Neon Waves Oscillator [NinjADeviL]Neon Waves Oscillator
The Neon Waves Oscillator is inspired by modern neon-style visual design and displays four smooth waves representing normalized price movement using ATR. The waves highlight changes in momentum, volatility, and market rhythm in a clean, sharp, and visually appealing way, enhanced by a soft glow effect that adds depth and clarity.
Key Features:
🌈 Four smooth neon-colored waves
⚡ ATR-based normalization for consistent behavior across all assets
🎨 Dynamic glow background for a rich visual appearance
🔎 Helps identify momentum shifts, volatility cycles, and trend transitions
🧠 EMA-based smoothing for stability and high accuracy
Ideal for traders focused on Price Action, Momentum, or anyone who prefers a clean, intuitive, and modern visual oscillator.
Developed by NinjADeviL.
Search in scripts for "Cycle"
Quantura - Average Intraday Candle VolumeIntroduction
“Quantura – Average Intraday Candle Volume” is a quantitative visualization tool that calculates and displays the average traded volume for each intraday time position based on a user-defined historical lookback period. It allows traders to analyze recurring intraday volume patterns, identify high-activity sessions, and detect liquidity shifts throughout the trading day.
Originality & Value
This indicator goes beyond standard volume averages by normalizing and aligning volume data according to the time of day. Instead of simply smoothing recent bars, it builds an intraday volume profile based on historical daily averages, enabling users to understand when during the day volume typically peaks or drops.
Its originality and usefulness come from:
Converting standard volume data into time-aligned intraday averages.
Visualization of historical intraday liquidity behavior, not just total daily volume.
Dynamic scaling using normalization and transparency to emphasize active and quiet periods.
Optional day-separator lines for precise intraday structure recognition.
Gradient-based coloring for better visual interpretation of volume intensity.
Functionality & Core Logic
The indicator divides each day into discrete intraday time positions (based on chart timeframe).
For each position, it stores and updates historical volume values across the selected number of days.
It calculates an average volume per time position by aggregating all stored values and dividing them by the number of valid days.
The result is plotted as a continuous histogram showing typical intraday volume distribution.
The bar colors and transparency dynamically reflect the relative intensity of volume at each point in the day.
Parameters & Customization
Number of Days for Averaging: Defines how many past days are included in the volume average calculation (default: 365).
UTC Offset: Allows synchronization of intraday cycles with local or exchange time zones.
Base Color: Sets the main color for plotted volume columns.
Color Mode: Choose between “Gradient” (transparency dynamically adjusts by intensity) or “Normal” (fixed opacity).
Day Line: Toggles dashed vertical lines marking the start of each trading day.
Visualization & Display
Volume is plotted as a series of histogram bars, each representing the average volume for a specific intraday time position.
A gradient color mode enhances readability by fading lower-intensity areas and highlighting high-volume regions.
Optional day-separator lines visually segment historical sessions for easy reference.
Works seamlessly across all chart timeframes that divide the 24-hour day into regular bar intervals.
Use Cases
Identify when trading activity typically peaks (e.g., session opens, news windows, or overlapping markets).
Compare current intraday volume to historical averages for early anomaly detection.
Enhance algorithmic or discretionary strategies that depend on volume-timing alignment.
Combine with volatility or price structure indicators to confirm market activity zones.
Evaluate session consistency across different time zones using the UTC offset parameter.
Limitations & Recommendations
The indicator requires intraday data (below 1D resolution) to function properly.
Volume behavior may vary across brokers and assets; adjust averaging period accordingly.
Does not predict price movement — it provides volume-based context for analysis.
Works best when combined with structure or momentum-based indicators.
Markets & Timeframes
Compatible with all intraday markets — including crypto, Forex, equities, and futures — and all intraday timeframes (from 1 minute to 4 hours). It is particularly valuable for analyzing assets with continuous 24-hour trading activity.
Author & Access
Developed 100% by Quantura. Published as a Open-source script indicator. Access is free.
Important
This description complies with TradingView’s Script Publishing and House Rules. It provides a clear explanation of the indicator’s originality, logic, and purpose, without any unrealistic performance or predictive claims.
Seasonal Performance Analyzer | AlphaNatt📊 Seasonal Performance Analyzer | AlphaNatt
📈 Overview
Unlock the power of seasonality with this advanced visualization tool that reveals hidden patterns in market behavior. The Seasonal Performance Analyzer overlays multiple years of historical data for any selected month, allowing traders to identify recurring seasonal trends, anomalies, and potential trading opportunities.
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✨ Key Features
🎯 Month-by-Month Analysis
- Isolate and analyze any single month across multiple years
- Compare up to 20 years of historical performance
- Instantly visualize seasonal patterns and trends
📊 Advanced Visualization
- Beautiful gradient coloring from oldest (light blue) to newest (dark blue) years
- Clean axis system with labeled days and months
- Professional grid layout for easy value reading
- Optional average line showing mean performance across all years
🔧 Flexible Display Options
- Normalize to 100: Start each year at a base value of 100 for easy percentage comparison
- Raw Price Mode: View actual price movements without normalization
- Customizable Colors: Adjust gradient colors and transparency to your preference
- Toggle Features: Show/hide year labels, average line, and day labels
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⚙️ Input Parameters
📅 Time Settings
- Select Month: Choose any month (1-12) for analysis
- Years to Display: Show 1-20 years of historical data
- Include Current Year: Option to include incomplete current year data
🎨 Visual Settings
- Line Transparency: Adjust the opacity of year lines (0-100)
- Gradient Colors: Customize oldest and newest year colors
- Average Line: Color and width customization
- Legend Display: Toggle year labels on/off
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💡 Use Cases
1. Seasonal Trading Strategies
Identify months with consistent directional bias for seasonal entry/exit timing
2. Risk Management
Spot historically volatile periods and adjust position sizes accordingly
3. Pattern Recognition
Discover recurring intra-month patterns like "first week strength" or "mid-month reversals"
4. Comparative Analysis
Compare current month's performance against historical averages to gauge relative strength
5. Anomaly Detection
Quickly identify years that deviated significantly from typical seasonal patterns
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📖 How to Use
Step 1: Add the indicator to your chart
Step 2: Select the month you want to analyze (default: November)
Step 3: Choose how many years of history to display
Step 4: Toggle normalization based on your analysis needs
Step 5: Look for patterns:
• Consistent trends across multiple years
• Divergences from the average line
• Specific days with recurring movements
• Years that broke the seasonal pattern
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🎯 Pro Tips
✅ For Swing Traders: Focus on months showing consistent multi-day trends
✅ For Day Traders: Identify specific days within a month that show repetitive behavior
✅ For Investors: Use normalized view to compare percentage gains across years
✅ For Risk Analysis: The wider the spread between years, the less reliable the seasonal pattern
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📊 Example Insights
This indicator can reveal powerful insights such as:
- "November typically shows strength in the first two weeks"
- "Years above the average line tend to continue outperforming"
- "Day 15-20 historically shows consolidation patterns"
- "Election years show different patterns than non-election years"
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⚠️ Important Notes
- Past performance does not guarantee future results
- Seasonality is one factor among many - combine with other analysis methods
- Major events can override seasonal patterns
- Works best on assets with long price history
- More years of data generally provides more reliable patterns
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🏆 Perfect For:
- Seasonal traders
- Swing traders looking for optimal entry months
- Analysts studying market cycles
- Anyone interested in historical market patterns
- Risk managers assessing seasonal volatility
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Created by AlphaNatt - Empowering traders with advanced seasonal analysis
Version: 1.0
Pine Script: v6
License: Mozilla Public License 2.0
DTCC RECAPS Dates 2020-2025This is a simple indicator which marks the RECAPS dates of the DTCC, during the periods of 2020 to 2025.
