Per Bak Self-Organized CriticalityTL;DR: This indicator measures market fragility. It measures the system's vulnerability to cascade failures and phase transitions. I've added four independent stress vectors: tail risk, volatility regime, credit stress, and positioning extremes. This allows us to quantify how susceptible markets are to disproportionate moves from small shocks, similar to how a steep sandpile is primed for avalanches.
Avalanches, forest fires, earthquakes, pandemic outbreaks, and market crashes. What do they all have in common? They are not random.
These events follow power laws - stable systems that naturally evolve toward critical states where small triggers can unleash catastrophic cascades.
For example, if you are building a sandpile, there will be a point with a little bit additional sand will cause a landslide.
Markets build fragility grain by grain, like a sandpile approaching avalanche.
The Per Bak Self-Organized Criticality (SOC) indicator detects when the markets are a few grains away from collapse.
This indicator is highly inspired by the work of Per Bak related to the science of self-organized criticality .
As Bak said:
"The earthquake does not 'know how large it will become'. Thus, any precursor state of a large event is essentially identical to a precursor state of a small event."
For markets, this means:
We cannot predict individual crash size from initial conditions
We can predict statistical distribution of crashes
We can identify periods of increased systemic risk (proximity to critical state)
BTW, this is a forwarding looking indicator and doesn't reprint. :)
The Story of Per Bak
In 1987, Danish physicist Per Bak and his colleagues discovered an important pattern in nature: self-organized criticality.
Their sandpile experiment revealed something: drop grains of sand one by one onto a pile, and the system naturally evolves toward a critical state. Most grains cause nothing. Some trigger small slides. But occasionally a single grain triggers a massive avalanche.
The key insight is that we cannot predict which grain will trigger the avalanche, but you can measure when the pile has reached a critical state.
Why Markets Are the Ultimate SOC System?
Financial markets exhibit all the hallmarks of self-organized criticality:
Interconnected agents (traders, institutions, algorithms) with feedback loops
Non-linear interactions where small events can cascade through the system
Power-law distributions of returns (fat tails, not normal distributions)
Natural evolution toward fragility as leverage builds, correlations tighten, and positioning crowds
Phase transitions where calm markets suddenly shift to crisis regimes
Mathematical Foundation
Power Law Distributions
Traditional finance assumes returns follow a normal distribution. "Markets return 10% on average." But I disagree. Markets follow power laws:
P(x) ∝ x^(-α)
Where P(x) is the probability of an event of size x, and α is the power law exponent (typically 3-4 for financial markets).
What this means: Small moves happen constantly. Medium moves are less frequent. Catastrophic moves are rare but follow predictable probability distributions. The "fat tails" are features of critical systems.
Critical Slowing Down
As systems approach phase transitions, they exhibit critical slowing down—reduced ability to absorb shocks. Mathematically, this appears as:
τ ∝ |T - T_c|^(-ν)
Where τ is the relaxation time, T is the current state, T_c is the critical threshold, and ν is the critical exponent.
Translation: Near criticality, markets take longer to recover from perturbations. Fragility compounds.
Component Aggregation & Non-Linear Emergence
The Per Bak SOC our index aggregates four normalized components (each scaled 0-100) with tunable weights:
SOC = w₁·C_tail + w₂·C_vol + w₃·C_credit + w₄·C_position
Default weights (you can change this):
w₁ = 0.34 (Tail Risk via SKEW)
w₂ = 0.26 (Volatility Regime via VIX term structure)
w₃ = 0.18 (Credit Stress via HYG/LQD + TED spread)
w₄ = 0.22 (Positioning Extremes via Put/Call ratio)
Each component uses percentile ranking over a 252-day lookback combined with absolute thresholds to capture both relative regime shifts and extreme absolute levels.
The Four Pillars Explained
1. Tail Risk (SKEW Index)
Measures options market pricing of fat-tail events. High SKEW indicates elevated outlier probability.
C_tail = 0.7·percentrank(SKEW, 252) + 0.3·((SKEW - 115)/0.5)
2. Volatility Regime (VIX Term Structure)
Combines VIX level with term structure slope. Backwardation signals acute stress.
C_vol = 0.4·VIX_level + 0.35·VIX_slope + 0.25·VIX_ratio
3. Credit Stress (HYG/LQD + TED Spread)
Tracks high-yield deterioration versus investment-grade and interbank lending stress.
C_credit = 0.65·percentrank(LQD/HYG, 252) + 0.35·(TED/0.75)·100
4. Positioning Extremes (Put/Call Ratio)
Detects extreme hedging demand through percentile ranking and z-score analysis.
C_position = 0.6·percentrank(P/C, 252) + 0.4·zscore_normalized
What the Indicator Really Measures?
Not Volatility but Fragility
Markets Going Down ≠ Fragility Building (actually when markets go down, risk and fragility are released)
The 0-100 Scale & Regime Thresholds
The indicator outputs a 0-100 fragility score with four regimes:
🟢 Safe (0-39): System resilient, can absorb normal shocks
🟡 Building (40-54): Early fragility signs, watch for deterioration
🟠 Elevated (55-69): System vulnerable
🔴 Critical (70-100): Highly susceptible to cascade failures
Further Reading for Nerds
Bak, P., Tang, C., & Wiesenfeld, K. (1987). "Self-organized criticality: An explanation of 1/f noise." Physical Review Letters.
Bak, P. & Chen, K. (1991). "Self-organized criticality." Scientific American.
Bak, P. (1996). How Nature Works: The Science of Self-Organized Criticality. Copernicus.
Feedback is appreciated :)
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Advanced ICC Multi-Timeframe 1.0Advanced ICC Multi-Timeframe Trading System
A comprehensive implementation and interpretation of the Indication, Correction, Continuation (ICC) trading methodology made popular by Trades by Sci, enhanced with advanced multi-timeframe analysis and automation features.
⚠️ CRITICAL TRADING WARNINGS:
DO NOT blindly follow BUY/SELL signals from this indicator
This indicator shows potential entry points but YOU must validate each trade
PAPER TRADE EXTENSIVELY before risking real capital
BACKTEST THOROUGHLY on your chosen instruments and timeframes
The ICC methodology requires understanding and discretion - automated signals are guidance only
This tool aids analysis but does not replace proper trade planning, risk management, or trader judgment
⚠️ Important Disclaimers:
This indicator is not endorsed by or affiliated with Trades by Sci
This is an early implementation and interpretation of the ICC methodology
May not work exactly as Trades by Sci executes his trades and entries
Requires further debugging, backtesting, and real-world validation
Completely free to use - no purchase required
I'm just one person obsessed with this method and wanted some better visualization of the chart/entries
About ICC:
The ICC method identifies complete market cycles through three phases: Indication (breakout), Correction (pullback), and Continuation (entry). This indicator automates the identification of these phases and adds powerful features for modern traders.
