Advanced VWAP CalendarThe Advanced VWAP Calendar is a designed to plot Volume Weighted Average Price (VWAP) lines anchored to user-defined and preset time periods, including weekly, monthly, quarterly, and custom anchors. As of August 15, 2025, this indicator provides traders with a robust tool for analyzing price trends relative to volume-weighted averages, with clear labeling and extensive customization options. Below is a summary of its key features and functionality, with technical details and code references updated to focus on user-facing behavior and presentation, while preserving all other aspects of the original summary.
Key Features
Multiple Time Period VWAPs:
Weekly VWAPs: Supports up to five VWAPs for a user-selected month and year, starting at midnight each Monday (e.g., W1 Aug 2025, W2 Aug 2025). Enabled via a single toggle, with anchors automatically set to the first Monday of the chosen month.
Monthly VWAPs: Plots VWAPs for all 12 months of a selected year (e.g., Jan 2025, Feb 2025) or a single user-specified month/year. Labels use month abbreviations (e.g., "Aug 2025").
Quarterly VWAPs: Covers four quarters of a selected year (e.g., Q1 2025, Q2 2025), with options to enable all quarters or individual ones (Q1–Q4).
Legacy VWAPs: Provides monthly and quarterly VWAPs for a user-selected legacy year (e.g., 2024), labeled with a "Legacy" prefix (e.g., "Legacy Jan 2024," "Legacy Q1 2024"), with similar enablement options.
Custom VWAPs: Includes 10 fully customizable VWAPs, each with user-defined anchor times, labels (e.g., "Q1 2025"), colors, line widths (1–5), text colors, bubble styles, text sizes (8–40), and background options.
Clear and Dynamic Labeling:
Labels appear to the right of the chart, showing the VWAP value (e.g., "Q1 2025 123.45").
Weekly labels follow a "W# Month Year" format (e.g., "W1 Aug 2025").
Monthly labels use abbreviated months (e.g., "Aug 2025"), while quarterly labels use "Q# Year" (e.g., "Q3 2025").
Legacy labels include a "Legacy" prefix (e.g., "Legacy Q1 2024").
Labels support customizable text sizes (tiny to huge) and can be displayed with or without a background, with optional bubble styles.
Flexible Customization:
Each VWAP can be enabled or disabled independently, with user inputs for anchor times, labels, and visual properties.
Colors are predefined for weekly (red, orange, blue, green, purple), monthly (varied), quarterly (red, blue, green, yellow), and legacy VWAPs, but custom VWAPs allow any color selection.
Line widths and text sizes are adjustable, ensuring visual clarity and chart readability.
This indicator was a dual effort, code was heavily contributed in effort by AzDxB, major credit and THANKS goes to him www.tradingview.com
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FVG + Bank Level Targeting w/ Alert TriggerDescription:
FVG + Bank Level Targeting w/ Alert Trigger is an intraday trading tool that combines Fair Value Gap (FVG) detection with dynamic institutional targeting using prior-day, weekly, and monthly high/low "Bank Levels." When a Fair Value Gap is detected, the script projects a logical target using the closest bank level in price's direction, and visually extends that level on your chart.
This tool is designed to help traders anticipate where price is most likely to move after an FVG appears — and alert them when price breaks through key target zones.
How It Works:
* Bank Level Calculation:
The indicator calculates Daily, Weekly, and Monthly high and low levels from the previous bar of each respective timeframe.
These are optionally plotted on the chart with a slight tick offset to avoid overlap with price.
* FVG Detection:
Bullish FVGs are defined by a gap between the low of the current candle and the high two candles prior, with a confirming middle candle.
Bearish FVGs follow the reverse pattern.
Once detected, the script finds the nearest unbroken institutional level (Bank Level) in the direction of the FVG and anchors a target line at that price level.
* Target Line Projection:
The script draws a persistent horizontal line (not just a plotted value) at the selected bank level.
These lines automatically extend a set number of bars into the future for clarity and trade planning.
* Breakout Detection:
When price crosses above a Bull Target or below a Bear Target, the script triggers a breakout condition.
These breakouts are useful for trade continuation or reversal setups.
* Alerts:
Built-in alert conditions notify you in real time when price crosses above or below a target.
These can be used to set TradingView alerts for your preferred Futures symbols or intraday pairs.
Parameters:
Tick Offset Multiplier: Adds distance between price and plotted levels.
Show Daily/Weekly/Monthly Levels: Toggle for each institutional level group.
FVG Extend Right (bars): Controls how far the target lines extend into the future.
Color Controls: Customize colors for FVG fill and target lines.
Use Case:
This indicator is designed for traders who want to:
Trade continuation or reversal moves around institutional price zones
Integrate Fair Value Gap concepts with more logical, historically anchored price targets
Trigger alerts when market structure evolves around key levels
It is especially useful for intraday Futures traders on the 15-minute chart or lower, but adapts well to any instrument with strong reactionary behavior at prior session highs/lows.
Linh Index Trend & Exhaustion SuitePurpose: One overlay to judge trend, reversal risk, overextension, and volatility squeezes on indexes (built for VNINDEX/VN30, works on any symbol & timeframe).
What it shows
Trend state: Bull / Bear / Transition via 20/50/200 EMAs + slope check.
Overextension heatmap: Background paints when price is stretched vs the 20-EMA by ATR or % (you set the thresholds).
Squeeze detection:
Squeeze ON (yellow dot): Bollinger Bands (20,2) inside Keltner Channels (20,1.5).
Squeeze OFF + Release: White dot; script confirms direction only when close > BB upper (up) or close < BB lower (down).
52-week context: Distance to 52-week high/low (%).
Higher-TF alignment: Optional weekly trend reading shown on the label while you’re on the daily.
Anchored VWAP(s): Two optional AVWAPs from dates you choose (e.g., YTD open, last big gap/earnings).
Plots & labels
EMAs 20/50/200 (toggle on/off).
Optional BB & KC bands for diagnostics.
AVWAP #1 / #2 (optional).
Status label with: Trend, EMAs, Dist to 20-EMA (%, ATR), 52-week distances, HTF state.
Built-in alerts (set “Once per bar close”)
EMA10 ↔ EMA20 cross (early momentum shift)
EMA20 ↔ EMA50 cross (trend confirmation/negation)
Price ↔ EMA200 cross (long-term regime)
Squeeze Release UP / DOWN (BB breakout after squeeze)
Overextension Cool-off UP / DN (stretched vs 20-EMA + momentum rolling)
Near 52-week High (within your % threshold)
How to use (playbook)
Map regime: Prefer trades when Daily = Bull and HTF (Weekly) = Bull (shown on label).
Hunt expansion: Yellow → White dot and close beyond BB = fresh move.
Avoid chasing stretch: If background is painted (overextended vs 20-EMA), wait for a pullback or intraday base.
Locations matter: 52-week proximity + HTF Bull improves breakout quality.
Anchors: Add AVWAP from YTD open or last major gap to frame support/resistance.
Suggested settings
Overextension: ATR = 2.0, % = 4.0 to start; tune per index volatility.
Squeeze bands: BB(20,2) & KC(20,1.5) default are balanced; tighten KC (1.3) for more signals, widen (1.8) for fewer/higher quality.
Timeframes: Daily for signals, Weekly for bias. Optional 65-min for entries.
Global Bond Yields Monitor [MarktQuant]Global Bond Yields Monitor
The Global Bond Yields Monitor is designed to help users track and compare government bond yields across major economies. It provides an at-a-glance view of short- and long-term interest rates for multiple countries, enabling users to observe shifts in global fixed-income markets.
Key Features:
Multi-Country Coverage: Includes major advanced and emerging economies such as the United States, China, Japan, Germany, United Kingdom, Canada, Australia, and more.
Multiple Maturities: Displays yields for the 2-year, 5-year, 10-year, and 30-year maturities (20-year for Russia).
Dynamic Yield Data: Plots real-time yields for the selected country directly from TradingView’s data sources.
Weekly Change Tracking: Calculates and displays the yield change from one week ago ( ) for each maturity.
Table Visualization: Option to display a compact data table showing current yields and weekly changes, color-coded for easier interpretation.
Visual Yield Curve Comparison: Plots yield lines for short- and long-term maturities, with shaded areas between curves for visual clarity.
Customizable Display: Choose table placement and whether to show or hide the weekly change table.
Use Cases
This script is intended for analysts, traders, and investors who want to monitor shifts in sovereign bond markets. Changes in yields can reflect adjustments in monetary policy expectations, inflation outlook, or broader macroeconomic trends.
❗Important Note❗
This indicator is for market monitoring and educational purposes only. It does not generate trading signals, and it should not be interpreted as financial advice. All data is sourced from TradingView’s available market feeds, and accuracy may depend on the source data.
cd_HTF_bias_CxOverview:
No matter our trading style or model, to increase our success rate, we must move in the direction of the trend and align with the Higher Time Frame (HTF). Trading "gurus" call this the HTF bias. While we small fish tend to swim in all directions, the smart way is to flow with the big wave and the current. This indicator is designed to help us anticipate that major wave.
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Details and Usage:
This indicator observes HTF price action across preferably seven different pairs, following specific rules. It confirms potential directional moves using CISD levels on a Medium Time Frame (MTF). In short, it forecasts the likely direction (HTF bias). The user can then search for trade opportunities aligned with this bias on a Lower Time Frame (LTF), using their preferred pair, entry model, and style.
