Rolling Compound ReturnRolling Compound Return Indicator - Summary
This indicator calculates and displays the compounded return over rolling time periods, showing how an investment would have performed if held for the specified lookback length.
How it works:
1. Rolling calculation - For each bar, looks back N periods and compounds all the returns together using the formula: (1 + return₁) × (1 + return₂) × ... × (1 + returnₙ) - 1
2. Multiple timeframes - Allows comparison of up to 3 different rolling periods simultaneously:
* Period 1 (default 20 bars): Blue line
* Period 2 (default 50 bars): Orange line
* Period 3 (default 100 bars): Purple line
3. Visual elements:
* Lines plotted as percentage returns on dedicated Y-axis
* Zero reference line to distinguish gains from losses
* Optional green/red fill showing positive/negative zones
* Info table displaying current values for each period
4. Key insight - Unlike simple moving averages of returns, this shows the actual cumulative effect of holding through all the ups and downs over the rolling window.
Use case: Helps identify whether recent price action (over your chosen lookback period) has resulted in net gains or losses, and how different time horizons compare. For example, you might see the 20-period showing +5% while the 50-period shows -2%, indicating recent strength after a longer decline.
The indicator updates on every bar to show the "rolling N-period return" at each point in time.
Forecasting
Blavk Terminal - OpenCheck For Green Tag Breakout. For confirmation check the ascending triangle.
15mins - Swing Trading
1 Day - 1Month - 2Month hold or Long Term
Contact ->
Instagram - blavkcorecapitals
Dynamic Buy/Sell Volume Visualizer [wjdtks255]Indicator Description:
The Dynamic Buy/Sell Volume Visualizer separates bullish and bearish volumes and calculates their moving averages with customizable colors and transparency. It dynamically visualizes buying strength relative to selling pressure by plotting a volume ratio line that changes color intensity and line thickness based on volume dominance. Background colors highlight strong buying or selling phases when volumes exceed thresholds. Volume bars and moving averages provide clear market volume context, and horizontal lines mark key neutral and strength levels.
How It Works:
Bull and bear volumes are distinguished by candle direction.
Moving averages (SMA) smooth volume data with user-defined length and customizable visual styles.
The volume ratio (buy volume MA over total MA) reflects buying strength from 0 (full sell) to 1 (full buy).
The volume ratio line’s color and thickness change dynamically according to the ratio’s magnitude.
Background colors alert users when buy or sell volumes surpass thresholds.
Volume bars and moving averages give detailed volume insights, complemented by horizontal lines showing neutral (0.5), strong buy (0.7), and strong sell (0.3) levels.
Trading Method:
Use the volume ratio line to gauge current market pressure; above 0.7 suggests strong buying, below 0.3 indicates strong selling.
Observe background color shifts as quick visual cues for volume surges or declines.
Combine this volume visualization with price actions to time entries and exits.
Customize moving average parameters to align the indicator with your trading style.
[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.
Deep Analyst - HorizontalDeep Analyst – Multi-Layer Market Intelligence Dashboard - Horizontal
Description:
The Deep Analyst indicator is an advanced multi-factor technical dashboard that consolidates key market signals into a single, intuitive on-chart table. It provides real-time insights across trend, momentum, volatility, sentiment, and volume dynamics — helping traders quickly assess overall market conditions and directional strength.
Features:
Trend Analysis: Detects short- and long-term direction using moving averages and custom trend-strength logic.
Moving Averages Setup: Evaluates MA alignment and crossover conditions (Golden/Death Cross).
Dual SuperTrend System: Combines fast and slow ATR-based SuperTrends to identify strong or weak bullish/bearish phases.
DMI + ADX: Measures directional strength and momentum intensity with visual feedback on rising or falling ADX.
RSI & Stochastic: Captures overbought/oversold conditions and short-term oscillations with sentiment coloring.
MACD: Tracks momentum transitions and crossovers for early signal confirmation.
Sentiment Gauge: Aggregates RSI, MACD, and price-action bias to form a clear BULL/BEAR/NEUTRAL sentiment reading.