Key Features:
Multi-Timeframe Capabilities:
Automatic timeframe detection with optimized settings for 5m, 15m, 30m, 1H, 4H, and Daily charts
Higher timeframe overlay to view HTF ICC levels on lower timeframe charts for precise entry timing
Smart defaults that adjust swing length and consolidation detection based on your timeframe
Advanced Phase Tracking:
Complete ICC cycle tracking: Indication, Correction, Consolidation, Continuation, and No Setup phases
Live structure detection shows potential peaks/troughs before full confirmation
Intelligent invalidation logic detects failed setups when market structure reverses
Dynamic phase backgrounds for instant visual confirmation
Three Types of Entry Signals:
Traditional Entries - Price crosses back through the original indication level (strongest signals)
"BUY" (green) / "SELL" (red)
Breakout Entries - Price breaks out of consolidation range in the same direction
"BUY" (green) / "SELL" (red)
Reversal Entries (Optional, can be toggled off) - Price breaks consolidation in opposite direction, indicating failed setup
"⚠ BUY" (yellow) / "⚠ SELL" (orange)
More aggressive, counter-trend signals
Can be disabled for more conservative trading
Professional Features:
Volatility-based support/resistance zones (ATR-adjusted) that adapt to market conditions
Historical zone tracking (0-3 configurable) with visual hierarchy
Comprehensive real-time info table displaying all key metrics
Full alert system for entries, indications, and consolidation detection
Visual distinction between high-confidence trend entries and cautionary reversal entries
📖 USAGE GUIDE
Entry Signal Types:
The indicator provides three types of entry signals with visual distinction:
Strong Entries (High Confidence):
"BUY" (bright green) / "SELL" (bright red)
Includes traditional entries (crossing back through indication level) and breakout entries (breaking consolidation in trend direction)
These are trend continuation or breakout signals with higher probability
Recommended for all traders
Reversal Entries (Caution - Counter-Trend):
"⚠ BUY" (yellow) / "⚠ SELL" (orange)
Triggered when price breaks out of correction/consolidation in the OPPOSITE direction
Indicates a failed setup and potential trend reversal
More aggressive, counter-trend plays
Can be toggled off in settings for more conservative trading
Recommended only for experienced traders or after thorough backtesting
Swing Length Settings:
The swing length determines how many bars on each side are needed to confirm a swing high/low. This is the most important setting for tuning the indicator to your style.
Auto Mode (Recommended for beginners): Toggle "Use Auto Timeframe Settings" ON
5-minute: 30 bars
15-minute: 20 bars
30-minute: 12 bars
1-hour: 7 bars
4-hour: 5 bars
Daily: 3 bars
Manual Mode: Toggle "Use Auto Timeframe Settings" OFF
Lower values (3-7): More aggressive, detects smaller swings
Pros: More signals, faster entries, catches smaller moves
Cons: More noise, more false signals, requires tighter stops
Best for: Scalping, active day trading, volatile markets
Higher values (12-20): More conservative, only major swings
Pros: More reliable signals, fewer false breakouts, clearer structure
Cons: Fewer signals, delayed entries, might miss smaller opportunities
Best for: Swing trading, position trading, trending markets
Default Manual Setting: 7 bars (balanced for 1H charts)
Minimum: 3 bars
Consolidation Bars Setting:
Determines how many bars without new structure are needed before flagging consolidation.
Lower values (3-10): Faster detection, catches brief pauses, more sensitive
Best for: Lower timeframes, volatile markets, avoiding any chop
Higher values (20-40): More reliable, only flags true extended consolidation
Best for: Higher timeframes, trending markets, patient traders
Current defaults scale with timeframe (more bars needed on shorter timeframes)
Historical S/R Zones:
Shows previous support and resistance levels to provide context.
Default: 2 historical zones (shows current + 2 previous)
Range: 0-3 zones
Visual Hierarchy: Older zones are more transparent with dashed borders
Usage: Higher numbers (2-3) show more historical context but can clutter the chart. Start with 2 and adjust based on your preference.
Live Structure Feature (Yellow Warning ⚠):
Provides early warning of potential structure changes before full confirmation.
What it does: Detects potential swing highs/lows after just 2 bars instead of waiting for full swing_length confirmation
Live Peak: Shows when a high is followed by 2 lower closes (potential top forming)
Live Trough: Shows when a low is followed by 2 higher closes (potential bottom forming)
Important: These are UNCONFIRMED - they may be invalidated if price reverses
Use case: Get early awareness of potential reversals while waiting for confirmation
Displayed in: Info table only (no visual markers on chart to reduce clutter)
Only shows: Peaks higher than last swing high, or troughs lower than last swing low (filters out noise)
Higher Timeframe (HTF) Analysis:
View higher timeframe ICC structure while trading on lower timeframes.
How to enable: Toggle "Show Higher Timeframe ICC" ON
Setup: Set "Higher Timeframe" to your reference timeframe
Example: Trading on 15-minute? Set HTF to 240 (4-hour) or 60 (1-hour)
Example: Trading on 5-minute? Set HTF to 60 (1-hour) or 15 (15-minute)
What it shows:
HTF indication levels displayed as dashed lines
Blue = HTF Bullish Indication
Purple = HTF Bearish Indication
HTF phase and levels shown in info table
Trading workflow:
Check HTF phase for overall market direction
Wait for HTF correction phase
Drop to lower timeframe to find precise entries
Enter when lower TF shows continuation in alignment with HTF
Best practice: HTF should be 3-4x your trading timeframe for best results
Reversal Entries Toggle:
Default: ON (shows all signal types)
Toggle OFF for more conservative trading (only trend continuation signals)
Recommended: Backtest with both settings to see which works better for your style
New traders should consider disabling reversal entries initially
Volatility-Based Zones:
When enabled, support/resistance zones automatically adjust their height based on ATR (Average True Range).
More volatile = wider zones
Less volatile = tighter zones
Toggle OFF for fixed-width zones
Community Feedback Welcome:
This is an evolving project and your input is valuable! Please share:
Bug reports and issues you encounter
Feature requests and suggestions for improvement
Results from your backtesting and live trading experience
Feedback on the reversal entry feature (too aggressive? working well?)
Ideas for better aligning with the ICC methodology
Perfect for traders learning or implementing the ICC methodology with the benefit of modern automation, multi-timeframe analysis, and flexible entry signal options.
FAIRPRICE_VWAP_RDFAIRPRICE_VWAP_RD
This script plots an **anchored VWAP (Volume Weighted Average Price)** that resets
based on the user-selected anchor period. It acts as a dynamic “fair value” line
that reflects where the market has actually transacted during the chosen period.
FEATURES
- Multiple anchor options: Session, Week, Month, Quarter, Year, Decade, Century,
Earnings, Dividends, or Splits.
- Intelligent handling of the “Session” anchor so it works correctly on both 1m
(resets each new day) and 1D (continuous, non-resetting VWAP).
- Manual VWAP calculation using cumulative(price * volume) and cumulative(volume),
ensuring the line is stable and works on all timeframes.
- Optional hiding of VWAP on daily or higher charts.
- Offset input for horizontal shifting if desired.
- VWAP provides a true “fair price” reference for trend, mean-reversion,
and institutional-level analysis.
PURPOSE
This indicator solves the common problem of VWAP behaving incorrectly on higher
timeframes, on synthetic data, or with unusual anchors. By implementing VWAP
manually and allowing flexible reset conditions, it functions reliably as
an institutional-style fair value benchmark across any timeframe.
