Sector Analysis [SS]Introducing the most powerful sector analysis tool/indicator available, to date, in Pine!
This is a whopper indicator, so be sure to read carefully to ensure you understand its applications and uses!
First of all, because this is a whopper, let's go over the key functional points of the indicator.
The indicator compares the 11 main sector ETFs against whichever ticker you are looking at.
The functions include the following:
Ability to pull technicals from the sectors, such as RSI, Stochastic and Z-Score;
Ability to look at the correlation of the sector ETF to the current ticker you are looking at.
Ability to calculate the R2 value between the ticker you are looking at and each sector.
The ability to run a Two Tailed T-Test against the log returns of the Ticker of interest and the Sector (to analyze statistically significant returns between sectors/tickers).
The ability to analyze the distribution of returns across all sector ETFs.
The ability to pull buying and selling volume across all sector ETFs.
The ability to create an integrated moving average using a sector ETF to predict the expected close range of a ticker of interest.
These are the highlight functions. Below, I will go more into them, what they mean and how to use them.
Pulling Technicals
This is pretty straight forward. You can pull technicals, such as RSI, Stochastic and Z-Score from all the sector ETFs and view them in a table.
See below for the example:
Pulling Correlation
In order to see which sector your ticker of interest follows more closely, we need to look first at correlation and then at R2.
The correlation will look at the immediate relationship over a specified time. A highly positive value, indicates a strong, symbiotic relationship, which the sector and the ticker follow each other. This would be represented by a correlation of 0.8 or higher.
A strong negative correlation, such as -0.8 or lower, indicates that the sector and the ticker are completely opposite. When one goes up, the other goes down and vice versa.
You can adjust your correlation assessment length directly in the settings menu:
If you want to use a sector ETF to find the expected range for a ticker of interest, it is important to locate the highest, POSITIVE, correlation value. Here are the results for MSFT at a correlation lookback of 200:
In this example, we can see the best relationship is with the ETF XLK.
Analysis of R2
R2 is an important metric. It essentially measures how much of the variance between 2 tickers are explained by a simple, linear relationship.
A high R2 means that a huge degree of variance can be explained between the 2 tickers. A low R2 means that it cannot and that the 2 tickers are likely not integrated or closely related.
In general, if you want to use the sector ETF to find the mean and trading range and identify over-valuation/over-extension and under-extension statistically, you need to see both a high correlation and a high R-Squared. These 2 metrics should be analyzed together.
Let's take a look at MSFT:
Here, despite the correlation implying that XLK was the ticker we should use to analyze, when we look at the R Squared, we see actually, we should be using XLI.
XLI has a strong positive relationship with MSFT, albeit a bit less than XLK, but the R2 is solid, > 0.9, indicating the XLI explains much of MSFT's variance.
Two Tailed T-Test
A two tailed T-test analyzes whether there is a statistically significant difference between 2 different groups, or in our case, tickers.
The T-Test is conducted on the log returns of the ticker of interest and the sector. You then can see the P value results, whether it is significant or not. Let's look at MSFT again:
Looking at this, we can see there is no statistically significant difference in returns between MSFT and any of the sectors.
We can also see the SMA of the log returns for more detailed comparison.
If we were to observe a significant finding on the T-Test metrics, this would indicate that one sector either outperforms or underperforms your ticker to a statistically significant degree! If you stumble upon this, you would check the average log returns to compare against the average returns of your ticker of interest, to see whether there is better performance or worse performance from the sector ETF vs. your ticker of interest.
Analyzing the Distribution
The indicator will also analyze the distribution of returns.
This is an interesting option as it can help you ascertain risk. Normally distributed returns imply mean reverting behavviour. Deviations from that imply trending behaviour with higher risk expectancy. If we look at the distribution statistics currently over the last 200 trading days, here are the results:
Here, we can see all show signs of trending, as none of the returns are normally distributed. The highest risk sectors are XLK and XLY.
Why are they the highest risk?
Because the indicator has found a heavy right tailed distribution, indicated sudden and erratic mean reversion/losses are possible.
Creating an MA
Now for the big bonus of the indicator!
The indicator can actually create a regression based range from closely correlated sectors, so you can see, in sectors that are strongly correlated to your ticker, whether your ticker is over-bought, oversold or has mean reverted.
Let's look at MSFT using XLI, our previously identified sector with a high correlation and high R2 value:
The results are pretty impressive.
You can see that MSFT has rode the mean of the sector on the daily timeframe for quite some time. Each time it over extended itself above the sector implied range, it mean reverted.
Currently, if you were to trade based on Pairs or statistics, MSFT is no trade as it is currently trading at its sector mean.
If you are a visual person, you can have the indicator plot the mean reversion points directly:
Green represents a bullish mean reversion and red a bearish mean reversion.
Concluding Remarks
If you like pair trading, following the link between sectors and tickers or want a more objective way to determine whether a ticker is over-bought or oversold, this indicator can help you.
In addition to doing this, the indicator can provide risk insights into different sectors by looking at the distribution, as well as identify under-performing sectors or tickers.
It can also shed light on sectors that may be technically over-bought or oversold by looking at Z-Score, stochastics and RSI.
Its a whopper and I really hope you find it helpful and useful!
Thanks everyone for reading and checking this out!
Safe trades!
Forecasting
Mum Formasyonları TespitiIt is used to detect candles.
It is designed to analyze all the candles that form.
The most frequently formed candles are displayed on the price chart.
Volumatic VIDYA – Pro+1. Professional & Clear (recommended for TradingView)
Volumatic VIDYA Pro+ combines a dynamic VIDYA trend filter, Delta Volume pressure, and automatic pattern recognition (Double/Triple Tops & Bottoms, Head & Shoulders).
