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Verified Astro-Table SimplifiedThis script, titled the **Financial Astrological Ephemeris Table**, is designed to be a high-precision astronomical dashboard for TradingView. Unlike standard indicators that rely on price formulas, this script serves as a **digital bridge** between professional Swiss Ephemeris data and your trading chart.
Here is a detailed breakdown of what the script provides and how to maximize its utility.
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**1. What the Script Provides**
**A. 100% Ephemeris Synchronization**
Most "Astro" indicators in TradingView use "mean motion" math, which drifts over time. This script uses **Static Switch Logic**. By hard-coding the data from the Swiss Ephemeris, the script ensures that the degrees you see on your chart match the physical reality of the sky.
* **Sun & Moon**: Accurate to the degree for the current period.
* **Saturn & Outer Planets**: Corrects the "sign drift" found in other scripts, keeping Saturn in its true position (late Pisces for 2025).
**B. Sign & Degree Tracking**
The script translates raw longitude (0–360°) into the traditional 12-sign zodiac format (`Sign` + `Degree`). This allows you to immediately identify where planets are transiting relative to key price levels.
**C. The Sun-Relative House System**
The script calculates an **Equal House System** based on the Sun's current position.
* This treats the Sun as the "Rising" point for the day's dashboard, showing you how other planets are "angled" relative to the Sun's current solar light.
**D. Stability and Performance**
Because the script uses `barstate.islast`, it only calculates for the most recent candle. This prevents "Runtime Errors" and ensures your TradingView platform remains fast and responsive, even on low-powered laptops.
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**2. How to Use it Effectively**
**A. Identifying Confluence with Price**
Watch for "Degree Hits." If the table shows **Saturn at 25° Pisces** and your asset is hitting a major resistance level at a number ending in **25** (or a harmonic like 2.50), it signifies a moment of "Astro-Price Confluence." These are often high-probability reversal points.
**B. Customizing the Visual Experience**
You can tailor the dashboard to your specific chart layout via the **Settings (Gear Icon)**:
* **Position**: Move the table to any corner (Top Right, Bottom Left, etc.) so it doesn't block your price action.
* **Transparency**: Adjust the "Background Color" to make the table more subtle or more prominent.
* **Text Size**: If you trade on a mobile device, set the text to "Normal." If you use a 4K monitor, set it to "Tiny" to save space.
**C. Managing the "Switch" Data**
To keep the script accurate for the long term, I will update the `get_pdf_lon` block once a month (or once a year) with the new coordinates from the Swiss Ephemeris.
**D. Directional Trading (The "Dir" Column)**
The script includes a "Direction" column. Use this to track if a planet is **Direct (D)** or **Retrograde (Rx)**.
**Strategy**: If a planet is listed as "D," its influence is considered "forward-moving" and predictable. If you update the code to show "Rx," expect the market sectors associated with that planet to experience "re-evaluations" or delays.
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### Summary of Benefits for the User
1. **Eliminates Guesswork**: You no longer have to flip between an Ephemeris and TradingView; the data is on your screen.
2. **Historical Analysis**: You can manually change the data in the script to a historical date to see exactly how the "Astro-Weather" looked during a previous market crash or rally.
Last 30 days 9-12 avg range NYaverage range for NY time 9-12 in last 30 days. 9-12 will be highlighted and turn red on the 5m chart when price reaches a range bigger than the average in the last 30 days for that time.
Time Exhaustion Counter [Adaptive]📌 Description
This indicator is a time-based trend exhaustion tool designed to identify when a price move becomes statistically mature relative to market structure — not momentum alone.
Instead of relying on traditional oscillators, it measures how long price has been moving from a confirmed pivot and validates potential exits using ATR-based volatility filtering.
The primary goal is to avoid premature exits, reduce market noise, and highlight high-probability reversal zones based on time exhaustion rather than price speed.
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🔍 Methodology & Core Logic
1️⃣ Pivot-Anchored Time Counting
The bar count begins only after a confirmed Swing High or Swing Low, ensuring that all calculations are anchored to real market structure rather than arbitrary candles.
2️⃣ Volatility Filtering (ATR-Based)
To prevent false resets during choppy or low-quality price action, the indicator applies an ATR filter.
A counter-move must exceed a dynamic ATR threshold before the count is reset, effectively filtering noise and unstable market conditions.
3️⃣ Confirmed Exit Logic
A TIME EXIT signal is not triggered immediately when the target bar count is reached.
The system waits for an opposite confirmed pivot, validating that momentum has truly shifted before signaling exhaustion.
✔️ This confirmation logic helps reduce fake reversals and late or emotional entries.
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📐 Fibonacci Confluence (Recommended)
For higher-probability setups, it is recommended to combine this indicator with Fibonacci Retracement levels.
TIME EXIT signals gain additional strength when they align with key Fibonacci correction zones such as:
• 0.382
• 0.5
• 0.618
🔹 Bullish Context:
A TIME EXIT (BOTTOM) signal near the 0.5 or 0.618 retracement level often indicates seller exhaustion and a potential upside reversal or continuation.
🔹 Bearish Context:
A TIME EXIT (PEAK) signal near the 0.382–0.618 retracement zone may suggest buyer exhaustion and an increased probability of downside correction.
Fibonacci levels are used strictly as a confluence tool to refine entries and improve risk-to-reward.
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📊 How to Trade – RSI Confluence Strategy
This indicator works best as a confirmation and timing tool, not as a standalone signal.
It is highly effective when combined with RSI or other momentum indicators.
🔵 Bullish Setup (Long)
• Wait for: TIME EXIT (BOTTOM) label
• Confirm with RSI:
– RSI below 30 (Oversold), or
– Bullish divergence
• Interpretation: Seller exhaustion and increased probability of upside reversal
🔴 Bearish Setup (Short)
• Wait for: TIME EXIT (PEAK) label
• Confirm with RSI:
– RSI above 70 (Overbought), or
– Bearish divergence
• Interpretation: Buyer exhaustion and potential downside correction
⚠️ Best used in ranging or slowing markets.
Avoid counter-trend trades during strong trends or high-impact news events.
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⚙️ Optimized Configuration Guide
While the script includes auto-adaptive presets, manual tuning allows better alignment with different trading styles.
A️⃣ Scalping (1m – 5m)
• Fast / Aggressive: Pivot L/R 3 | Target 50 | ATR Mult 1.0
• Balanced: Pivot L/R 4 | Target 60 | ATR Mult 1.2
• Conservative: Pivot L/R 5 | Target 70 | ATR Mult 1.4
(1m Target Bars ≈ 120)
B️⃣ Day Trading (15m – 1h)
• Aggressive: Pivot 2 | Target 20–30 | ATR 0.8
• Standard: Pivot 3 | Target 24–40 | ATR 1.0
• Conservative: Pivot 4 | Target 50 | ATR 1.2
C️⃣ Swing Trading (4h – Daily)
• Early Entry: Pivot 1–2 | Target 8–10 | ATR 0.5
• Standard: Pivot 2 | Target 10–12 | ATR 0.7
• Investment: Pivot 3 | Target 14–16 | ATR 0.9
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✅ Key Features
• Clean and uncluttered chart output
• No repaint (signals confirmed on bar close)
• ATR-based noise reduction
• Time-based exhaustion logic (not momentum-based)
• Built-in alert support
Market State Intelligence [Interakktive]Market State Intelligence (MSI) is a diagnostic market-context indicator that reveals how the market is behaving — not where price "should" go.
