PRICE MOVEMENT STATISTICS# Price Movement Statistics - Advanced Pattern Recognition System
## Foundation
Price Movement Statistics (PMS) represents a fundamentally different approach to market analysis compared to traditional indicators like RSI, Moving Averages, or Bollinger Bands. While most indicators rely on mathematical transformations of price data, PMS implements a **machine learning-inspired nearest-neighbor algorithm** that compares current market conditions against thousands of historical patterns across multiple correlated instruments.
### What Makes This Original
Unlike standard indicators that follow predetermined formulas, PMS:
1. **Multi-Symbol Pattern Database**: Analyzes up to 4 different but correlated symbols simultaneously, creating a massive historical pattern database that single-symbol indicators cannot access
2. **8-Feature Normalized Vector Comparison**: Converts each candlestick into 8 numerical features (body-to-range ratios, wick proportions, relative positioning, momentum characteristics) and uses Manhattan distance calculations to find statistically similar historical situations
3. **Forward-Looking Statistical Validation**: Instead of just identifying patterns, PMS tracks what actually happened 1-5 bars after similar patterns occurred historically, providing probabilistic forecasts with sample sizes and confidence levels
4. **Adaptive Similarity Scoring**: Uses real-time distance calculations between current conditions and historical patterns, allowing traders to see exactly how many similar cases existed and their outcomes
## Technical Methodology Explained
### Pattern Recognition Engine
The core algorithm transforms each market condition into a normalized 8-dimensional vector containing:
- Short vs. long-term range ratios computed using proprietary envelope calculations
- Price position relative to recent ranges using adaptive scaling methods
- Volatility comparisons across multiple timeframes with logarithmic return analysis
- Momentum divergences between short and long-term linear regression slopes
- Volume behavior patterns using statistical deviation scoring
- Candlestick structure metrics including ATR ratios and boundary touch frequencies
### Advanced Code Architecture
**Multi-Symbol Data Pipeline**: The system employs Pine Script's `request.security()` function in a sophisticated loop structure that simultaneously processes up to 4 different instruments. Each symbol contributes its own 8-feature vector, creating a 32-dimensional search space that dramatically expands pattern recognition capabilities beyond single-symbol analysis.
**Adaptive Normalization Engine**: Rather than using simple percentage changes, the code implements a custom `scale_adaptive()` function that ranks current values against rolling historical distributions. This percentile-based approach ensures pattern recognition remains consistent across different market volatility regimes and price levels.
**Distance Matrix Calculations**: The matching algorithm runs nested loops through thousands of historical bars, computing Manhattan distances for each potential match. The code optimizes performance by using vectorized operations and early termination conditions when similarity thresholds aren't met.
**Forward-Looking Analysis Pipeline**: Once matches are identified, the system implements a sophisticated outcome tracking mechanism that categorizes future price movements, volume behaviors, and candle characteristics. This requires careful index management to avoid look-ahead bias while maintaining real-time calculation efficiency.
### Similarity Matching Process
1. **Data Normalization**: Features are processed through custom percentile ranking against 500-bar rolling windows
2. **Distance Calculation**: Optimized Manhattan distance computation across 8-dimensional vectors with early exit conditions
3. **Multi-Symbol Aggregation**: Matches from different symbols are weighted and combined using statistical averaging techniques
4. **Threshold Filtering**: Dynamic similarity boundaries that adapt to market volatility conditions
5. **Outcome Analysis**: Forward-looking statistical compilation with bias tracking and magnitude calculations
### Statistical Output Generation
The system's proprietary aggregation engine provides:
- **Win/Loss Ratios**: Calculated from actual forward-price movements with statistical weighting
- **Sample Sizes**: Match counts across all symbols with confidence scoring algorithms
- **Average Magnitude**: Expected move calculations using historical outcome distributions
- **Volume Context**: Pattern-specific volume analysis using normalized scoring methods
- **Directional Bias**: Multi-timeframe probability calculations with cross-symbol validation
## Why This Approach is Worth the Investment
### Beyond Traditional Indicators
Standard indicators like RSI or MACD give you oversold/overbought signals or momentum divergences, but they don't answer the crucial question: "What happened historically when similar conditions occurred?" PMS bridges this gap by providing:
1. **Quantified Probabilities**: Instead of subjective pattern recognition, you get actual win rates and sample sizes
2. **Cross-Market Validation**: Patterns confirmed across multiple correlated instruments carry more statistical weight
3. **Sample Size Transparency**: You can see whether a signal is based on 5 occurrences or 500, adjusting confidence accordingly
4. **Magnitude Expectations**: Historical data shows not just direction, but expected move sizes
### Practical Trading Applications
**Entry Timing**: When PMS shows >70% historical win rate with 100+ matches, you have statistical evidence supporting your entry rather than relying on visual pattern interpretation.
**Risk Management**: Historical magnitude data helps size positions appropriately based on expected adverse moves in similar past situations.
**Confirmation**: Multi-symbol analysis provides cross-market confirmation that single-symbol indicators cannot offer.
## How to Use the System
### Signal Interpretation
- **Bias Ratio >1.5**: Historically bullish (more winning long trades than losing ones)
- **Bias Ratio <0.67**: Historically bearish (more winning short trades than losing ones)
- **Sample Size >50**: High confidence (sufficient historical data)
- **Sample Size <20**: Low confidence (limited historical precedent)
### Setup Optimization
- **Symbol Selection**: Choose 3-4 correlated instruments (e.g., stock + sector ETF + index, or currency pairs with base currency relationships)
- **Timeframe Coordination**: Use higher timeframes for broader context, lower timeframes for precise entry timing
- **Threshold Adjustment**: Lower similarity thresholds find more specific matches; higher thresholds increase sample sizes
## Technical Requirements and Limitations
**Data Depth**: Requires minimum 1000 bars per symbol for meaningful analysis; 3000+ bars recommended for optimal performance.
**Computational Load**: Real-time pattern matching across multiple symbols and thousands of historical bars requires TradingView's advanced Pine Script capabilities.
**Market Applicability**: Most effective in liquid markets with sufficient historical data; less reliable in newly listed instruments or during unprecedented market conditions.
## Important Disclaimers
This system identifies historical statistical patterns under similar conditions—it does not predict future movements with certainty. Effectiveness depends on intelligent symbol selection, appropriate timeframe usage, and integration with proper risk management. Past performance patterns do not guarantee future results, and all trading involves substantial risk of loss.
The algorithm's sophistication lies not in complex mathematical formulas, but in its ability to efficiently search through massive historical datasets and quantify pattern outcomes—something impossible to do manually and unavailable in standard technical indicators.
Statistics
SIP Evaluator and Screener [Trendoscope®]The SIP Evaluator and Screener is a Pine Script indicator designed for TradingView to calculate and visualize Systematic Investment Plan (SIP) returns across multiple investment instruments. It is tailored for use in TradingView's screener, enabling users to evaluate SIP performance for various assets efficiently.
🎲 How SIP Works
A Systematic Investment Plan (SIP) is an investment strategy where a fixed amount is invested at regular intervals (e.g., monthly or weekly) into a financial instrument, such as stocks, mutual funds, or ETFs. The goal is to build wealth over time by leveraging the power of compounding and mitigating the impact of market volatility through disciplined, consistent investing. Here’s a breakdown of how SIPs function:
Regular Investments : In an SIP, an investor commits to investing a fixed sum at predefined intervals, regardless of market conditions. This consistency helps inculcate a habit of saving and investing.
Cost Averaging : By investing a fixed amount regularly, investors purchase more units when prices are low and fewer units when prices are high. This approach, known as dollar-cost averaging, reduces the average cost per unit over time and mitigates the risk of investing a large amount at a peak price.
Compounding Benefits : Returns generated from the invested amount (e.g., capital gains or dividends) are reinvested, leading to exponential growth over the long term. The longer the investment horizon, the greater the potential for compounding to amplify returns.
Dividend Reinvestment : In some SIPs, dividends received from the underlying asset can be reinvested to purchase additional units, further enhancing returns. Taxes on dividends, if applicable, may reduce the reinvested amount.
Flexibility and Accessibility : SIPs allow investors to start with small amounts, making them accessible to a wide range of individuals. They also offer flexibility in terms of investment frequency and the ability to adjust or pause contributions.
In the context of the SIP Evaluator and Screener , the script simulates an SIP by calculating the number of units purchased with each fixed investment, factoring in commissions, dividends, taxes and the chosen price reference (e.g., open, close, or average prices). It tracks the cumulative investment, equity value, and dividends over time, providing a clear picture of how an SIP would perform for a given instrument. This helps users understand the impact of regular investing and make informed decisions when comparing different assets in TradingView’s screener. It offers insights into key metrics such as total invested amount, dividends received, equity value, and the number of installments, making it a valuable resource for investors and traders interested in understanding long-term investment outcomes.
🎲 Key Features
Customizable Investment Parameters: Users can define the recurring investment amount, price reference (e.g., open, close, HL2, HLC3, OHLC4), and whether fractional quantities are allowed.
Commission Handling: Supports both fixed and percentage-based commission types, adjusting calculations accordingly.
Dividend Reinvestment: Optionally reinvests dividends after a user-specified period, with the ability to apply tax on dividends.
Time-Bound Analysis: Allows users to set a start year for the analysis, enabling historical performance evaluation.
Flexible Dividend Periods: Dividends can be evaluated based on bars, days, weeks, or months.
Visual Outputs: Plots key metrics like total invested amount, dividends, equity value, and remainder, with customizable display options for clarity in the data window and chart.
🎲 Using the script as an indicator on Tradingview Supercharts
In order to use the indicator on charts, do the following.
Load the instrument of your choice - Preferably a stable stocks, ETFs.
Chose monthly timeframe as lower timeframes are insignificant in this type of investment strategy
Load the indicator SIP Evaluator and Screener and set the input parameters as per your preference.
Indicator plots, investment value, dividends and equity on the chart.
🎲 Visualizations
Installments : Displays the number of SIP installments (gray line, visible in the data window).
Invested Amount : Shows the cumulative amount invested, excluding reinvested dividends (blue area plot).
Dividends : Tracks total dividends received (green area plot).
Equity : Represents the current market value of the investment based on the closing price (purple area plot).
Remainder : Indicates any uninvested cash after each installment (gray line, visible in the data window).
🎲 Deep dive into the settings
The SIP Evaluator and Screener offers a range of customizable settings to tailor the Systematic Investment Plan (SIP) simulation to your preferences. Below is an explanation of each setting, its purpose, and how it impacts the analysis:
🎯 Duration
Start Year (Default: 2020) : Specifies the year from which the SIP calculations begin. When Start Year is enabled via the timebound option, the script only considers data from the specified year onward. This is useful for analyzing historical SIP performance over a defined period. If disabled, the script uses all available data.