A complete technical tool for detecting momentum shifts, trend reversals, and trade entries across multiple timeframes.
2. Short & Catchy
Adaptive VIDYA trendline + Delta Volume + Pattern detection in one tool.
Instantly visualize market bias, structure, and momentum strength.
3. Educational / Analytical
Analyze market dynamics with VIDYA-based trend filtering, volume delta analysis, and automated pattern recognition.
Ideal for traders who combine price action with quantitative confirmation.
Combined Signal + Auto Day Plan + Volume🧠 Combined Signal + Auto Day Plan + Volume
Version: Pine Script v5
Category: Strategy / Signal & Levels Tool
Author: (you can add your TradingView nickname)
📋 Overview
The Combined Signal + Auto Day Plan + Volume indicator merges multiple professional trading concepts into one visual tool — helping traders identify momentum shifts, entry zones, and daily trading plans with volume confirmation.
It automatically detects trend direction, generates dynamic take-profit & stop-loss levels, and overlays key daily reference points such as VWAP, pivot, support, and resistance zones based on ATR and trend context.
⚙️ Main Components
1️⃣ Signal System
Detects trend bias using SMA-based logic.
Generates entry price, TP1–TP3, and SL dynamically from recent impulse ranges.
Updates signals automatically when trend bias changes or previous targets are hit.
Visual levels are drawn directly on the chart.
2️⃣ Volume Analysis
Compares current volume against a moving average (SMA).
Classifies volume as:
🟢 Strong (above 1.5× average)
🟡 Average
🔴 Weak (below 0.8× average)
Displays the current volume strength and trend bias in an on-chart table.
3️⃣ Auto Day Plan
Uses multi-timeframe ATR calculations to define:
Support / Resistance zones
Pivot & Balance areas
Daily VWAP
Auto Targets (ATR-based expansion levels)
Adapts automatically to selected base timeframe (1H, 4H, or Daily).
4️⃣ Trend Context
Dual EMA system (50 & 200) to confirm bullish/bearish structure.
Aligns expected direction with VWAP & pivot location for context-aware bias.
🎯 What You Get on Chart
📈 Automatic LONG/SHORT signals
🎯 TP1, TP2, TP3, and SL levels
📊 Volume strength meter
🧭 VWAP, pivot, support/resistance & balance zones
🎨 Clean visual layout for intraday and swing traders
🧩 Inputs
Parameter Description
lenImpulse Impulse range length
smaLen SMA length for trend bias
levelRatio SL/TP ratio multiplier
volLen Volume SMA length
baseTF Base timeframe for zones/VWAP
atrMult1 / atrMult2 ATR multipliers for target levels
fwdBars Extension range for future projection
💡 How to Use
Add the script to your chart and choose your preferred timeframe.
Observe signal direction (📈 LONG / 📉 SHORT) and TP/SL levels.
Confirm entries when:
Trend aligns with VWAP direction, and
Volume category shows Strong or Average.
Use Auto Day Plan levels (pivot, balance, VWAP) as intraday reaction zones.
Gann Astronomical Turning PointsThis is a comprehensive Pine Script that implements W.D. Gann's astronomical theories to identify potential market turning points. Here's a detailed breakdown of the script:
Overview
The script identifies and displays astronomical events (sun angles, moon phases, and Mercury retrogrades) that Gann theorists believe correlate with market turning points. It also analyzes historical price performance following these events to provide statistical significance.
Key Components
1. Input Parameters
Date Range: Users can set the analysis period (start and end dates)
Display Options: Toggle visibility of different astronomical events and tables
Analysis Settings: Configure the lookback period for price change analysis (1-20 days)
2. Astronomical Calculations
The script includes several functions to calculate celestial positions:
getDaysSinceEpoch(t): Calculates days since January 1, 2000 (reference point)
getSunLongitude(t): Computes the Sun's position in the ecliptic (0-360°)
getMoonPhase(t): Determines the Moon's phase angle relative to the Sun
getMercuryLongitude(t): Calculates Mercury's position in the ecliptic
3. Gann Critical Angles (Sun Events)
The script identifies when the Sun reaches four critical angles that Gann considered significant:
0° Aries (Spring Equinox)
90° Cancer (Summer Solstice)
180° Libra (Fall Equinox)
270° Capricorn (Winter Solstice)
These are detected by tracking when the Sun's longitude crosses these specific angles.
4. Moon Phases
Four key moon phases are identified:
New Moon: Moon passes between Earth and Sun
First Quarter: Moon is 90° east of Sun
Full Moon: Moon is opposite the Sun
Last Quarter: Moon is 270° east of Sun
5. Mercury Retrograde Periods
The script detects when Mercury appears to move backward in its orbit:
Identifies start and end dates of retrograde motion
Displays these periods as highlighted zones on the chart
6. Price Change Analysis
For each astronomical event, the script:
Calculates the percentage price change over a user-defined lookback period
Categorizes changes as positive or negative
Stores this data for statistical analysis
7. Statistical Significance
The script calculates several metrics for each event type:
Average Price Change: Mean percentage change following events
Up/Down Ratio: Number of positive vs. negative changes
Accuracy Percentage: How often the dominant direction occurred
8. Visual Elements
The script includes multiple display components:
Event Labels
Sun Angles: Orange sun symbols displayed above price bars
Moon Phases: Moon phase emojis displayed below price bars
Mercury Retrograde: Red boxes highlighting the retrograde periods
Information Tables
Events Table: Shows upcoming and recent astronomical events
Significance Analysis Table: Displays statistical performance of each event type
Forecast Section: Identifies the next upcoming event and predicted direction
9. Forecasting Functionality
The script predicts market direction for the next astronomical event based on:
Historical average price change for that event type
Statistical accuracy of previous similar events
Color-coded forecast (green for bullish, red for bearish)
This script offers an interesting implementation of Gann's astronomical theories, but should be used as part of a broader analysis rather than as a standalone trading system.