Choppiness Index: Distinguishes between trending and ranging markets with dynamic status updates.
ATR Monitor: Evaluates volatility levels (HIGH/LOW/NORMAL) and direction of volatility change.
Volume Delta Analysis: Measures buy/sell pressure balance and strength of participation (BUY/SELL/STRONG signals).
Customizable Table Layout: Adjustable position, colors, and background for seamless chart integration.
Usage:
Ideal for traders who want a holistic, real-time technical overview without switching between multiple indicators. The Deep Analyst condenses core market analytics into a compact visual panel — making it easy to interpret trend alignment, momentum shifts, and sentiment transitions at a glance.
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
Adaptive Cortex Strategy (ACS)Strategy Title: Adaptive Cortex Strategy (ACS)
This script is invite-only.
Part 1: Philosophy and the Fundamental Problem It Solves
Adaptive Cortex Strategy (ACS) is an advanced decision support system designed to dynamically adapt to the ever-changing characteristics of the market. A major weakness of traditional approaches is that while successful in a specific market condition (e.g., a strong trend), they become ineffective when the market changes course (e.g., enters a sideways range). ACS solves this problem by continuously analyzing the market's current "regime" and instantly adapting its decision-making logic accordingly.
Its primary goal is to enable the strategy itself to "think" and evolve with the market, without requiring the trader to change their strategy.
Part 2: Original Methodology and Proprietary Logic
A Note on the Original Methodology and Intellectual Property
This algorithm is not based on or copied from any open-source strategy code. The system utilizes the mathematical principles of widely accepted indicators such as ADX, RSI, and Ichimoku as data sources for its analyses.
However, the intellectual property and unique value of the algorithm lies in its unique and closed-source architecture that processes, prioritizes, and synthesizes data from these standard tools. The methods used in core components, particularly the adaptive 'Cortex' memory system and statistical 'Forecast' engine, represent a unique set of logic developed from scratch for this script. The parameters, order of operations, and conditional logic are entirely custom-designed. Therefore, the system's performance is a result of its unique design, not a repetition of publicly available code.
ACS's power lies not in the individual indicators it uses, but in the unique and proprietary logic layers that process the information from these indicators.
1. Multi-Factor Scoring and Adaptive Weighting:
The heart of the methodology is a scoring system that analyzes the market in four main categories: Trend, Support/Resistance, Momentum, and Volume. However, what makes ACS unique is that it dynamically changes the importance it assigns to these categories based on the market regime.
Unique Application: Using ADX, DMI, and ATR indicators, the system detects whether the market is in different regimes, such as "Strong Trend" or "High Volatility Squeeze." When it detects a strong trend, it automatically increases the weight of the Trend scores from the Ichimoku and proprietary AMF Trend Engine. When it detects sideways or tightness, it shifts its focus to Support/Resistance zones determined by Dynamic Channels and the author's "Cortex" Memory System. A different approach was added here, inspired by the classic Fibonacci estimation. This "adaptive weighting" ensures that the strategy always focuses its attention on the most appropriate area.
2. Statistical Forecast Engine:
ACS goes beyond standard indicators and includes a proprietary forecasting algorithm that measures the probability of a potential price movement's success.
Unique Implementation: The system stores the results of past tests (successful bounces/breakouts) at key price levels in a "brain" (memory). At the time of a new test, it compares the current RSI momentum, volume anomalies, and market regime with similar past situations. Based on this comparison, it calculates the probability of the current test being successful as a statistical percentage and adds this percentage to the final score as a "bonus" or "penalty."
3. Walk-Forward Architecture:
Markets constantly evolve. ACS continues to learn from the latest market dynamics by resetting its memory at regular intervals (e.g., monthly) through its "Re-Learn Mode," rather than being trapped by old data. This is an advanced approach aimed at ensuring the strategy remains current and effective over the long term.
Part 3: Practical Features and User Benefits
HOW DOES IT HELP INVESTORS?
Customizable Trading Profiles: ACS does not come with a single set of settings. Users can instantly adapt all the algorithm's key periods and decision thresholds to their trading style by selecting one of the pre-configured trading profiles, such as "SCALPING," "INTRADAY TREND," or "SWING TRADE." Additionally, they can further fine-tune the selected profile with "Speed Adjustment."
Full Automation Compatibility (JSON): The strategy is equipped with fully configurable JSON-formatted alert messages for buy, sell, and position closing transactions. This makes it possible to establish a fully automated trading system by connecting ACS signals to automation platforms such as 3Commas and PineConnector. Dynamic values such as position size ({{strategy.order.contracts}}) are automatically added to alerts.
Advanced and Adaptive Risk Management: Protecting capital is as important as making a profit. ACS offers a multi-layered risk management framework for this purpose:
Flexible Position Size: Allows you to set the risk for each trade as a percentage of capital or a fixed dollar amount.
Adaptive ATR Stop: The stop-loss level is dynamically expanded or contracted based on current market volatility (the ratio of short-term ATR to long-term ATR).
Contingency Mechanisms: Includes safety nets such as "Maximum Drawdown Protection" and the "Praetorian Guard" engine, which detects sudden market shocks.
Clear and Comprehensible Dashboard: Transforms dozens of complex data points into an intuitive dashboard that provides critical information such as market trends, major trends, support/resistance zones, and final signals at a glance.
Section 4: Disclaimers and Rules
Transparency Note: This algorithm uses the mathematical foundations of publicly available indicators such as ADX, ATR, RSI, and Ichimoku. However, ACS's intellectual property and unique value lies in its unique architecture, which combines data from these standard tools, prioritizes it by market trend, and synthesizes it with its proprietary "Cortex" and "Statistical Forecast" engines.
Educational Use:
IMPORTANT WARNING: The Adaptive Cortex Strategy is a professional decision support and analysis tool. It is NOT a system that promises "guaranteed profits." All trading activities involve the risk of capital loss. Past performance is no guarantee of future results. All signals and analysis generated by this script are for educational purposes only and should not be construed as investment advice. Users are solely responsible for applying their own risk management rules and making their final trading decisions.
Strategy Backtest Information
Please remember that past performance is not indicative of future results. The published chart and performance report were generated on the 4-hour timeframe of the BTC/USD pair with the following settings:
Test Period: January 1, 2016 - November 2, 2025
Default Position Size: 15% of Capital
Pyramiding: Closed
Commission: 0.0008
Slippage: 2 ticks (Please enter the slippage you used in your own tests)
Testing Approach: The published test includes 123 trades and is statistically significant. It is strongly recommended that you test on different assets and timeframes for your own analysis. The default settings are a template and should be adjusted by the user for their own analysis.
Trailing 12M % Gain/Lossthis script shows profit or loss for training 12 months, works only on daily time frame
True Range + Average True Range (Status Line Only)This simple yet powerful indicator displays True Range (TR) and Average True Range (ATR) values directly in your TradingView status line, without cluttering your chart.
It’s designed for traders who want to quickly monitor volatility and price range expansion in real time.
⚙️ Features:
Real-time updating TR & ATR values
Clean and minimal — no chart clutter
Customizable ATR length and smoothing method (RMA, SMA, EMA, WMA)
Works on all timeframes and symbols
📈 Use Cases:
Monitor volatility changes during trading sessions
Confirm breakout strength or volatility contraction
Combine with price action or volume-based setups
Buy&Hold Profitcalculator in EuroTitle: Buy & Hold Strategy in Euro
Description:
This Pine Script implements a simple yet flexible Buy & Hold strategy denominated in Euros, suitable for a wide range of assets including cryptocurrencies, forex pairs, and stocks.
Key Features:
Custom Investment Amount: Define your invested capital in Euros.
Flexible Start & End Dates: Specify exact entry and exit dates for the strategy.
Automatic Currency Conversion: Supports assets priced in USD or USDT, converting the invested capital to chart currency using the EUR/USD exchange rate.
Single Entry and Exit: Executes a one-time Buy & Hold position based on the defined timeframe.
Profit and Performance Tracking: Calculates total profit/loss in Euros and percentage returns.
Smart Exit Label: Displays a dynamic label at the exit showing final position value, net profit/loss, and return percentage. The label automatically adjusts its position above or below the price bar for optimal visibility.
Visual Enhancements:
Position value and profit/loss plotted on the chart.
Background color highlights the active investment period.
Buy and Sell markers clearly indicate entry and exit points.
This strategy is ideal for traders and investors looking to simulate long-term positions and evaluate performance in Euro terms, even when trading USD-denominated assets.
Usage Notes:
Best used on daily charts for medium- to long-term analysis.
Adjust start and end dates, as well as invested capital, to simulate different scenarios.
Works with any asset, but currency conversion is optimized for USD or USDT-pegged instruments.
Doctor Scalp (BUY/SELL) [by Adi]A script for fast scalping using. Works best with a 5-minute-to-1-hour interval.
QV ATR Active Range ValuesQuantVault
### Description for Presentation
The "QV ATR Active Range Values" indicator is a forward-looking tool designed for traders to estimate potential price ranges over 1, 2, or 3 months based on historical volatility and momentum. It leverages the Average True Range (ATR) to measure volatility and incorporates a "win rate" derived from recent candle colors to bias projections toward upside or downside potential. This creates asymmetric range forecasts that reflect market directionality, helping users anticipate breakout levels, set targets, or manage risk. The indicator overlays projected high/low lines on the chart and displays a compact table summarizing days to key percentage targets (e.g., +30% or -20%) alongside projected prices and percentage changes. Ideal for swing traders or investors seeking data-driven price projections without relying on complex models.
### Detailed Explanation of How It Works
This indicator uses Pine Script v5 on TradingView to compute and visualize price projections. Below, I'll break it down step by step, including the key calculations, logic, and outputs. Note that it assumes a trading month has 21 days (a common approximation for business days), and all projections are based on daily timeframes derived from weekly data.
#### 1. **User Inputs**
- **ATR Length (Lookback)**: Default 25. This is the period used to calculate the ATR and count candle colors.
- **Show Projections**: Boolean toggles to display 1-month (yellow), 2-month (orange), or 3-month (green/red) lines. By default, only 1-month is shown.
#### 2. **Period Definitions**
- Months are converted to days assuming 21 trading days per month:
- 1 month: 21 days
- 2 months: 42 days
- 3 months: 63 days
- These periods represent the forward-looking horizons for projections.
#### 3. **Volatility Calculation (ATR)**
- **Weekly ATR**: Fetched using `request.security` on the weekly timeframe with the specified ATR length (e.g., average true range over the last 25 weeks).
- **Daily ATR**: Derived by dividing the weekly ATR by 5 (approximating 5 trading days per week). This scales volatility to a daily basis.
- **Base Projections**: For each period, multiply daily ATR by the number of days in that period. This estimates the total expected range if volatility persists:
- 3 months: `daily_atr * 63`
- 2 months: `daily_atr * 42`
- 1 month: `daily_atr * 21`
#### 4. **Momentum Bias (Win Rate)**
- Counts the number of "green" (close > open, bullish) and "red" (close < open, bearish) candles over the ATR lookback period.
- **Win Rate**: Fraction of green candles out of total colored candles (green + red). Defaults to 0.5 (50%) if no colored candles exist.
- This win rate introduces asymmetry: In bullish periods (high win rate), upside projections are larger; in bearish periods (low win rate), downside projections dominate.
#### 5. **Adjusted Projections**
- **Upside Projection**: Base projection multiplied by win rate (e.g., for 3 months: `base_projection_3 * win_rate`).
- **Downside Projection**: Base projection multiplied by (1 - win rate).
- **Projected Prices**:
- High: Current close + upside projection
- Low: Current close - downside projection
- This creates realistic, direction-biased ranges rather than symmetric ones.
#### 6. **Chart Overlays (Plots)**
- Lines are plotted only if the corresponding toggle is enabled, with 50% transparency for a dimmed effect:
- 3-month high: Solid green line
- 3-month low: Solid red line
- 2-month high/low: Dashed orange lines
- 1-month high/low: Dashed yellow lines (#f6e122)
- These lines extend horizontally from the current bar, visualizing potential future highs/lows.