Timebound (Default: False) : A toggle to enable or disable the Start Year restriction. When set to False, the SIP calculation starts from the earliest available data for the instrument.
🎯 Investment
Recurring Investment (Default: 1000.0) : The fixed amount invested in each SIP installment (e.g., $1000 per period). This represents the regular contribution to the SIP and directly influences the total invested amount and quantity purchased.
Allow Fractional Qty (Default: True) : When enabled, the script allows the purchase of fractional units (e.g., 2.35 shares). If disabled, only whole units are purchased (e.g., 2 shares), with any remaining funds carried forward as Remainder. This setting impacts the precision of investment allocation.
Price Reference (Default: OPEN): Determines the price used for purchasing units in each SIP installment. Options include:
OPEN : Uses the opening price of the bar.
CLOSE : Uses the closing price of the bar.
HL2 : Uses the average of the high and low prices.
HLC3 : Uses the average of the high, low, and close prices.
OHLC4 : Uses the average of the open, high, low, and close prices. This setting affects the cost basis of each purchase and, consequently, the total quantity and equity value.
🎯 Commission
Commission (Default: 3) : The commission charged per SIP installment, expressed as either a fixed amount (e.g., $3) or a percentage (e.g., 3% of the investment). This reduces the amount available for purchasing units.
Commission Type (Default: Fixed) : Specifies how the commission is calculated:
Fixed ($) : A flat fee is deducted per installment (e.g., $3).
Percentage (%) : A percentage of the investment amount is deducted as commission (e.g., 3% of $1000 = $30). This setting affects the net amount invested and the overall cost of the SIP.
🎯 Dividends
Apply Tax On Dividends (Default: False) : When enabled, a tax is applied to dividends before they are reinvested or recorded. The tax rate is set via the Dividend Tax setting.
Dividend Tax (Default: 47) : The percentage of tax deducted from dividends if Apply Tax On Dividends is enabled (e.g., 47% tax reduces a $100 dividend to $53). This reduces the amount available for reinvestment or accumulation.
Reinvest Dividends After (Default: True, 2) : When enabled, dividends received are reinvested to purchase additional units after a specified period (e.g., 2 units of time, defined by Dividends Availability). If disabled, dividends are tracked but not reinvested. Reinvestment increases the total quantity and equity over time.
Dividends Availability (Default: Bars) : Defines the time unit for evaluating when dividends are available for reinvestment. Options include:
Bars : Based on the number of chart bars.
Weeks : Based on weeks.
Months : Based on months (approximated as 30.5 days). This setting determines the timing of dividend reinvestment relative to the Reinvest Dividends After period.
🎯 How Settings Interact
These settings work together to simulate a realistic SIP. For example, a $1000 recurring investment with a 3% commission and fractional quantities enabled will calculate the number of units purchased at the chosen price reference after deducting the commission. If dividends are reinvested after 2 months with a 47% tax, the script fetches dividend data, applies the tax, and adds the net dividend to the investment amount for that period. The Start Year and Timebound settings ensure the analysis aligns with the desired timeframe, while the Dividends Availability setting fine-tunes dividend reinvestment timing.
By adjusting these settings, users can model different SIP scenarios, compare performance across instruments in TradingView’s screener, and gain insights into how commissions, dividends, and price references impact long-term returns.
🎲 Using the script with Pine Screener
The main purpose of developing this script is to use it with Tradingview Pine Screener so that multiple ETFs/Funds can be compared.
In order to use this as a screener, the following things needs to be done.
Add SIP Evaluator and Screener to your favourites (Required for it to be added in pine screener)
Create a watch list containing required instruments to compare
Open pine screener from Tradingview main menu Products -> Screeners -> Pine or simply load the URL - www.tradingview.com
Select the watchlist created from Watchlist dropdown.
Chose the SIP Evaluator and Screener from the "Choose Indicator" dropdown
Set timeframe to 1 month and update settings as required.
Press scan to display collected data on the screener.
🎲 Use Case
This indicator is ideal for educational purposes, allowing users to experiment with SIP strategies across different instruments. It can be applied in TradingView’s screener to compare SIP performance for stocks, ETFs, or other assets, helping users understand how factors like commissions, dividends, and price references impact returns over time.
Rapid Ultimat Trading ZonesCRITICAL: The "Set It and Forget It" Timezone System
Have you ever had your session indicators become misaligned when London or New York changes clocks for Daylight Saving Time (DST)? This is a universal problem for traders, forcing you to manually adjust settings twice a year to avoid missing key trading windows. It’s confusing, frustrating, and can lead to costly mistakes.
The Rapid Ultimate Trading Zones indicator permanently solves this issue. We have engineered it with a powerful 'Set It and Forget It' timezone system that provides unmatched accuracy and peace of mind.
How It Works : Automatic DST Adjustment
Each Killzone and each Opening Range in this indicator has its own independent timezone setting. You simply match each session to its real-world location one time. From that moment on, the indicator handles everything automatically.
For the London Session: Set its timezone to Europe/London. The indicator will automatically handle the switch between GMT (winter) and BST (summer). You do not need to do anything.
For the New York Session: Set its timezone to America/New_York. The indicator will automatically handle the switch between EST (winter) and EDT (summer).
Once configured, your session timings will remain perfectly accurate forever. No more manual adjustments. No more confusion. Just precise, reliable session data, day in and day out.
Here is the complete user guide with the newly emphasized section integrated for your convenience.
Rapid Ultimate Trading Zones - User Guide
Created by Rapid Lodgements
1. Introduction: Your All-in-One Session & Levels Tool
Tired of manually marking out trading sessions and key levels every day? The Rapid Ultimate Trading Zones indicator is a comprehensive, institutional-grade tool designed to automatically visualize the most important price and time levels on your chart.
From London Killzone highs and lows to multiple, flexible Opening Ranges, this indicator provides a clean, automated, and fully customizable solution to help you focus on what matters most: your trading.
2. CRITICAL: The "Set It and Forget It" Timezone System
Have you ever had your session indicators become misaligned when London or New York changes clocks for Daylight Saving Time (DST)? This is a universal problem for traders, forcing you to manually adjust settings twice a year to avoid missing key trading windows. It’s confusing, frustrating, and can lead to costly mistakes.
The Rapid Ultimate Trading Zones indicator permanently solves this issue. We have engineered it with a powerful 'Set It and Forget It' timezone system that provides unmatched accuracy and peace of mind.
How It Works: Automatic DST Adjustment
Each Killzone and each Opening Range in this indicator has its own independent timezone setting. You simply match each session to its real-world location one time. From that moment on, the indicator handles everything automatically.
For the London Session: Set its timezone to Europe/London. The indicator will automatically handle the switch between GMT (winter) and BST (summer). You do not need to do anything.
For the New York Session: Set its timezone to America/New_York. The indicator will automatically handle the switch between EST (winter) and EDT (summer).
Once configured, your session timings will remain perfectly accurate forever. No more manual adjustments. No more confusion. Just precise, reliable session data, day in and day out.
3. Feature Breakdown
Killzones & Killzone Pivots
This is the core feature of the indicator. Killzones are specific, high-volume time windows for the major market sessions. The indicator will automatically draw a box around these times and mark their high and low price pivots.
Killzones Settings:
Enable/disable each session (Asia, London, NY AM, NY Lunch, NY PM) with the checkbox.
Customize the Session start and end times.
Crucially, set the Timezone for each session to its local market time.
Killzone Pivots Settings:
Labels & Colors: Customize the text label and color for each Killzone's high and low pivot lines. The color you choose here controls the color for the pivots and the session box.
Extend Pivots: Choose if the pivot lines should disappear after being touched (Until Mitigated) or continue to extend.
Alert Broken Pivots: Enable this to receive a TradingView alert whenever price breaks a recent Killzone high or low.
Show Midpoints: Optionally display the 50% level between a Killzone's high and low.
Flexible Opening Ranges (Up to 3 Instances)
This powerful feature allows you to track the initial price range of up to three different sessions independently.
Use Cases:
Track the first 15 minutes of the New York session with Opening Range 1.
Track the first hour of the London session with Opening Range 2.
Track the Asian session range with Opening Range 3.
Configuration (for each OR):
Enable OR: Toggle the specific range on or off.
Session Start-End: Defines the main session you are analyzing.
Timezone: Set the correct local timezone for the session you are tracking.
Range Minutes: The most important setting. Defines how long the opening range lasts (e.g., 15 for the first 15 minutes).
Extend OR lines right: Extends the high and low lines into the future.
Custom Lines & Timestamps
For marking your own specific levels and times that are independent of the Killzones.
Dedicated Timezone : This entire section is controlled by one separate timezone menu, which is set to GMT+0 by default. All times you enter here will be interpreted based on this setting.
Horizontal Lines (H-Line): Draws a horizontal line at the open price of the candle that occurs at your specified time. You get two independent lines.
Vertical Lines (V-Line): Draws a vertical line at the time you specify. You get two independent lines.
Daily, Weekly, Monthly (DWM) Levels
For a higher-timeframe perspective, this feature automatically plots:
Daily, Weekly, and Monthly Opening Prices.
Previous Day, Week, and Month Highs and Lows.
Vertical line separators for the start of each Day, Week, or Month.
4. General Settings
Session Drawing Limit: This is your master history control. It sets how many past days of drawings (for Killzones, Opening Ranges, etc.) will be kept on your chart. A lower number improves performance.
Timeframe Limit: To keep your chart clean, drawings will not appear on timeframes greater than or equal to the one you select here.
Label Size / Text Color: Controls the appearance of all text and labels drawn by the indicator.
TradeCrafted - Previous 10 Highs and LowsUnlock the power of historical price action with the 10-Day Highs & Lows Indicator! This innovative tool analyzes the highest and lowest price levels of the past 10 trading days and projects them as fixed lines onto the current session. By plotting these crucial support and resistance levels, traders gain a clear visual edge to anticipate market reactions, trend reversals, and breakout opportunities.
🔥 Key Features:
✅ Precision Levels – Automatically plots the previous 10 days' highs and lows for accurate decision-making.
✅ Fixed Lines for Clarity – Levels remain unchanged throughout the session, providing a stable reference.
✅ Enhanced Market Structure Analysis – Identify key zones where price is likely to react.
✅ Ideal for All Traders – Whether you're a scalper, swing trader, or intraday enthusiast, these levels offer a strong foundation for your strategy.
🚀 Why Use This Indicator?