MSI does not generate buy/sell signals. Instead, it classifies market conditions into clear behavioural regimes by continuously measuring:
- DRIVE (directional effort)
- OPPOSITION (absorption / resistance)
- STABILITY (structural persistence)
MSI is designed to answer three practical questions:
- What state is the market in right now?
- Is energy building, releasing, or decaying?
- Is participation aligned with price, or opposing it?
█ WHAT MSI DOES
MSI operates as a real-time regime classification engine that processes each closed bar through three independent measurement systems:
DRIVE — Directional Effort (0–100)
- Displacement efficiency (net progress vs total path)
- Range expansion quality (actual range vs expected ATR range)
- Body dominance (body vs candle range)
OPPOSITION — Absorption / Resistance (0–100)
- Wick pressure (rejection relative to attempt)
- Effort–result gap (high effort, low progress)
- Reversal density (counter-moves frequency)
STABILITY — Persistence (0–100)
- Condition persistence (how long conditions hold)
- Variance score (flip frequency)
- Follow-through consistency (reaction continuity)
These three forces feed a deterministic classifier with hysteresis (anti-flicker) to identify five regimes:
COMPRESSION — low drive, low opposition, higher stability (pressure building, direction unclear)
EXPANSION — high drive, low opposition (directional energy release)
TREND — medium-high drive, higher stability, low-medium opposition (healthy continuation)
DISTRIBUTION — medium drive, high opposition (effort absorbed; progress blocked)
TRANSITION — rapidly rising opposition, low stability (regime breakdown / uncertainty)
█ WHAT MSI DOES NOT DO
- No buy/sell signals, entries/exits, or performance claims
- No prediction of future direction
- No repainting: calculations use closed-bar data only
MSI is a market state layer intended to support your execution framework.
█ VISUAL SYSTEM
MSI uses a layered visual grammar designed to remain readable on live charts:
Regime Ribbon
A thin horizontal band showing the current regime via colour. Ribbon opacity reflects regime confidence (stronger confidence = more visible).
Pressure Envelope (core visual)
A soft corridor around price that expands with Drive and becomes more visible as Opposition increases. This visualises "pressure thickness" around current action (not a volatility band for entries).
Structural Memory
Faint background stains appear where regimes previously failed (e.g., expansion collapsing into absorption). These are behavioural context zones showing where market intention was rejected — not support/resistance.
Regime Change Markers (optional)
Subtle labels appear when regimes transition after confirmation. Useful for replay and education.
Effort Halo (optional)
Candle highlighting when Opposition materially exceeds Drive, indicating absorption/inefficiency.
█ HUD PANEL
The HUD displays:
- Current regime name + colour indicator
- A context gate showing whether conditions are aligned with long-bias or short-bias context (not an entry/exit system)
█ REGIME LEGEND
When enabled, displays:
- A one-line definition of the current regime
- Live Drive / Opposition / Stability values for interpretation
█ TIME-TO-DECISION METER
A visual pressure gauge that tends to fill during Compression (energy building) and drain during Expansion (energy releasing). It is a state-tracking meter, not a timing tool.
█ SETTINGS
MSI — Settings
- Preset Mode: Scalper / Swing / Position
- Analysis Mode (Minimal): ON = subtle visuals, OFF = full intensity
- Regime Ribbon, Structural Memory, HUD Panel, Time-to-Decision Meter, Effort Halo
MSI — Visual Options
- Show Regime Changes: Labels when regime transitions occur
- Show Regime Legend: Definition and live values display
- Panel Position: Move the entire panel anywhere on chart
MSI — Advanced (Tuning)
- Sensitivity (0.5–2.0)
- Smoothing (0.5–2.0)
- Memory Decay (0.5–2.0)
- Visual Intensity (Low / Medium / High)
█ PRESETS EXPLAINED
Scalper
Higher sensitivity + lower smoothing + faster memory decay. Best for 1m–15m monitoring.
Swing (default)
Balanced behaviour. Best for 15m–4H analysis.
Position
Lower sensitivity + higher smoothing + slower memory decay. Best for 4H–1D macro context.
█ STRUCTURAL MEMORY
When a regime fails (example: Expansion → Distribution), MSI creates a memory imprint:
- Fixed stain window (preset dependent)
- Strength decays over time
- Limited to a maximum number of imprints to reduce chart clutter
These zones represent behavioural rejection, not levels.
█ SUITABLE MARKETS
MSI is designed for Forex, Crypto, Indices, Stocks, and Commodities.
Works from intraday to Daily, with particularly strong readability on 15m–4H.
█ DISCLAIMER
This indicator is for educational and informational purposes only. It does not constitute financial advice, trading recommendations, or solicitation. Trading involves substantial risk. Always use proper risk management and make independent decisions.
Daily High Low XAUUSD by RizalIndikator ini untuk mengetahui high low daily chart XAUUSD di timeframe 4h
BTC - Liquisync: Macro Pulse & Desync EngineLiquisync: Macro Pulse & Desync Engine | RM
Strategic Context: The Macro Fuel Tank
Why compare Global Liquidity to Bitcoin? Because Bitcoin acts as a "Global M2 Sponge." As central banks expand their balance sheets, this "Fuel" filters into the system, taking roughly 56 to 70 days to reach Bitcoin's price. Liquisync measures this lead-lag relationship to determine if the "Engine" (Price) is properly supported by the "Fuel" (M2).
How the Model Differs: Liquisync vs. Standard Macro Composites
Many existing macro scripts focus on a Linear Sum of indicators—adding up M2, Spread, and Copper/Gold into a single Z-score. While useful for general sentiment, these "Composite" models often suffer from Directional Blindness. They tell you if the environment is "Risk-On," but they cannot tell you if the Price is currently lying about the Liquidity.
The Liquisync Edge:
• Conflict Detection: Unlike composites that simply turn red or green, Liquisync identifies Desync.
• Velocity Normalization: Instead of Z-scoring absolute values, we measure the Acceleration (Slope) of the move, allowing us to see "Decay" before the trend actually flips.
How the Model Works
1. Pulse Velocity Mapping (The Dual-Slope Architecture)
The engine utilizes a Dual-Slope Architecture to measure the "Dynamic Force" behind the market. By calculating the Linear Regression Slope for both Global Liquidity and BTC Price, we are measuring Acceleration.
• Liquidity Slope (The Fuel): Measures the speed at which central banks are expanding or contracting the money supply.
• Price Slope (The Engine): Measures the speed at which the market is repricing Bitcoin in response to that money (or due to other factors).
The Mathematical Bridge: We don't just plot these lines independently; we normalize them. Because Global M2 is measured in Trillions and BTC in Thousands of Dollars, we transform both into a unified Relative Pulse Score (-100 to +100).