Disclaimer: This indicator is for educational purposes only. Past performance does not guarantee future results. Always conduct your own research and risk assessment before trading.
VIX Regime AnalyzerVIX Regime Analyzer
The VIX Regime Analyzer is an analytical tool that examines historical VIX patterns to provide insights into how your asset typically performs under similar volatility conditions.
Key Features:
Historical Pattern Matching: Automatically scans up to 1,000 bars of history to find all periods when VIX was at levels similar to today, using customizable tolerance ranges (absolute or percentage-based).
Forward-Looking Statistics: For each VIX regime match, calculates what actually happened to your asset over the next 1, 5, 10, and 20 trading days, providing both average returns and probability of positive outcomes.
Regime Classification System: Intelligently categorizes the current market environment as bullish or bearish: Visual Historical Context:
Background shading throughout your chart highlights every historical period when VIX matched current levels, color-coded by subsequent performance (green for gains, red for losses).
User Inputs:
VIX Level Tolerance (+/-): How closely VIX must match (default: ±5 points)
Use Relative Tolerance (%): Switch to percentage-based matching for consistency across different VIX levels
Lookback Period: How many bars to analyze
Highlight Historical VIX Matches: Toggle background highlighting of past matching periods
The Data Table
The statistics box appears in the right handside of your chart and contains three main sections:
Section 1: VIX REGIME
Current VIX: The live VIX closing price
Range: The tolerance band being searched (e.g., if VIX is 18 with ±5 tolerance, range is 13-23)
Historical Samples: Number of matching periods found in the lookback window (minimum 10 required for statistical validity)
Section 2: FORWARD RETURN
Shows the average percentage change in your asset over different timeframes following similar VIX levels:
Avg Next Day: What typically happened by the next trading session
Avg Next 5 Days: Average 5-day forward performance
Avg Next 10 Days: Average 10-day forward performance
Avg Next 20 Days: Average 20-day forward performance (approximately 1 month)
Section 3: PROBABILITY UP
Shows the win rate - the percentage of times your asset closed higher after VIX matched current levels:
Next Day: Probability of being up the next session
Next 5 Days: Probability of being up after 5 days
Next 10 Days: Probability of being up after 10 days
Next 20 Days: Probability of being up after 20 days
Colors:
🟢 Green: Bullish regimes (various strengths)
🔴 Red: Bearish regimes (various strengths)
🟡 Yellow: Choppy/uncertain regime
When "Highlight Historical VIX Matches" is enabled:
Scroll back through your chart and you'll see colored backgrounds highlighting every period when VIX matched today's level. The color tells you whether that match led to gains (green) or losses (red). This provides instant visual pattern recognition - you can quickly see if similar VIX levels historically led to bullish or bearish outcomes.
Practical Example:
If you see that most historical periods with similar VIX levels are highlighted in green, it suggests the current VIX level has historically been a bullish signal for your asset.
How The Indicator Makes Decisions
The regime classification uses both magnitude AND probability to avoid false signals:
Example of Strong Classification:
Average 5-day return: +1.5%
Win rate: 65%
Result: STRONG BULLISH (both high return and high probability)
Example of Weak Signal:
Average 5-day return: +2.0%
Win rate: 35%
Result: CHOPPY (high average but low consistency = unreliable)
This dual-factor approach ensures the indicator doesn't mislead you with regimes that had a few huge winners but mostly losers, or vice versa.
Best Practices
Combine with your existing strategy: Use this as a regime filter rather than standalone signals
Check sample size: More historical matches = more reliable statistics
Consider multiple timeframes: If 5-day and 20-day metrics disagree, proceed with caution
Asset-specific tuning: Different assets may require different tolerance settings
VIX spikes: The indicator is particularly useful during VIX spikes to understand if panic is justified
What Makes This Different
Unlike simple VIX indicators that just plot the fear index, this tool:
Quantifies the actual impact of VIX levels on YOUR specific asset
Provides probability-based forecasts rather than subjective interpretation
Shows historical context visually so you can see patterns at a glance
Uses rigorous statistical criteria to avoid false regime classifications
High and low statisticsHigh/Low Pattern Analyzer (All Timeframes)
Ever wonder if there's a hidden pattern in the market?
Does the high of the week usually happen on a Tuesday?
Does the low of the month always form in the first week?
Which 15-minute candle really sets the high for the entire day?
This indicator is a powerful statistical tool designed to answer these questions by analyzing historical price action to find patterns in when the high and low of a period are formed.
The Core Idea: Daily High & Low of the Week
The simplest and most popular feature of this indicator is the "Daily high and low of the week" analysis.
What it does:
It looks back over your chosen number of weeks (e.g., the last 100) and finds out which day of the week (Monday, Tuesday, Wednesday, etc.) made the final high and which day made the final low for each of those weeks.
How to use it:
Go to the script settings.
Enable the "Daily High/Low of the Week" module.
Set your chart to the 1D (Daily) timeframe.
A table will appear on your chart (bottom-right by default) showing the exact count and percentage for each day. This lets you see at a glance if there's a strong tendency for the market you're watching.
Advanced Analysis: Other Timeframes
This script goes far beyond just the daily chart. It includes four other independent analysis modules:
1. 4-Hour High/Low of the Week
What it does: For intraday and swing traders. This module finds which 4-hour candle session (e.g., the 08:00 candle, the 16:00 candle) tends to form the high or low of the entire week.
Key Feature (DST Aware): This table is "season-aware." It knows that the 08:00 "summertime" (DST) candle is the same trading session as the 07:00 "wintertime" (STD) candle. It groups them together so your data is never split or messy.
2. Weekly High/Low of the Month
What it does: For a monthly perspective. This module finds which week of the month (Week 1, 2, 3, 4, or 5) is most likely to form the monthly high or low.
How to use: Enable it and set your chart to the 1W (Weekly) timeframe.
3. Monthly High/Low of the Year
What it does: The ultimate "big picture" view. This module finds which month (Jan, Feb, Mar, etc.) most frequently forms the high or low for the entire year.
How to use: Enable it and set your chart to the 1M (Monthly) timeframe.
The Power User Module: Custom Timeframe Analysis
This is the most powerful feature. It lets you analyze any timeframe combination you want.
What it does: It finds out which "Lower Timeframe" (LTF) candle made the high or low of any "Higher Timeframe" (HTF) you choose.
Example: Do you want to know which 15-minute candle makes the Daily high?
Set your chart to the 15M timeframe.
Go to the "Custom Timeframe Analysis" settings.
Set the "Higher Timeframe" to "1D".
The script will draw a "season-aware" table (just like the 4H module) showing you the exact 15-minute candles (09:15, 09:30, etc.) that are statistically most likely to form the day's high or low.
Other Features
Show Labels: Each module has an option to "Show labels," which will draw a label (e.g., "Daily High of the Week") directly on the chart at the exact bar that made the high or low.
Custom Dividers: Each module has its own optional, color-customizable divider (e.g., weekly, monthly) that you can toggle on to see the periods more clearly.
Clean Settings: All modules are disabled by default (except for "Daily") to keep your chart clean. You only need to enable the specific analysis you want to see.
This tool was built to turn your curiosity about market patterns into actionable, statistical data. Enjoy!
VIX/VVIX Spike RiskVIX/VVIX Spike Risk Analyzer
The VIX/VVIX Spike Risk Analyzer analyzes historical VIX behavior under similar market conditions to forecast future VIX spike risk.
By combining current VIX and VVIX levels as dual filters, it identifies historical precedents and calculates the probability and magnitude of VIX spikes over the next 1, 5, and 10 trading days.
IMPORTANT: This indicator must be applied to the VIX chart (CBOE:VIX) to function correctly.
Methodology
1. Dual-Filter Pattern Matching
The indicator uses both VIX and VVIX as simultaneous filters to identify historically analogous market conditions:
By requiring BOTH metrics to match historical levels, the indicator creates more precise market condition filters than using VIX alone. This dual-filter approach significantly improves predictive accuracy because:
VIX alone might be at 15, but VVIX can tell us if that 15 is stable (low VVIX) or explosive (high VVIX)
High VVIX + Low VIX often precedes major spikes
Low VVIX + Low VIX suggests sustained calm
2. Tolerance Settings
VIX Matching (Default: ±10% Relative)
Uses relative percentage matching for consistency across different VIX regimes
Example: VIX at 15 matches 13.5-16.5 (±10%)
Can switch to absolute tolerance (±5 points) if preferred
VVIX Matching (Default: ±10 Points Absolute)
Uses absolute point matching as VVIX scales differently
Example: VVIX at 100 matches 90-110
Can switch to relative percentage if preferred
3. Historical Analysis Window
The indicator scans up to 500 bars backward (limited by VVIX data availability) to find all historical periods where both VIX and VVIX were at similar levels. Each match becomes a "sample" for statistical analysis.
4. Forward-Looking Spike Analysis
For each historical match, the indicator measures VIX behavior over the next 1, 5, and 10 days
Display Metrics Explained
Average Highest Spike
Shows the average of the maximum VIX spikes observed.
Highest Single Spike
Shows the single largest spike ever recorded
Probability No 10% Spike
Shows what percentage of historical cases stayed BELOW a 10% spike:
Probability No 20% Spike
Shows what percentage of historical cases stayed BELOW a 20% spike:
Note : You'll see many more shaded bars than the sample count because each match creates up to 5 consecutive shaded bars (bars 1-5 after the match all "look back" and see it).
Short Volatility Strategies:
Enter when there's a LOW probability of big vol spikes based on today's metrics
Long Volatility Strategies
Enter when there's a HIGH probability of big vol spikes based on today's metrics
Trailing 12M % Gain/Lossthis script shows profit or loss for training 12 months, works only on daily time frame
3D Institutional Battlefield [SurgeGuru]Professional Presentation: 3D Institutional Flow Terrain Indicator
Overview
The 3D Institutional Flow Terrain is an advanced trading visualization tool that transforms complex market structure into an intuitive 3D landscape. This indicator synthesizes multiple institutional data points—volume profiles, order blocks, liquidity zones, and voids—into a single comprehensive view, helping you identify high-probability trading opportunities.
