. Quantile Transformation Overview: Maps data to a uniform or normal distribution using quantiles. Benefits: Makes data follow a specified distribution, useful for non-linear scaling. Disadvantages: Can distort relationships between features, computationally expensive. Notes: Best used with a very long transformation period. Conclusion Feel free to explore these normalization/transformation techniques to see how they impact the performance of the CG Oscillator. Each method offers unique insights and benefits, making this study a valuable tool for traders, especially those with a passion for data analysis.
مؤشرات Pine Script™
من ‎TheArchbishop‎
2
Advanced ADX [CryptoSea]The Advanced ADX Analysis is a sophisticated tool designed to enhance market analysis through detailed ADX calculations. This tool is built for traders who seek to identify market trends, strength, and potential reversals with higher accuracy. By leveraging the Average Directional Index (ADX), Directional Indicator Plus (DI+), and Directional Indicator Minus (DI-), this indicator offers a comprehensive view of market dynamics. New Overlay Feature: This script uses the new 'force overlay' feature which lets you plot on the chart as well as plotting in an oscillator pane at the same time. force_overlay=true Key Features Comprehensive ADX Tracking: Tracks ADX values along with DI+ and DI- to provide a complete view of market trend strength and direction. The ADX measures the strength of the trend, while DI+ and DI- indicate the trend direction. This combined analysis helps traders identify strong and weak trends with precision. Trend Duration Monitoring: Monitors the duration of strong and weak trends, offering insights into trend persistence and potential reversals. By keeping track of how long the ADX has been above or below a certain threshold, traders can gauge the sustainability of the current trend. Customizable Alerts: Features multiple alert options for strong trends, weak trends, and DI crossovers, ensuring traders are notified of significant market events. These alerts can be tailored to notify traders when certain conditions are met, such as when the ADX crosses a threshold or when DI+ crosses DI-. Adaptive Display Options: Includes customizable background color settings and extended statistics display for in-depth market analysis. Users can choose to highlight strong or weak trends on the chart background, making it easier to visualize market conditions at a glance. In the example below, we have a bullish scenario play out where the DI+ has been above the DI- for 11 candles and our dashboard shows the average is 10.48 candles. With the ADX above its threshold this would be a bullish signal. This ended up in a 20%+ move to the upside. The dashboard will help point out things to consider when looking to exit the position, the DI+ getting close to the max DI+ duration would be a sign that momentum is weakening and that price may cool off or even reverse. How it Works ADX Calculation: Computes the ADX, DI+, and DI- values using a user-defined period. The ADX is derived from the smoothed average of the absolute difference between DI+ and DI-. This calculation helps determine the strength of a trend without considering its direction. Trend Duration Analysis: Tracks and calculates the duration of strong and weak trends, as well as DI+ and DI- durations. This analysis provides a detailed view of how long a trend has been in place, helping traders assess the reliability of the trend. Alert System: Provides a robust alert system that triggers notifications for strong trends, weak trends, and DI crossovers. The alerts are based on specific conditions such as the duration of the trend or the crossover of directional indicators, ensuring traders are informed about critical market movements. Visual Enhancements: Utilizes color gradients and background settings to visually represent trend strength and duration. This feature enhances the visual analysis of trends, making it easier for traders to identify significant market changes at a glance. In the example below, we see the ADX weakening after we have just had a move up, if you are looking to get into this position you want to see the ADX growing with either the DI+ or DI- breaking their average durations. As you can see below, although the ADX manages to move above the threshold, there are no DI+/- breaks which is shown by price moving sideways. Not something most traders would be interested in. Application Strategic Decision-Making: Assists traders in making informed decisions by providing detailed analysis of ADX movements and trend durations. By understanding the strength and direction of trends, traders can better time their entries and exits. Trend Confirmation: Reinforces trading strategies by confirming potential reversals and trend strength through ADX and DI analysis. This confirmation helps traders validate their trading signals, reducing the risk of false signals. Customized Analysis: Adapts to various trading styles with extensive input settings that control the display and sensitivity of trend data. Traders can customize the indicator to suit their specific needs, making it a versatile tool for different trading strategies. The Advanced ADX Analysis by is an invaluable addition to a trader's toolkit, offering depth and precision in market trend analysis to navigate complex market conditions effectively. With its comprehensive tracking, alert system, and customizable display options, this indicator provides traders with the tools they need to stay ahead of the market.
مؤشرات Pine Script™
من ‎CryptoSeaTV‎
1
SOL & BTC EMA with BTC/SOL Price Difference % and BTC Dom EMAThis script is designed to provide traders with a comprehensive analysis of Solana (SOL) and Bitcoin (BTC) by incorporating Exponential Moving Averages (EMAs) and price difference percentages. It also includes the BTC Dominance EMA to offer insights into the overall market dominance of Bitcoin. Features: SOL EMA: Plots the Exponential Moving Average (EMA) for Solana (SOL) based on a customizable period length. BTC EMA: Plots the Exponential Moving Average (EMA) for Bitcoin (BTC) based on a customizable period length. BTC Dominance EMA: Plots the Exponential Moving Average (EMA) for BTC Dominance, which helps in understanding Bitcoin's market share relative to other cryptocurrencies. BTC/SOL Price Difference %: Calculates and plots the percentage difference between BTC and SOL prices, adjusted for their respective EMAs. This helps in identifying relative strength or weakness between the two assets. Background Highlight: Colors the background to visually indicate whether the BTC/SOL price difference percentage is positive (green) or negative (red), aiding in quick decision-making. Inputs: SOL Ticker: Symbol for Solana (default: BINANCE ). BTC Ticker: Symbol for Bitcoin (default: BINANCE ). BTC Dominance Ticker: Symbol for Bitcoin Dominance (default: CRYPTOCAP .D). EMA Length: The length of the EMA (default: 20 periods). Usage: This script is intended for traders looking to analyze the relationship between SOL and BTC, using EMAs to smooth out price data and highlight trends. The BTC/SOL price difference percentage can help traders identify potential trading opportunities based on the relative movements of SOL and BTC. Note: Leverage trading involves significant risk and may not be suitable for all investors. Ensure you have a good understanding of the market conditions and employ proper risk management techniques.
مؤشرات Pine Script™
من ‎renegadewood3‎
Moving Average Z-Score Suite [BackQuant]Moving Average Z-Score Suite 1. What is this indicator The Moving Average Z-Score Suite is a versatile indicator designed to help traders identify and capitalize on market trends by utilizing a variety of moving averages. This indicator transforms selected moving averages into a Z-Score oscillator, providing clear signals for potential buy and sell opportunities. The indicator includes options to choose from eleven different moving average types, each offering unique benefits and characteristics. It also provides additional features such as standard deviation levels, extreme levels, and divergence detection, enhancing its utility in various market conditions. 2. What is a Z-Score A Z-Score is a statistical measurement that describes a value's relationship to the mean of a group of values. It is measured in terms of standard deviations from the mean. For instance, a Z-Score of 1.0 means the value is one standard deviation above the mean, while a Z-Score of -1.0 indicates it is one standard deviation below the mean. In the context of financial markets, Z-Scores can be used to identify overbought or oversold conditions by determining how far a particular value (such as a moving average) deviates from its historical mean. 3. What moving averages can be used The Moving Average Z-Score Suite allows users to select from the following eleven moving averages: Simple Moving Average (SMA) Hull Moving Average (HMA) Exponential Moving Average (EMA) Weighted Moving Average (WMA) Double Exponential Moving Average (DEMA) Running Moving Average (RMA) Linear Regression Curve (LINREG) (This script can be found standalone ) Triple Exponential Moving Average (TEMA) Arnaud Legoux Moving Average (ALMA) Kalman Hull Moving Average (KHMA) T3 Moving Average Each of these moving averages has distinct properties and reacts differently to price changes, allowing traders to select the one that best fits their trading style and market conditions. 4. Why Turning a Moving Average into a Z-Score is Innovative and Its Benefits Transforming a moving average into a Z-Score is an innovative approach because it normalizes the moving average values, making them more comparable across different periods and instruments. This normalization process helps in identifying extreme price movements and mean-reversion opportunities more effectively. By converting the moving average into a Z-Score, traders can better gauge the relative strength or weakness of a trend and detect potential reversals. This method enhances the traditional moving average analysis by adding a statistical perspective, providing clearer and more objective trading signals. 5. How It Can Be Used in the Context of a Trading System In a trading system, it can be used to generate buy and sell signals based on the Z-Score values. When the Z-Score crosses above zero, it indicates a potential buying opportunity, suggesting that the price is above its mean and possibly trending upward. Conversely, a Z-Score crossing below zero signals a potential selling opportunity, indicating that the price is below its mean and might be trending downward. Additionally, the indicator's ability to show standard deviation levels and extreme levels helps traders set profit targets and stop-loss levels, improving risk management and trade planning. 6. How It Can Be Used for Trend Following For trend-following strategies, it can be particularly useful. The Z-Score oscillator helps traders identify the strength and direction of a trend. By monitoring the Z-Score and its rate of change, traders can confirm the persistence of a trend and make informed decisions to enter or exit trades. The indicator's divergence detection feature further enhances trend-following by identifying potential reversals before they occur, allowing traders to capitalize on trend shifts. By providing a clear and quantifiable measure of trend strength, this indicator supports disciplined and systematic trend-following strategies. No backtests for this indicator due to the many options and ways it can be used, Enjoy
مؤشرات Pine Script™
من ‎BackQuant‎
Multiple Non-Linear Regression [ChartPrime]This indicator is designed to perform multiple non-linear regression analysis using four independent variables: close, open, high, and low prices. Here's a breakdown of its components and functionalities: Inputs: Users can adjust several parameters: Normalization Data Length: Length of data used for normalization. Learning Rate: Rate at which the algorithm learns from errors. Smooth?: Option to smooth the output. Smooth Length: Length of smoothing if enabled. Define start coefficients: Initial coefficients for the regression equation. Data Normalization: The script normalizes input data to a range between 0 and 1 using the highest and lowest values within a specified length. Non-linear Regression: It calculates the regression equation using the input coefficients and normalized data. The equation used is a weighted sum of the independent variables, with coefficients adjusted iteratively using gradient descent to minimize errors. Error Calculation: The script computes the error between the actual and predicted values. Gradient Descent: The coefficients are updated iteratively using gradient descent to minimize the error. // Compute the predicted values using the non-linear regression function predictedValues = nonLinearRegression(x_1, x_2, x_3, x_4, b1, b2, b3, b4) // Compute the error error = errorModule(initial_val, predictedValues) // Update the coefficients using gradient descent b1 := b1 - (learningRate * (error * x_1)) b2 := b2 - (learningRate * (error * x_2)) b3 := b3 - (learningRate * (error * x_3)) b4 := b4 - (learningRate * (error * x_4)) Visualization: Plotting of normalized input data (close, open, high, low). The indicator provides visualization of normalized data values (close, open, high, low) in the form of circular markers on the chart, allowing users to easily observe the relative positions of these values in relation to each other and the regression line. Plotting of the regression line. Color gradient on the regression line based on its value and bar colors. Display of normalized input data and predicted value in a table. Signals for crossovers with a midline (0.5). Interpretation: Users can interpret the regression line and its crossovers with the midline (0.5) as signals for potential buy or sell opportunities. This indicator helps users analyze the relationship between multiple variables and make trading decisions based on the regression analysis. Adjusting the coefficients and parameters can fine-tune the model's performance according to specific market conditions.