Liquisync: The 4 Macro Scenarios (Directional Matrix) By measuring the interconnectivity of these two pulses, the engine identifies four distinct market regimes:
Scenario A: Institutional Expansion (Harmony) Liquidity Slope (+ rising) | Price Slope (+ rising) Harmony. The trend is "True." The price increase is fully supported by global money. (Scenario Jan 2023)
Scenario B: The Bear Trap (Desync / "Open Mouth") Liquidity Slope (+ rising) | Price Slope (- falling) The Core Edge. Liquidity is filling up, but price is dropping due to short-term panic. Because the fuel is there, the price must eventually snap upward to catch up with the liquidity reality. (Scenario Jun 2020)
Scenario C: The Bull Trap (Desync / "Open Mouth") Liquidity Slope (- falling) | Price Slope (+ rising) The Danger Zone. Price is climbing on "Empty Fuel." Retail FOMO is driving the market while liquidity is being pulled. Highly unstable. (Scenario Jul 2022)
Scenario D: Macro Contraction (Harmony) Liquidity Slope (- falling) | Price Slope (- falling) The Drain. Global liquidity is shrinking and price is following. A fundamental bear market. (Scenario Nov/Dec 2021)
2. Directional Desync (The Conflict Filter)
Liquisync is a Conflict Filter. It ignores "Synchronous" phases where both lines move together and focuses 100% of its visual energy on the Desync scenarios (Bear Trap or Bull Trap). When the lines travel in opposite directions, the indicator generates Cyan Columns. The height of these columns tells you the intensity of the conflict. When the pulses move in Harmony (Scenario A & D), the desync value remains at zero. This creates a 'Visual Silence' on the chart, signaling that the current price trend is structurally healthy and macro-supported.
3. Liquisync Extreme (The Snap-Back Star ✦)
This triggers when the "Open Mouth" (the Liquidity Pulse (Golden Line) and the Price Pulse (White Area) pull in diametrically opposite directions) desync reaches 85% of its 1-year historical record. This is a generational signal identifying the absolute limits of market irrationality relative to the macro reality (Price up, M2 down or vice versa).
How to Read the Chart
• Golden Pulse: The Liquidity Slope
• White Area: The Price Slope
• Harmony (No Columns): Price and Liquidity are in sync. Trend-following is safe.
• Open Mouth (Cyan Columns): These are not momentum bars; they are Conflict Bars . They only appear when the Price and Liquidity are traveling in opposite directions. The taller the column, the more "stretched" the macro rubber band has become.
• Magenta Stars: The desync is at a statistical limit. Expect a violent Macro Snap-Back toward the Golden Liquidity line.
The 60-Day Lead-Lag Principle: Why the Delay?
The Liquisync engine utilizes a specific forward-lag (defaulted to 60–80 days or 9 weeks, to be parametrized by the user) based on the Monetary Transmission Mechanism. Research into global liquidity cycles shows that central bank injections (M2 expansion) do not impact high-beta risk assets instantaneously. Capital follows a "Waterfall Effect": it moves first into primary dealer banks, then into credit markets and equities, and finally—once the "liquidity tide" has sufficiently risen—into the cryptocurrency ecosystem. Statistical correlation studies confirm that the peak relationship between Global M2 and Bitcoin historically occurs with a 56 to 63-day delay. By shifting the liquidity data forward, we align the "Macro Cause" with its "Market Effect," revealing a clearer predictive map that standard, unlagged indicators miss.
Settings & Calibration: Tuning the Liquisync Engine
The Liquisync engine is a precision instrument that requires specific calibration to align the "Macro Fuel" with the "Price Engine."
Slope Lookback defines the sensitivity of our acceleration measurement; a setting of 6 (Weekly) or 30 (Daily) ensures we capture structural shifts while filtering out intraday noise
Liquidity Lag is perhaps the most critical setting, as it shifts the M2 data forward to account for the standard 60–80 day (or 9-week) transmission delay—the time it takes for central bank liquidity to actually hit the crypto order books.
Extreme Window establishes our statistical benchmark; by default, this is set to 52 (representing one full year on the Weekly timeframe), allowing the engine to identify "Magenta Star" signals by comparing the current directional desync against the highest records of the last 365 days.
Recommended Calibration :
• Daily (1D): Set Lag to 60–80 and Lookback to 30 .
• Weekly (1W): Set Lag to 9 (9 weeks) and Lookback to 6 . The 1W chart is the preferred filter for macro cycles.
Detailed Script Calculations
The script aggregates liquidity from the FED, RRP, TGA, PBoC, ECB, and BoJ using request.security. We calculate the ta.linreg slope of this aggregate, normalize it via EMA-smoothed RSI mapping (-100 to +100), and apply a ta.change filter to identify directional opposition. The "Extreme" signal is derived from a rolling ta.highest window of the desync intensity.
The Liquisync engine calculates the Linear Regression Slope (m) over a user-defined window:
m =
Where:
• Δy = The distance between the current linear regression end-point and the previous bar.
• Δx = The defined bar-count (Lookback).
Risk Disclaimer & Credits
The Liquisync is a thematic macro tool. Global liquidity data is subject to reporting delays (Note: Because central bank M2 data is typically reported with a lag, the Golden Pulse represents the most recently available macro data, not a real-time high-frequency feed.). This is not financial advice; it is a statistical model for institutional education. Rob Maths is not liable for losses incurred via use of this model.
Tags:
indicator, bitcoin, btc, macro, liquidity, desync, liquisync, institutional, m2, robmaths, Rob Maths
AAT AugustrendThis Script helps all to understand the overall trend focusing on the mayor timeframes. With the trend already identified it also help us to make decisions on the shorter time frames such as the 4 hpur timeframe or 1 hour timeframe.
On the chart there will be 2 backgrounds showing up, green or red. The green show us that the overall trend is bullish so with this information we will go to lower timframes to check for long trades.
On the other hand if the background is red, it means that the overall trend is bearish so we will focus on trading short on the lower timeframes.
Magic 13 for China Stock MarketPrice Exhaustion Counter - 9/13 Signals
This indicator tracks consecutive closes relative to their 4-bar precedent, identifying potential trend exhaustion points.
KEY FEATURES:
- Counts consecutive higher/lower closes up to 9
- Extends counting to 13 for confirmation signals
- Customizable early warning display (counts 5-8)
- Background highlighting for approaching signals
- Clean, non-overlapping label placement
SIGNAL GUIDE:
- Counts 5-8 (orange): Early momentum warning
- Count 9 (purple/green badge): Primary exhaustion signal
- Counts 10-13 (green/purple): Extended momentum - stronger reversal potential
CUSTOMIZATION:
- Toggle early signals visibility
- Adjust label offset for clarity
- Enable/disable background hints
- All timeframes supported
Identifies high-probability reversal zones based on consecutive price action.
Lindsey Measured Move Price TargetsLindsey is a pivot-structure target tool that auto-maps a simple 3-point swing sequence (P1 → P2 → P3) and projects a symmetry-based target (P4), then prints it as a clean “🎯” balloon on your chart. It’s designed to give traders a fast, repeatable way to visualize where the next measured move could resolve—without cluttering the price action.
How it works
The script detects pivot highs/lows using your chosen Left/Right Swing Bars (pivot confirmation).
It tracks a three-point structure:
Bull case: P1 = pivot low, P2 = pivot high, P3 = higher pivot low
Bear case: P1 = pivot high, P2 = pivot low, P3 = lower pivot high
Once a valid P3 prints, it calculates a projected target:
Bull target: P4 = P2 + (P2 − P3)
Bear target: P4 = P2 − (P3 − P2)
The target is displayed as a right-shifted balloon, so you can keep it visible ahead of current candles.
How to operate it (practical workflow)
Set Swing Sensitivity
Left Swing Bars / Right Swing Bars control how “strict” pivots are.
Lower values = more signals (noisier). Higher values = fewer, cleaner structures.
Place the balloon where you want it
Balloon Right Offset (bars) moves the 🎯 label forward in time for readability.
Vertical Offset nudges the label up/down in price units to avoid overlapping candles or other tools.
Lock or keep it live
Turn Lock Target Balloon ON to keep the last target fixed on-chart.
Leave it OFF to always display the most recent valid projection.
Style it to your theme
Customize bull/bear balloon colors, text color, and P1/P2/P3 marker colors.
Why it’s useful (benefits)
Clear targets without guesswork: turns swing structure into a consistent measured-move projection.
Less chart noise: one readable target balloon instead of multiple lines and annotations.
Works across assets/timeframes: pivots adapt naturally to volatility and timeframe.
Trader-friendly controls: offset + vertical spacing + lock mode make it easy to integrate with existing layouts.
Notes / best practices
Pivots confirm after the right-side bars complete—so targets are intentionally non-repainting in structure detection, but they appear with that normal pivot confirmation delay.
For choppy ranges, increase pivot bars to reduce whipsaw targets; for trends, slightly lower them to catch more swing opportunities.
Fractal HTF Lines The indicator “Fractal HTF Lines” draws time‑based vertical lines that mark where higher‑timeframe periods start on your chart. It adapts its behavior to the timeframe you are currently viewing.
4‑hour timeframe
On a 4‑hour chart, the indicator draws a vertical line on the first 4‑hour bar of each new trading day. This lets you quickly see where one day ends and the next begins without turning on session breaks.
Daily timeframe
On a daily chart, the indicator draws a vertical line on the first trading day of each new week. Visually, this separates weeks so you can see weekly structure while still trading and analyzing on the daily timeframe.
Weekly timeframe
On a weekly chart, the indicator draws a vertical line on the first trading week of each new month. That way you can identify monthly boundaries directly on the weekly chart and better align your analysis with monthly cycles.
Customization
The indicator includes settings to control:
Line color: You can choose any color from the palette.
Line width: You can adjust the thickness to make lines more or less prominent.
Line opacity: You can make lines more transparent or more solid, depending on how strong you want the visual emphasis.
ZLT - Date and Time MarkerPine Script v5 indicator called “DateTime Marker” that overlays on the chart and marks bars whose timestamp matches a user-defined schedule. When a bar “matches,” it can draw:
a vertical line through the bar,
a label with a time/date string, and
a triangle marker below the bar (always plotted on matches).
What you can configure
Marker Type (the matching rule)
You choose one of five modes:
Every Minute
Inputs: everyNMinutes (default 15), minuteOffset (default 0)
Match condition: minute % everyNMinutes == minuteOffset
Example with defaults: marks bars at :00, :15, :30, :45 each hour.
Hourly
Inputs: everyNHours (default 4), hourlyMinute (default 0)
Match condition: hour % everyNHours == 0 AND minute == hourlyMinute
Example with defaults: marks bars at 00:00, 04:00, 08:00, 12:00, 16:00, 20:00 (at minute 00).
Daily Time
Inputs: dailyHour (default 10), dailyMinute (default 0)
Match condition: hour == dailyHour AND minute == dailyMinute
Example with defaults: marks 10:00 every day.
Weekly Day & Time
Inputs: weekDay (default Tuesday), weeklyHour (default 16), weeklyMinute (default 0)
It converts the weekday name to Pine’s dayofweek number via getDayNumber().
Match condition: dayofweek == targetDay AND hour == weeklyHour AND minute == weeklyMinute
Example with defaults: marks Tuesday 16:00.
Monthly Date & Time
Inputs: monthlyDay (default 2), monthlyHour (default 23), monthlyMinute (default 0)
Match condition: dayofmonth == monthlyDay AND hour == monthlyHour AND minute == monthlyMinute
Example with defaults: marks the 2nd day of each month at 23:00.
Visual settings
showLine: whether to draw the vertical line.
lineStyle: Solid/Dashed/Dotted (mapped to Pine line styles by getLineStyle()).
lineColor, lineWidth: styling for the line (width is rounded to an integer because Pine line width is integer).
showLabel: whether to draw a label.
labelColor: background color of the label (text is forced white).
What happens when a bar matches
When isMatch becomes true on a bar:
Vertical line: line.new() at that bar’s bar_index, from low to high, extended extend.both (so it spans the full chart vertically).
Label: label.new() at the bar’s high, with mode-specific text:
Minute/Hourly/Daily: "HH:mm"
Weekly: "Tuesday HH:mm" (or whatever day selected)
Monthly: "Day 2 - HH:mm" (or chosen day)
Triangle marker: plotshape() draws a triangle up below the bar on every match (this happens regardless of showLine / showLabel).
Important practical implications
This uses the bar’s exchange/chart time (TradingView’s time, hour, minute, etc.), so results depend on the symbol/session and chart timezone settings.
On timeframes coarser than 1 minute, “Every Minute” still checks only the bar’s timestamp minute value; it won’t mark intra-bar minutes that don’t exist as separate bars.
Because it can create many objects (lines/labels), it sets max_labels_count=500. Lines are not capped here, so very dense marking can still clutter the chart.
If you tell me your intended use (e.g., “mark NY open,” “mark every 15m candle close,” “mark macro events weekly”), I can point out whether the current matching logic fits that precisely or needs adjustments (sessions, timezones, avoiding duplicates, limiting lines, etc.).
Dual MACD CrossWhat Is This Indicator?
This indicator is a visual tool for reading changes in market momentum.
Instead of giving buy or sell orders, it helps you see when the market’s short-term behavior starts to differ from its underlying direction. Think of it as a way to observe shifts in mood rather than make automatic decisions.
What Do the Lines Mean?
You will see three visual elements:
The thin green line represents the market’s short-term momentum.
It reacts quickly to recent price changes and shows what the market is doing right now.
The thicker white line represents the market’s reference trend.
It moves more slowly and reflects the broader, more stable direction of the market.
The yellow dotted line is the zero baseline.
It does not generate signals. Its only purpose is to help you visually judge whether momentum is generally positive (above zero) or negative (below zero).
How Should This Indicator Be Read?
The key is the relationship between the green and white lines.
When the green line is above the white line, short-term momentum is stronger than the market’s reference trend.
When the green line is below the white line, short-term momentum is weaker.
The indicator is not concerned with how high or low the lines are by themselves.
What matters is how they interact.
What Do the Triangle Markers Mean?
The small triangle markers highlight moments of transition.
An upward triangle appears when the green line crosses above the white line.
This suggests that short-term momentum is beginning to outperform the broader trend.
A downward triangle appears when the green line crosses below the white line.
This suggests that momentum is weakening relative to the broader trend.
These markers are attention points, not commands. They indicate potential change, not certainty.
Why Is the Zero Line Important?
The zero line provides context.
A crossover that happens above the zero line occurs while the market is already in a relatively strong state.
A crossover below the zero line happens in a weaker environment and may represent a failed move or an early attempt at reversal.
The same crossover can mean very different things depending on its position relative to zero.
What Is This Indicator Best Used For?
This indicator is best used to:
Observe early signs of trend changes
Compare short-term momentum versus underlying direction
Confirm what you are already seeing in price action or other indicators
It is not designed to:
Predict tops or bottoms precisely
Act as a standalone buy/sell system
Measure overbought or oversold conditions
A Simple Analogy
Imagine driving a car.
The green line is how hard you are pressing the accelerator.
The white line is your current speed.
The yellow zero line is the difference between moving forward or backward.
The triangles mark moments when acceleration begins to change the car’s actual movement.
The indicator helps you notice when effort starts to translate into direction.
The Right Way to Use It
This indicator does not tell you what to do.
It encourages you to ask better questions:
Is momentum starting to lead or lag?
Is this change supported by price structure?
Does the broader context confirm or contradict this signal?
Used this way, it becomes a tool for awareness, not prediction.
If you’d like, I can also provide:
A one-paragraph version for documentation
A training script for beginners
Or a minimal tooltip-style explanation for sharing with others
Institutional Cycle Intelligence SystemInstitutional Cycle Intelligence System: Architecture, Algorithms, and Application:
Abstract
The Institutional Cycle Intelligence System (ICIS) version 2.0 is a sophisticated Pine Script indicator designed to bridge the gap between retail technical analysis and quantitative hedge fund methodologies. Unlike standard oscillators (RSI, MACD) that rely on fixed lookback periods, ICIS utilizes Digital Signal Processing (DSP) and spectral analysis to dynamically identify, extract, and synthesize market cycles. This document details the system’s specialty, the mathematical underpinnings of its seven algorithms, and a strategic guide for its application in trading.
Part 1: The Specialty & Philosophy
1.1 The Problem with Static Indicators
Traditional technical indicators suffer from a fatal flaw: Stationarity Assumption. A 14-period RSI assumes the market’s "rhythm" is consistently relevant to 14 bars. However, financial markets are non-stationary; cycle lengths expand and contract based on volatility, liquidity, and macroeconomic events. A market might be oscillating on a 10-day cycle one month and shift to a 24-day cycle the next. Static indicators fail to adapt to these phase shifts, leading to false signals.
1.2 The ICIS Solution: Adaptive Spectral Analysis
The ICIS allows traders to visualize the market not as a linear trend, but as a composite of waves (frequencies). Its specialty lies in its "Ensemble Approach." Rather than relying on a single mathematical model, ICIS runs seven distinct advanced cycle detection algorithms simultaneously.
1.3 The "Intelligent" Consensus Engine
The core innovation of this script is the Intelligent Mode. It does not simply average the outputs of the seven models. Instead, it employs an adaptive weighting mechanism:
Normalization: It converts the raw output of each model into a standardized Z-score (standard deviation units) to ensure apples-to-apples comparison.
Scoring: It calculates a "Consistency Score" for each model. If a model is producing erratic, noisy signals, its weight is reduced. If a model detects a high-amplitude, clean sine wave, its weight is increased.
Synthesis: It fuses these weighted inputs into a single "Composite Signal" that represents the highest probability cycle currently driving price action.
Part 2: Algorithmic Deep Dive
The ICIS incorporates seven distinct methodologies drawn from physics, engineering, and econometrics. Understanding these algorithms is key to trusting the signals.
2.1 Ehlers Bandpass + Hilbert Transform
Origin: Digital Signal Processing (DSP).
The Logic: This model acts like a radio tuner. It filters out low-frequency trends and high-frequency noise, isolating a specific bandwidth of market data.
The Mechanism:
Bandpass Filter: Allows only frequencies within the user-defined cycle ranges (Short, Medium, Long) to pass through.
Hilbert Transform: A mathematical operation that shifts the signal by 90 degrees to create an analytic signal. This allows for the precise calculation of the instantaneous phase (where we are in the wave) and amplitude (how strong the wave is).
Strength: Excellent for identifying clean, sine-wave-like market behavior in ranging markets.
2.2 MESA Adaptive Cycle (Maximum Entropy Spectral Analysis)
Origin: Geophysical oil exploration.
The Logic: MESA provides high-resolution frequency estimation even when the data sample is short (a common limitation in trading).
The Mechanism: It uses a "Homodyne Discriminator." It measures the phase change of price relative to itself over time. By calculating the rate of phase change, it derives the dominant cycle period.
Strength: Highly responsive to rapid changes in market cycle length. It adapts faster than Fourier-based methods.
2.3 Autocorrelation Periodogram
Origin: Statistical Time Series Analysis.
The Logic: Markets often rhyme. Autocorrelation measures the similarity of the price series to a lagged version of itself.
The Mechanism: The script runs a loop testing lags from 5 to 150 bars. If price today correlates highly with price 20 days ago, it identifies a 20-day cycle.
Strength: The most robust method for confirming that a cycle actually exists physically, rather than being a mathematical artifact.
2.4 Empirical Mode Decomposition (EMD)
Origin: The Hilbert-Huang Transform (NASA).
The Logic: Markets are non-linear and non-stationary. EMD does not force data into sine waves (like Fourier). instead, it treats price like a rope made of different strands.
The Mechanism:
Sifting: It identifies local highs and lows to create upper and lower envelopes.
Mean Extraction: It subtracts the mean of these envelopes from the data to extract an "Intrinsic Mode Function" (IMF).
Residuals: It repeats this process to separate high-frequency noise (Short Cycle) from medium variations and long-term trends.
Strength: The "Holy Grail" of adaptive analysis. It handles trend reversals and sudden volatility spikes better than any linear filter.
2.5 Goertzel Power Spectrum
Origin: Telecommunications (used in decoding touch-tone phone sounds).
The Logic: A highly optimized version of the Discrete Fourier Transform (DFT). It scans specific frequencies to see which one has the most "Power" (Energy).
The Mechanism: The script calculates the Goertzel energy for various periods. The period with the highest energy is deemed the "Dominant Cycle" and is used to drive the oscillator.
Strength: Extremely precise at identifying the exact length of the current cycle (e.g., distinguishing between a 20-day and a 22-day cycle).
2.6 Singular Spectrum Analysis (SSA)
Origin: Meteorology and climatology.
The Logic: SSA decomposes a time series into principal components: Trend, Oscillatory (Cycle), and Noise.
The Mechanism: While a full SSA requires heavy matrix algebra (difficult in Pine Script), this implementation simulates SSA using weighted lag windows to separate eigen-components. It reconstructs the time series using only the oscillatory components.
Strength: Unrivaled noise reduction. It produces the smoothest "zero-lag" oscillators in the system.
2.7 Wavelet Multi-Resolution Analysis
Origin: Quantum Physics and Image Compression.
The Logic: Standard Fourier analysis loses time information (it tells you a frequency exists, but not when). Wavelets analyze both Frequency and Time simultaneously.
The Mechanism: The script passes price through a cascade of high-pass and low-pass filters (Haar-like decomposition).
Detail Coefficients: Capture high-frequency noise and short cycles.
Approximation Coefficients: Capture the underlying trend and long cycles.
Strength: Excellent for identifying "regime changes" where the market shifts from trending to ranging.
Part 3: Using the Code & Interface
3.1 Input Parameters
Model Selection: Defaults to "Intelligent" (recommended). You can switch to individual models (e.g., "EMD") to isolate their specific view.
Cycle Period Ranges:
Short (5-20): Captures swing trading noise and rapid reversals.
Medium (20-50): The primary swing cycle (often aligns with monthly flows).
Long (50-150): The structural trend cycle.
Advanced Settings:
Bandwidth (0.3): Controls how "wide" the filter is. Lower values = cleaner but lagging; Higher values = noisier but faster.
Signal Threshold (0.5): The level the oscillator must breach to be considered a "Strong" signal.
3.2 Visual Components
The Oscillators (Main Chart):
Red Line (Short): The fast heartbeat of the market.
Teal Line (Medium): The tradeable swing.
Blue Line (Long): The tidal direction.
Purple Line (Composite): The weighted average of all cycles. This is your primary trigger.
The Info Table: Displays the current exact period (in bars), phase (in degrees), and trend direction for all three cycle tiers. It also shows the "Confluence Score" (how many cycles agree).
Background Color: Changes dynamically based on cycle alignment.
Green: Bullish Confluence (2 or 3 cycles pointing up).
Red: Bearish Confluence (2 or 3 cycles pointing down).
Part 4: Trading Strategy & Application
The ICIS is designed to identify Turning Points and Trend Continuations.
4.1 The "Phasing" Concept
Understanding Phase is crucial. The script calculates phase in degrees (0° to 360°):
0° - 90° (Accumulation): The cycle has bottomed and is accelerating upward. Best time to enter.
90° - 180° (Markup): The cycle is mature but still rising. Hold positions.
180° - 270° (Distribution): The cycle has topped and is accelerating downward. Best time to short/sell.
270° - 360° (Decline): The cycle is mature in its downtrend. Hold shorts or cash.
4.2 Trade Setups
Setup A: The "Triple Confluence" Entry (Trend Following)
This is the safest signal, indicating all distinct time horizons are aligned.
Condition: The Short, Medium, and Long cycle lines are ALL sloping upwards.
Visual: Background turns bright Green.
Trigger: The Composite (Purple) line crosses above the Signal Threshold (+0.5).
Exit: When the Short Cycle (Red) crosses below the Medium Cycle (Teal).
Setup B: The "Cycle Bottom" (Reversal)
This catches the absolute low of a move.
Condition: The Long Cycle (Blue) is trending UP (Trend support).
Trigger: The Composite line is deeply negative (below -0.8) and crosses back ABOVE zero.
Validation: Wait for the "Cycle Bottom" circle marker to appear on the chart.
Stop Loss: Below the recent swing low.
Setup C: The "Divergence" Play (Advanced)
Condition: Price makes a Lower Low.
Indicator: The Composite Oscillator makes a Higher Low.
Logic: Momentum on the cyclical level is shifting bullish despite price action.
Execution: Enter on the first candle where the Composite line turns green (slopes up).
4.3 Interpreting the Information Table
The table is your dashboard.
Period: If the "Medium Period" is drastically changing (e.g., jumping from 20 to 50), the market is in a chaotic transition. Reduce position size.
Strength: Shows the cycle amplitude. If Strength < 20%, the market is chopping/sideways. Do not trade trend strategies. If Strength > 60%, the cycle is dominant; use aggressive targets.
Part 5: Optimization & Best Practices
5.1 Timeframes
While the math works on any timeframe, ICIS is computationally heavy and optimized for:
4H / 1D: Best for Swing Trading. The cycle periods (20-40 bars) align well with monthly/quarterly flows.
15m / 1H: Good for Intraday, but requires adjusting the "Short Cycle" inputs to be more sensitive (e.g., Min 5, Max 15).
5.2 Handling "Repainting" vs. "Recalculation"
This script uses max_bars_back and causal filters where possible. However, EMD and SSA are inherently adaptive.
Fact: The Phase calculation uses the Hilbert Transform, which requires a few bars of future data to be perfectly precise (theoretical limit).
Mitigation: The script uses a causal approximation of the Hilbert Transform (nz(src ) etc.) to minimize repainting.
Rule: Do not trade on the current forming bar. Wait for the bar to close to confirm the cycle direction.
5.3 Combining with Price Action
ICIS tells you the Time (When to trade), but Price Action tells you the Level (Where to trade).
Use ICIS to time the entry.
Use Support/Resistance or Supply/Demand zones to place the order.
Example: Price hits a Demand Zone + ICIS signals "Cycle Bottom" + Confluence turns Green = High Probability Trade.
Conclusion
The Institutional Cycle Intelligence System version 2.0 represents a paradigm shift from lagging indicators to predictive cycle modeling. By intelligently fusing seven different mathematical models, it cancels out the weaknesses of individual algorithms (like EMD's end-effect issues or Fourier's spectral leakage).
Summary of Workflow:
Check the Table: Is Cycle Strength high? Are cycles aligned?
Check the Background: Is it Green (Bullish) or Red (Bearish)?
Wait for the Composite Trigger: Cross of Zero or Cross of Threshold.
Execute: With defined risk based on market structure.
This tool provides the retail trader with the "X-Ray vision" into market structure typically reserved for quantitative trading desks.
Statistical Reversion FrameworkIntroduction and Core Philosophy
The Statistical Reversion Framework constitutes a sophisticated quantitative trading instrument designed to identify high-probability mean reversion opportunities across financial markets. Unlike traditional technical indicators that rely on a single dimension of market data, this framework adopts a multi-faceted approach, synthesizing statistical probability, volume profile analysis, institutional money flow proxies, and standard technical momentum into a singular composite score. The core philosophy driving this script is the concept of confluence through heterogeneity; by combining uncorrelated or loosely correlated market factors—such as price deviation (statistics), participant commitment (volume), and macro sentiment (intermarket data)—the algorithm aims to filter out the noise inherent in standard oscillators and isolate moments where market pricing has deviated unsustainably from its intrinsic equilibrium. This tool is specifically engineered to detect market extremes—tops and bottoms—where the probability of a counter-trend move or a snap-back to the mean is mathematically significant. It operates on the premise that while asset prices can remain irrational in the short term, they are bound by statistical variance and mean-reverting properties over longer horizons, particularly when institutional flows and volume exhaustion patterns align with those statistical extremes.
Methodology: The Composite Scoring Architecture
The underlying methodology of the framework relies on a weighted composite scoring system. Rather than generating binary buy or sell signals based on a threshold crossover, the script calculates a granular score ranging from zero to one hundred for various market dimensions. These dimension-specific scores are then weighted according to user-defined inputs to produce a final "Composite Score." This approach allows for a nuanced assessment of market conditions; a setup might have extreme statistical deviation but lack volume confirmation, resulting in a lower confidence score than a setup where price, volume, and macro factors all align. The algorithm normalizes all input data into a standardized scale, typically converting raw values—such as Z-Scores or volume ratios—into a zero-to-ten ranking before aggregating them. This normalization process is critical because it allows the algorithm to compare apples to oranges mathematically, treating a standard deviation of 3.0 and a Relative Strength Index (RSI) of 20 as compatible inputs within the same equation. By summing these normalized values and applying regime-based confidence adjustments, the framework produces a dynamic signal that adapts to the volatility and trend intensity of the current market environment.
Algorithmic Component I: Statistical Analysis via Multi-Timeframe Z-Scores
The backbone of the framework is the Statistical Component, which utilizes the Z-Score (or Standard Score) to quantify the degree of price deviation. The Z-Score measures how many standard deviations the current price is from its moving average. A crucial aspect of this algorithm is its fractal nature; it does not rely on a single lookback period. Instead, it computes Z-Scores across three distinct timeframes—Daily, Weekly, and Monthly—and within each timeframe, it calculates deviations for short, medium, and long-term periods. For instance, on the daily timeframe, it assesses deviation from 50-day, 200-day, and 500-day means simultaneously. This multi-timeframe approach is designed to filter out ephemeral noise. A price move that appears extreme on a 10-day basis but is normal on a 200-day basis is likely a trend pull-back rather than a reversal. Conversely, when the Z-Scores across daily, weekly, and monthly timeframes all register values beyond significant thresholds (such as 2.0 or 3.0 standard deviations), it indicates a rare fractal alignment where the asset is historically overextended on all relevant scales. The algorithm aggregates these nine distinct Z-Score data points to form the "Statistical Score," heavily rewarding scenarios where multiple timeframes show directional alignment, as these synchronized deviations often precede powerful mean-reversion events.
Algorithmic Component II: Volume Signature and Participation Analysis
While statistical deviation highlights where the price is, the Volume Component analyzes the conviction behind the move to determine if a reversal is imminent. This section of the code employs several sophisticated logic gates to identify specific volume signatures known as Capitulation and Exhaustion. The algorithm compares current volume against a 50-day moving average to generate a volume ratio. It then correlates this ratio with price action. For example, the script identifies "Capitulation" when price collapses significantly (more than 2%) on volume that is at least three times the average. This specific signature—panic selling—often marks the psychological wash-out necessary for a market bottom. Conversely, the script detects "Volume Exhaustion" when prices drift without conviction on extremely low volume, indicating a lack of participant interest in pushing the trend further. Furthermore, the algorithm integrates On-Balance Volume (OBV) analysis, specifically looking for divergences. It detects subtle shifts where the price makes a new low, but the OBV makes a higher low, signaling that smart money is accumulating positions despite the falling price. This divergence logic is automated using pivot-based high/low detection arrays, adding a layer of foreshadowing that price-only indicators often miss.
Algorithmic Component III: Institutional Proxy and Intermarket Correlations
The Institutional Component distinguishes this framework from standard retail indicators by incorporating intermarket data that serves as a proxy for macro sentiment and institutional flow. The script pulls data from extraneous tickers—specifically the VIX (Volatility Index), Government Bond Yields (10-year and 2-year), Copper, Gold, and the Dollar Index (DXY). The logic here is grounded in fundamental market mechanics. For instance, the script analyzes the VIX to gauge market fear; however, it applies a contrarian logic. An extremely high VIX (panic) coincident with a low equity price is scored as a bullish factor, while a complacently low VIX at market highs is viewed as bearish. Similarly, the algorithm analyzes the Yield Curve (the spread between 10-year and 2-year yields). A steepening or flattening curve provides context on economic expectations, influencing the score based on whether the environment is "risk-on" or "risk-off." The Copper/Gold ratio is utilized as a barometer for global economic health; rising copper relative to gold suggests industrial demand and growth, confirming bullish setups, whereas falling copper prices signal contraction. By integrating these non-price variables, the framework ensures that a trade signal is not just technically sound but is also supported by the broader macroeconomic undercurrents that drive institutional capital allocation.
Algorithmic Component IV: Technical Momentum and Structure
The final layer of input comes from standard Technical Analysis, which serves to fine-tune the timing of the entry. This component aggregates readings from the Relative Strength Index (RSI), Moving Average Convergence Divergence (MACD), Bollinger Bands, and Support/Resistance proximity. While Z-Scores measure linear distance from the mean, the RSI and Bollinger Bands measure the velocity and elasticity of that move. The algorithm assigns higher scores when RSI hits extreme levels (below 20 or above 80) and when price action pierces the outer bounds of the Bollinger Bands. Additionally, the MACD is monitored for histogram reversals and signal line crosses that align with the mean reversion bias. A unique feature of this component is the proximity logic, which calculates how close the current price is to a 50-period high or low. If a statistical extreme coincides with a retest of a major structural support level, the technical score is maximized. This ensures that the trader is not catching a falling knife in a void, but rather identifying a reversal at a location where technical structure provides a natural floor or ceiling for price.
Regime Detection and Confidence Adjustment
A critical vulnerability of mean reversion strategies is that they can suffer severe drawdowns during strong, unidirectional trending markets (momentum regimes). To mitigate this, the framework incorporates a Regime Detection module using the Average Directional Index (ADX) and volatility thresholds. The script calculates the ADX to measure trend strength regardless of direction. If the ADX is above a certain threshold (default 25), the market is classified as "Trending." The script then cross-references this with volatility data to classify the environment into regimes such as "Crisis," "Trending," "Range," or "Mean-Revert." This classification is not merely cosmetic; it actively influences the final output through a "Regime Confidence" multiplier. If the system detects a strong trending regime, it dampens the Composite Score, requiring extraordinary evidence from the other components to trigger a signal. Conversely, if the market is detected as "Mean-Revert" or "Low-Vol Range," the confidence multiplier boosts the score, making the system more sensitive to reversion signals. This adaptive logic helps protect the trader from fading strong breakouts while aggressively capitalizing on ranging markets.
Usage Instructions and Dashboard Interpretation
Traders utilizing this framework should primarily interact with the on-screen Dashboard, which provides a real-time summary of all computed metrics. The dashboard is organized hierarchically, with the "Composite Score" and "Signal Status" at the top. A Composite Score above 70 is generally considered actionable, with scores above 85 representing "Exceptional" setups. The Dashboard is color-coded: green hues indicate bullish/oversold conditions suitable for buying, while red hues indicate bearish/overbought conditions suitable for selling or shorting. Traders should look for "Confluence" across the rows. Ideally, a robust signal will show a high Statistical score (indicating price is cheap/expensive), a high Volume score (indicating capitulation or accumulation), and a supportive Institutional score. If the Composite Score is high but the Institutional score is low, the trader should proceed with caution, as the macro environment may not support the trade.
The chart visuals provide immediate entry triggers. "Strong Bottom" (Green Triangle) and "Strong Top" (Red Triangle) shapes appear when the Composite Score breaches the high threshold and Z-Scores are at extremes. These are the primary execution signals. Smaller "Potential" markers indicate developing setups that may require lower timeframe confirmation. Additionally, specific volume icons (Diamonds) will appear to denote Capitulation or Climax events. A trader should ideally wait for the candle to close to confirm these signals. The alerts configured in the script allow the trader to be notified of these events remotely. For risk management, because this is a mean reversion tool, stop-losses should typically be placed below the swing low of the capitulation candle (for longs) or above the swing high of the climax candle (for shorts), anticipating that the statistical extreme marks the distinct turning point. By systematically waiting for the Composite Score to align with the visual signals and verifying the regime context on the dashboard, the trader effectively filters out low-probability trades, engaging only when statistics, volume, and macro-economics align.
TZ - India VIX Volatility ZonesTZ – India VIX Volatility Zones is a long-term volatility analysis indicator designed to visually map important India VIX regimes using clearly defined horizontal zones and labels.
The indicator highlights how market volatility cycles between complacency, normal conditions, elevated risk, and panic phases. These zones are based on historical behavior of India VIX and help traders understand when risk is underpriced or overstretched.
This tool is especially useful for:
Index traders
Options sellers and buyers
Risk management and regime filtering
Long-term volatility study
How It Works
The script plots static, historically significant volatility zones on the India VIX chart and visually separates them using shaded bands and labels.
Volatility Zones Explained
1.Extreme Low Volatility (VIX 8–10)
Indicates market complacency and underpriced risk. Often precedes volatility expansion.
2.Low Volatility (VIX 10–13)
Stable market conditions with controlled movement.
3.Normal Volatility (VIX 13–18)
Healthy market behavior and balanced risk.
4.High Volatility (VIX 18–25)
Rising uncertainty and increased intraday swings.
5.Panic Zone (VIX 25–35+)
High fear environment, usually during major events or crises.
How Traders Can Use This Indicator
Identify volatility regimes before choosing option strategies
Avoid aggressive short-volatility trades during extreme zones
Prepare for volatility expansion during low-VIX phases
Use as a market risk context tool alongside price action
This indicator does not provide buy/sell signals. It is designed for contextual analysis and decision support.
Best Usage
Apply on India VIX (NSE:INDIAVIX)
Works best on Weekly and Monthly timeframes
Can be combined with index charts for volatility-based risk assessment
Disclaimer
This indicator is for educational and analytical purposes only.