#### 7. **Daily Rates and Days to Targets**
- **Up Rate**: `daily_atr * win_rate` (expected daily upward movement).
- **Down Rate**: `daily_atr * (1 - win_rate)` (expected daily downward movement).
- **Days to Targets**: Calculates approximate trading days to reach fixed percentage moves from the current close, using the rates:
- +30%: `(close * 0.30) / up_rate` (rounded)
- +20%: `(close * 0.20) / up_rate`
- +10%: `(close * 0.10) / up_rate`
- -10%: `(close * 0.10) / down_rate`
- -20%: `(close * 0.20) / down_rate`
- -30%: `(close * 0.30) / down_rate`
- If a rate is zero, days are set to `na` (not applicable).
#### 8. **Table Display**
- A single combined table is created at the top-center of the chart with a semi-transparent black background (80% opacity) and white borders.
- **Structure** (6 columns x 7 rows):
- **Left Section (Days to Targets, Columns 0-1)**:
- Lists percentage targets (+30% to -30%) with corresponding days, colored green for upside and red for downside.
- **Separation (Column 2)**: Empty for visual spacing.
- **Right Section (Projections, Columns 3-5)**:
- Shows 1M/2M/3M highs and lows with:
- Projected price (formatted to 2 decimals).
- Percentage change from close (e.g., `((projected_high - close) / close) * 100`).
- Colors match the plot lines: Yellow for 1M, orange for 2M, green for 3M high, red for 3M low.
- The table updates dynamically with each bar, providing at-a-glance insights.
#### Key Assumptions and Limitations
- **Volatility Persistence**: Assumes future ATR matches historical levels; actual volatility can fluctuate.
- **Linear Projection**: Treats price movement as additive daily increments, ignoring compounding or non-linear effects.
- **Candle Count**: Only considers colored candles (ignores doji where open = close), and uses a simple win rate without weighting by size.
- **Timeframe**: Best on daily charts; weekly ATR scaling assumes consistent weekly-to-daily ratios.
- **No Backtesting**: This is a visualization tool, not a strategy with entry/exit signals. Test projections against historical data for accuracy.
This indicator combines volatility forecasting with basic sentiment analysis for practical, visual projections. If you're presenting it, emphasize how the win rate adds a directional edge over plain ATR-based ranges, making it more adaptive to trending markets. If you need modifications or examples on specific tickers, let me know!
AI MEDEA FORECASTAI MEDEA searches for similar historical patterns and uses them to generate predictions. The longer it runs, the more data it gathers and the better the predictions become.
Important:
The indicator must remain enabled to:
- Collect predictions and check their accuracy
- Have as much data as possible for comparison
- Provide more accurate results
Recommendation:
Let the indicator run for several days on different timeframes (15m, 30m, 1H, 4H). The accuracy table will show the actual accuracy only after gathering enough predictions.
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
ANN TREND SPX500 1m-1HHappy Trading! This indicator is the successor to my previous ANN Trend Prediction, now featuring improved feature vectors, refined backpropagation, and a stronger focus on asset- and timeframe-specific patterns for more precise predictions.
Internally is a collection of nine artificial neural networks (ANNs) trained on the S&P 500 to forecast uptrends, downtrends, or ranging markets. Each ANN is trained on one of the following timeframes: 1m, 2m, 3m, 5m, 10m, 15m, 30m, 45m, and 60m, and the appropriate model is selected automatically.
1. Settings
In the settings menu shown in the image below, you’ll find six options:
Indicator Timeframe – Choose between 1m and 1H.
Intrabar – Choose between Alerts been send intrabar or only at bar closing.
Lookback – Define how many previous bars the ANN should use in its calculations.
Smoothing – To reduce short-term switching of the prediction you can activate Smoothing. Here-by the input datas get filtered by a mean function.
Range Filter – Enable a third class, Ranging, in addition to Uptrend and Downtrend. This enables you to avoid choppy markets.
Class Colors – Here you can change each Class (Up, Down Trend etc) color.