مؤشرات Pine Script™
من ‎ChartPrime‎
12
Six PillarsGeneral Overview The "Six Pillars" indicator is a comprehensive trading tool that combines six different technical analysis methods to provide a holistic view of market conditions. These six pillars are: Trend Momentum Directional Movement (DM) Stochastic Fractal On-Balance Volume (OBV) The indicator calculates the state of each pillar and presents them in an easy-to-read table format. It also compares the current timeframe with a user-defined comparison timeframe to offer a multi-timeframe analysis. A key feature of this indicator is the Confluence Strength meter. This unique metric quantifies the overall agreement between the six pillars across both timeframes, providing a score out of 100. A higher score indicates stronger agreement among the pillars, suggesting a more reliable trading signal. I also included a visual cue in the form of candle coloring. When all six pillars agree on a bullish or bearish direction, the candle is colored green or red, respectively. This feature allows traders to quickly identify potential high-probability trade setups. The Six Pillars indicator is designed to work across multiple timeframes, offering a comparison between the current timeframe and a user-defined comparison timeframe. This multi-timeframe analysis provides traders with a more comprehensive understanding of market dynamics. Origin and Inspiration The Six Pillars indicator was inspired by the work of Dr. Barry Burns, author of "Trend Trading for Dummies" and his concept of "5 energies." (Trend, Momentum, Cycle, Support/Resistance, Scale) I was intrigued by Dr. Burns' approach to analyzing market dynamics and decided to put my own twist upon his ideas. Comparing the Six Pillars to Dr. Burns' 5 energies, you'll notice I kept Trend and Momentum, but I swapped out Cycle, Support/Resistance, and Scale for Directional Movement, Stochastic, Fractal, and On-Balance Volume. These changes give you a more dynamic view of market strength, potential reversals, and volume confirmation all in one package. What Makes This Indicator Unique The standout feature of the Six Pillars indicator is its Confluence Strength meter. This feature calculates the overall agreement between the six pillars, providing traders with a clear, numerical representation of signal strength. The strength is calculated by considering the state of each pillar in both the current and comparison timeframes, resulting in a score out of 100. Here's how it calculates the strength: It considers the state of each pillar in both the current timeframe and the comparison timeframe. For each pillar, the absolute value of its state is taken. This means that both strongly bullish (2) and strongly bearish (-2) states contribute equally to the strength. The absolute values for all six pillars are summed up for both timeframes, resulting in two sums: current_sum and alternate_sum. These sums are then added together to get a total_sum. The total_sum is divided by 24 (the maximum possible sum if all pillars were at their strongest states in both timeframes) and multiplied by 100 to get a percentage. The result is rounded to the nearest integer and capped at a minimum of 1. This calculation method ensures that the Confluence Strength meter takes into account not only the current timeframe but also the comparison timeframe, providing a more robust measure of overall market sentiment. The resulting score, ranging from 1 to 100, gives traders a clear and intuitive measure of how strongly the pillars agree, with higher scores indicating stronger potential signals. This approach to measuring signal strength is unique in that it doesn't just rely on a single aspect of price action or volume. Instead, it takes into account multiple factors, providing a more robust and reliable indication of potential market moves. The higher the Confluence Strength score, the more confident traders can be in the signal. The Confluence Strength meter helps traders in several ways: It provides a quick and easy way to gauge the overall market sentiment. It helps prioritize potential trades by identifying the strongest signals. It can be used as a filter to avoid weaker setups and focus on high-probability trades. It offers an additional layer of confirmation for other trading strategies or indicators. By combining the Six Pillars analysis with the Confluence Strength meter, I've created a powerful tool that not only identifies potential trading opportunities but also quantifies their strength, giving traders a significant edge in their decision-making process. How the Pillars Work (What Determines Bullish or Bearish) While developing this indicator, I selected and configured six key components that work together to provide a comprehensive view of market conditions. Each pillar is set up to complement the others, creating a synergistic effect that offers traders a more nuanced understanding of price action and volume. Trend Pillar: Based on two Exponential Moving Averages (EMAs) - a fast EMA (8 period) and a slow EMA (21 period). It determines the trend by comparing these EMAs, with stronger trends indicated when the fast EMA is significantly above or below the slow EMA. Directional Movement (DM) Pillar: Utilizes the Average Directional Index (ADX) with a default period of 14. It measures trend strength, with values above 25 indicating a strong trend. It also considers the Positive and Negative Directional Indicators (DI+ and DI-) to determine trend direction. Momentum Pillar: Uses the Moving Average Convergence Divergence (MACD) with customizable fast (12), slow (26), and signal (9) lengths. It compares the MACD line to the signal line to determine momentum strength and direction. Stochastic Pillar: Employs the Stochastic oscillator with a default period of 13. It identifies overbought conditions (above 80) and oversold conditions (below 20), with intermediate zones between 60-80 and 20-40. Fractal Pillar: Uses Williams' Fractal indicator with a default period of 3. It identifies potential reversal points by looking for specific high and low patterns over the given period. On-Balance Volume (OBV) Pillar: Incorporates On-Balance Volume with three EMAs - short (3), medium (13), and long (21) periods. It assesses volume trends by comparing these EMAs. Each pillar outputs a state ranging from -2 (strongly bearish) to 2 (strongly bullish), with 0 indicating a neutral state. This standardized output allows for easy comparison and aggregation of signals across all pillars. Users can customize various parameters for each pillar, allowing them to fine-tune the indicator to their specific trading style and market conditions. The multi-timeframe comparison feature also allows users to compare pillar states between the current timeframe and a user-defined comparison timeframe, providing additional context for decision-making. Design From a design standpoint, I've put considerable effort into making the Six Pillars indicator visually appealing and user-friendly. The clean and minimalistic design is a key feature that sets this indicator apart. I've implemented a sleek table layout that displays all the essential information in a compact and organized manner. The use of a dark background (#030712) for the table creates a sleek look that's easy on the eyes, especially during extended trading sessions. The overall design philosophy focuses on presenting complex information in a simple, intuitive format, allowing traders to make informed decisions quickly and efficiently. The color scheme is carefully chosen to provide clear visual cues: White text for headers ensures readability Green (#22C55E) for bullish signals Blue (#3B82F6) for neutral states Red (#EF4444) for bearish signals This color coding extends to the candle coloring, making it easy to spot when all pillars agree on a bullish or bearish outlook. I've also incorporated intuitive symbols (↑↑, ↑, →, ↓, ↓↓) to represent the different states of each pillar, allowing for quick interpretation at a glance. The table layout is thoughtfully organized, with clear sections for the current and comparison timeframes. The Confluence Strength meter is prominently displayed, providing traders with an immediate sense of signal strength. To enhance usability, I've added tooltips to various elements, offering additional information and explanations when users hover over different parts of the indicator. How to Use This Indicator The Six Pillars indicator is a versatile tool that can be used for various trading strategies. Here are some general usage guidelines and specific scenarios: General Usage Guidelines: Pay attention to the Confluence Strength meter. Higher values indicate stronger agreement among the pillars and potentially more reliable signals. Use the multi-timeframe comparison to confirm signals across different time horizons. Look for alignment between the current timeframe and comparison timeframe pillars for stronger signals. One of the strengths of this indicator is it can let you know when markets are sideways – so in general you can know to avoid entering when the Confluence Strength is low, indicating disagreement among the pillars. Customization Options The Six Pillars indicator offers a wide range of customization options, allowing traders to tailor the tool to their specific needs and trading style. Here are the key customizable elements: Comparison Timeframe: Users can select any timeframe for comparison with the current timeframe, providing flexibility in multi-timeframe analysis. Trend Pillar: Fast EMA Period: Adjustable for quicker or slower trend identification Slow EMA Period: Can be modified to capture longer-term trends Momentum Pillar: MACD Fast Length MACD Slow Length MACD Signal Length These can be adjusted to fine-tune momentum sensitivity DM Pillar: ADX Period: Customizable to change the lookback period for trend strength measurement ADX Threshold: Adjustable to define what constitutes a strong trend Stochastic Pillar: Stochastic Period: Can be modified to change the sensitivity of overbought/oversold readings Fractal Pillar: Fractal Period: Adjustable to identify potential reversal points over different timeframes OBV Pillar: Short OBV EMA Medium OBV EMA Long OBV EMA These periods can be customized to analyze volume trends over different timeframes These customization options allow traders to experiment with different settings to find the optimal configuration for their trading strategy and market conditions. The flexibility of the Six Pillars indicator makes it adaptable to various trading styles and market environments.
