Amihud Illiquidity Ratio [MarkitTick]💡This indicator implements the Amihud Illiquidity Ratio, a financial metric designed to measure the price impact of trading volume. It assesses the relationship between absolute price returns and the volume required to generate that return, providing traders with insight into the "stress" levels of the market liquidity.
Concept and Originality
Standard volume indicators often look at volume in isolation. This script differentiates itself by contextualizing volume against price movement. It answers the question: "How much did the price move per unit of volume?" Furthermore, unlike static indicators, this implementation utilizes dynamic percentile zones (Linear Interpolation) to adapt to the changing volatility profile of the specific asset you are viewing.
Methodology
The calculation proceeds in three distinct steps:
1. Daily Return: The script calculates the absolute percentage change of the closing price relative to the previous close.
2. Raw Ratio: The absolute return is divided by the volume. I have introduced a standard scaling factor (1,000,000) to the calculation. This resolves the issue of the values being astronomically small (displayed as roughly 0) without altering the fundamental logic of the Amihud ratio (Absolute Return / Volume).
- High Ratio: Indicates that price is moving significantly on low volume (Illiquid/Thin Order Book).
- Low Ratio: Indicates that price requires massive volume to move (Liquid/Deep Order Book).
3. Dynamic Regimes: The script calculates the 75th and 25th percentiles of the ratio over a lookback period. This creates adaptive bands that define "High Stress" and "Liquid" zones relative to recent history.
How to Use
Traders can use this tool to identify market fragility:
- High Stress Zone (Red Background): When the indicator crosses above the 75th percentile, the market is in a High Illiquidity Regime. Price is slipping easily. This is often observed during panic selling or volatile tops where the order book is thin.
- Liquid Zone (Green Background): When the indicator drops below the 25th percentile, the market is in a Liquid Regime. The market is absorbing volume well, which is often characteristic of stable trends or accumulation phases.
- Dashboard: A visual table on the chart displays the current Amihud Ratio and the active Market Regime (High Stress, Normal, or Liquid).
Inputs
- Calculation Period: The lookback length for the average illiquidity (Default: 20).
- Smoothing Period: The length of the additional moving average to smooth out noise (Default: 5).
- Show Quant Dashboard: Toggles the visibility of the on-screen information table.
● How to read this chart
• Spike in Illiquidity (Red Zones)
Price is moving on "thin air." Expect high volatility or potential reversals.
• Low Illiquidity (Green/Stable Zones)
The market is deep and liquid. Trends here are more sustainable and reliable.
• Divergence
Watch for price making new highs while liquidity is drying up—a classic sign of an exhausted trend.
Example:
● Chart Overview
The chart displays the Amihud Illiquidity indicator applied to a Gold (XAUUSD) 4-hour timeframe.
Top Pane: Price action with manual text annotations highlighting market reversals relative to liquidity zones.
Bottom Pane: The specific technical indicator defined in the logic. It features a Blue Line (Raw Illiquidity), a Red Line (Signal/Smoothed), and dynamic background coloring (Red and Green vertical strips).
● Deep Visual Analysis
• High Stress Regime (Red Zones)
Visual Event: In the bottom pane, the background periodically shifts to a translucent red.
Technical Logic: This event is triggered when the amihudAvg (the smoothed illiquidity ratio) exceeds the 75th percentile ( hZone ) of the lookback period.
Forensic Interpretation: The logic calculates the absolute price change relative to volume. A spike into the red zone indicates that price is moving significantly on relatively lower volume (high price impact). Visually, the chart shows these red zones aligning with local price peaks (volatility expansion), leading to the bearish reversal marked by the red box in the top pane.
• Liquid Regime (Green Zones)
Visual Event: The background shifts to a translucent green in the bottom pane.
Technical Logic: This triggers when the amihudAvg falls below the 25th percentile ( lZone ).
Forensic Interpretation: This state represents a period where large volumes are absorbed with minimal price impact (efficiency). On the chart, this green zone corresponds to the consolidation trough (green box, top pane), validating the annotated accumulation phase before the bullish breakout.
• Indicator Lines
Blue Line: This is the illiquidityRaw value. It represents the raw daily return divided by volume.
Red Line: This is the smoothedVal , a Simple Moving Average (SMA) of the raw data, used to filter out noise and define the trend of liquidity stress.
● Anomalies & Critical Data
• The Reversal Pivot
The transition from the "High Stress" (Red) background to the "Liquid" (Green) background serves as a visual proxy for market regime change. The chart shows that as the Red zones dissipate (volatility contraction), the market enters a Green zone (efficient liquidity), which acted as the precursor to the sustained upward trend on the right side of the chart.
● About Yakov Amihud
Yakov Amihud is a leading researcher in market liquidity and asset pricing.
• Brief Background
Professor of Finance, affiliated with New York University (NYU).
Specializes in market microstructure, liquidity, and quantitative finance.
His work has had a major impact on both academic research and practical investment models.
● The Amihud (2002) Paper
In 2002, he published his influential paper: “Illiquidity and Stock Returns: Cross-Section and Time-Series Effects” .
• Key Contributions
Introduced the Amihud Illiquidity Measure, a simple yet powerful proxy for market liquidity.
Demonstrated that less liquid stocks tend to earn higher expected returns as compensation for liquidity risk.
The measure became one of the most widely used liquidity metrics in finance research.
● Why It Matters in Practice
Used in quantitative trading models.
Applied in portfolio construction and risk management.
Helpful as a liquidity filter to avoid assets with excessive price impact.
In short: Yakov Amihud established a practical and robust link between liquidity and returns, making his 2002 work a cornerstone in modern financial economics.
Disclaimer: All provided scripts and indicators are strictly for educational exploration and must not be interpreted as financial advice or a recommendation to execute trades. I expressly disclaim all liability for any financial losses or damages that may result, directly or indirectly, from the reliance on or application of these tools. Market participation carries inherent risk where past performance never guarantees future returns, leaving all investment decisions and due diligence solely at your own discretion.
Liquiditytrader
Math by Thomas Liquidity PoolDescription
Math by Thomas Liquidity Pool is a TradingView indicator designed to visually identify potential liquidity pools on the chart by detecting areas where price forms clusters of equal highs or equal lows.
Bullish Liquidity Pools (Green Boxes): Marked below price where two adjacent candles have similar lows within a specified difference, indicating potential demand zones or stop loss clusters below support.
Bearish Liquidity Pools (Red Boxes): Marked above price where two adjacent candles have similar highs within the difference threshold, indicating potential supply zones or stop loss clusters above resistance.
This tool helps traders spot areas where smart money might hunt stop losses or where price is likely to react, providing valuable insight for trade entries, exits, and risk management.
Features:
Adjustable box height (vertical range) in points.
Adjustable maximum difference threshold between candle highs/lows to consider them equal.
Boxes automatically extend forward for visibility and delete when price sweeps through or after a defined lifetime.
Separate visual zones for bullish and bearish liquidity with customizable colors.
How to Use
Add the Indicator to your chart (preferably on instruments like Nifty where point-based thresholds are meaningful).
Adjust Inputs:
Box Height: Set the vertical size of the liquidity zones (default 15 points).
Max Difference Between Highs/Lows: Set the max price difference to consider two candle highs or lows as “equal” (default 10 points).
Box Lifetime: How many bars the box stays visible if not swept (default 120 bars).
Interpret Boxes:
Green Boxes (Bullish Liquidity Pools): Areas of potential demand and stop loss clusters below price. Watch for price bounces or accumulation near these zones.
Red Boxes (Bearish Liquidity Pools): Areas of potential supply and stop loss clusters above price. Watch for price rejections or distribution near these zones.
Trading Strategy Tips:
Use these zones to anticipate where stop loss hunting or liquidity sweeps may occur.
Combine with your Order Block, Fair Value Gap, and Market Structure tools for higher probability setups.
Manage risk by avoiding entries into price regions just before large liquidity pools get swept.
Automatic Cleanup:
Boxes delete automatically once price breaks above (for bearish zones) or below (for bullish zones) the zone or after the set lifetime.
Cluster Reversal Zones📌 Cluster Reversal Zones – Smart Market Turning Point Detector
📌 Category : Public (Restricted/Closed-Source) Indicator
📌 Designed for : Traders looking for high-accuracy reversal zones based on price clustering & liquidity shifts.
🔍 Overview
The Cluster Reversal Zones Indicator is an advanced market reversal detection tool that helps traders identify key turning points using a combination of price clustering, order flow analysis, and liquidity tracking. Instead of relying on static support and resistance levels, this tool dynamically adjusts to live market conditions, ensuring traders get the most accurate reversal signals possible.
📊 Core Features:
✅ Real-Time Reversal Zone Mapping – Detects high-probability market turning points using price clustering & order flow imbalance.
✅ Liquidity-Based Support/Resistance Detection – Identifies strong rejection zones based on real-time liquidity shifts.
✅ Order Flow Sensitivity for Smart Filtering – Filters out weak reversals by detecting real market participation behind price movements.
✅ Momentum Divergence for Confirmation – Aligns reversal zones with momentum divergences to increase accuracy.
✅ Adaptive Risk Management System – Adjusts risk parameters dynamically based on volatility and trend state.
🔒 Justification for Mashup
The Cluster Reversal Zones Indicator contains custom-built methodologies that extend beyond traditional support/resistance indicators:
✔ Smart Price Clustering Algorithm: Instead of plotting fixed support/resistance lines, this system analyzes historical price clustering to detect active reversal areas.
✔ Order Flow Delta & Liquidity Shift Sensitivity: The tool tracks real-time order flow data, identifying price zones with the highest accumulation or distribution levels.
✔ Momentum-Based Reversal Validation: Unlike traditional indicators, this tool requires a momentum shift confirmation before validating a potential reversal.
✔ Adaptive Reversal Filtering Mechanism: Uses a combination of historical confluence detection + live market validation to improve accuracy.
🛠️ How to Use:
• Works well for reversal traders, scalpers, and swing traders seeking precise turning points.
• Best combined with VWAP, Market Profile, and Delta Volume indicators for confirmation.
• Suitable for Forex, Indices, Commodities, Crypto, and Stock markets.
🚨 Important Note:
For educational & analytical purposes only.
Liquidity Weighted Moving Averages [AlgoAlpha]Description:
The Liquidity Weighted Moving Averages by AlgoAlpha is a unique approach to identifying underlying trends in the market by looking at candle bars with the highest level of liquidity. This script offers a modified version of the classical MA crossover indicator that aims to be less noisy by using liquidity to determine the true fair value of price and where it should place more emphasis on when calculating the average.
Rationale:
It is common knowledge that liquidity makes it harder for market participants to move the price of assets, using this logic, we can determine the coincident liquidity of each bar by looking at the volume divided by the distance between the opening and closing price of that bar. If there is a higher volume but the opening and closing prices are near each other, this means that there was a high level of liquidity in that bar. We then use standard deviations to filter out high spikes of liquidity and record the closing prices on those bars. An average is then applied to these recorded prices only instead of taking the average of every single bar to avoid including outliers in the data processing.
Key features:
Customizable:
Fast Length - the period of the fast-moving average
Slow Length - the period of the slow-moving average
Outlier Threshold Length - the period of the outlier processing algorithm to detect spikes in liquidity
Significant Noise reduction from outliers:
