התחל

חפש סקריפטים עבור "accumulation"

Holographic Market Microstructure | AlphaNattHolographic Market Microstructure | AlphaNatt A multidimensional, holographically-rendered framework designed to expose the invisible forces shaping every candle — liquidity voids, smart money footprints, order flow imbalances, and structural evolution — in real time. --- 📘 Overview The Holographic Market Microstructure (HMS) is not a traditional indicator. It’s a visual architecture built to interpret the true anatomy of the market — a living data structure that fuses price, volume, and liquidity into one coherent holographic layer. Instead of reacting to candles, HMS visualizes the market’s underlying micro-dynamics : where liquidity hides, where volume flows, and how structure morphs as smart money accumulates or distributes. Designed for system-based traders, volume analysts, and liquidity theorists who demand to see the unseen — the invisible grid driving every price movement. --- 🔬 Core Analytical Modules Microstructure Analysis Deconstructs each bar’s internal composition to identify imbalance between aggressive buying and selling. Using a configurable Imbalance Ratio and Liquidity Threshold , the algorithm marks low-liquidity zones and price inefficiencies as “liquidity voids.” • Detects hidden supply/demand gaps. • Quantifies micro-level absorption and exhaustion. • Reveals flow compression and expansion phases. Smart Money Tracking Applies advanced volume-rate-of-change and price momentum relationships to map institutional activity. • Accumulation Zones – Where price rises on expanding volume. • Distribution Zones – Where price declines on rising volume. • Automatically visualized as glowing boxes, layered through time to simulate footprint persistence. Fractal Structure Mapping Reveals the recursive nature of price formation. HMS detects fractal highs/lows, then connects them into an evolving structure. • Defines nested market structure across multiple scales. • Maps trend progression and transition points. • Renders with adaptive glow lines to reflect depth and strength. Volume Heat Map Transforms historical volume data into a 3D holographic heat projection. • Each band represents a volume-weighted price level. • Gradient brightness = relative participation intensity. • Helps identify volume nodes, voids, and liquidity corridors. HUD Display System Real-time analytical dashboard summarizing the system’s internal metrics directly on the chart. • Flow, Structure, Smart$, Liquidity, and Divergence — all live. • Designed for both scalpers and swing traders to assess micro-context instantly. --- 🧠 Smart Money Intelligence Layer The Smart Money Index dynamically evaluates the harmony (or conflict) between price momentum and volume acceleration. When institutions accumulate or distribute discreetly, volume surges ahead of price. HMS detects this divergence and overlays it as glowing smart money zones. ◈ ACCUM → Institutional absorption, early uptrend formation. ◈ DISTRIB → Distribution and top-heavy conditions. ○ IDLE → Neutral flow equilibrium. Divergences between price and volume are signaled using holographic alerts ( ⚠ ALERT ) to highlight exhaustion or trap conditions — often precursors to structural reversals. --- 🌀 Fractal Market Structure Engine The fractal subsystem recursively identifies local pivot symmetry, connecting micro-structural highs and lows into a holographic skeleton. • Bullish Structure — Higher highs & higher lows align (▲ BULLISH). • Bearish Structure — Lower highs & lower lows dominate (▼ BEARISH). • Ranging — Fractal symmetry balance (◆ RANGING). Each transition is visually represented through adaptive glow intensity, producing a living contour of market evolution . --- 🔥 Volume Heat Map Projection The heatmap acts as a volumetric X-ray of the recent 100–300 bars. Each horizontal segment reflects liquidity density, rendered with gradient opacity from cold (inactive) to hot (highly active). • Detects hidden accumulation shelves and distribution ridges. • Identifies imbalanced liquidity corridors (voids). • Reveals the invisible scaffolding of the order book. When combined with smart money zones and structure lines, it creates a multi-layered holographic perspective — allowing traders to see liquidity clusters and their interaction with evolving structure in real time. --- 💎 Holographic Visual Engine Every element of HMS is dynamically color-mapped to its visual theme . Each theme carries a distinct personality: Aeon — Neon blue plasma aesthetic; futuristic and fluid. Cyber — High-contrast digital energy; circuit-like clarity. Quantum — Deep space gradients; reflective of non-linear flow. Neural — Organic transitions; biological intelligence simulation. Plasma — Vapor-bright gradients; high-energy reactive feedback. Crystal — Minimalist, transparent geometry; pristine data visibility. Optional Glow Effects and Pulse Animations create a living hologram that responds to real-time market conditions. --- 🧭 HUD Analytics Table A live data matrix placed anywhere on-screen (top, middle, or side). It summarizes five critical systems: Flow: Order flow bias — ▲ BUYING / ▼ SELLING / ◆ NEUTRAL. Struct: Microstructure direction — ▲ BULLISH / ▼ BEARISH / ◆ RANGING. Smart$: Institutional behavior — ◈ ACCUM / ◈ DISTRIB / ○ IDLE. Liquid: Market efficiency — ⚡ VOID / ● NORMAL. Diverg: Price/Volume correlation — ⚠ ALERT / ✓ CLEAR. Each metric’s color dynamically adjusts according to live readings, effectively serving as a neural HUD layer for rapid interpretation. --- 🚨 Alert Conditions Stay informed in real time with built-in alerts that trigger under specific structural or liquidity conditions. Liquidity Void Detected — Market inefficiency or thin volume region identified. Strong Order Flow Detected — Aggressive buying or selling momentum shift. Smart Money Activity — Institutional accumulation or distribution underway. Price/Volume Divergence — Volume fails to confirm price trend. Market Structure Shift — Fractal structure flips directional bias. --- ⚙️ Customization Parameters Adjustable Microstructure Depth (20–200 bars). Configurable Imbalance Ratio and Liquidity Threshold . Adaptive Smart Money Sensitivity via Accumulation Threshold (%). Multiple Fractal Depth Layers for precise structural analysis. Scalable Heatmap Resolution (5–20 levels) and opacity control. Selectable HUD Position to suit personal layout preferences. Each parameter adjusts the balance between visual clarity and data density , ensuring optimal performance across intraday and macro timeframes alike. --- 🧩 Trading Application Identify early signs of institutional activity before breakouts. Track structure transitions with fractal precision. Locate hidden liquidity voids and high-value areas. Confirm strength of trends using order-flow bias. Detect volume-based divergences that often precede reversals. HMS is designed not just for observation — but for contextual understanding . Its purpose is to help traders anchor strategies in liquidity and flow dynamics rather than surface-level price action. --- 🪞 Philosophy Markets are holographic. Each candle contains a reflection of every other candle — a fractal within a fractal, a structure within a structure. The HMS is built to reveal that reflection, allowing traders to see through the market’s multidimensional fabric. --- Developed by: AlphaNatt Version: v6 Category: Market Microstructure | Volume Intelligence Framework: PineScript v6 | Holographic Visualization System Not financial advice
אינדיקטור Pine Script®
מאת ‎AlphaNatt‎
14
Buying Climax + Spring [Darwinian]Buying Climax + Spring Indicator Overview Advanced Wyckoff-based indicator that identifies potential market reversals through **Buying Climax** patterns (exhaustion tops) and **Spring** patterns (accumulation bottoms). Designed for traders seeking high-probability reversal signals with strict uptrend validation. --- Method 🔴 Buying Climax Detection Identifies exhaustion patterns at market tops using multi-condition analysis: **Base Buying Climax (Red Triangle)** - Volume spike > 1.8x average - Range expansion > 1.8x average - New 20-bar high reached - Close finishes in lower 30% of bar range - **Strict uptrend validation**: Price must be 30%+ above 20-day low **Enhanced Buying Climax (Maroon Triangle)** - All Base BC conditions PLUS: - Gap up from previous high - Intraday fade (close < open and below midpoint) - **Higher confidence reversal signal** 🟢 Wyckoff Spring Detection Identifies accumulation patterns at support levels: - Price breaks below recent pivot low (false breakdown) - Close recovers above pivot level (rejection) - Occurs at trading range low - Optional volume confirmation (1.5x+ average) - Limited to 3 attempts per pivot (prevents over-signaling) ✅ Uptrend Validation Filter **Four-condition composite filter** prevents false signals in sideways/downtrending markets: 1. Close-to-close rise ≥ 5% over lookback period 2. Price structure: Close > MA(10) > MA(20) 3. Swing low significantly below current price 4. **Primary requirement**: Current high ≥ 30% above 20-day low --- Input Tuning Guide Buying Climax Settings: **Volume & Range Thresholds** - `Volume Spike Threshold`: Default 1.8x - Lower (1.5x) = More signals, more noise - Higher (2.0-2.5x) = Fewer but stronger exhaustion signals - `Range Spike Threshold`: Default 1.8x - Adjust parallel to volume threshold - Higher values = extreme volatility required **Pattern Detection** - `New High Lookback`: Default 20 bars - Shorter (10-15) = Recent highs only - Longer (30-50) = Major breakout detection - `Close Off High Fraction`: Default 0.3 (30%) - Lower (0.2) = Stricter rejection requirement - Higher (0.4-0.5) = Allow weaker intraday fades - `Gap Threshold`: Default 0.002 (0.2%) - Increase (0.005-0.01) for stocks with wider spreads - Decrease (0.001) for tight-spread instruments - `Confirmation Window`: Default 5 bars - Shorter (3) = Faster confirmation, more false positives - Longer (7-10) = Wait for deeper automatic reaction Uptrend Filter Settings **Critical for Signal Quality** - `Minimum Rise from 20-day Low`: Default 0.30 (30%) - **Most important parameter** - Lower (0.20-0.25) = More signals in moderate uptrends - Higher (0.40-0.50) = Only extreme parabolic moves - `Pole Lookback`: Default 30 bars - Shorter (20) = Recent momentum focus - Longer (40-50) = Longer-term trend validation - `Minimum Rise % for Pole`: Default 0.05 (5%) - Adjust based on market volatility - Higher in strong bull markets (7-10%) Wyckoff Spring Settings - `Pivot Length`: Default 6 bars - Shorter (3-4) = More frequent pivots, more signals - Longer (8-10) = Major support/resistance only - `Volume Threshold`: Default 1.5x - Higher (1.8-2.0x) = Stronger conviction required - Disable volume requirement for low-volume stocks - `Trading Range Period`: Default 20 bars - Match to consolidation timeframe being traded - Shorter (10-15) for intraday patterns - Longer (30-40) for weekly consolidations --- Recommended Workflow 1. **Start with defaults** on daily timeframe 2. **Adjust uptrend filter** first (30% rise parameter) - Too many signals? Increase to 35-40% - Too few? Decrease to 25% 3. **Fine-tune volume/range multipliers** based on instrument volatility 4. **Enable alerts** for real-time monitoring: - Base BC → Initial warning - Enhanced BC → High-priority reversal - Confirmed BC (AR) → Strong follow-through - Spring → Accumulation opportunity --- Alert System - **Base Buying Climax**: Standard exhaustion pattern detected - **Enhanced BC (Gap+Fade)**: Higher confidence reversal setup - **Confirmed BC (AR)**: Automatic reaction validated (price drops below BC midline) - **Wyckoff Spring**: Accumulation pattern at support --- Best Practices - Combine with support/resistance analysis - Watch for BC clusters (multiple timeframes) - Spring patterns work best after Buying Climax distribution - Backtest parameters on your specific instruments - Higher timeframes (daily/weekly) = higher reliability --- Technical Notes - Built with Pine Script v6 - No repainting (signals finalize on bar close) - Minimal CPU usage (optimized calculations) - Works on all timeframes and instruments - Overlay indicator (displays on price chart) --- *Indicator follows classical Wyckoff methodology with modern volatility filters*