مؤشرات Pine Script™
من ‎smraikai‎
2
Parabolic SAR Waves [MMA]Parabolic SAR Waves Description: The "Parabolic SAR Waves " is an advanced version of the traditional Parabolic SAR indicator, customized for TradingView. This script incorporates dynamic acceleration factors and optional gradient coloration to enhance visual interpretation and utility for traders aiming to accurately capture trends and predict potential reversals. Features: - Dynamic Acceleration: Adjust the initial, incremental, and maximum values of the acceleration factor to suit various market conditions and trading preferences. - Gradient Coloring: Use gradient colors to indicate the strength and stability of the trend, providing visual cues that are easy to interpret. - Trend Visibility: The SAR dots are plotted directly on the price chart, making it easy to spot trend changes and maintain situational awareness. - Overlay Feature: Designed to overlay directly on the price charts, allowing for seamless integration with other technical analysis tools. Benefits: - Trend Detection: Helps in identifying the beginning and potential reversal of trends, aiding in timely decision-making. - Stop-Loss Management: Utilizes the positions of the SAR dots as dynamic stop-loss points, which helps in risk management. - Visual Simplicity: Enhances the decision-making process through a straightforward visual representation of trend data. Parameters: - Acceleration Start (accel_start): The initial value for the acceleration, set to 0.02 by default. - Acceleration Increment (accel_inc): The amount by which the acceleration increases, set to 0.005 by default. - Acceleration Maximum (accel_max): The maximum limit of the acceleration factor, set to 0.1 by default. - Use Gradient Colors (use_gradient): A boolean toggle to enable or disable gradient coloring, enabled by default. Indicator Usage: 1. To apply, select this indicator from TradingView's indicator library. 2. Adjust the acceleration parameters based on your specific trading strategy and market analysis. 3. Interpret the indicator signals: - Green SAR dots below the price bars indicate a bullish trend. - Red SAR dots above the price bars signify a bearish trend. - Gradient colors, if enabled, provide insights into the acceleration factor's intensity relative to trend strength. Alerts: - Bullish Reversal Alert: Issues a notification if there is a potential upward reversal when the trend shifts to bullish. - Bearish Reversal Alert: Alerts when there's potential for a downward move as the trend turns bearish. The "Parabolic SAR Waves " is a robust tool, ideal for traders who need precise, customizable trend-following capabilities that integrate seamlessly with other market analysis strategies. Enhance your trading with detailed trend insights and adaptive parameter controls.
مؤشرات Pine Script™
من ‎moneymovesalgo‎
3
Bitcoin Trend Indicator█  Overview The Trend Indicator script is designed to help traders identify the direction and strength of momentum in the price of a digital asset. By using historical price data, it calculates and provides daily signals indicating whether the asset is in an uptrend, downtrend, or no trend at all. The script can be applied to various cryptocurrencies, such as Bitcoin and Ether, using their respective price charts. █  Key Concepts and Calculation Methodology For calculations, the script uses the 180 most recent candles. The Trend Indicator is calculated based on four moving average pairs (MAPs), which compare shorter-term and longer-term moving averages of the asset's price. The moving averages are exponentially weighted, meaning more recent prices have a greater impact on the average than older prices. The half-life of the moving averages determines the weight decay. The script uses the following moving average pairs: 1-day vs. 5-day 2.5-day vs. 10-day 5-day vs. 20-day 10-day vs. 40-day █  Calculation Steps Exponentially Weighted Moving Averages (EWMA): Each moving average is calculated using an exponential decay factor and a normalization factor to adjust for the fixed window of 180 observations. Component Inputs: For each moving average pair, the script compares the shorter-term moving average to the longer-term moving average. If the shorter-term average is greater than or equal to the longer-term average, the component input is +1 (indicating an uptrend). If it is less, the input is -1 (indicating a downtrend). Trend Indicator Value: The script averages the four component inputs to produce a final value ranging from -1 to +1, representing the trend's direction and strength: +1: Significant uptrend +0.5: Uptrend 0: No trend -0.5: Downtrend -1: Significant downtrend █  Learn More For more information about the Bitcoin Trend Indicator and other trading tools, please visit my TradingView profile. Feel free to reach out with any questions or feedback.
مؤشرات Pine Script™
من ‎cyatophilum‎
Volume-Adjusted Bollinger BandsThe Volume-Adjusted Bollinger Bands (VABB) indicator is an advanced technical analysis tool that enhances the traditional Bollinger Bands by incorporating volume data. This integration allows the bands to dynamically adjust based on market volume, providing a more nuanced view of price movements and volatility. The key qualities of the VABB indicator include: 1. Dynamic Adjustment with Volume: Traditional Bollinger Bands are based solely on price data and standard deviations. The VABB indicator adjusts the width of the bands based on the volume ratio, making them more responsive to changes in market activity. This means that during periods of high volume, the bands will expand, and during periods of low volume, they will contract. This adjustment helps to reinforce the significance of price movements relative to the central line (VWMA). 2. Volume-Weighted Moving Average (VWMA): Instead of using a simple moving average (SMA) as the central line, the VABB uses the VWMA, which weights prices by volume. This provides a more accurate representation of the average price level, considering the trading volume. 3. Enhanced Signal Reliability: By incorporating volume, the VABB can filter out false signals that might occur in low-volume conditions. This makes the indicator particularly useful for identifying significant price movements that are supported by strong trading activity. How to Use and Interpret the VABB Indicator To use the VABB indicator, you need to set it up on your trading platform with the following parameters: 1. BB Length: The number of periods for calculating the Bollinger Bands (default is 20). 2. BB Multiplier: The multiplier for the standard deviation to set the width of the Bollinger Bands (default is 2.0). 3. Volume MA Length: The number of periods for calculating the moving average of the volume (default is 14). Volume Ratio Smoothing Length: The number of periods for smoothing the volume ratio (default is 5). Interpretation 1.Trend Identification: The VWMA serves as the central line. When the price is above the VWMA, it indicates an uptrend, and when it is below, it indicates a downtrend. The direction of the VWMA itself can also signal the trend's strength. 2. Volatility and Volume Analysis: The width of the VABB bands reflects both volatility and volume. Wider bands indicate high volatility and/or high volume, suggesting significant price movements. Narrower bands indicate low volatility and/or low volume, suggesting consolidation. 3. Trading Signals: Breakouts: A price move outside the adjusted upper or lower bands can signal a potential breakout. High volume during such moves reinforces the breakout's validity. Reversals: When the price touches or crosses the adjusted upper band, it may indicate overbought conditions, while touching or crossing the adjusted lower band may indicate oversold conditions. These conditions can signal potential reversals, especially if confirmed by other indicators or volume patterns. Volume Confirmation: The volume ratio component helps confirm the strength of price movements. For instance, a breakout accompanied by a high volume ratio is more likely to be sustained than one with a low volume ratio. Practical Example Bullish Scenario: If the price crosses above the adjusted upper band with a high volume ratio, it suggests a strong bullish breakout. Traders might consider entering a long position, setting a stop-loss just below the VWMA or the lower band. Bearish Scenario: Conversely, if the price crosses below the adjusted lower band with a high volume ratio, it suggests a strong bearish breakout. Traders might consider entering a short position, setting a stop-loss just above the VWMA or the upper band. Conclusion The Volume-Adjusted Bollinger Bands (VABB) indicator is a powerful tool that enhances traditional Bollinger Bands by incorporating volume data. This dynamic adjustment helps traders better understand market conditions and make more informed trading decisions. By using the VABB indicator, traders can identify significant price movements supported by volume, improving the reliability of their trading signals. The Volume-Adjusted Bollinger Bands (VABB) indicator is provided for educational and informational purposes only. It is not financial advice and should not be construed as a recommendation to buy, sell, or hold any financial instrument. Trading involves significant risk of loss and is not suitable for all investors. Past performance is not indicative of future results.
مؤشرات Pine Script™
من ‎Julien_Eche‎
2
Dynamic Candle StrengthHow It Works Initialization of Dynamic Levels: The first candle's high and low are taken as the initial dynamic high and dynamic low levels. If the next candle's close price is above the dynamic high, the candle is colored green, indicating bullish conditions. If the next candle's close price is below the dynamic low, the candle is colored black, indicating bearish conditions. If a candle's high and low crossed both the dynamic high and dynamic low, the dynamic high and low levels are updated to the high and low of that candle, but the candle color will continue with the same color as the previous candle. Maintaining and Updating Dynamic Levels: The dynamic high and low are only updated if a candle's close is above the current dynamic high or below the current dynamic low. If the candle does not close above or below these levels, the dynamic high and low remain unchanged. Visual Signals: Green Bars: Indicate that the candle's close is above the dynamic high, suggesting bullish conditions. Black Bars: Indicate that the candle's close is below the dynamic low, suggesting bearish conditions. This method ensures that the dynamic high and low levels are adjusted in real-time based on the most recent significant price movements, providing a reliable measure of market sentiment.
مؤشرات Pine Script™
من ‎Optionsticker‎
RunRox - Backtesting System (ASMC)Introducing RunRox - Backtesting System (ASMC), a specially designed backtesting system built on the robust structure of our Advanced SMC indicator. This innovative tool evaluates various Smart Money Concept (SMC) trading setups and serves as an automatic optimizer, displaying which entry and exit points have historically shown the best results. With cutting-edge technology, RunRox - Backtesting System (ASMC) provides you with effective strategies, maximizing your trading potential and taking your trading to the next level 🟠 HOW OUR BACKTESTING SYSTEM WORKS Our backtesting system for the Advanced SMC (ASMC) indicator is meticulously designed to provide traders with a thorough analysis of their Smart Money Concept (SMC) strategies. Here’s an overview of how it works: 🔸 Advanced SMC Structure Our ASMC indicator is built upon an enhanced SMC structure that integrates the Institutional Distribution Model (IDM), precise retracements, and five types of order blocks (CHoCH OB, IDM OB, Local OB, BOS OB, Extreme OB). These components allow for a detailed understanding of market dynamics and the identification of key trading opportunities. 🔸 Data Integration and Analysis 1. Historical Data Testing: Our system tests various entry and exit points using historical market data. The ASMC indicator is used to simulate trades based on predefined SMC setups, evaluating their effectiveness over a specified time period. Traders can select different parameters such as entry points, stop-loss, and take-profit levels to see how these setups would have performed historically. 2. Entry and Exit Events: The backtester can simulate trades based on 12 different entry events, 14 target events, and 14 stop-loss events, providing a comprehensive testing framework. It allows for testing with multiple combinations of entry and exit strategies, ensuring a robust evaluation of trading setups. 3. Order Block Sensitivity: The system uses the sensitivity settings from the ASMC indicator to determine the most relevant order blocks and fair value gaps (FVGs) for entry and exit points. It distinguishes between different types of order blocks, helping traders identify strong institutional zones versus local zones. 🔸 Optimization Capabilities 1. Auto-Optimizer: The backtester includes an auto-optimizer feature that evaluates various setups to find those with the best historical performance. It automatically adjusts parameters to identify the most effective strategies for both trend-following and counter-trend trading. 2. Stop Loss and Take Profit Optimization: It optimizes stop-loss and take-profit levels by testing different settings and identifying those that provided the best historical results. This helps traders refine their risk management and maximize potential returns. 3. Trailing Stop Optimization: The system also optimizes trailing stops, ensuring that traders can maximize their profits by adjusting their stops dynamically as the market moves. 🔸 Comprehensive Reporting 1. Performance Metrics: The backtesting system provides detailed reports, including key performance metrics such as Net Profit, Win Rate, Profit Factor, and Max Drawdown. These metrics help traders understand the historical performance of their strategies and make data-driven decisions. 2. Flexible Settings: Traders can adjust initial balance, commission rates, and risk per trade settings to simulate real-world trading conditions. The system supports testing with different leverage settings, allowing for realistic assessments even with tight stop-loss levels. 🔸 Conclusion The RunRox Backtesting System (ASMC) is a powerful tool for traders seeking to validate and optimize their SMC strategies. By leveraging historical data and sophisticated optimization algorithms, it provides insights into the most effective setups, enhancing trading performance and decision-making. 🟠 HERE ARE THE AVAILABLE FEATURES Historical backtesting for any setup – Select any entry point, exit point, and various stop-loss options to see the results of your setup on historical data. Auto-optimizer for finding the best setups – The indicator displays settings that have shown the best results historically, providing valuable insights. Auto-optimizer for counter-trend setups – Discover entry and exit points for counter-trend trading based on historical performance. Auto-optimizer for stop-loss – The indicator shows stop-loss points that have been most effective historically. Auto-optimizer for take-profit – The indicator identifies take-profit points that have performed well in historical trading data. Auto-optimizer for trailing stop – The indicator presents trailing stop settings that have shown the best historical results. And much more within our indicator, all of which we will cover in this post. Next, we will showcase the possible entry points, targets, and stop-loss options available for testing your strategies 🟠 ENTRY SETTINGS 12 Event Triggers for Trade Entry Extr. ChoCh OB Extr. ChoCh FVG ChoCh ChoCh OB ChoCh FVG IDM OB IDM FVG BoS FVG BoS OB BoS Extr. BoS FVG Extr. BoS OB 3 Trade Direction Options Long Only: Enter long positions only Short Only: Enter short positions only Long and Short: Enter both long and short positions based on trend 3 Levels for Order Block/FVG Entries Beginning: Enter the trade at the first touch of the Order Block/FVG Middle: Enter the trade when the middle of the Order Block/FVG is reached End: Enter the trade upon full filling of the Order Block/FVG *Three levels work only for Order Blocks and FVG. For trade entries based on BOS or CHoCH, these settings do not apply as these parameters are not available for these types of entries You can choose any combination of trade entries imaginable. 🟠 TARGET SETTINGS 14 Target Events, Including Fixed % and Fixed RR (Risk/Reward): Fixed - % change in price Fixed RR - Risk Reward per trade Extr. ChoCh OB Extr. ChoCh FVG ChoCh ChoCh OB ChoCh FVG IDM OB IDM FVG BoS FVG BoS OB BoS Extr. BoS FVG Extr. BoS OB 3 Levels of Order Block/FVG for Target Beginning: Close the trade at the first touch of your target. Middle: Close the trade at the midpoint of your chosen target. End: Close the trade when your target is fully filled. Customizable Parameters Easily set your Fixed % and Fixed RR targets with a user-friendly input field. This field works only for the Fixed and Fixed RR entry parameters. When selecting a different entry point, this field is ignored Choose any combination of target events to suit your trading strategy. 