Markets move in cycles, and historical highs and lows act as magnets for price action. By integrating this tool into your trading arsenal, you can spot potential breakouts, retests, and reversals with greater confidence!
Elevate your technical analysis and trade smarter with the 10-Day Highs & Lows Indicator! 🔥
How to use : Trader Can take Buy entry if price is near line and taking reversal from it so it will be very good for trader to manage the stop loss. Simply if it goes below the line, just cut the trade to avoid unnecessary and huge loss. This Indicator will help Trader to take correct entry and exit.
Hope my effort will help trader to stay in profit.
QQQ NQ NDX SPY SPX ES Price Convert Overlay
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QQQ NQ NDX SPY SPX ES Price Convert Overlay Indicator
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This 'Prices Overlay' indicator is a minimalist tool for traders who want to track and compare Nasdaq and S&P 500 instruments quickly and clearly, boosting efficiency and decision-making with minimal distraction.
How to Use It
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Add the indicator onto your TradingView chart.
Adjust your Right Margin in TradingView Settings > Canvas to show as much or as little of the line as you want, based on the "Price Buffer" indicator setting.
Select which instruments to overlay (e.g., QQQ, SPX).
Adjust levels, buffer, font, transparency, and update interval.
Features and Functions
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1. Automatic Ticker Detection:
The indicator identifies the ticker of your current chart (e.g., NQ, ES, SPY).
It then shows price levels for related instruments, eg:
On an NQ or MNQ chart, it can display QQQ or NDX levels.
On an ES or MES chart, it can display SPY or SPX levels.
...and vice versa
2. Adjustable Number of Levels
You can choose how many price levels to show, from 10 to 100.
This lets you decide how much detail you want based on your trading needs.
3. Visual Customization
Price Buffer: Move the lines and labels horizontally closer/further price action.
Font Size: Pick from "Tiny," "Small," or "Normal" for label text size.
Line Transparency: Adjust the opacity of the lines (0% = solid, 100% = invisible) to blend them with your chart.
4. Support for Micro Futures
Works with both regular futures (NQ, ES) and micro futures (MNQ, MES), perfect for traders using smaller contract sizes.
5. Update Frequency
Set how often the price levels refresh, from every 5 seconds to every 60 seconds.
This keeps the data current without slowing down your chart.
6. Accurate Price Conversion
Uses specific multipliers for each instrument (e.g., 100.0 for NDX and SPX, 1.0 for QQQ and SPY) to calculate and display price levels correctly.
Fetches real-time prices and converts them to match your chart’s scale.
Price conversions courtesy of PtGambler.
Benefits
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Easier Analysis: See how prices from different instruments line up on one chart—no need for multiple screens or math.
Customizable: Turn on/off instruments and tweak visuals to fit your trading style.
Time-Saving: Automates price conversions, letting you focus on trading decisions.
Thanks!
____________________
Thank you for your interest in my work. This is something I use every day for my trading and wanted to share it with the public. If you have any comments, bugs, or suggestions, please leave them here, or you can find me on Twitter or Discord.
@ ContrarianIRL
Open-source developer for over 25 years
M2 Liquidity Divergence ModelM2 Liquidity Divergence Model
The M2 Liquidity Divergence Model is a macro-aware visualization tool designed to compare shifts in global liquidity (M2) against the performance of a benchmark asset (default: Bitcoin). This script captures liquidity flows across major global economies and highlights whether price action is aligned ("Agreement") or diverging ("Divergence") from macro trends.
🔍 Core Features
M2 Global Liquidity Index (GLI):
Aggregates M2 money supply from major global economies, FX-adjusted, including extended contributors like India, Brazil, and South Africa. The slope of this composite is used to infer macro liquidity trends.
Lag Offset Control:
Allows the M2 signal to lead benchmark asset price by a configurable number of days (Lag Offset), useful for modeling the forward-looking nature of macro flows.
Gradient Macro Context (Background):
Displays a color-gradient background—aqua for expansionary liquidity, fuchsia for contraction—based on the slope and volatility of M2. This contextual backdrop helps users visually anchor price action within macro shifts.
Divergence Histogram (Optional):
Plots a histogram showing dynamic correlation or divergence between the liquidity index and the selected benchmark.
Agreement Mode: M2 and asset are moving together.
Divergence Mode: Highlights break in expected macro-asset alignment.
Adaptive Transparency Scaling:
Histogram and background gradients scale their visual intensity based on statistical deviation to emphasize stronger signals.
Toggle Options:
Show/hide the M2 Liquidity Index line.
Show/hide divergence histogram.
Enable/disable visual offset of M2 to benchmark.
🧠 Suggested Usage
Macro Positioning: Use the background context to align directional trades with macro liquidity flows.
Disagreement as Signal: Use divergence plots to identify when price moves against macro expectations—potential reversal or exhaustion zones.
Time-Based Alignment: Adjust Lag Offset to synchronize M2 signals with asset price behavior across different market conditions.
⚠️ Disclaimer
This indicator is designed for educational and analytical purposes only. It does not constitute financial advice or an investment recommendation. Always conduct your own research and consult a licensed financial advisor before making trading decisions.
Hidden Markov Model [Extension] | FractalystWhat's the indicator's purpose and functionality?
The Hidden Markov Model is specifically designed to integrate with the Quantify Trading Model framework, serving as a probabilistic market regime identification system for institutional trading analysis.
Hidden Markov Models are particularly well-suited for market regime detection because they can model the unobservable (hidden) state of the market, capture probabilistic transitions between different states, and account for observable market data that each state generates.
The indicator uses Hidden Markov Model mathematics to automatically detect distinct market regimes such as low-volatility bull markets, high-volatility bear markets, or range-bound consolidation periods.
This approach provides real-time regime probabilities without requiring optimization periods that can lead to overfitting, enabling systematic trading based on genuine probabilistic market structure.
How does this extension work with the Quantify Trading Model?
The Hidden Markov Model | Fractalyst serves as a probabilistic state estimation engine for systematic market analysis.
Instead of relying on traditional technical indicators, this system automatically identifies market regimes using forward algorithm implementation with three-state probability calculation (bullish/neutral/bearish), Viterbi decoding process for determining most likely regime sequence without repainting, online parameter learning with adaptive emission probabilities based on market observations, and multi-feature analysis combining normalized returns, volatility comprehensive regime assessment.
The indicator outputs regime probabilities and confidence levels that can be used for systematic trading decisions, portfolio allocation, or risk management protocols.
Why doesn't this use optimization periods like other indicators?
The Hidden Markov Model | Fractalyst deliberately avoids optimization periods to prevent overfitting bias that destroys out-of-sample performance.
The system uses a fixed mathematical framework based on Hidden Markov Model theory rather than optimized parameters, probabilistic state estimation using forward algorithm calculations that work across all market conditions, online learning methodology with adaptive parameter updates based on real-time market observations, and regime persistence modeling using fixed transition probabilities with 70% diagonal bias for realistic regime behavior.
This approach ensures the regime detection signals remain robust across different market cycles without the performance degradation typical of over-optimized traditional indicators.
Can this extension be used independently for discretionary trading?
No, the Hidden Markov Model | Fractalyst is specifically engineered for systematic implementation within institutional trading frameworks.
The indicator is designed to provide regime filtering for systematic trading algorithms and risk management systems, enable automated backtesting through mathematical regime identification without subjective interpretation, and support institutional-level analysis when combined with systematic entry/exit models.
Using this indicator independently would miss the primary value proposition of systematic regime-based strategy optimization that institutional frameworks provide.
How do I integrate this with the Quantify Trading Model?
Integration enables institutional-grade systematic trading through advanced machine learning and statistical validation:
- Add both HMM Extension and Quantify Trading Model to your chart
- Select HMM Extension as the bias source using input.source()
- Quantify automatically uses the extension's bias signals for entry/exit analysis
- The built-in machine learning algorithms score optimal entry and exit levels based on trend intensity, and market structure patterns identified by the extension
The extension handles all bias detection complexity while Quantify focuses on optimal trade timing, position sizing, and risk management along with PineConnector automation
What markets and assets does the indicator Extension work best on?
The Hidden Markov Model | Fractalyst performs optimally on markets with sufficient price movement since the system relies on statistical analysis of returns, volatility, and momentum patterns for regime identification.
Recommended asset classes include major forex pairs (EURUSD, GBPUSD, USDJPY) with high liquidity and clear regime transitions, stock index futures (ES, NQ, YM) providing consistent regime behavior patterns, individual equities (large-cap stocks with sufficient volatility for regime detection), cryptocurrency markets (BTC, ETH with pronounced regime characteristics), and commodity futures (GC, CL showing distinct market cycles and regime transitions).
These markets provide sufficient statistical variation in returns and volatility patterns, ensuring the HMM system's mathematical framework can effectively distinguish between bullish, neutral, and bearish regime states.
Any timeframe from 15-minute to daily charts provides sufficient data points for regime calculation, with higher timeframes (4H, Daily) typically showing more stable regime identification with fewer false transitions, while lower timeframes (30m, 1H) provide more responsive regime detection but may show increased noise.
Acceptable Timeframes and Portfolio Integration:
- Any timeframe that can be evaluated within Quantify Trading Model's backtesting engine is acceptable for live trading implementation.
Legal Disclaimers and Risk Acknowledgments
Trading Risk Disclosure
The HMM Extension is provided for informational, educational, and systematic bias detection purposes only and should not be construed as financial, investment, or trading advice. The extension provides institutional analysis but does not guarantee profitable outcomes, accurate bias predictions, or positive investment returns.
Trading systems utilizing bias detection algorithms carry substantial risks including but not limited to total capital loss, incorrect bias identification, market regime changes, and adverse conditions that may invalidate analysis. The extension's performance depends on accurate data, TradingView infrastructure stability, and proper integration with Quantify Trading Model, any of which may experience data errors, technical failures, or service interruptions that could affect bias detection accuracy.
System Dependency Acknowledgment
The extension requires continuous operation of multiple interconnected systems: TradingView charts and real-time data feeds, accurate reporting from exchanges, Quantify Trading Model integration, and stable platform connectivity. Any interruption or malfunction in these systems may result in incorrect bias signals, missed transitions, or unexpected analytical behavior.
Users acknowledge that neither Fractalyst nor the creator has control over third-party data providers, exchange reporting accuracy, or TradingView platform stability, and cannot guarantee data accuracy, service availability, or analytical performance. Market microstructure changes, reporting delays, exchange outages, and technical factors may significantly affect bias detection accuracy compared to theoretical or backtested performance.
Intellectual Property Protection
The HMM Extension, including all proprietary algorithms, classification methodologies, three-state bias detection systems, and integration protocols, constitutes the exclusive intellectual property of Fractalyst. Unauthorized reproduction, reverse engineering, modification, or commercial exploitation of these proprietary technologies is strictly prohibited and may result in legal action.
Liability Limitation
By utilizing this extension, users acknowledge and agree that they assume full responsibility and liability for all trading decisions, financial outcomes, and potential losses resulting from reliance on the extension's bias detection signals. Fractalyst shall not be liable for any unfavorable outcomes, financial losses, missed opportunities, or damages resulting from the development, use, malfunction, or performance of this extension.
Past performance of bias detection accuracy, classification effectiveness, or integration with Quantify Trading Model does not guarantee future results. Trading outcomes depend on numerous factors including market regime changes, pattern evolution, institutional behavior shifts, and proper system configuration, all of which are beyond the control of Fractalyst.
User Responsibility Statement
Users are solely responsible for understanding the risks associated with algorithmic bias detection, properly configuring system parameters, maintaining appropriate risk management protocols, and regularly monitoring extension performance. Users should thoroughly validate the extension's bias signals through comprehensive backtesting before live implementation and should never base trading decisions solely on automated bias detection.
This extension is designed to provide systematic institutional flow analysis but does not replace the need for proper market understanding, risk management discipline, and comprehensive trading methodology. Users should maintain active oversight of bias detection accuracy and be prepared to implement manual overrides when market conditions invalidate analysis assumptions.
Terms of Service Acceptance
Continued use of the HMM Extension constitutes acceptance of these terms, acknowledgment of associated risks, and agreement to respect all intellectual property protections. Users assume full responsibility for compliance with applicable laws and regulations governing automated trading system usage in their jurisdiction.
VWAP/VOL [Extension] | FractalystWhat's the indicator's purpose and functionality?
The VWAP/VOL Extension is designed specifically as a bias identification system for the Quantify Trading Model.
This extension uses volume-weighted average price analysis combined with institutional volume classification to automatically detect market bias without requiring optimization periods that lead to overfitting.
The system provides real-time bias signals (bullish/bearish/neutral) that integrate directly with Quantify's machine learning algorithms, enabling institutional-level backtesting and automated entry/exit identification based on genuine market structure rather than curve-fitted parameters.
How does this extension work with the Quantify Trading Model?
The VWAP/VOL Extension serves as the bias detection engine for Quantify's automated trading system.
Instead of manually selecting bias direction, this extension automatically identifies market bias using:
- Volume-weighted VWAP analysis with three-state detection (bullish/bearish/neutral)
- Institutional volume classification using relative volume thresholds without optimization
- Non-repainting architecture ensuring consistent bias signals for Quantify's machine learning
The extension outputs bias signals that Quantify uses as input through the `input.source()` function, allowing the Trading Model to focus on optimal entry/exit timing while the extension handles bias identification.
Why doesn't this use optimization periods like other indicators?
The VWAP/VOL Extension deliberately avoids optimization periods to prevent overfitting bias that destroys out-of-sample performance. The system uses:
- Fixed mathematical thresholds based on market structure principles rather than optimized parameters
- Relative volume analysis using standard 2.0x/0.5x ratios that work across all market conditions
- VWAP distance calculations based on percentage thresholds without curve-fitting
- Gap enforcement using fixed 5-bar minimums for disciplined bias detection
This approach ensures the bias signals remain robust across different market regimes without the performance degradation typical of over-optimized systems.
Can this extension be used independently for discretionary trading?
No, the VWAP/VOL Extension is specifically engineered to work as a component within the Quantify ecosystem. The extension is designed to:
- Provide bias input for Quantify's machine learning algorithms
- Enable automated backtesting through systematic bias identification
- Support institutional-level analysis when combined with Quantify's ML entry model
Using this extension independently would miss the primary value proposition of systematic entry/exit optimization that Quantify provides.
The extension handles bias detection so Quantify can focus on probability-based trade timing and risk management.
How does this enable institutional-level backtesting?
The extension transforms discretionary bias identification into systematic institutional analysis by:
- Eliminating subjective bias selection through automated VWAP/volume analysis
- Providing consistent historical signals with non-repainting architecture for accurate backtesting
- Integrating with Quantify's algorithms to identify optimal entry patterns based on objective bias states
- Enabling performance analysis across multiple market regimes without optimization bias
This combination allows Quantify to run institutional-grade backtests with consistent bias identification, generating reliable performance statistics and risk metrics that reflect genuine market edge rather than curve-fitted results.
How do I integrate this with the Quantify Trading Model?
Integration enables institutional-grade systematic trading through advanced machine learning and statistical validation:
- Add both VWAP/VOL Extension and Quantify Trading Model to your chart
- Select VWAP/VOL Extension as the bias source using input.source()
- Quantify automatically uses the extension's bias signals for entry/exit analysis
- The built-in machine learning algorithms score optimal entry and exit levels based on trend intensity, volume conviction, and market structure patterns identified by the extension
The extension handles all bias detection complexity while Quantify focuses on optimal trade timing, position sizing, and risk management along with PineConnector automation
What markets and assets does the VWAP/VOL Extension work best on?
The VWAP/VOL Extension performs optimally on markets with consistent, high-volume participation since the system relies on institutional volume analysis for bias detection. Futures markets provide the most reliable performance due to their centralized volume data and continuous institutional participation.
Recommended Futures Markets:
- ES (S&P 500 E-mini) - Over 2 million contracts daily volume, excellent liquidity depth
- NQ (NASDAQ-100 E-mini) - Around 600,000 contracts daily, strong tech sector representation
- YM (Dow Jones E-mini) - Consistent institutional flow and volume patterns
- RTY (Russell 2000 E-mini) - Small-cap exposure with reliable volume data
- GC (Gold Futures) - High volume commodity with institutional participation
- CL (Crude Oil Futures) - Energy sector representation with strong volume consistency
Why Futures Markets Excel:
- Futures markets provide centralized volume reporting, ensuring the extension's volume classification system receives accurate institutional participation data. The standardized contract specifications and continuous trading hours create consistent volume patterns that the extension's algorithms can analyze effectively.
Acceptable Timeframes and Portfolio Integration:
- Any timeframe that can be evaluated within Quantify Trading Model's backtesting engine is acceptable for live trading implementation.
The extension is specifically designed to integrate with Quantify's portfolio management system, allowing multiple strategies across different timeframes and assets to operate simultaneously while maintaining consistent bias identification methodology across the entire automated trading portfolio.
Legal Disclaimers and Risk Acknowledgments
Trading Risk Disclosure
The VWAP/VOL Extension is provided for informational, educational, and systematic bias detection purposes only and should not be construed as financial, investment, or trading advice. The extension provides volume-weighted institutional analysis but does not guarantee profitable outcomes, accurate bias predictions, or positive investment returns.
Trading systems utilizing bias detection algorithms carry substantial risks including but not limited to total capital loss, incorrect bias identification, market regime changes, and adverse conditions that may invalidate volume-based analysis. The extension's performance depends on accurate volume data, TradingView infrastructure stability, and proper integration with Quantify Trading Model, any of which may experience data errors, technical failures, or service interruptions that could affect bias detection accuracy.
System Dependency Acknowledgment
The extension requires continuous operation of multiple interconnected systems: TradingView charts and real-time data feeds, accurate volume reporting from exchanges, Quantify Trading Model integration, and stable platform connectivity. Any interruption or malfunction in these systems may result in incorrect bias signals, missed transitions, or unexpected analytical behavior.
Users acknowledge that neither Fractalyst nor the creator has control over third-party data providers, exchange volume reporting accuracy, or TradingView platform stability, and cannot guarantee data accuracy, service availability, or analytical performance. Market microstructure changes, volume reporting delays, exchange outages, and technical factors may significantly affect bias detection accuracy compared to theoretical or backtested performance.
Intellectual Property Protection
The VWAP/VOL Extension, including all proprietary algorithms, volume classification methodologies, three-state bias detection systems, and integration protocols, constitutes the exclusive intellectual property of Fractalyst. Unauthorized reproduction, reverse engineering, modification, or commercial exploitation of these proprietary technologies is strictly prohibited and may result in legal action.
Liability Limitation
By utilizing this extension, users acknowledge and agree that they assume full responsibility and liability for all trading decisions, financial outcomes, and potential losses resulting from reliance on the extension's bias detection signals. Fractalyst shall not be liable for any unfavorable outcomes, financial losses, missed opportunities, or damages resulting from the development, use, malfunction, or performance of this extension.
Past performance of bias detection accuracy, volume classification effectiveness, or integration with Quantify Trading Model does not guarantee future results. Trading outcomes depend on numerous factors including market regime changes, volume pattern evolution, institutional behavior shifts, and proper system configuration, all of which are beyond the control of Fractalyst.
User Responsibility Statement
Users are solely responsible for understanding the risks associated with algorithmic bias detection, properly configuring system parameters, maintaining appropriate risk management protocols, and regularly monitoring extension performance. Users should thoroughly validate the extension's bias signals through comprehensive backtesting before live implementation and should never base trading decisions solely on automated bias detection.
This extension is designed to provide systematic institutional flow analysis but does not replace the need for proper market understanding, risk management discipline, and comprehensive trading methodology. Users should maintain active oversight of bias detection accuracy and be prepared to implement manual overrides when market conditions invalidate volume-based analysis assumptions.
Terms of Service Acceptance
Continued use of the VWAP/VOL Extension constitutes acceptance of these terms, acknowledgment of associated risks, and agreement to respect all intellectual property protections. Users assume full responsibility for compliance with applicable laws and regulations governing automated trading system usage in their jurisdiction.
Intraweek Highs & Lows🔎 Track and analyze intraweek price extremes with full flexibility.
The indicator detects weekly highs or lows for any selected weekday and monitors when other days break those levels.
⚙️ Inputs
Select day
Pick which weekday’s extreme you want to monitor.
Find Low/High
Select whether you want to track Lows or Highs.
Use candle Wick/Body
Choose if extremes are calculated by full wick or candle body.
Cutoff date
Toggle the date-based filter and choose the starting date for event display.
MC Geopolitical Tension Events📌 Script Title: Geopolitical Tension Events
📖 Description:
This script highlights key geopolitical and military tension events from 1914 to 2024 that have historically impacted global markets.
It automatically plots vertical dashed lines and labels on the chart at the time of each major event. This allows traders and analysts to visually assess how markets have responded to global crises, wars, and significant political instability over time.
🧠 Use Cases:
Historical backtesting: Understand how market responded to past geopolitical shocks.
Contextual analysis: Add macro context to technical setups.
🗓️ List of Geopolitical Tension Events in the Script
Date Event Title Description
1914-07-28 WWI Begins Outbreak of World War I following the assassination of Archduke Franz Ferdinand.
1929-10-24 Wall Street Crash Black Thursday, the start of the 1929 stock market crash.
1939-09-01 WWII Begins Germany invades Poland, starting World War II.
1941-12-07 Pearl Harbor Japanese attack on Pearl Harbor; U.S. enters WWII.
1945-08-06 Hiroshima Bombing First atomic bomb dropped on Hiroshima by the U.S.
1950-06-25 Korean War Begins North Korea invades South Korea.
1962-10-16 Cuban Missile Crisis 13-day standoff between the U.S. and USSR over missiles in Cuba.
1973-10-06 Yom Kippur War Egypt and Syria launch surprise attack on Israel.
1979-11-04 Iran Hostage Crisis U.S. Embassy in Tehran seized; 52 hostages taken.
1990-08-02 Gulf War Begins Iraq invades Kuwait, triggering U.S. intervention.
2001-09-11 9/11 Attacks Coordinated terrorist attacks on the U.S.
2003-03-20 Iraq War Begins U.S.-led invasion of Iraq to remove Saddam Hussein.
2008-09-15 Lehman Collapse Bankruptcy of Lehman Brothers; peak of global financial crisis.
2014-03-01 Crimea Crisis Russia annexes Crimea from Ukraine.
2020-01-03 Soleimani Strike U.S. drone strike kills Iranian General Qasem Soleimani.
2022-02-24 Ukraine Invasion Russia launches full-scale invasion of Ukraine.
2023-10-07 Hamas-Israel War Hamas launches attack on Israel, sparking war in Gaza.
2024-01-12 Red Sea Crisis Houthis attack ships in Red Sea, prompting Western naval response.
Volume Profile Delta & DOM @MaxMaserati 2.0Volume Profile Delta & DOM @Maxserati 2.0- Real Order Flow Analysis
What this indicator actually does!!!
Most volume indicators just show you total volume - which honestly doesn't tell you much. This one breaks down WHO is driving that volume. Big difference between 1000 shares of balanced buying/selling versus 800 buy + 200 sell. This tool shows you exactly that breakdown at every price level.
Trading without this kind of data means you're basically trading blind. Price action is important, but without knowing if smart money is buying or selling, you're mostly guessing. This gives you the same view that institutional traders have.
The main components
**DOM Display**: Shows real-time order flow with separate columns for buying and selling volume at each price level. You can toggle any column on/off depending on what you actually use.
**Volume Delta**: This is the key part - it shows net buying pressure (buy volume minus sell volume) at each price. When you see heavy buying at a support level, that's usually a good sign. When you see heavy selling at resistance, different story.
**Understanding the key columns:**
- **VPS (Volume Profile Sell)**: Shows selling volume (bid volume) at each price level - how much selling pressure exists
- **VPB (Volume Profile Buy)**: Shows buying volume (ask volume) at each price level - how much buying pressure exists
- **VPD (Volume Profile Delta)**: The difference between VPB and VPS (buy volume minus sell volume) - this tells you who's winning the battle at each price
**Time & Sales**: Live trade data with timestamps. There are filters so you can ignore the small retail trades and focus on the size that actually moves markets.
**Recent Activity**: Tracks momentum by showing cumulative buying/selling above and below current price. Useful for seeing if institutions are accumulating or distributing.
Why volume analysis works
Professional traders don't just look at price. They look at volume because volume precedes price movement. When smart money starts accumulating a position, you'll see it in the volume before you see it in price.
Think about it - if a stock is at $100 and someone wants to buy 100,000 shares, they can't just market buy it all at once without moving the price. They'll spread it out, but you can still see the accumulation pattern if you know where to look.
Real trading applications
**For day trading**: This works well for timing entries. If you see price breaking a level but volume delta is negative, that's usually a fake breakout. If volume confirms the move, much higher probability trade.
**For swing positions**: Great for finding accumulation zones. When you see consistent buying volume at certain levels over multiple days, institutions are likely building positions there.
**Risk management**: Volume shifts often happen before price reversals. If you're long and suddenly see heavy selling volume while price is still going up, that's a good exit signal.
Multi-market setup
Works on stocks, futures, forex, and crypto. The indicator automatically detects what type of market you're trading and adjusts accordingly. For forex it uses tick volume since real volume isn't available. For crypto it handles the decimal precision properly.
Customization options
You can show or hide any column depending on your trading style. If you're just scalping, maybe you only need price and delta. If you're doing deeper analysis, turn on all the columns.
There's color customization since everyone has their preferences, and text sizing because not everyone trades on huge monitors.
The indicator has both real-time and backtesting modes. Real-time for live trading, backtesting for developing strategies with historical volume data.
Learning curve
Fair warning - this isn't a simple moving average. There's a learning curve to reading order flow properly. Start by watching how volume patterns develop around known support and resistance levels.
Pay attention to volume divergences. If price makes a new high but volume delta is weaker, that's often a warning sign. If price breaks down but there's no real selling volume, it might be a false breakdown.
Performance notes
This processes a lot of data in real-time, so disable any columns you don't actually use. The more features you enable, the more processing power it needs.
Works best on lower timeframes (1-15 minutes) where you can see the tick-by-tick order flow. Still useful on higher timeframes but less granular.
## Bottom line
If you're serious about trading and want to see what institutional money is doing instead of just guessing from price action alone, this will help. It's not magic - you still need to understand market structure and have a trading plan. But it gives you information that most retail traders don't have access to.
The goal is to stop trading against smart money and start trading with them. Volume tells you where they're active.
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*Works on all markets. Real volume for stocks/futures, tick volume for forex. Compatible with TradingView's replay feature for backtesting.*
TradingIQ - OrderFlow IQIntroducing “OrderFlow IQ”
OrderFlow IQ is an all-in-one order-flow and volume-profiling suite crafted to bring true market microstructure to your TradingView charts. It bundles footprints, per-bar and intra-bar delta analytics, class-based delta tracking, adaptive volume profiles, bubble-style trade tapes, live time-and-sales feeds, cumulative-volume fight meters, iceberg detection, and more—all driven by a single, user-friendly interface.
Features
The list below details an ever=expanding list of the indicators capabilities; more to come in the future!
Tick-based Footprints
Imbalance and stacked imbalance detection
Tick-based chronicled volume profile
Delta classification (small order, medium order, and block order delta)
Tick-based order flow bubble tape
Live order feed with total buying volume against total selling volume
Tick-based CVD
Iceberg order detection
Delta class lines
Tick-based bar statistics
Key Components and Their Functions
Data Granularity
• 1-Tick / 1-Second / 1-Minute modes let you choose the resolution of every calculation. On true tick charts you get genuine tick-by-tick precision; on second charts you see every intra-second print; on anything else it falls back to minute bars.
Footprint Engine
Bid vs Ask Volume Columns – Each candle is sliced into tick-level price rows showing buy-volume, sell-volume, total volume, delta and delta%.
CVD-Level Columns – Optionally color each row by net cumulative delta instead of raw volume to spotlight buying or selling pressure trends.
Imbalance Detection – Highlight rows where one side exceeds your % threshold, with “stacked” imbalances calling out multi-row alignment ahead of potential breaks.
Value Area & POC – Automatically compute and draw the 70% value area (VAH/VAL) and mark the Point of Control per session or any chosen timeframe.
Footprint
The image above shows the volume profiling data calculated for each row across the footprint engine.
Delta: Shows the net difference between buying and selling
Delta Percentage: Calculates delta as a percentage of total volume
Total Volume: The total volume at the price block
Buy Volume: The total buying volume at the price block
Sell Volume: The total selling volume at the price block
Additionally, you can select to only show buying volume and selling volume at each price block, as shown in the image above.
POC
The image above shows the visuals used to mark the POC of the footprint. The POC is marked yellow by default; the color can be changed in the settings.
Value Area
The image above shows the visuals used to mark the value area of the footprint.
Imbalance Detection
The image above shows the Footprint Engine detecting and marking buying/selling imbalances.
Stacked Imbalances
The image above shows the Footprint Engine detecting and marking stacked imbalances. Stacked imbalances are shown as consecutive, small blocks to the right of the footprint.
CVD Levels
The image above shows the footprint engine calculating CVD across the footprint, rather than net delta that resets bar by bar. Traders can enable the "Use CVD Levels" setting to have net delta persist across price bars, allowing traders to see the net CVD across various price blocks as the footprint develops.
Delta Class Statistics
With the inclusion of tick volume, The Delta Class Statistics component of the indicator classifies volume delta by order size to give traders detailed insights into whether small players are buying/selling and whether big players are buying/selling.
The image above shows a full view of the Delta Class Statistics feature.
The image above further explains the Delta Class Statistics view.
Orders are distributed (classified) across various order size amounts. From here, a rolling CVD is calculated across each order size. This feature gives traders detailed insights into whether big money is buying/selling (big player sentiment) and whether small money is buying/selling (small player sentiment).
Analysis
The image above shows a net-negative CVD for the session for both small orders (small money) and big orders (big money), while "medium" sized orders are currently at a net-positive CVD.
Consequently, sentiment for big players is bearish.
Additionally, small triangles are printed alongside each Delta Class box for each bar. You can hover over these labels with your cursor to see the net delta for the bar for each order size.
Bar Delta Statistics
With the inclusion of tick data, OrderFlow IQ is designed to generate detailed tick-based bar statistics for each candlestick.
The image above shows the feature in action.
Metrics
Volume: Total volume for the bar
Bar VWAP: The individual bar's VWAP
Delta: Net delta for the bar
Delta %: Delta % of the bar
Max Delta: The maximum positive delta achieved during the bar
Min Delta: The lowest negative delta achieved during the bar
CVD: Cumulative volume delta measurement by the bar
Buy Volume: Total buying volume for the bar
Sell Volume: Total selling volume for the bar
Iceberg Detection (Tick-Data Only)
An Iceberg Order is a type of large trading order that is broken up into much smaller visible portions. Only a small part of the order is displayed in the public order book at any given time, while the rest is hidden (like an iceberg where only the tip is above water).
Why are Iceberg Orders Important?
Minimizing Market Impact
If a trader were to post a 10,000-share sell order openly, the market would immediately react:
Buyers might panic, thinking there's a rush to sell.
Sellers could undercut the price aggressively.
This would likely drive the price down before the large order even finishes executing.
By revealing only a small portion at a time, Iceberg orders help avoid spooking the market and allow the trader to sell closer to the original price.
Hiding Trading Intentions
Markets are highly sensitive to order flow — the balance of buying and selling pressure.
If competitors, market makers, or algorithmic traders see a massive order, they might:
Front-run it (selling before it completes to profit from the expected price drop).
Reassess their own models about supply/demand imbalances.
Iceberg orders protect against this by masking true supply or demand.
Our Iceberg Detection Model
Using a proprietary iceberg order detection algorithm, OrderFlow IQ is capable of detecting/alerting iceberg orders when they occur.
The image above shows the Iceberg Detector in action.
When an iceberg order is identified, the size of the order in the quote currency, price of execution, and number of executions will be displayed.
It's important to set alerts for this feature, as iceberg orders aren't frequent and are easy to miss when away from the chart.
IQ Volume Profile (Chronicled Volume Profile)
OrderFlow IQ generates a Chronicled Volume Profile to give traders detailed insights into net delta by price level, but also historical net delta by price level.
The image above shows the feature in action. While the chronicled volume profile is seemingly a normal volume profile, the narrow-lines across the chronicle profile show historical min/max delta at each price level.
The image above exemplifies the feature.
The wide price blocks show the current net delta at each price area, while the small lines (with a circle at the end) show historical min/max delta at the price level.
This tool allows traders to see if buying/selling always dominated a price level, or if control of the price level changed hands between buyers/sellers throughout development of the profile.
Additionally, traders can hover over the small circles on the profile with their cursor to see the detailed delta statistics at each price area. The statistics will show the minimum delta at the price area, maximum delta, and the live change in delta.
Order Feed
OrderFlow IQ is capable of generating a live order feed with various metrics to assist real time orderflow traders in their analysis.
The image above exemplifies the feature.
Bid/Ask: The bid price and ask price of the current bar
Buys | Price: The size of a buy order and price of execution
Sells | Price: The size of a sell order and price of execution
▴ Vol: Cumulative buying volume (in quote currency) for the feed
▾ Vol: Cumulative selling volume (in quote currency) for the feed
Speed of tape: The average speed between each order fill
OrderFlow Bubble Tape
OrderFlow IQ also displays a traditional orderflow indicator, also known as OrderFlow Bubble Tape.
The image above shows the feature in action.
Orderflow Bubble Tape is a visual tool that shows recent market trades ("tape") as bubbles, where each bubble represents a trade.
The size of each bubble indicates the trade size (volume), and the color shows whether the trade was a buy (aggressive at the ask) or sell (aggressive at the bid).
Instead of showing trades as plain text (like a traditional tape), the bubble format makes it easier to spot bursts of aggressive buying or selling visually.
Clusters of large, fast bubbles in one color suggest momentum or imbalances in order flow, often signaling short-term price pressure.
Traders use Bubble Tape to quickly read supply/demand dynamics, identify hidden buyers/sellers (like iceberg orders), and anticipate short-term price moves.
Blue Bubble = Buy
Red Bubble = Sell
The larger the bubble, the larger the order. Traders can hover over each bubble with their cursor to see the exact size of the order.
Delta Class Lines
OrderFlow IQ shows Live Delta Class Lines grouped by order size buckets:
The blue line shows delta coming only from very large orders (100K–10B in size).
The red line shows delta coming from medium-large orders (50K–100K size).
The green line shows delta from small to medium orders (0–50K size).
Each line is the cumulative net delta for its class — meaning it is adding the buy and sell imbalances only from trades of that size class, live as trades occur.
For example, when a 30K-sized aggressive buy hits, it adds to the green line; if a 70K-sized sell hits, it subtracts from the red line.
The number next to each label is the current net delta value for that class, telling you whether buyers or sellers are dominating at that order size.
• Three Custom Dollar Brackets – Define “small,” “mid,” and “block” trade-size ranges (e.g., 0–50 K, 50 K–100 K, > 100 K).
• Live Streaming Lines – While a bar is forming, watch real-time totals for each bracket plotted as vertical columns or stair-step lines on the chart edge.
CVD
OrderFlow IQ also displays CVD as either candles or a line.
The image above shows the candles visualization for CVD. CVD can be calculated using tick data, 1-second bars, or 1-minute bars. The higher the granularity the more accurate the measurement.
More Features To Come
New features and calculations will be added to OrderFlow IQ based on community feedback, so feel free to share any requests you might have!
Summary
OrderFlow IQ brings a full suite of order-flow analytics into one Pine Script: footprints, delta analytics, dollar-bracket classes, adaptive profiles, bubble tapes, live feeds, CVD meters, and iceberg scans. Its unified Data Granularity switch and Preset System let you toggle entire dashboards with a click—scalpers, intraday traders, and long-term analysts alike can dial in the exact microstructure view they need without switching scripts. Publish once, share your preset layouts, and your TradingView community gains plug-and-play access to professional-grade order-flow tools—no extra installations or feeds required.
Deviation Trend Profile [BigBeluga]🔵 OVERVIEW
A statistical trend analysis tool that combines moving average dynamics with standard deviation zones and trend-specific price distribution.
This is an experimental indicator designed for educational and learning purposes only.
🔵 CONCEPTS
Trend Detection via SMA Slope: Detects trend shifts when the slope of the SMA exceeds a ±0.1 threshold.
Standard Deviation Zones: Calculates ±1, ±2, and ±3 levels from the SMA using ATR, forming dynamic envelopes around the mean.
Trend Distribution Profile: Builds a histogram that shows how often price closed within each deviation zone during the active trend phase.
🔵 FEATURES
Trend Signals: Immediate shift markers using colored circles at trend reversals.
SMA Gradient Coloring: The SMA line dynamically changes color based on its directional slope.
Trend Duration Label: A label above the histogram shows how many bars the current trend has lasted.
Trend Distribution Histogram: Visual bin-based profile showing frequency of price closes within deviation bands during trend lookback period.
Adjustable Bin Count: Set the granularity of the distribution using the “Bins Amount” input.
Deviation Labels and Zones: Clearly marked ±1, ±2, ±3 lines with consistent color scheme.
Trend Strength Insight:
• Wide profile skewed to ±2/3 = strong directional trend.
• Profile clustered near SMA = potential trend exhaustion or range.
🔵 HOW TO USE
Use trend shift dots as entry signals:
• 🔵 = Bullish start
• 🔴 = Bearish start
Trade with the trend when price clusters in outer zones (±2 or ±3).
Be cautious or fade the trend when price distribution contracts toward the SMA.
View across multiple timeframes for trend confluence or divergence.
🔵 CONCLUSION
Deviation Trend Profile visualizes how price distributes during trends relative to statistical deviation zones.
It’s a powerful confluence tool for identifying strength, exhaustion, and the rhythm of price behavior—ideal for swing traders and volatility analysts alike.
Luma DCA Simulator (BTC only)Luma DCA Simulator – Guide
What is the Luma DCA Simulator?
The Luma DCA Tracker shows how regular Bitcoin investments (Dollar Cost Averaging) would have developed over a freely selectable period – directly in the chart, transparent and easy to follow.
Settings Overview
1. Investment amount per interval
Specifies how much capital is invested at each purchase (e.g. 100).
2. Start date
Defines the point in time from which the simulation begins – e.g. 01.01.2020.
3. Investment interval
Determines how frequently investments are made:
– Daily
– Weekly
– Every 14 days
– Monthly
4. Language
Switches the info box display between English and German.
5. Show investment data (optional)
If activated, the chart will display additional values such as total invested capital, BTC amount, current value, and profit/loss.
What the Chart Displays
Entry points: Each DCA purchase is marked as a point in the price chart.
Average entry price: An orange line visualizes the evolving DCA average.
Info box (bottom left) with a live summary of:
– Total invested capital
– Total BTC acquired
– Average entry price
– Current portfolio value
– Profit/loss in absolute terms and percentage
Note on Accuracy
This simulation is for illustrative purposes only.
Spreads, slippage, fees, and tax effects are not included.
Actual results may vary.
Technical Note
For daily or weekly intervals, the chart timeframe should be set to 1 day or lower to ensure all purchases are accurately included.
Larger timeframes (e.g. weekly or monthly charts) may result in missed investments.
Currency Handling
All calculations are based on the selected chart symbol (e.g. BTCUSD, BTCEUR, BTCUSDT).
The displayed currency is automatically determined by the chart used.
Adaptive Multi-MA OptimizerAdaptive Multi-MA Optimizer
This indicator provides a powerful, customizable solution for traders seeking dynamically optimized moving averages with precision and control. It integrates multiple custom-built moving average types, applies real-time volatility-based optimization, and includes an optional composite smoothing engine.
🧠 Key Features
Dynamic Optimization:
Automatically selects the optimal lookback length based on market volatility stability using a custom standard deviation differential model.
Multiple Custom MA Types:
Includes fully custom implementations of:
SMA (Simple Moving Average)
EMA (Exponential Moving Average)
WMA (Weighted Moving Average)
VWMA (Volume Weighted MA)
DEMA (Double EMA)
TEMA (Triple EMA)
Hull MA
ALMA (Arnaud Legoux MA)
Composite MA Option:
A unique "Composite" mode blends all supported MAs into a single average, then applies optional smoothing for enhanced signal clarity.
Dynamic Smoothing:
The composite mode supports volatility-adjusted smoothing (based on optimized lookback), making it adaptable to different market regimes.
Fully Custom Logic:
No built-in MA functions are used — every moving average is hand-coded for transparency and educational value.
⚙️ How It Works
Optimization:
The script evaluates a range of lengths (minLen to maxLen) using the standard deviation of price returns. It selects the length with the most stable recent volatility profile.
Calculation:
The selected MA type is calculated using that optimized length. If "Composite" is chosen, all MA types are averaged and smoothed dynamically.
Visualization:
The adaptive MA is plotted on the chart, changing color based on its position relative to price.
📌 Use Cases
Trend-following strategies that adapt to different market conditions.
Traders wanting a high-fidelity composite of multiple MAs.
Analysts interested in visualizing market smoothness without lag-heavy signals.
Coders looking to learn how to build custom indicators from scratch.
🧪 Inputs
MA Type: Choose from 8 MA types or a blended Composite.
Lookback Range: Control min/max and step size for optimization.
Source: Choose any price series (e.g., close, hl2).
⚠️ Disclaimer
This indicator is for educational and informational purposes only and does not constitute financial advice, trading advice, or investment recommendations. Use of this script is at your own risk. Past performance does not guarantee future results. Always perform your own analysis and consult with a qualified financial advisor before making trading decisions.
Adaptive Normalized Global Liquidity OscillatorAdaptive Normalized Global Liquidity Oscillator
A dynamic, non-repainting oscillator built on real central bank balance sheet data. This tool visualizes global liquidity shifts by aggregating monetary asset flows from the world’s most influential central banks.
🔍 What This Script Does:
Aggregates Global Liquidity:
Includes Federal Reserve (FED) assets and subtracts liabilities like the Treasury General Account (TGA) and Reverse Repo Facility (RRP), combined with asset positions from the ECB, BOJ, PBC, BOE, and over 10 other central banks. All data is normalized into USD using FX rates.
Adaptive Normalization:
Optimizes the lookback period dynamically based on rate-of-change stability—no fixed lengths, enabling adaptation across macro conditions.
Self-Optimizing Weighting:
Applies inverse standard deviation to balance raw liquidity, smoothed momentum (HMA), and standardized deviation from the mean.
Percentile-Ranked Highlights:
Liquidity readings are ranked relative to history—extremes are visually emphasized using gradient color and adaptive transparency.
Non-Repainting Design:
Data is anchored with bar index awareness and offset techniques, ensuring no forward-looking bias. What you see is what was known at that time.
⚠️ Important Interpretation Note:
This is not a zero-centered oscillator like RSI or MACD. The signal line does not represent neutrality at zero.
Instead, a dynamic baseline is calculated using a rolling mean of scaled liquidity.
0 is irrelevant on its own—true directional signals come from crosses above or below this adaptive baseline.
Even negative values may signal strength if they are rising above the moving average of past liquidity conditions.
✅ What to Watch For:
Crossover Above Dynamic Baseline:
Indicates liquidity is expanding relative to recent conditions—supports a risk-on interpretation.
Crossover Below Dynamic Baseline:
Suggests deteriorating liquidity conditions—may align with risk-off shifts.
Percentile Extremes:
Readings near the top or bottom historical percentiles can act as contrarian or confirmation signals, depending on momentum.
⚙️ How It Works:
Bounded Normalization:
The final oscillator is passed through a tanh function, keeping values within and reducing distortion.
Adaptive Transparency:
The strength of deviations dynamically adjusts plot intensity—visually highlighting stronger liquidity shifts.
Fully Customizable:
Toggle which banks are included, adjust dynamic optimization ranges, and control visual display options for plot and background layers.
🧠 How to Use:
Trend Confirmation:
Sustained rises in the oscillator above baseline suggest underlying monetary support for asset prices.
Macro Turning Points:
Reversals or divergences, especially near OB/OS zones, can foreshadow broader risk regime changes.
Visual Context:
Use the dynamic baseline to see if liquidity is supportive or suppressive relative to its own adaptive history.
📌 Disclaimer:
This indicator is for educational and informational purposes only. It does not constitute financial advice. Past performance is not indicative of future results. Always consult a qualified financial advisor before making trading or investment decisions.
Luma DCA Tracker (BTC)Luma DCA Tracker (BTC) – User Guide
Function
This indicator simulates a regular Bitcoin investment strategy (Dollar Cost Averaging). It calculates and visualizes:
Accumulated BTC amount
Average entry price
Total amount invested
Current portfolio value
Profit/loss in absolute and percentage terms
Settings
Investment per interval
Fixed amount to be invested at each interval (e.g., 100 USD)
Start date
The date when DCA simulation begins
Investment interval
Choose between:
daily, weekly, every 14 days, or monthly
Show investment data
Displays additional chart lines (total invested, value, profit, etc.)
Chart Elements
Orange line: Average DCA entry price
Grey dots: Entry points based on selected interval
Info box (bottom left): Live summary of all key values
Notes
Purchases are simulated at the closing price of each interval
No fees, slippage, or taxes are included
The indicator is a simulation only and not linked to an actual portfolio
GCM Price Based ColorIndicator Name:
GCM Price Based Color Indicator
Detailed Description:
The GCM Price Based Color Indicator is a unique tool designed to help traders spot potential "pump" events in the market. Unlike traditional Volume Rate of Change (VROC) indicators, this script is conditional: it calculates a VROC value only when both the average volume and the price are increasing. This focus helps filter out volume surges that don't accompany immediate price appreciation, highlighting more relevant "pump" signals.
Key Features & Calculation Logic:
Conditional Volume Rate of Change (VROC):
It first calculates a Simple Moving Average (SMA) of the volume over a user-defined length (lookback period).
It then checks two conditions:
Is the current SMA volume greater than the previous bar's SMA volume (i.e., volumeIncreasing)?
Is the current close price greater than the previous bar's close price (i.e., valueIncreasing)?
Only if both volume Increasing AND value Increasing are true, a VROC value is calculated as (current _ MA _ volume - previous _ MA _ volume) * (100 / previous _ MA _ volume). Otherwise, the VROC for that bar is 0.
Historical Normalization:
The raw VROC value is then normalized against its own historical maximum value observed since the indicator was applied. This scaling brings all VROC values into a common 0-100 range.
Why is this important? Normalization makes the indicator's readings comparable across different assets (e.g., high-volume vs. low-volume stocks/cryptos) and different timeframes, making it easier to interpret the strength of a "pump" relative to its own past.
Dynamic Plot Color (Price-Based):
The plot line's color itself provides an immediate visual cue about the current bar's price action:
Green: close is greater than close (price is up for the current bar).
Red: close is less than close (price is down for the current bar).
Grey: close is equal to close (price is flat for the current bar).
Important Note: The plot color reflects the price movement of the current bar, not the magnitude of the VROC Normalized value itself. This means you can have a high vrocNormalized value (indicating a strong conditional volume surge) but a red plot color if the very next bar's price closes lower, providing a multi-faceted view.
Thresholds & Alerts:
Two horizontal lines (small Pump Threshold and big Pump Threshold) are plotted to visually mark significant levels of normalized pump strength.
Customizable alerts can be set up to notify you when VROC Normalized reaches or exceeds these thresholds, helping you catch potential pump events in real-time.
How to Use It:
Identify Potential Pumps: Look for upward spikes in the VROC Normalized line. Higher spikes indicate stronger pump signals (i.e., a larger increase in average volume coinciding with an increasing price).
Monitor Thresholds: Pay attention when the VROC Normalized line crosses above your small Pump Threshold or big Pump Threshold. These are configurable levels to suit different assets and trading styles.
Observe Plot Color: The line color provides crucial context. A high VROC Normalized (strong pump signal) with a green line indicates current price momentum is still positive. If VROC Normalized is high but the line turns red, it might suggest the initial pump is losing steam or experiencing a pullback.
Combine with Other Tools: This indicator is best used in conjunction with other technical analysis tools (e.g., support/resistance, trend lines, other momentum indicators) for confirmation and a more holistic trading strategy.
Indicator Inputs:
Lookback period (1 - 4999) (default: 420): This length determines the period for the Simple Moving Average (SMA) of volume. A higher value will smooth the volume average more, reacting slower, while a lower value will make it more reactive. Adjust based on the timeframe and asset volatility.
Big Pump Threshold (0.01 - 99.99) (default: 10.0): The normalized VROC Normalized level that signifies a "Big Pump." When VROC Normalized reaches or exceeds this level, an alert can be triggered.
Small Pump Threshold (0.01 - 99.99) (default: 0.5): The normalized VROC Normalized level that signifies a "Small Pump." This is a lower threshold for earlier or less significant pump activity.
Alerts:
Small Pump: Triggers when VROC Normalized crosses above or equals the small Pump Threshold.
Big Pump: Triggers when VROC Normalized crosses above or equals the big Pump Threshold.
Best Practices & Considerations:
Timeframes: The indicator can be used on various timeframes, but its effectiveness may vary. Experiment to find what works best for your chosen asset and trading style.
Volatility: Highly volatile assets might require different threshold settings compared to less volatile ones.
Lag: Due to the use of a Simple Moving Average (SMA) for volume, there will be some inherent lag in the calculation.
Normalization Start: The historic Max for normalization starts with a default value of 10.0. For the very first bars, or if there hasn't been a significant VROC yet, the VROC Normalized might behave differently until a true historical maximum VROC establishes itself.
Not Financial Advice: This indicator is a tool for analysis and does not constitute financial advice. Always perform your own research and manage your risk.
Adaptive Signal Oscillator (ASO)📘 Adaptive Signal Oscillator (ASO)
A fully dynamic, self-calibrating oscillator that adapts to any asset or timeframe by optimizing for real-time signal stability and volatility structure — without relying on static parameters or hardcoded thresholds.
🔍 Overview
The Adaptive Signal Oscillator (ASO) is a next-generation technical analysis tool designed to provide context-aware long/short signals across crypto, equities, or forex markets. Unlike traditional oscillators (RSI, Stochastics, MACD), ASO requires no manual tuning of lookback periods or overbought/oversold zones — it self-optimizes based on current market behavior.
🧠 How It Works
✅ 1. Dynamic Lookback Optimization
ASO evaluates a range of lookback lengths between user-defined minLen and maxLen. For each length, it calculates the standard deviation of returns and finds the one with the least volatility change (i.e., the most stable structure). This length is dynamically assigned as bestLen, recalculated on every bar.
✅ 2. Multi-Layer Signal Composition
Four independent signal layers are computed using bestLen:
RSI Layer: Measures relative price strength via a custom dynamic RSI.
Z-Score Layer: Standardized deviation of price from its mean.
Volatility Layer: Standard deviation of log or percent returns.
Price Position Layer: Current price percentile within the lookback window.
Each of these layers is transformed into a percentile score scaled to the range .
✅ 3. Volatility-Based Weighting
The standard deviation (volatility) of each signal layer is computed. Less volatile layers are weighted more heavily, ensuring the final composite signal prioritizes stable, consistent inputs.
Weights are normalized and combined to form a composite score, representing a dynamically blended, noise-weighted signal across the four layers.
✅ 4. Optional Adaptive Smoothing
A boolean toggle lets users apply smoothing to the final score. The smoothing window scales proportionally to bestLen, preserving adaptiveness even during trend transitions.
✅ 5. Percentile-Based Thresholding
Rather than using arbitrary fixed thresholds, ASO converts the composite score into a ranked percentile. Long/short signals are then generated based on user-defined percentile bands, adapting naturally to each asset’s behavior.
📈 Interpreting ASO
Score > Threshold → Strong long signal (highlighted in aqua).
Score < Threshold → Strong short signal (highlighted in fuchsia).
Crossing h_thresh (e.g., 0) → Neutral-to-bias change; useful for early trend cues.
The background and label update in real time to reflect the current regime and bestLen.
⚙️ Inputs
minLen, maxLen, step: Define the search range for optimal lookback length.
retMethod: Choose between log or percent return calculations.
threshHigh, threshLow: Define signal zones using percentiles.
smooth: Enable dynamic score smoothing.
h_thresh: Midline crossover zone for directional context.
⚠️ Disclaimer
This tool is designed for exploratory and educational purposes only. It does not offer financial advice or trading recommendations. Past performance is not indicative of future results.
Always consult a licensed financial advisor before making investment decisions.
Flux Capacitor (FC)# Flux Capacitor
**A volume-weighted, outlier-resistant momentum oscillator designed to expose hidden directional pressure from institutional participants.**
---
### Why "Flux Capacitor"?
The name pays homage to the fictional energy core in *Back to the Future* — an invisible engine that powers movement. Similarly, this indicator detects whether price movement is being powered by real market participation (volume) or if it's coasting without conviction.
---
### Methodology
The Flux Capacitor fuses three statistical layers:
- **Normalized Momentum**: `(Close – Open) / ATR`
Controls for raw price size and volatility.
- **Volume Scaling**:
Amplifies the effect of price moves that occur with elevated volume.
- **Robust Normalization**:
- *Winsorization* caps outlier spikes.
- *MAD-Z scoring* normalizes the signal across assets (crypto, futures, stocks).
- This produces consistent scaling across timeframes and symbols.
The result is a smooth oscillator that reliably indicates **liquidity-backed momentum** — not just price movement.
---
### Signal Events
- **Divergence (D)**: Price makes higher highs or lower lows, but Flux does not.
- **Absorption (A)**: Candle shows high volume and small body, while Flux opposes the candle direction — indicates smart money stepping in.
- **Compression (◆)**: High volume with low momentum — potential breakout zone.
- **Zero-Cross**: Indicates directional regime flip.
- **Flux Acceleration**: Histogram shows pressure rate of change.
- **Regime Background**: Color fades with weakening trend conviction.
All signals are color-coded and visually compact for easy pattern recognition.
---
### Interpreting Divergence & Absorption Correctly
Signal strength improves significantly when it appears **in the correct zone**:
#### Divergence:
| Signal | Zone | Meaning | Strength |
|--------|------------|------------------------------------------|--------------|
| Green D | Below 0 | Bullish reversal forming in weakness | **Strong** |
| Green D | Above 0 | Bullish, but less convincing | Moderate |
| Red D | Above 0 | Bearish reversal forming in strength | **Strong** |
| Red D | Below 0 | Bearish continuation — low warning value | Weak |
#### Absorption:
| Signal | Zone | Meaning | Strength |
|--------|------------|-----------------------------------------|--------------|
| Green A | Below 0 | Buyers absorbing panic-selling | **Strong** |
| Green A | Above 0 | Support continuation | Moderate |
| Red A | Above 0 | Sellers absorbing FOMO buying | **Strong** |
| Red A | Below 0 | Trend continuation — not actionable | Weak |
Look for **absorption or divergence signals in “enemy territory”** for the most actionable entries.
---
### Reducing Visual Footprint
If your chart shows a long line of numbers across the top of the Flux Capacitor pane (e.g. "FC 14 20 9 ... Bottom Right"), it’s due to TradingView’s *status line input display*.
**To fix this**:
Right-click the indicator pane → **Settings** → **Status Line** tab → uncheck “Show Indicator Arguments”.
This frees up vertical space so top-edge signals (like red `D` or yellow `◆`) remain visible and unobstructed.
---
### Features
- Original MAD-Z based momentum design
- True volume-based divergence and absorption logic
- Built-in alerts for all signal types
- Works across timeframes (1-min to weekly)
- Minimalist, responsive layout
- 25+ customizable parameters
- No future leaks, no repainting
---
### Usage Scenarios
- **Trend confirmation**: Flux > 0 confirms bullish trend strength
- **Reversal detection**: Divergence or absorption in opposite territory = high-probability reversal
- **Breakout anticipation**: Compression signal inside range often precedes directional move
- **Momentum shifts**: Watch for zero-crosses + flux acceleration spikes
---
### ⚠ Visual Note for BTC, ETH, Crude Oil & Futures
These high-priced or rapidly accelerating instruments can visually compress any linear oscillator. You may notice the Flux Capacitor’s line appears "flat" or muted on these assets — especially over long lookbacks.
> **This does not affect signal validity.** Divergence, absorption, and compression triggers still fire based on underlying logic — only the line’s amplitude appears reduced due to scaling constraints.
---
### Disclaimer
This indicator is for educational purposes only. It is not trading advice. Past results do not guarantee future performance. Use in combination with your own risk management and analysis.
Multi-Period Performance TableHello friends,
I'm returning to the fascinating world of TradingView publications. Over time, I've accumulated many unpublished ideas — both open- and closed-source — that I now plan to share, alternating between the two. It felt like a shame to let so much valuable work remain unseen. The story isn't over yet — so today, we kick off a new series of invite-only scripts, starting with this indicator.
🛠️ How It Works
The script analyzes your selected number of years of price data, calculating returns for each month, quarter, and season
Advanced algorithms compute comprehensive statistics, including the mean, median, standard deviation, and extremes for each period
Data is presented in an intuitive table with optional heatmap coloring that makes patterns immediately stand out
Sorting of any column allows you to quickly identify the best and worst performing periods
🔥 Key Features
Pine Script V6 – leverages the latest version for better performance
Custom number of years to aggregate statistics
Complete breakdown for all 12 months (Jan-Dec)
Quarter (Q1, Q2, Q3, Q4) statistics
Season (Winter, Spring, Summer, Fall) statistics
Year/Year-to-Date (YTD) statistics
Enable/disable Right-side statistics for each row
Enable/disable Bottom statistics for each column
Heatmap mode with 10 palettes
Sortable columns
Customizable table
Optimized performance - efficient calculations for smooth operation
Universal compatibility – runs smoothly across all assets, timeframes, and market conditions — from euphoric peaks to capitulation lows
📸 Visual Examples
Monthly view
Quarterly view
Seasonal view
Clean table mode - without heatmaps
Default heatmap palette
June column sorted in descending order to quickly identify best/worst years
Turbo palette - high contrast
Spectral palette - professional look
Red/Yellow/Blue palette - classic style
My similar indicators that are also worth paying attention to
Still here? Unlock the full potential of multi-period market analysis — and take your trading to the next level today! 🚀
👋Good luck!
Normalized Volume & True RangeThis indicator solves a fundamental challenge that traders face when trying to analyze volume and volatility together on their charts. Traditionally, volume and price volatility exist on completely different scales, making direct comparison nearly impossible. Volume might range from thousands to millions of shares, while volatility percentages typically stay within single digits. This indicator brings both measurements onto a unified scale from 0 to 100 percent, allowing you to see their relationship clearly for the first time.
The core innovation lies in the normalization process, which automatically calculates appropriate scaling factors for both volume and volatility based on their historical statistical properties. Rather than using arbitrary fixed scales that might work for one stock but fail for another, this system adapts to each instrument's unique characteristics. The indicator establishes baseline averages for both measurements and then uses statistical analysis to determine reasonable maximum values, ensuring that extreme outliers don't distort the overall picture.
You can choose from three different volatility calculation methods depending on your analytical preferences. The "Body" option measures the distance between opening and closing prices, focusing on the actual trading range that matters most for price action. The "High/Low" method captures the full daily range including wicks and shadows, giving you a complete picture of intraday volatility. The "Close/Close" approach compares consecutive closing prices, which can be particularly useful for identifying gaps and overnight price movements.
The indicator displays volume as colored columns that match your candlestick colors, making it intuitive to see whether high volume occurred during up moves or down moves. Volatility appears as a gray histogram, providing a clean background reference that doesn't interfere with volume interpretation. Both measurements are clipped at 100 percent, which represents their calculated maximum normal values, so any readings near this level indicate unusually high activity in either volume or volatility.
The baseline reference line shows you what "normal" volume looks like for the current instrument, helping you quickly identify when trading activity is above or below average. Optional moving averages for both volume and volatility are available if you prefer smoothed trend analysis over raw daily values. The entire system updates in real-time as new data arrives, continuously refining its statistical calculations to maintain accuracy as market conditions evolve.
This two-in-one indicator provides a straightforward way to examine how price movements relate to trading volume by presenting both measurements on the same normalized scale, making it easier to spot patterns and relationships that might otherwise remain hidden when analyzing these metrics separately.
Technical Strength Index (TSI)📘 TSI with Dynamic Bands – Technical Strength Index
The TSI with Dynamic Bands is a multi-factor indicator designed to measure the statistical strength and structure of a trend. It combines several quantitative metrics into a single, normalized score between 0 and 1, allowing traders to assess the technical quality of market moves and detect overbought/oversold conditions with adaptive precision.
🧠 Core Components
This indicator draws from the StatMetrics library, blending:
📈 Trend Persistence: via the Hurst exponent, indicating whether price action is mean-reverting or trending.
📉 Risk-Adjusted Volatility: via the inverted , rewarding smoother, less erratic price movement.
🚀 Momentum Strength: using a combination of directional momentum and Z-score–normalized returns.
These components are normalized and averaged into the TSI line.
🎯 Features
TSI Line: Composite score of trend quality (0 = weak/noise, 1 = strong/structured).
Dynamic Bands: Mean ± 1 standard deviation envelopes provide adaptive context.
Overbought/Oversold Detection: Based on a rolling quantile (e.g. 90th/10th percentile of TSI history).
Signal Strength Bar (optional): Measures how statistically extreme the current TSI value is, helping validate confidence in trade setups.
Dynamic Color Cues: Background and bar gradients help visually identify statistically significant zones.
📈 How to Use
Look for overbought (red background) or oversold (green background) conditions as potential reversal zones.
Confirm trend strength with the optional signal strength bar — stronger values suggest higher signal confidence.
Use the TSI line and context bands to filter out noisy ranges and focus on structured price moves.
⚙️ Inputs
Lookback Period: Controls the smoothing and window size for statistical calculations.
Overbought/Oversold Quantiles: Adjust the thresholds for signal zones.
Plot Signal Strength: Enable or disable the signal confidence bar.
Overlay Signal Strength: Show signal strength in the same panel (compact) or not (cleaner TSI-only view).
🛠 Example Use Cases
Mean reversion traders identifying reversal zones with statistical backing
Momentum/Trend traders confirming structure before entries
Quantitative dashboards or multi-asset screening tools
⚠️ Disclaimer
This script is for educational and informational purposes only. It does not constitute financial advice or a recommendation to buy or sell any financial instrument.
This AI is not a financial advisor; please consult your financial advisor for personalized advice.
