Liquiditytrader — อินดิเคเตอร์และกลยุทธ์

Multi-Session Volume Profile Suite [MarkitTick]💡 This indicator provides a sophisticated, institutional-grade Volume Profile analysis suite that renders multiple temporal profiles simultaneously. It is designed for traders utilizing Auction Market Theory who require a holistic view of where value is being established across Daily, Weekly, and Monthly timeframes, alongside custom intraday sessions. By bypassing standard built-in functions in favor of a custom array-based calculation engine, this tool offers granular control over Value Area logic, Point of Control (POC) migration, and multi-timeframe confluence detection. ✨ Originality and Utility Standard Volume Profile tools often limit traders to a single timeframe or the visible range of the chart. This creates a fragmented view of the market, where a trader might see the daily value but miss the context of the weekly or monthly auction. This script solves that problem by layering three distinct higher-timeframe profiles (Daily, Weekly, Monthly) plus three customizable intraday session profiles onto a single chart. ● Key Differentiators Confluence Detection Engine: The script mathematically calculates when the Points of Control (POC) of different timeframes overlap (e.g., Daily POC inside Weekly POC). It explicitly highlights these high-probability zones with specific labels (e.g., "TRIPLE CONFLUENCE"), automating the search for key support/resistance levels. POC Migration Tracking: Unlike static profiles, this tool tracks the "Shift" of the POC. It visualizes whether value is migrating higher (▲), lower (▼), or remaining neutral (=) compared to the previous period, providing immediate insight into the trend's acceptance. Synthetic Chart Protection: The script includes logic to detect and prevent usage on non-standard chart types like Heikin Ashi or Renko, ensuring that the volume data processed is accurate and not subject to the repainting often found in synthetic OHLC variations. 🔬 Methodology and Concepts The core engine relies on a custom implementation of the Volume Profile formula using dynamic arrays. It does not simply pull pre-calculated data but processes the tick volume of the underlying asset relative to price action. • Volumetric Binning The script divides the price range of a specific period (e.g., a Day) into a user-defined number of "rows" (bins). As price trades within a specific bin, the corresponding volume is accumulated. Point of Control (POC): The bin with the highest accumulated volume is identified as the POC. This represents the "Fair Value" or the mode of the distribution for that period. Value Area (VA): The script calculates the total volume of the profile and then identifies the range surrounding the POC that contains a specific percentage (default 70%) of that volume. It uses a dual-scanning algorithm that expands upwards or downwards from the POC based on which adjacent row has higher volume, mimicking the auction process of testing prices. • Exact-Anchor Pivots Simultaneously, the script tracks "Exact-Anchor" pivots. Unlike standard pivots that settle at the close, these track the absolute High and Low of the period (Daily/Weekly/Monthly) in real-time and extend them until a new period begins. 🎨 Visual Guide The indicator uses a color-coded hierarchy to distinguish between timeframes. Understanding this visual language is critical for interpreting the data. ● Profile Hierarchy (Default Theme) Daily Profile (Yellow/Gold): Represents the immediate, short-term auction. Solid Line: Daily POC. Dotted Line: Daily Value Area High (VAH) and Low (VAL). Weekly Profile (Blue): Represents the intermediate auction. A solid Blue line indicates the Weekly POC. Monthly Profile (Purple): Represents the macro auction. A solid Purple line indicates the Monthly POC. ● Labels and Symbols Right-Side Labels: At the end of profile lines, text labels display the exact price of the POC. Shift Arrows (▲ / ▼): Located inside the POC label, these arrows indicate the direction the POC has moved relative to the previous period's POC. An Up arrow (▲) suggests buyers are accepting higher prices. Confluence Labels: If enabled, a text box appears near price action stating "POC CONFLUENCE" or "TRIPLE CONFLUENCE" when the POCs of different timeframes align within a tight margin. Block Symbol (⬛): A small block icon may appear above bars to denote the center of a specific session's time window. ● Pivot Lines Orange Lines: Previous Daily High (PDH) and Low (PDL). Green Dashed Lines: Previous Weekly High (PWH) and Low (PWL). Red Dotted Lines: Previous Monthly High (PMH) and Low (PML). White Dashed Line: New York Midnight Open price (if enabled). 