Key Features
🎥 Camera & Projection Controls
Yaw & Pitch: Adjust viewing angles (0-90°) for optimal perspective
Scale Controls: Fine-tune X (width), Y (depth), and Z (height) dimensions
Pro Tip: Increase Z-scale to amplify terrain features for better visibility
🌐 Grid & Surface Configuration
Resolution: Adjust X (16-64) and Y (12-48) grid density
Visual Elements: Toggle surface fill, wireframe, and node markers
Optimization: Higher resolution provides more detail but requires more processing power
📊 Data Integration
Lookback Period: 50-500 bars of historical analysis
Multi-Source Data: Combine volume profile, order blocks, liquidity zones, and voids
Weighted Analysis: Each data source contributes proportionally to the terrain height
How to Use the Frontend
💛 Price Line Tracking (Your Primary Focus)
The yellow price line is your most important guide:
Monitor Price Movement: Track how the yellow line interacts with the 3D terrain
Identify Key Levels: Watch for these critical interactions:
Order Blocks (Green/Red Zones):
When yellow price line enters green zones = Bullish order block
When yellow price line enters red zones = Bearish order block
These represent institutional accumulation/distribution areas
Liquidity Voids (Yellow Zones):
When yellow price line enters yellow void areas = Potential acceleration zones
Voids indicate price gaps where minimal trading occurred
Price often moves rapidly through voids toward next liquidity pool
Terrain Reading:
High Terrain Peaks: High volume/interest areas (support/resistance)
Low Terrain Valleys: Low volume areas (potential breakout zones)
Color Coding:
Green terrain = Bullish volume dominance
Red terrain = Bearish volume dominance
Purple = Neutral/transition areas
📈 Volume Profile Integration
POC (Point of Control): Automatically marks highest volume level
Volume Bins: Adjust granularity (10-50 bins)
Height Weight: Control how much volume affects terrain elevation
🏛️ Order Block Detection
Detection Length: 5-50 bar lookback for block identification
Strength Weighting: Recent blocks have greater impact on terrain
Candle Body Option: Use full candles or body-only for block definition
💧 Liquidity Zone Tracking
Multiple Levels: Track 3-10 key liquidity zones
Buy/Sell Side: Different colors for bid/ask liquidity
Strength Decay: Older zones have diminishing terrain impact
🌊 Liquidity Void Identification
Threshold Multiplier: Adjust sensitivity (0.5-2.0)
Height Amplification: Voids create significant terrain depressions
Acceleration Zones: Price typically moves quickly through void areas
Practical Trading Application
Bullish Scenario:
Yellow price line approaches green order block terrain
Price finds support in elevated bullish volume areas
Terrain shows consistent elevation through key levels
Bearish Scenario:
Yellow price line struggles at red order block resistance
Price falls through liquidity voids toward lower terrain
Bearish volume peaks dominate the landscape
Breakout Setup:
Yellow price line consolidates in flat terrain
Minimal resistance (low terrain) in projected direction
Clear path toward distant liquidity zones
Pro Tips
Start Simple: Begin with default settings, then gradually customize
Focus on Yellow Line: Your primary indicator of current price position
Combine Timeframes: Use the same terrain across multiple timeframes for confluence
Volume Confirmation: Ensure terrain peaks align with actual volume spikes
Void Anticipation: When price enters voids, prepare for potential rapid movement
Order Blocks & Voids Architecture
Order Blocks Calculation
Trigger: Price breaks fractal swing points
Bullish OB: When close > swing high → find lowest low in lookback period
Bearish OB: When close < swing low → find highest high in lookback period
Strength: Based on price distance from block extremes
Storage: Global array maintains last 50 blocks with FIFO management
Liquidity Voids Detection
Trigger: Price gaps exceeding ATR threshold
Bull Void: Low - high > (ATR200 × multiplier)
Bear Void: Low - high > (ATR200 × multiplier)
Validation: Close confirms gap direction
Storage: Global array maintains last 30 voids
Key Design Features
Real-time Updates: Calculated every bar, not just on last bar
Global Persistence: Arrays maintain state across executions
FIFO Management: Automatic cleanup of oldest entries
Configurable Sensitivity: Adjustable lookback periods and thresholds
Scientific Testing Framework
Hypothesis Testing
Primary Hypothesis: 3D terrain visualization improves detection of institutional order flow vs traditional 2D charts
Testable Metrics:
Prediction Accuracy: Does terrain structure predict future support/resistance?
Reaction Time: Faster identification of key levels vs conventional methods
False Positive Reduction: Lower rate of failed breakouts/breakdowns
Control Variables
Market Regime: Trending vs ranging conditions
Asset Classes: Forex, equities, cryptocurrencies
Timeframes: M5 to H4 for intraday, D1 for swing
Volume Conditions: High vs low volume environments
Data Collection Protocol
Terrain Features to Quantify:
Slope gradient changes at price inflection points
Volume peak clustering density
Order block terrain elevation vs subsequent price action
Void depth correlation with momentum acceleration
Control Group: Traditional support/resistance + volume profile
Experimental Group: 3D Institutional Flow Terrain
Statistical Measures
Signal-to-Noise Ratio: Terrain features vs random price movements
Lead Time: Terrain formation ahead of price confirmation
Effect Size: Performance difference between groups (Cohen's d)
Statistical Power: Sample size requirements for significance
Validation Methodology
Blind Testing:
Remove price labels from terrain screenshots
Have traders identify key levels from terrain alone
Measure accuracy vs actual price action
Backtesting Framework:
Automated terrain feature extraction
Correlation with future price reversals/breakouts
Monte Carlo simulation for significance testing
Expected Outcomes
If hypothesis valid:
Significant improvement in level prediction accuracy (p < 0.05)
Reduced latency in institutional level identification
Higher risk-reward ratios on terrain-confirmed trades
Research Questions:
Does terrain elevation reliably indicate institutional interest zones?
Are liquidity voids statistically significant momentum predictors?
Does multi-timeframe terrain analysis improve signal quality?
How does terrain persistence correlate with level strength?
LuxAlgo BigBeluga hapharmonic
[KF] Multi-Duration Rate Expectations IndicatorAfter last fed cut in Oct then following jump in rates, I was frustrated at not having access to good rate expectations vs actual because the market usually prices in prior to fed action. This indicator was developed to make futures market rate expectations accessible and interpretable without requiring professional bond analytics systems.
Summary
This Pine Script indicator reveals what the futures market expects for interest rates across three key durations: Fed Funds (overnight), 2-Year, and 10-Year Treasury yields. By comparing futures-implied rates against current spot yields, it provides a clear visual signal of whether the market expects rates to rise, fall, or remain steady.
Understanding Rate Futures
Fed Funds futures (ZQ1!) use a simple design where the expected rate equals 100 minus the futures price. If ZQ1! trades at 96.12, the market expects a 3.88% Fed Funds rate. Treasury futures work differently - they trade as bond prices (typically 102-115) that move inversely to yields. Converting Treasury futures to implied yields requires complex bond mathematics involving duration and conversion factors.
This indicator solves the Treasury futures complexity by implementing a self-calibrating sensitivity model. It observes the historical relationship between futures prices and yields, then uses this to project rate expectations. The model also compares front-month to next-month contracts to detect expected rate direction, automatically adapting as market conditions change.
How to Use
Add the indicator to any chart and select your desired duration in the settings. The display shows the futures-implied rate, current yield, and the difference between them. Green indicates the market expects higher rates, red means lower expectations, and gray shows expectations in line with current rates.
The indicator excels at identifying divergences between market expectations and current rates, which often precede rate movements or futures repricing. Comparing expectations across different durations reveals insights about yield curve positioning and Fed policy anticipation.
Technical Note
While Fed Funds futures provide exact rate expectations, Treasury futures conversions are sophisticated approximations that provide reliable directional signals and reasonable magnitude estimates sufficient for most trading applications.
Eagles CompassFree script
Helps detect specific body/wick ratios on chart for 1HR,2HR,4HR timeframes
Designed to help you detect large squeezes, bounces, and other moves
Ideally use in conjunction with an RSI to filter for false positives
Nqaba Probable High/Low — Overshoot/Undershoot{Larry Method)This Probable High/Low indicator is an advanced tool inspired by Larry R. Williams’ original projection formulas.
It calculates probable daily highs and lows based on the prior day’s open, high, low, and close, allowing traders to anticipate key intraday price levels with precision.
Nqaba Probable High/Low{Larry Method}The Probable High/Low indicator is an advanced tool inspired by Larry R. Williams’ original projection formulas.
It calculates probable daily highs and lows based on the prior day’s open, high, low, and close, allowing traders to anticipate key intraday price levels with precision.
This version provides full control over visibility, styling, and historical analysis — making it both educational and powerful for active traders.
Altseason Probability (BTC.D • USDT • TOTAL3 • DXY)Testing phase, workig out the kinks.
Works by aggregating several factors to define altseason probability in any given moment
8x Heikin Ashi Streak (1m) by Bitcoin Benito🧭 Indicator Description: “8x Heikin Ashi Streak (1m) by Bitcoin Benito”
**Purpose:**
The *8x Heikin Ashi Streak* indicator helps traders quickly identify strong short-term momentum on the **1-minute timeframe**. It automatically tracks Heikin Ashi candles and alerts you whenever **8 consecutive bullish or bearish candles** appear — a visual cue that a strong intraday trend or exhaustion point might be forming.
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🔍 **How It Works**
* The indicator continuously counts Heikin Ashi candles in real-time.
* When it detects **8 bullish (green)** or **8 bearish (red)** candles in a row:
* A green ▲ marker appears **below** the 8th candle for bullish streaks.
* A red ▼ marker appears **above** the 8th candle for bearish streaks.
* You can set alerts to automatically notify you when these streaks occur.
This makes it ideal for **momentum traders**, **scalpers**, and **trend-reversal spotters** who want to:
* Catch strong intraday moves early.
* Identify potential overextension zones before pullbacks.
* Automate alert signals for short-term trading setups.
IMPORTANT: Only trade when most of the 8 candles are below/above the EMA 8 Line respectively. Add an EMA 8 indicator to see if this is the case
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⚙️ **How to Use**
1. **Apply to a 1-minute chart** (this script is optimized for 1m timeframes).
2. When the indicator plots a green or red triangle:
* **Green triangle (8 bullish candles):** Trend momentum is strong upward.
* **Red triangle (8 bearish candles):** Downward momentum is dominant.
3. Optionally, combine with volume or EMA filters to confirm breakouts or exhaustion.
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🔔 **Setting Up Alerts**
* Click the **Alert (🔔)** icon on TradingView.
* Under *Condition*, select:
* “8x Heikin Ashi Streak (1m)” → “8 Bullish Heikin Ashi (1m)”
* OR “8x Heikin Ashi Streak (1m)” → “8 Bearish Heikin Ashi (1m)”
* Choose **Once per bar close** to trigger the alert when the 8th candle completes.
* Add your custom message, e.g.
> “🚀 8 bullish Heikin Ashi candles in a row on 1-minute chart!”
> “🔻 8 bearish Heikin Ashi candles in a row on 1-minute chart!”
---
📊 **Best Practices**
* Works best on **liquid assets** (major forex pairs, indices, BTC/USD, etc.).
* Pair with **RSI**, **EMA**, or **Volume** indicators for stronger confirmation.
* Not a standalone buy/sell signal — treat it as a **momentum or exhaustion alert**.
* Can be adapted to other timeframes by changing chart resolution.
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⚠️ **Disclaimer**
This indicator is for **educational and analytical purposes only**.
Trading carries risk — always test on demo accounts and use proper risk management.
No indicator guarantees profit; this is a tool for insight and timing, not financial advice.
Best Time Slots — Auto-Adapt (v6, TF-safe) + Range AlertsTime & binning
Auto-adapt to timeframe
Makes all time windows scale to your chart’s bar size (so it “just works” on 1m, 15m, 4H, Daily).
• On = recommended. • Off = fixed default lengths.
Minimum Bin (minutes)
The size of each daily time slot we track (e.g., 5-min bins). The script uses the larger of this and your bar size.
• Higher = fewer, broader slots; smoother stats. • Lower = more, narrower slots; needs more history.
