Volume Insignts AnalyzerDescription:
The Volume Insight Analyzer is an advanced Pine Script designed for traders who want a comprehensive view of volume dynamics on their charts. This script combines multiple volume-based indicators to help identify key trading opportunities, including significant volume days, volume dry-ups, and pocket pivots.
Key Features:
VDU (Volume Dry-Up) Detection: Automatically identifies and marks days when the volume is significantly below its moving average, helping to spot potential breakout or breakdown points. Customizable volume thresholds allow for tailored analysis based on your trading strategy. The Volume Dry-Up label appears when the volume is substantially below its average level and the price is near a key moving average. This condition indicates a period of equilibrium between supply and demand, suggesting a potential low-risk entry point for traders.
Pocket Pivot Analysis using 5 and 10 Length Pocket Pivots: Highlights days with exceptionally high volume compared to recent history, indicating potential pocket pivots. Visual markers on the chart and volume bars color-coded for 5 and 10-day lengths. Pocket pivot points are identified when the volume on a given day exceeds the maximum volume observed over the past several days. Specifically, a 5-day pocket pivot point is marked when today's volume surpasses the highest selling volume of the last 5 days. A cluster of 5-day pocket pivot points within a base is a strong indicator of stock strength. Similarly, a 10-day pocket pivot point following a Volume Dry-Up (VDU) suggests a potential entry opportunity. Moreover, a pre-existing cluster of 5-day pocket pivot points before a 10-day pocket pivot point provides greater conviction in the trade.
Volume Moving Averages: Set different lengths for primary and secondary moving averages to track volume trends over daily, weekly, and monthly timeframes. Options to display moving average lines on the volume chart.
Volume Visualization:
a. Major and Minor Volume Bars: Option to display bars that are either above or below average volume levels. Adjustable settings to show or hide these bars based on user preference.
b. Volume Bar Coloring: Volume bars are color-coded based on significant volume thresholds, including green for bullish signals, red for bearish signals, and orange for volume dry-ups.
Volume Metrics Table: A customizable table that displays real-time volume metrics including Relative Volume (RVOL), Turnover, and the number of high volume days. The table can be oriented horizontally or vertically and styled according to your theme preferences.
Visual Indicators:
a) Volume Dry-Up (VDU) Labels: Clearly marked VDU events with textual annotations on the chart.
b) Bullish and Bearish Arrows: Arrows indicating potential bullish or bearish closes based on volume analysis, enhancing decision-making.
Customization Options:
a) Dark and Light Theme Support: Toggle between dark and light themes to match your chart settings.
b) Adjustable Parameters: Easily configure input settings such as volume thresholds, MA lengths, and table display options to fit your trading style.
How to Use:
Set Parameters: Adjust the script settings such as volume thresholds, moving average lengths, and display preferences according to your analysis needs.
Analyze Volume Patterns: Use the indicators and visual markers provided by the script to identify significant volume patterns and potential trading signals.
Monitor Metrics: Refer to the volume metrics table for a quick overview of key volume-related statistics and trends.
Make Informed Decisions: Utilize the visual cues and volume data provided by the script to enhance your trading strategy and make more informed decisions.
Disclaimer:
This script is for informational purposes only and should not be considered as trading advice. Use it in conjunction with other analysis tools and consult with a financial advisor if needed. Trading involves risk, and past performance does not guarantee future results.
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Multi-Frame Market Sentiment DashboardOverview
This Pine Script™ code generates a "Market Sentiment Dashboard" on TradingView, providing a visual summary of market sentiment across multiple timeframes. This tool aids traders in making informed decisions by displaying real-time sentiment analysis based on Exponential Moving Averages (EMA).
Key Features
Panel Positioning:
Custom Placement: Traders can position the dashboard at the top, middle, or bottom of the chart and align it to the left, center, or right, ensuring optimal integration with other chart elements.
Customizable Colors:
Sentiment Colors: Users can define colors for bullish, bearish, and neutral market conditions, enhancing the dashboard's readability.
Text Color: Customizable text color ensures clarity against various background colors.
Label Size:
Scalable Labels: Adjustable label sizes (from very small to very large) ensure readability across different screen sizes and resolutions.
Market Sentiment Calculation:
EMA-Based Sentiment: The dashboard calculates sentiment using a 9-period EMA. If the EMA is higher than two bars ago, the sentiment is bullish; if lower, it's bearish; otherwise, it's neutral.
Multiple Timeframes: Sentiment is calculated for several timeframes: 1 minute, 3 minutes, 5 minutes, 15 minutes, 30 minutes, 1 hour, 4 hours, and 1 day. This broad analysis provides a comprehensive view of market conditions.
Dynamic Table:
Structured Display: The dashboard uses a table to organize and display sentiment data clearly.
Real-Time Updates: The table updates in real-time, providing traders with up-to-date market information.
How It Works
EMA Calculation: The script requests EMA(9) values for each specified timeframe and compares the current EMA with the EMA from two bars ago to determine market sentiment.
Color Coding: Depending on the sentiment (Bullish, Bearish, or Neutral), the corresponding cell in the table is color-coded using predefined colors.
Table Display: The table displays the timeframe and corresponding sentiment, allowing traders to quickly assess market trends.
Benefits to Traders
Quick Assessment: Traders can quickly evaluate market sentiment across multiple timeframes without switching charts or manually calculating indicators.
Enhanced Visualization: The color-coded sentiment display makes it easy to identify trends at a glance.
Multi-Timeframe Analysis: Provides a broad view of short-term and long-term market trends, helping traders confirm trends and avoid false signals.
This dashboard enhances the overall trading experience by providing a comprehensive, customizable, and easy-to-read summary of market sentiment.
Usage Instructions
Add the Script to Your Chart: Apply the "Market Sentiment Dashboard" indicator to your TradingView chart.
Customize Settings: Adjust the panel position, colors, and label sizes to fit your preferences.
Interpret Sentiment: Use the color-coded table to quickly understand the market sentiment across different timeframes and make informed trading decisions.
Nadaraya-Watson Probability [Yosiet]The script calculates and displays probability bands around price movements, offering insights into potential market trends.
Setting Up the Script
Window Size: Determines the length of the window for the Nadaraya-Watson estimation. A larger window smooths the data more but might lag current market conditions.
Bandwidth: Controls the bandwidth for the kernel regression, affecting the smoothness of the probability bands.
Reading the Data Table
The script dynamically updates a table positioned at the bottom right of your chart, providing real-time insights into market probabilities. Here's how to interpret the table:
Table Columns: The table is organized into three columns:
Up: Indicates the probability or relative change percentage for the upper band.
Down: Indicates the probability or relative change percentage for the lower band.
Table Rows: There are two main rows of interest:
P%: Shows the price change percentage difference between the bands and the closing price. A positive value in the "Up" column suggests the upper band is above the current close, indicating potential upward momentum. Conversely, a negative value in the "Down" column suggests downward momentum.
R%: Displays the relative inner change percentage difference between the bands, offering a measure of the market's volatility or stability within the bands.
Utilizing the Insights
Market Trends: A widening gap between the "Up" and "Down" percentages in the "P%" row might indicate increasing market volatility. Traders can use this information to adjust their risk management strategies accordingly.
Entry and Exit Points: The "R%" row provides insights into the relative position of the current price within the probability bands. Traders might consider positions closer to the lower band as potential entry points and positions near the upper band as exit points or take-profit levels.
Conclusion
The Nadaraya-Watson Probability script offers a sophisticated tool for traders looking to incorporate statistical analysis into their trading strategy. By understanding and utilizing the data presented in the script's table, traders can gain insights into market trends and volatility, aiding in decision-making processes. Remember, no indicator is foolproof; always consider multiple data sources and analyses when making trading decisions.
GKD-M Stepped Baseline Optimizer [Loxx]The Giga Kaleidoscope GKD-M Stepped Baseline Optimizer is a Metamorphosis module included in the "Giga Kaleidoscope Modularized Trading System."
█ Introduction
The GKD-M Stepped Baseline Optimizer is an advanced component of the Giga Kaleidoscope Modularized Trading System (GKD), designed to enhance trading strategy development by dynamically optimizing Baseline moving averages. This tool allows traders to evaluate over 65 moving averages, adjusting them across multiple periods to identify which settings yield the highest win rates for their trading strategies. The optimizer systematically tests these moving averages across specified timeframes and intervals, offering insights into net profit, total closed trades, win percentages, and other critical metrics for both long and short positions. Traders can define the initial period and incrementally adjust this value to explore a wide range of periods, thus fine-tuning their strategies with precision. What sets the GKD-M Stepped Baseline Optimizer apart is its unique capability to adapt the baseline moving average according to the highest win rates identified during backtesting, at each trading candle. This win-rate adaptive approach ensures that the trading system is always aligned with the most effective period settings for the selected moving average, enhancing the system's overall performance. Moreover, the 'stepped' aspect of this optimizer introduces a filtering process based ons, significantly reducing market noise and ensuring that identified trends are both significant and reliable. This feature is critical for traders looking to mitigate the risks associated with volatile market conditions and to capitalize on genuine market movements.In essence, the GKD-M Stepped Baseline Optimizer is tailored for traders who utilize the GKD trading system, offering a sophisticated tool to refine their baseline indicators dynamically, ensuring that their trading strategies are continuously optimized for maximum efficacy.
**the backtest data rendered to the chart above uses $5 commission per trade and 10% equity per trade with $1 million initial capital. Each backtest result for each ticker assumes these same inputs. The results are NOT cumulative, they are separate and isolated per ticker and trading side, long or short**
█ Core Features
Stepped Baseline for Noise Reduction
One of the hallmark features of the GKD-M Stepped Baseline Optimizer is its stepped baseline capability. This advanced functionality employs volatility filters to refine the selection of moving averages, significantly reducing market noise. The optimizer ensures that only substantial and reliable trends are considered, eliminating the false signals often caused by minor price fluctuations. This stepped approach to baseline optimization is critical for traders aiming to develop strategies that are both resilient and responsive to genuine market movements.
Dynamic Win Rate Adaptive Capability
Another cornerstone feature is the optimizer’s dynamic win rate adaptive capability. This unique aspect allows the optimizer to adjust the moving average period settings in real-time, based on the highest win rates derived from backtesting over a predefined range. At every trading candle, the optimizer evaluates a comprehensive set of backtesting data to ascertain the optimal period settings for the moving average in use. To perform the backtesting, the trader selects an initial period input (default is 60) and a skip value that increments the initial period input up to seven times. For instance, if a skip value of 5 is chosen, the Baseline Optimizer will run the backtest for the selected moving average on periods such as 60, 65, 70, 75, and so on, up to 90. If the user selects an initial period input of 45 and a skip value of 2, the Baseline Optimizer will conduct backtests for the chosen moving average on periods like 45, 47, 49, 51, and so forth, up to 57. The GKD-M Stepped Baseline Optimizer then exports the baseline with the highest cumulative win rate per candle to any baseline-enabled GKD backtest. This ensures that the baseline indicator remains continually aligned with the most efficacious parameters, dynamically adapting to changing market conditions.
Comprehensive Moving Averages Evaluation
The optimizer’s ability to test over 65 different moving averages across multiple periods stands as a testament to its comprehensive analytical capability. Traders have the flexibility to explore a wide array of moving averages, from traditional ones like the Simple Moving Average (SMA) and Exponential Moving Average (EMA) to more complex types such as the Hull Moving Average (HMA) and Adaptive Moving Average (AMA). This extensive evaluation allows traders to pinpoint the moving average that best aligns with their trading strategy and market conditions, further enhancing the system’s adaptability and effectiveness.
Volatility Filtering and Ticker Volatility Types
Incorporating a wide range of volatility types, including the option to utilize external volatility tickers like the VIX for filtering, adds another layer of sophistication to the optimizer. This feature allows traders to calibrate their baseline according to externals, providing an additional dimension of customization. Whether using standard deviation, ATR, or external volatility indices, traders can fine-tune their strategies to be responsive to the broader market sentiment and volatility trends.
█ Key Inputs
Baseline Settings
• Baseline Source: Determines the price data (Open, High, Low, Close) used for moving average calculations.
• Baseline Period: The starting period for moving average calculation.
• Backtest Skip: Incremental steps for period adjustments in the optimization process.
• Baseline Filter Type: Selection from over 65 moving averages for baseline calculation.
Volatility and Filter Settings
• Price Filter Type & Moving Average Filter Type: Defines thement applied to the price or the moving average, enhancing filter specificity.
• Filter Options: Allows users to select the application area of the volatility filter (price, moving average, or both).
• Filter Multiplier & Period: Configures the intensity and temporal scope of the filter, fine-tuning sensitivity to market volatility.
Backtest Configuration
• Window Period: Specifies the length of the backtesting window in days.
• Backtest Type: Chooses between a fixed window or cumulative data approach for backtesting.
• Initial Capital, Order Size, & Type: Sets the financial parameters for backtesting, including starting equity and the scale of trades.
• Commission per Order: Accounts for trading costs within backtest profitability calculations.
Date and Time Range
• From/Thru Year/Month/Day: Defines the historical period for strategy testing.
• Entry Time: Specifies the time frame during which trades can be initiated, crucial for strategies sensitive to market timing.
Volatility Measurements for Goldie Locks Volatility Qualifiers
• Mean Type & Period: Chooses the moving average type and period for volatility assessment.
• Inner/Outer Volatility Qualifier Multipliers: Adjusts the boundaries for volatility-based trade qualification.
• Activate Qualifier Boundaries: Enables or disables the upper and lower volatility qualifiers.
Advanced Volatility Inputs
• Volatility Ticker Selection & Trading Days: Incorporates external volatility indices (e.g., VIX) into the strategy, adjusting for market volatility.
• Static Percent, MAD Internal Filter Period, etc.: Provides fixed or adaptive volatility thresholds for filtering.
UI Customization
• Baseline Width & Table Display Options: Customizes the visual representation of the baseline and the display of optimization results.
• Table Header/Content Color & Text Size: Enhances readability and user interface aesthetics.
Export Options
• Export Data: Selects the specific metric to be exported from the script, such as net profit or average profit per trade.
Moving Average Specific Parameters
Specific inputs tailored to the characteristics of selected moving averages (e.g., Fractal Adjusted (FRAMA), Least Squares Moving Average (LSMA), T3, etc.), allowing users to fine-tune the behavior of these averages based on unique formula requirements.
█ Indicator UI
• Long and Short Baselines: The optimizer differentiates trends through two distinct baselines: a green line for long (uptrend) baselines and a red line for short (downtrend) baselines. These baselines alternate activation based on the current trend direction as determined by the moving average plus length combination for the candle in view.
Ambiguity in market direction, when an uptrend and downtrend are concurrently indicated, is visually represented by yellow lines.
• Stepping Mechanism for Trend Visualization: Adjusting the source input and the moving average output based on volatility, the indicator exhibits a stepped appearance on the chart. This mechanism ensures that only substantial market movements, surpassing a specified volatility threshold, are recognized as trend changes.
Stepping Activated
• Goldilocks Zone: Beyond the long and short baselines, the Goldilocks zone introduces a distinct moving average that closely follows the selected price or source input, aiming to strike the perfect balance between not too much and not too little market movement for trading. The upper limit of the Goldilocks zone indicates a market stretch too far for advantageous trading (overextension), while the lower limit suggests inadequate market movement for entry (underextension). Trading within the Goldilocks zone is deemed optimal, as it signifies sufficient but not excessive volatility for entering trades, aligning with either the long or short baseline recommendations. Moreover, the mean of the Goldilocks zone serves as a critical indicator, offering a median reference point that aligns closely with the market's current state. This mean is pivotal for traders, as it represents a 'just right' condition for market entry, embodying the essence of the Goldilocks principle in financial trading strategies.
• Signal Indicators and Entry Points: The chart includes with green or red dots to signify valid price points within the Goldilocks zone, indicative of conducive trading conditions. Furthermore, small directional arrows at the chart's bottom highlight potential long or short entry points, validated by the Goldilocks zone's parameters.
• Data Table: A table presenting real-time statistics from the current candle backward through the chosen range offers insights into win rates and other relevant data, aiding in informed decision-making. This table adapts with each new candle, highlighting the most favorable win rates for both long and short positions.
█ Optimizing Strategy with Backtesting
Optimizing a trading strategy with backtesting involves rigorously testing the strategy on historical data to evaluate its performance and robustness before applying it in live markets. The GKD-M Stepped Baseline Optimizer incorporates advanced backtesting capabilities, offering both cumulative and rolling window types of backtests. Here's how each backtest type operates and the insights they provide for refining trading strategies:
Cumulative Backtest
• Overview: A cumulative backtest evaluates a strategy's performance over a continuous period without resetting the strategy parameters or the simulated trading capital at the beginning of each new period.
• Utility: This type is useful for understanding a strategy's long-term viability, assessing how it adapts to different market conditions over an extended timeframe.
• Interpreting Statistics: Cumulative backtest results often focus on overall return, drawdowns, win rate, and the Sharpe ratio. A strategy with consistent returns, manageable drawdowns, a high win rate, and a favorable Sharpe ratio is considered robust.
Rolling Window Backtest
• Overview: Unlike the cumulative approach, a rolling window backtest divides the historical data into smaller, overlapping or non-overlapping periods (windows), running the strategy separately on each. After each window, the strategy parameters and simulated trading capital are reset.
• Utility: This method is invaluable for assessing a strategy's consistency and adaptability to various market phases. It helps identify if the strategy's performance is dependent on specific market conditions.
• Interpreting Statistics: For rolling window backtests, consistency is key. Look for similar performance metrics (returns, drawdowns, win rate) across different windows. Variability in performance indicates sensitivity to market conditions, suggesting the need for strategy adjustments.
Strategy Refinement Through Backtest Statistics
• Net Profit and Loss: Measures the strategy’s overall effectiveness. Consistent profitability across different market conditions is a positive indicator.
• Win Rate and Profit Factor: High win rates and profit factors indicate a strategy's efficiency in capturing gains over losses.
• Average Profit per Trade: Understanding the strategy's ability to generate profit on a per-trade basis can highlight its operational efficiency.
• Average Number of Bars in Trade: This metric helps understand the strategy's market exposure and timing efficiency.
█ Exporting Data and Integration with GKD Backtests
The GKD-M Stepped Baseline Optimizer seamlessly integrates with the broader GKD trading system, allowing traders to export the optimization data and leverage it within the various GKD backtest modules. This feature allows users to forward the GKD-M Stepped Baseline Optimizer adaptive signals to a GKD backtest to be used as a Baseline component in a GKD trading system.
█ Moving Averages included in the Stepped Baseline Optimizer
The GKD-M Stepped Baseline Optimizer incorporates an extensive array of over 65 moving averages, each with unique characteristics and implications for trading strategy development. This comprehensive suite enables traders to conduct nuanced analysis and optimization, ensuring the selection of the most effective moving average for Baseline input into their GKD trading system.
Adaptive Moving Average - AMA
ADXvma - Average Directional Volatility Moving Average
Ahrens Moving Average
Alexander Moving Average - ALXMA
Coral
Deviation Scaled Moving Average - DSMA
Donchian
Double Exponential Moving Average - DEMA
Double Smoothed Exponential Moving Average - DSEMA
Double Smoothed FEMA - DSFEMA
Double Smoothed Range Weighted EMA - DSRWEMA
Double Smoothed Wilders EMA - DSWEMA
Double Weighted Moving Average - DWMA
Ehlers Optimal Tracking Filter - EOTF
Exponential Moving Average - EMA
Fast Exponential Moving Average - FEMA
Fractal Adaptive Moving Average - FRAMA
Generalized DEMA - GDEMA
Generalized Double DEMA - GDDEMA
Geometric Mean Moving Average
Hull Moving Average (Type 1) - HMA1
Hull Moving Average (Type 2) - HMA2
Hull Moving Average (Type 3) - HMA3
Hull Moving Average (Type 4) - HMA4
IE/2 - Early T3 by Tim Tilson
Integral of Linear Regression Slope - ILRS
Instantaneous Trendline
Kalman Filter
Kaufman Adaptive Moving Average - KAMA
Laguerre Filter
Leader Exponential Moving Average
Linear Regression Value - LSMA (Least Squares Moving Average)
Linear Weighted Moving Average - LWMA
McGinley Dynamic
McNicholl EMA
Non-Lag Moving Average
Ocean NMA Moving Average - ONMAMA
One More Moving Average - OMA
Parabolic Weighted Moving Average
Probability Density Function Moving Average - PDFMA
Quadratic Regression Moving Average - QRMA
Range Filter
Range Weighted EMA - RWEMA
Recursive Moving Trendline
Regularized EMA - REMA
Simple Decycler - SDEC
Simple Loxx Moving Average - SLMA
Simple Moving Average - SMA
Sine Weighted Moving Average
Smoothed LWMA - SLWMA
Smoothed Moving Average - SMMA
Smoother
Super Smoother
T3
Tether Lines
Three-pole Ehlers Butterworth
Three-pole Ehlers Smoother
Triangular Moving Average - TMA
Triangle Moving Average Generalized
Triple Exponential Moving Average - TEMA
Two-pole Ehlers Butterworth
Two-pole Ehlers smoother
Ultimate Smoother
Variable Index Dynamic Average - VIDYA
Variable Moving Average - VMA
Volume Weighted EMA - VEMA
Volume Weighted Moving Average - VWMA
Zero-Lag DEMA - Zero Lag Double Exponential Moving Average
Zero-Lag Moving Average
Zero Lag TEMA - Zero Lag Triple Exponential Moving Average
█ Volatility Types and Filtering
The GKD-M Stepped Baseline Optimizer features a comprehensive selection of over 15 volatility types, each tailored to capture different aspects of market behavior and risk.
Volatility Ticker Selection: Enables direct incorporation of external volatility indicators like VIX and EUVIX into the script for market sentiment analysis, signal filtering enhancement, and real-time risk management adjustments.
Standard Deviation of Logarithmic Returns: Quantifies asset volatility using the standard deviation applied to logarithmic returns, capturing symmetric price movements and financial returns' compound nature.
Exponential Weighted Moving Average (EWMA) for Volatility: Focuses on recent market information by applying exponentially decreasing weights to squared logarithmic returns, offering a dynamic view of market volatility.
Roger-Satchell Volatility Measure: Estimates asset volatility by analyzing the high, low, open, and close prices, providing a nuanced view of intraday volatility and market dynamics.
Close-to-Close Volatility Measure: Calculates volatility based on the closing prices of stocks, offering a streamlined but limited perspective on market behavior.
Parkinson Volatility Measure: Enhances volatility estimation by including high and low prices of the trading day, capturing a more accurate reflection of intraday market movements.
Garman-Klass Volatility Measure: Incorporates open, high, low, and close prices for a comprehensive daily volatility measure, capturing significant price movements and market activity.
Yang-Zhang Volatility Measure: Offers an efficient estimation of stock market volatility by combining overnight and intraday price movements, capturing opening jumps and overall market dynamics.
Garman-Klass-Yang-Zhang Volatility Measure: Merges the benefits of Garman-Klass and Yang-Zhang measures, providing a fuller picture of market volatility including opening market reactions.
Pseudo GARCH(2,2) Volatility Model: Mimics a GARCH(2,2) process using exponential moving averages of squared returns, highlighting volatility shocks and their future impact.
ER-Adaptive Average True Range (ATR): Adjusts the ATR period length based on market efficiency, offering a volatility measure that adapts to changing market conditions.
Adaptive Deviation: Dynamically adjusts its calculation period to offer a nuanced measure of volatility that responds to the market's intrinsic rhythms.
Median Absolute Deviation (MAD): Provides a robust measure of statistical variability, focusing on deviations from the median price, offering resilience against outliers.
Mean Absolute Deviation (MAD): Measures the average magnitude of deviations from the mean price, facilitating a straightforward understanding of volatility.
ATR (Average True Range): Finds the average of true ranges over a specified period, indicating the expected price movement and market volatility.
True Range Double (TRD): Offers a nuanced view of volatility by considering a broader range of price movements, identifying significant market sentiment shifts.
Stock WatchOverview
Watch list are very common in trading, but most of them simply provide the means of tracking a list of symbols and their current price. Then, you click through the list and perform some additional analysis individually from a chart setup. What this indicator is designed to do is provide a watch list that employs a high/low price range analysis in a table view across multiple time ranges for a much faster analysis of the symbols you are watching.
Discussion
The concept of this Stock Watch indicator is best understood when you think in terms of a 52 Week Range indication on many financial web sites. Taken a given symbol, what is the high and the low over a 52 week range and then determine where current price is within that range from a percentage perspective between 0% and 100%.
With this concept in mind, let's see how this Stock Watch indicator is meant to benefit.
There are four different H/L ranges relative to the chart's setting and a Scope property. Let's use a three month (3M) chart as our example and set the indicator's Scope = 4. A 3M chart provides three months of data in a single candle, now when we set the Scope = 4 we are stating that 1X is going to look over four candles for the high/low range.
The Scope property is used to determine how many candles it is to scan to determine the high/low range for the corresponding 1X, 3X, 5X and 10X periods. This is how different time ranges are put into perspective. Using a 3M chart with Scope = 4 would represent the following time windows:
- 1X = 3M * 4 is a 12 Months or 1 Year High/Low Range
- 3X = 3M * 4 * 3 is a 36 Months or 3 Years High/Low Range
- 5X = 3M * 4 * 5 is a 60 Months or 5 Years High/Low Range
- 10X = 3M * 4 * 10 is a 120 Months or 10 Years High/Low Range.
With these calculations, the indicator then determines where current price is within each of these High/Low ranges from a percentage perspective between 0% and 100%.
Once the 0% to 100% value is calculated, it then will shade the value according to a color gradient from red to green (or any other two colors you set the indictor to). This color shading really helps to interpret current price quickly.
The greater power to this range and color shading comes when you are able to see where price is according to price history across the multiple time windows. In this example, there is quick analysis across 1 Year, 3 Year, 5 Year and 10 Year windows.
Now let's further improve this quick analysis over 15 different stocks for which the indicator allows you to watch up to at any one time.
For value traders this is huge, because we're always looking for the bargains and we wait for price to be in the value range. Using this indicator helps to instantly see if price has entered a value range before we decide to do further analysis with other charting and fundamental tools.
The Code
The heart of all this is really very simple as you can see in the following code snippet. We're simply looking for the highest high and lowest low across the different scopes and calculating the percentage of the range where current price is for each symbol being watched.
scope = baseScope
watch1X = math.round(((watchClose - ta.lowest(watchLow, scope)) / (ta.highest(watchHigh, scope) - ta.lowest(watchLow, scope))) * 100, 0)
table.cell(tblWatch, columnId, 2, str.format("{0, number, #}%", watch1X), text_size = size.small, text_color = colorText, bgcolor = getBackColor(watch1X))
//3X Lookback
scope := baseScope * 3
watch3X = math.round(((watchClose - ta.lowest(watchLow, scope)) / (ta.highest(watchHigh, scope) - ta.lowest(watchLow, scope))) * 100, 0)
table.cell(tblWatch, columnId, 3, str.format("{0, number, #}%", watch3X), text_size = size.small, text_color = colorText, bgcolor = getBackColor(watch3X))
Conclusion
The example I've laid out here are for large time windows, because I'm a long term investor. However, keep in mind that this can work on any chart setting, you just need to remember that your chart's time period and scope work together to determine what 1X, 3X, 5X and 10X represent.
Let me try and give you one last scenario on this. Consider your chart is set for a 60 minute chart, meaning each candle represents 60 minutes of time and you set the Stock Watch indicator to a scope = 4. These settings would now represent the following and you would be watching up to 15 different stocks across these windows at one time.
1X = 60 minutes * 4 is 240 minutes or 4 hours of time.
3X = 60 minutes * 4 * 3 = 720 minutes or 12 hours of time.
5X = 60 minutes * 4 * 5 = 1200 minutes or 20 hours of time.
10X = 60 minutes * 4 * 10 = 2400 minutes or 40 hours of time.
I hope you find value in my contribution to the cause of trading, and if you have any comments or critiques, I would love to here from you in the comments.
Dividend Calendar (Zeiierman)█ Overview
The Dividend Calendar is a financial tool designed for investors and analysts in the stock market. Its primary function is to provide a schedule of expected dividend payouts from various companies.
Dividends, which are portions of a company's earnings distributed to shareholders, represent a return on their investment. This calendar is particularly crucial for investors who prioritize dividend income, as it enables them to plan and manage their investment strategies with greater effectiveness. By offering a comprehensive overview of when dividends are due, the Dividend Calendar aids in informed decision-making, allowing investors to time their purchases and sales of stocks to optimize their dividend income. Additionally, it can be a valuable tool for forecasting cash flow and assessing the financial health and dividend-paying consistency of different companies.
█ How to Use
Dividend Yield Analysis:
By tracking dividend growth and payouts, traders can identify stocks with attractive dividend yields. This is particularly useful for income-focused investors who prioritize steady cash flow from their investments.
Income Planning:
For those relying on dividends as a source of income, the calendar helps in forecasting income.
Trend Identification:
Analyzing the growth rates of dividends helps in identifying long-term trends in a company's financial health. Consistently increasing dividends can be a sign of a company's strong financial position, while decreasing dividends might signal potential issues.
Portfolio Diversification:
The tool can assist in diversifying a portfolio by identifying a range of dividend-paying stocks across different sectors. This can help mitigate risk as different sectors may react differently to market conditions.
Timing Investments:
For those who follow a dividend capture strategy, this indicator can be invaluable. It can help in timing the buying and selling of stocks around their ex-dividend dates to maximize dividend income.
█ How it Works
This script is a comprehensive tool for tracking and analyzing stock dividend data. It calculates growth rates, monthly and yearly totals, and allows for custom date handling. Structured to be visually informative, it provides tables and alerts for the easy monitoring of dividend-paying stocks.
Data Retrieval and Estimation: It fetches dividend payout times and amounts for a list of stocks. The script also estimates future values based on historical data.
Growth Analysis: It calculates the average growth rate of dividend payments for each stock, providing insights into dividend consistency and growth over time.
Summation and Aggregation: The script sums up dividends on a monthly and yearly basis, allowing for a clear view of total payouts.
Customization and Alerts: Users can input custom months for dividend tracking. The script also generates alerts for upcoming or current dividend payouts.
Visualization: It produces various tables and visual representations, including full calendar views and income tables, to display the dividend data in an easily understandable format.
█ Settings
Overview:
Currency:
Description: This setting allows the user to specify the currency in which dividend values are displayed. By default, it's set to USD, but users can change it to their local currency.
Impact: Changing this value alters the currency denomination for all dividend values displayed by the script.
Ex-Date or Pay-Date:
Description: Users can select whether to show the Ex-dividend day or the Actual Payout day.
Impact: This changes the reference date for dividend data, affecting the timing of when dividends are shown as due or paid.
Estimate Forward:
Description: Enables traders to predict future dividends based on historical data.
Impact: When enabled, the script estimates future dividend payments, providing a forward-looking view of potential income.
Dividend Table Design:
Description: Choose between viewing the full dividend calendar, just the cumulative monthly dividend, or a summary view.
Impact: This alters the format and extent of the dividend data displayed, catering to different levels of detail a user might require.
Show Dividend Growth:
Description: Users can enable dividend growth tracking over a specified number of years.
Impact: When enabled, the script displays the growth rate of dividends over the selected number of years, providing insight into dividend trends.
Customize Stocks & User Inputs:
This setting allows users to customize the stocks they track, the number of shares they hold, the dividend payout amount, and the payout months.
Impact: Users can tailor the script to their specific portfolio, making the dividend data more relevant and personalized to their investments.
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Disclaimer
The information contained in my Scripts/Indicators/Ideas/Algos/Systems does not constitute financial advice or a solicitation to buy or sell any securities of any type. I will not accept liability for any loss or damage, including without limitation any loss of profit, which may arise directly or indirectly from the use of or reliance on such information.
All investments involve risk, and the past performance of a security, industry, sector, market, financial product, trading strategy, backtest, or individual's trading does not guarantee future results or returns. Investors are fully responsible for any investment decisions they make. Such decisions should be based solely on an evaluation of their financial circumstances, investment objectives, risk tolerance, and liquidity needs.
My Scripts/Indicators/Ideas/Algos/Systems are only for educational purposes!
Liquidity Depth [Pro+]Description:
Liquidity Depth Pro+ is a trading tool with a remarkable adaptability and perfectly aligned with the intricate demands of the futures, forex, and bond markets. This indicator is based on a concept taught by the Inner Circle Trader (ICT), who explains that institutions tend to dig deeper into Liquidity Pools above highs and below lows. Specifically, ICT mentions how in Forex these Liquidity Depths are classically manifested as 10-20-30 pips respectively.
This tool allows the Analyst to adapt this concept based on their understanding of price. It delves into the essence of institutional trading, exposing deeper liquidity depth pursued by institutional giants and astute bank traders that lay further than the mere extremities of price.
CME_MINI:NQ1! Example (Tuesday):
Price raids Monday's low
Price raids Friday's low
Price digs deeper into one of Friday's Deep Liquidity Pools
Low of the Day Reversal
Note: the Depths used in this example are 30-60-90 points.
Key Features:
Versatility Across Assets: Liquidity Depth Pro+ is finely tailored for futures, forex, and bond markets, making it an all-encompassing solution suitable for a broad range of financial instruments.
Timeframe Customization: Liquidity Depth Pro+ allows users to decide Timeframe Liquidity empowering the analyst with flexibility.
Historical Pools: Choose up to the last 20 highs and lows to mark liquidity pools from the User Selected Timeframe.
Universal Trading Style: Regardless of your trading approach, be it trend-following or reversal models, this indicator embraces all styles. It offers a holistic perspective to navigating liquidity zones above highs and below lows of the chosen Timeframe.
Visual Precision: This indicator visualizes the liquidity depth with a customizable style, allowing the analyst to frame the position of deeper liquidity pools above highs and below lows.
Liquidity Table: Keep track of liquidity levels and unlock faster decision making by taking advantage of the visual Liquidity Table cues.
Adaptive Table Colors: When price is above your desired liquidity pool high, the table will match the liquidity high color to indicate a current liquidity raid or deeper pool being attacked. Vice versa, when price is below your desired liquidity pool low, the table will match the liquidity low color.
Real-Time Alerts: Save Time with live alerts that provide valuable insights into potential opportunities and liquidity purges at your desired liquidity levels.
Other Features:
Choose the Depth Type ("Auto", "Value", "Ticks", "Pips"). The “Auto” feature will select the best unit of measurement for the depths based on the current market on chart.
Choose to show up to Three Liquidity Depths.
Customize the Liquidity Line Style.
Customize the Liquidity Line Color.
Customize the Liquidity Line Width.
Customize Table Size and Location
Usage Guidance:
Add Liquidity Depth to your Tradingview chart.
Customize your desired Timeframe and Liquidity Depths to align with your personal preference.
Observe where the Liquidity Lines manifest above and below your chosen Timeframe’s highs and lows respectively, once they are raided.
Leverage this invaluable information to frame the narrative, whether you opt to pursue liquidity or capitalize on post-purge reversals.
These tools are available ONLY on the TradingView platform.
Terms and Conditions
Our charting tools are products provided for informational and educational purposes only and do not constitute financial, investment, or trading advice. Our charting tools are not designed to predict market movements or provide specific recommendations. Users should be aware that past performance is not indicative of future results and should not be relied upon for making financial decisions. By using our charting tools, the purchaser agrees that the seller and the creator are not responsible for any decisions made based on the information provided by these charting tools. The purchaser assumes full responsibility and liability for any actions taken and the consequences thereof, including any loss of money or investments that may occur as a result of using these products. Hence, by purchasing these charting tools, the customer accepts and acknowledges that the seller and the creator are not liable nor responsible for any unwanted outcome that arises from the development, the sale, or the use of these products.
Finally, the purchaser indemnifies the seller from any and all liability. If the purchaser was invited through the Friends and Family Program, they acknowledge that the provided discount code only applies to the first initial purchase of the Toodegrees Premium Suite subscription. The purchaser is therefore responsible for cancelling – or requesting to cancel – their subscription in the event that they do not wish to continue using the product at full retail price. If the purchaser no longer wishes to use the products, they must unsubscribe from the membership service, if applicable. We hold no reimbursement, refund, or chargeback policy. Once these Terms and Conditions are accepted by the Customer, before purchase, no reimbursements, refunds or chargebacks will be provided under any circumstances.
By continuing to use these charting tools, the user acknowledges and agrees to the Terms and Conditions outlined in this legal disclaimer.
Forex & Stock Daily WatchList And Screener [M]Hi, this is a watchlist and screener indicator for Forex and Stocks.
This indicator is designed for traders who trade in the forex markets and monitor developments in indices and other currency pairs.
It includes information on 14 indices such as the volatility index, Baltic dry index, etc. You can customize the indices as you wish. The indices table contains the index's price (or points), daily change, stochastic value, and trend direction.
The second table is designed for trading forex and stock currency pairs.
In this table, you will find information such as price, volume, change, stochastic, RSI, trend direction, and MACD result for all traded pairs. You can customize all the currency pairs in this table as you wish, and you can also tailor the oscillator settings to your preferences.
In the settings section, you can use checkboxes to hide the pairs in both tables.
The "Customize" section in the settings allows you to personalize the table appearances according to your preferences.
Buy/Sell EMA CandleThis indicator is designed to display various technical indicators, candle patterns, and trend directions on a price chart. Let's break down the code and explain its different sections:
Exponential Moving Averages (EMA):
The code calculates and plots five EMAs of different lengths (13, 21, 55, 90, and 200) on the price chart. These EMAs are used to identify trends and potential crossovers.
Engulfing Candle Patterns:
The code identifies and highlights potential bullish and bearish engulfing candle patterns. It checks if the current candle's body size is larger than the combined body sizes of the previous and subsequent four candles. If this condition is met, it marks the pattern on the chart.
s3.tradingview.com
EMA Crossovers:
The code identifies and highlights points where the shorter EMA (ema1) crosses above or below the longer EMA (ema2). It plots circles to indicate these crossover points.
Candle Direction and RSI Trend:
The code determines the trend direction of the last candle based on whether it closed higher or lower than its open price. It also calculates the RSI (Relative Strength Index) and determines its trend direction (overbought, oversold, or neutral) based on predefined thresholds.
s3.tradingview.com
Table Display:
The code creates a table displaying trend directions for different timeframes (monthly, weekly, daily, 4-hour, and 1-hour) for candle direction and RSI trends. The trends are labeled with "L" for long, "S" for short, and "N/A" for not applicable.
High Volume Bars (HVB):
The code identifies and colors bars with above-average volume as either bullish or bearish based on whether the price closed higher or lower than it opened. The color and conditions for high volume bars can be customized.
s3.tradingview.com
Doji Candle Pattern:
The code identifies and marks doji candle patterns, where the open and close prices are very close to each other within a certain percentage of the candle's high-low range.
RSI-Based Candle Coloring:
The code adjusts the color of the candles based on the RSI value. If the RSI value is above the overbought threshold or below the oversold threshold, the candles are colored yellow.
Usage and Interpretation:
Traders can use this indicator to identify potential trend changes based on EMA crossovers and candle patterns like engulfing and doji.
The RSI trend direction can provide additional insight into potential overbought or oversold conditions.
High volume bars can indicate potential price reversals or continuation patterns.
The table provides an overview of trend directions on different timeframes for both candle direction and RSI trends.
Keep in mind that this is a complex indicator with multiple features. Users should carefully evaluate its performance and consider combining it with other indicators and analysis methods for more accurate trading decisions.
The table is designed to provide a consolidated view of trend directions and other indicators across multiple timeframes. It is displayed on the chart and organized into rows and columns. Each row corresponds to a specific aspect of analysis, and each column corresponds to a different timeframe.
Here's a breakdown of the components of the table:
Row 1: Separation.
Row 2 (Header Row): This row contains the headers for the columns. The headers represent the different timeframes being analyzed, such as Monthly (M), Weekly (W), Daily (D), 4-hour (4h), and 1-hour (1h).
Row 3 (Content Row): This row contains labels indicating the types of information being displayed in the columns. The labels include "T" for Trend, "C" for Current Candle, and "R" for RSI Trend.
Row 4 and Onwards: These rows display the actual data for each aspect of analysis across different timeframes.
For each aspect of analysis (Trend, Current Candle, RSI Trend), the corresponding rows display the following information:
Monthly (M): The trend direction for the given aspect on the monthly timeframe.
Weekly (W): The trend direction for the given aspect on the weekly timeframe.
Daily (D): The trend direction for the given aspect on the daily timeframe.
4-hour (4h): The trend direction for the given aspect on the 4-hour timeframe.
1-hour (1h): The trend direction for the given aspect on the 1-hour timeframe.
The trend directions are represented by labels such as "L" for Long, "S" for Short, or "N/A" for Not Applicable.
The table's purpose is to provide a quick overview of trend directions and related information across multiple timeframes, aiding traders in making informed decisions based on the analysis of trend changes and other indicators.
ProfitAlgoOverview
ProfitAlgo is a powerful and intuitive trading tool specifically developed to cater to the requirements of both beginners and experienced traders. It is designed to function in every timeframe and on all cryptocurrencies, stocks, indices, forex, futures, currencies, ETF's, energy and commodities. This innovative tool provides real-time signals, comprehensive trend analysis, and advanced risk management features, making it an indispensable asset for traders of all levels. This cutting-edge tool generates 'BUY' and 'SELL' signals, complemented by an array of robust analytical tools. Empower your trading analysis with this all-in-one solution and add to your arsenal of indicators to make well-informed decisions.
This algorithm incorporates a sophisticated Fourier smoothing technique to effectively filter price data, reduce noise and reveal underlying patterns and trends. By utilizing multiple price series data and incorporating Price Volume Trend, it leverages volume analysis and price movement patterns. Furthermore, the algorithm employs relative and simple moving average calculations to enhance signal clarity and filter out outliers, resulting in a more refined and robust indicator.
Features
Buy/Sell signals: Visually illustrated by 'BUY' and 'SELL' labels, these signals provide indications to traders about optimal times to enter or exit positions in the market based on the particular asset they are trading. Traders may want to enter long positions when buy signals appear, and enter short positions when 'SELL' signals appear.
Stop Loss/Take Profit Levels: Stop loss and take profit levels are predefined price thresholds that allow traders to automatically exit trades to limit losses or secure profits, respectively. Stop loss and take profit levels are visually depicted through three dotted lines on the trading chart, including the entry price, take profit (TP), and stop loss (SL). Additionally, a table displays the corresponding price entries for all three levels, providing a comprehensive overview of the trade. Traders can effectively manage their risk and optimize their trading by implementing predefined threshold settings and establishing take profit levels, thus safeguarding their profits using a strategic approach.
Support and Resistance Levels: Support and resistance levels are key price levels in the market that act as barriers or turning points for the price movement of an asset. Traders utilize these levels to identify potential areas of buying and selling opportunities. These can be depicted as red (resistance) and green (support) horizontal lines. These levels can serve as valuable complements to stop/loss and take profit levels, providing confirmation for profit-taking opportunities and facilitating effective risk management. Moreover, they can synergistically work alongside the price lines to identify potential reversal zones by visualizing market highs/lows in conjunction with areas of supply & demand.
Moving Average Bands: Moving average bands, plotted alongside the price data, dynamically change color based on the prevailing trend, with red indicating a downtrend and green representing an uptrend. This visual tool provides valuable insights to users, allowing them to quickly identify and interpret market trends. Integrating Moving Average bands with our buy/sell signals offers added confidence in identifying market trends, enabling traders to seek validation and enhance their decision-making process.
Trend Table: The trend table provides real-time information on the current trend of an asset, displaying three distinct outputs: "Uptrend," "Downtrend," and "Ranging Trend." This valuable tool enables users to assess the live trend of an asset, which may differ from the buy/sell signals. The primary objective of this feature is to analyze real-time trends in both ranging and trending market conditions. While the current signal may indicate a 'BUY' signal, the table can present an alternative output, providing valuable insights for traders and investors.
Price Lines: Price lines are depicted as two parallel grey lines running alongside the price data, representing the highs and lows of the market. This visual tool is utilized to identify patterns of higher highs and lower lows, enabling traders to gain insights into the overall trend and potential reversals in the market. When used in conjunction with our signals, MA bands and trend table, it may reinforce your interpretation of the underlying trend as well as provide insights into the trend strength.
*Note: These features are customizable via the settings menu in TradingView.
Calculations
How are buy/sell signals calculated?
The buy and sell signals are generated through a comprehensive calculation process that encompasses various types of analysis techniques. With permission from the author, wbburgin's Fourier transform is utilized to filter and extract relevant information from the price data, removing noise from the signals (filter is only applied in this feature). The buy and sell conditions are calculated based on a combination of volume-based analysis, and price movement patterns, employed to assess the direction and strength of market trends. The combination aims to produce a comprehensive view of both volume-based and price-based market dynamics. By integrating these analysis techniques, traders can gain insights into the relationship between volume, price, and market trends. This combined approach, as well as Fourier smoothing, can help identify potential market reversals, confirm trend strength, produce less noisy data and provide additional confirmation signals for trading decisions. By considering the insights provided by this analysis, the algorithm determines the appropriate actions, signaling the opportunities to enter or exit positions in the market. In summary, these calculations aim to identify favorable trading opportunities by considering factors such as trend strength, volume dynamics, and price patterns, ultimately assisting traders in making well-informed decisions in the market.
How are stop/loss and take/profit levels calculated?
The stop loss and take profit levels are calculated using a combination of technical factors, including the Average True Range (ATR) and Exponential Moving Average (EMA). The rationale for this combination is to enable dynamic risk management and align profit targets with the prevailing market conditions; ATR provides a measure of volatility and risk, while EMA helps identify the underlying trend, allowing for effective stop-loss and take-profit placement. These indicators are utilized to gauge market volatility and determine suitable levels for managing risk and securing potential profits. By incorporating ATR and EMA calculations, the algorithm generates dynamic stop loss and take profit levels that adapt to market conditions.
Calculating support and resistance levels
These levels help identify areas where the price tends to find support (support levels) or encounter resistance (resistance levels). This script utilizes pivot point calculations to determine these significant price levels, which can assist traders in trading decisions regarding potential price reversals, trend continuations, and entry/exit points in their strategies.
What are the moving average bands based on?
The moving average bands, based on VWMA (Volume Weighted Moving Average) calculations using OHLC4 price data, are visualized as unique bands on the chart. VWMA bands are chosen to find trends because they effectively combine volume-weighted calculations with moving averages, providing valuable insights into the strength and direction of price movements. These bands dynamically change color to reflect the prevailing trend. In an uptrend, the bands are represented by a green color, while in a downtrend, they appear in red. The VWMA bands utilize a unique counting method to capture trend movements and potential reversals.
How is the Trend Table calculated?
The underlying trends in the trend table are calculated based on counting methods applied to the VWMA bands. It utilizes specific thresholds to determine different trends, such as "Up Trend," "Down Trend," and "Ranging Trend." These thresholds are used to assess the current trend of the asset and provide valuable insights for traders.
Price Lines Calculation
The price lines are calculated based on the price data. They represent the range of prices, with one line plotted above the closing price and another line plotted below it. The space between these lines is filled to visualize the price volatility. Traders can utilize these lines to identify significant price levels and observe the overall price movement.
Disclaimer:
The information provided in my indicators/strategies/systems is not intended as financial advice. I assume no responsibility for any losses or damages, including loss of profits, resulting from the use of or reliance on such information.
All investments carry risks, and past performance of a security, industry, sector, market, financial product, trading strategy, backtest, or individual's trading does not guarantee future results or returns. Investors bear full responsibility for their investment decisions, which should be based on their own evaluation of financial circumstances, investment objectives, risk tolerance, and liquidity requirements.
Please note that my indicators/strategies/systems are solely for educational purposes! DO NOT request access in the comment's section.
Trend Following with Dynamic Price ZonesThis script provides a complete framework for following trends , especially on those assets which are sufficiently liquid and don't go through random spikes.
Since it is a trend-following system, it works well during trends only. However, I cannot claim any numbers since the execution requires some discretion at the user's end. This framework can also be combined with other technical tools such as trend lines to increase its efficacy.
Features:
Dynamic Price Zones:
• The Dynamic Price Zones (DPZ) are determined using a proprietary logic that incorporates price movement and certain other factors.
• These zones change more rapidly than conventional support and resistance (S/R) zones, which is why I have named them "Dynamic".
• DPZs can serve as support and resistance zones and help with trend identification to some extent.
• The upper boundary of a zone is called Dynamic Price Zone High (DPZ-H) , while the lower boundary is called Dynamic Price Zone Low (DPZ-L) .
Colour Bars:
• Candle colours are based on another proprietary logic, independent of dynamic price zones .
• These are not traditional moving average-based coloured bars, which is evident from the presence of uncoloured bars in between.
• The uncoloured bars indicate periods of uncertain trends .
• Colour functionality helps in smoothening the trend and assists in riding it for as long as possible.
Stats Table:
• RSI
• VWAP
• % Change from the previous day's closing
• Dynamic Price Zone High (DPZ-H) value
• Dynamic Price Zone Low (DPZ-L) value
Settings:
• DPZs are displayed as horizontal lines with background fill by default, but users can toggle lines and background fill on or off.
• Bar colours can be customized according to user preferences.
• The table can be enabled or disabled based on user input.
• The position of the table can be changed based on 4 available options: Top Left, Top Right, Bottom Left, and Bottom Right.
• Users can toggle individual table fields on or off . For example: If the user wants to hide "Vwap" and "%Change" values, he can turn them off. In that case, only 3 fields will be displayed on the table without occupying additional space.
• Background and text colours for each field of the table can be customized based on user preferences.
How to Use the Dynamic Price Zones:
• When the price is above a DPZ, it indicates a bullish trend , suggesting the possibility of higher prices. These zones are termed Bullish DPZs.
• Conversely, if the price is below a DPZ, it signals a bearish trend , with an expectation of lower prices. These zones are termed Bearish DPZs.
• In a trending market, when the price returns to a previous DPZ, it can present a trading opportunity in the direction of the prior trend (e.g., if the market is falling and the price returns to a previous DPZ, it is likely to reject it).
• Consecutive ascending DPZs indicate a shift in buyers from lower to higher levels and can provide buying opportunities. This also indicates a period of a strong bullish trend.
• Similarly, consecutive descending DPZs indicate a shift in sellers from higher to lower levels and can provide selling opportunities. This also indicates a period of a strong bearish trend.
• Please note that we must be flexible when determining the consecutive zones. For example: There may be a few smaller bearish DPZs in between the bullish DPZs but if the area is dominated by the bullish DPZs then we can consider the zones as consecutive. Similar is true for bearish consecutive zones.
• Closely stacked or adjacent zones suggest that prices will likely remain within a range, moving sideways.
• Wider zones act as big hurdles and, the price may struggle to cross them. They may also lead to a sideways movement.
• Zones that remain clean and untested for several sessions are likely to act as strong support or resistance when the price revisits them.
Bullish Examples:
Bearish Examples:
Some Examples of the Complete System
Trend follower system combined with Trendlines
Special Thanks
I would like to extend my special thanks to all the experts whose lectures and blogs I have studied to gain a limited yet significant knowledge of the Pine language.
Best regards,
Rajat Kumar Singh (@johntradingwick)
Community Manager (India), TradingView.
Market Structure & Liquidity: CHoCHs+Nested Pivots+FVGs+Sweeps//Purpose:
This indicator combines several tools to help traders track and interpret price action/market structure; It can be divided into 4 parts;
1. CHoCHs, 2. Nested Pivot highs & lows, 3. Grade sweeps, 4. FVGs.
This gives the trader a toolkit for determining market structure and shifts in market structure to help determine a bull or bear bias, whether it be short-term, med-term or long-term.
This indicator also helps traders in determining liquidity targets: wether they be voids/gaps (FVGS) or old highs/lows+ typical sweep distances.
Finally, the incorporation of HTF CHoCH levels printing on your LTF chart helps keep the bigger picture in mind and tells traders at a glance if they're above of below Custom HTF CHoCH up or CHoCH down (these HTF CHoCHs can be anything from Hourly up to Monthly).
//Nomenclature:
CHoCH = Change of Character
STH/STL = short-term high or low
MTH/MTL = medium-term high or low
LTH/LTL = long-term high or low
FVG = Fair value gap
CE = consequent encroachement (the midline of a FVG)
~~~ The Four components of this indicator ~~~
1. CHoCHs:
•Best demonstrated in the below charts. This was a method taught to me by @Icecold_crypto. Once a 3 bar fractal pivot gets broken, we count backwards the consecutive higher lows or lower highs, then identify the CHoCH as the opposite end of the candle which ended the consecutive backwards count. This CHoCH (UP or DOWN) then becomes a level to watch, if price passes through it in earnest a trader would consider shifting their bias as market structure is deemed to have shifted.
•HTF CHoCHs: Option to print Higher time frame chochs (default on) of user input HTF. This prints only the last UP choch and only the last DOWN choch from the input HTF. Solid line by default so as to distinguish from local/chart-time CHoCHs. Can be any Higher timeframe you like.
•Show on table: toggle on show table(above/below) option to show in table cells (top right): is price above the latest HTF UP choch, or is price below HTF DOWN choch (or is it sat between the two, in a state of 'uncertainty').
•Most recent CHoCHs which have not been met by price will extend 10 bars into the future.
• USER INPUTS: overall setting: SHOW CHOCHS | Set bars lookback number to limit historical Chochs. Set Live CHoCHs number to control the number of active recent chochs unmet by price. Toggle shrink chochs once hit to declutter chart and minimize old chochs to their origin bars. Set Multi-timeframe color override : to make Color choices auto-set to your preference color for each of 1m, 5m, 15m, H, 4H, D, W, M (where up and down are same color, but 'up' icon for up chochs and down icon for down chochs remain printing as normal)
2. Nested Pivot Highs & Lows; aka 'Pivot Highs & Lows (ST/MT/LT)'
•Based on a seperate, longer lookback/lookforward pivot calculation. Identifies Pivot highs and lows with a 'spikeyness' filter (filtering out weak/rounded/unimpressive Pivot highs/lows)
•by 'nested' I mean that the pivot highs are graded based on whether a pivot high sits between two lower pivot highs or vice versa.
--for example: STH = normal pivot. MTH is pivot high with a lower STH on either side. LTH is a pivot high with a lower MTH on either side. Same applies to pivot lows (STL/MTL/LTL)
•This is a useful way to measure the significance of a high or low. Both in terms of how much it might be typically swept by (see later) and what it would imply for HTF bias were we to break through it in earnest (more than just a sweep).
• USER INPUTS: overall setting: show pivot highs & lows | Bars lookback (historical pivots to show) | Pivots: lookback/lookforward length (determines the scale of your pivot highs/lows) | toggle on/off Apply 'Spikeyness' filter (filters out smooth/unimpressive pivot highs/lows). Set Spikeyness index (determines the strength of this filter if turned on) | Individually toggle on each of STH, MTH, LTH, STL, MTL, LTL along with their label text type , and size . Toggle on/off line for each of these Pivot highs/lows. | Set label spacer (atr multiples above / below) | set line style and line width
3. Grade Sweeps:
•These are directly related to the nested pivots described above. Most assets will have a typical sweep distance. I've added some of my expected sweeps for various assets in the indicator tooltips.
--i.e. Eur/Usd 10-20-30 pips is a typical 'grade' sweep. S&P HKEX:5 - HKEX:10 is a typical grade sweep.
•Each of the ST/MT/LT pivot highs and lows have optional user defined grade sweep boxes which paint above until filled (or user option for historical filled boxes to remain).
•Numbers entered into sweep input boxes are auto converted into appropriate units (i.e. pips for FX, $ or 'handles' for indices, $ for Crypto. Very low $ units can be input for low unit value crypto altcoins.
• USER INPUTS: overall setting: Show sweep boxes | individually select colors of each of STH, MTH, LTH, STL, MTL, LTL sweep boxes. | Set Grade sweep ($/pips) number for each of ST, MT, LT. This auto converts between pips and $ (i.e. FX vs Indices/Crypto). Can be a float as small or large as you like ($0.000001 to HKEX:1000 ). | Set box text position (horizontal & vertical) and size , and color . | Set Box width (bars) (for non extended/ non-auto-terminating at price boxes). | toggle on/off Extend boxes/lines right . | Toggle on/off Shrink Grade sweeps on fill (they will disappear in realtime when filled/passed through)
4. FVGs:
•Fair Value gaps. Represent 'naked' candle bodies where the wicks to either side do not meet, forming a 'gap' of sorts which has a tendency to fill, or at least to fill to midline (CE).
•These are ICT concepts. 'UP' FVGS are known as BISIs (Buyside imbalance, sellside inefficiency); 'DOWN' FVGs are known as SIBIs (Sellside imbalance, buyside inefficiency).
• USER INPUTS: overall setting: show FVGs | Bars lookback (history). | Choose to display: 'UP' FVGs (BISI) and/or 'DOWN FVGs (SIBI) . Choose to display the midline: CE , the color and the line style . Choose threshold: use CE (as opposed to Full Fill) |toggle on/off Shrink FVG on fill (CE hit or Full fill) (declutter chart/see backtesting history)
////••Alerts (general notes & cautionary notes)::
•Alerts are optional for most of the levels printed by this indicator. Set them via the three dots on indicator status line.
•Due to dynamic repainting of levels, alerts should be used with caution. Best use these alerts either for Higher time frame levels, or when closely monitoring price.
--E.g. You may set an alert for down-fill of the latest FVG below; but price will keep marching up; form a newer/higher FVG, and the alert will trigger on THAT FVG being down-filled (not the original)
•Available Alerts:
-FVG(BISI) cross above threshold(CE or full-fill; user choice). Same with FVG(SIBI).
-HTF last CHoCH down, cross below | HTF last CHoCH up, cross above.
-last CHoCH down, cross below | last CHoCH up, cross above.
-LTH cross above, MTH cross above, STH cross above | LTL cross below, MTL cross below, STL cross below.
////••Formatting (general)::
•all table text color is set from the 'Pivot highs & Lows (ST, MT, LT)' section (for those of you who prefer black backgrounds).
•User choice of Line-style, line color, line width. Same with Boxes. Icon choice for chochs. Char or label text choices for ST/MT/LT pivot highs & lows.
////••User Inputs (general):
•Each of the 4 components of this indicator can be easily toggled on/off independently.
•Quite a lot of options and toggle boxes, as described in full above. Please take your time and read through all the tooltips (hover over '!' icon) to get an idea of formatting options.
•Several Lookback periods defined in bars to control how much history is shown for each of the 4 components of this indicator.
•'Shrink on fill' settings on FVGs and CHoCHs: Basically a way to declutter chart; toggle on/off depending on if you're backtesting or reading live price action.
•Table Display: applies to ST/MT/LT pivot highs and to HTF CHoCHs; Toggle table on or off (in part or in full)
////••Credits:
•Credit to ICT (Inner Circle Trader) for some of the concepts used in this indicator (FVGS & CEs; Grade sweeps).
•Credit to @Icecold_crypto for the specific and novel concept of identifying CHoCHs in a simple, objective and effective manner (as demonstrated in the 1st chart below).
CHoCH demo page 1: shifting tweak; arrow diagrams to demonstrate how CHoCHs are defined:
CHoCH demo page 2: Simplified view; short lookback history; few CHoCHs, demo of 'latest' choch being extended into the future by 10 bars:
USAGE: Bitcoin Hourly using HTF daily CHoCHs:
USAGE-2: Cotton Futures (CT1!) 2hr. Painting a rather bullish picture. Above HTF UP CHoCH, Local CHoCHs show bullish order flow, Nice targets above (MTH/LTH + grade sweeps):
Full Demo; 5min chart; CHoCHs, Short term pivot highs/lows, grade sweeps, FVGs:
Full Demo, Eur/Usd 15m: STH, MTH, LTH grade sweeps, CHoCHs, Usage for finding bias (part A):
Full Demo, Eur/Usd 15m: STH, MTH, LTH grade sweeps, CHoCHs, Usage for finding bias, 3hrs later (part B):
Realtime Vs Backtesting(A): btc/usd 15m; FVGs and CHoCHs: shrink on fill, once filled they repaint discreetly on their origin bar only. Realtime (Shrink on fill, declutter chart):
Realtime Vs Backtesting(B): btc/usd 15m; FVGs and CHoCHs: DON'T shrink on fill; they extend to the point where price crosses them, and fix/paint there. Backtesting (seeing historical behaviour):
Nasdaq 100 ScreenerNasdaq 100 screener is comprehensive table displaying the following parameters :
Op = Open Price of the Day.
LaP = Last Price.
O-L = Open Price of the Day - Last Price.
ROC = Rate of Change .
SMA20 = Simple Moving Average 20 period.
S20d = Last Price - SMA 20.
SMA50 = Simple Moving Average 50 period.
S50d = Last Price - SMA 50.
SMA200 = Simple Moving Average 200 period.
S200d = Last Price - SMA 200.
ADX(14) = Average Directional Index.
RSI(14) = Relative Strength Index.
CCI(20) = Commodity Channel Index.
ATR(14) = Average True Range.
MOM(10) = Momentum.
AcDis(K) = Accumulation/Distribution.
CMF(20) = Chaikin Money Flow.
MACD = Moving Average Convergence Divergence.
Sig = MACD signal.
Nasdaq 100 stocks are divided into following alphabetical grouping for input access purpose under “Options” in “Settings” menu.
A to B 21 stocks “Input symbols” are listed under the “Options” in “Input A to B”
C to E 18 stocks “Input symbols” are listed under the head “Options” in “Input C to E”
F to L 19 stocks “Input symbols” are listed under the head “Options” in “Input F to L”
M to P 22 stocks “Input symbols” are listed under the head “Options” in “Input M to P”
R to Z 20 stocks “Input symbols” are listed under the head “Options” in “Input R to Z”
A to Z 100 stocks “Input symbols” are listed under the head “Options” in “Input A to Z”
User after visiting the “Settings” menu simply is required to select the “input symbol” from the stock listed under respective alphabetical Input lists to which the particular stock belongs. The resultant data is tabulated under respective row in Table .At a time User can see 5 different stocks i.e one each in different alphabetical lists in respective alphabetical order rows stated in the Table. User can scroll in each list to access and shift to any other stock in the list. In addition a Master list of all 100 stocks is given under “ Input A to Z “ at the last row of table.
Nasdaq 100 screener is a simple table , which facilitate to view 6 different stocks at a time (inclusive one from Master list of “Input A to Z” with a display of 19 parameters.
ICT AI ATR Signals [TradingFinder]🔵 Introduction
In financial markets, two main factors always have the greatest impact on traders’ decisions: the direction of the trend and the level of price volatility. Although there are various tools to analyze each of these factors, very few indicators can combine them in a coordinated and simultaneous way.
The ICT AI ATR indicator has been designed with this purpose in mind, to provide a unified and comprehensive view of the market instead of relying on multiple scattered indicators.
This indicator is built upon two widely used tools: the Moving Average (MA) and the Average True Range (ATR). The combination of these two indicators allows traders to simultaneously track the trend direction and account for market volatility two elements that always play a decisive role in trading decisions.
In the structure of the indicator, the Moving Average acts as the central line and serves as the backbone of the tool. By calculating the average price over a defined period, the Moving Average filters out excess market noise and provides a clearer picture of the overall price movement.
This helps traders focus on the main trend instead of being distracted by minor and temporary fluctuations. The central line is thus the main reference point for identifying the trend direction.
Alongside this, the ATR is responsible for measuring the real volatility of the market. Unlike many tools that only look at closing price changes, the ATR considers the true range of candlestick movements, giving a more accurate view of market dynamics.
In the ICT AI ATR indicator, this feature is used to draw dynamic bands above and below the Moving Average line. These bands shift with changing market conditions and act like dynamic support and resistance levels, areas where strong price reactions often occur.
This combination allows traders not only to see the dominant market trend through the Moving Average but also to understand volatility and the natural price range via the ATR. For this reason, the ICT AI ATR identifies points that are likely to act as reaction or reversal zones, whether during bounces off the bands or breakouts through them.
With this structure, the trader can at a glance :
Identify the overall market direction using the Moving Average.
Observe volatility and the natural range of price movement through ATR.
Recognize key levels where strong reactions or potential reversals are more likely.
As a result, the ICT AI ATR functions as a combined tool that replaces the need to use several separate indicators, enabling traders to analyze trend, volatility, price bands, and even Fibonacci targets within a single unified framework.
🔵 How to Use
The ICT AI ATR indicator is designed to simplify market analysis through two main components: visual display of bands and signals on the chart itself, and a multi-symbol analytical dashboard capable of monitoring over 20 different assets simultaneously across multiple timeframes.
This dashboard feature allows traders to gain a quick overview of overall market conditions without opening multiple charts or constantly switching timeframes. It updates in real-time, showing active Buy (Long) and Sell signals for each symbol.
As such, the combination of direct chart display and dashboard analytics makes the indicator useful both for detailed analysis of a single symbol and for monitoring multiple markets at once.
🟣 How do ICT AI ATR trading signals work?
Sell Signal (Short) : Triggered when the price pushes below the lower band (Low goes outside the lower band) and then closes back above it. This indicates potential weakness in bullish momentum and suggests possible selling pressure or the start of a downward correction. Traders can use this to spot sell setups or manage long positions.
Buy Signal (Long) : Triggered when the price extends above the upper band (High goes outside the upper band) and then closes back below it. This often signals exhaustion in bearish pressure and the return of buying strength, potentially marking the start of a new upward move.
This signaling logic is based on the actual behavior of price relative to the ATR dynamic bands. Unlike static formulas, signals adapt to changing market conditions, making them more accurate and reliable.
The main advantage of the ICT AI ATR indicator is that traders can benefit from real-time analysis directly on the chart by observing price interactions with the bands and signals while also receiving a multi-market overview through the dashboard. This combination is especially valuable for traders who operate across multiple instruments or markets simultaneously.
🔵 Settings
🟣 Logical settings
Moving Average Type : Select the type of moving average for the central line. Options include EMA, SMA, RMA, WMA, or HMA depending on the trading strategy.
Moving Average Period : Defines the length of the moving average. Shorter periods make the central line more responsive to price changes, while longer periods smooth out the line to show the broader trend.
ATR Period : Determines the number of candles considered for volatility calculation. Shorter periods increase sensitivity, while longer periods provide a more stable view of volatility.
ATR Multiplier : Sets the distance between the upper/lower bands and the central moving average line. Higher values widen the bands, while lower values bring them closer to price.
Smooth Period: Used to smooth data and reduce chart noise. Higher values produce smoother, more consistent indicator lines.
Signal Gap : Defines the minimum number of candles required between two consecutive signals. This prevents back-to-back signals from appearing too frequently and ensures only the more reliable ones are shown.
🟣 Display Settings
Table on Chart : Allows users to choose the position of the signal dashboard either directly on the chart or below it, depending on their layout preference.
Number of Symbols : Enables users to control how many symbols are displayed in the screener table, from 10 to 20, adjustable in increments of 2 symbols for flexible screening depth.
Table Mode : This setting offers two layout styles for the signal table :
Basic : Mode displays symbols in a single column, using more vertical space.
Extended : Mode arranges symbols in pairs side-by-side, optimizing screen space with a more compact view.
Table Size : Lets you adjust the table’s visual size with options such as: auto, tiny, small, normal, large, huge.
Table Position : Sets the screen location of the table. Choose from 9 possible positions, combining vertical (top, middle, bottom) and horizontal (left, center, right) alignments.
🟣 Symbol Settings
Each of the 10 symbol slots comes with a full set of customizable parameters :
Symbol : Define or select the asset (e.g., XAUUSD, BTCUSD, EURUSD, etc.).
Timeframe : Set your desired timeframe for each symbol (e.g., 15, 60, 240, 1D).
🟣 Alert Settings
Alert : Enables alerts for AAS.
Message Frequency : Determines the frequency of alerts. Options include 'All' (every function call), 'Once Per Bar' (first call within the bar), and 'Once Per Bar Close' (final script execution of the real-time bar). Default is 'Once per Bar'.
Show Alert Time by Time Zone : Configures the time zone for alert messages. Default is 'UTC'.
🔵 Conclusion
The ICT AI ATR indicator, by combining three core elements Moving Average for trend detection, ATR for volatility measurement and dynamic bands, and Fibonacci levels for price targets—provides a multi-layered and intelligent tool for market analysis. In addition to showing accurate bands directly on the chart, it also offers a multi-symbol dashboard that allows traders to monitor signals across different assets and timeframes in real time.
The key advantage of this indicator is that it eliminates the need to use several separate tools by integrating trend, volatility, key levels, and trade signals into one unified framework. For this reason, ICT AI ATR is a reliable and effective choice for both short-term traders seeking quick market moves and long-term traders focused on dynamic support and resistance levels.
Trade Calculator {Phanchai}Trade Calculator 🧮 {Phanchai} — Documentation
A lightweight sizing helper for TradingView that turns your risk per trade into an estimated maximum nominal position size — using the most recent chart low as your stop reference. Built for speed and clarity right on the chart.
Key Features
Clean on-chart info table with configurable font size and position.
Row toggles: show/hide each line (Price, Last Low, Risk per Trade, Entry − Low, SL to Low %, Max. Nominal Value in USDT).
Configurable low reference: Last N bars or Running since load .
Low label placed exactly at the wick of the lowest bar (no horizontal line).
Custom padding: add extra rows above/below and blank columns left/right (with custom whitespace/text fillers) to fine-tune layout.
Integer display for Risk per Trade (USDT) and Max. Nominal Value (USDT); decimals configurable elsewhere.
Open source script — easy to read and extend.
How to Use
Add the indicator: open TradingView → Indicators → paste the source code → Add to chart.
Pick your low reference in settings:
Last N bars — uses the lowest low within your chosen lookback.
Running since load — tracks the lowest low since the script loaded.
Set your capital and risk:
Total Capital — your account size in USDT.
Max. invest Capital per Trade (%) — your risk per trade as a percent of Total Capital.
Tidy the table:
Use Table Position and Table Size to place it.
Add Extra rows/columns and set left/right fillers (spaces allowed) for padding.
Toggle individual rows (on/off) to show only what you need.
Read the numbers:
Act. Price in USDT — current close.
Last Low in USDT — stop reference price.
Risk per Trade — whole-USDT value of your risk budget for this trade.
Entry − Low — absolute risk per unit.
SL to Low (%) — percentage distance from price to low.
Max. Nominal Value in USDT — estimated max nominal position size given your risk budget and stop at the low.
Scope
This calculator is designed for long trades only (stop below price at the chart low).
Notes & Assumptions
Does not factor fees, funding, slippage, tick size, or broker/venue position limits.
“Running since load” updates as new lows appear; “Last N bars” uses only the selected lookback window.
If price equals the low (zero distance), sizing will be undefined (division by zero guarded as “—”).
Risk Warning
Trading involves substantial risk. Always double-check every value the calculator shows, confirm your stop distance, and verify position sizing with your broker/platform before entering any order. Never risk money you cannot afford to lose.
Open Source & Feedback
The source code is open. If you spot a bug or have an idea to improve the tool, feel free to share suggestions — I’m happy to iterate and make it better.
Weekly pecentage tracker by PRIVATE
Settings Picture below this link: 👇
i.ibb.co
What it is
A lightweight “Weekly % Tracker” overlay that lets you manually enter weekly performance (in percent) for XAUUSD + up to 10 FX pairs, then shows:
a small table panel with each enabled symbol and its % result
one TOTAL row (Sum / Average / Compounded across all enabled symbols)
an optional mini badge showing the % for a single selected symbol
Nothing is auto-calculated from price—you type the % yourself.
Key settings
Panel: show/hide, position, number of decimals, colors (background, text, green/red).
Total mode:
Sum – adds percentages
Average – mean of enabled rows
Compounded –
(
∏
(
1
+
𝑝
/
100
)
−
1
)
×
100
(∏(1+p/100)−1)×100
Symbols:
XAUUSD (toggle + label + % input)
10 FX pairs (each has On/Off, label text, % input). You can rename labels to any symbol text you want.
Mini badge: show/hide, position, and symbol to display.
How it works
Overlay indicator: overlay=true; just draws UI on the chart (no plots).
Arrays (syms, vals, ons) collect the row data in order: XAU first, then FX1…FX10.
Helpers:
posFrom() converts a position string (e.g., “Top Right”) into a position.* constant.
wp_col() picks green/red/neutral based on the sign of the %.
wp_round() rounds values to the selected decimals.
calc_total() computes the TOTAL with the chosen mode over enabled rows only.
Table creation logic:
Counts how many rows are enabled.
If none enabled or panel is off: the panel table is deleted, so no box/background is visible.
If enabled and on: the panel is (re)created at the chosen position.
On each last bar (barstate.islast), it clears the table to transparent (bgcolor=na) and then fills one row per enabled symbol, followed by a single TOTAL row.
Mini badge:
Always (re)created on position change.
Shows selected symbol’s % (or “-” if that symbol isn’t enabled or has no value).
Colors text green/red by sign.
Notes & limits
It’s manual input—the script doesn’t read trades or P/L from price.
You can rename each row’s label to match any symbol name you want.
When no rows are enabled, the panel disappears entirely (no empty background).
Designed to be light: only draws tables; no heavy plotting.
If you want the TOTAL row to be optional, or different color thresholds, or CSV-style export/import of the values, say the word and I’ll add it.
Advanced Swing Trading Suite(Mastersinnifty)🔹 Core Logic
The Advanced Swing Trading Suite is a complete framework for analyzing and trading market swings.
It combines:
A modified QQE momentum engine (adapted from the original QQE by © Peter_O under MPL 2.0).
RSI-based trend strength filter for validation.
Zigzag-driven swing structure detection (higher highs, higher lows, lower highs, lower lows).
Dynamic trade and risk management modules for practical execution.
By merging momentum, structure, and risk control, this tool goes beyond standalone indicators and provides a structured decision-support system for swing traders.
🔹 Uniqueness
While the QQE concept is freely available, this script builds an integrated swing trading ecosystem that adds multiple layers of functionality:
Swing structure analyzer that maps price action into HH, HL, LH, LL patterns in real time.
Dynamic percentage-based trade table that automatically logs entries, exits, P&L %, and timestamps.
Lot size calculator that converts account capital into position size per trade.
Swing extensions and retracement projections for planning targets.
Momentum confirmation via a tuned QQE + RSI engine.
This makes it not just an indicator, but a complete swing trading suite.
🔹 Key Features
✔ Modified QQE + RSI Momentum Filter → Early trend confirmation.
✔ Real-Time Swing Structure Labels (HH, HL, LH, LL) → Clear market context.
✔ Trade Performance Table → Tracks signals with percentage P&L and timing.
✔ Lot Size Calculator → Position sizing based on account capital.
✔ Dynamic Stops & Targets → Swing highs/lows as stops, extensions for projections.
✔ Alerts Ready → Configurable buy/sell alerts.
✔ Visual Labels → Background highlighting and trade markers.
🔹 How to Use
Entries: Green background = Long entry, Red background = Short entry.
Structure: HH/HL/LH/LL labels mark evolving swing structure.
Trade Table: Displays performance stats of past signals.
Risk Control: Use lot size calculator for instant position sizing.
Targets: Refer to swing extensions for profit zones.
Alerts: Set alerts for buy/sell triggers to receive notifications.
🔹 Disclaimer
This script integrates a modified version of QQE by © Peter_O (MPL 2.0 License).
Original QQE source: mozilla.org
All additional modules (swing analyzer, trade table, lot calculator, extensions) are original contributions by Mastersinnifty.
⚠️ Trading Disclaimer:
This script is for educational purposes only and does not constitute financial advice. Past performance is not indicative of future results. Always conduct your own research, test thoroughly, and trade with proper risk management.
Mikula's Master 360° Square of 12Mikula’s Master 360° Square of 12
An educational W. D. Gann study indicator for price and time. Anchor a compact Square of 12 table to a start point you choose. Begin from a bar’s High or Low (or set a manual start price). From that anchor you can progress or regress the table to study how price steps through cycles in either direction.
What you’re looking at :
Zodiac rail (far left): the twelve signs.
Degree rail: 24 rows in 15° steps from 15° up to 360°/0°.
Transit rail and Natal rail: track one planet per rail. Each planet is placed at its current row (℞ shown when retrograde). As longitude advances, the planet climbs bottom → top, then wraps to the bottom at the next sign; during retrograde it steps downward.
Hover a planet’s cell to see a tooltip with its exact longitude and sign (e.g., 152.4° ♌︎). The linked price cell in the grid moves with the planet’s row so you can follow a planet’s path through the zodiac as a path through price.
Price grid (right): the 12×24 Square of 12. Each column is a cycle; cells are stepped price levels from your start price using your increment.
Bottom rail: shows the current square number and labels the twelve columns in that square.
How the square is read
The square always begins at the bottom left. Read each column bottom → top. At the top, return to the bottom of the next column and read up again. One square contains twelve cycles. Because the anchor can be a High or a Low, you can progress the table upward from the anchor or regress it downward while keeping the same bottom-to-top reading order.
Iterate Square (shifting)
Iterate Square shifts the entire 12×24 grid to the next set of twelve cycles.
Square 1 shows cycles 1–12; Square 2 shows 13–24; Square 3 shows 25–36, etc.
Visibility rules
Pivot cells are table-bound. If you shift the square beyond those prices, their highlights won’t appear in the table.
A/B levels and Transit/Natal planetary lines are chart overlays and can remain visible on the table as you shift the square.
Quick use
Choose an anchor (date/time + High/Low) or enable a manual start price .
Set the increment. If you anchored with a Low and want the table to step downward from there, use a negative value.
Optional: pick Transit and Natal planets (one per rail), toggle their plots, and hover their cells for longitude/sign.
Optional: turn on A/B levels to display repeating bands from the start price.
Optional: enable swing pivots to tint matching cells after the anchor.
Use Iterate Square to shift to later squares of twelve cycles.
Examples
These are exploratory examples to spark ideas:
Overview layout (zodiac & degree rails, Transit/Natal rails, price grid)
A-levels plotted, pivots tinted on the table, real-time price highlighted
Drawing angles from the anchor using price & time read from the table
Using a TradingView Gann box along the A-levels to study reactions
Attribution & originality
This script is an original implementation (no external code copied). Conceptual credit to Patrick Mikula, whose discussion of the Master 360° Square of 12 inspired this study’s presentation.
Further reading (neutral pointers)
Patrick Mikula, Gann’s Scientific Methods Unveiled, Vol. 2, “W. D. Gann’s Use of the Circle Chart.”
W. D. Gann’s Original Commodity Course (as provided by WDGAN.com).
No affiliation implied.
License CC BY-NC-SA 4.0 (non-commercial; please attribute @Javonnii and link the original).
Dependency AstroLib by @BarefootJoey
Disclaimer Educational use only; not financial advice.
A best Seasonality Monthly IndicatorSeasonality Monthly is a custom indicator designed for TradingView that calculates and displays monthly seasonality performance as a table overlay on the chart.
Key aspects and functionality:
It requires the timeframe to be either monthly or daily; otherwise, it throws an error.
The user can set the starting year (default 2015) from which the seasonality statistics begin.
It collects monthly percentage change data (close to close returns) for each month and year dynamically using request.security.
Data is stored in a two-dimensional matrix representing years by months, accumulating returns for each month over the years.
The table is drawn on the chart showing monthly returns for each year, with cells colored green for positive returns and red for negatives.
The bottom rows of the table show summary statistics per month:
AVG: Average monthly returns
SUM: Sum of returns
+ive: Count of months with positive returns over total counts
WR: Win rate (ratio of positive months)
Text sizes and colors are customizable via inputs.
Uses Pine Script v5 features like matrix, table API, and new runtime error handling.
This script is useful for visualizing historical monthly seasonality patterns for any symbol on TradingView.
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The Seasonality Monthly Pine Script indicator is a powerful tool designed for TradingView that enables traders to analyze and visualize the historical seasonal performance of an asset on a monthly basis. This script focuses on identifying recurring monthly patterns by accumulating monthly percentage returns over multiple years, providing insights that help traders understand when certain months tend to perform better or worse historically.
The script requires the chart to be set to either a daily or monthly timeframe to ensure accurate calculations and data retrieval. It uses the request. security function to fetch monthly data, extracting each bar's year, month, and monthly price change percent based on close-to-close returns. These returns are then accumulated into a matrix data structure, organizing the percentage changes for each year and month to build a comprehensive historical dataset.
A dynamic table is constructed and displayed on the chart, showing a detailed breakdown of percentage changes each month for every year starting from a customizable start year (default is 2015). Each cell in the table is color-coded—green for positive monthly returns and red for negative—making it visually easy to interpret seasonal trends. This immediate visual feedback is valuable for traders looking to identify strong or weak months historically.
Beyond just the yearly data, the script calculates aggregate statistics for each month, which are displayed in summary rows at the bottom of the table. These include the average monthly return, the sum of returns, the count of positive-return months versus total months ("+ive"), and the win rate (WR), which is the proportion of positive months over the total number of months observed. These statistics assist traders in quantifying the strength and consistency of monthly seasonal effects.
The script also includes user customization options such as the starting year for seasonality analysis and adjustable text size for better readability. It incorporates modern Pine Script v5 features like runtime error handling, matrix operations, and the enhanced table API for efficient and clear display.
Overall, This is a practical indicator that helps traders incorporate seasonality insights into their decision-making process, potentially improving timing entries and exits by leveraging historical monthly market behaviors. It is particularly useful for spotting cyclic tendencies and planning strategies around historically strong or weak months, adding a valuable dimension to technical analysis.
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#Seasonality #TradingView #PineScript #TechnicalAnalysis #StockMarket #MonthlyPerformance #SeasonalTrends #MarketAnalysis #TradingStrategy #PricePatterns #Charting #DataVisualization #AlgorithmicTrading #FinancialMarkets #TradingIndicators #InvestmentStrategy #QuantitativeAnalysis #MarketSeasonality #StockTrading #TradingTools
BPS Multi-MA 5 — 22/30, SMA/WMA/EMA# Multi-MA 5 — 22/30 base, SMA/WMA/EMA
**What it is**
A lightweight 5-line moving-average ribbon for fast visual bias and trend/mean-reversion reads. You can switch the MA type (SMA/WMA/EMA) and choose between two ways of setting lengths: by monthly “session-based” base (22 or 30) with multipliers, or by entering exact lengths manually. An optional info table shows the effective settings in real time.
---
## How it works
* Calculates five moving averages from the selected price source.
* Lengths are either:
* **Multipliers mode:** `Base × Multiplier` (e.g., base 22 → 22/44/66/88/110), or
* **Manual mode:** any five exact lengths (e.g., 10/22/50/100/200).
* Plots five lines with fixed legend titles (MA1…MA5); the **info table** displays the actual type and lengths.
---
## Inputs
**Length Mode**
* **Multipliers** — choose a **Base** of **22** (≈ trading sessions per month) or **30** (calendar-style, smoother) and set **×1…×5** multipliers.
* **Manual** — enter **Len1…Len5** directly.
**MA Settings**
* **MA Type:** SMA / WMA / EMA
* **Source:** any series (e.g., `close`, `hlc3`, etc.)
* **Use true close (ignore Heikin Ashi):** when enabled, the MA is computed from the underlying instrument’s real `close`, not HA candles.
* **Show info table:** toggles the on-chart table with the current mode, type, base, and lengths.
---
## Quick start
1. Add the indicator to your chart.
2. Pick **MA Type** (e.g., **WMA** for faster response, **SMA** for smoother).
3. Choose **Length Mode**:
* **Multipliers:** set **Base = 22** for session-based monthly lengths (stocks/FX), or **30** for heavier smoothing.
* **Manual:** enter your exact lengths (e.g., 10/22/50/100/200).
4. (Optional) On **Heikin Ashi** charts, enable **Use true close** if you want the lines based on the instrument’s real close.
---
## Tips & notes
* **1 month ≈ 21–22 sessions.** Using 30 as “monthly” yields a smoother, more delayed curve.
* **WMA** reacts faster than **SMA** at the same length; expect earlier signals but more whipsaws in chop.
* **Len = 1** makes the MA track the chosen source (e.g., `close`) almost exactly.
* If changing lengths doesn’t move the lines, ensure you’re editing fields for the **active Length Mode** (Multipliers vs Manual).
* For clean comparisons, use the **same timeframe**. If you later wrap this in MTF logic, keep `lookahead_off` and handle gaps appropriately.
---
## Use cases
* Trend ribbon and dynamic bias zones
* Pullback entries to the mid/slow lines
* Crossovers (fast vs slow) for confirmation
* Volatility filtering by spreading lengths (e.g., 22/44/88/132/176)
---
**Credits:** Built for clarity and speed; designed around session-based “monthly” lengths (22) or smoother calendar-style (30).
[c3s] CWS - M2 Global Liquidity Index & BTC Correlation CWS - M2 Global Liquidity Index with Offset BTC Correlation
This custom indicator visualizes and analyzes the relationship between the global M2 money supply and Bitcoin (BTC) price movements. It calculates the correlation between these two variables to provide insights into how changes in global liquidity may impact Bitcoin’s price over time.
Key Features:
Global M2 Liquidity Index Calculation:
Fetches M2 money supply data from multiple economies (China, US, EU, Japan, UK) and normalizes using currency exchange rates (e.g., CNY/USD, EUR/USD).
Combines all M2 data points and normalizes by dividing by 1 trillion (1e12) for easier visualization.
Offset for M2 Data:
The offset parameter allows users to shift the M2 data by a specified number of days, helping track the influence of past global liquidity on Bitcoin.
BTC Price Correlation:
Computes the correlation between shifted global M2 liquidity and Bitcoin (BTC) price, using a 52-day lookback period by default.
Correlation Quality Display:
Categorizes correlation quality as:
Excellent : Correlation >= 0.8
Good : Correlation >= 0.6 and < 0.8
Weak : Correlation >= 0.4 and < 0.6
Very Weak : Correlation < 0.4
Displays correlation quality as a label on the chart for easy assessment.
Visual Enhancements:
Labels : Displays dynamic labels on the chart with metrics like M2 value and correlation.
Plot Shapes : Uses shapes to indicate data availability for global M2 and correlation.
Data Table : Optionally shows a data table in the top-right corner summarizing:
Global M2 value (in trillions)
The correlation between global M2 and BTC
The correlation quality
Optional Debugging:
Debug plots help identify when data is missing for M2 or correlation, ensuring transparency and accurate functionality.
Inputs:
Offset: Shift the M2 data (in days) to see past liquidity effects on Bitcoin.
Lookback Period: Number of periods (default 52) used to calculate the correlation.
Show Labels: Toggle to show or hide labels for M2 and correlation values.
Show Table: Toggle to show or hide the data table in the top-right corner.
Usage:
Ideal for traders and analysts seeking to understand the relationship between global liquidity and Bitcoin price. The offset and lookback period can be adjusted to explore different timeframes and correlation strengths, aiding more informed trading decisions.
Correlation Heatmap Matrix [TradingFinder] 20 Assets Variable🔵 Introduction
Correlation is one of the most important statistical and analytical metrics in financial markets, data mining, and data science. It measures the strength and direction of the relationship between two variables.
The correlation coefficient always ranges between +1 and -1 : a perfect positive correlation (+1) means that two assets or currency pairs move together in the same direction and at a constant ratio, a correlation of zero (0) indicates no clear linear relationship, and a perfect negative correlation (-1) means they move in exactly opposite directions.
While the Pearson Correlation Coefficient is the most common method for calculation, other statistical methods like Spearman and Kendall are also used depending on the context.
In financial market analysis, correlation is a key tool for Forex, the Stock Market, and the Cryptocurrency Market because it allows traders to assess the price relationship between currency pairs, stocks, or coins. For example, in Forex, EUR/USD and GBP/USD often have a high positive correlation; in stocks, companies from the same sector such as Apple and Microsoft tend to move similarly; and in crypto, most altcoins show a strong positive correlation with Bitcoin.
Using a Correlation Heatmap in these markets visually displays the strength and direction of these relationships, helping traders make more accurate decisions for risk management and strategy optimization.
🟣 Correlation in Financial Markets
In finance, correlation refers to measuring how closely two assets move together over time. These assets can be stocks, currency pairs, commodities, indices, or cryptocurrencies. The main goal of correlation analysis in trading is to understand these movement patterns and use them for risk management, trend forecasting, and developing trading strategies.
🟣 Correlation Heatmap
A correlation heatmap is a visual tool that presents the correlation between multiple assets in a color-coded table. Each cell shows the correlation coefficient between two assets, with colors indicating its strength and direction. Warm colors (such as red or orange) represent strong negative correlation, cool colors (such as blue or cyan) represent strong positive correlation, and mid-range tones (such as yellow or green) indicate correlations that are close to neutral.
🟣 Practical Applications in Markets
Forex : Identify currency pairs that move together or in opposite directions, avoid overexposure to similar trades, and spot unusual divergences.
Crypto : Examine the dependency of altcoins on Bitcoin and find independent movers for portfolio diversification.
Stocks : Detect relationships between stocks in the same industry or find outliers that move differently from their sector.
🟣 Key Uses of Correlation in Trading
Risk management and diversification: Select assets with low or negative correlation to reduce portfolio volatility.
Avoiding overexposure: Prevent opening multiple positions on highly correlated assets.
Pairs trading: Exploit temporary deviations between historically correlated assets for arbitrage opportunities.
Intermarket analysis: Study the relationships between different markets like stocks, currencies, commodities, and bonds.
Divergence detection: Spot when two typically correlated assets move apart as a possible trend change signal.
Market forecasting: Use correlated asset movements to anticipate others’ behavior.
Event reaction analysis: Evaluate how groups of assets respond to economic or political events.
❗ Important Note
It’s important to note that correlation does not imply causation — it only reflects co-movement between assets. Correlation is also dynamic and can change over time, which is why analyzing it across multiple timeframes provides a more accurate picture. Combining correlation heatmaps with other analytical tools can significantly improve the precision of trading decisions.
🔵 How to Use
The Correlation Heatmap Matrix indicator is designed to analyze and manage the relationships between multiple assets at once. After adding the tool to your chart, start by selecting the assets you want to compare (up to 20).
Then, choose the Correlation Period that fits your trading strategy. Shorter periods (e.g., 20 bars) are more sensitive to recent price movements, making them suitable for short-term trading, while longer periods (e.g., 100 or 200 bars) provide a broader view of correlation trends over time.
The indicator outputs a color-coded matrix where each cell represents the correlation between two assets. Warm colors like red and orange signal strong negative correlation, while cool colors like blue and cyan indicate strong positive correlation. Mid-range tones such as yellow or green suggest correlations that are close to neutral. This visual representation makes it easy to spot market patterns at a glance.
One of the most valuable uses of this tool is in portfolio risk management. Portfolios with highly correlated assets are more vulnerable to market swings. By using the heatmap, traders can find assets with low or negative correlation to reduce overall risk.
Another key benefit is preventing overexposure. For example, if EUR/USD and GBP/USD have a high positive correlation, opening trades on both is almost like doubling the position size on one asset, increasing risk unnecessarily. The heatmap makes such relationships clear, helping you avoid them.
The indicator is also useful for pairs trading, where a trader identifies assets that are usually correlated but have temporarily diverged — a potential arbitrage or mean-reversion opportunity.
Additionally, the tool supports intermarket analysis, allowing traders to see how movements in one market (e.g., crude oil) may impact others (e.g., the Canadian dollar). Divergence detection is another advantage: if two typically aligned assets suddenly move in opposite directions, it could signal a major trend shift or a news-driven move.
Overall, the Correlation Heatmap Matrix is not just an analytical indicator but also a fast, visual alert system for monitoring multiple markets at once. This is particularly valuable for traders in fast-moving environments like Forex and crypto.
🔵 Settings
🟣 Logic
Correlation Period : Number of bars used to calculate correlation between assets.
🟣 Display
Table on Chart : Enable/disable displaying the heatmap directly on the chart.
Table Size : Choose the table size (from very small to very large).
Table Position : Set the table location on the chart (top, middle, or bottom in various alignments).
🟣 Symbol Custom
Select Market : Choose the market type (Forex, Stocks, Crypto, or Custom).
Symbol 1 to Symbol 20: In custom mode, you can define up to 20 assets for correlation calculation.
🔵 Conclusion
The Correlation Heatmap Matrix is a powerful tool for analyzing correlations across multiple assets in Forex, crypto, and stock markets. By displaying a color-coded table, it visually conveys both the strength and direction of correlations — warm colors for strong negative correlation, cool colors for strong positive correlation, and mid-range tones such as yellow or green for near-zero or neutral correlation.
This helps traders select assets with low or negative correlation for diversification, avoid overexposure to similar trades, identify arbitrage and pairs trading opportunities, and detect unusual divergences between typically aligned assets. With support for custom mode and up to 20 symbols, it offers high flexibility for different trading strategies, making it a valuable complement to technical analysis and risk management.
Strong Indicator for ISM Services PMI XAUUSD (mtbr)Description:
This indicator is designed to help traders visualize entry levels, targets (TP1, TP2, TP3), and stop loss around the ISM Services PMI economic event for the XAUUSD asset. It provides a clear reference for potential market movements based on the event’s surprise and market direction (Bullish or Bearish).
Key Features:
Customizable event date and time:
You can set the exact year, month, day, hour, and minute of the event so that the lines and labels appear precisely on the corresponding bar.
Surprise calculation and market direction:
The difference between Actual and Forecast is calculated and displayed in the table as Bullish, Bearish, or Neutral.
Price levels in pips:
Entry (Entry), three targets (TP1, TP2, TP3), and Stop Loss (SL) can be set in pips relative to the entry price.
Each level has independent lines and labels, which update only if the corresponding input value changes, keeping the rest of the chart intact.
Clear visualization on the chart:
Colored lines:
Entry → blue
TPs → green
Stop Loss → red
Vertical event line → orange, highlighting the release moment.
Integrated informative table:
Displays:
Event name
Entry price
TP1, TP2, TP3
Market direction status (Bullish/Bearish/Neutral)
Table colors reflect market direction (green for bullish, red for bearish, gray for neutral).
How to use the script:
Add the indicator to the XAUUSD chart.
Set the ISM Services PMI event date and time in the input panel.
Enter the Entry Price and pip values for TP1, TP2, TP3, and SL according to your strategy.
The indicator will automatically draw lines and labels on the chart and update the table with the event details and market direction.
Whenever you change an input value, only the corresponding line and label will update, keeping other levels fixed.
Important Notes:
The indicator does not perform automatic trades; it serves as a visual reference for trading decisions.
Ensure the event timezone is set correctly to match the release time in your local time zone.
Use in combination with your own risk management and trading strategy.
TradingView publication rules followed:
Full instructions for using the indicator
Clear explanation of inputs and settings
Description of lines and label behavior
Disclaimer that the script is educational and visual, not automated trading