2. Comparison with EMA crossover
The Prediction of the ANN Trend SPX500 1m-1H is more reliable as the prediction of the EMA crossover, shown in the Image below.
Both indicators use the same period of 65 bars and source their input data from the same chart.
While the EMA crosses over multiple times (shown as red vertical lines in the image), the ANN Trend maintains its prediction signal as Uptrend.
This advantage of the ANN comes from its learned knowledge. During training, it was exposed to a vast number of price charts, enabling it to distinguish between a trend setback and a true trend reversal.
3. Alerts
The indicator generates two types of alert signals:
Trade Signal:
1 = Uptrend
0 = Ranging
-1 = Downtrend
-2 = no prediction
Signal Age: Counts the number of bars since the last signal change. With the Signal Age you have access to the entry-price of the actual Trend. If you use You just call close to get the last entry-price.
4. Declaration for TradingView House Rules on Script Publishing
The unique feature of ANN Trend SPX500 1m-1H is it's real-time range detection capability and it's capability to distinguishes between a Trend set back and a Trend reversal which results in longer lasting trend predictions in comparison to any Moving Average Crossover Indicators.
This script is closed-source and invite-only, to support and compensate for months of development work.
5. Disclaimer
Trading involves risk, and losses can and do occur. This script is intended for informational and educational purposes only. All examples are hypothetical and not financial advice.
Decisions to buy, sell, hold, or trade securities, commodities, or other assets should be based on the advice of qualified financial professionals. Past performance does not guarantee future results.
Use this script at your own risk. It may contain bugs, and I cannot be held responsible for any financial losses resulting from its use.
Cheers!
OU Mean-Reversion Bands This indicator applies the Ornstein-Uhlenbeck (OU) mean-reversion model to price or spread data and automatically visualizes the dynamic equilibrium (μ) and its deviation bands.
It estimates the OU parameters (φ, μ, σₛₜₐₜ) directly from price history, generating adaptive statistical bands that represent overbought and oversold zones.
Market Breadth & Forward ReturnsThis indicator shows how future index performance has historically behaved after different levels of market breadth. The heatmap reveals which breadth zones have tended to precede better or worse forward returns. This is strictly a statistical conditional-expectation map, not a set of signals.
Scope
This is not meant for any arbitrary asset.
It is meant for broad indices only (S&P 500, Nasdaq 100, Dow, Russell, major sector families).
The breadth data is derived from index-level market universes.
Do not apply this on single stocks, crypto or FX. The method only makes sense with large diversified universes.
Core method
Daily breadth is normalized 0 to 100.
For each bar, six forward horizons are evaluated on the index: performance after X days.
Each observation is placed into a breadth bin.
Each bin/horizon pair has mean, variance and count computed.
Each bin/horizon mean is t-tested against zero.
Benjamini-Hochberg False Discovery Rate weighting allocates weight only to horizons where evidence exists.
Weighted horizon means are aggregated and annualized (252 trading days).
The map displays annualized conditional forward returns per breadth bin.
Why this is robust
Non-repainting. Breadth is in the past, returns are strictly future, lookahead_off.
Multiple horizons avoid single-window biases.
Variance, t-tests and FDR correction drastically reduce false positives.
Bins with poor sample size are visually suppressed to avoid over-interpretation.
How to use
Daily timeframe only.
Select the correct index family (S&P 500, Nasdaq 100, Russell…).
Bin size 5 to 10 points is a realistic range.
Min occurrences per bin ≥ 5 recommended.
FDR alpha 0.05 to 0.10 is a good working envelope.
Interpret as conditional expectations, not a forecast guarantee.
Notes
Do not use on random assets.
Do not extrapolate outside the chosen index family.
Always keep symbol and timeframe visible when publishing.
Indicator by Julien Eche
Seasonal Performance Analyzer | AlphaNatt📊 Seasonal Performance Analyzer | AlphaNatt
📈 Overview
Unlock the power of seasonality with this advanced visualization tool that reveals hidden patterns in market behavior. The Seasonal Performance Analyzer overlays multiple years of historical data for any selected month, allowing traders to identify recurring seasonal trends, anomalies, and potential trading opportunities.