It does not constitute financial advice or trade recommendations.
Users should apply proper risk management and confirm signals using additional analysis.
Pivot Edge ProOverview
Smart Pivot Analytics is a highly accurate technical analysis tool designed to identify and validate significant price levels. Unlike standard pivot indicators that only mark recent highs, this tool backtests each identified pivot against thousands of historical candlesticks to calculate its real-world “success rate.”
Key Features
Historical Backtesting: The indicator scans up to 4,900 historical columns to find every instance where price interacted with a specific pivot level.
Strength Score (%): Each level is assigned a percentage score based on its reversal rate. It calculates how many times the price has successfully reached and rejected the level, providing a statistical “hit rate.”
Dynamic Hit Counter: Displays the exact number of times a level has been tested (hit), helping traders distinguish between new levels and established “old” levels.
Smart Filtering: To keep the chart clean, the indicator automatically filters out weak levels and prevents “clutter” by merging levels that are too close together.
Infinite Left Projection: Lines extend left to infinity, allowing traders to see the historical significance of a level across the entire price history at a glance.
How to Trade with It
Red Levels (High Power > 75%): These are “Top Reaction Zones”. Expect a strong price rejection or significant breakout when these levels are tested.
Orange Levels (Medium Power): Suitable for profit targets or as secondary confirmation for entering a trade.
Encounter: Use these levels in conjunction with your existing strategy. When a high power pivot aligns with your entry signal, the probability of a successful trade increases significantly.
Technical Parameters
Lookback Period: Defines how far back in history the script calculates power.
Touch Radius: The "sensitivity" of the level (how close the price has to get to be considered a "hit").
Minimum Strength: A filter to show only the most reliable levels.
TCI Time Oracle - Intraday
🟢 Green Zone — Opening & Closing Liquidity Window
Time:
Opening Green: ~9:15 – 9:30 AM
Closing Green: ~3:15 – 3:30 PM
Market Character:
Highest liquidity of the day
Overnight positions unwind / fresh positions initiate
Strong directional intent often revealed
Smart money sets the day’s bias
Trading Insight:
Best zone for trend bias identification
Option premiums react fastest here
Not ideal for late entries, but excellent for confirmation
🔵 Blue Zone — Midday Compression / Algo Control
Time: ~11:15 AM – 12:00 PM
Market Character:
Volatility contraction
Algo-driven price control
Time decay dominates options
Fake breakouts and mean reversion
Trading Insight
Worst zone for aggressive option buying
Best for range scalping or staying flat
Institutions wait, retailers get chopped
🔴 Red Zone — Institutional Expansion / Trap Zone
Time: ~1:15 PM – 2:00 PM
Market Character:
Sudden volatility expansion
Institutional orders hit the market
Trend acceleration or sharp reversal
Options see rapid delta & gamma shift
Trading Insight:
High probability trend continuation or trap creation
Strong zone for directional option trades
Requires strict risk management
Big Picture Takeaway
Green sets the intent
Blue compresses and traps
Red expands and delivers the real move
This time-zone behavior is exactly why one strategy cannot work all day. Edge comes from trading the right setup in the right time window.
Sector Rotation ULTIMATE: 7 Narrativas IndependientesSector Rotation ULTIMATE: Crypto Narrative Rotation (7 Independent Sectors)
Advanced indicator displaying the relative strength of major crypto sectors through 7 independently normalized lines (0-100):
• Layer1 (ETH, SOL, BNB, TON, etc.) - Pink
• Enterprise (XRP, HBAR, XLM, QNT, VET) - Yellow
• DeFi (UNI, AAVE, MKR, LDO, CRV, etc.) - Cyan
• Memecoins (SHIB, DOGE, PEPE, WIF, FLOKI, BONK) - Green
• AI (TAO, FET, ICP, GRT, etc.) - Orange
• L2 / Scalability (ARB, OP, MATIC, STRK) - Purple
• RWA + Infra (ONDO, LINK) - Brown
Each sector sums the dominance of its top coins (40 total) and is normalized independently so the lines cross constantly, revealing real capital rotations.
- Colored fills to visually highlight the leading sector
- Works perfectly on any timeframe (clean daily data, no intraday noise)
- Ideal for spotting altseason, sector rotations, and entry timing
Use on CRYPTOCAP:TOTAL. The definitive narrative oscillator for 2026!
#Crypto #Altcoins #SectorRotation #DeFi #Memecoins #AI #RWA
4MA / 4MA[1] Forward Projection with 4 SD Forecast Bands4MA / 4MA Projection + 4 SD Bands + Cross Table is a forward-projection tool built around a simple moving average pair: the 4-period SMA (MA4) and its 1-bar lagged value (MA4 ). It takes a prior MA behavior pattern, projects that structure forward, and wraps the projected mean path with four Standard Deviation (SD) bands to visualize probable future price ranges.
This indicator is designed to help you anticipate:
Where the MA structure is likely to travel next
How wide the “expected” future price corridor may be
Where a future MA4 vs MA4 crossover is most likely to occur
When the real (live) crossover actually prints on the chart
What you see on the chart
1) Live moving averages (current market)
MA4 tracks the short-term mean of price.
MA4 is simply the previous bar’s MA4 value (a 1-bar lag).
Their relationship (MA4 above/below MA4 ) gives a clean, minimal read on trend alignment and directional bias.
2) Projected MA path (forward curve)
A forward “ghost” of the MA structure is drawn ahead of price. This projected curve represents the indicator’s best estimate of how the moving average structure may evolve if the market continues to rhyme with the selected historical behavior window.
3) 4 Standard Deviation bands (predictive future price ranges)
Surrounding the projected mean path are four SD envelopes. Think of these as forecast corridors:
Inner bands = tighter “expected” range
Outer bands = wider “stress / extreme” range
These bands are not a guarantee—rather, they’re a structured way to visualize “how far price can reasonably swing” around the projected mean based on observed volatility.
4) Vertical projection lines (most probable cross zone)
Within the projected region you’ll see vertical lines running through the bands. These lines mark the most probable zone where MA4 and MA4 are expected to cross in the projection.
In plain terms:
The projected MAs are two curves.
When those curves are forecasted to intersect, the script marks the intersection region with a vertical line.
This gives you a forward “timing window” for a potential MA shift.
5) Cross Table (top-right)
The table is your confirmation layer. It reports:
Current MA4 value
Current MA4 value
Whether MA4 is above or below MA4
The most recent BUY / SELL cross event
When a real, live crossover happens on the actual chart:
It registers as BUY (MA4 crosses above MA4 )
Or SELL (MA4 crosses below MA4 )
…and the table updates immediately so you can confirm the event without guessing.
How to use it
Practical workflow
Use the projected SD bands as future range context
If price is projected to sit comfortably inside inner bands, the market is behaving “normally.”
If price reaches outer bands, you’re in a higher-volatility / stretched scenario.
Use vertical lines as a “watch zone”
Vertical lines do not force a trade.
They act like a forward “heads-up”: this is the most likely window for an MA crossover to occur if the projection holds.
Use the table for confirmation
When the crossover happens for real, the table is your confirmation signal.
Combine it with structure (support/resistance, trendlines, market context) rather than trading it in isolation.
Notes and best practices
This is a projection tool: it helps visualize a structured forward hypothesis, not a certainty.
SD bands are best used as forecast corridors (risk framing, range planning, and expectation management).
The table is the execution/confirmation layer: it tells you what the MAs are doing now.