🟠 STOPLOSS SETTINGS 14 Possible StopLoss Events Including Entry Orderblock/FVG Fixed - Fix the loss on the trade when the price moves by N% Entry Block Extr. ChoCh OB Extr. ChoCh FVG ChoCh ChoCh OB ChoCh FVG IDM OB IDM FVG BoS FVG BoS OB BoS Extr. BoS FVG Extr. BoS OB 3 Levels for Order Blocks/FVG Exits Beginning: Exit the trade at the first touch of the order block/FVG. Middle: Exit the trade at the middle of the order block/FVG. End: Exit the trade at the full completion of the order block/FVG. Dedicated Field for Setting Fixed % Value Set a fixed % value in a dedicated field for the Fixed parameter. This field works only for the Fixed parameter. When selecting other exit parameters, this field is ignored. 🟠 ADDITIONAL SETTINGS Trailing Stop, % Set a Trailing Stop as a percentage of your trade to potentially increase profit based on historical data. Move SL to Breakeven, bars Move your StopLoss to breakeven after exiting the entry zone for a specified number of bars. This can enhance your potential WinRate based on historical performance. Skip trade if RR less than This feature allows you to skip trades where the potential Risk-to-Reward ratio is less than the number set in this field. 🟠 EXAMPLE OF MANUAL SETUP For example, let me show you how it works on the chart. You select entry parameters, stop loss parameters, and take profit parameters for your trades, and the strategy automatically tests this setup on historical data, allowing you to see the results of this strategy. In the screenshot above, the parameters were as follows: Trade Entry: CHoCH OB (Beginning) Stop Loss: Entry Block Take Profit: Break of BOS The indicator will automatically test all possible trades on the chart and display the results for this setup. 🟠 AUTO OPTIMIZATION SETTINGS In the screenshot above, you can see the optimization table displaying various entry points, exits, and stop-loss settings, along with their historical performance results and other parameters. This feature allows you to identify trading setups that have shown the best historical outcomes. This functionality will enhance your trading approach, providing you with valuable insights based on historical data. You’ll be aware of the Smart Money Concept settings that have historically worked best for any specific chart and timeframe. Our indicator includes various optimization options designed to help you find the most effective settings based on historical data. There are 5 optimization modes, each offering unique benefits for every trader Trend Entry - Optimization of the best settings for trend-following trades. The strategy will enter trades only in the direction of the trend. If the trend is upward, it will look for long entry points and vice versa. Counter Trend Entry - Finding setups against the trend. If the trend is upward, the script will search for short entry points. This is the opposite of trend entry optimization. Stop Loss - Identifying stop-loss points that showed the best historical performance for the specific setup you have configured. This helps in finding effective exit points to minimize losses. Take Profit - Determining targets for the configured setup based on historical performance, helping to identify potentially profitable take profit levels. Trailing Stop - Finding optimal percentages for the trailing stop function based on historical data, which can potentially increase the profit of your trades. Ability to set parameters for auto-optimization within a specified range. For example, if you choose FixRR TP from 1 to 10, the indicator will automatically test all possible Risk Reward Take Profit variations from 1 to 10 and display the results for each parameter individually. Ability to set initial deposit parameters, position commissions, and risk per trade as a fixed percentage or fixed amount. Additionally, you can set the maximum leverage for a trade. There are times when the stop loss is very close to the entry point, and adhering to the risk per trade values set in the settings may not allow for such a loss in any situation. That’s why we added the ability to set the maximum possible leverage, allowing you to test your trading strategy even with very tight stop losses. Duplicated Smart Money Structure settings from our Advanced SMC indicator that you can adjust to match your trading style flexibly. All these settings will be taken into account during the optimization process or when manually calculating settings. Additionally, you can test your strategy based on higher timeframe order blocks. For example, you can test a strategy on a 1-minute chart while displaying order blocks from a 15-minute timeframe. The auto-optimizer will consider all these parameters, including higher timeframe order blocks, and will enter trades based on these order blocks. Highly flexible dashboard and results optimization settings allow you to display the tables you need and sort results by six different criteria: Profit Factor, Profit, Winrate, Max Drawdown, Wins, and Trades. This enables you to find the exact setup you desire, based on these comprehensive data points. 🟠 ALERT CUSTOMIZATION With this indicator, you can set up buy and sell alerts based on the test results, allowing you to create a comprehensive trading strategy. This feature enables you to receive real-time signals, making it a powerful tool for implementing your trading strategies. 🟠 STRATEGY PROPERTIES For backtesting, we used realistic initial data for entering trades, such as: Starting balance: $1000 Commission: 0.01% Risk per trade: 1% To ensure realistic data, we used the above settings. We offer two methods for calculating your order size, and in our case, we used a 1% risk per trade. Here’s what it means: Risk per trade: This is the maximum loss from your deposit if the trade goes against you. The trade volume can change depending on your stop-loss distance from the entry point. Here’s the formula we use to calculate the possible volume for a single trade: 1. quantity = percentage_risk * balance / loss_per_1_contract (incl. fee) Then, we calculate the maximum allowed volume based on the specified maximum leverage: 2. max_quantity = maxLeverage * balance / entry_price 3. If quantity < max_quantity, meaning the leverage is less than the maximum allowed, we keep quantity. If quantity > max_quantity, we use max_quantity (the maximum allowed volume according to the set leverage). This way, depending on the stop-loss distance, the position size can vary and be up to 100% of your deposit, but the loss in each trade will not exceed the set percentage, which in our case is 1% for this backtest. This is a standard risk calculation method based on your stop-loss distance. 🔸 Statistical Significance of Trade Data In our strategy, you may notice there weren’t enough trades to form statistically significant data. This is inherent to the Smart Money Concept (SMC) strategy, where the focus is not on the number of trades but rather on the risk-to-reward ratio per trade. In SMC strategies, it’s crucial to avoid taking numerous uncertain setups and instead perform a comprehensive analysis of the market situation. Therefore, our strategy results show fewer than 100 trades. It’s important to understand that this small sample size isn’t statistically significant and shouldn’t be relied upon for strategy analysis. Backtesting with a small number of trades should not be used to draw conclusions about the effectiveness of a strategy. 🔸 Versatile Use Cases The methods of using this indicator are numerous, ranging from identifying potentially the best-performing order blocks on the chart to creating a comprehensive trading strategy based on the data provided by our indicator. We believe that every trader will find a valuable application for this tool, enhancing their entry and exit points in trades. Disclaimer Past performance is not indicative of future results. The results shown by this indicator do not guarantee similar outcomes in the future. Use this tool as part of a comprehensive trading strategy, considering all market conditions and risks. How to access For access to this indicator, please read the author’s instructions below this post
استراتيجيات Pine Script™
من ‎RunRox‎
2