אינדיקטור Pine Script®
מאת ‎DarwinDarma‎
6
MFx Radar (Money Flow x-Radar)Description: MFx Radar is a precision-built multi-timeframe analysis tool designed to identify high-probability trend shifts and accumulation/distribution events using a combination of WaveTrend dynamics, normalized money flow, RSI, BBWP, and OBV-based trend biasing. Multi-Timeframe Trend Scanner Analyze trend direction across 5 customizable timeframes using WaveTrend logic to produce a clear trend consensus. Smart Money Flow Detection Adaptive hybrid money flow combines CMF and MFI, normalized across lookback periods, to pinpoint shifts in accumulation or distribution with high sensitivity. Event-Based Labels & Alerts Minimalist "Accum" and "Distr" text labels appear at key inflection points, based on hybrid flow flips — designed to highlight smart money moves without clutter. Trigger & Pattern Recognition Built-in logic detects anchor points, trigger confirmations, and rare "Snake Eye" formations directly on WaveTrend, enhancing trade timing accuracy. Visual Dashboard Table A real-time table provides score-based insight into signal quality, trend direction, and volume behavior, giving you a full picture at a glance. MFx Radar helps streamline discretionary and system-based trading decisions by surfacing key confluences across price, volume, and momentum all while staying out of your way visually. How to Use MFx Radar MFx Radar is a multi-timeframe market intelligence tool designed to help you spot trend direction, momentum shifts, volume strength, and high-probability trade setups using confluence across price, flow, and timeframes. Where to find settings To see the full visual setup: After adding the script, open the Settings gear. Go to the Inputs tab and enable: Show Trigger Diamonds Show WT Cross Circles Show Anchor/Trigger/Snake Eye Labels Show Table Show OBV Divergence Show Multi-TF Confluence Show Signal Score Then, go to the Style tab to adjust colors and fills for the wave plots and hybrid money flow. (Use published chart as a reference.) What the Waves and Colors Mean Blue WaveTrend (WT1 / WT2). These are the main momentum waves. WT1 > WT2 = bullish momentum WT1 < WT2 = bearish momentum Above zero = bullish bias Below zero = bearish bias When WT1 crosses above WT2, it often marks the beginning of a move — these are shown as green trigger diamonds. VWAP-MACD Line The yellow fill helps spot volume-based momentum. Rising = trend acceleration Use together with BBWP (bollinger band width percentile) and hybrid money flow for confirmation. Hybrid Money Flow Combines CMF and MFI, normalized and smoothed. Green = accumulation Red = distribution Transitions are key — especially when price moves up, but money flow stays red (a divergence warning). This is useful for spotting fakeouts or confirming smart money shifts. Orange Vertical Highlights Shows when price is rising, but money flow is still red. Often a sign of hidden distribution or "exit pump" behavior. Table Dashboard (Bottom-Right) BBWP (Volatility Pulse) When BBWP is low (<20), it signals consolidation — a breakout is likely to follow. Use this with ADX and WaveTrend position to anticipate directional breakouts. Trend by ADX Shows whether the market is trending and in which direction. Combined with money flow and RSI, this gives strong confirmation on breakouts. OBV HTF Bias Gives higher timeframe pressure (bullish/bearish/neutral). Helps avoid taking counter-trend trades. Pattern Labels (WT-Based) A = Anchor Wave — WT hitting oversold T = Trigger Wave — WT turning back up after anchor 👀 = Snake Eyes — Rare pattern, usually signaling strong reversal potential These help in timing entries, especially when they align with other signals like BBWP breakouts, confluence, or smart money flow flips. Multi-Timeframe (MTF) Consensus The system checks WaveTrend on 5 different timeframes and gives: Color-coded signals on each TF A final score: “Mostly Up,” “Mostly Down,” or “Mixed” When MTFs align with wave crosses, BBWP expansion, and hybrid money flow shifts, the probability of sustained move is higher. Divergence Spotting (Advanced Tip) Watch for:Price rising while money flow is red → Possible trap / early exit Price dropping while money flow is green → Early accumulation Combine this with anchor-trigger patterns and MTF trend support for spotting bottoms or tops early. Final Tips Use WT trigger crosses as initial signal. Confirm with money flow direction + color flip Look at BBWP for breakout timing. Use table as your decision dashboard Favor trades that align with MTF consensus
אינדיקטור Pine Script®
מאת ‎renderingnature1‎
9
DYNAMIC TRADING DASHBOARDStudy Material for the "Dynamic Trading Dashboard" This Dynamic Trading Dashboard is designed as an educational tool within the TradingView environment. It compiles commonly used market indicators and analytical methods into one visual interface so that traders and learners can see relationships between indicators and price action. Understanding these indicators, step by step, can help traders develop discipline, improve technical analysis skills, and build strategies. Below is a detailed explanation of each module. ________________________________________ 1. Price and Daily Reference Points The dashboard displays the current price, along with percentage change compared to the day’s opening price. It also highlights whether the price is moving upward or downward using directional symbols. Alongside, it tracks daily high, low, open, and daily range. For traders, daily levels provide valuable reference points. The daily high and low are considered intraday support and resistance, while the median price of the day often acts as a pivot level for mean reversion traders. Monitoring these helps learners see how price oscillates within daily ranges. ________________________________________ 2. VWAP (Volume Weighted Average Price) VWAP is calculated as a cumulative average price weighted by volume. The dashboard compares the current price with VWAP, showing whether the market is trading above or below it. For traders, VWAP is often a guide for institutional order flow. Price trading above VWAP suggests bullish sentiment, while trading below VWAP indicates bearish sentiment. Learners can use VWAP as a training tool to recognize trend-following vs. mean reversion setups. ________________________________________ 3. Volume Analysis The system distinguishes between buy volume (when the closing price is higher than the open) and sell volume (when the closing price is lower than the open). A progress bar highlights the ratio of buying vs. selling activity in percentage. This is useful because volume confirms price action. For instance, if prices rise but sell volume dominates, it can signal weakness. New traders learning with this tool should focus on how volume often precedes price reversals and trends. ________________________________________ 4. RSI (Relative Strength Index) RSI is a momentum oscillator that measures price strength on a scale from 0 to 100. The dashboard classifies RSI readings into overbought (>70), oversold (<30), or neutral zones and adds visual progress bars. RSI helps learners understand momentum shifts. During training, one should notice how trending markets can keep RSI extended for longer periods (not immediate reversal signals), while range-bound markets react more sharply to RSI extremes. It is an excellent tool for practicing trend vs. range identification. ________________________________________ 5. MACD (Moving Average Convergence Divergence) The MACD indicator involves a fast EMA, slow EMA, and signal line, with focus on crossovers. The dashboard shows whether a “bullish cross” (MACD above signal line) or “bearish cross” (MACD below signal line) has occurred. MACD teaches traders to identify trend momentum shifts and divergence. During practice, traders can explore how MACD signals align with VWAP trends or RSI levels, which helps in building a structured multi-indicator analysis. ________________________________________ 6. Stochastic Oscillator This indicator compares the current close relative to a range of highs and lows over a period. Displayed values oscillate between 0 and 100, marking zones of overbought (>80) and oversold (<20). Stochastics are useful for students of trading to recognize short-term momentum changes. Unlike RSI, it reacts faster to price volatility, so false signals are common. Part of the training exercise can be to observe how stochastic “flips” can align with volume surges or daily range endpoints. ________________________________________ 7. Trend & Momentum Classification The dashboard adds simple labels for trend (uptrend, downtrend, neutral) based on RSI thresholds. Additionally, it provides quick momentum classification (“bullish hold”, “bearish hold”, or neutral). This is beneficial for beginners as it introduces structured thinking: differentiating long-term market bias (trend) from short-term directional momentum. By combining both, traders can practice filtering signals instead of trading randomly. ________________________________________ 8. Accumulation / Distribution Bias Based on RSI levels, the script generates simplified tags such as “Accumulate Long”, “Accumulate Short”, or “Wait”. This is purely an interpretive guide, helping learners think in terms of accumulation phases (when markets are low) and distribution phases (when markets are high). It reinforces the concept that trading is not only directional but also involves timing. ________________________________________ 9. Overall Market Status and Score Finally, the dashboard compiles multiple indicators (VWAP position, RSI, MACD, Stochastics, and price vs. median levels) into a Market Score expressed as a percentage. It also labels the market as Overbought, Oversold, or Normal. This scoring system isn’t a recommendation but a learning framework. Students can analyze how combining different indicators improves decision-making. The key training focus here is confluence: not depending on one indicator but observing when several conditions align. Extended Study Material with Formulas ________________________________________ 1. Daily Reference Levels (High, Low, Open, Median, Range) • Day High (H): Maximum price of the session. DayHigh=max⁡(Hightoday)DayHigh=max(Hightoday) • Day Low (L): Minimum price of the session. DayLow=min⁡(Lowtoday)DayLow=min(Lowtoday) • Day Open (O): Opening price of the session. DayOpen=OpentodayDayOpen=Opentoday • Day Range: Range=DayHigh−DayLowRange=DayHigh−DayLow • Median: Mid-point between high and low. Median=DayHigh+DayLow2Median=2DayHigh+DayLow These act as intraday guideposts for seeing how far the price has stretched from its key reference levels. ________________________________________ 2. VWAP (Volume Weighted Average Price) VWAP considers both price and volume for a weighted average: VWAPt=∑i=1t(Pricei×Volumei)∑i=1tVolumeiVWAPt=∑i=1tVolumei∑i=1t(Pricei×Volumei) Here, Price_i can be the average price (High + Low + Close) ÷ 3, also known as hlc3. • Interpretation: Price above VWAP = bullish bias; Price below = bearish bias. ________________________________________ 3. Volume Buy/Sell Analysis The dashboard splits total volume into buy volume and sell volume based on candle type. • Buy Volume: BuyVol=Volumeif Close > Open, else 0BuyVol=Volumeif Close > Open, else 0 • Sell Volume: SellVol=Volumeif Close < Open, else 0SellVol=Volumeif Close < Open, else 0 • Buy Ratio (%): VolumeRatio=BuyVolBuyVol+SellVol×100VolumeRatio=BuyVol+SellVolBuyVol×100 This helps traders gauge who is in control during a session—buyers or sellers. ________________________________________ 4. RSI (Relative Strength Index) RSI measures strength of momentum by comparing gains vs. losses. Step 1: Compute average gains (AG) and losses (AL). AG=Average of Upward Closes over N periodsAG=Average of Upward Closes over N periodsAL=Average of Downward Closes over N periodsAL=Average of Downward Closes over N periods Step 2: Calculate relative strength (RS). RS=AGALRS=ALAG Step 3: RSI formula. RSI=100−1001+RSRSI=100−1+RS100 • Used to detect overbought (>70), oversold (<30), or neutral momentum zones. ________________________________________ 5. MACD (Moving Average Convergence Divergence) • Fast EMA: EMAfast=EMA(Close,length=fast)EMAfast=EMA(Close,length=fast) • Slow EMA: EMAslow=EMA(Close,length=slow)EMAslow=EMA(Close,length=slow) • MACD Line: MACD=EMAfast−EMAslowMACD=EMAfast−EMAslow • Signal Line: Signal=EMA(MACD,length=signal)Signal=EMA(MACD,length=signal) • Histogram: Histogram=MACD−SignalHistogram=MACD−Signal Crossovers between MACD and Signal are used in studying bullish/bearish phases. ________________________________________ 6. Stochastic Oscillator Stochastic compares the current close against a range of highs and lows. %K=Close−LowestLowHighestHigh−LowestLow×100%K=HighestHigh−LowestLowClose−LowestLow×100 Where LowestLow and HighestHigh are the lowest and highest values over N periods. The %D line is a smooth version of %K (using a moving average). %D=SMA(%K,smooth)%D=SMA(%K,smooth) • Values above 80 = overbought; below 20 = oversold. ________________________________________ 7. Trend and Momentum Classification This dashboard generates simplified trend/momentum logic using RSI. • Trend: • RSI < 40 → Downtrend • RSI > 60 → Uptrend • In Between → Neutral • Momentum Bias: • RSI > 70 → Bullish Hold • RSI < 30 → Bearish Hold • Otherwise Neutral This is not predictive, only a classification framework for educational use. ________________________________________ 8. Accumulation/Distribution Bias Based on extreme RSI values: • RSI < 25 → Accumulate Long Bias • RSI > 80 → Accumulate Short Bias • Else → Wait/No Action This helps learners understand the idea of accumulation at lows (strength building) and distribution at highs (profit booking). ________________________________________ 9. Overall Market Status and Score The tool adds up 5 bullish conditions: 1. Price above VWAP 2. RSI > 50 3. MACD > Signal 4. Stochastic > 50 5. Price above Daily Median BullishScore=ConditionsMet5×100BullishScore=5ConditionsMet×100 Then it categorizes the market: • RSI > 70 or Stoch > 80 → Overbought • RSI < 30 or Stoch < 20 → Oversold • Else → Normal This encourages learners to think in terms of probabilistic conditions instead of single-indicator signals. ________________________________________ ⚠️ Warning: • Trading financial markets involves substantial risk. • You can lose more money than you invest. • Past performance of indicators does not guarantee future results. • This script must not be copied, resold, or republished without authorization from aiTrendview. By using this material or the code, you agree to take full responsibility for your trading decisions and acknowledge that this is not financial advice. ________________________________________ ⚠️ Disclaimer and Warning (From aiTrendview) This Dynamic Trading Dashboard is created strictly for educational and research purposes on the TradingView platform. It does not provide financial advice, buy/sell recommendations, or guaranteed returns. Any use of this tool in live trading is completely at the user’s own risk. Markets are inherently risky; losses can exceed initial investment. The intellectual property of this script and its methodology belongs to aiTrendview. Unauthorized reproduction, modification, or redistribution of this code is strictly prohibited. By using this study material or the script, you acknowledge personal responsibility for any trading outcomes. Always consult professional financial advisors before making investment decisions.
אינדיקטור Pine Script®
מאת ‎aiTrendview-Charting-System‎
Advanced Volume Profile Pro Delta + POC + VAH/VAL# Advanced Volume Profile Pro - Delta + POC + VAH/VAL Analysis System ## WHAT THIS SCRIPT DOES This script creates a comprehensive volume profile analysis system that combines traditional volume-at-price distribution with delta volume calculations, Point of Control (POC) identification, and Value Area (VAH/VAL) analysis. Unlike standard volume indicators that show only total volume over time, this script analyzes volume distribution across price levels and estimates buying vs selling pressure using multiple calculation methods to provide deeper market structure insights. ## WHY THIS COMBINATION IS ORIGINAL AND USEFUL **The Problem Solved:** Traditional volume indicators show when volume occurs but not where price finds acceptance or rejection. Standalone volume profiles lack directional bias information, while basic delta calculations don't provide structural context. Traders need to understand both volume distribution AND directional sentiment at key price levels. **The Solution:** This script implements an integrated approach that: - Maps volume distribution across price levels using configurable row density - Estimates delta (buying vs selling pressure) using three different methodologies - Identifies Point of Control (highest volume price level) for key support/resistance - Calculates Value Area boundaries where 70% of volume traded - Provides real-time alerts for key level interactions and volume imbalances **Unique Features:** 1. **Developing POC Visualization**: Real-time tracking of Point of Control migration throughout the session via blue dotted trail, revealing institutional accumulation/distribution patterns before they complete 2. **Multi-Method Delta Calculation**: Price Action-based, Bid/Ask estimation, and Cumulative methods for different market conditions 3. **Adaptive Timeframe System**: Auto-adjusts calculation parameters based on chart timeframe for optimal performance 4. **Flexible Profile Types**: N Bars Back (precise control), Days Back (calendar-based), and Session-based analysis modes 5. **Advanced Imbalance Detection**: Identifies and highlights significant buying/selling imbalances with configurable thresholds 6. **Comprehensive Alert System**: Monitors POC touches, Value Area entry/exit, and major volume imbalances ## HOW THE SCRIPT WORKS TECHNICALLY ### Core Volume Profile Methodology: **1. Price Level Distribution:** - Divides price range into user-defined rows (10-50 configurable) - Calculates row height: `(Highest Price - Lowest Price) / Number of Rows` - Distributes each bar's volume across price levels it touched proportionally **2. Delta Volume Calculation Methods:** **Price Action Method:** ``` Price Range = High - Low Buy Pressure = (Close - Low) / Price Range Sell Pressure = (High - Close) / Price Range Buy Volume = Total Volume × Buy Pressure Sell Volume = Total Volume × Sell Pressure Delta = Buy Volume - Sell Volume ``` **Bid/Ask Estimation Method:** ``` Average Price = (High + Low + Close) / 3 Buy Volume = Close > Average ? Volume × 0.6 : Volume × 0.4 Sell Volume = Total Volume - Buy Volume ``` **Cumulative Method:** ``` Buy Volume = Close > Open ? Volume : Volume × 0.3 Sell Volume = Close ≤ Open ? Volume : Volume × 0.3 ``` **3. Point of Control (POC) Identification:** - Scans all price levels to find maximum volume concentration - POC represents the price level with highest trading activity - Acts as significant support/resistance level - **Developing POC Feature**: Tracks POC evolution in real-time via blue dotted trail, showing how institutional interest migrates throughout the session. Upward POC migration indicates accumulation patterns, downward migration suggests distribution, providing early trend signals before price confirmation. **4. Value Area Calculation:** - Starts from POC and expands up/down to encompass 70% of total volume - VAH (Value Area High): Upper boundary of value area - VAL (Value Area Low): Lower boundary of value area - Expansion algorithm prioritizes direction with higher volume **5. Adaptive Range Selection:** Based on profile type and timeframe optimization: - **N Bars Back**: Fixed lookback period with performance optimization (20-500 bars) - **Days Back**: Calendar-based analysis with automatic timeframe adjustment (1-365 days) - **Session**: Current trading session or custom session times ### Performance Optimization Features: - **Sampling Algorithm**: Reduces calculation load on large datasets while maintaining accuracy - **Memory Management**: Clears previous drawings to prevent performance degradation - **Safety Constraints**: Prevents excessive memory usage with configurable limits ## HOW TO USE THIS SCRIPT ### Initial Setup: 1. **Profile Configuration**: Select profile type based on trading style: - N Bars Back: Precise control over data range - Days Back: Intuitive calendar-based analysis - Session: Real-time session development 2. **Row Density**: Set number of rows (30 default) - more rows = higher resolution, slower performance 3. **Delta Method**: Choose calculation method based on market type: - Price Action: Best for trending markets - Bid/Ask Estimate: Good for ranging markets - Cumulative: Smoothed approach for volatile markets 4. **Visual Settings**: Configure colors, position (left/right), and display options ### Reading the Profile: **Volume Bars:** - **Length**: Represents relative volume at that price level - **Color**: Green = net buying pressure, Red = net selling pressure - **Intensity**: Darker colors indicate volume imbalances above threshold **Key Levels:** - **POC (Blue Line)**: Highest volume price - major support/resistance - **VAH (Purple Dashed)**: Value Area High - upper boundary of fair value - **VAL (Orange Dashed)**: Value Area Low - lower boundary of fair value - **Value Area Fill**: Shaded region showing main trading range **Developing POC Trail:** - **Blue Dotted Lines**: Show real-time POC evolution throughout the session - **Migration Patterns**: Upward trail indicates bullish accumulation, downward trail suggests bearish distribution - **Early Signals**: POC movement often precedes price movement, providing advance warning of institutional activity - **Institutional Footprints**: Reveals where smart money concentrated volume before final POC establishment ### Trading Applications: **Support/Resistance Analysis:** - POC acts as magnetic price level - expect reactions - VAH/VAL provide intermediate support/resistance levels - Profile edges show areas of low volume acceptance **Developing POC Analysis:** - **Upward Migration**: POC moving higher = institutional accumulation, bullish bias - **Downward Migration**: POC moving lower = institutional distribution, bearish bias - **Stable POC**: Tight clustering = balanced market, range-bound conditions - **Early Trend Detection**: POC direction change often precedes price breakouts **Entry Strategies:** - Buy at VAL with POC as target (in uptrends) - Sell at VAH with POC as target (in downtrends) - Breakout plays above/below profile extremes **Volume Imbalance Trading:** - Strong buying imbalance (>60% threshold) suggests continued upward pressure - Strong selling imbalance suggests continued downward pressure - Imbalances near key levels provide high-probability setups **Multi-Timeframe Context:** - Use higher timeframe profiles for major levels - Lower timeframe profiles for precise entries - Session profiles for intraday trading structure ## SCRIPT SETTINGS EXPLANATION ### Volume Profile Settings: - **Profile Type**: Determines data range for calculation - N Bars Back: Exact number of bars (20-500 range) - Days Back: Calendar days with timeframe adaptation (1-365 days) - Session: Trading session-based (intraday focus) - **Number of Rows**: Profile resolution (10-50 range) - **Profile Width**: Visual width as chart percentage (10-50%) - **Value Area %**: Volume percentage for VA calculation (50-90%, 70% standard) - **Auto-Adjust**: Automatically optimizes for different timeframes ### Delta Volume Settings: - **Show Delta Volume**: Enable/disable delta calculations - **Delta Calculation Method**: Choose methodology based on market conditions - **Highlight Imbalances**: Visual emphasis for significant volume imbalances - **Imbalance Threshold**: Percentage for imbalance detection (50-90%) ### Session Settings: - **Session Type**: Daily, Weekly, Monthly, or Custom periods - **Custom Session Time**: Define specific trading hours - **Previous Sessions**: Number of historical sessions to display ### Days Back Settings: - **Lookback Days**: Number of calendar days to analyze (1-365) - **Automatic Calculation**: Script automatically converts days to bars based on timeframe: - Intraday: Accounts for 6.5 trading hours per day - Daily: 1 bar per day - Weekly/Monthly: Proportional adjustment ### N Bars Back Settings: - **Lookback Bars**: Exact number of bars to analyze (20-500) - **Precise Control**: Best for systematic analysis and backtesting ### Visual Customization: - **Colors**: Bullish (green), Bearish (red), and level colors - **Profile Position**: Left or Right side of chart - **Profile Offset**: Distance from current price action - **Labels**: Show/hide level labels and values - **Smooth Profile Bars**: Enhanced visual appearance ### Alert Configuration: - **POC Touch**: Alerts when price interacts with Point of Control - **VA Entry/Exit**: Alerts for Value Area boundary interactions - **Major Imbalance**: Alerts for significant volume imbalances ## VISUAL FEATURES ### Profile Display: - **Horizontal Bars**: Volume distribution across price levels - **Color Coding**: Delta-based coloring for directional bias - **Smooth Rendering**: Optional smoothing for cleaner appearance - **Transparency**: Configurable opacity for chart readability ### Level Lines: - **POC**: Solid blue line with optional label - **VAH/VAL**: Dashed colored lines with value displays - **Extension**: Lines extend across relevant time periods - **Value Area Fill**: Optional shaded region between VAH/VAL ### Information Table: - **Current Values**: Real-time POC, VAH, VAL prices - **VA Range**: Value Area width calculation - **Positioning**: Multiple table positions available - **Text Sizing**: Adjustable for different screen sizes ## IMPORTANT USAGE NOTES **Realistic Expectations:** - Volume profile analysis provides structural context, not trading signals - Delta calculations are estimations based on price action, not actual order flow - Past volume distribution does not guarantee future price behavior - Combine with other analysis methods for comprehensive market view **Best Practices:** - Use appropriate profile types for your trading style: - Day Trading: Session or Days Back (1-5 days) - Swing Trading: Days Back (10-30 days) or N Bars Back - Position Trading: Days Back (60-180 days) - Consider market context (trending vs ranging conditions) - Verify key levels with additional technical analysis - Monitor profile development for changing market structure **Performance Considerations:** - Higher row counts increase calculation complexity - Large lookback periods may affect chart performance - Auto-adjust feature optimizes for most use cases - Consider using session profiles for intraday efficiency **Limitations:** - Delta calculations are estimations, not actual transaction data - Profile accuracy depends on available price/volume history - Effectiveness varies across different instruments and market conditions - Requires understanding of volume profile concepts for optimal use **Data Requirements:** - Requires volume data for accurate calculations - Works best on liquid instruments with consistent volume - May be less effective on very low volume or exotic instruments This script serves as a comprehensive volume analysis tool for traders who need detailed market structure information with integrated directional bias analysis and real-time POC development tracking for informed trading decisions.
אינדיקטור Pine Script®
מאת ‎DeltaSpeedEdge‎
6
Dark Pool Block Trades - Institutional Volume📊 Dark Pool Block Trades - Institutional Volume Visualize where institutional money positions before major price moves occur. This indicator reveals hidden dark pool block trades that often precede significant price movements - because when smart money deploys millions and billions in strategic accumulation or distribution, retail traders need to see where it's happening. 🎯 WHY DARK POOL DATA MATTERS: Institutions don't move large capital randomly. Dark pool block trades represent strategic positioning by sophisticated money managers with superior research and conviction. These trades create hidden support/resistance levels that often predict future price action. The key principle: Follow institutional flow, don't fight it. When institutions get involved, they create high-probability trading opportunities. 💰 HOW INSTITUTIONS INFLUENCE PRICE: - Large block trades establish hidden accumulation/distribution zones - Smart money builds positions BEFORE retail awareness increases - Institutional activity creates "footprints" at key technical levels - These trades often signal conviction plays ahead of major moves - Institutions typically add to winning positions throughout trends 🔍 WHAT THIS INDICATOR SHOWS: - Visual overlay of dark pool block trades directly on price charts - Track institutional positioning across major stocks and ETFs - Identify accumulation/distribution zones before they become obvious to retail - Spot high-conviction institutional trades in real-time visualization - Customizable block trade size filters and timeframe selection - Historical institutional activity up to 5 years or custom ranges 💡 THE TRADING ADVANTAGE: Instead of guessing price direction, see where institutions are already positioning. When large block trades appear in dark pools, you're witnessing strategic institutional commitment that frequently leads to significant price movements. ⚡ HOW IT WORKS: This Pine Script displays institutional dark pool transactions as visual markers on your charts. The script comes with sample data for immediate use. For expanded ticker coverage and real-time updates, external data services are available. 🎯 IDEAL FOR: - Swing traders following institutional footprints - Traders seeking setups backed by smart money conviction - Position traders looking for accumulation zones - Anyone wanting to align with institutional flow rather than fight it 🔄 SAMPLE DATA INCLUDED: Pre-loaded with institutional activity data across popular tickers, updated daily to demonstrate how dark pool activity correlates with future price movements. The script initially covers these tickers going back 6 months showing the top 10 trades by volume over 400,000 shares: AAPL, AMD, AMZN, ARKK, ARKW, BAC, BITO, COIN, COST, DIA, ETHA, GLD, GOOGL, HD, HYG, IBB, IWM, JNJ, JPM, LQD, MA, META, MSFT, NVDA, PG, QQQ, RIOT, SLV, SMCI, SMH, SOXX, SPY, TLT, TSLA, UNH, USO, V, VEA, VNQ, VOO, VTI, VWO, WMT, XLE, XLF, XLK, XLU, XLV, XLY
אינדיקטור Pine Script®
מאת ‎Mobytick‎
15
Volume Range Profile with Fair Value (Zeiierman)█ Overview The Volume Range Profile with Fair Value (Zeiierman) is a precision-built volume-mapping tool designed to help traders visualize where institutional-level activity is occurring within the price range — and how that volume behavior shifts over time. Unlike traditional volume profiles that rely on fixed session boundaries or static anchors, this tool dynamically calculates and displays volume zones across both the upper and lower ends of a price range, revealing point-of-control (POC) levels, directional volume flow, and a fair value drift line that updates live with each candle. You’re not just looking at volume anymore. You’re dissecting who’s in control — and at what price. ⚪ In simple terms: Upper Zone = The upper portion of the price range, showing concentrated volume activity — typically where selling or distribution may occur Lower Zone = The lower portion of the price range, highlighting areas of high volume — often associated with buying or accumulation POC Bin = The bin (price level) with the highest traded volume in the zone — considered the most accepted price by the market Fair Value Trend = A dynamic trend line tracking the average POC price over time — visualizing the evolving fair value Zone Labels = Display real-time breakdown of buy/sell volume within each zone and inside the POC — revealing who’s in control █ How It Works ⚪ Volume Zones Upper Zone: Anchored at the highest high in the lookback period Lower Zone: Anchored at the lowest low in the lookback period Width is user-defined via % of range Each zone is divided into a series of volume bins ⚪ Volume Bins (Histograms) Each zone is split into N bins that show how much volume occurred at each level: Taller = More volume The POC bin (Point of Control) is highlighted Labels show % of volume in the POC relative to the whole zone ⚪ Buy vs Sell Breakdown Each volume bin is split by: Buy Volume = Close ≥ Open Sell Volume = Close < Open The script accumulates these and displays total Buy/Sell volume per zone. ⚪ Fair Value Drift Line A POC trend is plotted over time: Represents where volume was most active across each range Color changes dynamically — green for rising, red for falling Serves as a real-time fair value anchor across changing market structure █ How to Use ⚪ Identify Key Control Zones Use Upper/Lower Zone structures to understand where supply and demand is building. Zones automatically adapt to recent highs/lows and re-center volume accordingly. ⚪ Follow Institutional Activity Watch for POC clustering near price tops or bottoms. Large volumes near extremes may indicate accumulation or distribution. ⚪ Spot Fair Value Drift The fair value trend line (average POC price) gives insight into market equilibrium. One strategy can be to trade a re-test of the fair value trend, trades are taken in the direction of the current trend. █ Understanding Buy & Sell Volume Labels (Zone Totals) These labels show the total buy and sell volume accumulated within each zone over the selected lookback period: Buy Vol (green label) → Total volume where candles closed bullish Sell Vol (red label) → Total volume where candles closed bearish Together, they tell you which side dominated: Higher Buy Vol → Bullish accumulation zone Higher Sell Vol → Bearish distribution zone This gives a quick visual insight into who controlled the zone, helping you spot areas of demand or supply imbalance. █ Understanding POC Volume Labels The POC (Point of Control) represents the price level where the most volume occurred within the zone. These labels break down that volume into: Buy % – How much of the volume was buying (price closed up) Sell % – How much was selling (price closed down) Total % – How much of the entire zone’s volume happened at the POC Use it to spot strong demand or supply zones: High Buy % + High Total % → Strong buying interest = likely support High Sell % + High Total % → Strong selling pressure = likely resistance It gives a deeper look into who was in control at the most important price level. █ Why It’s Useful Track where fair value is truly forming Detect aggressive volume accumulation or dumping Visually split buyer/seller control at the most relevant price levels Adapt volume structures to current trend direction █ Settings Explained Lookback Period: Number of bars to scan for highs/lows. Higher = smoother zones, Lower = reactive. Zone Width (% of Range): Controls how much of the range is used to define each zone. Higher = broader zones. Bins per Zone: Number of volume slices per zone. Higher = more detail, but heavier on resources. ----------------- Disclaimer The content provided in my scripts, indicators, ideas, algorithms, and systems is for educational and informational purposes only. It does not constitute financial advice, investment recommendations, or a solicitation to buy or sell any financial instruments. I will not accept liability for any loss or damage, including without limitation any loss of profit, which may arise directly or indirectly from the use of or reliance on such information. All investments involve risk, and the past performance of a security, industry, sector, market, financial product, trading strategy, backtest, or individual's trading does not guarantee future results or returns. Investors are fully responsible for any investment decisions they make. Such decisions should be based solely on an evaluation of their financial circumstances, investment objectives, risk tolerance, and liquidity needs.
אינדיקטור Pine Script®
מאת ‎Zeiierman‎
13
Grid TraderGrid Trader Indicator ( GTx ): Overview The Grid Trader Indicator is a tool that helps traders visualize key levels within a specified trading range. The indicator plots accumulation and distribution levels, an entry level, an exit level, and a midpoint. This guide will help you understand how to use the indicator and its features for effective grid trading. Basics of Trading Range, Grid Buy, and Grid Sell Trading Range A trading range is the horizontal price movement between a defined upper ( resistance ) and lower ( support ) level over a period of time. When a security trades within a range, it repeatedly moves between these two levels without trending upwards or downwards significantly. Traders often use the trading range to identify potential buy and sell points: Upper Level (Resistance): This is the price level at which selling pressure overcomes buying pressure, preventing the price from rising further. Lower Level (Support): This is the price level at which buying pressure overcomes selling pressure, preventing the price from falling further. Grid Trading Strategy Grid trading is a type of trading strategy that involves placing buy and sell orders at predefined intervals around a set price. It aims to profit from the natural market volatility by buying low and selling high in a range-bound market. The strategy divides the trading range into several grid levels where orders are placed. Grid Buy Grid buy orders are placed at intervals below the current price . When the price drops to these levels, buy orders are triggered . This strategy ensures that the trader buys more as the price falls, potentially lowering the average purchase price . Grid Sell Grid sell orders are placed at intervals above the current price . When the price rises to these levels, sell orders are triggered . This ensures that the trader sells portions of their holdings as the price increases, potentially securing profits at higher levels . Key Points of Grid Trading Grid Size : The interval between each buy and sell order. This can be constant (e.g., $2 intervals) or variable based on certain conditions. Accumulation Range : The lower part of the trading range where buy orders are placed. Distribution Range : The upper part of the trading range where sell orders are placed. Midpoint : The average price of the entry and exit levels, often used as a reference point for balance. As the price moves up and down within this range, your buy orders will be triggered as the price drops and your sell orders will be triggered as the price rises. This allows you to accumulate more of the asset at lower prices and sell portions at higher prices, profiting from the price oscillations within the defined range. Grid trading can be particularly effective in a sideways market where there is no clear long-term trend. However, it requires careful monitoring and adjustment of grid levels based on market conditions to minimize risks and maximize returns . Configuring the Indicator : Once the indicator is added, you will see a settings icon next to it. Click on it to open the settings menu. Adjust the Upper Level , Lower Level , Entry Level , and Exit Level to match your trading strategy and market conditions. Set the Levels Visibility to control how many bars back the levels will be plotted. Interpreting the Levels : Accumulation Levels : These are plotted below the entry level and are potential buy zones. They are labeled as Accumulation Level 1, 2, and 3. Distribution Levels : These are plotted above the exit level and are potential sell zones. They are labeled as Distribution Level 1, 2, and 3. Upper Level : Marked in fuchsia, indicating the top boundary of the trading range. Exit Level : Marked in yellow, indicating the level at which you plan to exit trades. Midpoint : Marked in white, indicating the average of the entry and exit levels. Entry Level : Marked in yellow, indicating the level at which you plan to enter trades. Lower Level : Marked in aqua, indicating the bottom boundary of the trading range. By visualizing key levels, you can make informed decisions on where to place buy and sell orders, potentially maximizing your trading profits through systematic grid trading.
אינדיקטור Pine Script®
מאת ‎Dantawe‎
Sadgir Patterns with SL/TPThe "Sadgir Patterns with SL/TP" is a cutting-edge trading indicator designed for traders seeking to leverage the power of Hull Moving Averages in conjunction with phase accumulation analysis. This unique indicator, developed on the Pine Script platform, is ideal for various markets, including stocks, forex, cryptocurrencies, and commodities. Key Features: Adaptive Hull Moving Average: Utilizes an adaptive Hull Moving Average, which provides a smooth and responsive moving average line, aiding in identifying trend directions and potential market reversals. Phase Accumulation Analysis: Integrates phase accumulation calculations to dynamically adjust the length of the Hull Moving Average, ensuring that the indicator stays in sync with market conditions. Signal Generation: Generates clear "Long" and "Short" signals, which are visually represented on the chart, assisting traders in making informed decisions. Dynamic Stop Loss and Take Profit Levels: Automatically calculates and plots dynamic stop loss (SL) and take profit (TP) levels as horizontal lines on the chart, based on user-defined percentage settings. These levels adjust in real-time with the price action, offering a systematic approach to risk management. Customizable Settings: Provides users with the flexibility to adjust the source of the moving average, power settings for the Hull Moving Average, cycles, and powers for phase accumulation, as well as the percentage values for SL and TP levels. Visual and Alert Features: Includes options for coloring the bars based on the trend direction and displays trade signals with distinct shapes. Additionally, alert conditions are set for both Long and Short signals, enabling traders to stay informed of potential trade opportunities. Usage: This indicator is designed for traders of all levels, from beginners to advanced. It can be used for trend following, catching reversals, or as part of a larger trading strategy. The dynamic SL and TP levels aid in managing trades effectively, providing both entry and exit points. However, traders are advised to use this indicator in conjunction with other analysis tools and consider the overall market context for the best results. Disclaimer: Trading involves risk, and it's important to do your own research and consider your risk tolerance before using this indicator. This tool is not intended as financial advice. NSE:BANKNIFTY NSE:NIFTY MCX:CRUDEOIL1!
אינדיקטור Pine Script®
מאת ‎gaurisadgir9‎
Market Phases NJRMarket Phases Indicator Overview: The Market Phases Indicator is a versatile tool designed for traders to identify key market phases, including accumulation, distribution, markup, and markdown. By analyzing the relationship between price and volume, this indicator aims to assist traders in recognizing potential shifts in market sentiment and trend direction. Features: 1. **Moving Average Analysis:** - Utilizes a customizable moving average length to assess the overall trend direction. 2. **Volume Confirmation:** - Incorporates volume analysis to confirm the strength of identified market phases. 3. **Visualization:** - Clearly visualizes accumulation, distribution, markup, and markdown phases on the price chart using intuitive shapes. Input Parameters: - **Moving Average Length (default: 20):** - Adjusts the length of the moving average for trend analysis. - **Volume Multiplier (default: 1.5):** - Sets the multiplier to customize the volume threshold for identifying significant market phases. How to Use: 1. **Accumulation and Distribution:** - Green triangles indicate potential accumulation phases when the closing price is above the moving average, and volume is higher than the specified threshold. Red triangles indicate potential distribution phases. 2. **Markup and Markdown:** - Blue triangles suggest potential markup phases when the closing price is above the moving average, and volume is below the specified threshold. Orange triangles indicate potential markdown phases. Important Notes: - This indicator is a tool for analysis and should be used in conjunction with other technical analysis methods. - Parameters can be adjusted based on the specific characteristics of the asset being analyzed. Disclaimer: Trading involves risk, and no indicator can guarantee profits. Users should exercise caution, conduct thorough research, and consider risk management principles when making trading decisions.
אינדיקטור Pine Script®
מאת ‎jayarakinisjrh‎
PA-Adaptive T3 Loxxer [Loxx]PA-Adaptive T3 Loxxer is a Loxxer indicator that is Phase Accumulation Cycle adaptive and uses T3 moving average for smoothing instead of the typical SMA or EMA . this allows for smoother signals by reducing noise. What is Loxxer? The Loxxer indicator is a technical analysis tool that compares the most recent maximum and minimum prices to the previous period's equivalent price to measure the demand of the underlying asset. What is the Phase Accumulation Cycle? The phase accumulation method of computing the dominant cycle is perhaps the easiest to comprehend. In this technique, we measure the phase at each sample by taking the arctangent of the ratio of the quadrature component to the in-phase component. A delta phase is generated by taking the difference of the phase between successive samples. At each sample we can then look backwards, adding up the delta phases.When the sum of the delta phases reaches 360 degrees, we must have passed through one full cycle, on average.The process is repeated for each new sample. The phase accumulation method of cycle measurement always uses one full cycle’s worth of historical data.This is both an advantage and a disadvantage.The advantage is the lag in obtaining the answer scales directly with the cycle period.That is, the measurement of a short cycle period has less lag than the measurement of a longer cycle period. However, the number of samples used in making the measurement means the averaging period is variable with cycle period. longer averaging reduces the noise level compared to the signal.Therefore, shorter cycle periods necessarily have a higher out- put signal-to-noise ratio. Included Bar coloring Signals Alerts Loxx's Expanded Source Types Divergences
אינדיקטור Pine Script®
מאת ‎loxx‎
3
[blackcat] L3 Banker Fund AttackLevel 3 Background This indicator is used to capture the movement of the banker fund. The buying and selling point is determined according to whether the momentum of the banker fund and the price momentum resonate. How to use the indicator: The red column line indicates that the banker fund accumulation signal appears, and the following 2 conditions are all satisfied to buy; (both above the green line of the banker fund attack threshold) 1. The yellow line and the purple line all cross the red accumulation histogram signal; 2. The yellow and purple trend lines are up Key point: If the yellow line crosses the green line of the banker fund attack threshold, it will be pulled up or the big market will open! The main thing is to see the red accumulation histogram signal, or the green line that crosses the banker fund attack threshold. If there is a red accumulation histogram signal, it means that there are main low-acquisition chips, and start trading on the left to open a position. The area above the green line of the banker fund attack threshold belongs to the main force pulling stage. When the green line of the banker fund attack threshold is not broken upwards, there is still a lot of profit space, but if it can be effectively broken through, it is highly profitable! Remarks This indicator only effective for instruments that contains banker fund. If there is no obvious large fund inside, the indicator is not as meaningful as it is called. I verified it worked well for > 4H or 1D timeframe. For the other time frames, you may need to check and verify by yourself. Feedbacks are appreciated.
אינדיקטור Pine Script®
מאת ‎blackcat1402‎
10
PA-Adaptive Polynomial Regression Fitted Moving Average [Loxx]PA-Adaptive Polynomial Regression Fitted Moving Average is a moving average that is calculated using Polynomial Regression Analysis. The purpose of this indicator is to introduce polynomial fitting that is to be used in future indicators. This indicator also has Phase Accumulation adaptive period inputs. Even though this first indicator is for demonstration purposes only, its still one of the only viable implementations of Polynomial Regression Analysis on TradingView is suitable for trading, and while this same method can be used to project prices forward, I won't be doing that since forecasting is generally worthless and causes unavoidable repainting. This indicator only repaints on the current bar. Once the bar closes, any signal on that bar won't change. For other similar Polynomial Regression Fitted methodologies, see here Poly Cycle What is the Phase Accumulation Cycle? The phase accumulation method of computing the dominant cycle is perhaps the easiest to comprehend. In this technique, we measure the phase at each sample by taking the arctangent of the ratio of the quadrature component to the in-phase component. A delta phase is generated by taking the difference of the phase between successive samples. At each sample we can then look backwards, adding up the delta phases.When the sum of the delta phases reaches 360 degrees, we must have passed through one full cycle, on average.The process is repeated for each new sample. The phase accumulation method of cycle measurement always uses one full cycle’s worth of historical data.This is both an advantage and a disadvantage.The advantage is the lag in obtaining the answer scales directly with the cycle period.That is, the measurement of a short cycle period has less lag than the measurement of a longer cycle period. However, the number of samples used in making the measurement means the averaging period is variable with cycle period. longer averaging reduces the noise level compared to the signal.Therefore, shorter cycle periods necessarily have a higher out- put signal-to-noise ratio. What is Polynomial Regression? In statistics, polynomial regression is a form of regression analysis in which the relationship between the independent variable x and the dependent variable y is modelled as an nth degree polynomial in x. Polynomial regression fits a nonlinear relationship between the value of x and the corresponding conditional mean of y, denoted E(y |x). Although polynomial regression fits a nonlinear model to the data, as a statistical estimation problem it is linear, in the sense that the regression function E(y | x) is linear in the unknown parameters that are estimated from the data. For this reason, polynomial regression is considered to be a special case of multiple linear regression. Things to know You can select from 33 source types The source is smoothed before being injected into the Polynomial fitting algorithm, there are 35+ moving averages to choose from for smoothing The output of the Polynomial fitting algorithm is then smoothed to create the signal, there are 35+ moving averages to choose from for smoothing Included Alerts Signals Bar coloring
אינדיקטור Pine Script®
מאת ‎loxx‎
PA-Adaptive TRIX Log [Loxx]PA-Adaptive TRIX Log is a Phase Accumulation Adaptive TRIX Log indicator. This adaptation smooths the signal to catch larger trends. What is TRIX? TRIX is a momentum oscillator that displays the percent rate of change of a TEMA . It was developed in the early 1980's by Jack Hutson, an editor for "Technical Analysis of Stocks and Commodities" magazine. With its triple smoothing, TRIX is designed to filter insignificant price movements. In his article he uses a logarithm of a price (which is in many versions, left out). What is the Phase Accumulation Cycle? The phase accumulation method of computing the dominant cycle is perhaps the easiest to comprehend. In this technique, we measure the phase at each sample by taking the arctangent of the ratio of the quadrature component to the in-phase component. A delta phase is generated by taking the difference of the phase between successive samples. At each sample we can then look backwards, adding up the delta phases.When the sum of the delta phases reaches 360 degrees, we must have passed through one full cycle, on average.The process is repeated for each new sample. The phase accumulation method of cycle measurement always uses one full cycle’s worth of historical data.This is both an advantage and a disadvantage.The advantage is the lag in obtaining the answer scales directly with the cycle period.That is, the measurement of a short cycle period has less lag than the measurement of a longer cycle period. However, the number of samples used in making the measurement means the averaging period is variable with cycle period. longer averaging reduces the noise level compared to the signal.Therefore, shorter cycle periods necessarily have a higher out- put signal-to-noise ratio. Included Bar coloring 2 signal options Alerts
אינדיקטור Pine Script®
מאת ‎loxx‎
1
Volume Indicators PackageCONTAINS 3 OF MY BEST VOLUME INDICATORS ALL FOR THE PRICE OF ONE! CONTAINS: Average Dollar Volume in RED Up/Down Volume Ratio in Green Volume Buzz/Volume Run Rate in BLUE If you would like to get these individually, I also have scripts for that too. Below is information about all three of these indicators, what they do, and why they are important. ---------------------------------------------------------------------------------------------AVERAGE DOLLAR VOLUME---------------------------------------------------------------------------------------- Dollar volume is simply the volume traded multiplied times the cost of the stock. Dollar volume is an extremely important metric for finding stocks with enough liquidity for market makers to position themselves in. Market Liquidity is defined as market's feature whereby an individual or firm can quickly purchase or sell an asset without causing a drastic change in the asset's price. The key concept you want to understand is that these big instructions with billions of dollars need liquidity in a stock in order to even think about buying it, and therefore these institutions will demand a large dollar volume . A good dollar volume amount, that represents a pretty liquid name, is typically above 100 million $ average. Why are institutions important? Simple because they are the ones who make stocks move, and I mean really move. If you want to see large growth from a stock in a short amount of time, you need institutions wielding billions of dollars to be fighting one another to buy more shares. Institutions are the ones who make or break a stock, this is why we call them market makers. My script calculates average dollar volume using four averages: the 50, the 30, the 20, and the 10 period. I use multiple averages in order to provide the accurate and up to date information to you. It then selects the minimum of these averages and divides this value by 1 million and displays this number to you. TL;DR? If you want monster moves from your stocks, you need to pick names with average high liquidity(dollar volume >= $100 million). The number presented to you is in millions of whatever currency the name is traded in. ---------------------------------------------------------------------------------------------UP/DOWN VOLUME RATIO----------------------------------------------------------------------------------------- Up/Down Volume Ratio is calculated by summing volume on days when it closes up and divide that total by the volume on days when the stock closed down. High volume up days are typically a sign of accumulation(buying) by big players, while down days are signs of distribution(selling) by big market players. The Up Down volume ratio takes this assumption and turns it into a tangible number that's easier for the trader to understand. My formula is calculated using the past 50 periods, be warned it will not display a value for stocks with under 50 periods of trading history. This indicator is great for identify accumulation of growth stocks early on in their moves, most of the time you would like a growth stocks U/D value to be above 2, showing institutional sponsorship of a stock. Up/Down Volume value interpretation: U/D < 1 -> Bearish outlook, as sellers are in control U/D = 1 -> Sellers and Buyers are equal U/D > 1 -> Bullish outlook, as buyers are in control U/D > 2 -> Bullish outlook, significant accumulation underway by market makers U/D >= 3 -> MONSTER STOCK ALERT, market makers can not get enough of this stock and are ravenous to buy more U/D values greater than 2 are rare and typically do not last very long, and U/D >= 3 are extremely rare one example I kind find of a stock's U/D peaking above 3 was Google back in 2005. -----------------------------------------------------------------------------------------------------VOLUME BUZZ----------------------------------------------------------------------------------------------- Volume Buzz/ Volume Run Rate as seen on TC2000 and MarketSmith respectively. Basically, the volume buzz tells you what percentage over average(100 time period moving average) the volume traded was. You can use this indicator to more readily identify above-average trading volume and accumulation days on charts. The percentage will show up in the top left corner, make sure to click the settings button and uncheck the second box(left of plot) in order to get rid of the chart line.
אינדיקטור Pine Script®
מאת ‎monkaOMEGA‎
2
Dynamic Money FlowDynamic Money Flow is a volume indicator based on Marc Chaikin's Money Flow with a few improvements. It can be used to confirm break-outs and trends. Zero line crosses and divergences can provide useful signals while considering chart analysis as well. Two weaknesses of CMF have been already fixed by Colin Twiggs (IncredibleCharts)... 1.CMF uses Chaikin's accumulation/distribution line to calculate the flow of money. Accumulation/distribution line does not take the gaps into account. This can be solved using true range. I call it true accumulation/distribution. 2.Oscillators have a tendency to center because of averaging calculations. DMF is average of flowing volume divided by average of total volume. This means indicator plots the change of first factor compared to the other one. In Simple Averaging method every data is given an equal weight thus when the last data drops it will have heavy impact on the averages and the change of them. It is much easier to identity these impacts after the drop of very high or very low data... So reducing the weight exponentially is a better option. 3.There is something else with CMF... changes of close price is ignored, because the formula only compares close price to its range. To include the movements of close beside the close to range comparison, the distance between two last close prices should be compared to true range as well. So volume can be distributed between close to range comparison (True Accumulation/Distribution) and close to close comparison automatically. And then results are summed to have a single multiplier. An example for how close to close comparison affects DMF... Or here you can see how lower wicks keep TMF (same as CMF in this case) from crossing zero line while price is trending down.
אינדיקטור Pine Script®
מאת ‎RezzaHmt‎
45
Fabio Valentini Pro Scalper [PickMyTrade]Fabio Valentini Pro Scalper Inspired by Fabio Valentini's NASDAQ scalping methodology, this strategy approximates professional order flow analysis using volume-based techniques, volume profile, and institutional trading concepts for liquid markets. CORE METHODOLOGY This strategy uses volume analysis to approximate order flow concepts typically seen in professional trading platforms: Volume Profile Analysis: Calculates Point of Control (POC), Value Area High (VAH), and Value Area Low (VAL) to identify institutional price acceptance zones where the majority of trading activity occurs. Delta Approximation: Estimates buying versus selling pressure by analyzing volume distribution within candles, helping identify which side of the market is in control. Absorption Detection: Identifies high-volume, low-price-movement candles that indicate institutional passive order absorption - when large players are building positions by absorbing aggressive orders. Triple-A Setup: Tracks the three-phase institutional trading pattern: - Absorption - Large players build positions passively - Accumulation - Price contracts into tight range as positions build - Aggression - Breakout with volume as institutional move initiates ENTRY SIGNAL TYPES Triple-A Setups: Identifies the complete absorption-accumulation-aggression sequence. When absorption is detected, followed by range contraction, and then aggressive breakout with volume confirmation. Opening Range Breakout (ORB): Trades breakouts from the configurable opening range period (default 30 minutes). Based on the concept that early session range defines key levels. Value Area Bounces: Identifies reactions at Value Area High or Value Area Low levels with absorption confirmation, suggesting institutional support or resistance. KEY FEATURES - VWAP with Dynamic Bands: Volume-weighted average price with ATR-based bands for trend and mean reversion context - Session-Based Filtering: Fully customizable trading session (default NY hours 9:30 AM - 4:00 PM) - Built-in Risk Management: Customizable risk percentage per trade with adjustable Risk:Reward ratios - Daily Loss Limit: Enforces maximum daily losses rule (default 3 losses) to prevent overtrading - Trailing Stop System: Optional ATR-based trailing stops to lock in profits - Real-Time Dashboard: Shows delta control, absorption status, market phase, and session information - Multiple Signal Filters: Combine or isolate different setup types for optimization CUSTOMIZABLE PARAMETERS Session Settings: Trading session times (any timezone), session filter enable/disable Volume Profile: Lookback period (default: 50 bars), row resolution for price levels (default: 24 rows) Absorption Detection: Volume multiplier threshold (default: 2.0), maximum price movement threshold (default: 0.3 ATR) Delta Analysis: Smoothing period (default: 5 bars) VWAP Settings: Enable/disable VWAP filter, band width multiplier (default: 0.5 ATR) Risk Management: Risk per trade percentage (default: 1%), Risk:Reward ratio (default: 2.0), maximum daily losses before stopping (default: 3), trailing stop toggle and ATR multiplier (default: 1.5) Opening Range Breakout: ORB period in minutes (default: 30), enable/disable ORB signals VISUAL ELEMENTS The strategy provides comprehensive visual feedback including VWAP bands, volume profile levels (POC, VAH, VAL), ORB lines, absorption signals, Triple-A setup markers, entry arrows with labels, session background highlighting, live statistics table, and daily loss limit warning background. BUILT-IN ALERT CONDITIONS Long and Short entry signals, strong absorption detection, Triple-A setup completion, and daily loss limit warnings. STRATEGY PHILOSOPHY Based on institutional trading principles: identify where large players are positioning through absorption patterns, wait for the accumulation phase shown by range contraction, then trade the aggressive move during expansion. The strategy combines multiple confirmation factors to filter high-probability setups. IMPORTANT NOTES AND DISCLAIMERS Not True Order Flow: This script approximates order flow concepts using publicly available volume data. True order flow analysis requires tick-by-tick bid/ask data from specialized platforms (e.g., Sierra Chart, Investor/RT with exchange feeds). This implementation provides educational approximation using TradingView's available data. Performance Sensitivity: Scalping strategy results are extremely sensitive to commission rates, slippage assumptions, position sizing decisions, parameter optimization for specific instruments, and market conditions. Cost Configuration Required: Before backtesting or live use, you MUST configure the Properties tab with realistic trading costs: Commission: Set to match your broker's actual fee structure (crypto spot: typically 0.05-0.20% per side, crypto futures: typically 0.02-0.05% per side, stock/futures: varies by broker and contract) Slippage: Set based on instrument liquidity (high liquidity: 2-5 ticks, medium liquidity: 5-10 ticks, lower liquidity or volatile conditions: 10+ ticks) Even small changes in commission or slippage can significantly impact profitability for scalping strategies. Parameter Optimization: Default settings are educational starting points. Users should test different absorption multiplier values (1.5-3.5), experiment with Risk:Reward ratios (2.0-4.0), try each signal type individually to find best performers, adjust parameters for their specific instrument and timeframe, and always validate changes with forward testing. Market Dependence: Strategy performance varies significantly across different instruments (futures vs crypto vs stocks), various timeframes (1-min vs 5-min vs 15-min), market conditions (trending vs ranging vs volatile), and trading sessions (high vs low liquidity periods). Educational Purpose: This strategy demonstrates order flow concepts, volume profile analysis, and institutional trading patterns for learning purposes. It is not a guaranteed profitable system and requires user optimization. RISK WARNING Scalping strategies require strict discipline and emotional control, excellent execution infrastructure (low latency, reliable fills), understanding of costs impact on profitability, respect for daily loss limits to prevent revenge trading, and realistic expectations - backtest results typically exceed live performance. This strategy enforces a daily loss limit (default 3 losses) based on professional trading risk management principles. When the limit is reached, the strategy stops generating signals to prevent overtrading. DISCLAIMER This is an educational tool for learning order flow concepts and institutional trading patterns. It is not financial advice. Past performance does not guarantee future results. Strategy profitability is highly dependent on execution quality, trading costs, parameter optimization, and market conditions. Users are solely responsible for their own testing, risk management, and trading decisions. No trading strategy is guaranteed to be profitable. Always test thoroughly on paper accounts before risking real capital.
אסטרטגיית Pine Script®
מאת ‎PickMyTrade_Official‎
DafeLiquidityEngineDafeLiquidityEngine: The Institutional Liquidity & Microstructure Engine This is not a volume indicator. This is a complete, institutional-grade quantitative laboratory for the analysis of market liquidity. It is a toolkit for seeing the invisible architecture of the order book and trading the cause, not the effect. █ CHAPTER 1: THE PHILOSOPHY - BEYOND VOLUME, INTO LIQUIDITY The standard volume bar is a lie. It tells you that the market was active, but it tells you nothing about the quality of that activity. Was it a deep, liquid market that could easily absorb large orders, or a thin, fragile market on the verge of a violent cascade? Was the volume driven by informed, institutional flow, or by reactive, retail panic? The DafeLiquidityEngine was created to answer these critical questions. This library is not a simple "mashup" of existing indicators; it is a foundational, original work that brings a suite of concepts from academic and institutional quantitative finance directly into the Pine Script environment. Its purpose is to move beyond the one-dimensional view of volume and provide a multi-faceted, high-resolution picture of the market's true, underlying liquidity structure. b]This is not an indicator that gives buy or sell signals. It is a far more powerful tool: a measurement device. It provides you with the crucial intelligence to assess the quality of the market environment. It tells you when liquidity is deep and signals can be trusted, and when liquidity has vanished and risk is extreme. It is the definitive engine for understanding the hidden structure of the market auction. █ CHAPTER 2: THE CORE INNOVATIONS - A UNIVERSITY-LEVEL TOOLKIT This library's value is rooted in its implementation of sophisticated, academically recognized models for liquidity and price impact, many for the first time on this platform. Multi-Scale Delta Divergence Engine: The engine doesn't just calculate one Cumulative Volume Delta (CVD). It calculates two simultaneously: a fast delta (representing scalpers and retail flow) and a slow delta (representing institutional accumulation/distribution). Its true genius lies in its ability to analyze the divergence between these two flows, classifying the market into one of five distinct states like "Absorption" (institutions absorbing retail selling) or "Stealth" (institutions quietly building a position). Advanced Bid-Ask Spread Estimation: Without access to Level 2 data, how can you know the spread? This library uses two renowned academic models—the Corwin-Schultz estimator (using high-low data) and the Roll spread estimator (using serial covariance)—to create a high-fidelity proxy for the live bid-ask spread. This is a direct measure of market tightness. Amihud Illiquidity Ratio: A classic, powerful measure of illiquidity. It calculates the absolute price return per dollar of volume traded. A high Amihud score means that even small amounts of volume are causing large, violent price swings—a clear sign of a dangerously illiquid market. Kyle's Lambda (Price Impact): This is the professional's measure of market impact. Lambda calculates how much the price moves for every unit of signed order flow. A high Lambda value indicates a "thin" order book where a single large market order can cause a significant price cascade. It is a direct measure of market fragility. The Volume Clock Engine: This module analyzes the market in "volume time" instead of chronological time. It detects volume "droughts" and "floods," measures the "participation rate" against historical norms, and analyzes the acceleration of volume to determine if a move is gaining or losing institutional support. The Composite Liquidity Regime: The capstone of the engine. It synthesizes the intelligence from all other modules into a single, unified classification of the market's liquidity state, from "Deep" and "Normal" to "Thin," "Desert," and the dreaded "Frozen." For developers, this provides a simple, powerful output: a risk_multiplier and a signal_penalty to automatically adjust position sizing and signal confidence based on the current liquidity environment. █ CHAPTER 3: A DEEP DIVE INTO THE ENGINE'S MODULES This is your guide to the engine room. Each module is a specialized analytical tool. The DeltaState Module: This is the heart of the divergence engine. It provides you with the raw and Z-scored values for both fast and slow delta, their velocity, and the final divergence classification ("absorption," "exhaustion," etc.) along with a confidence score. This is your primary tool for detecting conflicts between retail and institutional flow. The SpreadState Module: This gives you a direct, quantitative measure of market tightness. Use the spread_z score to see if the current bid-ask spread is statistically wide or tight, and the spread_regime to know if the market is "Blown" (extremely wide and risky) or "Tight" (liquid and efficient). The AmihudState & KyleState Modules: These are your professional-grade risk assessment tools. A rising illiquidity_z score from Amihud is a clear warning that the market is becoming fragile. A rising lambda_z from Kyle's Lambda tells you that price impact is increasing, and the risk of a slippage cascade is high. The VolumeClockState Module: This is your lens into market participation. The vol_clock_regime ("drought," "low," "normal," "elevated," "flood") tells you the character of the current volume, while the vol_trend_strength provides a measure of the momentum of participation. The LiquidityRegime