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
✨ Key Features
🎯 Month-by-Month Analysis
- Isolate and analyze any single month across multiple years
- Compare up to 20 years of historical performance
- Instantly visualize seasonal patterns and trends
📊 Advanced Visualization
- Beautiful gradient coloring from oldest (light blue) to newest (dark blue) years
- Clean axis system with labeled days and months
- Professional grid layout for easy value reading
- Optional average line showing mean performance across all years
🔧 Flexible Display Options
- Normalize to 100: Start each year at a base value of 100 for easy percentage comparison
- Raw Price Mode: View actual price movements without normalization
- Customizable Colors: Adjust gradient colors and transparency to your preference
- Toggle Features: Show/hide year labels, average line, and day labels
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
⚙️ Input Parameters
📅 Time Settings
- Select Month: Choose any month (1-12) for analysis
- Years to Display: Show 1-20 years of historical data
- Include Current Year: Option to include incomplete current year data
🎨 Visual Settings
- Line Transparency: Adjust the opacity of year lines (0-100)
- Gradient Colors: Customize oldest and newest year colors
- Average Line: Color and width customization
- Legend Display: Toggle year labels on/off
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
💡 Use Cases
1. Seasonal Trading Strategies
Identify months with consistent directional bias for seasonal entry/exit timing
2. Risk Management
Spot historically volatile periods and adjust position sizes accordingly
3. Pattern Recognition
Discover recurring intra-month patterns like "first week strength" or "mid-month reversals"
4. Comparative Analysis
Compare current month's performance against historical averages to gauge relative strength
5. Anomaly Detection
Quickly identify years that deviated significantly from typical seasonal patterns
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
📖 How to Use
Step 1: Add the indicator to your chart
Step 2: Select the month you want to analyze (default: November)
Step 3: Choose how many years of history to display
Step 4: Toggle normalization based on your analysis needs
Step 5: Look for patterns:
• Consistent trends across multiple years
• Divergences from the average line
• Specific days with recurring movements
• Years that broke the seasonal pattern
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
🎯 Pro Tips
✅ For Swing Traders: Focus on months showing consistent multi-day trends
✅ For Day Traders: Identify specific days within a month that show repetitive behavior
✅ For Investors: Use normalized view to compare percentage gains across years
✅ For Risk Analysis: The wider the spread between years, the less reliable the seasonal pattern
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
📊 Example Insights
This indicator can reveal powerful insights such as:
- "November typically shows strength in the first two weeks"
- "Years above the average line tend to continue outperforming"
- "Day 15-20 historically shows consolidation patterns"
- "Election years show different patterns than non-election years"
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
⚠️ Important Notes
- Past performance does not guarantee future results
- Seasonality is one factor among many - combine with other analysis methods
- Major events can override seasonal patterns
- Works best on assets with long price history
- More years of data generally provides more reliable patterns
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
🏆 Perfect For:
- Seasonal traders
- Swing traders looking for optimal entry months
- Analysts studying market cycles
- Anyone interested in historical market patterns
- Risk managers assessing seasonal volatility
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
Created by AlphaNatt - Empowering traders with advanced seasonal analysis
Version: 1.0
Pine Script: v6
License: Mozilla Public License 2.0
Perpetual Swing [HCR]The Perpetual Swing is a fully automated swing-direction indicator designed to help traders visualize long-term trend regimes and smooth out noise in volatile markets.
It combines:
• Hash Adaptive CCI – a dynamically tuned Commodity Channel Index that adapts to volatility conditions.
• Regime-based SMMA – a Smoothed Moving Average model used to define bullish and bearish environments.
The indicator continuously monitors both momentum and structural trend, switching bias automatically between long and short conditions.
It can be used on any asset or timeframe to identify directional bias, trend transitions, and potential swing entries.
How it works:
– When the adaptive CCI confirms bullish strength above the SMMA regime, the indicator signals a long bias.
– When momentum and regime flip bearish, it switches to short bias.
– The system remains continuously engaged to capture multi-cycle swings.
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.