• Try: 5–15 on intraday, 60–240 on higher TFs.
Lookback windows (used when Auto-adapt = ON)
Target ER Window (minutes)
How far back we look to judge Efficiency Ratio (how “straight” the move was).
• Higher = stricter/smoother; fewer bars qualify as “movement”. • Lower = more sensitive.
• Try: 60–120 min intraday; 240–600 min for higher TFs.
Target ATR Window (minutes)
How far back we compute ATR (typical range).
• Higher = steadier ATR baseline. • Lower = reacts faster.
• Try: 30–120 min intraday; 240–600 min higher TFs.
Target Normalization Window (minutes)
How far back for the average ATR (the baseline we compare to).
• Higher = stricter “above average range” check. • Lower = easier to pass.
• Try: ~500–1500 min.
What counts as “movement”
ER Threshold (0–1)
Minimum efficiency a bar must have to count as movement.
• Higher = only very “clean, one-direction” bars count. • Lower = more bars count.
• Try: 0.55–0.65. (0.60 = balanced.)
ATR Floor vs SMA(ATR)
Requires range to be at least this many × average ATR.
• Higher (e.g., 1.2) = demand bigger-than-usual ranges. • Lower (e.g., 0.9) = allow smaller ranges.
• Try: 1.0 (above average).
How history is averaged
Recent Days Weight (per-day decay)
Gives more weight to recent days. Example: 0.97 ≈ each day old counts ~3% less.
• Higher (0.99) = slower fade (older days matter more). • Lower (0.95) = faster fade.
• Try: 0.97–0.99.
Laplace Prior Seen / Laplace Prior Hit
“Starter counts” so early stats aren’t crazy when you have little data.
• Higher priors = probabilities start closer to average; need more real data to move.
• Try: Seen=3, Hit=1 (defaults).
Min Samples (effective)
Don’t highlight a slot unless it has at least this many effective samples (after decay + priors).
• Higher = safer, but fewer highlights early.
• Try: 3–10.
When to highlight on the chart
Min Probability to Highlight
We shade/mark bars only if their slot’s historical movement probability is ≥ this.
• Higher = pickier, fewer highlights. • Lower = more highlights.
• Try: 0.45–0.60.
Show Markers on Good Bins
Draws a small square on bars that fall in a “good” slot (in addition to the soft background).
Limit to market hours (optional)
Restrict to Session + Session
Only learn/score inside this time window (e.g., “0930-1600”). Uses the chart/exchange timezone.
• Turn on if you only care about RTH.
Range (chop) alerts
Range START if ER ≤
Triggers range when efficiency drops below this level (price starts zig-zagging).
• Higher = easier to call “range”. • Lower = stricter.
Range START if ATR ≤ this × SMA(ATR)
Also triggers range when ATR shrinks below this fraction of its average (volatility contraction).
• Higher (e.g., 1.0) = stricter (must be at/under average). • Lower (e.g., 0.9) = easier to call range.
Alerts on bar close
If ON, alerts fire once per bar close (cleaner). If OFF, they can trigger intrabar (faster, noisier).
Quick “what happens if I change X?”
Want more highlighted times? ↓ Min Probability, ↓ ER Threshold, or ↓ ATR Floor (e.g., 0.9).
Want stricter highlights? ↑ Min Probability, ↑ ER Threshold, or ↑ ATR Floor (e.g., 1.2).
Want recent days to matter more? ↑ Recent Days Weight toward 0.99.
On 4H/Daily, widen Minimum Bin (e.g., 60–240) and maybe lower Min Probability a bit.
EMA Crosses with Independent Fading Background1. Overall Purpose
The script is an EMA crossover indicator with the following features:
Calculates four EMA pairs: 5/13, 21/50, 20/200, 50/200.
Plots optional EMA lines.
Shows fading background highlights for bullish/bearish crosses.
Places labels at the points of crossover.
Provides a price source input, so EMAs can be based on close, hl2, ohlc4, etc.
2. Strengths
Flexible inputs: Users can change EMA lengths, choose a price source, enable/disable plots, adjust background highlight duration and fade.
Independent fading: Each EMA pair has its own counter for background highlights, preventing overlaps from canceling each other.
Clear labeling: Crosses are labeled distinctly with different colors.
Overlay: Works directly on the chart with overlay=true.
Pullback Levels from ATH# ATH Pullback Levels
**Assess correction depth with precision – 5%, 10%, 15%, 20% below All-Time High**
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### Overview
This indicator draws **horizontal support lines** at **5%, 10%, 15%, and 20%** below the **All-Time High (ATH)** of any asset. Perfect for **swing traders**, **long-term investors**, and **bull market participants** who want to:
- Measure **pullback depth** in real-time
- Identify **potential support zones**
- Set **alerts** when price enters key retracement levels
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### Features
| Feature | Description |
|--------|-------------|
| **Dynamic ATH Tracking** | Automatically updates with every new high |
| **4 Pullback Levels** | 5%, 10%, 15%, 20% below ATH |
| **Live Pullback % Label** | Shows current % drop from ATH (top-right) |
| **Customizable Lines** | Toggle visibility, change colors & styles |
| **Built-in Alerts** | Trigger on entry into each zone |
| **No Errors** | Works on 50k+ bar charts (BTC, SPX, etc.) |
| **Time-Based Lines** | Uses `xloc.bar_time` – no 500-bar future limit |
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### How to Use
1. Apply to any chart (stocks, crypto, forex, indices)
2. Watch the **info box** for current pullback %
3. Use lines as **potential buy zones** during corrections
4. Set **alerts** to be notified when price enters a level
> Example: If ATH = $100 →
> - 5% = $95
> - 10% = $90
> - 15% = $85
> - 20% = $80
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### Inputs
- **Show 5% / 10% / 15% / 20% Level** → Toggle on/off
- **Line Colors** → Fully customizable
- **Line Style** → Solid, Dashed, or Dotted
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### Alerts
Create alerts directly from the indicator:
- `"Entered 5% Pullback"`
- `"Entered 10% Pullback"`
- etc.