Growth TrendThis powerful indicator plots the number of growth stocks in an uptrend, providing a comprehensive view of the market's overall direction. By applying a simple moving average, users can quickly gauge the trend and make informed trading decisions. How does it work? The script pulls tickers from the S & P 500 Growth ETF. It then plots the number of stocks from the ETF that are trending above a medium-term Moving Average, signaling an uptrend. A moving average is applied to help understand the trend. The background is shaded when 3 or more consecutive days are above (green) or below (red) the moving average. Key Features: Visual Trend Identification: The indicator shades the background green when three or more consecutive days are above the moving average, indicating a strong uptrend. Conversely, it shades red when three consecutive days are below the moving average, signaling a downtrend. Breakout Insights: By tracking the trend, traders can identify when breakouts in growth stocks are more likely to occur or fail. This helps traders time their entries and exits more effectively. Trend Strength Assessment: The indicator provides a quick visual assessment of the trend's strength, enabling traders to adjust their strategies accordingly. Why is this indicator helpful? Improved Trading Decisions: By understanding the overall trend and strength of growth stocks, traders can make more informed decisions about when to buy or sell. Enhanced Risk Management: The indicator helps traders identify potential trend reversals, enabling them to adjust their positions and manage risk more effectively. Market Insights: The Growth Stock Trend Indicator provides a valuable perspective on the market's overall direction, helping traders stay ahead of the curve. By incorporating this indicator into their trading strategy, traders can gain a competitive edge and make more informed decisions in the growth stock market.
مؤشرات Pine Script™
من ‎Ollie_AllCaps‎
1
mentfx Volume SimpleThe "ment vol" indicator can be integrated into various trading strategies to gain deeper insights into market volume dynamics: Trend Confirmation: Use the black bars to identify general volume trends in conjunction with price movements. Green bars highlight moments of increasing volume, potentially indicating stronger market momentum. Swing Detection: Blue swing bars help identify significant volume spikes that may signify potential reversals or key market turning points. Swing bars can be used to spot accumulation or distribution phases within the market. Volume-Based Alerts: Traders can set alerts based on the appearance of green or blue bars to catch significant volume changes in real time. Helps in identifying potential breakout or breakdown points before they occur. Why It's Unique: The "ment vol" indicator is unique because it combines multiple volume analysis techniques into a single, easy-to-interpret visual format. By focusing on key volume patterns such as larger bars and swing bars, traders are equipped with actionable insights that go beyond simple volume analysis. This indicator is particularly useful for traders who rely on volume to confirm price movements and identify potential market shifts. Conclusion: Incorporating the "ment vol" indicator into your trading toolkit can provide a deeper understanding of market volume dynamics and enhance your ability to make timely and informed trading decisions. Whether you're a novice trader looking to improve your strategy or an experienced trader seeking a robust volume analysis tool, "ment vol" offers valuable insights that can help you navigate the markets with confidence. How It Works: The "ment vol" indicator evaluates the volume of each bar and applies specific coloring rules based on volume patterns: Up and Down Bars: The indicator colors bars black if the closing price is higher or lower than the opening price, respectively. Larger Bars: If the volume of the current bar is greater than the volume of the previous bar, the bar is colored green. Swing Bars: If the volume of a bar is greater than both the preceding and following bars, forming a swing, it is colored blue. These color-coded volume bars allow traders to quickly assess the strength and significance of volume changes in the market, providing a visual representation of potential trading opportunities.
مؤشرات Pine Script™
من ‎mentfx50‎
1
Absolute Move BandsOverview: The Absolute Move Bands indicator calculates the absolute value of the expected return, also known as "momentum" by some traders, and then displays it with standard deviation bands. The indicator also shows a moving average and a Kalman filter of the absolute move. If you take the expected return, you get what many traders commonly call "momentum." Now, if you turn the negative values into positive values by getting the magnitude of the expected return, it shows the "strength or intensity of the expected return." A low value of the absolute value of the expected return shows that the expected return is close to 0, which means that there is no significant trending behavior. The higher the value, the higher the deviation is from the mean, indicating stronger trend moves in the expected return itself. This indicator then gets the standard score of the absolute value of the expected return and then gets the moving average and Kalman Filter. This indicator is not a directional indicator, but it can help you time moves and determine the "strength" of the expected returns (also known as momentum). Interpreting the Magnitude: Low Values: A low absolute value of the expected return indicates that the expected return is close to 0, suggesting no significant trending behavior in the market. High Values: A high absolute value indicates a strong deviation from the mean, reflecting stronger trend moves in the expected return itself. Standard Score Calculation: This indicator computes the standard score (z-score) of the absolute value of the expected return. The value shows how many standard deviations the absolute return is from the mean. This helps in identifying periods of extreme magnitude. Moving Average and Kalman Filter: Moving Average: The indicator calculates the moving average of the standard score to smooth out the short-term fluctuations and show the longer-term trends in the absolute returns. Kalman Filter: Applied to further reduce noise and provide a clearer signal, it enhances the indicator's effectiveness in determining the strength of the expected returns. Standard Deviation Bands Purpose: The standard deviation bands help determine if the standard score is at an extreme low or high. High Standard Score (+2 Standard Deviation Band): Indicates that the absolute value of the expected return is at a high level, suggesting a strong trend. This could mean that the trend is at its peak and might be nearing completion. Low Standard Score (-2 Standard Deviation Band): Indicates that the absolute value of the expected return is at a low level, suggesting minimal or no trending behavior. This could imply that the expected return is around 0, and a new trend (in any direction) may start soon. How to interpret and use this indicator Two ways will be discussed on how you can use this indicator. First of all lets go back over the interpretation of the standard score and bands. High Standard Score: Indicates that the absolute value is significantly higher than usual, which suggest a strong trend which may be nearing its peak. Some traders who entered a trade at a low standard score value might want to consider taking profits or preparing for a potential reversal. Low Standard Score: Indicates that the absolute value is significantly low, close to 0, which suggest minimal trending behavior and a new trend or move may soon start. This indicator shouldn't be used alone; you may need an indicator that shows you the trend with an expected return indicator or a "momentum" indicator, because all this shows you is the strength of the trend or "momentum." So let's say that if you see that the standard score is low and the Kalman filter is increasing, then this shows that a trend may start soon, so you can use the "momentum" indicator and enter with whatever the trend is on. Another way to use the indicator is to trade extreme occurrences. If on an indicator that shows the expected returns, or "momentum," and its at an extreme standard deviation occurrence level like -2 standard deviation from the mean, and the standard score is at 2 standard deviation (the top band), and the Kalman filter starts decreasing, then the downtrend may be over and you could place a long.