📖 How to Use This suite is designed for "Contextual Trading." It answers the question: Where are we relative to value? • Trend Acceptance Observe the Shift Arrows on the POC labels. In a healthy uptrend, you should see a sequence of Daily and Weekly profiles with (▲) arrows, indicating that the market is validating higher prices as fair value. If price rises but the POC remains lower or shifts down, it may indicate a "weak high" or a potential reversal (divergence between price and value). • Support and Resistance The POC lines act as high-probability support and resistance. Price returning to a Weekly (Blue) or Monthly (Purple) POC often results in a reaction, as these are areas of significant historical agreement between buyers and sellers. • The Confluence Play Pay special attention when the "Confluence" label appears. When a Daily POC aligns with a Weekly or Monthly POC, that specific price level possesses reinforced structural importance. A rejection from such a level is a strong signal; a breakout through such a level often leads to an explosive move as value transitions rapidly. ⚙️ Inputs and Settings The script is highly customizable via the settings menu. ● General Settings Row Resolution: Determines the granularity of the profile. Higher numbers (e.g., 100) create smoother, more detailed profiles but use more calculation resources. Value Area %: Default is 70.0, representing the standard deviation of value. Show POC Shift: Toggles the (▲/▼) comparison logic. ● Profile Scope Show Daily/Weekly/Monthly: Checkboxes to individually enable or disable specific timeframe profiles. Session Lookback: Controls how many historical days/weeks the profiles are kept on the chart. ● Pivots (PDH/PMH/NYM) Show Pivots: Enables the High/Low lines for previous periods. Show NY Midnight: Specifically toggles the opening price of the New York session (00:00 EST). ● Alerts Approach Distance: Sets the sensitivity (in ticks) for alerts when price nears a key POC level. 🔍 Deconstruction of the Underlying Scientific and Academic Framework This indicator is grounded in Auction Market Theory (AMT) and statistical distribution analysis. • The Market as a Mechanism AMT postulates that the primary purpose of the market is to facilitate trade. Price advertises opportunity, while Time regulates the opportunity. Volume is the validation of that price. When the market spends significant time and transacts significant volume at a specific level, it establishes "Value." • Gaussian Distribution and Central Limit Theorem A Volume Profile is essentially a histogram of volume over price, often resembling a Gaussian (Normal) Distribution or "Bell Curve" when the market is balanced. POC (Mode): The peak of the curve. Mathematically, this is the mode of the dataset—the price occurring with the highest frequency (volume). Value Area (Standard Deviation): In a normal distribution, approximately 68.2% of data points fall within one standard deviation of the mean. This script defaults to a 70% Value Area to approximate this statistical boundary. Prices outside this area are considered statistically significant anomalies or "imbalanced." • Confluence and Probability The "Confluence" feature leverages the intersection of independent datasets. If the mode (POC) of a short-term distribution (Daily) aligns with the mode of a long-term distribution (Weekly), the probability of that price representing "True Value" increases exponentially. This aligns with statistical principles where overlapping data clusters suggest a stronger underlying signal amidst market noise. ⚠️ 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.