RSI_RDRSI_RD - RSI Divergence Detector (Ryan DeBraal)
This script plots a standard RSI along with advanced automatic divergence detection.
It identifies four types of divergences using pivot logic and configurable
lookback windows. Signals appear directly on the RSI line as plotted marks and labels.
FEATURES
- Standard RSI with user-defined length and source.
- Midline (50), overbought (70), and oversold (30) levels with shaded background.
- Automatic detection of:
• Regular Bullish Divergence
• Regular Bearish Divergence
• Hidden Bullish Divergence
• Hidden Bearish Divergence
- Each divergence type can be toggled on/off individually.
- Pivot-based detection using left/right lookback lengths.
- Range filter (bars since pivot) to avoid stale or invalid divergences.
- Colored markers and labels placed exactly on pivot points.
- Alerts for all four divergence conditions.
PURPOSE
This indicator makes RSI divergence trading systematic and visual.
It highlights when price action disagrees with RSI momentum — often signaling
exhaustion, reversal setups, or continuation opportunities depending on the divergence type.
Ideal for combining with trend filters, VWAP, or ORB structures.
Quantrader📊 Overview
This custom indicator combines intraday session analysis with multi-timeframe trend confirmation to identify high-probability trading opportunities. It features:
Custom intraday session tracking (GMT+7 timezone)
Multi-level moving average confluence (SMA 20, 100, 200)
Bollinger Bands mean reversion signals
Key intraday reference levels
⚙️ Core Components
1. Custom Intraday Session Tracking
Session Start: 7:00 AM GMT+7 (Vietnamese market open)
Calculates per session:
Intraday High/Low (resets at 7:00 AM daily)
Intraday Midline = (Session High + Session Low) / 2
Pre-Day Center = Previous day's midline (carried forward)
Open Day = First 15-minute candle's open price
2. Trend Analysis Framework
SMA 20 (Short-term momentum)
SMA 100 (Medium-term trend)
SMA 200 (Long-term trend direction)
Bollinger Bands (20-period, 2 standard deviations)
3. Signal Detection Logic
Bullish Mean Reversion Setup:
javascript
Condition 1: Green candle closes ABOVE Upper Bollinger Band
Condition 2: Following candle is ALSO green
→ Triggers: Green highlight + Triangle below bar
Bearish Mean Reversion Setup:
javascript
Condition 1: Red candle closes BELOW Lower Bollinger Band
Condition 2: Following candle is ALSO red
→ Triggers: Red highlight + Triangle above bar
🎯 Visual Elements
Element Color Description
Intraday Midline Blue Real-time session midpoint
Pre-Day Center Yellow Yesterday's midline (reference)
Open Day Purple (dashed) Day's opening price
SMA 20 Red Short-term trend
SMA 100 Green Medium-term trend
SMA 200 Orange Long-term trend
Bollinger Bands Red/Green/Blue Volatility boundaries
Bull Signal Green triangle ↓ Oversold bounce potential
Bear Signal Red triangle ↑ Overbought rejection potential
📈 Trading Applications
1. Trend Confirmation
Bullish Alignment: Price > All SMAs + Above Intraday Midline
Bearish Alignment: Price < All SMAs + Below Intraday Midline
2. Mean Reversion Opportunities
Overbought Scenario: Consecutive green candles above Upper BB → Potential reversal
Oversold Scenario: Consecutive red candles below Lower BB → Potential bounce
3. Intraday Level Trading
Intraday Midline: Dynamic support/resistance
Pre-Day Center: Psychological reference level
Open Day: Key opening price level
⚡ Key Features
Automatic Session Reset: Daily at 7:00 AM GMT+7
Multi-Timeframe Confluence: Combines intraday, daily, and trend analysis
Clean Visual Design: Non-cluttered, focused on key levels
Real-Time Calculation: All levels update with each new candle
🛠️ Recommended Settings
Timeframe: 15-minute to 1-hour charts
Markets: Forex, Indices, Commodities
Best Pairs: EURUSD, XAUUSD, VN30, USDJPY
Trading Style: Swing trading, Day trading
📖 Usage Tips
Trend Trading: Enter in direction of SMA alignment (20 > 100 > 200 for bullish)
Mean Reversion: Use BB signals at key intraday levels (Midline, Pre-Day Center)
Confirmation: Wait for candle close above/below key levels
Risk Management: Place stops beyond opposite intraday extreme
🎨 Customization Options
Users can modify:
Session start time (line 6)
Bollinger Band parameters (length, multiplier)
SMA periods
Color schemes
ADX_RDADX_RD - Average Directional Index (Ryan DeBraal)
This script plots a refined version of the **ADX (Average Directional Index)**,
used to measure trend strength regardless of trend direction. It includes
custom smoothing, modified DM (Directional Movement) logic, dynamic coloring,
and a built-in 20-level threshold.
FEATURES
- Calculates +DI, –DI, and ADX using standard Wilder smoothing (RMA).
- Signal color turns **white** when ADX < 20 (low-trend or choppy conditions).
- Signal color turns **blue** when ADX >= 20 (trend strengthening).
- Horizontal dotted reference line at **20**, a widely used threshold:
ADX < 20 → weak or ranging market
ADX > 20 → strengthening trend
- Works on all timeframes, supports custom smoothing lengths.
PURPOSE
This indicator helps identify when a market is trending vs when it is flat.
It does not indicate direction by itself — only the strength of the move —
making it ideal for confirming breakout setups, trend-following entries,
and filtering out low-probability trades during chop.
ORB_RDORB_RD - Opening Range Box (Ryan DeBraal)
This indicator automatically draws a high/low box for the first portion of
each trading day, automatically stepping the range window from 15, 30, 45,
up to 60 minutes after the session starts. The box updates live as the range
forms, then optionally extends across the rest of the session.
FEATURES
-----------------------------------------------------------------------------
• Opening Range Detection
- Automatically ladders the range window: 0–15, 0–30, 0–45, 0–60 minutes
- Automatic reset at each new trading day
- Live high/low updates while inside the 0–60 minute window
• Auto-Drawing Range Box
- Draws a dynamic rectangle as the range forms
- Top and bottom update with every new high/low
- Extends sideways in real time during formation
- Optional full-day extension after the 60-minute range finalizes
• Customizable Visuals
- Adjustable fill transparency
- Mild green tint by default for clarity
PURPOSE
-----------------------------------------------------------------------------
This tool highlights the evolving opening range, a widely used intraday
reference for breakout traders, mean-reversion setups, and session structure
analysis. Ideal for:
• Identifying early support and resistance
• Framing breakout and pullback decisions
• Tracking intraday trend bias after the morning range
TREND_34EMA_RDTREND_34EMA_RD - Enhanced 34 EMA Trend Suite (Ryan DeBraal)
This indicator overlays a trend-adaptive 34 EMA along with optional ATR-based
volatility bands, trend-strength scoring, and crossover alerts. It is built
to give a clean, fast visual read on the current trend direction, volatility,
and momentum quality.
FEATURES
-----------------------------------------------------------------------------
• Core 34 EMA Trend Line
- Standard EMA calculation (default length 34)
- Aqua coloring for clean visibility
- Adjustable line thickness
• ATR-Based Volatility Bands
- Upper and lower bands derived from ATR
- Adjustable ATR length and multiplier
- Optional shaded channel for volatility visualization
- Helps identify trend stability and over-extension
• Trend Strength Score
- Measures slope of the EMA over a lookback window
- Normalizes slope using ATR for consistency across markets
- Outputs a 0–100 score
- Auto-updating label placed at the latest bar
• Gray for weak trend
• Orange for moderate trend
• Green for strong trend
• Optional Crossover Signals
- Detects when price crosses above or below the EMA
- Can display arrows on the chart
- Built-in alert conditions
PURPOSE
-----------------------------------------------------------------------------
This suite provides a clean, minimalistic way to monitor directional bias,
volatility, and trend quality. Ideal for:
• Identifying early trend shifts
• Confirming trend continuation
• Filtering trades based on trend strength
• Detecting over-extension using volatility bands
MACD_RDMACD_RD - Moving Average Convergence Divergence (Ryan DeBraal)
This indicator plots a standard MACD along with a color-adaptive histogram and
integrated momentum-shift alerts. It preserves the normal MACD structure while
improving visual clarity and signal recognition.
FEATURES
-----------------------------------------------------------------------------
• Standard MACD Calculation
- Fast MA (12 by default)
- Slow MA (26)
- Signal line (9)
- Choice between SMA/EMA for both MACD and Signal smoothing
• Color-Changing Histogram
- Green shades for positive momentum
- Red shades for negative momentum
- Lighter/darker tones depending on whether momentum is increasing or fading
- 50% opacity for improved readability
• Crossover-Based MACD Line Coloring
- MACD line turns green on bullish cross (MACD > Signal)
- MACD line turns red on bearish cross (MACD < Signal)
- Default blue when no crossover occurs
• Momentum-Shift Alerts
- Alerts when histogram flips direction
PURPOSE
-----------------------------------------------------------------------------
This MACD version emphasizes momentum shifts and trend transitions by
highlighting subtle histogram changes and providing clean crossover visuals.
Ideal for:
• Identifying early momentum reversals
• Filtering breakout/trend setups
• Confirming trend continuation vs exhaustion
Watchlist Volume Surge AlertOverview
This indicator is designed for traders who monitor large watchlists and need instant notification when a stock is experiencing unusual volume activity relative to its recent history.
Standard volume indicators often include the current day's volume in the average calculation. This causes a problem: if a stock is having a massive breakout, that high volume pulls the average up immediately, making it harder to hit the "relative" threshold.
This script solves that by comparing the current volume against the Simple Moving Average (SMA) of the previous n bars. This ensures a clean baseline and accurate alerts, even during massive volatility.
Key Features
Smart RVOL Calculation: Calculates Relative Volume (RVOL) based on the previous 30 bars (adjustable), ensuring the current breakout doesn't skew the average.
Visual Clarity:
Bars: Normal volume is transparent. Surge volume turns bright Teal (Bullish Close) or Red (Bearish Close).
Background: The indicator panel background highlights when a surge is active, making it impossible to miss when scanning visually.
Data Window: Displays the exact RVOL ratio (e.g., 2.11) in the Data Window for verification.
Watchlist Alert Optimized: Specifically designed to work with TradingView's "Any alert function call" or standard condition alerts across multiple tickers.
How to Set Up Alerts
This script is perfect for setting a single alert on a large watchlist to catch breakouts as they happen.
Add the indicator to your chart.
Go to the Alerts menu and create a new alert.
Condition: Select Watchlist Volume Surge Alert.
Trigger: Select "Once Per Bar".
Note: Using "Once Per Bar" ensures you are notified the moment the volume crosses the threshold during the trading day, rather than waiting for the market to close.
Message: The script includes a dynamic message: "Volume Surge! {{ticker}} volume is {{plot("RVOL Ratio")}}x the average."
Settings
Average Length (Days): The lookback period for the volume average (Default: 30).
Alert Threshold (x Average): The multiple required to trigger an alert (Default: 1.5x).
Note: This works better when you have a watchlist with similar volatility and/or market cap
Multi-Tool VWAP + EMAs (Multi-Timeframe) + Key LevelsDescription
This indicator combines several commonly used technical analysis tools into a single script, especially useful for traders using the free version of TradingView or anyone looking to reduce the number of indicators on their chart.
The goal is to provide clear visual references for trend, structure, and key levels—without generating buy/sell signals or automated trading functions.
Included Features
1. VWAP (session-anchored)
Source: HLC3
Purple line, thickness 2
Useful as a reference for daily institutional average price.
2. EMAs of the current timeframe
EMA 200 (red, thickness 3)
EMA 9 (green, thickness 1)
These EMAs help visualize long-term trend and short-term momentum.
3. Dynamic EMAs (MTF – Multi-Timeframe)
The indicator displays the 200 EMA from higher timeframes as dynamic horizontal levels:
5 minutes
15 minutes
30 minutes
1 hour
4 hours
1 day
Each level includes a descriptive label such as “15 min EMA 200”.
These EMAs serve as reference points for potential support/resistance areas coming from higher timeframes.
4. Automatic Key Levels
The indicator plots several important price levels:
Previous day:
PDH (Previous Day High)
PDL (Previous Day Low)
Previous Day 50% Fibonacci level
Pre-market (04:00–09:30 exchange time):
PMH (Pre-Market High)
PML (Pre-Market Low)
Current session:
Open (session opening price)
Previous Close (prior day’s closing price)
Purpose and Scope
This script is designed to provide basic visual reference points to support discretionary analysis.
It does not generate signals or trading suggestions, and it is not intended to predict future price movements.
How to Use It
Enable or disable each block in the Inputs section according to your analysis style.
Observe how the levels, EMAs, and VWAP interact with market structure.
Use it as a visual complement to your personal technical analysis.
Limitations
This indicator is not a trading system and does not guarantee results.
It does not include alerts, backtesting, or entry/exit logic.
Some values (such as PMH/PML) depend on the symbol’s exchange trading hours.
Credits
Designed as an educational and analytical tool for traders seeking to simplify their charts without losing key information.
Echo Chamber [theUltimator5]The Echo Chamber - When history repeats, maybe you should listen.
Ever had that eerie feeling you've seen this exact price action before? The Echo Chamber doesn't just give you déjà vu—it mathematically proves it, scales it, and projects what happened next.
📖 WHAT IT DOES
The Echo Chamber is an advanced pattern recognition tool that scans your chart's history to find segments that closely match your current price action. But here's where it gets interesting: it doesn't just find similar patterns - It expands and contracts the time window to create a uniquely scaled fractal. Patterns don't always follow the same timeframe, but they do follow similar patterns.
Using a custom correlation analysis algorithm combined with flexible time-scaling, this indicator:
Finds historical price segments that mirror your current market structure
Scales and overlays them perfectly onto your current chart
Projects forward what happened AFTER that historical match
Gives you a visual "echo" from the past with a glimpse into potential futures
══════════════════════════════
HOW TO USE IT
This indicator starts off in manual mode, which means that YOU, the user, can select the point in time that you want to project from. Simply click on a point in time to set the starting value.
Once you select your point in time, the indicator will automatically plot the chosen historical chart pattern and correlation over the current chart and project the price forwards based on how the chart looked in the past. If you want to change the point in time, you can update it from the settings, or drag the point on the chart over to a new position.
You can manually select any point in time, and the chart will quickly update with the new pattern. A correlation will be shown in a table alongside the date/timestamp of the selected point in time.
You can switch to auto mode, which will automatically search out the best-fit pattern over a defined lookback range and plot the past/future projection for you without having to manually select a point in time at all. It simply finds the best fit for you.
You can change the scale factor by adjusting multiplication and division variables to find time-scaled fractal patterns.
══════════════════════════════
🎯 KEY FEATURES
Two Operating Modes:
🔧 MANUAL MODE - Select any historical point and see how it correlates with current price action in real-time. Perfect for:
• Analyzing specific past events (crashes, rallies, consolidations)
• Testing historical patterns against current conditions
• Educational analysis of market structure repetition
🤖 AUTO MODE - It automatically scans through your lookback period to find the single best-correlated historical match. Ideal for:
• Quick pattern discovery
• Systematic trading approach
• Unbiased pattern recognition
Time Warp Technology:
The time warp feature expands and compresses the correlation window to provide a custom fractal so you can analyze windows of time that don't necessarily match the current chart.
💡 *Example: Multiplier=3, Divisor=2 gives you a 1.5x time stretch—perfect for finding patterns that played out 50% slower than current price action.*
Drawing Modes:
Scale Only : Pure vertical scaling—matches price range while maintaining temporal alignment at bar 0
Rotate & Scale : Advanced geometric transformation that anchors both the start AND end points, creating a rotated fit that matches your current segment's slope and range
Visual Components:
🟠 Orange Overlay : The historical match, perfectly scaled to your current price action
🟣 Purple Projection : What happened NEXT after that historical pattern (dotted line into the future)
📦 Highlight Boxes : Shows you exactly where in history these patterns came from
📊 Live Correlation Table : Real-time correlation coefficient with color-coded strength indicator
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⚙️ PARAMETERS EXPLAINED
Correlation Window Length (20) : How many bars to match. Smaller = more precise matches but noisier. Larger = broader patterns but fewer matches.
Note: if this value is too high in auto mode, the script may time out from computational overload.
Multiplication Factor : Historical time multiplier. 2 = sample every 2nd bar from history. Higher values find slower historical patterns.
Division Factor : Historical time divisor applied after multiplication. Final sample rate = (Length × Factor) ÷ Divisor, rounded down.
Lookback Range : How far back to search for patterns. More history = better chance of finding matches but slower performance.
Note: if this value is too high in auto mode, the script may time out from computational overload.
Future Projection Length : How many bars forward to project from the historical match. Your crystal ball's focal length.
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💼 TRADING APPLICATIONS
Trend Continuation/Reversal :
If the purple projection continues the current trend, that's your historical confirmation. If it reverses, you've found a potential turning point that's happened before under similar conditions.
Support/Resistance Validation :
Does the projection respect your S/R levels? History suggests those levels matter. Does it break through? You've found historical precedent for a breakout.
Time-Based Exits :
The projection shows not just WHERE price might go, but WHEN. Use it to anticipate timing of moves.
Multi-Timeframe Analysis :
Use time compression to overlay higher timeframe patterns onto lower timeframes. See daily patterns on hourly charts, weekly on daily, etc.
Pattern Education :
In Manual Mode, study how specific historical events correlate with current conditions. Build your pattern recognition library.
══════════════════════════════
📊 CORRELATION TABLE
The table shows your correlation coefficient as a percentage:
80-100%: Extremely strong correlation—history is practically repeating
60-80%: Strong correlation—significant similarity
40-60%: Moderate correlation—some structural similarity
20-40%: Weak correlation—limited similarity
0-20%: Very weak correlation—essentially random match
-20-40%: Weak inverse correlation
-40-60%: Moderate inverse correlation
-60-80%: Strong inverse correlation
-80-100%: Extremely strong inverse correlation—history is practically inverting
**Important**: The correlation measures SHAPE similarity, not price level. An 85% correlation means the price movements follow a very similar pattern, regardless of whether prices are higher or lower.
══════════════════════════════
⚠️ IMPORTANT DISCLAIMERS
- Past performance does NOT guarantee future results (but it sure is interesting to study)
- High correlation doesn't mean causation—markets are complex adaptive systems
- Use this as ONE tool in your analytical toolkit, not a standalone trading system
- The projection is what HAPPENED after a similar pattern in the past, not a prediction
- Always use proper risk management regardless of what the Echo Chamber suggests
══════════════════════════════
🎓 PRO TIPS
1. Start with Auto Mode to find high-correlation matches, then switch to Manual Mode to study why that period was similar
2. Experiment with time warping on different timeframes—a 2x factor on a daily chart lets you see weekly patterns
3. Watch for correlation decay —if correlation drops sharply after the match, current conditions are diverging from history
4. Combine with volume —check if volume patterns also match
5. Use "Rotate & Scale" mode when the current trend angle differs from the historical match
6. Increase lookback range to 500-1000+ on daily/weekly charts for finding rare historical parallels
══════════════════════════════
🔧 TECHNICAL NOTES
- Uses Pearson correlation coefficient for pattern matching
- Implements range-based scaling to normalize different price levels
- Rotation mode uses linear interpolation for geometric transformation
- All calculations are performed on close prices
- Boxes highlight actual historical bar ranges (high/low)
- Maximum of 500 lines and 500 boxes for performance optimization
Market Internals Dashboard: Trend, Breadth, Volume PressureOverview
The Market Internals Dashboard Pro is a professional-grade toolkit modeled after what prop firms and institutional desks use to understand real intraday market conditions.
Instead of relying solely on price, this indicator analyzes three critical internal forces:
USI:TICK : Microstructure buying/selling pressure
USI:ADD : Market breadth participation (advancers vs decliners proxy)
USI:VOLD : Volume pressure (buying vs selling volume)
These internals determine whether the market is:
Trending or ranging
Bullish or bearish
Likely to follow through or mean-revert
Favoring continuation trades or fade setups
The script also produces a Market Environment Score (–3 to +3) and a real-time Trade Recommendation Table that updates every bar. This helps answer the single most important question in intraday trading: “What type of trades should I be taking right now given current market conditions?”
1. TICK Proxy: Microstructure Pressure
Measures buying vs. selling aggressiveness across the market This proxy simulates the NYSE TICK index by evaluating whether bars close above or below the prior bar.
Positive TICK → Buyers lifting offers
Negative TICK → Sellers hitting bids
Neutral TICK → No microstructure conviction
Why it matters:
Strong TICK is often the earliest sign of:
Trend initiation
Algorithmic buy/sell programs
Shifts in short‑term sentiment
Weak or choppy TICK often signals:
Range conditions
Failed breakouts
Low‑quality trend attempts
2. ADD Proxy: Market Breadth Strength
Shows how many stocks are participating in a move Because real USI:ADD data isn't available for all users, this script uses a self-contained breadth approximation built from:
Price slope
Volatility expansion
Volume‑weighted directional pressure
Why it matters? Breadth reveals whether the move is:
Broad and healthy → likely to continue
Narrow and weak → vulnerable to reversal
Strong trends require strong breadth. Weak breadth often precedes:
Failed breakouts
Reversal setups
Chop (ewww)
3. VOLD Proxy: Volume Pressure
The most important internal of all. This proxy measures whether trading volume is flowing into up bars or down bars.
Positive VOLD → Net buying pressure
Negative VOLD → Net selling pressure
Why it matters:
VOLD is considered the "truth serum" of the tape:
Strong VOLD drives trend days
Negative VOLD kills long setups
Mixed VOLD creates chop
You should rarely trend trade against VOLD.
4. Market Environment Score (–3 to +3)
The Environment Score combines the three internals into a single view:
|| Score || Interpretation || Market Type ||
| +3 | Strong Bull | Trend Day (Long) |
| +2 | Bull | Pullback Buys / Breakout Continuation |
| +1 | Mild Bull | Conservative Long Scalps |
| 0 | Neutral | CHOP – VWAP Reversions / Fades |
| -1 | Mild Bear | Short Failed Breakouts |
| -2 | Bear | Trend Shorts / Breakdown Continuation |
| -3 | Strong Bear | Trend Day (Short) |
Why it matters:
The market behaves differently depending on internal alignment. This score prevents traders from:
Forcing trend trades on chop days
Chasing breakouts when breadth is weak
Fading strong directional days
It tells you in real time whether conditions favor:
Trend following
Mean reversion
Breakout continuation
Liquidity grabs
Or sitting out
5. Trade Recommendation Engine
Based on the Environment Score, the indicator outputs a real-time playbook recommending which trade types have the highest probability of success right now.
Examples:
Score = 0 (Neutral)
VWAP Reversions
Liquidity Grabs
Failed Breakouts
Quick Scalps
Score = +2/+3 (Strong Bull)
Pullback Buys
Breakout Continuation
Trend Longs
Score = -2/-3 (Strong Bear)
Pullback Shorts
Breakdown Continuation
Trend Shorts Only
This turns the internals into a trade selection engine, not just a data display.
Why Market Internals Matter
Most indicators look only at price, but price is the result, not the cause.
Market internals show:
Where volume is flowing
Whether buying is aggressive or passive
How many stocks are participating
Whether algorithms are supporting or fighting the move
This dashboard helps traders:
Avoid chop
Stay out of low‑quality setups
Time entries with institutional flows
Improve win rate by trading the right setups at the right times
Final Notes
Works on any symbol or timeframe
Fully customizable colors
Two clean visual tables: Internals + Trade Playbook
Ideal for futures, ETFs, and options day traders
If you enjoy this tool, please like, comment, or follow. More enhancements are coming.
Trade smart.
BTC – LEVR: Leverage Efficiency & Volume RatioLEVR: Leverage Efficiency & Volume Ratio
Observation-only. Data: IntoTheBlock.
Overview
The Leverage Efficiency & Volume Ratio (LEVR) is a market structure oscillator designed to detect "Paper Bubbles" and "Organic Bottoms" by separating speculative greed from network utility. While most indicators analyze price action, LEVR analyzes market fragility. It operates on the thesis that Sustainable Rallies are driven by Spot/Network Activity, while Fragile Rallies are driven by Derivatives Leverage.
Synergy
How it works with VERI
LEVR is designed to be the tactical counterpart to the fundamental VERI Indicator (Valuation & Entity Ratio Index).
Use VERI for Strategy: To identify Value. (Is Bitcoin cheap? Are Whales buying?)
Use LEVR for Risk: To identify Structure. (Is the current price move real, or is it a leverage bubble about to pop?)
The "Perfect Setup"
The strongest buy signals occur when VERI is in the Accumulation Zone (Whales buying) AND LEVR is in the Organic Zone (Leverage is flushed out) (as it was the case in the Dec 2022 Bear Market Bottom).
Why LEVR is Unique
Standard indicators often fail to contextualize Open Interest:
vs. Raw Open Interest: Raw OI always trends up over time as the market grows. LEVR solves this by normalizing OI against Active Addresses. This reveals when leverage is outpacing actual adoption.
vs. ELR (Estimated Leverage Ratio): Classic ELR divides Open Interest by Exchange Reserves. However, Exchange Reserves are notoriously difficult to track accurately. LEVR uses Active Addresses (Network Utility) as a cleaner, more reliable denominator for network health.
Methodology
The Mathematics: The indicator calculates a normalized Z-Score ratio between two IntoTheBlock datasets:
The Numerator (Greed): Perpetual Open Interest. The total dollar value of all open futures contracts. This represents the "Gambling" capital.
The Denominator (Utility): Active Addresses. The number of unique addresses transacting on-chain. This represents the "Real" user base.
The Formula : LEVR = Z-Score ( Perpetual Open Interest / Active Addresses )
How to Interpret the Visuals
The line color changes dynamically to reflect the current risk regime:
🟥 Speculative Premium (Red Line > 2.0) :
Signal: "Leverage Bubble."
Context: Open Interest is rising significantly faster than User Growth. The rally is fueled by debt.
Risk: High probability of a "Long Squeeze" or liquidation cascade.
🟦 Organic Base (Blue Line < -1.5) :
Signal: "Spot Driven Market."
Context: Speculators have been flushed out, but active network usage remains high. The line turns Blue to signal a healthy opportunity zone.
Risk: Low. Historically marks robust bottoms where hands are strong.
🟧 Neutral (Orange Line) :
The market is in a transition phase between organic growth and speculation.
Settings & Inputs
Users can customize the sensitivity of the Z-Score to fit their trading style (in brackets their current standard value):
Lookback Period (365) : The rolling window used to establish the "Baseline." A 365-day window captures the yearly trend.
Signal Smoothing (7) : A short moving average to reduce daily data noise.
Bubble Zone Top/Bottom (3.0 / 2.0) : The thresholds for the Red Zone. Raising the "Top" value will only show the most extreme, generational leverage bubbles.
Organic Zone Top/Bottom (-1.5 / -2.5) : The thresholds for the Green Zone. Lowering these values requires a deeper "flush" to trigger a signal.
Optimization
This indicator is mathematically optimized for the Daily (1D) timeframe. Using it on lower timeframes may result in noise due to the daily resolution of on-chain data.
Important Note on Historical Data
Please be aware that aggregated global Perpetual Open Interest data only becomes reliable and widely available starting around 2020-2021.
Pre-2021: The indicator will show a flat line or empty values. This is not a bug; it reflects the lack of historical derivatives market data for that period.
2021-Present: The indicator functions fully as intended.
Credits
Concept inspired by the "Estimated Leverage Ratio" (ELR) popularised by CryptoQuant and analysts like Willy Woo. LEVR adapts this concept for TradingView by substituting Exchange Reserves with Network Activity for better reliability.
Disclaimer
This tool is for research purposes only. It visualizes market structure data and does not constitute financial advice.
Tags
bitcoin, btc, open interest, leverage, on-chain, intotheblock, risk, derivatives, levr, veri
S&P Options Patterns Detector (6-20 Candles)Pattern detector for S&P options. Detects alerts for bullish or bearish signals for any stock in S&P 500
Session important reference linesThis indicator automatically plots crucial price reference points for the Regular Trading Hours (RTH) session, including Yesterday's High/Low/Close, Session Open, Midpoint, and the Initial Balance (IB) range with its 2x extension .
In the example above the lines are:
Dotted green - Today's open price
Dashed yellow - Today's mid line
Solid yellow - Initial Balance high/low
Dotted yellow - Initial Balance extension
Dotted dark green - Previous session high
Dotted dark red - Previous session low
Dotted orange - Previous session close
LiquidityPulse Multi-Timeframe Volume Zones/ LevelsLiquidityPulse Multi-Timeframe Volume Zones/ Levels
Non-repainting: levels appear on bar close and do not change.
What This Indicator Does
This indicator scans lower-timeframe price action to identify bars where volume and candle behaviour suggest that a notable price interaction occurred. When all conditions align, the script extracts a precise price level from that bar, plots it on your higher-timeframe chart, and extends it forward so you can observe whether the market interacts with it again later.
Each selected timeframe is processed independently. For every timeframe you enable, the script looks for the following criteria:
1. A shift in candle direction between the previous bar and the current bar
2. A close-to-open body alignment , helping filter out irregular or noisy movement
3. A volume increase relative to the recent average , based on a user-selected multiplier
If these conditions are met, the script marks the corresponding price level on the chart. You can enable up to seven lower timeframes at once, each with its own independent settings, colours, strength filters, and display capacity. This allows you to build a layered, multi-timeframe view of the levels/ zones.
How It Works
1. Candle Behaviour Shift
The script checks whether the previous bar and the current bar show opposing directional behaviour. This helps highlight moments that may reflect a shift in directional behaviour or a change in price movement characteristics.
2. Body Alignment
The previous bar’s close must closely align with the current bar’s open. This requirement reduces random noise and focuses detection on areas where structure between candles is unusually clean.
3. Volume Requirement
The combined volume of the current bar and the previous bar must exceed the recent average by a multiplier you choose.
Lower multiplier - more levels
Higher multiplier - only the most significant activity spikes qualify
This filters for bars with above-average participation (volume).
4. Price Level Identification
If all conditions are met, a price edge is defined:
Bearish pressure: upper edge
Bullish pressure: lower edge
This edge marks the price level where the qualifying candle behaviour occurred.
5. Zone Drawing
Each qualifying event produces:
A horizontal line marking the level
A (optional) shaded box around the level
A label showing the timeframe and the exact volume multiplier amount detected
The level then extends forward so you can monitor future interactions.
Key Settings
Zone Strength (Volume Multiplier)
Determines how selective the volume filter is.
Lower settings show more frequent activity
Higher settings restrict detection to only the strongest activity (volume) increases
Multi-Timeframe Framework
Enable/disable per timeframe
Custom source timeframe (e.g., 1m, 5m, 15m, etc.)
Strength threshold per timeframe
How many recent levels to display per timeframe (Show Last N Zones.)
You can display a single timeframe or stack several to highlight clustering.
How traders can use this indicator
This script is not a buy/sell signal generator. It is best used as a structural overlay that helps you identify:
Where candle behaviour abruptly shifted with increased volume
Whether multiple timeframes highlight similar levels
Comparing how frequently these conditions appear across different timeframes
How price behaves when revisiting areas of prior activity (levels)
Why this type of detection can be informative
Higher-timeframe charts compress a large amount of lower-timeframe activity. By identifying where the script found notable changes in direction, structure, and relative volume on a lower timeframe, it provides a way to reference points in the price history where behaviour differed from nearby bars. Displaying these levels on a higher timeframe allows traders to see how these conditions align with their broader analysis.
Disclaimer
This indicator does not measure true liquidity or order flow. It uses candle structure and relative-volume comparisons as interpretive tools, and the plotted levels do not represent signals or predictions. All analysis is user-interpreted, and past behaviour does not imply future behaviour.
FUSED 9.5 INSTITUTIONAL [FINAL] - AgTradezInstitutional style Indicator that gives you trend direction, MSS, with Tp levels and much more.
BTC Price Prediction Model [Global PMI]V2🇺🇸 English Guide
1. Introduction
This indicator was created by GW Capital using Gemini Vibe Coding technology. It leverages advanced AI coding capabilities to reconstruct complex macroeconomic models into actionable trading tools.
2. Credits
Special thanks to the original model author, Marty Kendall. His research into the correlation between Bitcoin's price and macroeconomic factors lays the foundation for this algorithm.
3. Model Principles & Formula
This model calculates the "Fair Value" of Bitcoin based on four key macroeconomic pillars. It assumes that Bitcoin's price is a function of Global Liquidity, Network Security, Risk Appetite, and the Economic Cycle.
💡 Unique Insight: PMI & The 4-Year Cycle
A key distinguishing feature of this model is the hypothesis that Bitcoin's famous "4-Year Halving Cycle" may be intrinsically linked to the Global Business Cycle (PMI), rather than just supply shocks.
Therefore, the model incorporates PMI as a valuation "Amplifier".
Note: Due to TradingView data limitations, US PMI is currently used as the proxy for the global cycle.
The Formula
$$\ln(BTC) = \alpha + (1 + \beta \cdot PMI_{z}) \times $$
Global Liquidity (M2): Sum of M2 supply from US, China, Eurozone, and Japan (converted to USD). Represents the pool of fiat money available to flow into assets.
Network Security (Hashrate): Bitcoin's hashrate, representing the physical security and utility of the network.
Risk Appetite (S&P 500): Used as a proxy for global risk sentiment.
Economic Cycle (PMI Z-Score): US Manufacturing PMI is used to amplify or dampen the valuation based on where we are in the business cycle (Expansion vs. Contraction).
4. How to Use
The indicator plots the Fair Value (White Line) and four sentiment bands based on statistical deviation (Z-Score).
Sentiment Zones
🚨 Extreme Greed (Red Zone): Price > +0.3 StdDev. Historically indicates a market top or overheated sentiment.
⚠️ Greed (Orange Zone): Price > +0.15 StdDev. Bullish momentum is strong but caution is advised.
⚖️ Fair Value (White Line): The theoretical "correct" price based on macro data.
😨 Fear (Teal Zone): Price < -0.15 StdDev. Undervalued territory.
💎 Extreme Fear (Green Zone): Price < -0.3 StdDev. Historically a generational buying opportunity.
Sentiment Score (0-100)
100: Maximum Greed (Top)
50: Fair Value
0: Maximum Fear (Bottom)
5. Usage Recommendations
Timeframe: Daily (1D) or Weekly (1W) ONLY.
Reason: The underlying data sources (M2, PMI) are updated monthly. The S&P 500 and Hashrate are daily. Using this indicator on intraday charts (e.g., 15m, 1h, 4h) adds no value because the fundamental data does not change that fast.
Long-Term View: This is a macro-cycle indicator designed for identifying cycle tops and bottoms over months and years, not for day trading.