مؤشرات Pine Script™
من ‎Traders_Endeavors‎
2
Dickey-Fuller Test for Mean Reversion and Stationarity **IF YOU NEED EXTRA SPECIAL HELP UNDERSTANDING THIS INDICATOR, GO TO THE BOTTOM OF THE DESCRIPTION FOR AN EVEN SIMPLER DESCRIPTION** Dickey Fuller Test: The Dickey-Fuller test is a statistical test used to determine whether a time series is stationary or has a unit root (a characteristic of a time series that makes it non-stationary), indicating that it is non-stationary. Stationarity means that the statistical properties of a time series, such as mean and variance, are constant over time. The test checks to see if the time series is mean-reverting or not. Many traders falsely assume that raw stock prices are mean-reverting when they are not, as evidenced by many different types of statistical models that show how stock prices are almost always positively autocorrelated or statistical tests like this one, which show that stock prices are not stationary. Note: This indicator uses past results, and the results will always be changing as new data comes in. Just because it's stationary during a rare occurrence doesn't mean it will always be stationary. Especially in price, where this would be a rare occurrence on this test. (The Test Statistic is below the critical value.) The indicator also shows the option to either choose Raw Price, Simple Returns, or Log Returns for the test. Raw Prices: Stock prices are usually non-stationary because they follow some type of random walk, exhibiting positive autocorrelation and trends in the long term. The Dickey-Fuller test on raw prices will indicate non-stationary most of the time since prices are expected to have a unit root. (If the test statistic is higher than the critical value, it suggests the presence of a unit root, confirming non-stationarity.) Simple Returns and Log Returns: Simple and log returns are more stationary than prices, if not completely stationary, because they measure relative changes rather than absolute levels. This test on simple and log returns may indicate stationary behavior, especially over longer periods. (The test statistic being below the critical value suggests the absence of a unit root, indicating stationarity.) Null Hypothesis (H0): The time series has a unit root (it is non-stationary). Alternative Hypothesis (H1): The time series does not have a unit root (it is stationary) Interpretation: If the test statistic is less than the critical value, we reject the null hypothesis and conclude that the time series is stationary. Types of Dickey-Fuller Tests: 1. (What this indicator uses) Standard Dickey-Fuller Test: Tests the null hypothesis that a unit root is present in a simple autoregressive model. This test is used for simple cases where we just want to check if the series has a consistent statistical property over time without considering any trends or additional complexities. It examines the relationship between the current value of the series and its previous value to see if the series tends to drift over time or revert to the mean. 2. Augmented Dickey-Fuller (ADF) Test: Tests for a unit root while accounting for more complex structures like trends and higher-order correlations in the data. This test is more robust and is used when the time series has trends or other patterns that need to be considered. It extends the regular test by including additional terms to account for the complexities, and this test may be more reliable than the regular Dickey-Fuller Test. For things like stock prices, the ADF would be more appropriate because stock prices are almost always trending and positively autocorrelated, while the Dickey-Fuller Test is more appropriate for more simple time series. Critical Values This indicator uses the following critical values that are essential for interpreting the Dickey-Fuller test results. The critical values depend on the chosen significance levels: 1% Significance Level: Critical value of -3.43. 5% Significance Level: Critical value of -2.86. 10% Significance Level: Critical value of -2.57. These critical values are thresholds that help determine whether to reject the null hypothesis of a unit root (non-stationarity). If the test statistic is less than (or more negative than) the critical value, it indicates that the time series is stationary. Conversely, if the test statistic is greater than the critical value, the series is considered non-stationary. This indicator uses a dotted blue line by default to show the critical value. If the test-static, which is the gray column, goes below the critical value, then the test-static will become yellow, and the test will indicate that the time series is stationary or mean reverting for the current period of time. What does this mean? This is the weekly chart of BTCUSD with the Dickey-Fuller Test, with a length of 100 and a critical value of 1%. So basically, in the long term, mean-reversion strategies that involve raw prices are not a good idea. You don't really need a statistical test either for this; just from seeing the chart itself, you can see that prices in the long term are trending and no mean reversion is present. For the people who can't understand that the gray column being above the blue dotted line means price doesn't mean revert, here is a more simple description (you know you are): Average (I have to include the meaning because they may not know what average is): The middle number is when you add up all the numbers and then divide by how many numbers there are. EX: If you have the numbers 2, 4, and 6, you add them up to get 12, and then divide by 3 (because there are 3 numbers), so the average is 4. It tells you what a typical number is in a group of numbers. This indicator checks if a time series (like stock prices) tends to return to its average value or time. Raw prices, which is just the regular price chart, are usually not mean-reverting (It's "always" positively autocorrelating but this group of people doesn't like that word). Price follows trends. Simple returns and log returns are more likely to have periods of mean reversion. How to use it: Gray Column (the gray bars) Above the Blue Dotted Line: The price does not mean revert (non-stationary). Gray Column Below Blue Line: The time series mean reverts (stationary) So, if the test statistic (gray column) is below the critical value, which is the blue dotted line, then the series is stationary and mean reverting, but if it is above the blue dotted line, then the time series is not stationary or mean reverting, and strategies involving mean reversion will most likely result in a loss given enough occurrences.
مؤشرات Pine Script™
من ‎Traders_Endeavors‎
1