Period Range AnalyzerThis indicator analyzes a specific periodic range, which can start from a fixed date or a defined lookback period. It draws percentage levels and colored zones between the highest and lowest price. It also displays a detailed information table, which shows the price's position within the range in "Trend" mode, and the relative strength of currency pairs in "Forex" mode. The current price position is also indicated by a label with a percentage value and the name of the corresponding zone.
User Guide
Calculation Method
This setting determines how the indicator defines the range used for the calculation.
Lookback Period: In this mode, the indicator uses the last N candles (the number can be specified in the "Lookback Period (bars)" field). The range (the highest and lowest price) is "floating," meaning it is recalculated with each new candle based on the last N candles.
Date Based: In this mode, the calculation starts from a fixed date and time you select. The indicator finds the opening price of the start date and continuously tracks the highest and lowest price from that point on. This mode is ideal for measuring performance from a specific event (e.g., start of a week/month/year, news).
Data Handling Note: If you select a date in "Date Based" mode for which no data is available on the current timeframe (e.g., switching to a very low timeframe), the indicator will automatically use the earliest available candle as the starting point. All calculations (Open, Max, Min, Range, Percentage, Change, Trend) are based on this actual start date.
Start Date & Time
This setting is only active in "Date Based" mode.
Here you can specify the fixed starting point for the calculation.
The specified time is in the Exchange timezone.
Important limitation: Due to TradingView platform limits, visual elements (levels, zones) are only drawn for a maximum of 250 candles back. If the set date is older than this, the calculation still applies to the entire period (from the set date), but the drawing only covers the last 250 candles. The table always displays accurate data for the entire period.
When switching to a higher timeframe, the range may restart from a slightly later bar due to TradingView's bar alignment. For best accuracy, set your timeframe first, then select the start date.
Table Mode
This setting controls what data the information table displays.
Trend: This is the default mode, which works on any symbol (stock, index, crypto, etc.). It displays information related to the trend and the range.
Forex: This is a special mode used to measure the strength of currency and crypto pairs. It only works on symbols with exactly 6 characters (e.g., "EURUSD", "BTCUSD"). It treats the first 3 characters as the base currency (e.g., EUR) and the last 3 as the quote currency (e.g., USD). If the symbol does not have 6 characters, the table will automatically display in "Trend" mode.
Trend
This trend determination operates based on the formation order of the high and low within the analyzed range:
Its switch is located in the “Table Additional Rows” menu.
Bullish: Indicated if the low was formed before the high (on different candles). Or if they formed on the same candle, it was a bullish candle.
Bearish: Indicated if the high was formed before the low (on different candles). Or if they formed on the same candle, it was a bearish candle.
Neutral: Indicated if the high and low formed on the same candle, and it was a "doji" candle (close = open).
Upper & Lower Threshold
These settings (Upper Threshold (%) and Lower Threshold (%) in the "Label Coloring" section) primarily determine the state (Bullish/Bearish/Neutral) of the top row of the table.
The logic is not based on the percentage change of the price movement, but on the current price's position within the range, where the bottom of the range is 0% and the top is 100%.
Upper Threshold (%): The percentage level (e.g., 60.0) above which the indicator considers the price position "Bullish" (or "Strong").
Lower Threshold (%): The percentage level (e.g., 40.0) below which the indicator considers the price position "Bearish" (or "Weak").
If the price is between the two (e.g., between 40% and 60%), the signal is Neutral.
Secondary function: These thresholds also control the color of the label next to the price, provided the "Dynamic Label Coloring" option is enabled.
스크립트에서 "Table"에 대해 찾기
Range Percentage Analyzer This indicator is a tool for analyzing the market range and trend. It calculates the extent of price movement between a specified starting point and the current price, displaying it as a percentage.
The calculation can be based on a fixed lookback period (e.g., the last 30 candles) or from a fixed start date. It also provides a clear table that shows the general trend in "Trend" mode, and the relative strength of the base and quote currencies of forex pairs (e.g., EURUSD) in "Forex" mode.
User Guide
Calculation Method
This setting determines how the indicator defines the starting point for the calculation.
Lookback Period: In this mode, the indicator uses the last N candles (the number can be specified in the "Lookback Period (bars)" field, maximum 250).
The starting point is "floating," meaning it shifts with each new candle. For example, with a setting of 30, the 30th candle from the current one will always be the starting point.
Date Based: In this mode, the calculation starts from a fixed date and time you select.
This mode is ideal for measuring performance from a specific event (e.g., news, start of a week/month).
Note: If you select a date in "Date Based" mode for which no data is available on the current timeframe (e.g., switching to a very low timeframe), the indicator will automatically use the earliest available candle as the starting point.
Start Date & Time
This setting is only active in "Date Based" mode.
Here you can specify the fixed starting point for the calculation.
The specified time is in the Exchange timezone.
Important limitation: Due to TradingView platform limits, visual elements (box, line) are only drawn for a maximum of 250 candles back.
If the set date is older than this, the calculation still applies to the entire period (from the set date), but the drawing only covers the last 250 candles.
When switching to a higher timeframe, the range may restart from a slightly later bar due to TradingView's bar alignment. For best accuracy, set your timeframe first, then select the start date.
Table Mode
This setting controls what data the information table displays.
Trend: This is the default mode, which works on any symbol (stock, index, crypto, etc.). It displays information related to the trend.
Forex: This is a special mode used to measure the strength of currency pairs.
It only works on symbols with exactly 6 characters (e.g., "EURUSD", "BTCUSD"). It treats the first 3 characters as the base currency (e.g., EUR) and the last 3 as the quote currency (e.g., USD).
If the symbol does not have 6 characters, the table will automatically display in "Trend" mode.
Extremes Trend Row
If this is enabled, the table displays an additional row that determines the trend based on the formation order of the high and low within the analyzed range.
The logic is as follows:
Bullish: Indicated if the low was formed before the high.
(Or if they formed on the same candle, which was a bullish candle).
Bearish: Indicated if the high was formed before the low.
(Or if they formed on the same candle, which was a bearish candle).
Neutral: Indicated if the high and low formed on the same candle, and it was a "doji" candle (close = open).
Upper & Lower Threshold
These settings control the logic for the "Change Trend" and "Forex Display" rows at the top of the table.
They determine when the total percentage change for the entire period is considered "Bullish/Strong", "Bearish/Weak", or "Neutral".
Upper Threshold (%): The percentage value (default 0.1%) above which the indicator considers the change "Bullish/Strong".
Lower Threshold (%): The percentage value (default -0.1%) below which the indicator considers the change "Bearish/Weak".
If the change is between the two, the signal is Neutral.
SECTOR ROTATION Sector Rotation Indicator with Auto Chart Symbol
This indicator helps traders track relative performance across multiple indices/sectors simultaneously, making it easy to identify sector rotation and market leadership.
Key Features:
✅ 21 Symbols Tracking: Monitor 20 customizable symbols + your current chart symbol automatically(DIVIDEND SYMBOL)
✅ Percentage Performance: All moving averages show percentage gain/loss from 1 timeframe period ago
✅ Color-Coded Visualization: Heat map coloring (red to green) based on relative performance ranking
✅ Flexible Timeframes: Works on any timeframe from 1-minute to 12-month charts
✅ Performance Table: Quick-view table showing candle performance with inside/outside bar detection
✅ Indian Market Ready: Pre-configured with NSE indices (NIFTY, BANKNIFTY, and sectoral indices)
Default Symbols (Customizable):
NIFTY, CNXSMALLCAP, CNXMIDCAP, BANKNIFTY
Sector indices: IT, AUTO, PHARMA, METAL, ENERGY, FMCG, etc.
Plus your current chart symbol (automatically added)
How It Works:
Select your preferred timeframe (1D, 1W, 1M, etc.)
The indicator calculates percentage performance from given period ago
Moving averages show smoothed performance trends
Colors indicate relative strength: Green = outperformers, Red = underperformers
Perfect For:
Sector rotation analysis
Relative strength comparison
Market breadth assessment
Index/ETF traders
Swing and position traders
Settings:
Adjustable MA length (default: 20)
Customizable colors and table position
Show/hide percentage labels
Horizontal or vertical table layout
This is not any buy or sell signal or recommendation, consult with your advisor first.
Buy And Hold Performance Screener - [JTCAPITAL]Buy And Hold Performance Screener – is a script designed to track and display multi-asset “buy and hold” performance curves and performance statistics over defined timeframes for selected symbols. It doesn’t attempt to time entries or exits; rather, it shows what would happen if one simply bought the asset at the defined start date and held it.
The indicator works by calculating in the following steps:
Start Date Definition
The script begins by reading an input for the start date. This defines the bar from which the equity curves begin.
Symbol Definitions & Close Price Retrieval
The script allows the user to specify up to ten tickers. For each ticker it uses request.security() on the “1D” timeframe to retrieve the daily close price of that symbol.
Plot Enable Inputs
For each ticker there is an input boolean controlling whether the equity curve for that ticker should be plotted.
Asset Name Cleaning
The helper function clean_name(string asset) => … takes the asset string (e.g., “CRYPTO:SOLUSD”) and manipulates it (via string splitting and replacements) to derive a cleaned short name (e.g., “SOL”). This name is used for visuals (labels, table headers).
Equity Curve Calculation (“HODL”)
The helper function f_HODL(closez) defines a variable equity that assumes a starting equity of 1 unit at the start date and then multiplies by the ratio of each bar’s close to the prior bar’s close: i.e. daily compounding of returns.
Performance Metrics Calculation
The helper function f_performance(closez) calculates, for each symbol’s close series, the percentage change of the current close relative to its close 30 days ago, 90 days ago, 180 days ago, 1 year ago (365 days), 2 years ago (730 days) and 3 years ago (1095 days).
Equity Curve Plots
For each ticker, if the corresponding plot input is true, the script assigns a plotted variable equal to the equity curve value. Its then drawing each selected equity curve on the chart, each in a distinct color.
Table Construction
If the plottable input is true, the script constructs a table and populates it with rows and column corresponding to the assigned tickers and the set 6 timeframes used for display.
Buy and Sell Conditions:
Since this is strictly a “buy-and-hold” performance screener, there are no explicit buy or sell signals generated or plotted. The script assumes: buy at the defined start_date, hold continuously to present. There are no filters, no exit logic, no take-profit or stop-loss. The benefit of this approach is to provide a clean benchmark of how selected assets would have performed if one simply adopted a passive “buy & hold” approach from a given start date.
Features and Parameters:
start_date (input.time) : Defines the date from which performance and equity curves begin.
ticker1 … ticker10 (input.symbol) : User-selectable asset symbols to include in the screener.
plot1 … plot10 (input.bool) : Boolean flags to enable/disable plotting of each asset’s equity curve.
plottable (input.bool) : Flag to enable/disable drawing the performance table.
Colored plotting + Labels for identifying each asset curve on the chart.
Specifications:
Here is a detailed breakdown of every calculation/variable/function used in the script and what each part means:
start_date
This is defined via input.time(timestamp("1 Jan 2025"), title = "Start Date"). It allows the user to pick a specific calendar date from which the equity curves and performance calculations will start.
ticker1 … ticker10
These inputs allow the user to select up to ten different assets (symbols) to monitor. The script uses each of these to fetch daily close prices.
plot1 … plot10
Boolean inputs controlling which of the ten asset equity curves are plotted. If plotX is true, the equity curve for ticker X will be visible; otherwise it will be not plotted. This gives the user flexibility to include or exclude specific assets on the chart.
Returns the cleaned asset short name.
This provides friendly text labels like “BTC”, “ETH”, “SOL”, etc., instead of full symbol codes.
The choice of distinct colours for each asset helps differentiate curves visually when multiple assets are overlaid.
Colour definitions
Variables color1…color10 are explicitly defined via color.rgb(r,g,b) to give each asset a unique colour (e.g., red, orange, yellow, green, cyan, blue, purple, pink, etc.).
What are the benefits of combining these calculations?
By computing equity curves for multiple assets from the same start date and overlaying them, you can visualise comparative performance of different assets under a uniform “buy & hold” assumption.
The performance table adds multi-horizon returns (30 D, 90 D, 180 D, 1 Y, 2 Y, 3 Y) which helps the user see both short-term and longer-term performance without having to manually compute returns.
The use of daily close data via request.security(..., "1D") removes dependency on the chart’s timeframe, thereby standardising the comparison across assets.
The equity curve and table together provide both visual (curve) and numerical (table) summaries of performance, making it easier to spot trends, divergences, and cross-asset comparisons at a glance.
Because it uses compounding (equity := equity * (closez / closez )), the curves reflect the real growth of a 1-unit investment held over time, rather than only simple returns.
The labelling of curves and the color-coding make the multi-asset overlay easier to interpret.
Using a clean start date ensures that all curves begin at the same point (1 unit at start_date), making relative performance intuitive.
Because of this, the script is useful as a benchmarking tool: rather than trying to pick entries or exit points, you can simply compare “what if I had held these assets since Jan 1 2025” (or your chosen date), and see which assets out-/under-performed in that period. It helps an investor or trader evaluate the long-term benefits of passive vs. active management, or of allocation decisions.
Please note:
The script assumes continuous daily data and does not account for dividends, fees, slippage, or tax implications.
It does not attempt to optimise timing or provide trading signals.
Returns prior to the start date are ignored (equity only begins once time >= start_date).
For newly listed assets with fewer than 365 or 730 or 1095 days of history, the longer-horizon returns may return na or misleading values.
Because it uses request.security() without specifying lookahead, and on “1D” timeframe, it complies with standard usage but you should verify there is no look-ahead bias in your particular setup.
ENJOY!
Multi-Timeframe EMA (5 Configurable)Here's a comprehensive description you can use for your indicator:
Multi-Timeframe EMA Indicator (5 Configurable Slots)
Description
This indicator displays up to 5 Exponential Moving Averages (EMAs) from different timeframes simultaneously on a single chart. Perfect for multi-timeframe analysis, it allows traders to visualize key EMAs from intraday to higher timeframes without switching charts.
Key Features
5 Independent EMA Slots: Each slot can be configured with its own timeframe, EMA length, and color
Flexible Configuration: Mix any timeframes and EMA lengths (e.g., 1m EMA 50, 15m EMA 200, 4h EMA 100)
Smart Label Formatting: Automatically displays timeframes in readable format (minutes, hours, or days)
Optional Data Table: Toggle a compact table showing EMA values and price distance percentages
Individual Toggle Controls: Enable/disable each EMA independently without losing settings
Customizable Styling: Adjust colors and line width to match your chart theme
Default Configuration
EMA 1: 1-minute timeframe, EMA 200 (Red)
EMA 2: 5-minute timeframe, EMA 200 (Purple)
EMA 3: 15-minute timeframe, EMA 200 (Yellow)
EMA 4: 1-hour timeframe, EMA 200 (Blue)
EMA 5: 4-hour timeframe, EMA 200 (Orange)
How to Use
Add the indicator to any chart
Configure each EMA slot in the settings:
Timeframe: Choose from 1m, 5m, 15m, 1h, 4h, D, W, M, or custom
Length: Set the EMA period (default 200)
Color: Select a color for easy identification
Enable "Show Line Labels" to see EMA identifiers on the right side
Enable "Show Values Table" for a detailed view of current values and distances
Use Cases
Trend Analysis: Identify alignment across multiple timeframes
Support/Resistance: Use higher timeframe EMAs as dynamic S/R levels
Entry/Exit Timing: Enter on lower timeframe signals near higher timeframe EMAs
Multi-Timeframe Confirmation: Validate setups when price is above/below key EMAs
Scalping: Monitor 1m/5m EMAs while respecting 1h/4h trend direction
Tips
All EMAs update in real-time and move with the chart
Use contrasting colors for easier visual distinction
Disable unused slots to declutter your chart
The table shows percentage distance from current price to each EMA
Works on any symbol and any chart timeframe
TradeVision Pro - Multi-Factor Analysis System═══════════════════════════════════════════════════════════════════
TRADEVISION PRO - MULTI-FACTOR ANALYSIS SYSTEM
Created by Zakaria Safri
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A comprehensive technical analysis tool combining multiple factors for
signal generation, trend analysis, and dynamic risk management visualization.
Designed for educational purposes to study multi-factor convergence trading
strategies across all markets and timeframes.
⚠️ IMPORTANT DISCLAIMER:
This indicator is provided for EDUCATIONAL and INFORMATIONAL purposes only.
It does NOT constitute financial advice, investment advice, or trading advice.
Past performance does not guarantee future results. Trading involves
substantial risk of loss. Always do your own research and consult a
financial advisor before making trading decisions.
🎯 KEY FEATURES
═══════════════════════════════════════════════════════════════════
✅ MULTI-FACTOR SIGNAL GENERATION
• Price Volume Trend (PVT) analysis
• Rate of Change (ROC) momentum confirmation
• Volume-Weighted Moving Average (VWMA) trend filter
• Simple Moving Average (SMA) price smoothing
• Signals only when all factors align
✅ DYNAMIC RISK VISUALIZATION (Educational Only)
• ATR-based stop loss calculation
• Risk-reward based take profit levels (1-5 targets)
• Visual lines and labels showing entry, SL, and TPs
• Automatically adapts to market volatility
• ⚠️ VISUAL REFERENCE ONLY - Does not execute trades
✅ SUPPORT & RESISTANCE DETECTION
• Automatic pivot-based level identification
• Red dashed lines for resistance zones
• Green dashed lines for support areas
• Helps identify key price levels
✅ VWMA TREND BANDS
• Volume-weighted moving average with standard deviation
• Color-changing bands (Green = Uptrend, Red = Downtrend)
• Filled band area for easy visualization
• Volume-confirmed trend strength
✅ TREND DETECTION SYSTEM
• Counting-based trend confirmation
• Three states: Up Trend, Down Trend, Ranging
• Requires threshold of consecutive bars
• Independent trend validation
✅ PRICE RANGE VISUALIZATION
• High/Low range lines showing market structure
• Filled area highlighting price volatility
• Helps identify breakout zones
✅ COMPREHENSIVE INFO TABLE
• Real-time trend status
• Last signal type (BUY/SELL)
• Entry price display
• Stop loss level
• All active take profit levels
• Clean, professional layout
✅ OPTIONAL FEATURES
• Bar coloring by trend direction
• Customizable alert notifications
• Toggle visibility for all components
• Fully configurable parameters
📊 HOW IT WORKS
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SIGNAL METHODOLOGY:
BUY SIGNAL generates when ALL conditions are met:
• Smoothed price > Moving Average (upward price trend)
• PVT > PVT Average (volume supporting uptrend)
• ROC > 0 (positive momentum)
• Close > VWMA (above volume-weighted average)
SELL SIGNAL generates when ALL conditions are met:
• Smoothed price < Moving Average (downward price trend)
• PVT < PVT Average (volume supporting downtrend)
• ROC < 0 (negative momentum)
• Close < VWMA (below volume-weighted average)
This multi-factor approach filters out weak signals and waits for
strong convergence before generating alerts.
RISK CALCULATION:
Stop Loss = Entry ± (ATR × SL Multiplier)
• Uses Average True Range for volatility measurement
• Automatically adjusts to market conditions
Take Profit Levels = Entry ± (Risk Distance × TP Multiplier × Level)
• Risk Distance = |Entry - Stop Loss|
• Creates risk-reward based targets
• Example: TP Multiplier 1.0 = 1:1, 2:2, 3:3 risk-reward
⚠️ NOTE: All risk levels are VISUAL REFERENCES for educational study.
They do not execute trades automatically.
⚙️ SETTINGS GUIDE
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SIGNAL SETTINGS:
• Signal Length (14): Main calculation period for averages
• Smooth Length (8): Price data smoothing period
• PVT Length (14): Price Volume Trend calculation period
• ROC Length (9): Rate of Change momentum period
RISK MANAGEMENT (Visual Only):
• ATR Length (14): Volatility measurement lookback
• SL Multiplier (2.2): Stop loss distance (× ATR)
• TP Multiplier (1.0): Risk-reward ratio per TP level
• TP Levels (1-5): Number of take profit targets to display
• Show TP/SL Lines: Toggle visual reference lines
SUPPORT & RESISTANCE:
• Pivot Lookback (10): Sensitivity for S/R detection
• Show SR: Toggle support/resistance lines
VWMA BANDS:
• VWMA Length (20): Volume-weighted average period
• Show Bands: Toggle band visibility
TREND DETECTION:
• Trend Threshold (5): Consecutive bars required for trend
PRICE LINES:
• Period (20): High/low calculation lookback
• Show: Toggle price range visualization
DISPLAY OPTIONS:
• Signals: Show/hide BUY/SELL labels
• Table: Show/hide information panel
• Color Bars: Enable trend-based bar coloring
ALERTS:
• Enable: Activate alert notifications for signals
💡 USAGE INSTRUCTIONS
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RECOMMENDED APPROACH:
• Works on all timeframes (1m to Monthly)
• Suitable for all markets (Stocks, Forex, Crypto, etc.)
• Best used with additional analysis and confirmation
• Always practice proper risk management
ENTRY STRATEGY:
1. Wait for BUY or SELL signal to appear
2. Check trend table for trend confirmation
3. Verify VWMA band color matches signal direction
4. Look for nearby support/resistance confluence
5. Consider entering on next candle open
6. Use visual SL level for risk management
EXIT STRATEGY:
1. Use TP levels as potential exit zones
2. Consider scaling out at multiple TP levels
3. Exit on opposite signal
4. Adjust stops as trade progresses
5. Account for spread and slippage
TREND TRADING:
• "Up Trend" → Focus on BUY signals
• "Down Trend" → Focus on SELL signals
• "Ranging" → Wait for clear trend or use range strategies
🎨 VISUAL ELEMENTS
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• GREEN VWMA BANDS → Bullish trend indication
• RED VWMA BANDS → Bearish trend indication
• ORANGE DASHED LINE → Entry price reference
• RED SOLID LINE → Stop loss level
• GREEN DOTTED LINES → Take profit targets
• RED DASHED LINES → Resistance levels
• GREEN DASHED LINES → Support levels
• GREY FILLED AREA → Price high/low range
• GREEN BUY LABEL → Long signal
• RED SELL LABEL → Short signal
• BLUE INFO TABLE → Current trade details
• GREEN/RED BARS → Trend direction (optional)
⚠️ IMPORTANT NOTES
═══════════════════════════════════════════════════════════════════
RISK WARNING:
• Trading involves substantial risk of loss
• You can lose more than your initial investment
• Past performance does not guarantee future results
• No indicator is 100% accurate
• Always use proper position sizing
• Never risk more than you can afford to lose
EDUCATIONAL PURPOSE:
• This tool is for learning and research
• Not a complete trading system
• Should be combined with other analysis
• Requires interpretation and context
• Test thoroughly before live use
• Consider consulting a financial advisor
TECHNICAL LIMITATIONS:
• Signals lag price action (all indicators lag)
• False signals occur in choppy markets
• Works better in trending conditions
• Support/resistance levels are approximate
• TP/SL levels are suggestions, not guarantees
📚 METHODOLOGY
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This indicator combines established technical analysis concepts:
• Price Volume Trend (PVT): Volume-weighted price momentum
• Rate of Change (ROC): Momentum measurement
• Volume-Weighted Moving Average (VWMA): Trend identification
• Average True Range (ATR): Volatility measurement (J. Welles Wilder)
• Pivot Points: Support/resistance detection
All methods are based on publicly available technical analysis
principles. No proprietary or "secret" algorithms are used.
⚖️ FULL DISCLAIMER
═══════════════════════════════════════════════════════════════════
LIABILITY:
The creator (Zakaria Safri) assumes NO liability for:
• Trading losses or damages of any kind
• Loss of capital or profits
• Incorrect signal interpretation
• Technical issues, bugs, or errors
• Any consequences of using this tool
USER RESPONSIBILITY:
By using this indicator, you acknowledge that:
• You are solely responsible for your trading decisions
• You understand the substantial risks involved
• You will not hold the creator liable for losses
• You will conduct your own research and analysis
• You may consult a licensed financial professional
• You are using this tool entirely at your own risk
AS-IS PROVISION:
This indicator is provided "AS IS" without warranty of any kind,
express or implied, including but not limited to warranties of
merchantability, fitness for a particular purpose, or non-infringement.
The creator is not a registered investment advisor, financial planner,
or broker-dealer. This tool is not approved or endorsed by any
financial authority.
📞 ABOUT THE CREATOR
═══════════════════════════════════════════════════════════════════
Created by: Zakaria Safri
Specialization: Technical analysis indicator development
Focus: Multi-factor analysis, risk visualization, trend detection
This is an educational tool designed to demonstrate technical
analysis concepts and multi-factor signal generation methods.
📋 VERSION INFO
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Version: 1.0
Platform: TradingView Pine Script v5
License: Mozilla Public License 2.0
Creator: Zakaria Safri
Year: 2024
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Study Carefully, Trade Wisely, Manage Risk Properly
TradeVision Pro - Educational Trading Tool
Created by Zakaria Safri
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Seasonality Heatmap [QuantAlgo]🟢 Overview
The Seasonality Heatmap analyzes years of historical data to reveal which months and weekdays have consistently produced gains or losses, displaying results through color-coded tables with statistical metrics like consistency scores (1-10 rating) and positive occurrence rates. By calculating average returns for each calendar month and day-of-week combination, it identifies recognizable seasonal patterns (such as which months or weekdays tend to rally versus decline) and synthesizes this into actionable buy low/sell high timing possibilities for strategic entries and exits. This helps traders and investors spot high-probability seasonal windows where assets have historically shown strength or weakness, enabling them to align positions with recurring bull and bear market patterns.
🟢 How It Works
1. Monthly Heatmap
How % Return is Calculated:
The indicator fetches monthly closing prices (or Open/High/Low based on user selection) and calculates the percentage change from the previous month:
(Current Month Price - Previous Month Price) / Previous Month Price × 100
Each cell in the heatmap represents one month's return in a specific year, creating a multi-year historical view
Colors indicate performance intensity: greener/brighter shades for higher positive returns, redder/brighter shades for larger negative returns
What Averages Mean:
The "Avg %" row displays the arithmetic mean of all historical returns for each calendar month (e.g., averaging all Januaries together, all Februaries together, etc.)
This metric identifies historically recurring patterns by showing which months have tended to rise or fall on average
Positive averages indicate months that have typically trended upward; negative averages indicate historically weaker months
Example: If April shows +18.56% average, it means April has averaged a 18.56% gain across all years analyzed
What Months Up % Mean:
Shows the percentage of historical occurrences where that month had a positive return (closed higher than the previous month)
Calculated as:
(Number of Months with Positive Returns / Total Months) × 100
Values above 50% indicate the month has been positive more often than negative; below 50% indicates more frequent negative months
Example: If October shows "64%", then 64% of all historical Octobers had positive returns
What Consistency Score Means:
A 1-10 rating that measures how predictable and stable a month's returns have been
Calculated using the coefficient of variation (standard deviation / mean) - lower variation = higher consistency
High scores (8-10, green): The month has shown relatively stable behavior with similar outcomes year-to-year
Medium scores (5-7, gray): Moderate consistency with some variability
Low scores (1-4, red): High variability with unpredictable behavior across different years
Example: A consistency score of 8/10 indicates the month has exhibited recognizable patterns with relatively low deviation
What Best Means:
Shows the highest percentage return achieved for that specific month, along with the year it occurred
Reveals the maximum observed upside and identifies outlier years with exceptional performance
Useful for understanding the range of possible outcomes beyond the average
Example: "Best: 2016: +131.90%" means the strongest January in the dataset was in 2016 with an 131.90% gain
What Worst Means:
Shows the most negative percentage return for that specific month, along with the year it occurred
Reveals maximum observed downside and helps understand the range of historical outcomes
Important for risk assessment even in months with positive averages
Example: "Worst: 2022: -26.86%" means the weakest January in the dataset was in 2022 with a 26.86% loss
2. Day-of-Week Heatmap
How % Return is Calculated:
Calculates the percentage change from the previous day's close to the current day's price (based on user's price source selection)
Returns are aggregated by day of the week within each calendar month (e.g., all Mondays in January, all Tuesdays in January, etc.)
Each cell shows the average performance for that specific day-month combination across all historical data
Formula:
(Current Day Price - Previous Day Close) / Previous Day Close × 100
What Averages Mean:
The "Avg %" row at the bottom aggregates all months together to show the overall average return for each weekday
Identifies broad weekly patterns across the entire dataset
Calculated by summing all daily returns for that weekday across all months and dividing by total observations
Example: If Monday shows +0.04%, Mondays have averaged a 0.04% change across all months in the dataset
What Days Up % Mean:
Shows the percentage of historical occurrences where that weekday had a positive return
Calculated as:
(Number of Positive Days / Total Days Observed) × 100
Values above 50% indicate the day has been positive more often than negative; below 50% indicates more frequent negative days
Example: If Fridays show "54%", then 54% of all Fridays in the dataset had positive returns
What Consistency Score Means:
A 1-10 rating measuring how stable that weekday's performance has been across different months
Based on the coefficient of variation of daily returns for that weekday across all 12 months
High scores (8-10, green): The weekday has shown relatively consistent behavior month-to-month
Medium scores (5-7, gray): Moderate consistency with some month-to-month variation
Low scores (1-4, red): High variability across months, with behavior differing significantly by calendar month
Example: A consistency score of 7/10 for Wednesdays means they have performed with moderate consistency throughout the year
What Best Means:
Shows which calendar month had the strongest average performance for that specific weekday
Identifies favorable day-month combinations based on historical data
Format shows the month abbreviation and the average return achieved
Example: "Best: Oct: +0.20%" means Mondays averaged +0.20% during October months in the dataset
What Worst Means:
Shows which calendar month had the weakest average performance for that specific weekday
Identifies historically challenging day-month combinations
Useful for understanding which month-weekday pairings have shown weaker performance
Example: "Worst: Sep: -0.35%" means Tuesdays averaged -0.35% during September months in the dataset
3. Optimal Timing Table/Summary Table
→ Best Month to BUY: Identifies the month with the lowest average return (most negative or least positive historically), representing periods where prices have historically been relatively lower
Based on the observation that buying during historically weaker months may position for subsequent recovery
Shows the month name, its average return, and color-coded performance
Example: If May shows -0.86% as "Best Month to BUY", it means May has historically averaged -0.86% in the analyzed period
→ Best Month to SELL: Identifies the month with the highest average return (most positive historically), representing periods where prices have historically been relatively higher
Based on historical strength patterns in that month
Example: If July shows +1.42% as "Best Month to SELL", it means July has historically averaged +1.42% gains
→ 2nd Best Month to BUY: The second-lowest performing month based on average returns
Provides an alternative timing option based on historical patterns
Offers flexibility for staged entries or when the primary month doesn't align with strategy
Example: Identifies the next-most favorable historical buying period
→ 2nd Best Month to SELL: The second-highest performing month based on average returns
Provides an alternative exit timing based on historical data
Useful for staged profit-taking or multiple exit opportunities
Identifies the secondary historical strength period
Note: The same logic applies to "Best Day to BUY/SELL" and "2nd Best Day to BUY/SELL" rows, which identify weekdays based on average daily performance across all months. Days with lowest averages are marked as buying opportunities (historically weaker days), while days with highest averages are marked for selling (historically stronger days).
🟢 Examples
Example 1: NVIDIA NASDAQ:NVDA - Strong May Pattern with High Consistency
Analyzing NVIDIA from 2015 onwards, the Monthly Heatmap reveals May averaging +15.84% with 82% of months being positive and a consistency score of 8/10 (green). December shows -1.69% average with only 40% of months positive and a low 1/10 consistency score (red). The Optimal Timing table identifies December as "Best Month to BUY" and May as "Best Month to SELL." A trader recognizes this high-probability May strength pattern and considers entering positions in late December when prices have historically been weaker, then taking profits in May when the seasonal tailwind typically peaks. The high consistency score in May (8/10) provides additional confidence that this pattern has been relatively stable year-over-year.
Example 2: Crypto Market Cap CRYPTOCAP:TOTALES - October Rally Pattern
An investor examining total crypto market capitalization notices September averaging -2.42% with 45% of months positive and 5/10 consistency, while October shows a dramatic shift with +16.69% average, 90% of months positive, and an exceptional 9/10 consistency score (blue). The Day-of-Week heatmap reveals Mondays averaging +0.40% with 54% positive days and 9/10 consistency (blue), while Thursdays show only +0.08% with 1/10 consistency (yellow). The investor uses this multi-layered analysis to develop a strategy: enter crypto positions on Thursdays during late September (combining the historically weak month with the less consistent weekday), then hold through October's historically strong period, considering exits on Mondays when intraweek strength has been most consistent.
Example 3: Solana BINANCE:SOLUSDT - Extreme January Seasonality
A cryptocurrency trader analyzing Solana observes an extraordinary January pattern: +59.57% average return with 60% of months positive and 8/10 consistency (teal), while May shows -9.75% average with only 33% of months positive and 6/10 consistency. August also displays strength at +59.50% average with 7/10 consistency. The Optimal Timing table confirms May as "Best Month to BUY" and January as "Best Month to SELL." The Day-of-Week data shows Sundays averaging +0.77% with 8/10 consistency (teal). The trader develops a seasonal rotation strategy: accumulate SOL positions during May weakness, hold through the historically strong January period (which has shown this extreme pattern with reasonable consistency), and specifically target Sunday exits when the weekday data shows the most recognizable strength pattern.
Candle Body Break (M/W/D/4H/1H)v5# Candle Body Break (M/W/D/4H/1H) Multi-Timeframe Indicator
This indicator identifies and plots **Candle Body Breaks** across five key timeframes: Monthly (M), Weekly (W), Daily (D), 4-Hour (4H), and 1-Hour (1H).
## Core Logic: Candle Body Break
The core concept is a break in the swing high/low defined by the body of the previous counter-trend candle(s). It focuses purely on **closing price breaks** of remembered highs/lows established by full candle bodies (close > open or close < open).
1. **Remembering the Swing:**
* After a bullish break (upward trend), the indicator waits for the first **bearish (close < open) candle** to appear. This bearish candle's high (`rememberedHigh`) and low (`rememberedLow`) are saved as the **breakout level**.
* Subsequent bearish candles that make a new low update this saved level, continuously adjusting the level to the most significant recent resistance/support established by the body's range.
2. **Executing the Break:**
* **Bull Break (Long signal):** Occurs when a **bullish candle's closing price** exceeds the last remembered bearish high (`rememberedHigh`).
* **Bear Break (Short signal):** Occurs when a **bearish candle's closing price** falls below the last remembered bullish low (`rememberedLow_Bull`).
Once a break occurs, the memory is cleared, and the indicator waits for the next counter-trend candle to establish a new level.
## Features
* **Multi-Timeframe Analysis:** Displays break lines and labels for M, W, D, 4H, and 1H timeframes on any chart.
* **Timeframe Filtering:** Break lines are only shown for timeframes **equal to or higher** than the current chart timeframe (e.g., on a 4H chart, only 4H, D, W, and M breaks are displayed).
* **Candidate Lines (Dotted Green):** Plots the current potential breakout level (the remembered high/low) that must be broken to trigger the next signal.
* **Direction Table:** A table in the top right corner summarizes the latest break direction (⇧ Up / ⇩ Down) for all five timeframes. This can be optionally limited to the 4H chart only.
* **1H Alert:** Triggers an alert when a 1-Hour break is detected.
## Input Settings Translation (for Mod Compliance)
| English Input Text | Original Japanese Text |
| :--- | :--- |
| **Show Monthly Break Lines** | 月足ブレイクを描画する |
| **Show Weekly Break Lines** | 週足ブレイクを描画する |
| **Show Daily Break Lines** | 日足ブレイクを描画する |
| **Show 4-Hour Break Lines** | 4時間足ブレイクを描画する |
| **Show 1-Hour Break Lines** | 1時間足ブレイクを描画する |
| **Show Monthly Candidate Lines** | 月足ブレイク候補ラインを描画する |
| **Show Weekly Candidate Lines** | 週足ブレイク候補ラインを描画する |
| **Show Daily Candidate Lines** | 日足ブレイク候補ラインを描画する |
| **Show 4-Hour Candidate Lines** | 4時間足ブレイク候補ラインを描画する |
| **Show 1-Hour Candidate Lines** | 1時間足ブレイク候補ラインを描画する |
| **Show Only Current TF Candidate Lines** | チャート時間足の候補ラインのみ表示 |
| **Show Table Only on 4H Chart** | テーブルを4Hチャートのみ表示 |
*Please note: The default alert message "1-Hour Break Detected" is also in English.*
※日本語訳
ろうそく足実体ブレイク（M/W/D/4H/1H）マルチタイムフレーム・インジケーター（日本語訳）
このインジケーターは、月足（M）、週足（W）、日足（D）、4時間足（4H）、1時間足（1H）の5つの主要な時間足におけるろうそく足実体ブレイクを検出し、プロットします。
コアロジック：ろうそく足実体ブレイク
このロジックの中核は、直近の**逆行ろうそく足（カウンター・トレンド・キャンドル）**の実体によって定義されたスイングの高値/安値のブレイクです。終値が実体のレンジ外で確定することを純粋に追跡します。
スイングの記憶（Remembering the Swing）:
強気のブレイク（上昇トレンド）の後、インジケーターは最初に現れる弱気（終値＜始値）のろうそく足を待ちます。この弱気ろうそく足の高値（rememberedHigh）と安値（rememberedLow）が、ブレイクアウトレベルとして保存されます。
その後、安値を更新する弱気ろうそく足が続いた場合、この保存されたレベルが更新され、実体のレンジによって確立された最新の重要なレジスタンス/サポートにレベルが継続的に調整されます。
ブレイクの実行（Executing the Break）:
ブルブレイク（買いシグナル）: 最後に記憶された弱気ろうそく足の高値（rememberedHigh）を、強気ろうそく足の終値が上回ったときに発生します。
ベアブレイク（売りシグナル）: 最後に記憶された強気ろうそく足の安値（rememberedLow_Bull）を、弱気ろうそく足の終値が下回ったときに発生します。
一度ブレイクが発生すると、記憶されたレベルはクリアされ、インジケーターは次の逆行ろうそく足が出現し、新しいレベルを確立するのを待ちます。
機能
マルチタイムフレーム分析: 現在のチャートの時間足に関わらず、M、W、D、4H、1Hのブレイクラインとラベルを表示します。
時間足フィルタリング: ブレイクラインは、現在のチャート時間足と同じか、それよりも上位の時間足のもののみが表示されます（例：4時間足チャートでは、4H、D、W、Mのブレイクのみが表示されます）。
候補ライン（緑の点線）: 次のシグナルをトリガーするためにブレイクされる必要がある、現在の潜在的なブレイクアウトレベル（記憶された高値/安値）をプロットします。
方向テーブル: 右上隅のテーブルに、5つの全時間足の最新のブレイク方向（⇧ 上昇 / ⇩ 下降）をまとめて表示します。これは、オプションで4時間足チャートのみに表示するように制限できます。
1時間足アラート: 1時間足のブレイクが検出されたときにアラートをトリガーします。
入力設定の翻訳
コード内の入力設定（UIテキスト）の日本語訳は以下の通りです。
英語の入力テキスト 日本語訳
Show Monthly Break Lines 月足ブレイクを描画する
Show Weekly Break Lines 週足ブレイクを描画する
Show Daily Break Lines 日足ブレイクを描画する
Show 4-Hour Break Lines 4時間足ブレイクを描画する
Show 1-Hour Break Lines 1時間足ブレイクを描画する
Show Monthly Candidate Lines 月足ブレイク候補ラインを描画する
Show Weekly Candidate Lines 週足ブレイク候補ラインを描画する
Show Daily Candidate Lines 日足ブレイク候補ラインを描画する
Show 4-Hour Candidate Lines 4時間足ブレイク候補ラインを描画する
Show 1-Hour Candidate Lines 1時間足ブレイク候補ラインを描画する
Show Only Current TF Candidate Lines チャート時間足の候補ラインのみ表示
Show Table Only on 4H Chart テーブルを4Hチャートのみ表示
Alert Message: 1-Hour Break Detected アラートメッセージ: 1時間足ブレイク発生
Golden Cross Screener [Pineify]Golden Cross Screener Pineify – Multi-Symbol Trend Detection Screener for TradingView
Discover the Golden Cross Screener Pineify for TradingView: a multi-symbol, multi-timeframe indicator for crypto and other assets. Customizable Golden Cross detection, robust algorithm, and intuitive screener design for smarter portfolio trend analysis.
Key Features
Multi-symbol screening across major cryptocurrencies or assets – BTCUSD, ETHUSD, XRPUSD, USDT, BNB, SOLUSD, DOGEUSD, TRXUSD (fully customizable).
Multi-timeframe analysis (e.g., 1m, 5m, 10m, 30m), enabling robust trend detection from scalp to swing.
Customizable Moving Average settings for both Fast and Slow MA (source and length).
Efficient screener table, highlighting Golden Cross events and current asset trends in one panel.
Visual cues for bullish, bearish, and cross states using intuitive color-coding and labels.
Flexible symbol and timeframe inputs to tailor the screener to any portfolio or watchlist.
How It Works
The Golden Cross Screener Pineify leverages the classic Golden Cross methodology—a bullish trend signal triggered when a shorter-term moving average crosses above a longer-term moving average. To improve robustness, you are empowered to configure both Fast MA and Slow MA periods and sources, making the detection logic applicable to any symbol, timeframe, or asset class.
Internally, the script runs dedicated calculations on each chosen symbol and timeframe, generating independent signals using exponential moving averages (EMA). Using the TradingView `request.security` function, it fetches and processes price data for up to eight portfolio assets on four timeframes, displaying the detected Golden Cross, Bullish, or Bearish states in a central screener table.
Trading Ideas and Insights
Spot emerging bullish or bearish trends across your favorite crypto pairs or trading assets in real time.
Capture prime opportunities when multiple assets align with Golden Cross signals—ideal for portfolio rebalancing or rotational strategies.
Analyze trend consistency by monitoring cross events at multiple timeframes for a given asset.
Swiftly identify when short-term and long-term momentum diverge—flagging potential reversals or trend initiations.
The Golden Cross Screener Pineify is not just a trend signal; it’s a holistic multi-asset scanner built for traders who know the power of combining technical breadth with agile timing.
How Multiple Indicators Work Together
This screener stands out with its modular approach: each asset/timeframe pair is monitored in isolation, yet displayed collectively for multidimensional market insight. Each symbol’s price action is processed through independently configured EMAs—Fast and Slow—whose crossovers are analyzed for directional bias. The implementation’s real innovation is in its screener table engine: it aggregates signals, synchronizes timeframes, and color-codes market states, allowing users to see confluences, divergences, and sector trends at a glance.
Combining Golden Cross detection with customizable moving averages and flexible multi-timeframe, multi-symbol scanning means users can fine-tune sensitivity, focus on specific signals, and adapt screener logic for scalping, swing trading, or investing.
Unique Aspects
True multi-symbol screener within the TradingView indicator framework.
Full customization of screener assets, timeframes, and moving averages.
Advanced, efficient use of TradingView table for clear, actionable visualization.
No dependency on standard, static MA settings—adjust everything to match your strategy.
Big-picture and granular trend detection in one tool, designed for both active traders and portfolio managers.
How to Use
Add the Golden Cross Screener Pineify to your TradingView chart.
Choose up to eight symbols—crypto, stock, forex, or custom assets.
Set four timeframes for screening, from lower to higher intervals.
Adjust moving average sources (price, close, etc.) and period lengths for both Fast and Slow MAs to suit your trading style.
Interpret table cells: clear labels and color indicate Golden Cross (trend shift), Bullish (uptrend), Bearish (downtrend) states for each symbol/timeframe.
React to signal alignments—deploy or rebalance positions, increase alert sensitivity, or backtest sequence confluences.
Customization
The indicator’s inputs panel gives full control:
Select which symbols to screen, making it perfect for any asset watchlist.
Pick the desired timeframes—mix daily, hourly, or minute-based intervals.
Adjust Fast and Slow MA settings: switch source type, change period length, and fine-tune detection logic as needed.
Style your screener table via TradingView settings (colors, font sizes, alignment).
Every element is customizable—adapt the Golden Cross Screener Pineify for your specific portfolio, trading timeframe, and strategy focus.
Conclusion
The Golden Cross Screener Pineify elevates multi-symbol trend detection to a new level on TradingView. By combining configurable Golden Cross logic with a powerful screener engine, it serves both precision and broad market insight—crucial for agile traders and strategic portfolio managers. Whether you’re tracking crypto pairs, stocks, forex, or a mix, this tool transforms static trend analysis into an active, multi-dimensional trading edge.
RVol+ Enhanced Relative Volume Indicator📊 RVol+ Enhanced Relative Volume Indicator
Overview
RVol+ (Relative Volume Plus) is an advanced time-based relative volume indicator designed specifically for swing traders and breakout detection. Unlike simple volume comparisons, RVol+ analyzes volume at the same time of day across multiple sessions, providing statistically significant insights into institutional activity and breakout potential.
🎯 Key Features
Core Volume Analysis
Time-Based RVol Calculation - Compares current cumulative volume to the average volume at this exact time over the past N days
Statistical Z-Score - Measures volume in standard deviations from the mean for true anomaly detection
Volume Percentile - Shows where current volume ranks historically (0-100%)
Sustained Volume Filter - 3-bar moving average prevents false signals from single-bar spikes
Breakout Detection
🚀 Confirmed Breakouts - Identifies price breakouts validated by high volume (RVol > 1.5x)
⚠️ False Breakout Warnings - Alerts when price breaks key levels on low volume (high failure risk)
Multi-Timeframe Context - Weekly volume overlay prevents chasing daily noise
Advanced Metrics
OBV Divergence Detection - Spots bullish/bearish accumulation/distribution patterns
Volume Profile Integration - Identifies institutional positioning
Money Flow Analysis - Tracks smart money vs retail activity
Extreme Volume Alerts - 🔥 Labels mark unusual spikes beyond the display cap
Visual Intelligence
Smart Color Coding:
🟢 Bright Teal = High activity (RVol ≥ 1.5x)
🟡 Medium Teal = Caution zone (RVol ≥ 1.2x)
⚪ Light Teal = Normal activity
🟠 Orange = Breakout confirmed
🔴 Red = False breakout risk
Comprehensive Stats Table:
Current Volume (formatted as M/K/B)
RVol ratio
Z-Score with significance
Volume percentile
Historical average and standard deviation
Sustained volume confirmation
📈 How to Use
For Swing Trading (1D - 3W Holds)
Perfect Setup:
✓ RVol > 1.5x (bright teal)
✓ Z-Score > 2.0 (⚡ alert)
✓ Percentile > 90%
✓ Sustained = ✓
✓ 🚀 Breakout label appears
Avoid:
✗ Red "Low Vol" warning during breakouts
✗ RVol < 1.0 at key levels
✗ Sustained volume not confirmed
Signal Interpretation
⚡ Z>2 Labels - Statistically significant volume (95th+ percentile) - highest probability moves
↗️ OBV+ Labels - Bullish accumulation (OBV rising while price consolidates)
↘️ OBV- Labels - Bearish distribution (OBV falling while price rises)
🔵 Blue Background - Weekly volume elevated (confirms daily strength)
⚙️ Customization
Basic Settings
N Day Average - Number of historical days for comparison (default: 5)
RVol Thresholds - Customize highlight levels (default: 1.2x, 1.5x)
Visual Display Cap - Prevent extreme spikes from compressing view (default: 4.0x)
Advanced Metrics (Toggle On/Off)
Z-Score analysis
Weekly RVol context
OBV divergence detection
Volume percentile ranking
Breakout signal generation
Table Customization
Position - 9 placement options to avoid chart overlap
Size - Tiny to Huge
Colors - Full customization of positive/negative/neutral values
Transparency - Adjustable background
Debug Mode
Enable Pine Logs for calculation transparency
Adjustable log frequency
Real-time calculation breakdown
🔬 Technical Details
Algorithm:
Binary search for historical lookups (O(log n) performance)
Time-zone aware session detection
DST-safe timestamp calculations
Exponentially weighted standard deviation
Anti-repainting architecture
Performance:
Optimized for max_bars_back = 5000
Efficient array management
Built-in function optimization
Memory-conscious data structures
📊 What Makes RVol+ Different?
vs. Standard Volume:
Context-aware (time-of-day matters)
Statistical significance testing
False breakout filtering
vs. Basic RVol:
Z-Score normalization (2-3 sigma detection)
Multi-timeframe confirmation
OBV divergence integration
Sustained volume filtering
Smart visual scaling
vs. Professional Tools:
Free and open-source
Fully customizable
No black-box algorithms
Educational debug logs
💡 Best Practices
Wait for Confirmation - Don't enter on first bar; wait for sustained volume ✓
Combine with Price Action - RVol validates, price structure determines entry
Weekly Context Matters - Blue background = institutional interest
Z-Score is King - Focus on ⚡ alerts for highest probability
Avoid Low Volume Breakouts - Red ⚠️ labels = high failure risk
🎓 Trading Psychology
Volume precedes price. When RVol+ shows:
High RVol + Rising OBV = Accumulation before breakout
High RVol at Resistance = Test of conviction
Low RVol on Breakout = Retail-driven (fade candidate)
Z-Score > 3 = Potential "whale" positioning
📝 Credits
Based on the time-based RVol concept from /u/HurlTeaInTheSea, enhanced with:
Statistical analysis (z-scores, percentiles)
Multi-timeframe integration
OBV divergence detection
Professional-grade visualization
Swing trading optimization
🔧 Version History
v2.0 - Enhanced Edition
Added Z-Score analysis
Multi-timeframe volume context
OBV divergence detection
Breakout confirmation system
Smart color coding
Customizable stats table
Debug logging mode
Performance optimizations
📚 Learn More
For optimal use with swing trading:
Combine with support/resistance levels
Watch for volume clusters in consolidation
Use weekly timeframe for trend confirmation
Monitor OBV divergence for early warnings
⚠️ Disclaimer
This indicator is for educational purposes. Volume analysis is one component of trading decisions. Always use proper risk management, consider multiple timeframes, and validate signals with price structure. Past performance does not guarantee future results.
🚀 Getting Started
Add indicator to chart
Adjust "N Day Average" to your preference (5-10 days typical)
Position stats table to avoid overlap
Enable features you want to monitor
Watch for 🚀 breakout confirmations!
Happy Trading! 📈
Intraday Rising & Reversal ScannerPine Script Description: Intraday Rising & Reversal ScannerThis Pine Script is a TradingView indicator designed to identify stocks with intraday (1-hour timeframe) potential for bullish (rising) or bearish (reversal) movements. It scans for stocks based on user-defined technical criteria, including price change, relative volume, RSI, EMA, ATR, and VWAP. The script plots signals on the chart, displays a summary table, and triggers alerts when conditions are met.FeaturesBullish Signal (Rising Stocks):1H Price Change: > 1% (configurable, e.g., >2% for volatile markets).
Relative Volume: > 2.0 (volume is at least twice the 20-period average).
RSI (14): Between 50 and 70 (strong but not overbought momentum).
Price vs EMA 13: Price above the 13-period EMA (confirms short-term uptrend).
ATR (14): Current ATR above its 20-period average (indicates volatility).
VWAP: Price above VWAP (optional, shown on chart for manual confirmation).
Bearish Signal (Reversal Stocks):1H Price Change: < -1% (configurable, e.g., <-2% for stronger reversals).
Relative Volume: > 2.0 (high volume confirms selling pressure).
RSI (14): > 70 (overbought, increasing reversal likelihood).
Price vs EMA 13: Price below the 13-period EMA (confirms short-term downtrend).
ATR (14): Current ATR above its 20-period average (indicates volatility).
VWAP: Price below VWAP (optional, shown on chart for manual confirmation).
Visualization:Bullish Signal: Green triangle below the bar.
Bearish Signal: Red triangle above the bar.
VWAP: Plotted as a blue line for manual verification.
Table: Displays real-time metrics (Change %, Relative Volume, RSI, Price vs EMA, ATR, VWAP) in the top-right corner, color-coded (green for bullish, red for bearish).
Alerts:Separate alerts for bullish ("Intraday Bullish Signal") and bearish ("Intraday Bearish Signal") conditions.
Customizable alert messages include parameter values for easy tracking.
How It WorksThe script runs on the 1-hour (1H) timeframe, ensuring all calculations are based on hourly data.
Indicators are computed:Change %: Percentage price change over the last hour.
Relative Volume: Current volume divided by the 20-period SMA of volume.
RSI: 14-period Relative Strength Index.
EMA 13: 13-period Exponential Moving Average.
ATR: 14-period Average True Range, compared to its 20-period SMA.
VWAP: Volume Weighted Average Price, plotted for visual confirmation.
Signals are generated when all conditions for either bullish or bearish criteria are met.
A table summarizes key metrics, and alerts can be set up for real-time notifications.
Usage InstructionsApply the Script:Open TradingView’s Pine Editor.
Copy and paste the script.
Click "Add to Chart" and set the chart to the 1-hour (1H) timeframe.
Set Up Alerts:Right-click on the chart > "Add Alert".
Select "Intraday Bullish Signal" or "Intraday Bearish Signal" as the condition.
Configure notifications (e.g., SMS, email, or TradingView alerts).
Manual VWAP Check:VWAP is plotted as a blue line. Verify that the price is above VWAP for bullish signals or below for bearish signals using the table or chart.
To make VWAP a mandatory filter, uncomment the VWAP conditions in the bull_signal and bear_signal definitions.
BOCS Channel Scalper Indicator - Mean Reversion Alert System# BOCS Channel Scalper Indicator - Mean Reversion Alert System
## WHAT THIS INDICATOR DOES:
This is a mean reversion trading indicator that identifies consolidation channels through volatility analysis and generates alert signals when price enters entry zones near channel boundaries. **This indicator version is designed for manual trading with comprehensive alert functionality.** Unlike automated strategies, this tool sends notifications (via popup, email, SMS, or webhook) when trading opportunities occur, allowing you to manually review and execute trades. The system assumes price will revert to the channel mean, identifying scalp opportunities as price reaches extremes and preparing to bounce back toward center.
## INDICATOR VS STRATEGY - KEY DISTINCTION:
**This is an INDICATOR with alerts, not an automated strategy.** It does not execute trades automatically. Instead, it:
- Displays visual signals on your chart when entry conditions are met
- Sends customizable alerts to your device/email when opportunities arise
- Shows TP/SL levels for reference but does not place orders
- Requires you to manually enter and exit positions based on signals
- Works with all TradingView subscription levels (alerts included on all plans)
**For automated trading with backtesting**, use the strategy version. For manual control with notifications, use this indicator version.
## ALERT CAPABILITIES:
This indicator includes four distinct alert conditions that can be configured independently:
**1. New Channel Formation Alert**
- Triggers when a fresh BOCS channel is identified
- Message: "New BOCS channel formed - potential scalp setup ready"
- Use this to prepare for upcoming trading opportunities
**2. Long Scalp Entry Alert**
- Fires when price touches the long entry zone
- Message includes current price, calculated TP, and SL levels
- Notification example: "LONG scalp signal at 24731.75 | TP: 24743.2 | SL: 24716.5"
**3. Short Scalp Entry Alert**
- Fires when price touches the short entry zone
- Message includes current price, calculated TP, and SL levels
- Notification example: "SHORT scalp signal at 24747.50 | TP: 24735.0 | SL: 24762.75"
**4. Any Entry Signal Alert**
- Combined alert for both long and short entries
- Use this if you want a single alert stream for all opportunities
- Message: "BOCS Scalp Entry: at "
**Setting Up Alerts:**
1. Add indicator to chart and configure settings
2. Click the Alert (⏰) button in TradingView toolbar
3. Select "BOCS Channel Scalper" from condition dropdown
4. Choose desired alert type (Long, Short, Any, or Channel Formation)
5. Set "Once Per Bar Close" to avoid false signals during bar formation
6. Configure delivery method (popup, email, webhook for automation platforms)
7. Save alert - it will fire automatically when conditions are met
**Alert Message Placeholders:**
Alerts use TradingView's dynamic placeholder system:
- {{ticker}} = Symbol name (e.g., NQ1!)
- {{close}} = Current price at signal
- {{plot_1}} = Calculated take profit level
- {{plot_2}} = Calculated stop loss level
These placeholders populate automatically, creating detailed notification messages without manual configuration.
## KEY DIFFERENCE FROM ORIGINAL BOCS:
**This indicator is designed for traders seeking higher trade frequency.** The original BOCS indicator trades breakouts OUTSIDE channels, waiting for price to escape consolidation before entering. This scalper version trades mean reversion INSIDE channels, entering when price reaches channel extremes and betting on a bounce back to center. The result is significantly more trading opportunities:
- **Original BOCS**: 1-3 signals per channel (only on breakout)
- **Scalper Indicator**: 5-15+ signals per channel (every touch of entry zones)
- **Trade Style**: Mean reversion vs trend following
- **Hold Time**: Seconds to minutes vs minutes to hours
- **Best Markets**: Ranging/choppy conditions vs trending breakouts
This makes the indicator ideal for active day traders who want continuous alert opportunities within consolidation zones rather than waiting for breakout confirmation. However, increased signal frequency also means higher potential commission costs and requires disciplined trade selection when acting on alerts.
## TECHNICAL METHODOLOGY:
### Price Normalization Process:
The indicator normalizes price data to create consistent volatility measurements across different instruments and price levels. It calculates the highest high and lowest low over a user-defined lookback period (default 100 bars). Current close price is normalized using: (close - lowest_low) / (highest_high - lowest_low), producing values between 0 and 1 for standardized volatility analysis.
### Volatility Detection:
A 14-period standard deviation is applied to the normalized price series to measure price deviation from the mean. Higher standard deviation values indicate volatility expansion; lower values indicate consolidation. The indicator uses ta.highestbars() and ta.lowestbars() to identify when volatility peaks and troughs occur over the detection period (default 14 bars).
### Channel Formation Logic:
When volatility crosses from a high level to a low level (ta.crossover(upper, lower)), a consolidation phase begins. The indicator tracks the highest and lowest prices during this period, which become the channel boundaries. Minimum duration of 10+ bars is required to filter out brief volatility spikes. Channels are rendered as box objects with defined upper and lower boundaries, with colored zones indicating entry areas.
### Entry Signal Generation:
The indicator uses immediate touch-based entry logic. Entry zones are defined as a percentage from channel edges (default 20%):
- **Long Entry Zone**: Bottom 20% of channel (bottomBound + channelRange × 0.2)
- **Short Entry Zone**: Top 20% of channel (topBound - channelRange × 0.2)
Long signals trigger when candle low touches or enters the long entry zone. Short signals trigger when candle high touches or enters the short entry zone. Visual markers (arrows and labels) appear on chart, and configured alerts fire immediately.
### Cooldown Filter:
An optional cooldown period (measured in bars) prevents alert spam by enforcing minimum spacing between consecutive signals. If cooldown is set to 3 bars, no new long alert will fire until 3 bars after the previous long signal. Long and short cooldowns are tracked independently, allowing both directions to signal within the same period.
### ATR Volatility Filter:
The indicator includes a multi-timeframe ATR filter to avoid alerts during low-volatility conditions. Using request.security(), it fetches ATR values from a specified timeframe (e.g., 1-minute ATR while viewing 5-minute charts). The filter compares current ATR to a user-defined minimum threshold:
- If ATR ≥ threshold: Alerts enabled
- If ATR < threshold: No alerts fire
This prevents notifications during dead zones where mean reversion is unreliable due to insufficient price movement. The ATR status is displayed in the info table with visual confirmation (✓ or ✗).
### Take Profit Calculation:
Two TP methods are available:
**Fixed Points Mode**:
- Long TP = Entry + (TP_Ticks × syminfo.mintick)
- Short TP = Entry - (TP_Ticks × syminfo.mintick)
**Channel Percentage Mode**:
- Long TP = Entry + (ChannelRange × TP_Percent)
- Short TP = Entry - (ChannelRange × TP_Percent)
Default 50% targets the channel midline, a natural mean reversion target. These levels are displayed as visual lines with labels and included in alert messages for reference when manually placing orders.
### Stop Loss Placement:
Stop losses are calculated just outside the channel boundary by a user-defined tick offset:
- Long SL = ChannelBottom - (SL_Offset_Ticks × syminfo.mintick)
- Short SL = ChannelTop + (SL_Offset_Ticks × syminfo.mintick)
This logic assumes channel breaks invalidate the mean reversion thesis. SL levels are displayed on chart and included in alert notifications as suggested stop placement.
### Channel Breakout Management:
Channels are removed when price closes more than 10 ticks outside boundaries. This tolerance prevents premature channel deletion from minor breaks or wicks, allowing the mean reversion setup to persist through small boundary violations.
## INPUT PARAMETERS:
### Channel Settings:
- **Nested Channels**: Allow multiple overlapping channels vs single channel
- **Normalization Length**: Lookback for high/low calculation (1-500, default 100)
- **Box Detection Length**: Period for volatility detection (1-100, default 14)
### Scalping Settings:
- **Enable Long Scalps**: Toggle long alert generation on/off
- **Enable Short Scalps**: Toggle short alert generation on/off
- **Entry Zone % from Edge**: Size of entry zone (5-50%, default 20%)
- **SL Offset (Ticks)**: Distance beyond channel for stop (1+, default 5)
- **Cooldown Period (Bars)**: Minimum spacing between alerts (0 = no cooldown)
### ATR Filter:
- **Enable ATR Filter**: Toggle volatility filter on/off
- **ATR Timeframe**: Source timeframe for ATR (1, 5, 15, 60 min, etc.)
- **ATR Length**: Smoothing period (1-100, default 14)
- **Min ATR Value**: Threshold for alert enablement (0.1+, default 10.0)
### Take Profit Settings:
- **TP Method**: Choose Fixed Points or % of Channel
- **TP Fixed (Ticks)**: Static distance in ticks (1+, default 30)
- **TP % of Channel**: Dynamic target as channel percentage (10-100%, default 50%)
### Appearance:
- **Show Entry Zones**: Toggle zone labels on channels
- **Show Info Table**: Display real-time indicator status
- **Table Position**: Corner placement (Top Left/Right, Bottom Left/Right)
- **Long Color**: Customize long signal color (default: darker green for readability)
- **Short Color**: Customize short signal color (default: red)
- **TP/SL Colors**: Customize take profit and stop loss line colors
- **Line Length**: Visual length of TP/SL reference lines (5-200 bars)
## VISUAL INDICATORS:
- **Channel boxes** with semi-transparent fill showing consolidation zones
- **Colored entry zones** labeled "LONG ZONE ▲" and "SHORT ZONE ▼"
- **Entry signal arrows** below/above bars marking long/short alerts
- **TP/SL reference lines** with emoji labels (⊕ Entry, 🎯 TP, 🛑 SL)
- **Info table** showing channel status, last signal, entry/TP/SL prices, risk/reward ratio, and ATR filter status
- **Visual confirmation** when alerts fire via on-chart markers synchronized with notifications
## HOW TO USE:
### For 1-3 Minute Scalping with Alerts (NQ/ES):
- ATR Timeframe: "1" (1-minute)
- ATR Min Value: 10.0 (for NQ), adjust per instrument
- Entry Zone %: 20-25%
- TP Method: Fixed Points, 20-40 ticks
- SL Offset: 5-10 ticks
- Cooldown: 2-3 bars to reduce alert spam
- **Alert Setup**: Configure "Any Entry Signal" for combined long/short notifications
- **Execution**: When alert fires, verify chart visuals, then manually place limit order at entry zone with provided TP/SL levels
### For 5-15 Minute Day Trading with Alerts:
- ATR Timeframe: "5" or match chart
- ATR Min Value: Adjust to instrument (test 8-15 for NQ)
- Entry Zone %: 20-30%
- TP Method: % of Channel, 40-60%
- SL Offset: 5-10 ticks
- Cooldown: 3-5 bars
- **Alert Setup**: Configure separate "Long Scalp Entry" and "Short Scalp Entry" alerts if you trade directionally based on bias
- **Execution**: Review channel structure on alert, confirm ATR filter shows ✓, then enter manually
### For 30-60 Minute Swing Scalping with Alerts:
- ATR Timeframe: "15" or "30"
- ATR Min Value: Lower threshold for broader market
- Entry Zone %: 25-35%
- TP Method: % of Channel, 50-70%
- SL Offset: 10-15 ticks
- Cooldown: 5+ bars or disable
- **Alert Setup**: Use "New Channel Formation" to prepare for setups, then "Any Entry Signal" for execution alerts
- **Execution**: Larger timeframes allow more analysis time between alert and entry
### Webhook Integration for Semi-Automation:
- Configure alert webhook URL to connect with platforms like TradersPost, TradingView Paper Trading, or custom automation
- Alert message includes all necessary order parameters (direction, entry, TP, SL)
- Webhook receives structured data when signal fires
- External platform can auto-execute based on alert payload
- Still maintains manual oversight vs full strategy automation
## USAGE CONSIDERATIONS:
- **Manual Discipline Required**: Alerts provide opportunities but execution requires judgment. Not all alerts should be taken - consider market context, trend, and channel quality
- **Alert Timing**: Alerts fire on bar close by default. Ensure "Once Per Bar Close" is selected to avoid false signals during bar formation
- **Notification Delivery**: Mobile/email alerts may have 1-3 second delay. For immediate execution, use desktop popups or webhook automation
- **Cooldown Necessity**: Without cooldown, rapidly touching price action can generate excessive alerts. Start with 3-bar cooldown and adjust based on alert volume
- **ATR Filter Impact**: Enabling ATR filter dramatically reduces alert count but improves quality. Track filter status in info table to understand when you're receiving fewer alerts
- **Commission Awareness**: High alert frequency means high potential trade count. Calculate if your commission structure supports frequent scalping before acting on all alerts
## COMPATIBLE MARKETS:
Works on any instrument with price data including stock indices (NQ, ES, YM, RTY), individual stocks, forex pairs (EUR/USD, GBP/USD), cryptocurrency (BTC, ETH), and commodities. Volume-based features are not included in this indicator version. Multi-timeframe ATR requires higher-tier TradingView subscription for request.security() functionality on timeframes below chart timeframe.
## KNOWN LIMITATIONS:
- **Indicator does not execute trades** - alerts are informational only; you must manually place all orders
- **Alert delivery depends on TradingView infrastructure** - delays or failures possible during platform issues
- **No position tracking** - indicator doesn't know if you're in a trade; you must manage open positions independently
- **TP/SL levels are reference only** - you must manually set these on your broker platform; they are not live orders
- **Immediate touch entry can generate many alerts** in choppy zones without adequate cooldown
- **Channel deletion at 10-tick breaks** may be too aggressive or lenient depending on instrument tick size
- **ATR filter from lower timeframes** requires TradingView Premium/Pro+ for request.security()
- **Mean reversion logic fails** in strong breakout scenarios - alerts will fire but trades may hit stops
- **No partial closing capability** - full position management is manual; you determine scaling out
- **Alerts do not account for gaps** or overnight price changes; morning alerts may be stale
## RISK DISCLOSURE:
Trading involves substantial risk of loss. This indicator provides signals for educational and informational purposes only and does not constitute financial advice. Past performance does not guarantee future results. Mean reversion strategies can experience extended drawdowns during trending markets. Alerts are not guaranteed to be profitable and should be combined with your own analysis. Stop losses may not fill at intended levels during extreme volatility or gaps. Never trade with capital you cannot afford to lose. Consider consulting a licensed financial advisor before making trading decisions. Always verify alerts against current market conditions before executing trades manually.
## ACKNOWLEDGMENT & CREDITS:
This indicator is built upon the channel detection methodology created by **AlgoAlpha** in the "Smart Money Breakout Channels" indicator. Full credit and appreciation to AlgoAlpha for pioneering the normalized volatility approach to identifying consolidation patterns. The core channel formation logic using normalized price standard deviation is AlgoAlpha's original contribution to the TradingView community.
Enhancements to the original concept include: mean reversion entry logic (vs breakout), immediate touch-based alert generation, comprehensive alert condition system with customizable notifications, multi-timeframe ATR volatility filtering, cooldown period for alert management, dual TP methods (fixed points vs channel percentage), visual TP/SL reference lines, and real-time status monitoring table. This indicator version is specifically designed for manual traders who prefer alert-based decision making over automated execution.
Macro & Earnings Dashboard — NY Fed CalendarMacro & Earnings Dashboard — NY Fed Calendar
This is an overlay indicator designed to provide a quick, real-time overview of the most critical upcoming US economic data releases and corporate earnings reports directly on your TradingView chart. It functions as a dynamic dashboard, removing the need to constantly check external calendars.
Key Features
1. Real-Time Economic Calendar (Bottom-Right Table)
The dashboard tracks the time remaining until the next release of five major, high-impact economic indicators. The data for these dates is pre-loaded directly from the New York Fed Economic Indicators Calendar (currently loaded for October through December 2025).
The tracked events include:
CPI (Consumer Price Index)
PPI (Producer Price Index)
Employment Situation (Non-Farm Payrolls / Unemployment Rate)
Interest Rate Decision (FOMC Meetings)
Consumer Sentiment (University of Michigan Survey)
2. Corporate Earnings Tracker (Top-Right Table)
This table uses TradingView's built-in data to calculate the estimated days remaining until the next Earnings Per Share (EPS) report for a curated list of high-profile NASDAQ tickers:
AAPL, NVDA, GOOG, TSLA, MSFT, AMZN, META
3. Color-Coded Urgency
The "Days" column for both macro and earnings tables uses a traffic light system to instantly communicate how soon the event is:
Red: The event is scheduled for Today or Tomorrow (0–1 day away).
Orange: The event is scheduled for the current week (within 6 days).
Teal: The event is more than a week away.
Gray: The date is currently unavailable or outside the loaded calendar range.
cd_indiCATor_CxGeneral:
This indicator is the redesigned, simplified, and feature-enhanced version of the previously shared indicators:
cd_cisd_market_Cx, cd_HTF_Bias_Cx, cd_sweep&cisd_Cx, cd_SMT_Sweep_CISD_Cx, and cd_RSI_divergence_Cx.
Within the holistic setup, the indicator tracks:
• HTF bias
• Market structure (trend) in the current timeframe
• Divergence between selected pairs (SMT)
• Divergence between price and RSI values
• Whether the price is in an important area (FVG, iFVG, and Volume Imbalance)
• Whether the price is at a key level
• Whether the price is within a user-defined special timeframe
The main condition and trigger of the setup is an HTF sweep with CISD confirmation on the aligned timeframe.
When the main condition occurs, the indicator provides the user with a real-time market status summary, enriched with other data.
________________________________________
What’s new?
-In the SMT module:
• Triad SMT analysis (e.g.: NQ1!, ES1!, and YM1!)
• Dyad SMT analysis (e.g.: EURUSD, GBPUSD)
• Alternative pair definition and divergence analysis for non-correlated assets
o For crypto assets (xxxUSDT <--> xxxUSDT.P) (e.g.: SOLUSDT.P, SOLUSDT)
o For stocks, divergence analysis by comparing the asset with its value in another currency
(BIST:xxx <--> BIST:xxx / EURTRY), (BAT:xxx <--> BAT:xxx / EURUSD)
-Special timeframe definition
-Configurable multi-option alarm center
-Alternative summary presentation (check list / status table / stickers)
________________________________________
Details and usage:
The user needs to configure four main sections:
• Pair and correlated pairs
• Timeframes (Auto / Manual)
• Alarm center
• Visual arrangement and selections
Pair Selections:
The user should adjust trading pairs according to their trade preferences.
Examples:
• Triad: NQ1!-ES1!-YM1!, BTC-ETH-Total3
• Dyad: NAS100-US500, XAUUSD-XAGUSD, XRPUSDT-XLMUSDT
Single pairs:
-Crypto Assets:
If crypto assets are not in the triad or dyad list, they are automatically matched as:
Perpetual <--> Spot (e.g.: DOGEUSDT.P <--> DOGEUSDT)
If the asset is already defined in a dyad list (e.g., DOGE – SHIB), the dyad definition takes priority.
________________________________________
-Stocks:
If stocks are defined in the dyad list (e.g.: BIST:THYAO <--> BIST:PGSUS), the dyad definition takes priority.
If not defined, the stock is compared with its value in the selected currency.
For example, in the Turkish Stock Exchange:
BIST:FENER stock, if EUR is chosen from the menu, is compared as BIST:FENER / OANDA:EURTRY.
Here, “OANDA” and the stock market currency (TRY) are automatically applied for the exchange rate.
For NYSE:XOM, its pair will be NYSE:XOM / EURUSD.
________________________________________
Timeframes:
By default, the menu is set to “Auto.” In this mode, aligned timeframes are automatically selected.
Aligned timeframes (LTF-HTF):
1m-15m, 3m-30m, 5m-1h, 15m-4h, 1h-D, 4h-W, D-M
Example: if monitoring the chart on 5m:
• 1h sweep + 5m CISD confirmation
• D sweep + 1h CISD confirmation (bias)
• 5m market structure
• 1h SMT and 1h RSI divergence analysis
For manual selections, the user must define the timeframes for Sweep and HTF bias.
FVG, iFVG, and Volume Imbalance timeframes must be manually set in both modes.
________________________________________
Alarm Center:
The user can choose according to preferred criteria.
Each row has options.
“Yes” → included in alarm condition.
“No” → not included in alarm condition.
If special timeframe criteria are added to the alarm, the hour range must also be entered in the same row, and the “Special Zone” tab (default: -4) should be checked.
Key level timeframes and plot options must be set manually.
Example alarm setup:
Alongside the main Sweep + CISD condition, if we also want HTF bias + Trend alignment + key level (W, D) and special timeframe (09:00–11:00), we should set up the menu as follows:
________________________________________
Visual Arrangement and Selections:
Users can control visibility with checkboxes according to their preferences.
In the Table & Sticker tab, table options and labels can be controlled.
• Summary Table has two options: Check list and Status Table
• From the HTF bias section, real-time bias and HTF sweep zone (optional) are displayed
• The RSI divergence section only shows divergence analysis results
• The SMT 2 sub-section only functions when triad is selected
Labels are shown on the bar where the sweep + CISD condition occurs, displaying the current situation.
With the Check box option, all criteria’s real-time status is shown (True/False).
Status Table provides a real-time summary table.
Although the menu may look crowded, most settings only need to be adjusted once during initial use.
________________________________________
What’s next?
• Suggestions from users
• Standard deviation projection
• Mitigation/order blocks (cd special mtg)
• PSP /TPD
________________________________________
Final note:
Every additional criterion in the alarm settings will affect alarm frequency.
Multiple conditions occurring at the same time is not, by itself, sufficient to enter a trade—you should always apply your own judgment.
Looking forward to your feedback and suggestions.
Happy trading! 🎉
EMA-RSI-ADX Trend Bands
📌 EMA-RSI-ADX Trend Bands (ERA Trend Bands)
🔥 Overview
The ERA Trend Bands indicator combines Exponential Moving Average (EMA), Relative Strength Index (RSI), and Average Directional Index (ADX) into a powerful multi-factor trend system.
It helps traders:
Identify trend direction (Bullish / Bearish)
Measure trend strength using EMA deviation bands
Confirm momentum with RSI & ADX filters
Visualize conditions with dynamic colors, labels, tables, and signals
⚡ Key Features
📍 EMA Trend Bands
EMA100 with gradient glow effect showing trend bias
Strength bands around EMA (Very Weak → Hyper levels)
Bands color-coded for bullish/bearish extremes
📊 RSI + ADX Confluence
Bullish Signal: RSI ≥ threshold & ADX ≥ threshold → 🟢
Bearish Signal: RSI ≤ threshold & ADX ≤ threshold → 🔴
Candles recolored when conditions are met
Auto-generated labels show live RSI/ADX values
🧩 Strength Levels
Classifies deviation from EMA into 8 levels:
Neutral → Very Weak → Weak → Moderate → Strong → Very Strong → Extreme → Hyper
Dashboard table shows deviation % ranges & strength colors
Dynamic labels display Trend, Strength, Deviation %, RSI & ADX
🎨 Visual Enhancements
Gradient EMA line with glow effect
Bullish (greens) & bearish (reds) vibrant palettes
Background coloring (optional) based on strength
Symbols & labels for entry confirmation
🎯 How to Use
Trend Direction – EMA color + deviation bands show whether market is bullish or bearish.
Strength Confirmation – Use strength labels & dashboard table to gauge overextension.
Entry Signals – Watch for RSI/ADX confluence (green/red labels on chart).
Exits – Monitor when strength fades back toward Neutral/Weak levels.
⚙️ Settings & Inputs
EMA Settings → Length, Line Width, Gradient Intensity
RSI Settings → Length & Thresholds (Bullish / Bearish)
ADX Settings → Length & Thresholds (Bullish / Bearish)
Bands → Enable/disable EMA deviation bands
Labels/Table → Toggle strength info display
Colors → Fully customizable vibrant palettes
🚨 Alerts & Signals
Bullish Condition → RSI & ADX above thresholds
Bearish Condition → RSI & ADX below thresholds
Visual confirmation with labels, candles, and background
⚠️ Disclaimer
This script is for educational purposes only.
It does not constitute financial advice.
Always backtest and use proper risk management before trading live.
✨ Add EMA-RSI-ADX Trend Bands (ERA Trend Bands) to your chart to trade with clarity, strength, and precision.
Tzotchev Trend Measure [EdgeTools]Are you still measuring trend strength with moving averages? Here is a better variant at scientific level:
Tzotchev Trend Measure: A Statistical Approach to Trend Following
The Tzotchev Trend Measure represents a sophisticated advancement in quantitative trend analysis, moving beyond traditional moving average-based indicators toward a statistically rigorous framework for measuring trend strength. This indicator implements the methodology developed by Tzotchev et al. (2015) in their seminal J.P. Morgan research paper "Designing robust trend-following system: Behind the scenes of trend-following," which introduced a probabilistic approach to trend measurement that has since become a cornerstone of institutional trading strategies.
Mathematical Foundation and Statistical Theory
The core innovation of the Tzotchev Trend Measure lies in its transformation of price momentum into a probability-based metric through the application of statistical hypothesis testing principles. The indicator employs the fundamental formula ST = 2 × Φ(√T × r̄T / σ̂T) - 1, where ST represents the trend strength score bounded between -1 and +1, Φ(x) denotes the normal cumulative distribution function, T represents the lookback period in trading days, r̄T is the average logarithmic return over the specified period, and σ̂T represents the estimated daily return volatility.
This formulation transforms what is essentially a t-statistic into a probabilistic trend measure, testing the null hypothesis that the mean return equals zero against the alternative hypothesis of non-zero mean return. The use of logarithmic returns rather than simple returns provides several statistical advantages, including symmetry properties where log(P₁/P₀) = -log(P₀/P₁), additivity characteristics that allow for proper compounding analysis, and improved validity of normal distribution assumptions that underpin the statistical framework.
The implementation utilizes the Abramowitz and Stegun (1964) approximation for the normal cumulative distribution function, achieving accuracy within ±1.5 × 10⁻⁷ for all input values. This approximation employs Horner's method for polynomial evaluation to ensure numerical stability, particularly important when processing large datasets or extreme market conditions.
Comparative Analysis with Traditional Trend Measurement Methods
The Tzotchev Trend Measure demonstrates significant theoretical and empirical advantages over conventional trend analysis techniques. Traditional moving average-based systems, including simple moving averages (SMA), exponential moving averages (EMA), and their derivatives such as MACD, suffer from several fundamental limitations that the Tzotchev methodology addresses systematically.
Moving average systems exhibit inherent lag bias, as documented by Kaufman (2013) in "Trading Systems and Methods," where he demonstrates that moving averages inevitably lag price movements by approximately half their period length. This lag creates delayed signal generation that reduces profitability in trending markets and increases false signal frequency during consolidation periods. In contrast, the Tzotchev measure eliminates lag bias by directly analyzing the statistical properties of return distributions rather than smoothing price levels.
The volatility normalization inherent in the Tzotchev formula addresses a critical weakness in traditional momentum indicators. As shown by Bollinger (2001) in "Bollinger on Bollinger Bands," momentum oscillators like RSI and Stochastic fail to account for changing volatility regimes, leading to inconsistent signal interpretation across different market conditions. The Tzotchev measure's incorporation of return volatility in the denominator ensures that trend strength assessments remain consistent regardless of the underlying volatility environment.
Empirical studies by Hurst, Ooi, and Pedersen (2013) in "Demystifying Managed Futures" demonstrate that traditional trend-following indicators suffer from significant drawdowns during whipsaw markets, with Sharpe ratios frequently below 0.5 during challenging periods. The authors attribute these poor performance characteristics to the binary nature of most trend signals and their inability to quantify signal confidence. The Tzotchev measure addresses this limitation by providing continuous probability-based outputs that allow for more sophisticated risk management and position sizing strategies.
The statistical foundation of the Tzotchev approach provides superior robustness compared to technical indicators that lack theoretical grounding. Fama and French (1988) in "Permanent and Temporary Components of Stock Prices" established that price movements contain both permanent and temporary components, with traditional moving averages unable to distinguish between these elements effectively. The Tzotchev methodology's hypothesis testing framework specifically tests for the presence of permanent trend components while filtering out temporary noise, providing a more theoretically sound approach to trend identification.
Research by Moskowitz, Ooi, and Pedersen (2012) in "Time Series Momentum in the Cross Section of Asset Returns" found that traditional momentum indicators exhibit significant variation in effectiveness across asset classes and time periods. Their study of multiple asset classes over decades revealed that simple price-based momentum measures often fail to capture persistent trends in fixed income and commodity markets. The Tzotchev measure's normalization by volatility and its probabilistic interpretation provide consistent performance across diverse asset classes, as demonstrated in the original J.P. Morgan research.
Comparative performance studies conducted by AQR Capital Management (Asness, Moskowitz, and Pedersen, 2013) in "Value and Momentum Everywhere" show that volatility-adjusted momentum measures significantly outperform traditional price momentum across international equity, bond, commodity, and currency markets. The study documents Sharpe ratio improvements of 0.2 to 0.4 when incorporating volatility normalization, consistent with the theoretical advantages of the Tzotchev approach.
The regime detection capabilities of the Tzotchev measure provide additional advantages over binary trend classification systems. Research by Ang and Bekaert (2002) in "Regime Switches in Interest Rates" demonstrates that financial markets exhibit distinct regime characteristics that traditional indicators fail to capture adequately. The Tzotchev measure's five-tier classification system (Strong Bull, Weak Bull, Neutral, Weak Bear, Strong Bear) provides more nuanced market state identification than simple trend/no-trend binary systems.
Statistical testing by Jegadeesh and Titman (2001) in "Profitability of Momentum Strategies" revealed that traditional momentum indicators suffer from significant parameter instability, with optimal lookback periods varying substantially across market conditions and asset classes. The Tzotchev measure's statistical framework provides more stable parameter selection through its grounding in hypothesis testing theory, reducing the need for frequent parameter optimization that can lead to overfitting.
Advanced Noise Filtering and Market Regime Detection
A significant enhancement over the original Tzotchev methodology is the incorporation of a multi-factor noise filtering system designed to reduce false signals during sideways market conditions. The filtering mechanism employs four distinct approaches: adaptive thresholding based on current market regime strength, volatility-based filtering utilizing ATR percentile analysis, trend strength confirmation through momentum alignment, and a comprehensive multi-factor approach that combines all methodologies.
The adaptive filtering system analyzes market microstructure through price change relative to average true range, calculates volatility percentiles over rolling windows, and assesses trend alignment across multiple timeframes using exponential moving averages of varying periods. This approach addresses one of the primary limitations identified in traditional trend-following systems, namely their tendency to generate excessive false signals during periods of low volatility or sideways price action.
The regime detection component classifies market conditions into five distinct categories: Strong Bull (ST > 0.3), Weak Bull (0.1 < ST ≤ 0.3), Neutral (-0.1 ≤ ST ≤ 0.1), Weak Bear (-0.3 ≤ ST < -0.1), and Strong Bear (ST < -0.3). This classification system provides traders with clear, quantitative definitions of market regimes that can inform position sizing, risk management, and strategy selection decisions.
Professional Implementation and Trading Applications
The indicator incorporates three distinct trading profiles designed to accommodate different investment approaches and risk tolerances. The Conservative profile employs longer lookback periods (63 days), higher signal thresholds (0.2), and reduced filter sensitivity (0.5) to minimize false signals and focus on major trend changes. The Balanced profile utilizes standard academic parameters with moderate settings across all dimensions. The Aggressive profile implements shorter lookback periods (14 days), lower signal thresholds (-0.1), and increased filter sensitivity (1.5) to capture shorter-term trend movements.
Signal generation occurs through threshold crossover analysis, where long signals are generated when the trend measure crosses above the specified threshold and short signals when it crosses below. The implementation includes sophisticated signal confirmation mechanisms that consider trend alignment across multiple timeframes and momentum strength percentiles to reduce the likelihood of false breakouts.
The alert system provides real-time notifications for trend threshold crossovers, strong regime changes, and signal generation events, with configurable frequency controls to prevent notification spam. Alert messages are standardized to ensure consistency across different market conditions and timeframes.
Performance Optimization and Computational Efficiency
The implementation incorporates several performance optimization features designed to handle large datasets efficiently. The maximum bars back parameter allows users to control historical calculation depth, with default settings optimized for most trading applications while providing flexibility for extended historical analysis. The system includes automatic performance monitoring that generates warnings when computational limits are approached.
Error handling mechanisms protect against division by zero conditions, infinite values, and other numerical instabilities that can occur during extreme market conditions. The finite value checking system ensures data integrity throughout the calculation process, with fallback mechanisms that maintain indicator functionality even when encountering corrupted or missing price data.
Timeframe validation provides warnings when the indicator is applied to unsuitable timeframes, as the Tzotchev methodology was specifically designed for daily and higher timeframe analysis. This validation helps prevent misapplication of the indicator in contexts where its statistical assumptions may not hold.
Visual Design and User Interface
The indicator features eight professional color schemes designed for different trading environments and user preferences. The EdgeTools theme provides an institutional blue and steel color palette suitable for professional trading environments. The Gold theme offers warm colors optimized for commodities trading. The Behavioral theme incorporates psychology-based color contrasts that align with behavioral finance principles. The Quant theme provides neutral colors suitable for analytical applications.
Additional specialized themes include Ocean, Fire, Matrix, and Arctic variations, each optimized for specific visual preferences and trading contexts. All color schemes include automatic dark and light mode optimization to ensure optimal readability across different chart backgrounds and trading platforms.
The information table provides real-time display of key metrics including current trend measure value, market regime classification, signal strength, Z-score, average returns, volatility measures, filter threshold levels, and filter effectiveness percentages. This comprehensive dashboard allows traders to monitor all relevant indicator components simultaneously.
Theoretical Implications and Research Context
The Tzotchev Trend Measure addresses several theoretical limitations inherent in traditional technical analysis approaches. Unlike moving average-based systems that rely on price level comparisons, this methodology grounds trend analysis in statistical hypothesis testing, providing a more robust theoretical foundation for trading decisions.
The probabilistic interpretation of trend strength offers significant advantages over binary trend classification systems. Rather than simply indicating whether a trend exists, the measure quantifies the statistical confidence level associated with the trend assessment, allowing for more nuanced risk management and position sizing decisions.
The incorporation of volatility normalization addresses the well-documented problem of volatility clustering in financial time series, ensuring that trend strength assessments remain consistent across different market volatility regimes. This normalization is particularly important for portfolio management applications where consistent risk metrics across different assets and time periods are essential.
Practical Applications and Trading Strategy Integration
The Tzotchev Trend Measure can be effectively integrated into various trading strategies and portfolio management frameworks. For trend-following strategies, the indicator provides clear entry and exit signals with quantified confidence levels. For mean reversion strategies, extreme readings can signal potential turning points. For portfolio allocation, the regime classification system can inform dynamic asset allocation decisions.
The indicator's statistical foundation makes it particularly suitable for quantitative trading strategies where systematic, rules-based approaches are preferred over discretionary decision-making. The standardized output range facilitates easy integration with position sizing algorithms and risk management systems.
Risk management applications benefit from the indicator's ability to quantify trend strength and provide early warning signals of potential trend changes. The multi-timeframe analysis capability allows for the construction of robust risk management frameworks that consider both short-term tactical and long-term strategic market conditions.
Implementation Guide and Parameter Configuration
The practical application of the Tzotchev Trend Measure requires careful parameter configuration to optimize performance for specific trading objectives and market conditions. This section provides comprehensive guidance for parameter selection and indicator customization.
Core Calculation Parameters
The Lookback Period parameter controls the statistical window used for trend calculation and represents the most critical setting for the indicator. Default values range from 14 to 63 trading days, with shorter periods (14-21 days) providing more sensitive trend detection suitable for short-term trading strategies, while longer periods (42-63 days) offer more stable trend identification appropriate for position trading and long-term investment strategies. The parameter directly influences the statistical significance of trend measurements, with longer periods requiring stronger underlying trends to generate significant signals but providing greater reliability in trend identification.
The Price Source parameter determines which price series is used for return calculations. The default close price provides standard trend analysis, while alternative selections such as high-low midpoint ((high + low) / 2) can reduce noise in volatile markets, and volume-weighted average price (VWAP) offers superior trend identification in institutional trading environments where volume concentration matters significantly.
The Signal Threshold parameter establishes the minimum trend strength required for signal generation, with values ranging from -0.5 to 0.5. Conservative threshold settings (0.2 to 0.3) reduce false signals but may miss early trend opportunities, while aggressive settings (-0.1 to 0.1) provide earlier signal generation at the cost of increased false positive rates. The optimal threshold depends on the trader's risk tolerance and the volatility characteristics of the traded instrument.
Trading Profile Configuration
The Trading Profile system provides pre-configured parameter sets optimized for different trading approaches. The Conservative profile employs a 63-day lookback period with a 0.2 signal threshold and 0.5 noise sensitivity, designed for long-term position traders seeking high-probability trend signals with minimal false positives. The Balanced profile uses a 21-day lookback with 0.05 signal threshold and 1.0 noise sensitivity, suitable for swing traders requiring moderate signal frequency with acceptable noise levels. The Aggressive profile implements a 14-day lookback with -0.1 signal threshold and 1.5 noise sensitivity, optimized for day traders and scalpers requiring frequent signal generation despite higher noise levels.
Advanced Noise Filtering System
The noise filtering mechanism addresses the challenge of false signals during sideways market conditions through four distinct methodologies. The Adaptive filter adjusts thresholds based on current trend strength, increasing sensitivity during strong trending periods while raising thresholds during consolidation phases. The Volatility-based filter utilizes Average True Range (ATR) percentile analysis to suppress signals during abnormally volatile conditions that typically generate false trend indications.
The Trend Strength filter requires alignment between multiple momentum indicators before confirming signals, reducing the probability of false breakouts from consolidation patterns. The Multi-factor approach combines all filtering methodologies using weighted scoring to provide the most robust noise reduction while maintaining signal responsiveness during genuine trend initiations.
The Noise Sensitivity parameter controls the aggressiveness of the filtering system, with lower values (0.5-1.0) providing conservative filtering suitable for volatile instruments, while higher values (1.5-2.0) allow more signals through but may increase false positive rates during choppy market conditions.
Visual Customization and Display Options
The Color Scheme parameter offers eight professional visualization options designed for different analytical preferences and market conditions. The EdgeTools scheme provides high contrast visualization optimized for trend strength differentiation, while the Gold scheme offers warm tones suitable for commodity analysis. The Behavioral scheme uses psychological color associations to enhance decision-making speed, and the Quant scheme provides neutral colors appropriate for quantitative analysis environments.
The Ocean, Fire, Matrix, and Arctic schemes offer additional aesthetic options while maintaining analytical functionality. Each scheme includes optimized colors for both light and dark chart backgrounds, ensuring visibility across different trading platform configurations.
The Show Glow Effects parameter enhances plot visibility through multiple layered lines with progressive transparency, particularly useful when analyzing multiple timeframes simultaneously or when working with dense price data that might obscure trend signals.
Performance Optimization Settings
The Maximum Bars Back parameter controls the historical data depth available for calculations, with values ranging from 5,000 to 50,000 bars. Higher values enable analysis of longer-term trend patterns but may impact indicator loading speed on slower systems or when applied to multiple instruments simultaneously. The optimal setting depends on the intended analysis timeframe and available computational resources.
The Calculate on Every Tick parameter determines whether the indicator updates with every price change or only at bar close. Real-time calculation provides immediate signal updates suitable for scalping and day trading strategies, while bar-close calculation reduces computational overhead and eliminates signal flickering during bar formation, preferred for swing trading and position management applications.
Alert System Configuration
The Alert Frequency parameter controls notification generation, with options for all signals, bar close only, or once per bar. High-frequency trading strategies benefit from all signals mode, while position traders typically prefer bar close alerts to avoid premature position entries based on intrabar fluctuations.
The alert system generates four distinct notification types: Long Signal alerts when the trend measure crosses above the positive signal threshold, Short Signal alerts for negative threshold crossings, Bull Regime alerts when entering strong bullish conditions, and Bear Regime alerts for strong bearish regime identification.
Table Display and Information Management
The information table provides real-time statistical metrics including current trend value, regime classification, signal status, and filter effectiveness measurements. The table position can be customized for optimal screen real estate utilization, and individual metrics can be toggled based on analytical requirements.
The Language parameter supports both English and German display options for international users, while maintaining consistent calculation methodology regardless of display language selection.
Risk Management Integration
Effective risk management integration requires coordination between the trend measure signals and position sizing algorithms. Strong trend readings (above 0.5 or below -0.5) support larger position sizes due to higher probability of trend continuation, while neutral readings (between -0.2 and 0.2) suggest reduced position sizes or range-trading strategies.
The regime classification system provides additional risk management context, with Strong Bull and Strong Bear regimes supporting trend-following strategies, while Neutral regimes indicate potential for mean reversion approaches. The filter effectiveness metric helps traders assess current market conditions and adjust strategy parameters accordingly.
Timeframe Considerations and Multi-Timeframe Analysis
The indicator's effectiveness varies across different timeframes, with higher timeframes (daily, weekly) providing more reliable trend identification but slower signal generation, while lower timeframes (hourly, 15-minute) offer faster signals with increased noise levels. Multi-timeframe analysis combining trend alignment across multiple periods significantly improves signal quality and reduces false positive rates.
For optimal results, traders should consider trend alignment between the primary trading timeframe and at least one higher timeframe before entering positions. Divergences between timeframes often signal potential trend reversals or consolidation periods requiring strategy adjustment.
Conclusion
The Tzotchev Trend Measure represents a significant advancement in technical analysis methodology, combining rigorous statistical foundations with practical trading applications. Its implementation of the J.P. Morgan research methodology provides institutional-quality trend analysis capabilities previously available only to sophisticated quantitative trading firms.
The comprehensive parameter configuration options enable customization for diverse trading styles and market conditions, while the advanced noise filtering and regime detection capabilities provide superior signal quality compared to traditional trend-following indicators. Proper parameter selection and understanding of the indicator's statistical foundation are essential for achieving optimal trading results and effective risk management.
References
Abramowitz, M. and Stegun, I.A. (1964). Handbook of Mathematical Functions with Formulas, Graphs, and Mathematical Tables. Washington: National Bureau of Standards.
Ang, A. and Bekaert, G. (2002). Regime Switches in Interest Rates. Journal of Business and Economic Statistics, 20(2), 163-182.
Asness, C.S., Moskowitz, T.J., and Pedersen, L.H. (2013). Value and Momentum Everywhere. Journal of Finance, 68(3), 929-985.
Bollinger, J. (2001). Bollinger on Bollinger Bands. New York: McGraw-Hill.
Fama, E.F. and French, K.R. (1988). Permanent and Temporary Components of Stock Prices. Journal of Political Economy, 96(2), 246-273.
Hurst, B., Ooi, Y.H., and Pedersen, L.H. (2013). Demystifying Managed Futures. Journal of Investment Management, 11(3), 42-58.
Jegadeesh, N. and Titman, S. (2001). Profitability of Momentum Strategies: An Evaluation of Alternative Explanations. Journal of Finance, 56(2), 699-720.
Kaufman, P.J. (2013). Trading Systems and Methods. 5th Edition. Hoboken: John Wiley & Sons.
Moskowitz, T.J., Ooi, Y.H., and Pedersen, L.H. (2012). Time Series Momentum. Journal of Financial Economics, 104(2), 228-250.
Tzotchev, D., Lo, A.W., and Hasanhodzic, J. (2015). Designing robust trend-following system: Behind the scenes of trend-following. J.P. Morgan Quantitative Research, Asset Management Division.
Strat Failed 2-Up/2-Down Scanner v2**Strat Failed 2-Up/2-Down Scanner**
The Strat Failed 2-Up/2-Down Scanner is designed for traders using The Strat methodology, developed by Rob Smith, to identify key reversal patterns in any market and timeframe. This indicator detects two specific candlestick patterns: Failed 2-Up (bearish) and Failed 2-Down (bullish), which signal potential reversals when a directional move fails to follow through.
**What It Does**
- **Failed 2-Up**: Identifies a bearish candle where the low and high are higher than the previous candle’s low and high, but the close is below the open, indicating a failed attempt to continue an uptrend. These are marked with a red candlestick, a red downward triangle above the bar, and a table entry.
- **Failed 2-Down**: Identifies a bullish candle where the high and low are lower than the previous candle’s high and low, but the close is above the open, signaling a failed downtrend. These are marked with a green candlestick, a green upward triangle below the bar, and a table entry.
- A table in the top-right corner displays the signal type ("Failed 2-Up" or "Failed 2-Down") and the ticker symbol for quick reference.
- Alerts are provided for both patterns, making the indicator compatible with TradingView’s screener for automated scanning.
**How It Works**
The indicator analyzes each candlestick’s high, low, and close relative to the previous candle:
- Failed 2-Up: `low > low `, `high > high `, `close < open`.
- Failed 2-Down: `high < high `, `low < low `, `close > open`.
When these conditions are met, the indicator applies visual markers (colored bars and triangles) and updates the signal table. Alert conditions trigger notifications for integration with TradingView’s alert system.
**How to Use**
1. Apply the indicator to any chart (stocks, forex, crypto, etc.) on any timeframe (e.g., 1-minute, hourly, daily).
2. Monitor the chart for red (Failed 2-Up) or green (Failed 2-Down) candlesticks with corresponding triangles.
3. Check the top-right table for the latest signal and ticker.
4. Set alerts by selecting “Failed 2-Up Detected” or “Failed 2-Down Detected” in TradingView’s alert menu to receive notifications (e.g., via email or app).
5. Use the signals to identify potential reversal setups in conjunction with other Strat-based analysis, such as swing levels or time-based strategies.
**Originality**
Unlike other Strat indicators that may focus on swing levels or complex candlestick combinations, this scanner specifically targets Failed 2-Up and Failed 2-Down patterns with clear, minimalist visualizations (bars, triangles, table) and robust alert functionality. Its simplicity makes it accessible for both novice and experienced traders using The Strat methodology.
**Ideal For**
Day traders, swing traders, and scalpers looking to capitalize on reversal signals in trending or ranging markets. The indicator is versatile for any asset class and timeframe, enhancing trade decision-making with The Strat’s pattern-based approach.
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.
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.
Awesome Indicator# Moving Average Ribbon with ADR% - Complete Trading Indicator
## Overview
The **Moving Average Ribbon with ADR%** is a comprehensive technical analysis indicator that combines multiple analytical tools to provide traders with a complete picture of price trends, volatility, relative performance, and position sizing guidance. This multi-faceted indicator is designed for both swing and positional traders looking for data-driven entry and exit signals.
## Key Components
### 1. Moving Average Ribbon System
- **4 Customizable Moving Averages** with default periods: 13, 21, 55, and 189
- **Multiple MA Types**: SMA, EMA, SMMA (RMA), WMA, VWMA
- **Color-coded visualization** for easy trend identification
- **Flexible configuration** allowing users to modify periods, types, and colors
### 2. Average Daily Range Percentage (ADR%)
- Calculates the average daily volatility as a percentage
- Uses a 20-period simple moving average of (High/Low - 1) * 100
- Helps traders understand the stock's typical daily movement range
- Essential for position sizing and stop-loss placement
### 3. Volume Analysis (Up/Down Ratio)
- Analyzes volume distribution over the last 55 periods
- Calculates the ratio of volume on up days vs down days
- Provides insight into buying vs selling pressure
- Values > 1 indicate more buying volume, < 1 indicate more selling volume
### 4. Absolute Relative Strength (ARS)
- **Dual timeframe analysis** with customizable reference points
- **High ARS**: Performance relative to benchmark from a high reference point (default: Sep 27, 2024)
- **Low ARS**: Performance relative to benchmark from a low reference point (default: Apr 7, 2025)
- Uses NSE:NIFTY as default comparison symbol
- Color-coded display: Green for outperformance, Red for underperformance
### 5. Relative Performance Table
- **5 timeframes**: 1 Week, 1 Month, 3 Months, 6 Months, 1 Year
- Shows stock performance **relative to benchmark index**
- Formula: (Stock Return - Index Return) for each period
- **Color coding**:
- Lime: >5% outperformance
- Yellow: -5% to +5% relative performance
- Red: <-5% underperformance
### 6. Dynamic Position Allocation System
- **6-factor scoring system** based on price vs EMAs (21, 55, 189)
- Evaluates:
- Price above/below each EMA
- EMA alignment (21>55, 55>189, 21>189)
- **Allocation recommendations**:
- 100% allocation: Score = 6 (all bullish signals)
- 75% allocation: Score = 4
- 50% allocation: Score = 2
- 25% allocation: Score = 0
- 0% allocation: Score = -2, -4, -6 (bearish signals)
## Display Tables
### Performance Table (Top Right)
Shows relative performance vs benchmark across multiple timeframes with intuitive color coding for quick assessment.
### Metrics Table (Bottom Right)
Displays key statistics:
- **ADR%**: Average Daily Range percentage
- **U/D**: Up/Down volume ratio
- **Allocation%**: Recommended position size
- **High ARS%**: Relative strength from high reference
- **Low ARS%**: Relative strength from low reference
## How to Use This Indicator
### For Trend Analysis
1. **Moving Average Ribbon**: Look for price above ascending MAs for bullish trends
2. **MA Alignment**: Bullish when shorter MAs are above longer MAs
3. **Color coordination**: Use consistent color scheme for quick visual analysis
### For Entry/Exit Timing
1. **Performance Table**: Enter when showing consistent outperformance across timeframes
2. **Volume Analysis**: Confirm entries with U/D ratio > 1.5 for strong buying
3. **ARS Values**: Look for positive ARS readings for relative strength confirmation
### For Position Sizing
1. **Allocation System**: Use the recommended allocation percentage
2. **ADR% Consideration**: Adjust position size based on volatility
3. **Risk Management**: Lower allocation in high ADR% stocks
### For Risk Management
1. **ADR% for Stop Loss**: Set stops at 1-2x ADR% below entry
2. **Relative Performance**: Reduce positions when consistently underperforming
3. **Volume Confirmation**: Be cautious when U/D ratio deteriorates
## Best Practices
### Timeframe Recommendations
- **Intraday**: Use lower MA periods (5, 13, 21, 55)
- **Swing Trading**: Default settings work well (13, 21, 55, 189)
- **Position Trading**: Consider higher periods (21, 50, 100, 200)
### Market Conditions
- **Trending Markets**: Focus on MA alignment and relative performance
- **Sideways Markets**: Rely more on ADR% for range trading
- **Volatile Markets**: Reduce allocation percentage regardless of signals
### Customization Tips
1. Adjust reference dates for ARS calculation based on significant market events
2. Change comparison symbol to sector-specific indices for better relative analysis
3. Modify MA periods based on your trading style and market characteristics
## Technical Specifications
- **Version**: Pine Script v6
- **Overlay**: Yes (plots on price chart)
- **Real-time Updates**: Yes
- **Data Requirements**: Minimum 252 bars for complete calculations
- **Compatible Timeframes**: All standard timeframes
## Limitations
- Performance calculations require sufficient historical data
- ARS calculations depend on selected reference dates
- Volume analysis may be less reliable in low-volume stocks
- Relative performance is only as good as the chosen benchmark
This indicator is designed to provide a comprehensive analysis framework rather than simple buy/sell signals. It's recommended to use this in conjunction with your overall trading strategy and risk management rules.