These dates have marked clear settlement squeezes in the past, such as GME's squeeze of January 2021.
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The Depository Trust & Clearing Corporation (DTCC) has published the 2025 schedule for its Reconfirmation and Re-pricing Service (RECAPS) through the National Securities Clearing Corporation (NSCC). RECAPS is a monthly process for comparing and re-pricing eligible equities, municipals, corporate bonds, and Unit Investment Trusts (UITs) that have aged two business days or more .
At its core, the Reconfirmation and Re-pricing Service (RECAPS) is a risk management tool used by the National Securities Clearing Corporation (NSCC), a subsidiary of the DTCC. Its primary purpose is to reduce the risks associated with aged, unsettled trades in the U.S. securities market .
When a trade is executed, it is sent to the NSCC for clearing and settlement. However, for various reasons, some trades may not settle on their scheduled date and become "aged." These unsettled trades create risk for both the trading parties and the clearinghouse (NSCC) because the value of the underlying securities can change over time. If a trade fails to settle and one of the parties defaults, the NSCC may have to step in to complete the transaction at the current market price, which could result in a loss.
RECAPS mitigates this risk by systematically re-pricing these aged, open trading obligations to the current market value. This process ensures that the financial obligations of the clearing members accurately reflect the present value of the securities, preventing the accumulation of significant, unmanaged market risk .
Detailed Mechanics: How Does it Work?
The RECAPS process revolves around two key dates you asked about: the RECAPS Date and the Settlement Date .
The RECAPS Date: On this day, the NSCC runs a process to identify all eligible trades that have remained unsettled for two business days or more. These "aged" trades are then re-priced to the current market value. This re-pricing is not just a simple recalculation; it generates new settlement instructions. The original, unsettled trade is effectively cancelled and replaced with a new one at the current market price. This is done through the NSCC's Obligation Warehouse.
The Settlement Date: This is typically the business day following the RECAPS date. On this date, the financial settlement of the re-priced trades occurs. The difference in value between the original trade price and the new, re-priced value is settled between the two trading parties. This "mark-to-market" adjustment is processed through the members' settlement accounts at the DTCC.
Essentially, the process ensures that any gains or losses due to price changes in the underlying security are realized and settled periodically, rather than being deferred until the trade is ultimately settled or cancelled.
Are These Dates Used to Check Margin Requirements?
Yes, indirectly, this process is closely tied to managing margin and collateral requirements for NSCC members. Here’s how:
The NSCC requires its members to post collateral to a clearing fund, which acts as a mutualized guarantee against defaults. The amount of collateral each member must provide is calculated based on their potential risk exposure to the clearinghouse.
By re-pricing aged trades to current market values through RECAPS, the NSCC gets a more accurate picture of each member's outstanding obligations and, therefore, their current risk profile. If a member has a large number of unsettled trades that have moved against them in value, the re-pricing will crystallize that loss, which will be settled the next day.
This regular re-pricing and settlement of aged trades prevent the build-up of large, unrealized losses that could increase a member's risk profile beyond what their posted collateral can cover. While RECAPS is not the only mechanism for calculating margin (the NSCC has a complex system for daily margin calls based on overall portfolio risk), it is a crucial component for managing the specific risk posed by aged, unsettled transactions. It ensures that the value of these obligations is kept current, which in turn helps ensure that collateral levels remain adequate.
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Future dates of 2025:
- November 12, 2025 (Wed)
- November 25, 2025 (Tue)
- December 11, 2025 (Thu)
- December 29, 2025 (Mon)
The dates for 2026 haven't been published yet at this time.
The RECAPS process is essentially the industry's way of retrying the settlement of all unresolved FTDs, netting outstanding obligations, and gradually forcing resolution (either delivery or buy-in). Monitoring RECAPS cycles is one way to track the lifecycle, accumulation, and eventual resolution (or persistence) of failures to deliver in the U.S. market.
The US Stock market has become a game of settlement dates and FTDs, therefore this can be useful to track.
Squeeze Hour Frequency [CHE]Squeeze Hour Frequency (ATR-PR) — Standalone — Tracks daily squeeze occurrences by hour to reveal time-based volatility patterns
Summary
This indicator identifies periods of unusually low volatility, defined as squeezes, and tallies their frequency across each hour of the day over historical trading sessions. By aggregating counts into a sortable table, it helps users spot hours prone to these conditions, enabling better scheduling of trading activity to avoid or target specific intraday regimes. Signals gain robustness through percentile-based detection that adapts to recent volatility history, differing from fixed-threshold methods by focusing on relative lowness rather than absolute levels, which reduces false positives in varying market environments.
Motivation: Why this design?
Traders often face uneven intraday volatility, with certain hours showing clustered low-activity phases that precede or follow breakouts, leading to mistimed entries or overlooked calm periods. The core idea of hourly squeeze frequency addresses this by binning low-volatility events into 24 hourly slots and counting distinct daily occurrences, providing a historical profile of when squeezes cluster. This reveals time-of-day biases without relying on real-time alerts, allowing proactive adjustments to session focus.
What’s different vs. standard approaches?
- Reference baseline: Classical volatility tools like simple moving average crossovers or fixed ATR thresholds, which flag squeezes uniformly across the day.
- Architecture differences:
- Uses persistent arrays to track one squeeze per hour per day, preventing overcounting within sessions.
- Employs custom sorting on ratio arrays for dynamic table display, prioritizing top or bottom performers.
- Handles timezones explicitly to ensure consistent binning across global assets.
- Practical effect: Charts show a persistent table ranking hours by squeeze share, making intraday patterns immediately visible—such as a top hour capturing over 20 percent of total events—unlike static overlays that ignore temporal distribution, which matters for avoiding low-liquidity traps in crypto or forex.
How it works (technical)
The indicator first computes a rolling volatility measure over a specified lookback period. It then derives a relative ranking of the current value against recent history within a window of bars. A squeeze is flagged when this ranking falls below a user-defined cutoff, indicating the value is among the lowest in the recent sample.
On each bar, the local hour is extracted using the selected timezone. If a squeeze occurs and the bar has price data, the count for that hour increments only if no prior mark exists for the current day, using a persistent array to store the last marked day per hour. This ensures one tally per unique trading day per slot.
At the final bar, arrays compile counts and ratios for all 24 hours, where the ratio represents each hour's share of total squeezes observed. These are sorted ascending or descending based on display mode, and the top or bottom subset populates the table. Background shading highlights live squeezes in red for visual confirmation. Initialization uses zero-filled arrays for counts and negative seeds for day tracking, with state persisting across bars via variable declarations.
No higher timeframe data is pulled, so there is no repaint risk from external fetches; all logic runs on confirmed bars.
Parameter Guide
ATR Length — Controls the lookback for the volatility measure, influencing sensitivity to short-term fluctuations; shorter values increase responsiveness but add noise, longer ones smooth for stability — Default: 14 — Trade-offs/Tips: Use 10-20 for intraday charts to balance quick detection with fewer false squeezes; test on historical data to avoid over-smoothing in trending markets.
Percentile Window (bars) — Sets the history depth for ranking the current volatility value, affecting how "low" is defined relative to past; wider windows emphasize long-term norms — Default: 252 — Trade-offs/Tips: 100-300 bars suit daily cycles; narrower for fast assets like crypto to catch recent regimes, but risks instability in sparse data.
Squeeze threshold (PR < x) — Defines the cutoff for flagging low relative volatility, where values below this mark a squeeze; lower thresholds tighten detection for rarer events — Default: 10.0 — Trade-offs/Tips: 5-15 percent for conservative signals reducing false positives; raise to 20 for more frequent highlights in high-vol environments, monitoring for increased noise.
Timezone — Specifies the reference for hourly binning, ensuring alignment with market sessions — Default: Exchange — Trade-offs/Tips: Set to "America/New_York" for US assets; mismatches can skew counts, so verify against chart timezone.
Show Table — Toggles the results display, essential for reviewing frequencies — Default: true — Trade-offs/Tips: Disable on mobile for performance; pair with position tweaks for clean overlays.
Pos — Places the table on the chart pane — Default: Top Right — Trade-offs/Tips: Bottom Left avoids candle occlusion on volatile charts.
Font — Adjusts text readability in the table — Default: normal — Trade-offs/Tips: Tiny for dense views, large for emphasis on key hours.
Dark — Applies high-contrast colors for visibility — Default: true — Trade-offs/Tips: Toggle false in light themes to prevent washout.
Display — Filters table rows to focus on extremes or full list — Default: All — Trade-offs/Tips: Top 3 for quick scans of risky hours; Bottom 3 highlights safe low-squeeze periods.
Reading & Interpretation
Red background shading appears on bars meeting the squeeze condition, signaling current low relative volatility. The table lists hours as "H0" to "H23", with columns for daily squeeze counts, percentage share of total squeezes (summing to 100 percent across hours), and an arrow marker on the top hour. A summary row above details the peak count, its share, and the leading hour. A label at the last bar recaps total days observed, data-valid days, and top hour stats. Rising shares indicate clustering, suggesting regime persistence in that slot.
Practical Workflows & Combinations
- Trend following: Scan for hours with low squeeze shares to enter during stable regimes; confirm with higher highs or lower lows on the 15-minute chart, avoiding top-share hours post-news like tariff announcements.
- Exits/Stops: Tighten stops in high-share hours to guard against sudden vol spikes; use the table to shift to conservative sizing outside peak squeeze times.
- Multi-asset/Multi-TF: Defaults work across crypto pairs on 5-60 minute timeframes; for stocks, widen percentile window to 500 bars. Combine with volume oscillators—enter only if squeeze count is below average for the asset.
Behavior, Constraints & Performance
Logic executes on closed bars, with live bars updating counts provisionally but finalizing on confirmation; table refreshes only at the last bar, avoiding intrabar flicker. No security calls or higher timeframes, so no repaint from external data. Resources include a 5000-bar history limit, loops up to 24 iterations for sorting and totals, and arrays sized to 24 elements; labels and table are capped at 500 each for efficiency. Known limits: Skips hours without bars (e.g., weekends), assumes uniform data availability, and may undercount in sparse sessions; timezone shifts can alter profiles without warning.
Sensible Defaults & Quick Tuning
Start with ATR Length at 14, Percentile Window at 252, and threshold at 10.0 for broad crypto use. If too many squeezes flag (noisy table), raise threshold to 15.0 and narrow window to 100 for stricter relative lowness. For sluggish detection in calm markets, drop ATR Length to 10 and threshold to 5.0 to capture subtler dips. In high-vol assets, widen window to 500 and threshold to 20.0 for stability.
What this indicator is—and isn’t
This is a historical frequency tracker and visualization layer for intraday volatility patterns, best as a filter in multi-tool setups. It is not a standalone signal generator, predictive model, or risk manager—pair it with price action, news filters, and position sizing rules.
Disclaimer
The content provided, including all code and materials, is strictly for educational and informational purposes only. It is not intended as, and should not be interpreted as, financial advice, a recommendation to buy or sell any financial instrument, or an offer of any financial product or service. All strategies, tools, and examples discussed are provided for illustrative purposes to demonstrate coding techniques and the functionality of Pine Script within a trading context.
Any results from strategies or tools provided are hypothetical, and past performance is not indicative of future results. Trading and investing involve high risk, including the potential loss of principal, and may not be suitable for all individuals. Before making any trading decisions, please consult with a qualified financial professional to understand the risks involved.
By using this script, you acknowledge and agree that any trading decisions are made solely at your discretion and risk.
Do not use this indicator on Heikin-Ashi, Renko, Kagi, Point-and-Figure, or Range charts, as these chart types can produce unrealistic results for signal markers and alerts.
Best regards and happy trading
Chervolino
Thanks to Duyck
for the ma sorter
WRESBAL ROC Oscillator (Clean)This indicator tracks the rate of change in Federal Reserve reserve balances (WRESBAL) to visualize shifts in systemic liquidity. It measures how quickly reserves are expanding or contracting over a chosen lookback window (default 26 weeks), then smooths the result to highlight durable macro trends rather than short-term noise.
Green = expanding reserves → liquidity easing → risk-asset support
Red = contracting reserves → liquidity tightening → headwind for risk assets
The oscillator is designed for macro context rather than short-term trading. It correlates strongly with major equity and credit cycles, often leading inflection points in the S&P 500 and Nasdaq by several weeks.
Use it to identify transitions between QE (quantitative easing) and QT (quantitative tightening) regimes and to gauge the liquidity environment driving broad market behavior.
Nth Candle by exp3rtsThis lightweight and versatile TradingView indicator highlights every Xth candle on your chart, making it easy to spot cyclical price behavior or track specific intervals in the market.
- Custom Interval – Choose how often candles should be highlighted (e.g., every 5th, 10th, or
20th bar).
- Color Coding – Highlighted candles are shaded green if bullish and red if bearish, giving you
quick visual insights into momentum at those intervals.
- Clean Overlay – The indicator draws directly on your main chart without clutter, so you can
combine it with your favorite setups and strategies.
Use this tool to:
1) Identify repeating patterns and cycles
2) Mark periodic reference candles
3) Support discretionary trading decisions with clear visual cues
Global Liquidity Proxy vs BitcoinGlobal Liquidity Proxy vs Bitcoin. Helps to understand the cycles with liquidty.
Planetary Signs - CEPlanetary Signs - Community Edition
Welcome to the Planetary Signs - Community Edition , a specialized tool designed to enhance W.D. Gann-inspired trading by highlighting zodiac sign transitions for selected planets. This indicator marks when planets enter specific zodiac signs, which may correlate with market turning points, making it ideal for traders analyzing equities, forex, commodities, and cryptocurrencies.
Overview
The Planetary Signs - Community Edition calculates the ecliptic longitude of a chosen planet (Sun, Moon, Mercury, Venus, Mars, Jupiter, Saturn, Uranus, Neptune, or Pluto) and highlights periods when it enters user-selected zodiac signs (Aries, Taurus, Gemini, etc.). Supporting heliocentric and geocentric modes, the script plots sign transitions with minute-level accuracy, syncing perfectly with chart timeframes. Traders can customize colors for each sign and add multiple instances for multi-planet analysis, aligning with Gann’s belief that zodiac transitions influence market trends.
Key Features
Highlights zodiac sign transitions for ten celestial bodies (Sun, Moon, Mercury, Venus, Mars, Jupiter, Saturn, Uranus, Neptune, Pluto)
Supports heliocentric and geocentric modes (Pluto heliocentric-only; Sun and Moon geocentric)
Allows selection of one or multiple zodiac signs with customizable highlight colors
Plots vertical lines and labels (e.g., “☿ 0 ♈ Aries”) at sign transitions with minute-level accuracy
Projects future sign transitions up to 120 days with daily resolution
Enables multiple script instances for tracking different planets or signs on the same chart
How to Use
Access the script’s settings to configure preferences
Choose a planet from the Sun, Moon, Mercury, Venus, Mars, Jupiter, Saturn, Uranus, Neptune, or Pluto
Select one or more zodiac signs (e.g., Aries, Taurus) to highlight
Customize the highlight color for each selected zodiac sign
Select heliocentric or geocentric mode for calculations
Review highlighted periods and labeled lines to identify zodiac sign transitions
Use transitions to anticipate potential market turning points, integrating Gann’s astrological principles
Get Started
The Planetary Signs - Community Edition provides full functionality for astrological market analysis. Designed to highlight Gann’s zodiac cycles, this tool empowers traders to explore celestial transitions. Trade wisely and harness the power of planetary alignments!
Muzyorae - ICT Quarterly Theory (Intraday)ICT Quarterly Theory — Intraday
What it is
ICT’s Quarterly Theory models the intraday session as repeating cycles of four “quarters.” On NY time, a trading day is split into four macro quarters of 6 hours each:
Q1: 00:00–06:00 NY (Asia / pre-London)
Q2: 06:00–12:00 NY (London–NY overlap, AM session)
Q3: 12:00–18:00 NY (Midday / PM session)
Q4: 18:00–24:00 NY (Asia re-open / late session)
Each macro quarter can be further subdivided into micro quarters of 90 minutes (q1–q4). This fractal view helps traders frame accumulation → expansion → distribution → liquidation phases and align executions with time-of-day liquidity.
Why it matters
Orderflow, liquidity raids, and displacement are highly time-dependent. Marking the quarters makes it easier to:
Anticipate when the market is likely to deliver the day’s expansion (often Q2) versus retracement/distribution (often Q3) or late liquidity runs (often Q4).
Compare today’s behavior to prior days within the same quarter windows.
Anchor bias, entries, and risk management to session-specific highs/lows rather than arbitrary clock times.
What this indicator shows
Macro quarters (6h): Vertical lines and optional labels (Q1–Q4) on NY time.
Micro quarters (90m): Optional finer verticals inside each macro quarter (q1–q4) for precise timing.
True Open (Q2 AM): Optional line at the AM session’s true open (default 06:00 NY) to study premium/discount development from the intraday benchmark.
Futures Sunday handling: Optional treatment of Sunday 18:00 NY as Q4 (useful for FX/futures).
Label controls: Choose above/below placement, offset, size, and colors; micro labels can be toggled independently.
Performance-friendly: De-duplicated labels and a look-back “days to show” setting keep charts clean.
How to use
Timeframe: Works on intraday charts (1–60m). 5–15m is a common balance of signal vs. noise.
Bias framing:
Map Asia (Q1), AM expansion (Q2), midday distribution (Q3), late session runs (Q4).
Compare where the daily range forms versus the True Open to gauge premium/discount and likely continuations.
Execution: Look for standard ICT tools (liquidity sweeps, FVGs, displacement, PD arrays) inside the active quarter to avoid fighting time-of-day flow.
Review: Scroll back multiple days and evaluate where the day’s high/low typically forms relative to Q2–Q3; adapt expectations.
Settings (high level)
Show Macro Labels / Micro Lines / Micro Labels
Label position (above/below), X-shift, colors, sizes
Days to show, de-dup window (prevents label overlaps)
Q2 True Open toggle and extension (doesn't work)
Include Sunday as Q4 (18:00 NY)
Notes
Quarter boundaries are fixed to America/New York session logic to match ICT timing.
This is a context tool; it does not generate buy/sell signals. Combine with your existing execution model.
Past behavior does not guarantee future results. Use proper risk management.
Gann Static Square of 9 - CEGann Static Square of 9 - Community Edition
Welcome to the Gann Static Square of 9 - Community Edition, a meticulously crafted tool designed to empower traders with the timeless principles of W.D. Gann’s Square of 9 methodology. This indicator is tailored for the TradingView community and Gann Traders, providing a robust solution for analyzing price and time dynamics across various markets.
Overview
The Gann Static Square of 9 harnesses the mathematical precision of Gann’s Square of 9 chart, plotting key price and time levels based on a fixed starting point of 1. Unlike its dynamic counterpart , this static version uses a consistent origin, making it ideal for traders seeking to map Gann’s geometric angles (45°, 90°, 135°, 180°, 225°, 270°, 315°, and 360°) with a standardized framework. By adjusting the price and time units, users can tailor the indicator to suit any asset, from equities and forex to commodities and cryptocurrencies.
Key Features
Fixed Starting Point: Begins calculations at a base value of 1, providing a standardized approach to plotting Gann’s Square of 9 levels.
Comprehensive Angle Projections: Plots eight critical Gann angles (45°, 90°, 135°, 180°, 225°, 270°, 315°, and 360°), enabling precise identification of support, resistance, and time-based targets.
Customizable Price and Time Units: Adjust the price unit (Y-axis) and time unit (X-axis) to align with the specific characteristics of your chosen market, ensuring optimal fit for price action and volatility.
Horizontal and Vertical Levels: Enable horizontal price levels to identify key support and resistance zones, and vertical time levels to pinpoint potential market turning points.
Revolution Control: Extend projections across multiple 360° cycles to uncover long-term price and time objectives, with user-defined revolution counts.
Customizable Aesthetics: Assign distinct colors to each angle for enhanced chart clarity and visual differentiation.
and more!
How It Works
Configure Settings: Set the price and time units to match your asset’s characteristics, and select the desired number of revolutions to project future levels.
Enable Levels: Choose which Gann angles (45° to 360°) to display, tailoring the indicator to your analysis needs.
Visualize Key Levels: The indicator plots horizontal price levels and optional vertical time levels, each labeled with its corresponding angle and price/time value.
Analyze and Trade: Leverage the plotted levels to identify critical support, resistance, and time-based turning points, enhancing your trading strategy with Gann’s proven methodology.
Get Started
As a token of appreciation for the TradingView community, and Gann traders, this Community Edition is provided free of charge. Trade safe and enjoy!
US Presidents 1920–2024Description:
This indicator displays all U.S. presidential elections from 1920 to 2024 on your chart.
Features:
Vertical lines at the date of each presidential election.
Line color by party:
Red = Republican
Blue = Democrat
Gray = Other/None
Labels showing the name of each president.
Modern flag style: Presidents from 1900 onward are highlighted as modern, giving clear historical separation.
Fully overlayed on the price chart for timeline context.
Customizable: Label position (above/below bar) and line width.
Use case: Useful for analyzing modern U.S. presidential cycles, market reactions to elections, or quickly referencing recent presidents directly on charts.
Auto-Fit Growth Trendline# **Theoretical Algorithmic Principles of the Auto-Fit Growth Trendline (AFGT)**
## **🎯 What Does This Algorithm Do?**
The Auto-Fit Growth Trendline is an advanced technical analysis system that **automates the identification of long-term growth trends** and **projects future price levels** based on historical cyclical patterns.
### **Primary Functionality:**
- **Automatically detects** the most significant lows in regular periods (monthly, quarterly, semi-annually, annually)
- **Constructs a dynamic trendline** that connects these historical lows
- **Projects the trend into the future** with high mathematical precision
- **Generates Fibonacci bands** that act as dynamic support and resistance levels
- **Automatically adapts** to different timeframes and market conditions
### **Strategic Purpose:**
The algorithm is designed to identify **fundamental value zones** where price has historically found support, enabling traders to:
- Identify optimal entry points for long positions
- Establish realistic price targets based on mathematical projections
- Recognize dynamic support and resistance levels
- Anticipate long-term price movements
---
## **🧮 Core Mathematical Foundations**
### **Adaptive Temporal Segmentation Theory**
The algorithm is based on **dynamic temporal partition theory**, where time is divided into mathematically coherent uniform intervals. It uses modular transformations to create bijective mappings between continuous timestamps and discrete periods, ensuring each temporal point belongs uniquely to a specific period.
**What does this achieve?** It allows the algorithm to automatically identify natural market cycles (annual, quarterly, etc.) without manual intervention, adapting to the inherent periodicity of each asset.
The temporal mapping function implements a **discrete affine transformation** that normalizes different frequencies (monthly, quarterly, semi-annual, annual) to a space of unique identifiers, enabling consistent cross-temporal comparative analysis.
---
## **📊 Local Extrema Detection Theory**
### **Multi-Point Retrospective Validation Principle**
Local minima detection is founded on **relative extrema theory with sliding window**. Instead of using a simple minimum finder, it implements a cross-validation system that examines the persistence of the extremum across multiple historical periods.
**What problem does this solve?** It eliminates false minima caused by temporal volatility, identifying only those points that represent true historical support levels with statistical significance.
This approach is based on the **statistical confirmation principle**, where a minimum is only considered valid if it maintains its extremum condition during a defined observation period, significantly reducing false positives caused by transitory volatility.
---
## **🔬 Robust Interpolation Theory with Outlier Control**
### **Contextual Adaptive Interpolation Model**
The mathematical core uses **piecewise linear interpolation with adaptive outlier correction**. The key innovation lies in implementing a **contextual anomaly detector** that identifies not only absolute extreme values, but relative deviations to the local context.
**Why is this important?** Financial markets contain extreme events (crashes, bubbles) that can distort projections. This system identifies and appropriately weights them without completely eliminating them, preserving directional information while attenuating distortions.
### **Implicit Bayesian Smoothing Algorithm**
When an outlier is detected (deviation >300% of local average), the system applies a **simplified Kalman filter** that combines the current observation with a local trend estimation, using a weight factor that preserves directional information while attenuating extreme fluctuations.
---
## **📈 Stabilized Extrapolation Theory**
### **Exponential Growth Model with Dampening**
Extrapolation is based on a **modified exponential growth model with progressive dampening**. It uses multiple historical points to calculate local growth ratios, implements statistical filtering to eliminate outliers, and applies a dampening factor that increases with extrapolation distance.
**What advantage does this offer?** Long-term projections in finance tend to be exponentially unrealistic. This system maintains short-to-medium term accuracy while converging toward realistic long-term projections, avoiding the typical "exponential explosions" of other methods.
### **Asymptotic Convergence Principle**
For long-term projections, the algorithm implements **controlled asymptotic convergence**, where growth ratios gradually converge toward pre-established limits, avoiding unrealistic exponential projections while preserving short-to-medium term accuracy.
---
## **🌟 Dynamic Fibonacci Projection Theory**
### **Continuous Proportional Scaling Model**
Fibonacci bands are constructed through **uniform proportional scaling** of the base curve, where each level represents a linear transformation of the main curve by a constant factor derived from the Fibonacci sequence.
**What is its practical utility?** It provides dynamic resistance and support levels that move with the trend, offering price targets and profit-taking points that automatically adapt to market evolution.
### **Topological Preservation Principle**
The system maintains the **topological properties** of the base curve in all Fibonacci projections, ensuring that spatial and temporal relationships are consistently preserved across all resistance/support levels.
---
## **⚡ Adaptive Computational Optimization**
### **Multi-Scale Resolution Theory**
It implements **automatic multi-resolution analysis** where data granularity is dynamically adjusted according to the analysis timeframe. It uses the **adaptive Nyquist principle** to optimize the signal-to-noise ratio according to the temporal observation scale.
**Why is this necessary?** Different timeframes require different levels of detail. A 1-minute chart needs more granularity than a monthly one. This system automatically optimizes resolution for each case.
### **Adaptive Density Algorithm**
Calculation point density is optimized through **adaptive sampling theory**, where calculation frequency is adjusted according to local trend curvature and analysis timeframe, balancing visual precision with computational efficiency.
---
## **🛡️ Robustness and Fault Tolerance**
### **Graceful Degradation Theory**
The system implements **multi-level graceful degradation**, where under error conditions or insufficient data, the algorithm progressively falls back to simpler but reliable methods, maintaining basic functionality under any condition.
**What does this guarantee?** That the indicator functions consistently even with incomplete data, new symbols with limited history, or extreme market conditions.
### **State Consistency Principle**
It uses **mathematical invariants** to guarantee that the algorithm's internal state remains consistent between executions, implementing consistency checks that validate data structure integrity in each iteration.
---
## **🔍 Key Theoretical Innovations**
### **A. Contextual vs. Absolute Outlier Detection**
It revolutionizes traditional outlier detection by considering not only the absolute magnitude of deviations, but their relative significance within the local context of the time series.
**Practical impact:** It distinguishes between legitimate market movements and technical anomalies, preserving important events like breakouts while filtering noise.
### **B. Extrapolation with Weighted Historical Memory**
It implements a memory system that weights different historical periods according to their relevance for current prediction, creating projections more adaptable to market regime changes.
**Competitive advantage:** It automatically adapts to fundamental changes in asset dynamics without requiring manual recalibration.
### **C. Automatic Multi-Timeframe Adaptation**
It develops an automatic temporal resolution selection system that optimizes signal extraction according to the intrinsic characteristics of the analysis timeframe.
**Result:** A single indicator that functions optimally from 1-minute to monthly charts without manual adjustments.
### **D. Intelligent Asymptotic Convergence**
It introduces the concept of controlled asymptotic convergence in financial extrapolations, where long-term projections converge toward realistic limits based on historical fundamentals.
**Added value:** Mathematically sound long-term projections that avoid the unrealistic extremes typical of other extrapolation methods.
---
## **📊 Complexity and Scalability Theory**
### **Optimized Linear Complexity Model**
The algorithm maintains **linear computational complexity** O(n) in the number of historical data points, guaranteeing scalability for extensive time series analysis without performance degradation.
### **Temporal Locality Principle**
It implements **temporal locality**, where the most expensive operations are concentrated in the most relevant temporal regions (recent periods and near projections), optimizing computational resource usage.
---
## **🎯 Convergence and Stability**
### **Probabilistic Convergence Theory**
The system guarantees **probabilistic convergence** toward the real underlying trend, where projection accuracy increases with the amount of available historical data, following **law of large numbers** principles.
**Practical implication:** The more history an asset has, the more accurate the algorithm's projections will be.
### **Guaranteed Numerical Stability**
It implements **intrinsic numerical stability** through the use of robust floating-point arithmetic and validations that prevent overflow, underflow, and numerical error propagation.
**Result:** Reliable operation even with extreme-priced assets (from satoshis to thousand-dollar stocks).
---
## **💼 Comprehensive Practical Application**
**The algorithm functions as a "financial GPS"** that:
1. **Identifies where we've been** (significant historical lows)
2. **Determines where we are** (current position relative to the trend)
3. **Projects where we're going** (future trend with specific price levels)
4. **Provides alternative routes** (Fibonacci bands as alternative targets)
This theoretical framework represents an innovative synthesis of time series analysis, approximation theory, and computational optimization, specifically designed for long-term financial trend analysis with robust and mathematically grounded projections.
ECG chart - mauricioofsousaMGO Primary – Matriz Gráficos ON
The Blockchain of Trading applied to price behavior
The MGO Primary is the foundation of Matriz Gráficos ON — an advanced graphical methodology that transforms market movement into a logical, predictable, and objective sequence, inspired by blockchain architecture and periodic oscillatory phenomena.
This indicator replaces emotional candlestick reading with a mathematical interpretation of price blocks, cycles, and frequency. Its mission is to eliminate noise, anticipate reversals, and clearly show where capital is entering or exiting the market.
What MGO Primary detects:
Oscillatory phenomena that reveal the true behavior of orders in the book:
RPA – Breakout of Bullish Pivot
RPB – Breakout of Bearish Pivot
RBA – Sharp Bullish Breakout
RBB – Sharp Bearish Breakout
Rhythmic patterns that repeat in medium timeframes (especially on 12H and 4H)
Wave and block frequency, highlighting critical entry and exit zones
Validation through Primary and Secondary RSI, measuring the real strength behind movements
Who is this indicator for:
Traders seeking statistical clarity and visual logic
Operators who want to escape the subjectivity of candlesticks
Anyone who values technical precision with operational discipline
Recommended use:
Ideal timeframes: 12H (high precision) and 4H (moderate intensity)
Recommended assets: indices (e.g., NASDAQ), liquid stocks, and futures
Combine with: structured risk management and macro context analysis
Real-world performance:
The MGO12H achieved a 92% accuracy rate in 2025 on the NASDAQ, outperforming the average performance of major global quantitative strategies, with a net score of over 6,200 points for the year.
BUY in HASH RibbonsHash Ribbons Indicator (BUY Signal)
A TradingView Pine Script v6 implementation for identifying Bitcoin miner capitulation (“Springs”) and recovery phases based on hash rate data. It marks potential low-risk buying opportunities by tracking short- and long-term moving averages of the network hash rate.
⸻
Key Features
• Hash Rate SMAs
• Short-term SMA (default: 30 days)
• Long-term SMA (default: 60 days)
• Phase Markers
• Gray circle: Short SMA crosses below long SMA (start of capitulation)
• White circles: Ongoing capitulation, with brighter white when the short SMA turns upward
• Yellow circle: Short SMA crosses back above long SMA (end of capitulation)
• Orange circle: Buy signal once hash rate recovery aligns with bullish price momentum (10-day price SMA crosses above 20-day price SMA)
• Display Modes
• Ribbons: Plots the two SMAs as colored bands—red for capitulation, green for recovery
• Oscillator: Shows the percentage difference between SMAs as a histogram (red for negative, blue for positive)
• Optional Overlays
• Bitcoin halving dates (2012, 2016, 2020, 2024) with dashed lines and labels
• Raw hash rate data in EH/s
• Alerts
• Configurable alerts for capitulation start, recovery, and buy signals
⸻
How It Works
1. Data Source: Fetches daily hash rate values from a selected provider (e.g., IntoTheBlock, Quandl).
2. Capitulation Detection: When the 30-day SMA falls below the 60-day SMA, miners are likely capitulating.
3. Recovery Identification: A rising 30-day SMA during capitulation signals miner recovery.
4. Buy Signal: Confirmed when the hash rate recovery coincides with a bullish shift in price momentum (10-day price SMA > 20-day price SMA).
⸻
Inputs
Hash Rate Short SMA: 30 days
Hash Rate Long SMA: 60 days
Plot Signals: On
Plot Halvings: Off
Plot Raw Hash Rate: Off
⸻
Considerations
• Timeframe: Best applied on daily charts to capture meaningful miner behavior.
• Data Reliability: Ensure the chosen hash rate source provides consistent, gap-free data.
• Risk Management: Use alongside other technical indicators (e.g., RSI, MACD) and fundamental analysis.
• Backtesting: Evaluate performance over different market cycles before live deployment.
signBTC Day&Session BoxesThis indicator visually segments the trading week on your chart, drawing each day from 17:00 to 17:00 New York time (corresponding to the typical forex daily rollover). For enhanced session structure, every day is further divided into three major trading sessions:
Asian Session
London Session
New York Session
Additionally, the indicator automatically marks the opening time of each new day at 17:00 (New York time) directly on the chart, helping traders quickly identify daily cycles and session transitions.
Customization Features
Adjustable Session Times: Users can modify the start and end times for each session (Asian, London, New York) to match personal or institutional trading hours.
Flexible Day Boundaries: The time marking the start and end of each day (default: 17:00 NY) can also be adjusted according to preference or asset specifics.
Opening Time Marker: The feature for drawing the daily opening time can be enabled or disabled in the settings.
This tool is ideal for traders needing clear visual cues for session boundaries and daily market resets, especially those operating across multiple time zones or managing strategies dependent on session-specific behavior. All settings are conveniently accessible and fully customizable within the indicator’s parameter panel.
JXMJXRS - Macro Flow CompassThe Macro Flow Compass is designed to give a high-level view of market behaviour by tracking how capital is moving across the crypto ecosystem. It’s not an entry or exit tool. Instead, it helps identify when the overall environment is shifting, whether capital is favouring majors like BTC and ETH, rotating into altcoins, or moving into stables.
The goal is to keep you aligned with broader market cycles, so trades are taken with macro context in mind.
The script works by analyzing four key metrics:
Total crypto market cap (CRYPTOCAP:TOTAL)
Bitcoin dominance (CRYPTOCAP:BTC.D)
Ethereum dominance (CRYPTOCAP:ETH.D)
Combined stable coin dominance from USDT and USDC (CRYPTOCAP:USDT.D + USDC.D)
These are smoothed using a basic EMA (Exponential Moving Average) to reduce noise. The script then checks for changes in dominance and market cap slope to detect when capital is likely flowing into or out of specific sectors.
When certain conditions align, the script will shade the background with one of the following colours:
Green Panel – Risk-on behaviour in majors. Usually appears when total market cap is trending up and BTC dominance is dropping, or stable coin dominance is falling. It suggests BTC and ETH are likely receiving capital inflow, not necessarily pumping but positioned better for upside.
Orange Panel – Altcoin rotation. Happens when ETH dominance is rising or stables are pulling back, while the market cap is also rising. These tend to precede altcoin outperformance phases.
Blue Panel – Stable coin build-up. Signals increasing stable coin dominance. Often a defensive move, either after a drop or in anticipation of volatility. This can mean risk-off conditions.
The indicator uses three main settings:
Smoothing Length – Controls how reactive the EMAs are. Lower values react quicker to short-term changes; higher values will slow things down and highlight more persistent trends.
Dominance Flip Threshold (%) – Sets how much a dominance value must change in one bar to trigger a condition. It’s there to avoid reacting to tiny shifts that don’t really matter.
Macro Cap Slope Length – Determines how the macro market cap trend is calculated. It looks at the slope of a long-term regression to decide if we’re in an uptrend or downtrend.
This tool works on higher timeframes like the weekly or monthly, and it’s especially useful when combined with your own technical analysis.
Durdens Global M2 Liquidity Tracker🧠 Durdens Global M2 Liquidity Tracker | Bitcoin vs Liquidity, Visualized
If you’re not watching global liquidity, you’re not really trading macro.
This indicator tracks FX-adjusted M2 money supply across 20+ countries, aggregated into a single global liquidity signal. It can then be used to overlay against Bitcoin for timing macro shifts with precision.
🔍 Core Features:
🌐 USD-adjusted M2 from the US, China, Eurozone, UK, Japan, and more
📊 Normalization modes: None (raw), Index (Based to 100), Z-Score
⏳ Offset input to shift liquidity data forward — aligns with Bitcoin's delayed reaction (84–107 days common)
🧠 BTC correlation matrix: 30D, 90D, 365D correlation values
🧪 Top 3 M2 delta signals: Tracks 90-day % change for US, China, EU
🧮 Fibonacci SMAs: 13 / 34 / 89 for structural macro context
🟢🔴 Liquidity regime engine: EMA 89 defines "Risk-On" vs "Risk-Off" states
🧩 How It Works:
Each country’s M2 is multiplied by its FX rate (to USD) and summed into a single global M2 line. This ensures comparability across nations. The user can choose to:
Normalize the output (raw, indexed, or z-scored)
Shift the global M2 forward in time (offset), simulating the lag effect liquidity has on Bitcoin
Visualize macro risk conditions using EMA 89 as a liquidity regime filter
Analyze BTC correlation across 3 windows and track key regions’ M2 delta
❓ FAQ:
Why does this matter?
M2 is the monetary fuel behind asset bubbles. When liquidity rises, Bitcoin follows; with a delay. This tracker helps you front-run macro flows before they hit the chart.
Why use Index or Z-Score modes?
Raw values skew long-term visual analysis. Index mode rebases data for comparative trend tracking. Z-Score shows when liquidity is overheated or suppressed (mean reversion).
What does the offset input do?
Liquidity doesn’t hit Bitcoin instantly. Many traders use an 84–107 day forward shift to align M2 changes with BTC price action. The offset helps you visualize this.
Why track top 3 M2 regions?
US, China, and Eurozone are the heavyweights in global liquidity. Tracking their offset-day % change gives immediate insight into capital expansion or contraction.
Can I use this to trade?
Absolutely; but it’s best used as a macro filter. Combine with price structure, funding, or on-chain data to optimize timing and conviction.
⚡ Use Cases:
Spot early pivots in liquidity regimes (Risk-Off to Risk-On)
Quantify macro backdrop for Bitcoin or altcoin cycles
Understand when the Fed or PBOC are tightening or easing
Ditch the hopium. Trade with context.
—
Built by: @DurdensBitcoinLedger
Follow for updates — future upgrades include:
• Regional toggles
• Custom M2 baskets
• Alert conditions
• Continued revisions & updates
Stay liquid, not wrecked.
Economy RadarEconomy Radar — Key US Macro Indicators Visualized
A handy tool for traders and investors to monitor major US economic data in one chart.
Includes:
Inflation: CPI, PCE, yearly %, expectations
Monetary policy: Fed funds rate, M2 money supply
Labor market: Unemployment, jobless claims, consumer sentiment
Economy & markets: GDP, 10Y yield, US Dollar Index (DXY)
Options:
Toggle indicators on/off
Customizable colors
Tooltips explain each metric (in Russian & English)
Perfect for spotting economic cycles and supporting trading decisions.
Add to your chart and get a clear macro picture instantly!
Global Risk Matrix [QuantAlgo]🟢 Overview
The Global Risk Matrix is a comprehensive macro risk assessment tool that aggregates multiple global financial indicators into a unified risk sentiment framework. It transforms diverse economic data streams (from currency strength and liquidity measures to volatility indices and commodity prices) into standardized Z-Score readings to identify market regime shifts across risk-on and risk-off conditions.
The indicator displays both a risk oscillator showing weighted average sentiment and a dynamic 2D matrix visualization that plots signal strength against momentum to reveal current market phase and historical evolution. This helps traders and investors understand broad market conditions, identify regime transitions, and align their strategies with prevailing macro risk environments across all asset classes.
🟢 How It Works
The indicator employs Z-Score normalization across various global macro components, each representing distinct aspects of market liquidity, sentiment, and economic health. Raw data from sources like DXY, S&P 500, Fed liquidity, global M2 money supply, VIX, and commodities undergoes statistical standardization. Several components are inverted (USDT.D, DXY, VIX, credit spreads, treasury bonds, gold) to align with risk-on interpretation, where positive values indicate bullish conditions.
This unique system applies configurable weights to each component based on selected asset class presets (Crypto Investor/Trader, Stock Trader, Commodity Trader, Forex Trader, Risk Parity, or Custom), creating a weighted average Z-Score. It then analyzes both signal strength and momentum direction to classify market conditions into four distinct phases: Risk-On (positive signal, rising momentum), Risk-Off (negative signal, falling momentum), Recovery (negative signal, rising momentum), and Weakening (positive signal, falling momentum). The 2D matrix visualization plots these dimensions with historical trail tracking to show regime evolution over time.