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Timeframe Alignment:
The commonly accepted LTF/MTF/HTF combinations include:
• 1m – 15m – H4
• 3m – H1 – Daily / 3m – 30m – Daily
• 5m – H1 – Daily
• 15m – H4 – Weekly
• H1 – Daily – Monthly
• H4 – Weekly – Quarterly
Example: If you're trading with a 3m model on a 30m/3m setup, you should seek trades in the direction of the H1/Daily bias.
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How It Works:
The indicator first looks for sweeps on the selected HTF — when any of the last four candles are swept, the first condition is met.
The second step is confirmation with a CISD close on the MTF — once a candle closes above/below the CISD level, the second condition is fulfilled. This suggests the price has made its directional decision.
Example: If a previous HTF candle is swept and we receive a bearish CISD confirmation on H1, the HTF bias becomes bearish.
After this, you may switch to a more granular setup like HTF: 30m and MTF: 3m to look for trade entries aligned with the bias (e.g., 30m sweep + 3m CISD).
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How Is Bias Determined?
• HTF Sweep + MTF CISD = SC (Sweep & CISD)
• Latest Bullish SC → Bias: Bullish
• Latest Bearish SC → Bias: Bearish
• Price closes above the last Bearish SC → Bias: Strong Bullish
• Price closes below the last Bullish SC → Bias: Strong Bearish
• Strong Bullish bias + Bearish CISD (without HTF sweep) → Bias: Bullish
• Strong Bearish bias + Bullish CISD (without HTF sweep) → Bias: Bearish
• Bearish price violates SC high, but Bullish SC is untouched → Bias: Bullish
• Bullish price violates SC low, but Bearish SC is untouched → Bias: Bearish
• If neither side generates SC → Bias: No Bias
The logic is built on the idea that a price overcoming resistance is stronger, and encountering resistance is weaker. This model is based on the well-known “Daily Bias” structure, but with personal refinements.
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What’s on the Screen?
• Classic HTF zones (boxes)
• Potential MTF CISD levels
• Confirmed MTF lines
• Sweep zones when HTF sweeps occur
• Result table showing current bias status
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Usage:
• Select HTF and MTF timeframes aligned with your trading timeframe.
• Adjust color and position settings as needed.
• Enter up to seven pairs to track via the menu.
• Use the checkbox next to each pair to enable/disable them.
• If “Ignore these assets” is checked, all pairs will be disabled, and only the currently open chart pair will be tracked.
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Alerts:
You can choose alerts for Bullish, Bearish, Strong Bullish, or Strong Bearish conditions.
There are two types of alert sources:
1. From the indicator’s internal list
2. From TradingView’s watchlist
Visual example:
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How I Use It:
• For spot trades, I use HTF: Weekly and MTF: H4 and look for Bullish or Strong Bullish pairs.
• For scalping, I follow bias from HTF: Daily and MTF: H1.
Example: If the indicator shows a Bearish HTF Bias, I switch to HTF: 30m and MTF: 3m and enter trades once bearish conditions are met (timeframe alignment).
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Important Notes:
• The indicator defines CISD levels only at HTF high and low levels.
• If your chart is on a higher timeframe than your selected HTF/MTF, no data will appear.
Example: If HTF = H1 and MTF = 5m, opening a chart on H4 will result in a blank screen.
• The drawn CISD level on screen is the MTF CISD level.
• Not every alert should be traded. Always confirm with personal experience and visual validation.
• Receiving multiple Strong Bullish/Bearish alerts is intentional. (Trick 😊)
• Please share your feedback and suggestions!
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And Most Importantly:
Don't leave street animals without water and food!
Happy trading!
Portfolio Tracker ARJO (V-01)Portfolio Tracker ARJO (V-01)
This indicator is a user-friendly portfolio tracking tool designed for TradingView charts. It overlays a customizable table on your chart to monitor up to 15 stocks or symbols in your portfolio. It calculates real-time metrics like current market price (CMP), gains/losses, and stoploss breaches, helping you stay on top of your investments without switching between multiple charts. The table uses color-coding for quick visual insights: green for profits, red for losses, and highlights breached stoplosses in red for alerts. It also shows portfolio-wide totals for overall performance.
Key Features
Supports up to 15 Symbols: Enter stock tickers (e.g., NSE:RELIANCE or BSE:TCS) with details like buy price, date, units, and stoploss.
Symbol: The stock ticker and description.
Buy Date: When you purchased it.
Units: Number of shares/units held.
Buy Price: Your entry price.
Stop Loss: Your set stoploss level (highlighted in red if breached by CMP).
CMP: Current market price (fetched from the chart's timeframe).
% Gain/Loss: Percentage change from buy price (color-coded: green for positive, red for negative).
Gain/Loss: Total monetary gain/loss based on units.
Optional Timeframe Columns: Toggle to show % change over 1 Week (1W), 1 Month (1M), 3 Months (3M), and 6 Months (6M) for historical performance.
Portfolio Summary: At the top of the table, see total % gain/loss and absolute gain/loss for your entire portfolio.
Visual Customizations: Adjust table position (e.g., Top Right), size, colors for positive/negative values, and intensity cutoff for gradients.
Benchmark Index-Based Header: The title row's background color reflects NIFTY's weekly trend (green if above 10-week SMA, red if below) for market context.
Benchmark Index-Based Header: The title row's background color reflects NIFTY's weekly trend (green if above 10-week SMA, red if below) for market context.
How to Use It: Step-by-Step Guide
Add the Indicator to Your Chart: Search for "Portfolio Tracker ARJO (V-01)" in TradingView's indicator library and add it to any chart (preferably Daily timeframe for accuracy).
Input Your Portfolio Symbols:
Open the indicator settings (gear icon).
In the "Symbol 1" to "Symbol 15" groups, fill in:
Symbol: Enter the ticker (e.g., NSE:INFY).
Year/Month/Day: Select your buy date (e.g., 2024-07-01).
Buy Price: Your purchase price per unit.
Stoploss: Your exit price if things go south.
Units: How many shares you own.
Only fill what you need—leave extras blank. The table auto-adjusts to show only entered symbols.
Customize the Table (Optional):
In "Table settings":
Choose position (e.g., Top Right) and size (% of chart).
Toggle "Show Timeframe Columns" to add 1W/1M/3M/6M performance.
In "Color settings":
Pick colors for positive (green) and negative (red) cells.
Set "Color intensity cutoff (%)" to control how strong the colors get (e.g., 10% means changes above 10% max out the color).
Interpret the Table on Your Chart:
The table appears overlaid—scan rows for each symbol's stats.
Look at colors: Greener = better gains; redder = bigger losses.
Check CMP cell: Red means stoploss breached—consider selling!
Portfolio Gain/Loss at the top gives a quick overall health check.
For Best Results:
Use on a Daily chart to avoid CMP errors (the script will warn if on Weekly/Monthly).
Refresh the chart or wait for a new bar if data doesn't update immediately.
For Indian stocks, prefix with NSE: or BSE: (e.g., BSE:RELIANCE).
This is for tracking only—not trading signals. Combine with your strategy.
If no symbols show, ensure inputs are valid (e.g., buy price > 0, valid date).
Finally, this tool makes it quite easy for beginners to track their portfolios, while also giving advanced traders powerful and customizable insights. I'd love to hear your feedback—happy trading!
Super MTF Clouds (4x3 Pairs)Overview:
This script is based on Ripster's MTF clouds, which transcends the standard moving average cloud indicator by offering a powerful and deeply customizable Multi-Timeframe (MTF) analysis. Instead of being limited to the moving averages of your current charts from the current timeframe, this tool allows you to project and visualize the trend and key support/resistance zones from up to 4 different timeframes simultaneously. User can input up to 6 different EMA values which will form 3 pairs of EMA clouds, for each of the timeframes.
The primary purpose is to provide traders with immediate confluence. By observing how price interacts with moving average clouds from higher timeframes (e.g., Hourly, Daily, Weekly), you can make more informed decisions on your active trading timeframe (e.g., 10 Minute). It's designed as a complete MTF Cloud toolkit, allowing you to display all necessary MTFs in a single script to build a comprehensive view of the market structure without having to flick to different timeframe to look for cloud positions.
Key features:
Four Independent Multi-Timeframe Slots: Each slot can be assigned any timeframe available on TradingView (e.g., D, W, M, 4H).
Three MA Pairs Per Timeframe: For each timeframe, configure up to three separate MA clouds (e.g., a 9/12 EMA pair, a 20/50 EMA pair, and a 100/200 SMA pair).
Complete Customisation: For every single moving average (24 in total), you can independently control:
MA Type: Choose between EMA or SMA.
Length: Any period you require.
Line Color: Full colour selection.
Line Thickness: Adjust the visual weight of each line.
Cloud Control: For every pair (12 in total), you can set the fill colour and transparency.
How To Use This Script:
This tool is best used for confirmation and context. Here are some practical strategies that one can adopt:
Trend Confluence: Before taking a trade based on a signal on your current timeframe, glance at the higher timeframe clouds. If you see a buy signal on the 15-minute chart and the price is currently trading above a thick, bullish Daily cloud, the probability of that trade succeeding is significantly higher. Conversely, shorting into strong HTF support is a low-probability trade.
Dynamic Support & Resistance: The edges of the higher timeframe clouds often act as powerful, dynamic levels of support and resistance. A pullback to the 4-Hour 50 EMA on your 15-minute chart can be a prime area to look for entries in the direction of the larger trend.
Gauging Market Regimes: Use the toggles in the settings to quickly switch between different views. You can have a "risk-on" view with short-term clouds and a "macro" view with weekly and monthly clouds. This helps you adapt your trading style to the current market conditions.
Key Settings:
1. Global Setting
Source For All MAs: This determines the price data point used for every single moving average calculation.
Default: hl2 (an average of the High and Low of each bar). This gives a smooth midpoint price.
Options: You can change this to Close (the most common method), Open, High, Low, or ohlc4 (an average of the open, high, low, and close), among others.
Recommendation: For most standard trend analysis, the default hl2 is the common choice.
2. The Timeframe Group Structure
The rest of the settings are organized into four identical, collapsible groups: "Timeframe 1 Settings" through "Timeframe 4 Settings". Each group acts as a self-contained control panel for one multi-timeframe view.
Within each timeframe group, you have two master controls:
Enable Timeframe: This is the main power switch for the entire group. Uncheck this box to instantly hide all three clouds and lines associated with this timeframe. This is perfect for quickly decluttering your chart or focusing on a different set of analyses.
Timeframe: This dropdown menu is the heart of the MTF feature. Here, you select the higher timeframe you want to analyse (e.g., 1D for Daily, 1W for Weekly, 4H for 4-Hour). All calculations for the three pairs within this group will be based on the timeframe you select here.
3. Pair-Specific Controls
Inside each timeframe group, there are three sections for "Pair 1", "Pair 2", and "Pair 3". These control each individual moving average cloud.
Enable Pair: Just like the master switch for the timeframe, this checkbox turns a single cloud and its two MA lines on or off.
For each pair, the settings are further broken down:
Moving Average Lines (A and B): These two rows control the two moving averages that form the cloud. 'A' is typically used for the shorter-period MA and 'B' for the longer-period one.
Type (A/B): A dropdown menu to select either EMA (Exponential Moving Average) or SMA (Simple Moving Average). EMAs react more quickly to recent price changes, while SMAs are smoother and react more slowly.
Length (A/B): The lookback period for the moving average (e.g., 21, 50, 200).
Color (A/B): Sets the specific colour of the MA line itself on your chart.
Cloud Fill Settings
Fill Color: This controls the colour of the shaded area (the "cloud") between the two moving average lines. For a consistent look, you can set this to the same colour as your shorter MA line.
Transparency: Controls how see-through the cloud is, on a scale of 0 to 100. 0 is a solid, opaque colour, while 100 is completely invisible. The default of 85 provides a light, "cloud-like" appearance that doesn't obscure the price action.
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If anything is not clear please let me know!
Luma DCA Simulator (BTC only)Luma DCA Simulator – Guide
What is the Luma DCA Simulator?
The Luma DCA Tracker shows how regular Bitcoin investments (Dollar Cost Averaging) would have developed over a freely selectable period – directly in the chart, transparent and easy to follow.
Settings Overview
1. Investment amount per interval
Specifies how much capital is invested at each purchase (e.g. 100).
2. Start date
Defines the point in time from which the simulation begins – e.g. 01.01.2020.
3. Investment interval
Determines how frequently investments are made:
– Daily
– Weekly
– Every 14 days
– Monthly
4. Language
Switches the info box display between English and German.
5. Show investment data (optional)
If activated, the chart will display additional values such as total invested capital, BTC amount, current value, and profit/loss.
What the Chart Displays
Entry points: Each DCA purchase is marked as a point in the price chart.
Average entry price: An orange line visualizes the evolving DCA average.
Info box (bottom left) with a live summary of:
– Total invested capital
– Total BTC acquired
– Average entry price
– Current portfolio value
– Profit/loss in absolute terms and percentage
Note on Accuracy
This simulation is for illustrative purposes only.
Spreads, slippage, fees, and tax effects are not included.
Actual results may vary.
Technical Note
For daily or weekly intervals, the chart timeframe should be set to 1 day or lower to ensure all purchases are accurately included.
Larger timeframes (e.g. weekly or monthly charts) may result in missed investments.
Currency Handling
All calculations are based on the selected chart symbol (e.g. BTCUSD, BTCEUR, BTCUSDT).
The displayed currency is automatically determined by the chart used.
TBL HTF Highs&LowsThis script plots the previous Daily, Weekly, and Monthly High and Low levels directly on your chart, helping you identify key higher-timeframe support and resistance zones.
Features:
Daily, Weekly, Monthly Lines: Toggle visibility for each timeframe's high/low levels.
Customization Options:
Choose color, style (Solid, Dashed, Dotted), width, and transparency for each line type.
Automatic Updates: Lines update at the start of each new session (day, week, or month).
Summary Table: Displays the latest Pre-Daily High/Low (PDH/PDL), Pre-Weekly High/Low (PWH/PWL), and Pre-Monthly High/Low (PMH/PML) in the top-right corner of the chart.
Configurable Table Font Size: Choose between Tiny, Small, Medium, or Large text.
Use Case:
Ideal for traders who rely on key higher-timeframe levels for confluence, breakout trading, or mean-reversion strategies. The visual lines and summary table provide instant context without cluttering your chart.
NSE/BSE Derivative - Next Expiry Date With HolidaysNSE & BSE Expiry Tracker with Holiday Adjustments
This Pine Script is a TradingView indicator that helps traders monitor upcoming expiry dates for major Indian derivative contracts. It dynamically adjusts these expiry dates based on weekends and holidays, and highlights any expiry that falls on the current day.
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Key Features
1. Tracks Expiry Dates for Major Contracts
The script calculates and displays the next expiry dates for the following instruments:
• NIFTY (weekly expiry every Thursday)
• BANKNIFTY, FINNIFTY, MIDCPNIFTY, NIFTYNXT50 (monthly expiry on the last Thursday of the month)
• SENSEX (weekly expiry every Tuesday)
• BANKEX and SENSEX 50 (monthly expiry on the last Tuesday of the month)
• Stocks in the F&O segment (monthly expiry on the last Thursday)
2. Holiday Awareness
Users can input a list of holiday dates in the format YYYY-MM-DD,YYYY-MM-DD,.... If any calculated expiry falls on one of these holidays or a weekend, the script automatically adjusts the expiry to the previous working day (Monday to Friday).
3. Customization Options
The user can:
• Choose the position of the expiry table on the chart (e.g. top right, bottom left).
• Select the font size for the expiry table.
• Enable or disable the table entirely (if implemented as an input toggle).
4. Visual Expiry Highlighting
If today is an expiry day for any instrument, the script highlights that instrument in the display. This makes it easy to spot significant expiry days, which are often associated with increased volatility and trading volume.
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How It Works
• The script calculates the next expiry for each index using built-in date/time functions.
• For weekly expiries, it finds the next occurrence of the designated weekday.
• For monthly expiries, it finds the last Thursday or Tuesday of the month.
• Each expiry date is passed through a check to adjust for holidays or weekends.
• If today matches the adjusted expiry date, that row is visually emphasized.
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Use Case
This script is ideal for traders who want a quick glance at which instruments are expiring soon — especially those managing options, futures, or expiry-based strategies.
VWAP Indicator Channel | Multi Timeframe by Osbrah📊 Multi-Timeframe VWAP Indicator (Session / Weekly / Monthly)
This powerful indicator plots the Volume Weighted Average Price (VWAP) across multiple timeframes: intraday session, weekly, and monthly. It's designed to give traders a clear understanding of the market’s fair value over different horizons.
Key Features:
* Display Session VWAP (resets daily)
* Enable Weekly and Monthly VWAPs for broader market context
* Customize colors, styles, and visibility for each VWAP
* Toggle between standard VWAP or anchored to session opens
Use Cases:
* Identify value zones where price tends to gravitate
* Spot institutional levels of interest and potential reversal points
* Align entries with VWAP bounces or breaks
* Combine with EMAs or price action for high-probability setups
Perfect for day traders, swing traders, and institutional-style strategies, this VWAP tool helps you stay aligned with volume-based price dynamics across all market phases.
True Seasonal Pattern [tradeviZion]True Seasonal Pattern: Uncover Hidden Market Cycles
Markets have rhythms and patterns that repeat with surprising regularity. The True Seasonal Pattern indicator reveals these hidden cycles across different timeframes, helping you anticipate potential market movements based on historical seasonal tendencies.
What This Indicator Does
The True Seasonal Pattern analyzes years of historical price data to identify recurring seasonal trends. It then plots these patterns on your chart, showing you both the historical pattern and future projection based on past seasonal behavior.
Automatic Timeframe Detection: Works with Monthly, Weekly, and Daily charts
Historical Pattern Analysis: Analyzes up to 100 years of data (customizable)
Future Projection: Projects the seasonal pattern ahead on your chart
Smart Smoothing: Applies appropriate smoothing based on your timeframe
How to Use This Indicator
Add the indicator to a Daily, Weekly, or Monthly chart (not designed for intraday timeframes)
The indicator automatically detects your chart's timeframe
The blue line shows the historical seasonal pattern
Watch for potential turning points in the pattern that align with other technical signals
Seasonal patterns work best as a supporting factor in your analysis, not as standalone trading signals. They are particularly effective in markets with well-established seasonal influences.
Best Applications
Futures Markets: Commodities and futures often show strong seasonal tendencies due to production cycles, weather patterns, and economic factors
Stock Indices: Many stock markets demonstrate regular seasonal patterns (like the "Sell in May" phenomenon)
Individual Stocks: Companies with seasonal business cycles often show predictable price patterns
Practical Applications
Identify potential turning points based on historical seasonal patterns
Plan entries and exits around seasonal tendencies
Add seasonal context to your existing technical analysis
Understand why certain months or periods might show consistent behavior
Pro Tip: For best results, use this tool on instruments with at least 5+ years of historical data. Longer timeframes often reveal more reliable seasonal patterns.
Important Notes
This indicator works best on Daily, Weekly, and Monthly timeframes - not intraday charts
Seasonal patterns are tendencies, not guarantees
Always combine seasonal analysis with other technical tools
Past patterns may not repeat exactly in the future
// Sample of the seasonal calculation approach
float yearHigh = array.max(currentYearHighs)
float yearLow = array.min(currentYearLows)
// Calculate seasonality for each period
for i = 0 to array.size(currentYearCloses) - 1
float periodClose = array.get(currentYearCloses, i)
if not na(periodClose) and yearHigh != yearLow
float seasonality = (periodClose - yearLow) / (yearHigh - yearLow) * 100
I developed this indicator to help traders incorporate seasonal analysis into their trading approach without the complexity of traditional seasonal tools. Whether you're analyzing agricultural commodities, energy futures, or stock indices, understanding the seasonal context can provide valuable insights for your trading decisions.
Remember: Markets don't always follow seasonal patterns, but when they do, being aware of these tendencies can give you a meaningful edge in your analysis.
MACD Multi-Timeframe x4 (Custom Params)■About this indicator
・This indicator can display 4 MACD lines for different time frames. (Multi-time framework)
・The color of the MACD line changes when the MACD has a golden or dead cross.
All MACDs can be set individually for long time period, short time period, and signal smoothing.
All MACDs can show/hide MACD lines, signal lines, histograms, and select colors.
■Explanation of effective usage
By displaying MACDs in multiple time frames, you can time the push.
For example, let's say you have three MACDs: one weekly, one daily, and one hour.
With the weekly and daily MACDs continuing to golden cross, the timing for the hourly MACD to golden cross is considered a push opportunity.
An example chart is attached below for your reference.
The area circled vertically is a push-buying opportunity.
Yellow-green: Weekly Green: Daily Light blue: Hourly
-------------------------------------------------------------------------------------------------------------
■このインジケーターについて
・このインジケーターは別の時間軸の4本のMACDを表示させることが出来ます。（マルチタイムフレームワーク）
・MACDがゴールデンクロス・デッドクロスした場合にMACDラインの色が変化します。
・全てのMACDについて個別に長期の期間・短期の期間・シグナルの平滑化を設定できます。
・全てのMACDはMACDライン・シグナルライン・ヒストグラムの表示/非表示、色の選択ができます。
■有効な使い方の説明
マルチタイムフレームでMACDを表示することで、押し目のタイミングを計ることが出来ます。
例えば、3本のMACDを1週間・1日・1時間とします。
週足と日足のMACDがゴールデンクロスを継続した状態で、1時間足のMACDがゴールデンクロスしてくるタイミングは押し目買いのチャンスと考えられます。
以下に例題のチャートを付けますので、参考にしてください。
縦に囲った辺りが押し目買いのチャンスになります。
黄緑：週足 緑：日足 水色：1時間足
Multi-Timeframe Closures with Signals month week dayMulti-Timeframe Price Anchoring Indicator (Monthly, Weekly, Daily)
This indicator provides a powerful visual framework for analyzing price action across three major timeframes: monthly, weekly, and daily. It plots the closing prices of each timeframe directly on the chart to help traders assess where current price stands in relation to significant historical levels.
🔍 Core Features:
Monthly, Weekly, and Daily Close Lines: Automatically updated at the start of each new period.
Color-coded Price Anchors: Each timeframe is visually distinct for fast interpretation.
Multi-timeframe Awareness: Helps you identify trend alignment or divergence across different time horizons.
Long & Short Bias Signals: The script can optionally display long or short suggestions based on where the current price stands relative to the anchored closing prices.
📈 How to Use:
Trend Confirmation: If price is consistently above all three levels, it signals a strong bullish trend (potential long bias). If it’s below, the opposite applies (short bias).
Reversal or Pullback Zones: When price becomes extended far above/below the monthly and weekly closes, it may suggest overbought/oversold conditions and the possibility of a reversal or retracement.
Intraday Alignment: Useful for traders who want to enter positions on lower timeframes while being aware of higher timeframe trends.
This indicator is ideal for swing traders, day traders, and position traders who want to anchor their decisions to meaningful multi-timeframe reference points.
Aurora Flow Oscillator [QuantAlgo]The Aurora Flow Oscillator is an advanced momentum-based technical indicator designed to identify market direction, momentum shifts, and potential reversal zones using adaptive filtering techniques. It visualizes price momentum through a dynamic oscillator that quantifies trend strength and direction, helping traders and investors recognize momentum shifts and trading opportunities across various timeframes and asset class.
🟢 Technical Foundation
The Aurora Flow Oscillator employs a sophisticated mathematical approach with adaptive momentum filtering to analyze market conditions, including:
Price-Based Momentum Calculation: Calculates logarithmic price changes to measure the rate and magnitude of market movement
Adaptive Momentum Filtering: Applies an advanced filtering algorithm to smooth momentum calculations while preserving important signals
Acceleration Analysis: Incorporates momentum acceleration to identify shifts in market direction before they become obvious
Signal Normalization: Automatically scales the oscillator output to a range between -100 and 100 for consistent interpretation across different market conditions
The indicator processes price data through multiple filtering stages, applying mathematical principles including exponential smoothing with adaptive coefficients. This creates an oscillator that dynamically adjusts to market volatility while maintaining responsiveness to genuine trend changes.
🟢 Key Features & Signals
1. Momentum Flow and Extreme Zone Identification
The oscillator presents market momentum through an intuitive visual display that clearly indicates both direction and strength:
Above Zero: Indicates positive momentum and potential bullish conditions
Below Zero: Indicates negative momentum and potential bearish conditions
Slope Direction: The angle and direction of the oscillator provide immediate insight into momentum strength
Zero Line Crossings: Signal potential trend changes and new directional momentum
The indicator also identifies potential overbought and oversold market conditions through extreme zone markings:
Upper Zone (>50): Indicates strong bullish momentum that may be approaching exhaustion
Lower Zone (<-50): Indicates strong bearish momentum that may be approaching exhaustion
Extreme Boundaries (±95): Mark potentially unsustainable momentum levels where reversals become increasingly likely
These zones are displayed with gradient intensity that increases as the oscillator moves toward extremes, helping traders and investors:
→ Identify potential reversal zones
→ Determine appropriate entry and exit points
→ Gauge overall market sentiment strength
2. Customizable Trading Style Presets
The Aurora Flow Oscillator offers pre-configured settings for different trading approaches:
Default (80,150): Balanced configuration suitable for most trading and investing situations.
Scalping (5,80): Highly responsive settings for ultra-short-term trades. Generates frequent signals and catches quick price movements. Best for 1-15min charts when making many trades per day.
Day Trading (8,120): Optimized for intraday movements with faster response than default settings while maintaining reasonable signal quality. Ideal for 5-60min or 4h-12h timeframes.
Swing Trading (10,200): Designed for multi-day positions with stronger noise filtering. Focuses on capturing larger price swings while avoiding minor fluctuations. Works best on 1-4h and daily charts.
Position Trading (14,250): For longer-term position traders/investors seeking significant market trends. Reduces false signals by heavily filtering market noise. Ideal for daily or even weekly charts.
Trend Following (16,300): Maximum smoothing that prioritizes established directional movements over short-term fluctuations. Best used on daily and weekly charts, but can also be used for lower timeframe trading.
Countertrend (7,100): Tuned to detect potential reversals and exhaustion points in trends. More sensitive to momentum shifts than other presets. Effective on 15min-4h charts, as well as daily and weekly charts.
Each preset automatically adjusts internal parameters for optimal performance in the selected trading context, providing flexibility across different market approaches without requiring complex manual configuration.
🟢 Practical Usage Tips
1/ Trend Analysis and Interpretation
→ Direction Assessment: Evaluate the oscillator's position relative to zero to determine underlying momentum bias
→ Momentum Strength: Measure the oscillator's distance from zero within the -100 to +100 range to quantify momentum magnitude
→ Trend Consistency: Monitor the oscillator's path for sustained directional movement without frequent zero-line crossings
→ Reversal Detection: Watch for oscillator divergence from price and deceleration of movement when approaching extreme zones
2/ Signal Generation Strategies
Depending on your trading approach, multiple signal strategies can be employed:
Trend Following Signals:
Enter long positions when the oscillator crosses above zero
Enter short positions when the oscillator crosses below zero
Add to positions on pullbacks while maintaining the overall trend direction
Countertrend Signals:
Look for potential reversals when the oscillator reaches extreme zones (±95)
Enter contrary positions when momentum shows signs of exhaustion
Use oscillator divergence with price as additional confirmation
Momentum Shift Signals:
Enter positions when oscillator changes direction after establishing a trend
Exit positions when oscillator direction reverses against your position
Scale position size based on oscillator strength percentage
3/ Timeframe Optimization
The indicator can be effectively applied across different timeframes with these considerations:
Lower Timeframes (1-15min):
Use Scalping or Day Trading presets
Focus on quick momentum shifts and zero-line crossings
Be cautious of noise in extreme market conditions
Medium Timeframes (30min-4h):
Use Default or Swing Trading presets
Look for established trends and potential reversal zones
Combine with support/resistance analysis for entry/exit precision
Higher Timeframes (Daily+):
Use Position Trading or Trend Following presets
Focus on major trend identification and long-term positioning
Use extreme zones for position management rather than immediate reversals
🟢 Pro Tips
Price Momentum Period:
→ Lower values (5-7) increase sensitivity to minor price fluctuations but capture more market noise
→ Higher values (10-16) emphasize sustained momentum shifts at the cost of delayed response
→ Adjust based on your timeframe (lower for shorter timeframes, higher for longer timeframes)
Oscillator Filter Period:
→ Lower values (80-120) produce more frequent directional changes and earlier response to momentum shifts
→ Higher values (200-300) filter out shorter-term fluctuations to highlight dominant market cycles
→ Match to your typical holding period (shorter holding time = lower filter values)
Multi-Timeframe Analysis:
→ Compare oscillator readings across different timeframes for confluence
→ Look for alignment between higher and lower timeframe signals
→ Use higher timeframe for trend direction, lower for earlier entries
Volatility-Adaptive Trading:
→ Use oscillator strength to adjust position sizing (stronger = larger)
→ Consider reducing exposure when oscillator reaches extreme zones
→ Implement tighter stops during periods of oscillator acceleration
Combination Strategies:
→ Pair with volume indicators for confirmation of momentum shifts
→ Use with support/resistance levels for strategic entry and exit points
→ Combine with volatility indicators for comprehensive market context
Quarterly Cycle Theory with DST time AdjustedThe Quarterly Theory removes ambiguity, as it gives specific time-based reference points to look for when entering trades. Before being able to apply this theory to trading, one must first understand that time is fractal:
Yearly Quarters = 4 quarters of three months each.
Monthly Quarters = 4 quarters of one week each.
Weekly Quarters = 4 quarters of one day each (Monday - Thursday). Friday has its own specific function.
Daily Quarters = 4 quarters of 6 hours each = 4 trading sessions of a trading day.
Sessions Quarters = 4 quarters of 90 minutes each.
90 Minute Quarters = 4 quarters of 22.5 minutes each.
Yearly Cycle: Analogously to financial quarters, the year is divided in four sections of three months each:
Q1 - January, February, March.
Q2 - April, May, June (True Open, April Open).
Q3 - July, August, September.
Q4 - October, November, December.
S&P 500 E-mini Futures (daily candles) — Monthly Cycle.
Monthly Cycle: Considering that we have four weeks in a month, we start the cycle on the first month’s Monday (regardless of the calendar Day):
Q1 - Week 1: first Monday of the month.
Q2 - Week 2: second Monday of the month (True Open, Daily Candle Open Price).
Q3 - Week 3: third Monday of the month.
Q4 - Week 4: fourth Monday of the month.
S&P 500 E-mini Futures (4 hour candles) — Weekly Cycle.
Weekly Cycle: Daye determined that although the trading week is composed by 5 trading days, we should ignore Friday, and the small portion of Sunday’s price action:
Q1 - Monday.
Q2 - Tuesday (True Open, Daily Candle Open Price).
Q3 - Wednesday.
Q4 - Thursday.
S&P 500 E-mini Futures (1 hour candles) — Daily Cycle.
Daily Cycle: The Day can be broken down into 6 hour quarters. These times roughly define the sessions of the trading day, reinforcing the theory’s validity:
Q1 - 18:00 - 00:00 Asia.
Q2 - 00:00 - 06:00 London (True Open).
Q3 - 06:00 - 12:00 NY AM.
Q4 - 12:00 - 18:00 NY PM.
S&P 500 E-mini Futures (15 minute candles) — 6 Hour Cycle.
6 Hour Quarters or 90 Minute Cycle / Sessions divided into four sections of 90 minutes each (EST/EDT):
Asian Session
Q1 - 18:00 - 19:30
Q2 - 19:30 - 21:00 (True Open)
Q3 - 21:00 - 22:30
Q4 - 22:30 - 00:00
London Session
Q1 - 00:00 - 01:30
Q2 - 01:30 - 03:00 (True Open)
Q3 - 03:00 - 04:30
Q4 - 04:30 - 06:00
NY AM Session
Q1 - 06:00 - 07:30
Q2 - 07:30 - 09:00 (True Open)
Q3 - 09:00 - 10:30
Q4 - 10:30 - 12:00
NY PM Session
Q1 - 12:00 - 13:30
Q2 - 13:30 - 15:00 (True Open)
Q3 - 15:00 - 16:30
Q4 - 16:30 - 18:00
S&P 500 E-mini Futures (5 minute candles) — 90 Minute Cycle.
Micro Cycles: Dividing the 90 Minute Cycle yields 22.5 Minute Quarters, also known as Micro Sessions or Micro Quarters:
Asian Session
Q1/1 18:00:00 - 18:22:30
Q2 18:22:30 - 18:45:00
Q3 18:45:00 - 19:07:30
Q4 19:07:30 - 19:30:00
Q2/1 19:30:00 - 19:52:30 (True Session Open)
Q2/2 19:52:30 - 20:15:00
Q2/3 20:15:00 - 20:37:30
Q2/4 20:37:30 - 21:00:00
Q3/1 21:00:00 - 21:23:30
etc. 21:23:30 - 21:45:00
London Session
00:00:00 - 00:22:30 (True Daily Open)
00:22:30 - 00:45:00
00:45:00 - 01:07:30
01:07:30 - 01:30:00
01:30:00 - 01:52:30 (True Session Open)
01:52:30 - 02:15:00
02:15:00 - 02:37:30
02:37:30 - 03:00:00
03:00:00 - 03:22:30
03:22:30 - 03:45:00
03:45:00 - 04:07:30
04:07:30 - 04:30:00
04:30:00 - 04:52:30
04:52:30 - 05:15:00
05:15:00 - 05:37:30
05:37:30 - 06:00:00
New York AM Session
06:00:00 - 06:22:30
06:22:30 - 06:45:00
06:45:00 - 07:07:30
07:07:30 - 07:30:00
07:30:00 - 07:52:30 (True Session Open)
07:52:30 - 08:15:00
08:15:00 - 08:37:30
08:37:30 - 09:00:00
09:00:00 - 09:22:30
09:22:30 - 09:45:00
09:45:00 - 10:07:30
10:07:30 - 10:30:00
10:30:00 - 10:52:30
10:52:30 - 11:15:00
11:15:00 - 11:37:30
11:37:30 - 12:00:00
New York PM Session
12:00:00 - 12:22:30
12:22:30 - 12:45:00
12:45:00 - 13:07:30
13:07:30 - 13:30:00
13:30:00 - 13:52:30 (True Session Open)
13:52:30 - 14:15:00
14:15:00 - 14:37:30
14:37:30 - 15:00:00
15:00:00 - 15:22:30
15:22:30 - 15:45:00
15:45:00 - 15:37:30
15:37:30 - 16:00:00
16:00:00 - 16:22:30
16:22:30 - 16:45:00
16:45:00 - 17:07:30
17:07:30 - 18:00:00
S&P 500 E-mini Futures (30 second candles) — 22.5 Minute Cycle.
Multi-Timeframe Anchored VWAP Valuation# Multi-Timeframe Anchored VWAP Valuation
## Overview
This indicator provides a unique perspective on potential price valuation by comparing the current price to the Volume Weighted Average Price (VWAP) anchored to the start of multiple timeframes: Weekly, Monthly, Quarterly, and Yearly. It synthesizes these comparisons into a single oscillator value, helping traders gauge if the current price is potentially extended relative to significant volume-weighted levels.
## Core Concept & Calculation
1. **Anchored VWAP:** The script calculates the VWAP separately for the current Week, Month, Quarter (3 Months), and Year (12 Months), starting the calculation from the first bar of each period.
2. **Price Deviation:** It measures how far the current `close` price is from each of these anchored VWAPs. This distance is measured in terms of standard deviations calculated *within* that specific anchor period (e.g., how many weekly standard deviations the price is away from the weekly VWAP).
3. **Deviation Score (Multiplier):** Based on this standard deviation distance, a score is assigned. The further the price is from the VWAP (in terms of standard deviations), the higher the absolute score. The indicator uses linear interpolation to determine scores between the standard deviation levels (defaulted at 1, 2, and 3 standard deviations corresponding to scores of +/-2, +/-3, +/-4, with a score of 1 at the VWAP).
4. **Timeframe Weighting:** Longer timeframes are considered more significant. The deviation scores are multiplied by fixed scalars: Weekly (x1), Monthly (x2), Quarterly (x3), Yearly (x4).
5. **Final Valuation Metric:** The weighted scores from all four timeframes are summed up to produce the final oscillator value plotted in the indicator pane.
## How to Interpret and Use
* **Histogram (Indicator Pane):**
* The main output is the histogram representing the `Final Valuation Metric`.
* **Positive Values:** Suggest the price is generally trading above its volume-weighted averages across the timeframes, potentially indicating strength or relative "overvaluation."
* **Negative Values:** Suggest the price is generally trading below its volume-weighted averages, potentially indicating weakness or relative "undervaluation."
* **Values Near Zero:** Indicate the price is relatively close to its volume-weighted averages.
* **Histogram Color:**
* The color of the histogram bars provides context based on the metric's *own recent history*.
* **Green (Positive Color):** The metric is currently *above* its recent average plus a standard deviation band (dynamic upper threshold). This highlights potentially significant "overvalued" readings relative to its normal range.
* **Red (Negative Color):** The metric is currently *below* its recent average minus a standard deviation band (dynamic lower threshold). This highlights potentially significant "undervalued" readings relative to its normal range.
* **Gray (Neutral Color):** The metric is within its typical recent range (between the dynamic upper and lower thresholds).
* **Orange Line:** Plots the moving average of the `Final Valuation Metric` itself (based on the "Threshold Lookback Period"), serving as the centerline for the dynamic thresholds.