6. Disclaimer
This indicator is for educational and informational purposes only. It does not constitute financial advice. The model relies on historical correlations which may not hold true in the future. All trading involves risk. GW Capital and the creators assume no responsibility for any trading losses.
7. Support Us ❤️
If you find this indicator useful, please Boost 👍, Comment, and add it to your Favorites! Your support keeps us going.
🇨🇳 中文说明 (Chinese Version)
1. 简介
本指标由 GW Capital 使用 Gemini Vibe Coding 技术制作。利用先进的 AI 编程能力，将复杂的宏观经济模型重构为可执行的交易工具。
2. 致谢
特别感谢模型原作者 Marty Kendall。他对这一算法的研究奠定了基础，揭示了比特币价格与宏观经济因素之间的深层联系。
3. 模型原理与公式
该模型基于四大宏观经济支柱计算比特币的“公允价值”。它假设比特币的价格是全球流动性、网络安全性、风险偏好和经济周期的函数。
💡 独家洞察：PMI 与 4年周期
本模型的一个核心独特之处在于：我们认为比特币著名的“4年减半周期”背后的真正驱动力，可能与全球商业周期 (PMI) 高度同步，而不仅仅是供应减半。
因此，模型特别引入 PMI 作为估值的“放大器” (Amplifier)。
注：由于 TradingView 数据源限制，目前采用历史数据最详尽的美国 PMI 作为全球周期的代理指标。
模型公式
$$\ln(BTC) = \alpha + (1 + \beta \cdot PMI_{z}) \times $$
全球流动性 (M2): 美、中、欧、日四大经济体的 M2 总量（折算为美元）。代表可流入资产的法币资金池。
网络安全性 (Hashrate): 比特币全网算力，代表网络的物理安全性和实用价值。
风险偏好 (S&P 500): 作为全球风险情绪的代理指标。
经济周期 (PMI Z-Score): 美国制造业 PMI 用于根据商业周期（扩张 vs 收缩）来放大或抑制估值。
4. 指标用法
指标会在图表上绘制 公允价值 (白线) 以及基于统计偏差 (Z-Score) 的四条情绪带。
情绪区间
🚨 极度贪婪 (红色区域): 价格 > +0.3 标准差。历史上通常预示市场顶部或情绪过热。
⚠️ 一般贪婪 (橙色区域): 价格 > +0.15 标准差。多头动能强劲，但需谨慎。
⚖️ 公允价值 (白线): 基于宏观数据的理论“正确”价格。
😨 一般恐惧 (青色区域): 价格 < -0.15 标准差。进入低估区域。
💎 极度恐惧 (绿色区域): 价格 < -0.3 标准差。历史上通常是代际级别的买入机会。
情绪评分 (0-100)
100: 极度贪婪 (顶部)
50: 公允价值
0: 极度恐惧 (底部)
5. 使用建议
周期: 仅限日线 (1D) 或周线 (1W)。
原因: 底层数据源（M2, PMI）是月度更新的。标普500和算力是日度更新的。在日内图表（如15分钟、1小时、4小时）上使用此指标没有任何意义，因为基本面数据不会变化得那么快。
长期视角: 这是一个宏观周期指标，旨在识别数月甚至数年的周期顶部和底部，而非用于日内交易。
6. 免责声明
本指标仅供教育和参考使用，不构成任何财务建议。该模型依赖于历史相关性，未来可能不再适用。所有交易均涉及风险。GW Capital 及制作者不对任何交易损失承担责任。
Opcje: Sugestia Strike'ów (HV Based)How to interpret this script?
1. Dotted Lines:
Red (Upper): The price level above which the asset is statistically unlikely to rise within X days. This is where you look for a Strike Price to sell a CALL option (Short Call).
Green (Lower): The price level below which the asset is statistically unlikely to fall. This is where you look for a Strike Price to sell a PUT option (Short Put).
2. Sigma Multiplier (Important!):
The default setting is 2.0. This represents 2 Standard Deviations.
In a normal distribution, 2 standard deviations cover approximately 95% of outcomes.
This means you theoretically have a 95% probability that the option will expire worthless (meaning you keep the full premium), but the premium received will be lower.
If you change it to 1.0, you will be closer to the current price = higher premium, but the risk of assignment (exercise) increases to about 32%.
3. DTE (Days to Expiration):
Enter the actual number of days for the option you intend to sell (e.g., 45). The script will calculate where the price might be in 45 days based on current volatility.
ADX with 20 ThresholdI wanted an ADX with a threshold line so I created an indicator.
ADX (20 Threshold) Cheat-Sheet
Purpose: Filter trades by trend strength.
Indicator: ADX (derived from DMI) with optional +DI/−DI lines.
Key Rules:
ADX > 20: Trend is strong → trade OK
ADX < 20: Trend is weak/choppy → avoid trades
Optional +DI / −DI: Shows momentum direction
HTF Use: Stable trend confirmation
LTF Use: Optional filter with EMA slope for entries
Tips:
Combine with EMAs or MACD for directional bias.
ADX does not indicate direction, only strength.
Best used to avoid low-probability trades in sideways markets.
Global M2(USD) V2This indicator tracks the total Global M2 Money Supply in USD. It aggregates economic data from the world's four largest central banks (Fed, PBOC, ECB, BOJ). The script automatically converts non-USD money supplies (CNY, EUR, JPY) into USD using real-time exchange rates to provide a unified view of global liquidity.
Usage
Macro Analysis: Overlay this on assets like Bitcoin or the S&P 500 to see if price appreciation is driven by fiat currency debasement ("money printing").
Liquidity Trends: A rising orange line indicates expanding global liquidity (generally bullish for risk assets), while a falling line suggests monetary tightening.
Real-time Data: A label at the end of the line displays the exact raw total in USD for precise tracking.
该脚本旨在追踪以美元计价的全球 M2 货币供应总量。它聚合了四大央行（美联储、中国央行、欧洲央行、日本央行）的经济数据，并通过实时汇率将非美货币（人民币、欧元、日元）统一折算为美元，从而构建出一个标准化的全球流动性指标。
用法
宏观对冲： 将其叠加在比特币或股票图表上，用于判断资产价格的上涨是否由全球法币“大放水”推动。
趋势研判： 橙色曲线向上代表全球流动性扩张（通常利好风险资产），向下则代表流动性紧缩。
数据直观： 脚本会在图表末端生成一个标签，实时显示当前全球 M2 的具体美元总额。
MA + ATR Channel V2This script creates a dynamic volatility channel (similar to a Keltner Channel). It plots a central Moving Average (SMA or EMA) to represent the baseline trend and uses the Average True Range (ATR) to calculate the Upper and Lower bands. The channel automatically widens during high volatility and narrows during low volatility.
Usage
Mean Reversion: In sideways markets, prices touching the outer bands often tend to revert back to the central line.
该脚本构建了一个基于波动率的动态通道（类似肯特纳通道）。它以**移动平均线（SMA或EMA）为中轴判断趋势，并利用真实波幅（ATR）**计算通道宽度。通道范围会随市场波动加剧而变宽，随波动平缓而收窄。
用法
震荡回归： 在横盘行情中，价格触及通道边缘时，往往有回调至中轴的倾向。