🟢 How to Use
1. Risk Oscillator Interpretation and Phase Analysis
Positive Territory (Above Zero) : Indicates risk-on conditions with capital flowing toward growth assets and higher risk tolerance
Negative Territory (Below Zero) : Signals risk-off sentiment with capital seeking safety and defensive positioning
Extreme Levels (±2.0) : Represent statistically significant deviations that often precede regime reversals or trend exhaustion
Zero Line Crosses : Mark critical transitions between risk regimes, providing early signals for portfolio rebalancing
Phase Color Coding : Green (Risk-On), Red (Risk-Off), Blue (Recovery), Yellow (Weakening) for immediate regime identification
2. Risk Matrix Visualization and Trail Analysis
Current Position Marker (⌾) : Shows real-time location in the risk/momentum space for immediate situational awareness
Historical Trail : Connected path showing recent market evolution and regime transition patterns
Quadrant Analysis : Risk-On (upper right), Risk-Off (lower left), Recovery (lower right), Weakening (upper left)
Trail Patterns : Clockwise rotation typically indicates healthy regime cycles, while erratic movement suggests uncertainty
3. Pro Tips for Trading and Investing
→ Portfolio Allocation Filter : Use Risk-On phases to increase exposure to growth assets, small caps, and emerging markets while reducing defensive positions during confirmed green phases
→ Entry Timing Enhancement : Combine Recovery phase signals with your technical analysis for optimal long entry points when macro headwinds are clearing but prices haven't fully recovered
→ Risk Management Overlay : Treat Weakening phase transitions as early warning systems to tighten stop losses, reduce position sizes, or hedge existing positions before full Risk-Off conditions develop
→ Sector Rotation Strategy : During Risk-On periods, favor cyclical sectors (technology, consumer discretionary, financials) while Risk-Off phases favor defensive sectors (utilities, consumer staples, healthcare)
→ Multi-Timeframe Confluence : Use daily matrix readings for strategic positioning while applying your regular technical analysis on lower timeframes for precise entry and exit execution
→ Divergence Detection : Watch for situations where your asset shows bullish technical patterns while the matrix shows Risk-Off conditions—these often provide the highest probability short opportunities and vice versa
Calendar TableThis script displays a calendar-style visual grid directly on the TradingView chart. Unlike fundamental calendars or event indicators, this tool does not mark earnings, news, or economic data. Instead, it provides a simple and clean visual calendar layout for better understanding of date structures across timeframes.
The purpose of this script is purely visual – helping traders and analysts recognize monthly, weekly, and daily boundaries in a calendar format. It’s especially useful for visually aligning price action with time cycles, month-start effects, or periodic strategies.
✅ Key Features
🗓️ Calendar Grid Overlay
Displays calendar-style lines or boxes across candles based on real date logic (year, month, day).
📦 Minimalist Design
Non-intrusive layout that doesn’t interfere with price action or indicators.
⏳ Timeframe-Aware
Adjusts the calendar structure to match the selected chart timeframe.
🎨 Custom Styling Options
Choose line colors, label sizes, and boundary highlights.
⚙️ How to Use
Add the script to your chart.Adjust the visual style and frequency in the settings .
⚠️ Notes
This script does not fetch news, earnings, or events.
It is purely a static calendar layout based on date/time.
No user-defined events, reminders, or alerts are included.
📄 Licensing
This script is Protected Script its only for educational and analytical use.
RSI - PRIMARIO -mauricioofsousa
MGO Primary – Matriz Gráficos ON
The Blockchain of Trading applied to price behavior
The MGO Primary is the foundation of Matriz Gráficos ON — an advanced graphical methodology that transforms market movement into a logical, predictable, and objective sequence, inspired by blockchain architecture and periodic oscillatory phenomena.
This indicator replaces emotional candlestick reading with a mathematical interpretation of price blocks, cycles, and frequency. Its mission is to eliminate noise, anticipate reversals, and clearly show where capital is entering or exiting the market.
What MGO Primary detects:
Oscillatory phenomena that reveal the true behavior of orders in the book:
RPA – Breakout of Bullish Pivot
RPB – Breakout of Bearish Pivot
RBA – Sharp Bullish Breakout
RBB – Sharp Bearish Breakout
Rhythmic patterns that repeat in medium timeframes (especially on 12H and 4H)
Wave and block frequency, highlighting critical entry and exit zones
Validation through Primary and Secondary RSI, measuring the real strength behind movements
Who is this indicator for:
Traders seeking statistical clarity and visual logic
Operators who want to escape the subjectivity of candlesticks
Anyone who values technical precision with operational discipline
Recommended use:
Ideal timeframes: 12H (high precision) and 4H (moderate intensity)
Recommended assets: indices (e.g., NASDAQ), liquid stocks, and futures
Combine with: structured risk management and macro context analysis
Real-world performance:
The MGO12H achieved a 92% accuracy rate in 2025 on the NASDAQ, outperforming the average performance of major global quantitative strategies, with a net score of over 6,200 points for the year.
ICT-Elliott Hybrid Oscillator네이버 프리미엄 콘텐츠 > 재테크 사관학교 검색
This indicator uses Elliott Wave Theory and ICT (Inner Circle Trader) concepts to help easily and accurately predict when asset prices like cryptocurrencies or stocks will rise or fall.
📌 Easy Explanation of Terms
✅ What is Elliott Wave?
A theory stating that price movements follow a specific pattern (5 upward waves + 3 downward waves) repeatedly. Simply put, it's about repetitive cycles of rises and falls creating overall trends.
✅ What is ICT Theory?
A strategy that identifies optimal trading times by observing critical price areas traded by institutional investors (Order Blocks), imbalances in price (Fair Value Gaps - FVG), and major turning points (Break of Structure - BOS).
📈 Signals Provided by the Indicator
🔹 ① Pivot Highs & Lows
Red ▼: Short-term high (increased likelihood of price falling)
Green ▲: Short-term low (increased likelihood of price rising)
🔹 ② Fair Value Gap (FVG)
Green highlighted area: Zone where price is likely to rise again
Red highlighted area: Zone where price is likely to fall again
🔹 ③ Break of Structure (BOS)
Blue "BOS Up": Indicates a shift to an upward trend
Orange "BOS Down": Indicates a shift to a downward trend
⏳ Recommended Timeframe Combinations
| Major Trend (Basic Analysis) | Entry Point (Detailed Analysis) | Short-term Timing (Precision Analysis) |
| ---------------------------- | ------------------------------- | -------------------------------------- |
| 4-hour | 1-hour | 15-minute |
Use the 4-hour timeframe to gauge overall trends,
the 1-hour timeframe to pinpoint exact entry and exit points,
and the 15-minute timeframe for precise timing.
Include Source
🕯 Recommended Candle Patterns
* Pin Bar (Long wick candle) → Trend reversal signal
* Engulfing Candle (fully covering previous candle) → Strong trend reversal signal
* Hammer & Shooting Star (small body with a long wick) → Bullish or bearish reversal signal
* Doji (balance between buyers and sellers) → High potential for trend reversal