* **On-Chart Table:**
* Provides a detailed breakdown for transparency.
* Shows the calculated VWAP, the raw deviation multiplier score, and the final weighted (adjusted) metric for each individual timeframe (W, M, Q, Y).
* Displays the current price, the final combined metric value, and a textual interpretation ("Overvalued", "Undervalued", "Neutral") based on the dynamic thresholds.
## Potential Use Cases
* Identifying potential exhaustion points when the indicator reaches statistically high (green) or low (red) levels relative to its recent history.
* Assessing whether price trends are supported by underlying volume-weighted average prices across multiple timeframes.
* Can be used alongside other technical analysis tools for confirmation.
## Settings
* **Calculation Settings:**
* `STDEV Level 1`: Adjusts the 1st standard deviation level (default 1.0).
* `STDEV Level 2`: Adjusts the 2nd standard deviation level (default 2.0).
* `STDEV Level 3`: Adjusts the 3rd standard deviation level (default 3.0).
* **Interpretation Settings:**
* `Threshold Lookback Period`: Defines the number of bars used to calculate the average and standard deviation of the final metric for dynamic thresholds (default 200).
* `Threshold StDev Multiplier`: Controls how many standard deviations above/below the metric's average are used to set the "Overvalued"/"Undervalued" thresholds (default 1.0).
* **Table Settings:** Customize the position and colors of the data table displayed on the chart.
## Important Considerations
* This indicator measures price deviation relative to *anchored* VWAPs and its *own historical range*. It is not a standalone trading system.
* The interpretation of "Overvalued" and "Undervalued" is relative to the indicator's logic and calculations; it does not guarantee future price movement.
* Like all indicators, past performance is not indicative of future results. Use this tool as part of a comprehensive analysis and risk management strategy.
* The anchored VWAP and Standard Deviation values reset at the beginning of each respective period (Week, Month, Quarter, Year).
Correlation Heatmap█ OVERVIEW
This indicator creates a correlation matrix for a user-specified list of symbols based on their time-aligned weekly or monthly price returns. It calculates the Pearson correlation coefficient for each possible symbol pair, and it displays the results in a symmetric table with heatmap-colored cells. This format provides an intuitive view of the linear relationships between various symbols' price movements over a specific time range.
█ CONCEPTS
Correlation
Correlation typically refers to an observable statistical relationship between two datasets. In a financial time series context, it usually represents the extent to which sampled values from a pair of datasets, such as two series of price returns, vary jointly over time. More specifically, in this context, correlation describes the strength and direction of the relationship between the samples from both series.
If two separate time series tend to rise and fall together proportionally, they might be highly correlated. Likewise, if the series often vary in opposite directions, they might have a strong anticorrelation . If the two series do not exhibit a clear relationship, they might be uncorrelated .
Traders frequently analyze asset correlations to help optimize portfolios, assess market behaviors, identify potential risks, and support trading decisions. For instance, correlation often plays a key role in diversification . When two instruments exhibit a strong correlation in their returns, it might indicate that buying or selling both carries elevated unsystematic risk . Therefore, traders often aim to create balanced portfolios of relatively uncorrelated or anticorrelated assets to help promote investment diversity and potentially offset some of the risks.
When using correlation analysis to support investment decisions, it is crucial to understand the following caveats:
• Correlation does not imply causation . Two assets might vary jointly over an analyzed range, resulting in high correlation or anticorrelation in their returns, but that does not indicate that either instrument directly influences the other. Joint variability between assets might occur because of shared sensitivities to external factors, such as interest rates or global sentiment, or it might be entirely coincidental. In other words, correlation does not provide sufficient information to identify cause-and-effect relationships.
• Correlation does not predict the future relationship between two assets. It only reflects the estimated strength and direction of the relationship between the current analyzed samples. Financial time series are ever-changing. A strong trend between two assets can weaken or reverse in the future.
Correlation coefficient
A correlation coefficient is a numeric measure of correlation. Several coefficients exist, each quantifying different types of relationships between two datasets. The most common and widely known measure is the Pearson product-moment correlation coefficient , also known as the Pearson correlation coefficient or Pearson's r . Usually, when the term "correlation coefficient" is used without context, it refers to this correlation measure.
The Pearson correlation coefficient quantifies the strength and direction of the linear relationship between two variables. In other words, it indicates how consistently variables' values move together or in opposite directions in a proportional, linear manner. Its formula is as follows:
𝑟(𝑥, 𝑦) = cov(𝑥, 𝑦) / (𝜎𝑥 * 𝜎𝑦)
Where:
• 𝑥 is the first variable, and 𝑦 is the second variable.
• cov(𝑥, 𝑦) is the covariance between 𝑥 and 𝑦.
• 𝜎𝑥 is the standard deviation of 𝑥.
• 𝜎𝑦 is the standard deviation of 𝑦.
In essence, the correlation coefficient measures the covariance between two variables, normalized by the product of their standard deviations. The coefficient's value ranges from -1 to 1, allowing a more straightforward interpretation of the relationship between two datasets than what covariance alone provides:
• A value of 1 indicates a perfect positive correlation over the analyzed sample. As one variable's value changes, the other variable's value changes proportionally in the same direction .
• A value of -1 indicates a perfect negative correlation (anticorrelation). As one variable's value increases, the other variable's value decreases proportionally.
• A value of 0 indicates no linear relationship between the variables over the analyzed sample.
Aligning returns across instruments
In a financial time series, each data point (i.e., bar) in a sample represents information collected in periodic intervals. For instance, on a "1D" chart, bars form at specific times as successive days elapse.
However, the times of the data points for a symbol's standard dataset depend on its active sessions , and sessions vary across instrument types. For example, the daily session for NYSE stocks is 09:30 - 16:00 UTC-4/-5 on weekdays, Forex instruments have 24-hour sessions that span from 17:00 UTC-4/-5 on one weekday to 17:00 on the next, and new daily sessions for cryptocurrencies start at 00:00 UTC every day because crypto markets are consistently open.
Therefore, comparing the standard datasets for different asset types to identify correlations presents a challenge. If two symbols' datasets have bars that form at unaligned times, their correlation coefficient does not accurately describe their relationship. When calculating correlations between the returns for two assets, both datasets must maintain consistent time alignment in their values and cover identical ranges for meaningful results.
To address the issue of time alignment across instruments, this indicator requests confirmed weekly or monthly data from spread tickers constructed from the chart's ticker and another specified ticker. The datasets for spreads are derived from lower-timeframe data to ensure the values from all symbols come from aligned points in time, allowing a fair comparison between different instrument types. Additionally, each spread ticker ID includes necessary modifiers, such as extended hours and adjustments.
In this indicator, we use the following process to retrieve time-aligned returns for correlation calculations:
1. Request the current and previous prices from a spread representing the sum of the chart symbol and another symbol ( "chartSymbol + anotherSymbol" ).
2. Request the prices from another spread representing the difference between the two symbols ( "chartSymbol - anotherSymbol" ).
3. Calculate half of the difference between the values from both spreads ( 0.5 * (requestedSum - requestedDifference) ). The results represent the symbol's prices at times aligned with the sample points on the current chart.
4. Calculate the arithmetic return of the retrieved prices: (currentPrice - previousPrice) / previousPrice
5. Repeat steps 1-4 for each symbol requiring analysis.
It's crucial to note that because this process retrieves prices for a symbol at times consistent with periodic points on the current chart, the values can represent prices from before or after the closing time of the symbol's usual session.
Additionally, note that the maximum number of weeks or months in the correlation calculations depends on the chart's range and the largest time range common to all the requested symbols. To maximize the amount of data available for the calculations, we recommend setting the chart to use a daily or higher timeframe and specifying a chart symbol that covers a sufficient time range for your needs.
█ FEATURES
This indicator analyzes the correlations between several pairs of user-specified symbols to provide a structured, intuitive view of the relationships in their returns. Below are the indicator's key features:
Requesting a list of securities
The "Symbol list" text box in the indicator's "Settings/Inputs" tab accepts a comma-separated list of symbols or ticker identifiers with optional spaces (e.g., "XOM, MSFT, BITSTAMP:BTCUSD"). The indicator dynamically requests returns for each symbol in the list, then calculates the correlation between each pair of return series for its heatmap display.
Each item in the list must represent a valid symbol or ticker ID. If the list includes an invalid symbol, the script raises a runtime error.
To specify a broker/exchange for a symbol, include its name as a prefix with a colon in the "EXCHANGE:SYMBOL" format. If a symbol in the list does not specify an exchange prefix, the indicator selects the most commonly used exchange when requesting the data.
Note that the number of symbols allowed in the list depends on the user's plan. Users with non-professional plans can compare up to 20 symbols with this indicator, and users with professional plans can compare up to 32 symbols.
Timeframe and data length selection
The "Returns timeframe" input specifies whether the indicator uses weekly or monthly returns in its calculations. By default, its value is "1M", meaning the indicator analyzes monthly returns. Note that this script requires a chart timeframe lower than or equal to "1M". If the chart uses a higher timeframe, it causes a runtime error.
To customize the length of the data used in the correlation calculations, use the "Max periods" input. When enabled, the indicator limits the calculation window to the number of periods specified in the input field. Otherwise, it uses the chart's time range as the limit. The top-left corner of the table shows the number of confirmed weeks or months used in the calculations.
It's important to note that the number of confirmed periods in the correlation calculations is limited to the largest time range common to all the requested datasets, because a meaningful correlation matrix requires analyzing each symbol's returns under the same market conditions. Therefore, the correlation matrix can show different results for the same symbol pair if another listed symbol restricts the aligned data to a shorter time range.
Heatmap display
This indicator displays the correlations for each symbol pair in a heatmap-styled table representing a symmetric correlation matrix. Each row and column corresponds to a specific symbol, and the cells at their intersections correspond to symbol pairs . For example, the cell at the "AAPL" row and "MSFT" column shows the weekly or monthly correlation between those two symbols' returns. Likewise, the cell at the "MSFT" row and "AAPL" column shows the same value.
Note that the main diagonal cells in the display, where the row and column refer to the same symbol, all show a value of 1 because any series of non-na data is always perfectly correlated with itself.
The background of each correlation cell uses a gradient color based on the correlation value. By default, the gradient uses blue hues for positive correlation, orange hues for negative correlation, and white for no correlation. The intensity of each blue or orange hue corresponds to the strength of the measured correlation or anticorrelation. Users can customize the gradient's base colors using the inputs in the "Color gradient" section of the "Settings/Inputs" tab.
█ FOR Pine Script® CODERS
• This script uses the `getArrayFromString()` function from our ValueAtTime library to process the input list of symbols. The function splits the "string" value by its commas, then constructs an array of non-empty strings without leading or trailing whitespaces. Additionally, it uses the str.upper() function to convert each symbol's characters to uppercase.
• The script's `getAlignedReturns()` function requests time-aligned prices with two request.security() calls that use spread tickers based on the chart's symbol and another symbol. Then, it calculates the arithmetic return using the `changePercent()` function from the ta library. The `collectReturns()` function uses `getAlignedReturns()` within a loop and stores the data from each call within a matrix . The script calls the `arrayCorrelation()` function on pairs of rows from the returned matrix to calculate the correlation values.
• For consistency, the `getAlignedReturns()` function includes extended hours and dividend adjustment modifiers in its data requests. Additionally, it includes other settings inherited from the chart's context, such as "settlement-as-close" preferences.
• A Pine script can execute up to 40 or 64 unique `request.*()` function calls, depending on the user's plan. The maximum number of symbols this script compares is half the plan's limit, because `getAlignedReturns()` uses two request.security() calls.
• This script can use the request.security() function within a loop because all scripts in Pine v6 enable dynamic requests by default. Refer to the Dynamic requests section of the Other timeframes and data page to learn more about this feature, and see our v6 migration guide to learn what's new in Pine v6.
• The script's table uses two distinct color.from_gradient() calls in a switch structure to determine the cell colors for positive and negative correlation values. One call calculates the color for values from -1 to 0 based on the first and second input colors, and the other calculates the colors for values from 0 to 1 based on the second and third input colors.
Look first. Then leap.
Relative Crypto Dominance Polar Chart [LuxAlgo]The Relative Crypto Dominance Polar Chart tool allows traders to compare the relative dominance of up to ten different tickers in the form of a polar area chart, we define relative dominance as a combination between traded dollar volume and volatility, making it very easy to compare them at a glance.
🔶 USAGE
The use is quite simple, traders just have to load the indicator on the chart, and the graph showing the relative dominance will appear.
The 10 tickers loaded by default are the major cryptocurrencies by market cap, but traders can select any ticker in the settings panel.
Each area represents dominance as volatility (radius) by dollar volume (arc length); a larger area means greater dominance on that ticker.
🔹 Choosing Period
The tool supports up to five different periods
Hourly
Daily
Weekly
Monthly
Yearly
By default, the tool period is set on auto mode, which means that the tool will choose the period depending on the chart timeframe
timeframes up to 2m: Hourly
timeframes up to 15m: Daily
timeframes up to 1H: Weekly
timeframes up to 4H: Monthly
larger timeframes: Yearly
🔹 Sorting & Sizing
Traders can sort the graph areas by volatility (radius of each area) in ascending or descending order; by default, the tickers are sorted as they are in the settings panel.
The tool also allows you to adjust the width of the chart on a percentage basis, i.e., at 100% size, all the available width is used; if the graph is too wide, just decrease the graph size parameter in the settings panel.
🔹 Set your own style
The tool allows great customization from the settings panel, traders can enable/disable most of the components, and add a very nice touch with curved lines enabled for displaying the areas with a petal-like effect.
🔶 SETTINGS
Period: Select up to 5 different time periods from Hourly, Daily, Weekly, Monthly and Yearly. Enable/disable Auto mode.
Tickers: Enable/disable and select tickers and colors
🔹 Style
Graph Order: Select sort order
Graph Size: Select percentage of width used
Labels Size: Select size for ticker labels
Show Percent: Show dominance in % under each ticker
Curved Lines: Enable/disable petal-like effect for each area
Show Title: Enable/disable graph title
Show Mean: Enable/disable volatility average and select color
Bitcoin Polynomial Regression ModelThis is the main version of the script. Click here for the Oscillator part of the script.
💡Why this model was created:
One of the key issues with most existing models, including our own Bitcoin Log Growth Curve Model , is that they often fail to realistically account for diminishing returns. As a result, they may present overly optimistic bull cycle targets (hence, we introduced alternative settings in our previous Bitcoin Log Growth Curve Model).
This new model however, has been built from the ground up with a primary focus on incorporating the principle of diminishing returns. It directly responds to this concept, which has been briefly explored here .
📉The theory of diminishing returns:
This theory suggests that as each four-year market cycle unfolds, volatility gradually decreases, leading to more tempered price movements. It also implies that the price increase from one cycle peak to the next will decrease over time as the asset matures. The same pattern applies to cycle lows and the relationship between tops and bottoms. In essence, these price movements are interconnected and should generally follow a consistent pattern. We believe this model provides a more realistic outlook on bull and bear market cycles.
To better understand this theory, the relationships between cycle tops and bottoms are outlined below:https://www.tradingview.com/x/7Hldzsf2/
🔧Creation of the model:
For those interested in how this model was created, the process is explained here. Otherwise, feel free to skip this section.
This model is based on two separate cubic polynomial regression lines. One for the top price trend and another for the bottom. Both follow the general cubic polynomial function:
ax^3 +bx^2 + cx + d.
In this equation, x represents the weekly bar index minus an offset, while a, b, c, and d are determined through polynomial regression analysis. The input (x, y) values used for the polynomial regression analysis are as follows:
Top regression line (x, y) values:
113, 18.6
240, 1004
451, 19128
655, 65502
Bottom regression line (x, y) values:
103, 2.5
267, 211
471, 3193
676, 16255
The values above correspond to historical Bitcoin cycle tops and bottoms, where x is the weekly bar index and y is the weekly closing price of Bitcoin. The best fit is determined using metrics such as R-squared values, residual error analysis, and visual inspection. While the exact details of this evaluation are beyond the scope of this post, the following optimal parameters were found:
Top regression line parameter values:
a: 0.000202798
b: 0.0872922
c: -30.88805
d: 1827.14113
Bottom regression line parameter values:
a: 0.000138314
b: -0.0768236
c: 13.90555
d: -765.8892
📊Polynomial Regression Oscillator:
This publication also includes the oscillator version of the this model which is displayed at the bottom of the screen. The oscillator applies a logarithmic transformation to the price and the regression lines using the formula log10(x) .
The log-transformed price is then normalized using min-max normalization relative to the log-transformed top and bottom regression line with the formula:
normalized price = log(close) - log(bottom regression line) / log(top regression line) - log(bottom regression line)
This transformation results in a price value between 0 and 1 between both the regression lines. The Oscillator version can be found here.
🔍Interpretation of the Model:
In general, the red area represents a caution zone, as historically, the price has often been near its cycle market top within this range. On the other hand, the green area is considered an area of opportunity, as historically, it has corresponded to the market bottom.
The top regression line serves as a signal for the absolute market cycle peak, while the bottom regression line indicates the absolute market cycle bottom.
Additionally, this model provides a predicted range for Bitcoin's future price movements, which can be used to make extrapolated predictions. We will explore this further below.
🔮Future Predictions:
Finally, let's discuss what this model actually predicts for the potential upcoming market cycle top and the corresponding market cycle bottom. In our previous post here , a cycle interval analysis was performed to predict a likely time window for the next cycle top and bottom:
In the image, it is predicted that the next top-to-top cycle interval will be 208 weeks, which translates to November 3rd, 2025. It is also predicted that the bottom-to-top cycle interval will be 152 weeks, which corresponds to October 13th, 2025. On the macro level, these two dates align quite well. For our prediction, we take the average of these two dates: October 24th 2025. This will be our target date for the bull cycle top.
Now, let's do the same for the upcoming cycle bottom. The bottom-to-bottom cycle interval is predicted to be 205 weeks, which translates to October 19th, 2026, and the top-to-bottom cycle interval is predicted to be 259 weeks, which corresponds to October 26th, 2026. We then take the average of these two dates, predicting a bear cycle bottom date target of October 19th, 2026.
Now that we have our predicted top and bottom cycle date targets, we can simply reference these two dates to our model, giving us the Bitcoin top price prediction in the range of 152,000 in Q4 2025 and a subsequent bottom price prediction in the range of 46,500 in Q4 2026.
For those interested in understanding what this specifically means for the predicted diminishing return top and bottom cycle values, the image below displays these predicted values. The new values are highlighted in yellow:
And of course, keep in mind that these targets are just rough estimates. While we've done our best to estimate these targets through a data-driven approach, markets will always remain unpredictable in nature. What are your targets? Feel free to share them in the comment section below.
Bitcoin Polynomial Regression OscillatorThis is the oscillator version of the script. Click here for the other part of the script.
💡Why this model was created:
One of the key issues with most existing models, including our own Bitcoin Log Growth Curve Model , is that they often fail to realistically account for diminishing returns. As a result, they may present overly optimistic bull cycle targets (hence, we introduced alternative settings in our previous Bitcoin Log Growth Curve Model).
This new model however, has been built from the ground up with a primary focus on incorporating the principle of diminishing returns. It directly responds to this concept, which has been briefly explored here .
📉The theory of diminishing returns:
This theory suggests that as each four-year market cycle unfolds, volatility gradually decreases, leading to more tempered price movements. It also implies that the price increase from one cycle peak to the next will decrease over time as the asset matures. The same pattern applies to cycle lows and the relationship between tops and bottoms. In essence, these price movements are interconnected and should generally follow a consistent pattern. We believe this model provides a more realistic outlook on bull and bear market cycles.
To better understand this theory, the relationships between cycle tops and bottoms are outlined below:https://www.tradingview.com/x/7Hldzsf2/
🔧Creation of the model:
For those interested in how this model was created, the process is explained here. Otherwise, feel free to skip this section.
This model is based on two separate cubic polynomial regression lines. One for the top price trend and another for the bottom. Both follow the general cubic polynomial function:
ax^3 +bx^2 + cx + d.
In this equation, x represents the weekly bar index minus an offset, while a, b, c, and d are determined through polynomial regression analysis. The input (x, y) values used for the polynomial regression analysis are as follows:
Top regression line (x, y) values:
113, 18.6
240, 1004
451, 19128
655, 65502
Bottom regression line (x, y) values:
103, 2.5
267, 211
471, 3193
676, 16255
The values above correspond to historical Bitcoin cycle tops and bottoms, where x is the weekly bar index and y is the weekly closing price of Bitcoin. The best fit is determined using metrics such as R-squared values, residual error analysis, and visual inspection. While the exact details of this evaluation are beyond the scope of this post, the following optimal parameters were found:
Top regression line parameter values:
a: 0.000202798
b: 0.0872922
c: -30.88805
d: 1827.14113
Bottom regression line parameter values:
a: 0.000138314
b: -0.0768236
c: 13.90555
d: -765.8892
📊Polynomial Regression Oscillator:
This publication also includes the oscillator version of the this model which is displayed at the bottom of the screen. The oscillator applies a logarithmic transformation to the price and the regression lines using the formula log10(x) .
The log-transformed price is then normalized using min-max normalization relative to the log-transformed top and bottom regression line with the formula:
normalized price = log(close) - log(bottom regression line) / log(top regression line) - log(bottom regression line)
This transformation results in a price value between 0 and 1 between both the regression lines.
🔍Interpretation of the Model:
In general, the red area represents a caution zone, as historically, the price has often been near its cycle market top within this range. On the other hand, the green area is considered an area of opportunity, as historically, it has corresponded to the market bottom.
The top regression line serves as a signal for the absolute market cycle peak, while the bottom regression line indicates the absolute market cycle bottom.
Additionally, this model provides a predicted range for Bitcoin's future price movements, which can be used to make extrapolated predictions. We will explore this further below.
🔮Future Predictions:
Finally, let's discuss what this model actually predicts for the potential upcoming market cycle top and the corresponding market cycle bottom. In our previous post here , a cycle interval analysis was performed to predict a likely time window for the next cycle top and bottom:
In the image, it is predicted that the next top-to-top cycle interval will be 208 weeks, which translates to November 3rd, 2025. It is also predicted that the bottom-to-top cycle interval will be 152 weeks, which corresponds to October 13th, 2025. On the macro level, these two dates align quite well. For our prediction, we take the average of these two dates: October 24th 2025. This will be our target date for the bull cycle top.
Now, let's do the same for the upcoming cycle bottom. The bottom-to-bottom cycle interval is predicted to be 205 weeks, which translates to October 19th, 2026, and the top-to-bottom cycle interval is predicted to be 259 weeks, which corresponds to October 26th, 2026. We then take the average of these two dates, predicting a bear cycle bottom date target of October 19th, 2026.
Now that we have our predicted top and bottom cycle date targets, we can simply reference these two dates to our model, giving us the Bitcoin top price prediction in the range of 152,000 in Q4 2025 and a subsequent bottom price prediction in the range of 46,500 in Q4 2026.
For those interested in understanding what this specifically means for the predicted diminishing return top and bottom cycle values, the image below displays these predicted values. The new values are highlighted in yellow:
And of course, keep in mind that these targets are just rough estimates. While we've done our best to estimate these targets through a data-driven approach, markets will always remain unpredictable in nature. What are your targets? Feel free to share them in the comment section below.
Super Cycle Low FinderHow the Indicator Works
1. Inputs
Users can adjust the cycle lengths:
Daily Cycle: Default is 40 days (within 36-44 days).
Weekly Cycle: Default is 26 weeks (182 days, within 22-31 weeks).
Yearly Cycle: Default is 4 years (1460 days).
2. Cycle Low Detection
Function: detect_cycle_low finds the lowest low over the specified period and confirms it with a bullish candle (close > open).
Timeframes: Daily lows are calculated directly; weekly and yearly lows use request.security to fetch data from higher timeframes.
3. Half Cycle Lows
Detected over half the cycle length, plotted to show mid-cycle strength or weakness.
4. Cycle Translation
Logic: Compares the position of the highest high to the cycle’s midpoint.
Output: "R" for right translated (bullish), "L" for left translated (bearish), displayed above bars.
5. Cycle Failure
Flags when a new low falls below the previous cycle low, indicating a breakdown.
6. Visualization
Cycle Lows: Diamonds below bars (yellow for daily, green for weekly, blue for yearly).
Half Cycle Lows: Circles below bars (orange, lime, aqua).
Translations: "R" or "L" above bars in distinct colors.
Failures: Downward triangles below bars (red, orange, purple).
TimeMapTimeMap is a visual price-reference indicator designed to help traders rapidly visualize how current price levels relate to significant historical closing prices. It overlays your chart with reference lines representing past weekly, monthly, quarterly (3-month), semi-annual (6-month), and annual closing prices. By clearly plotting these historical price references, TimeMap helps traders quickly gauge price position relative to historical market structure, aiding in the identification of trends, support/resistance levels, and potential reversals.
How it Works:
The indicator calculates the precise number of historical bars corresponding to weekly, monthly, quarterly, semi-annual, and annual intervals, dynamically adjusting according to your chart’s timeframe (intraday, daily, weekly, monthly) and chosen market type (Stocks US, Crypto, Forex, or Futures). Historical closing prices from these periods are plotted directly on your chart as horizontal reference lines.
For intraday traders, the script accurately calculates historical offsets considering regular and extended trading sessions (e.g., pre-market and after-hours sessions for US stocks), ensuring correct positioning of historical lines.
User-Configurable Inputs Explained in Detail:
Market Type:
Allows you to specify your trading instrument type, automatically adjusting calculations for:
- Stocks US (default): 390 minutes per regular session (780 minutes if extended hours enabled), 5 trading days/week.
- Crypto: 1440 minutes/day, 7 trading days/week.
- Forex: 1440 minutes/day, 5 trading days/week.
- Futures: 1320 minutes/day, 5 trading days/week.
Show Weekly Close:
When enabled, plots a line at the exact closing price from one week ago. Provides short-term context and helps identify recent price momentum.
Show Monthly Close:
When enabled, plots a line at the exact closing price from one month ago. Helpful for evaluating medium-term price positioning and monthly trend strength.
Show 3-Month Close:
When enabled, plots a line at the exact closing price from three months ago. Useful for assessing quarterly market shifts, intermediate trend changes, and broader market sentiment.
Show 6-Month Close:
When enabled, plots a line at the exact closing price from six months ago. Useful for identifying semi-annual trends, significant price pivots, and longer-term support/resistance levels.
Show 1-Year Close:
When enabled, plots a line at the exact closing price from one year ago. Excellent for assessing long-term market direction and key annual price levels.
Enable Smoothing:
Activates a Simple Moving Average (SMA) smoothing of historical reference lines, reducing volatility and providing clearer visual references. Recommended for traders preferring less volatile reference levels.
Smoothing Length:
Determines the number of bars used in calculating the SMA smoothing of historical lines. Higher values result in smoother but slightly delayed reference lines; lower values offer more immediate yet more volatile levels.
Use Extended Hours (Intraday Only):
When enabled (only applicable for Stocks US), it accounts for pre-market and after-hours trading sessions, providing accurate intraday historical line calculations based on extended sessions (typically 780 minutes/day total).
Important Notes and Compliance:
- This indicator does not provide trading signals, recommendations, or predictions. It serves purely as a visual analytical tool to supplement traders’ existing methods.
- Historical lines plotted are strictly based on past available price data; the indicator never accesses future data or data outside the scope of Pine Script’s standard capabilities.
- The script incorporates built-in logic to avoid runtime errors if insufficient historical data exists for a selected timeframe, ensuring robustness even with limited historical bars.
- TimeMap is original work developed exclusively by Julien Eche (@Julien_Eche). It does not reuse or replicate third-party or existing open-source scripts.
Recommended Best Practices:
- Use TimeMap as a complementary analytical reference, not as a standalone strategy or trade decision-making tool.
- Adapt displayed historical periods and smoothing settings based on your trading style and market approach.
- Default plot colors are optimized for readability on dark-background charts; adjust as necessary according to your preference and chart color scheme.
This script is published open-source to benefit the entire TradingView community and fully complies with all TradingView script publishing rules and guidelines.