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### Best For
- Bull market corrections
- Long-term position sizing
- Risk management in uptrends
- Swing entries on dips
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### Notes
- Works on **all timeframes**
- **Log scale compatible** (lines adjust correctly)
- No repainting – ATH only updates on confirmed highs
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**Built with Pine Script v6 – Clean, fast, reliable.**
*Happy trading!*
Z-Score Bands + SignalsZ-Score Statistical Market Analyzer
A multi-dimensional market structure indicator based on standardized deviation & regime logic
English Description
Concept
This indicator builds a statistical model of price behaviour by converting every candle’s movement into a Z-score — how many standard deviations each close is away from its moving average.
It visualizes the normal distribution structure of returns and provides adaptive entry signals for both Mean Reversion and Breakout regimes.
Rather than predicting price direction, it measures statistical displacement from equilibrium and dynamically adjusts the decision logic according to the market’s volatility regime.
⚙️ Main Components
Z-Score Bands (±1σ, ±2σ, ±3σ)
– The core structure visualizes volatility boundaries based on rolling mean and standard deviation.
– Price outside ±2σ often indicates statistical extremes.
Dual Signal Systems
Mean Reversion (MRL / MRS): when price (or return z-score) crosses back inside ±2σ bands.
Breakout (BOL / BOS): when price continues to expand beyond ±2σ.
Volatility Regime Classification
The indicator detects whether the market is currently in a low-vol or high-vol regime using percentile statistics of σ.
Low vol → Mean Reversion preferred
High vol → Breakout preferred
🧠 Adaptive Switches
A. Freeze MA/σ - Use previous-bar stats to avoid repainting and lag.
B. Confirm on Close - Only generate signals once the base-timeframe bar closes (eliminates look-ahead bias).
C. Return-based Signal - Use log-return Z-score instead of price deviation — normalizes volatility across assets.
D. Outlier Filter - Exclude bars with abnormal single-bar returns (e.g., >20%). Reduces false spikes.
E. Regime Gating - Automatically switch between Mean Reversion and Breakout logic depending on volatility percentile.
Each module can be toggled individually to test different statistical behaviours or tailor to a specific market condition.
📊 Interpretation
When the histogram of returns approximates a normal distribution, mean-reversion logic is often more effective.
When price persistently drifts beyond ±2σ or ±3σ, the distribution becomes leptokurtic (fat-tailed) — a breakout structure dominates.
Hence, this tool can help you:
Identify whether an asset behaves more “Gaussian” or “fat-tailed”;
Select the correct trading regime (MR or BO);
Quantitatively measure market tension and volatility clusters.
🧩 Recommended Use
Works on any timeframe and any asset.
Best used on liquid instruments (e.g., XAU/USD, indices, major FX pairs).
Combine with volume, sentiment or structural filters to confirm signals.
For strategy automation, pair with the companion script:
🧠 “Z-Score Strategy • Multi-Source Confirm (MRL/MRS/BOL/BOS)”.
⚠️ Disclaimer
This script is designed for educational and research purposes.
Statistical deviation ≠ directional prediction — use with sound risk management.
Past distribution patterns may shift under new volatility regimes.
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中文说明（简体）
概念简介
该指标基于价格的统计分布原理，将每根 K 线的波动转化为标准化的 Z-Score（标准差偏离值），用于刻画市场处于均衡或偏离状态。
它同时支持 均值回归（Mean Reversion） 与 突破延展（Breakout） 两种逻辑，并可根据市场波动结构自动切换策略模式。
⚙️ 主要功能模块
Z-Score 通道（±1σ / ±2σ / ±3σ）
用滚动均值与标准差动态绘制的统计波动带，价格超出 ±2σ 区域通常意味着极端偏离。
双信号系统
MRL / MRS（均值回归多空）：价格重新回到 ±2σ 以内时触发。
BOL / BOS（突破延展多空）：价格持续运行在 ±2σ 之外时触发。
波动率分层
自动识别市场处于高波动还是低波动区间：
低波动期 → 适合均值回归逻辑；
高波动期 → 适合突破趋势逻辑。
🧠 A–E 模块说明
A. 固定统计参数：使用上一根 K 线的均值和标准差，防止重绘。
B. 收盘确认信号：仅在当前时间框架收盘后生成信号，避免前视偏差。
C. 收益率信号模式：采用对数收益率的 Z-Score，更具普适性。
D. 异常波过滤：忽略单根极端波动（如 >20%）的噪声信号。
E. 波动率调节逻辑：根据市场处于高/低波动区间，自动切换 MRL/MRS 或 BOL/BOS。
📊 应用解读
如果收益率分布接近正态分布 → 市场倾向震荡，MRL/MRS 效果较佳；
若价格频繁偏离 ±2σ 或 ±3σ → 市场呈现“肥尾”分布，趋势延展占主导。
因此，该指标的核心目标是：
识别当前市场的统计结构类型；
根据波动特征自动切换交易逻辑；
提供结构化、可量化的市场状态刻画。
💡 使用建议
适用于所有时间框架与金融品种。
建议结合成交量或结构性指标过滤。
若用于策略回测，可搭配同名 “Z-Score Strategy • Multi-Source Confirm” 策略脚本。
⚠️ 免责声明
本指标仅用于研究与教学，不构成任何投资建议。
统计偏离 ≠ 趋势预测，实际市场行为可能在不同波动结构下改变。