Smart Money Flow Oscillator [MarkitTick]💡This script introduces a sophisticated method for analyzing market liquidity and institutional order flow. Unlike traditional volume indicators that treat all market activity equally, the Smart Money Flow Oscillator (SMFO) employs a Logic Flow Architecture (LFA) to filter out market noise and "churn," focusing exclusively on high-impact, high-efficiency price movements. By synthesizing price action, volume, and relative efficiency, this tool aims to visualize the accumulation and distribution activities that are often attributed to "smart money" participants. ✨ Originality and Utility Standard indicators like On-Balance Volume (OBV) or Money Flow Index (MFI) often suffer from noise because they aggregate volume based simply on the close price relative to the previous close, regardless of the quality of the move. This script differentiates itself by introducing an "Efficiency Multiplier" and a "Momentum Threshold." It only registers volume flow when a price move is considered statistically significant and structurally efficient. This creates a cleaner signal that highlights genuine supply and demand imbalances while ignoring indecisive trading ranges. It combines the trend-following nature of cumulative delta with the mean-reverting insights of an In/Out ratio, offering a dual-mode perspective on market dynamics. 🔬 Methodology The underlying calculation of the SMFO relies on several distinct quantitative layers: • Efficiency Analysis The script calculates a "Relative Efficiency" ratio for every candle. This compares the current price displacement (body size) per unit of volume against the historical average. If price moves significantly with relatively low volume, or proportional volume, it is deemed "efficient." If significant volume occurs with little price movement (churn/absorption), the efficiency score drops. This score is clamped between a user-defined minimum and maximum (Efficiency Cap) to prevent outliers from distorting the data. • Momentum Thresholding Before adding any data to the flow, the script checks if the current price change exceeds a volatility threshold derived from the previous candle's open-close range. This acts as a gatekeeper, ensuring that only "strong" moves contribute to the oscillator. • Variable Flow Calculation If a move passes the threshold, the script calculates the flow value by multiplying the Typical Price and Volume (Money Flow) by the calculated Efficiency Multiplier. Bullish Flow: Strong upward movement adds to the positive delta. Bearish Flow: Strong downward movement adds to the negative delta. Neutral: Bars that fail the momentum threshold contribute zero flow, effectively flattening the line during consolidation. • Calculation Modes Cumulative Delta Flow (CDF): Sums the flow values over a rolling period. This creates a trend-following oscillator similar to OBV but smoother and more responsive to real momentum. In/Out Ratio: Calculates the percentage of bullish inflow relative to the total absolute flow over the period. This oscillates between 0 and 100, useful for identifying overextended conditions. 📖 How to Use Traders can utilize this oscillator to identify trend strength and potential reversals through the following signals: • Signal Line Crossovers The indicator plots the main Flow line (colored gradient) and a Signal line (grey). Bullish (Green Cloud): When the Flow line crosses above the Signal line, it suggests rising buying pressure and efficient upward movement. Bearish (Red Cloud): When the Flow line crosses below the Signal line, it suggests dominating selling pressure. • Divergences The script automatically detects and plots divergences between price and the oscillator: Regular Divergence (Solid Lines): Suggests a potential trend reversal (e.g., Price makes a Lower Low while Oscillator makes a Higher Low). Hidden Divergence (Dashed Lines): Suggests a potential trend continuation (e.g., Price makes a Higher Low while Oscillator makes a Lower Low). "R" labels denote Regular, and "H" labels denote Hidden divergences. • Dashboard A dashboard table is displayed on the chart, providing real-time metrics including the current Efficiency Multiplier, Net Flow value, and the active mode status. • In/Out Ratio Levels When using the Ratio mode: Values above 50 indicate net buying pressure. Values below 50 indicate net selling pressure. Approaching 70 or 30 can indicate overbought or oversold conditions involving volume exhaustion. ⚙️ Inputs and Settings Calculation Mode: Choose between "Cumulative Delta Flow" (Trend focus) or "In/Out Ratio" (Oscillator focus). Auto-Adjust Period: If enabled, automatically sets the lookback period based on the chart timeframe (e.g., 21 for Daily, 52 for Weekly). Manual Period: The rolling lookback length for calculations if Auto-Adjust is disabled. Efficiency Length: The period used to calculate the average body and volume for the efficiency baseline. Eff. Min/Max Cap: Limits the impact of the efficiency multiplier to prevent extreme skewing during anomaly candles. Momentum Threshold: A factor determining how much price must move relative to the previous candle to be considered a "strong" move. Show Dashboard/Divergences: Toggles for visual elements. 🔍 Deconstruction of the Underlying Scientific and Academic Framework This indicator represents a hybrid synthesis of academic Market Microstructure theory and classical technical analysis. It utilizes an advanced algorithm to quantify "Price Impact," leveraging the following theoretical frameworks: • 1. The Amihud Illiquidity Ratio (2002) The core logic (calculating body / volume) functions as a dynamic implementation of Yakov Amihud’s Illiquidity Ratio. It measures price displacement per unit of volume. A high efficiency score indicates that "Smart Money" has moved the price significantly with minimal resistance, effectively highlighting liquidity gaps or institutional control. • 2. Kyle’s Lambda (1985) & Market Depth Drawing from Albert Kyle’s research on market microstructure, the indicator approximates Kyle's Lambda to measure the elasticity of price in response to order flow. By analyzing the "efficiency" of a move, it identifies asymmetries—specifically where price reacts disproportionately to low volume—signaling potential manipulation or specific Market Maker activity. • 3. Wyckoff’s Law of Effort vs. Result From a classical perspective, the algorithm codifies Richard Wyckoff’s "Effort vs. Result" logic. It acts as an oscillator that detects anomalies where "Effort" (Volume) diverges from the "Result" (Price Range), predicting potential reversals. • 4. Quantitative Advantage: Efficiency-Weighted Volume Unlike linear indicators such as OBV or Chaikin Money Flow—which treat all volume equally—this indicator (LFA) utilizes Efficiency-Weighted Volume. By applying the efficiency_mult factor, the algorithm filters out market noise and assigns higher weight to volume that drives structural price changes, adopting a modern quantitative approach to flow analysis. ● 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.

Liquidity Strain Detector [MarkitTick]💡 This indicator provides a specialized method for detecting market anomalies where price movement becomes disconnected from typical volume profiles, signaling potential exhaustion events. By combining statistical analysis of liquidity (price impact) with a directional trend filter, the tool aims to highlight moments of extreme market stress, such as panic selling or euphoric buying, that often precede mean reversions or trend pauses. ● Originality and Utility Standard volume indicators often look at raw volume levels, which can be misleading during different times of the day or across different assets. This script calculates the efficiency of moving price (Illiquidity) and normalizes it statistically. This allows the trader to see when the market is becoming thin or stressed relative to recent history. It is particularly useful for contrarian traders looking for capitulation points within established trends, offering a unique perspective beyond standard RSI or MACD divergence. ● Methodology The core mechanism drives a custom Liquidity Engine that performs the following steps: Price Impact Calculation: It computes the ratio of the True Range to Volume. High values indicate that price is moving significant distances on relatively low volume or that volatility is extreme relative to participation. Normalization: The raw impact data is smoothed using a logarithmic scale to handle the wide variance in volume data. Statistical Scoring (Z-Score): The script calculates the Z-Score of this normalized data over a user-defined lookback period. This determines how many standard deviations the current liquidity stress is away from the mean. Trend Filtering: A standard Exponential Moving Average (EMA) determines the dominant market direction to contextualize the stress signal. ● How to Use The indicator plots labels on the chart when specific High Stress conditions are met during a trend: SE (Seller Exhaustion - Green Label): Appears when the market is in a downtrend (price below EMA), the current candle is bearish, and the liquidity stress Z-Score breaches the upper threshold. This suggests panic selling or a liquidity gap down, often marking a temporary bottom or reversal point. BE (Buyer Exhaustion - Red Label): Appears when the market is in an uptrend (price above EMA), the current candle is bullish, and the liquidity stress Z-Score breaches the upper threshold. This suggests a melt-up or buying climax into thin liquidity, often preceding a pullback. ● Inputs Trend Filter Length: The period for the EMA used to determine the baseline trend direction. Statistical Lookback: The number of bars used to calculate the mean and standard deviation for the Z-Score. Stress Threshold (Sigma): The Z-Score value required to trigger a high-stress signal. Higher values result in fewer, more extreme signals. ● 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.

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.

Math by Thomas Liquidity Pool Description 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: