Chart Theme - Change Bar and Background Colors using HEX #sAdds aesthetic ability to charts by allowing the trader to change the color of the bars, background, and plots using HEX colors, rather than TradingView's limited color selector box. This makes for easy application of color palettes to charts. The color palettes can be saved as indicators and applied quickly, as desired.
Komut dosyalarını "chart" için ara
15-Year Seasonality ChartThis is 15 years seasonality line chat to help you make informed decision on your trading
Üç Beyaz Asker ve Üç Siyah Karga FormasyonlarıThis code is a custom indicator written for use on the TradingView platform. The code is designed to detect "Three White Soldiers" and "Three Black Crows" formations and scan stocks where these formations occur. It also displays the stocks where these formations occur in a table.
Working Logic
The code searches for Three White Soldiers and Three Black Crows formations in the specified stocks and time period.
It detects the stocks where the formations occur and displays these stocks in a table.
The table is positioned in the upper right corner of the chart and lists the stocks where the formations occur.
Usage Scenario
The user selects the stock group and time period they want to scan.
The code searches for formations in the selected stocks and displays the results it finds in a table.
The user can determine trading strategies according to the results in the table.
Customization
The code can be easily customized for different stocks and time periods.
New formations or scanning criteria can be added.
This code is a useful tool especially for traders who do technical analysis and allows automatic detection of certain formations.
BTC/Gold RatioThis Indicator displays the ratio between Bitcoin and Gold.
Grok was the writer, I, Felipe Robayo, was the prompter, tester and reporter to Grok to emit a new script, and now the publisher.
We also wrote the BTC/Gold Ratio Price Chart as well as the Gold/BTC Ratio.
You can find those as well.
Merged Dynamic Deviation & Twin Range FilterThis script integrates the Twin Range Filter and Deviation Levels, keeping all original inputs while ensuring deviation levels are plotted on the chart
RSI Swing Indicator [future bot]This Pine Script indicator is designed to identify and visualize price swings based on the Relative Strength Index (RSI). It draws swing lines and labels on the chart to highlight overbought and oversold conditions, as well as the structure of price movements (e.g., Higher Highs, Lower Lows). The indicator is useful for traders who want to track RSI-based price swings and identify potential trend reversals or continuations.
Key Features
RSI-Based Swing Detection:
The indicator uses RSI to detect overbought (above a user-defined threshold) and oversold (below a user-defined threshold) conditions.
It tracks price swings between these extremes, drawing lines and labels to visualize the swings.
Swing Lines:
Draws lines connecting oversold to overbought levels and vice versa.
Adjusts the lines dynamically as new extremes are reached.
Labels for Price Structure:
Labels are added to indicate the relationship between swings:
HH (Higher High): The current swing high is higher than the previous one.
LH (Lower High): The current swing high is lower than the previous one.
HL (Higher Low): The current swing low is higher than the previous one.
LL (Lower Low): The current swing low is lower than the previous one.
Dynamic Updates:
The indicator updates swing lines and labels in real-time as new price data comes in.
If the price moves deeper into overbought or oversold territory, the swing lines and labels adjust accordingly.
Input Parameters
RSI Source:
The price source for calculating RSI (default: close).
RSI Length:
The number of periods used to calculate RSI (default: 7).
RSI Overbought Level:
The threshold above which RSI is considered overbought (default: 70).
RSI Oversold Level:
The threshold below which RSI is considered oversold (default: 30).
How It Works
RSI Calculation:
The script calculates the RSI value based on the user-defined source and length.
State Detection:
The script tracks whether the RSI is in an overbought or oversold state.
Swing Detection:
When the RSI transitions from oversold to overbought (or vice versa), the script draws a new swing line and labels the swing.
If the price continues to move deeper into overbought or oversold territory, the swing lines and labels are updated to reflect the new extremes.
Labeling Price Structure:
The script compares the current swing high/low to the previous one and labels it as:
HH (Higher High) or LH (Lower High) for swing highs.
HL (Higher Low) or LL (Lower Low) for swing lows.
Visualization:
Swing lines are drawn between oversold and overbought levels.
Labels are placed above/below the price to indicate the swing structure.
Example Use Cases
Trend Identification:
Use the labels (HH, LH, HL, LL) to identify the overall trend structure.
For example, a series of HH and HL labels indicates an uptrend, while a series of LH and LL labels indicates a downtrend.
Reversal Signals:
Look for divergences between price and RSI swings to identify potential reversals.
For example, if the price makes a higher high (HH) but the RSI makes a lower high (LH), it could signal a bearish reversal.
Swing Trading:
Use the swing lines to identify potential entry and exit points based on RSI extreme
Long-Only For SPXThe "GOATED Long-Only" TradingView strategy, written in Pine Script v5, is designed for long-term momentum trading with a $50 initial capital. It identifies high-momentum stocks by calculating a composite momentum score across 3-month (63 days), 6-month (126 days), 9-month (189 days), and 12-month (252 days) periods, using the formula (current_price / past_price) - 1. The strategy filters stocks with annualized volatility below 0.5 (calculated as the standard deviation of daily returns, annualized by multiplying by the square root of 252 trading days) and requires momentum to exceed a customizable threshold (default 0.0). It enters long positions when momentum becomes positive and exits when it turns negative, using stop-loss (1%) and take-profit (50%) levels to manage risk. The strategy visualizes momentum and volatility on the chart, plotting entry/exit signals as green triangles (long entry) and red triangles (long exit) for backtesting and analysis.
Supertrend Strategy with Money Ocean TradeStrategy Overview
The Supertrend Strategy with Trend Change Confirmation leverages the Supertrend indicator to identify potential buy and sell signals based on changes in trend direction and subsequent price action. The strategy is designed to work with any financial instrument (symbol) and aims to provide clear entry and exit signals.
Key Components
Supertrend Indicator: The core of this strategy is the Supertrend indicator, calculated using a length of 3 and a factor of 1. The Supertrend line is plotted on the chart to visually represent trend direction.
Direction 1: Indicates an uptrend (bullish).
Direction -1: Indicates a downtrend (bearish).
Trend Change Detection: The strategy monitors changes in the trend direction. When a trend change is detected, it checks if the next candle confirms the trend change by breaking above or below the Supertrend line.
Entry Conditions:
Long Entry (Buy): When the Supertrend direction changes to 1 (uptrend) and the next candle closes above the Supertrend line.
Short Entry (Sell): When the Supertrend direction changes to -1 (downtrend) and the next candle closes below the Supertrend line.
Exit Conditions: The strategy closes the position based on the opposite signal.
Long Exit: When the Supertrend direction changes to -1 (downtrend) and the next candle closes below the Supertrend line.
Short Exit: When the Supertrend direction changes to 1 (uptrend) and the next candle closes above the Supertrend line.
Visual Signals: The strategy plots buy and sell signals on the chart using plotshape:
BUY: A green label below the bar when a long entry is triggered.
SELL: A red label above the bar when a short entry is triggered.
Alerts: Alerts are set up to notify when a buy or sell signal is triggered.
Script Summary
This strategy helps traders identify potential trading opportunities based on trend changes and confirms the trend by checking the next candle's price action. The visual signals and dashboard enhance the user's ability to monitor and manage trades effectively.
Feel free to test and adjust the parameters to suit your trading preferences! If you need further customizations or explanations, let me know.
Opposite Delta Candle Highlighter with EMAs & Delta Boxes**Description:**
This indicator is designed to enhance market analysis by highlighting **candles with opposite-colored delta**, plotting **Exponential Moving Averages (EMAs)**, and displaying **delta volume as small boxes below the chart**.
🔹 **Key Features:**
✅ **Opposite Delta Candle Highlighting** – Candles where delta volume contradicts the price direction are highlighted with a **yellow background** and a **blue triangle** above the bar.
✅ **Three Exponential Moving Averages (EMAs)** – Includes **EMA (9, 21, 50)** to help identify trends and dynamic support/resistance levels.
✅ **Delta Volume Display** – Instead of large volume columns, delta is plotted as **small square boxes below the chart**, ensuring clear visibility without overlapping price candles.
✅ **Optimized for Lower Timeframes** – The indicator **automatically selects an appropriate lower timeframe** for more precise delta calculations.
🔹 **How It Works:**
- **Green Candle + Red Delta** → Opposite delta signal (Bearish Sign).
- **Red Candle + Green Delta** → Opposite delta signal (Bullish Sign).
- **Delta bars below the chart** indicate the strength of buying/selling pressure.
- **EMAs help identify the market trend** and potential trade entry zones.
🔹 **Use Cases:**
✔ **Scalping & Day Trading** – Identify potential reversals and trend continuation setups.
✔ **Volume Analysis** – Understand market participation and possible absorption.
✔ **Trend Confirmation** – Use EMAs to confirm trend direction alongside delta volume.
📌 *Best used with lower timeframes (1m, 5m, 15m) for detailed volume analysis.*
🚀 **Enhance your trading with real-time delta insights and price action analysis!**
Bars pattern MLThis script implements a K-Nearest Neighbors (KNN)-based machine learning model to predict future price movements in financial markets. It analyzes past price action using Euclidean distance and selects the most similar historical patterns to estimate future price changes. Unlike traditional KNN implementations, this approach optimizes distance calculations by maintaining a dynamically updated list of the closest neighbors, ensuring efficient selection without the need for sorting. The model generates a forecasted price trajectory based on incremental predictions, which are visualized on the chart using polylines for better interpretability.
DCA Price LevelsThe indicator is used to set price targets in the chart on the basis of waste.
Whenever the price falls from the current DCA price to minus 30 percent, a new price target is set.
There are a total of 10 price targets, so a drop of up to minus 71 percent is covered by the default setting.
The number of price targets can be set individually, up to a maximum of 10, and the percentages can also be changed.
Forward Curve Visualization ToolProvide the spot symbol and the futures product root, and the script automatically scans all relevant contracts for you—no more tedious manual searches. The result is a clean, intuitive chart showing the live forward curve in real time.
It also detects contango or backwardation conditions (based on spot < F1 < F2 < F3).
Future Features:
Plot historical snapshots of the curve (1 day, 1 week, or 1 month ago) to understand market trends over time.
Display additional metrics such as annualized basis, cost of carry (CoC), and even volume or open interest for deeper insights.
If you trade futures and watch the forward curve, this script will give you the actionable data you need and get more ideas or features you’d like to see. Let’s build them together!
Disclaimer
Please remember that past performance may not be indicative of future results.
Due to various factors, including changing market conditions, the strategy may no longer perform as well as in historical backtesting.
This post and the script don’t provide any financial advice.
NFP High/Low LevelsThis indicator plots high and low levels with horizontal lines for the last 12 NFP Days
NFP Days are input in the indicator settings
Labels are placed according to the Month and if it is a High or Low price for the NFP Day
Price tracking on each NFP day starts 30 min before market open until market close (0830-1559 EST)
NFP hours are marked at the bottom of the chart to verify the NFP session visually, adjustable in settings
Works for 1H and below timeframes and on Futures
Here is an example of the indicator on NQ1! chart
Turtle Soup Model [PhenLabs]📊 Turtle Soup Model
Version: PineScript™ v6
Description
The Turtle Soup Model is an innovative technical analysis tool that combines market structure analysis with inter-market comparison and gap detection. Unlike traditional structure indicators, it validates market movements against a comparison symbol (default: ES1!) to identify high-probability trading opportunities. The indicator features a unique “soup pattern” detection system, comprehensive gap analysis, and real-time structure breaks visualization.
Innovation Points:
First indicator to combine structure analysis with gap detection and inter-market validation
Advanced memory management system for efficient long-term analysis
Sophisticated pattern recognition with multi-market confirmation
Real-time structure break detection with comparative validation
🔧 Core Components
Structure Analysis: Advanced pivot detection with inter-market validation
Gap Detection: Sophisticated gap identification and classification system
Inversion Patterns: “Soup pattern” recognition for reversal opportunities
Visual System: Dynamic rendering of structure levels and gaps
Alert Framework: Multi-condition notification system
🚨 Key Features 🚨
The indicator provides comprehensive analysis through:
Structure Levels: Validated support and resistance zones
Gap Patterns: Identification of significant market gaps
Inversion Signals: Detection of potential reversal points
Real-time Comparison: Continuous inter-market analysis
Visual Alerts: Dynamic structure break notifications
📈 Visualization
Structure Lines: Color-coded for highs and lows
Gap Boxes: Visual representation of gap zones
Inversion Patterns: Clear marking of potential reversal points
Comparison Overlay: Inter-market divergence visualization
Alert Indicators: Visual signals for structure breaks
💡Example
📌 Usage Guidelines
The indicator offers multiple customization options:
Structure Settings:
Pivot Period: Adjustable for different market conditions
Comparison Symbol: Customizable reference market
Visual Style: Configurable colors and line widths
Gap Analysis:
Signal Mode: Choice between close and wick-based signals
Box Rendering: Automatic gap zone visualization
Middle Line: Reference point for gap measurements
✅ Best Practices:
🚨Use comparison symbol from related market🚨
Monitor both structure breaks and gap inversions
Combine signals for higher probability trades
Pay attention to inter-market divergences
⚠️ Limitations
Requires comparison symbol data
Performance depends on market correlation
Best suited for liquid markets
What Makes This Unique
Inter-market Validation: Uses comparison symbol for signal confirmation
Gap Integration: Combines structure and gap analysis
Soup Pattern Detection: Identifies specific reversal patterns
Dynamic Structure Management: Automatically updates and removes invalid levels
Memory-Efficient Design: Optimized for long-term chart analysis
🔧 How It Works
The indicator processes market data through three main components:
1. Structure Analysis:
Detects pivot points with comparison validation
Tracks structure levels with array management
Identifies and processes structure breaks
2. Gap Analysis:
Identifies significant market gaps
Processes gap inversions
Manages gap zones visualization
3. Pattern Recognition:
Detects “soup” patterns
Validates with comparison market
Generates structure break signals
💡 Note: The indicator performs best when used with correlated comparison symbols and appropriate timeframe selection. Its unique inter-market validation system provides additional confirmation for traditional structure-based trading strategies.
3-1 Setup Detector (Multi-Timeframe)📌 3-1 Setup Detector (Multi-Timeframe) – Description
The 3-1 Setup Detector (Multi-Timeframe) is a powerful price action indicator designed for The Strat trading method. It automatically detects 3-1 setups, where an outside bar (3) is followed by an inside bar (1), signaling potential breakout opportunities.
🔥 Key Features:
✅ Multi-Timeframe Support – Works on 1H, 2H, 3H, 4H, 6H, 12H, Daily, 2D, 3D, Weekly, 2W, 3W, Monthly, Quarterly
✅ Real-Time Alerts – Get notified when a 3-1 setup forms
✅ Easy Visualization – Plots markers on the chart for quick recognition
✅ Customizable Timeframe – Select a specific higher timeframe for confirmation
📊 How It Works:
Identifies an outside bar (3), where the high is higher and the low is lower than the previous bar.
Detects an inside bar (1), where the high is lower and the low is higher than the previous bar.
If a 3-1 sequence occurs, the indicator marks the setup on the chart and triggers an alert.
🎯 Trading Applications:
Breakout Strategy: Trade breakouts when the 3-1 setup forms near key levels.
Reversal Signals: Use in combination with support/resistance for confirmation.
Multi-Timeframe Analysis: Detect setups on higher timeframes while trading lower ones.
🚀 Perfect for traders who use The Strat method and want real-time, high-probability trade setups across multiple timeframes!
Month of Year Performance█ OVERVIEW
The Month of Year Performance indicator is designed to visualize and compare the cumulative percentage change for each month of the year. By aggregating monthly returns, it helps uncover seasonal trends and potential anomalies in financial markets.
In financial analysis, a calendar based anomaly refers to recurring patterns or tendencies associated with specific time periods, such as days of the week. By calculating the cumulative percentage change for each month (January through December) and displaying the results both graphically and in a summary table, this indicator helps identify whether certain months
consistently outperform others.
█ FEATURES
Customisable time window via Time Settings.
Calculates cumulative percentage change for each month (January to December) separately.
Built-in error check to ensure the indicator is applied on a Monthly timeframe.
Distinct visual representation for each month using unique colours.
Customisable table settings including location and font size.
Displays a performance summary table with metrics such as performance, average return, % positive, and count.
█ HOW TO USE
Add the indicator to a chart set to a Monthly timeframe.
Select your desired Start Time and End Time in the Time Settings.
Toggle the performance table on or off in the Table Settings.
Adjust the table’s location and font size as needed.
View the cumulative monthly performance plotted in distinct colours.
Colour Scheme:
January: Blue
February: Red
March: Green
April: Orange
May: Purple
June: Fuchsia
July: Teal
August: Yellow
September: Navy
October: Lime
November: Maroon
December: Aqua
Day of Week Performance█ OVERVIEW
The Day of Week Performance indicator is designed to visualise and compare the cumulative percentage change for each day of the week. This indicator explores one of the many calendar based anomalies in financial markets.
In financial analysis, a calendar based anomaly refers to recurring patterns or tendencies associated with specific time periods, such as days of the week. By calculating the cumulative percentage change for each day (Monday through Friday) and displaying the results both graphically and in a summary table, this indicator helps identify whether certain days consistently outperform others.
█ FEATURES
Customisable time window via Time Settings.
Calculates cumulative percentage change for each day (Monday to Friday) separately.
Option to use Sunday instead of Friday for CFDs and Futures analysis.
Distinct visual representation for each day using unique colours.
Customisable table settings including position and font size.
Built-in error checks to ensure the indicator is applied on a Daily timeframe.
█ HOW TO USE
Add the indicator to a chart set to a Daily timeframe.
Select your desired Start Time and End Time in the Time Settings.
Toggle the performance table on or off in the Table Settings.
Adjust the table’s location and font size as needed.
Use the "Use Sunday instead of Friday" option if your market requires it.
View the cumulative performance plotted in distinct colours.
Colour Scheme:
Monday: Blue
Tuesday: Red
Wednesday: Green
Thursday: Orange
Friday: Purple
Quarterly Performance█ OVERVIEW
The Quarterly Performance indicator is designed to visualise and compare the performance of different Quarters of the year. This indicator explores one of the many calendar based anomalies that exist in financial markets.
In the context of financial analysis, a calendar based anomaly refers to patterns or tendencies that are linked to specific time periods, such as days of the week, weeks of the month, or months of the year. This indicator helps explore whether such a calendar based anomaly exists between quarters.
By calculating cumulative quarterly performance and counting the number of quarters with positive returns, it provides a clear snapshot of whether one set of quarters tends to outperform the others, potentially highlighting a calendar based anomaly if a significant difference is observed.
█ FEATURES
Customisable time window through input settings.
Tracks cumulative returns for each quarter separately.
Easily adjust table settings like position and font size via input options.
Clear visual distinction between quarterly performance using different colours.
Built-in error checks to ensure the indicator is applied to the correct timeframe.
█ HOW TO USE
Add the indicator to a chart with a 3 Month (Quarterly) timeframe.
Choose your start and end dates in the Time Settings.
Enable or disable the performance table in the Table Settings as needed.
View the cumulative performance, with Q1 in blue, Q2 in red, Q3 in green and Q4 in purple.
Even vs Odd Days Performance█ OVERVIEW
The Even vs Odd Days Performance indicator is designed to visualise and compare the performance of even-numbered days versus odd-numbered days. This indicator explores one of the many calendar based anomalies that exist in financial markets.
In the context of financial analysis, a calendar based anomaly refers to patterns or tendencies that are linked to specific time periods, such as days of the week, weeks of the month, or months of the year. This indicator helps explore whether such a calendar based anomaly exists between even and odd days.
By calculating cumulative daily performance and counting the number of days with positive returns, it provides a clear snapshot of whether one set of days tends to outperform the other, potentially highlighting a calendar based anomaly if a significant difference is observed.
█ FEATURES
Customisable time window through input settings.
Tracks cumulative returns for even and odd days separately.
Easily adjust table settings like position and font size via input options.
Clear visual distinction between even and odd day performance using different colours.
Built-in error checks to ensure the indicator is applied to the correct timeframe.
█ HOW TO USE
Add the indicator to a chart with a Daily timeframe.
Choose your start and end dates in the Time Settings.
Enable or disable the performance table in the Table Settings as needed.
View the cumulative performance, with even days in green and odd days in red.
Even vs Odd Weeks Performance█ OVERVIEW
The Even vs Odd Weeks Performance indicator is designed to visualise and compare the performance of even-numbered weeks versus odd-numbered weeks. This indicator explores one of the many calendar based anomalies that exist in financial markets.
In the context of financial analysis, a calendar based anomaly refers to patterns or tendencies that are linked to specific time periods, such as days of the week, weeks of the month, or months of the year. This indicator helps explore whether such a calendar based anomaly exists between even and odd weeks.
By calculating cumulative weekly performance and counting the number of weeks with positive returns, it provides a clear snapshot of whether one set of weeks tends to outperform the other, potentially highlighting a calendar based anomaly if a significant difference is observed.
█ FEATURES
Customisable time window through input settings.
Tracks cumulative returns for even and odd weeks separately.
Easily adjust table settings like position and font size via input options.
Clear visual distinction between even and odd week performance using different colours.
Built-in error checks to ensure the indicator is applied to the correct timeframe.
█ HOW TO USE
Add the indicator to a chart with a Weekly timeframe.
Choose your start and end dates in the Time Settings.
Enable or disable the performance table in the Table Settings as needed.
View the cumulative performance, with even weeks in green and odd weeks in red.
CCI Buy and Sell Signals with 20/30 EMACCI Buy and Sell Signals with EMA and ATR Stop Loss/Take Profit
This indicator is designed to identify buy and sell signals based on a combination of the Commodity Channel Index (CCI) and Exponential Moving Averages (EMA). It also includes an optional ATR-based stop loss and take profit system, which is useful for traders who want to manage their trades with dynamic risk levels.
Features:
CCI Buy and Sell Signals:
Buy Signal: A buy signal is triggered when the CCI crosses up through -100 (from an oversold condition), the 20-period EMA is above the 30-period EMA, and the price is above the 200-period EMA. This suggests that the market is entering an upward trend.
Sell Signal: A sell signal is triggered when the CCI crosses down through +100 (from an overbought condition), the 20-period EMA is below the 30-period EMA, and the price is below the 200-period EMA. This suggests that the market is entering a downward trend.
Exponential Moving Averages (EMA):
The script plots three EMAs:
20-period EMA (Green): Used to identify short-term trends.
30-period EMA (Red): Used to capture medium-term trends.
200-period EMA (Orange): A long-term trend filter, with the price above it generally indicating bullish conditions and below it indicating bearish conditions.
ATR-Based Stop Loss and Take Profit:
Optional Feature: The ATR (Average True Range) indicator can be used to set stop loss and take profit levels based on market volatility.
Stop Loss: Set at a multiple of the ATR below the entry price for long positions and above the entry price for short positions.
Take Profit: Set at a multiple of the ATR above the entry price for long positions and below the entry price for short positions.
Customizable: You can adjust the ATR length, Stop Loss Multiplier, and Take Profit Multiplier through the settings.
Dots: The stop loss and take profit levels are plotted as dots on the chart when the ATR feature is enabled.
Alert Conditions:
Buy Signal Alert: Triggered when a buy signal occurs based on CCI crossing up -100 and other conditions being met.
Sell Signal Alert: Triggered when a sell signal occurs based on CCI crossing down +100 and other conditions being met.
Any Signal Alert: This is a combined alert that triggers for either a buy or sell signal. It helps you stay updated on both types of signals simultaneously.
How to Use:
The indicator will plot buy and sell arrows on the chart, giving clear entry points for trades based on CCI and EMA conditions.
The ATR stop loss and take profit dots (when enabled) provide automatic risk management levels, adjusting dynamically with market volatility.
Traders can customize the ATR settings to fine-tune their stop loss and take profit levels, making this strategy adaptable to different trading styles and market conditions.
Support and Resistancelookback: This input allows you to specify the number of bars to look back to calculate the support and resistance levels.
support: This is calculated as the lowest low over the specified lookback period.
resistance: This is calculated as the highest high over the specified lookback period.
plot: The support and resistance levels are plotted on the chart with different colors.
bgcolor: This optional feature highlights the support and resistance zones with a semi-transparent background color.
Overnight vs Intra-day Performance█ STRATEGY OVERVIEW
The "Overnight vs Intra-day Performance" indicator quantifies price behaviour differences between trading hours and overnight periods. It calculates cumulative returns, compound growth rates, and visualizes performance components across user-defined time windows. Designed for analytical use, it helps identify whether returns are primarily generated during market hours or overnight sessions.
█ USAGE
Use this indicator on Stocks and ETFs to visualise and compare intra-day vs overnight performance
█ KEY FEATURES
Return Segmentation : Separates total returns into overnight (close-to-open) and intraday (open-to-close) components
Growth Tracking : Shows simple cumulative returns and compound annual growth rates (CAGR)
█ VISUALIZATION SYSTEM
1. Time-Series
Overnight Returns (Red)
Intraday Returns (Blue)
Total Returns (White)
2. Summary Table
Displays CAGR
3. Price Chart Labels
Floating annotations showing absolute returns and CAGR
Color-coded to match plot series
█ PURPOSE
Quantify market behaviour disparities between active trading sessions and overnight positioning
Provide institutional-grade attribution analysis for returns generation
Enable tactical adjustment of trading schedules based on historical performance patterns
Serve as foundational research for session-specific trading strategies
█ IDEAL USERS
1. Portfolio Managers
Analyse overnight risk exposure across holdings
Optimize execution timing based on return distributions
2. Quantitative Researchers
Study market microstructure through time-segmented returns
Develop alpha models leveraging session-specific anomalies
3. Market Microstructure Analysts
Identify liquidity patterns in overnight vs daytime sessions
Research ETF premium/discount mechanics
4. Day Traders
Align trading hours with highest probability return windows
Avoid overnight gaps through informed position sizing