Module: This is the final, synthesized verdict. It provides a single, easy-to-use regime name ("Flush," "Deep," "Normal," "Thin," "Desert," "Frozen") that encapsulates the combined intelligence of the entire system. Crucially, it also outputs the risk_multiplier and signal_penalty—direct, actionable factors you can use to modulate your own strategy's behavior. █ CHAPTER 4: THE DEVELOPER'S MASTERCLASS - IMPLEMENTATION GUIDE The DafeLiquidityEngine is a professional framework designed for seamless integration. This guide provides the complete instructions for leveraging its power. PART I: THE INPUTS TEMPLATE (THE CONTROL PANEL) While this is a library, a high-quality indicator built upon it would expose these parameters to the user for fine-tuning. This is the recommended input structure. // ╔═════════════════════════════════════════════════════════╗ // ║ INPUTS TEMPLATE ║ // ╚═════════════════════════════════════════════════════════╝ // INPUT GROUPS string G_LIQ_ENGINE = "═══════════ 💧 LIQUIDITY ENGINE ════════════" string G_LIQ_DELTA = "═══════════ 📊 DELTA & DIVERGENCE ══════════" string G_LIQ_RISK = "═══════════ ⚖️ RISK & SPREAD ════════════" // ENGINE CONFIG int i_liq_fast = input.int(8, "Fast Delta Length", minval=3, maxval=20, group=G_LIQ_ENGINE, tooltip="Lookback for the 'fast' retail/scalper delta.") int i_liq_slow = input.int(34, "Slow Delta Length", minval=21, maxval=100, group=G_LIQ_ENGINE, tooltip="Lookback for the 'slow' institutional delta.") int i_liq_zlookback = input.int(50, "Normalization Lookback", minval=20, maxval=200, group=G_LIQ_ENGINE, tooltip="The lookback period for all Z-Score calculations, which makes the metrics adaptive to the asset.") PART II: THE IMPLEMENTATION LOGIC (THE HEART OF YOUR SCRIPT) This is the boilerplate code you will adapt to your indicator. It shows the complete lifecycle of creating, updating, and using the engine. // ╔═════════════════════════════════════════════════════════╗ // ║ USAGE EXAMPLE (ADAPT TO YOUR SCRIPT) ║ // ╚═════════════════════════════════════════════════════════╝ // 1. IMPORT THE LIBRARY import YourUsername/DafeLiquidityEngine/1 as liq // 2. INITIALIZE THE ENGINE (happens only on the first bar) // The 'engine' must be a 'var' to retain its state across bars. var liq.LiquidityEngine engine = liq.create_engine(i_liq_fast, i_liq_slow, i_liq_zlookback) // 3. UPDATE THE ENGINE (runs on every bar) // Feed the current bar's OHLCV data into the engine. It handles all internal calculations. engine := liq.update(engine, open, high, low, close, volume) // 4. EXTRACT INTELLIGENCE (runs on every bar) // Get the final, synthesized output state from the engine. liq.LiquidityState state = liq.get_state(engine) // 5. USE THE INTELLIGENCE TO BUILD YOUR LOGIC // --- Example 1: Creating a Sophisticated Signal Filter --- bool my_raw_buy_signal = ta.crossover(ta.ema(close, 10), ta.ema(close, 20)) // The liquidity engine provides a simple penalty score. 1.0 = good liquidity, 0.2 = bad liquidity. float liquidity_penalty = state.signal_penalty // Only trust the signal if liquidity is good enough. bool final_buy_signal = my_raw_buy_signal and liquidity_penalty > 0.6 plotshape(final_buy_signal, "Filtered Buy", ...) // --- Example 2: Dynamic Position Sizing --- float base_position_size = 10000 // Your base size in dollars // The engine provides a risk multiplier. 1.0 = normal risk, 0.3 = high risk (reduce size). float liquidity_risk_multiplier = state.risk_multiplier float final_position_size = base_position_size * liquidity_risk_multiplier // Now use 'final_position_size' in your strategy logic. // --- Example 3: Building a Divergence-Based Strategy --- if state.divergence_type == "accumulation" and state.divergence_confidence > 0.7 // This is a high-confidence signal that institutions are quietly buying while price is falling. // A powerful setup for a long entry. strategy.entry("Accumulation Long", strategy.long) // --- Example 4: Displaying the State on a Dashboard --- if barstate.islast label.new(bar_index, high, "Liquidity Regime: " + state.liq_regime_name + "\nRisk Multiplier: " + str.tostring(state.risk_multiplier, "#.##") + "\nDivergence: " + state.divergence_type) █ DEVELOPMENT PHILOSOPHY The DafeLiquidityEngine was born from a single, guiding principle: liquidity is the fuel of the market. Price cannot move without it, and its absence or presence dictates the character of every trading session. This library provides, for the first time, a comprehensive, institutional-grade toolkit for quantifying this elusive but critical variable. It is a tool for the serious developer and the quantitative trader who is not satisfied with surface-level analysis, but who seeks to understand the deep, structural mechanics of the market auction. █ DISCLAIMER & IMPORTANT NOTES THIS IS A LIBRARY FOR ADVANCED DEVELOPERS: This script does nothing on its own. It is a powerful engine that must be imported and used by other indicator developers to build their own tools. THIS IS AN ESTIMATION ENGINE: The algorithms used (Corwin-Schultz, Kyle's Lambda, Delta Estimation) are highly respected academic and institutional proxies for true order book data. They are high-fidelity estimates, not a direct feed of Level 2 data. CONTEXT IS KEY: The output of this engine is contextual intelligence, not direct trading signals. A "Thin" liquidity regime is not a signal to sell; it is a signal to reduce position size, widen stops, and be wary of false breakouts. Create with DAFE.
ספריית Pine Script®
מאת ‎DskyzInvestments‎
SMC One Candle + AMD Bias (CT Focus)This indicator is a specialized Smart Money Concepts (SMC) tool designed for QQQ on the 5-minute chart. It fuses Tony Trades' "One Candle Rule" execution with the AMD (Accumulation, Manipulation, Distribution) cycle logic found in your previous CRT Pro V2 script. The primary goal of this indicator is to identify high-probability entries during the Purge Window (9:00 AM – 11:30 AM CT) by detecting when price manipulates morning liquidity before expanding in the direction of the daily bias. ## Core Components ### 1. Master Candle Range (Accumulation) Timeframe: 05:00 AM – 09:00 AM CT. Function: It automatically plots the Master High (CRH) and Master Low (CRL). This represents the "Accumulation" phase where orders are built up before the New York open. ### 2. The One Candle Zone (Execution) Timeframe: 08:35 AM CT (The 5-minute candle immediately following the high-volatility open). Function: It creates a blue "Value Zone" based on Tony Trades’ logic. This zone acts as the ultimate filter—price must reclaim or break this zone to confirm that the "Manipulation" phase is over and the "Distribution" has begun. ### 3. Multi-Timeframe Daily Bias Calculation: It tracks the midpoint (Equilibrium) of the previous day's range. Premium/Discount: Bullish (Discount): Price is trading above the daily midpoint. Bearish (Premium): Price is trading below the daily midpoint. Logic: Signals are filtered by this bias to ensure you are always trading with the higher-timeframe flow. ## Signal Logic Descriptions ### SMC Long (Bullish Distribution) A Long signal is generated when: Bias: The Daily Bias is Bullish. Manipulation: Price has ideally swept the Master Low (CRL) during the open. The Trigger: A 5-minute candle closes above the 08:35 AM "One Candle" High. Confirmation: This suggests shorts are trapped and Smart Money is distributing price toward the Previous Day High (PDH). ### SMC Short (Bearish Distribution) A Short signal is generated when: Bias: The Daily Bias is Bearish. Manipulation: Price has ideally swept the Master High (CRH). The Trigger: A 5-minute candle closes below the 08:35 AM "One Candle" Low. Confirmation: This confirms a rejection of the opening range, signaling a move toward the Previous Day Low (PDL) or the current Low of Day. ## Visual Guide Blue Box: The One Candle Zone (Tony Trades' "Line in the Sand"). Gray Stepline: The Master Candle Range (0500–0900 CT). Yellow Background: The Purge Window (0900–1130 CT), where your logic dictates the highest probability of a successful trade. Labels: Real-time Daily Bias updates in the top right corner.
אינדיקטור Pine Script®
מאת ‎day_trade_mind‎
Smart Trader, Episode 04, by Ata Sabanci, Candles and Z ScoresSmart Trader, Episode 04 Candles and Z-Scores: A Statistical Approach to Market Analysis ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ OVERVIEW This indicator applies Z-Score statistical analysis to measure how unusual current market conditions are compared to historical norms. It simultaneously analyzes five key metrics: Price, Total Volume, Buy Volume, Sell Volume, and Delta (Buy minus Sell) . The system detects 60 academically-researched market scenarios and provides visual feedback through Z-Lines (support/resistance levels), Event Markers, Trend Channels, and a comprehensive Dashboard. ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ CORE CONCEPT: WHY Z-SCORE? A Z-Score measures how many standard deviations a value is from its mean. In financial markets, extreme Z-Scores indicate statistically rare events that often precede significant price movements. Mathematical Formula: Z = (Current Value - Mean) / Standard Deviation Interpretation: • Z ≥ +2.0: Extremely high (occurs approximately 2.5% of the time) • Z ≥ +1.0: Above average • Z ≈ 0: Normal (near the mean) • Z ≤ -1.0: Below average • Z ≤ -2.0: Extremely low (occurs approximately 2.5% of the time) ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ ACADEMIC FOUNDATION This indicator is inspired by / grounded in market microstructure literature (abbreviated citations in-script) from market microstructure literature: • Price-Volume Relationship - Karpoff (1987), Journal of Financial and Quantitative Analysis, Cambridge Volume is positively correlated with price change magnitude • Order Flow Imbalance - Cont, Kukanov, Stoikov (2014), Journal of Financial Econometrics Order imbalance drives price more reliably than raw volume • Informed Trading (PIN Model) - Easley, Kiefer, O'Hara, Paperman (1996), Journal of Finance Buy/Sell imbalance reveals informed trader activity • Mixture of Distributions - Tauchen & Pitts (1983), Clark (1973) Volume clusters with volatility regimes • Volume Predictability - Gervais, Kaniel, Mingelgrin (2001) Volume shocks predict future returns • Liquidity & Order Imbalance - Chordia, Roll, Subrahmanyam (2002) Order imbalance affects short-term returns • Volume-Return Dynamics - Llorente, Michaely, Saar, Wang (2002) Speculation vs. risk-sharing patterns • Reversal vs. Continuation - Campbell, Grossman, Wang (MIT) High volume predicts lower autocorrelation ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ VOLUME ENGINE The indicator offers two methods for decomposing total volume into Buy and Sell components: Method 1: Geometry (Approximation) Uses candle structure to estimate buying and selling pressure: Buy Volume = Total Volume × (Close - Low) / (High - Low) Sell Volume = Total Volume × (High - Close) / (High - Low) • Works on all instruments without additional data requirements • Fast calculation • Less precise than intrabar method Method 2: Intrabar (Precise) Uses Lower Timeframe (LTF) tick/second data to aggregate actual up-ticks versus down-ticks: • More accurate volume decomposition • Requires LTF data availability • Configurable LTF: 1T (tick), 1S, 15S, 1M Delta Calculation: Delta = Buy Volume - Sell Volume ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ Z-SCORE SYSTEM The system calculates Z-Scores for five metrics simultaneously, using a configurable lookback period (default: 20 bars): • Zp (Price Z-Score): Measures price deviation from its mean • Zv (Volume Z-Score): Measures total volume deviation • Zbuy (Buy Volume Z-Score): Measures buying pressure deviation • Zsell (Sell Volume Z-Score): Measures selling pressure deviation • ZΔ (Delta Z-Score): Measures order flow imbalance deviation Threshold Constants: • ZH (Z High) = 2.0: Extreme threshold • ZM (Z Medium) = 1.0: Moderate threshold • Z0 (Z Zero) = 0.5: Near-zero threshold Group System: The analysis window is divided into groups (default: 5 groups × 20 bars = 100 bar total window). Group numbers (1, 2, 3...) are displayed above candles when enabled, helping identify the relative age of detected levels. ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ Z-LINES (SUPPORT/RESISTANCE LEVELS) When any metric reaches an extreme Z-Score, the system marks that price level as a significant support or resistance zone. Detection Logic: • Upper Z-Line: Drawn from the HIGH when Z ≥ upper threshold (default +2.0) • Lower Z-Line: Drawn from the LOW when Z ≤ lower threshold (default -2.0) Multi-Metric Detection: Z-Lines can be triggered by any of the five metrics (Price, Volume, Buy, Sell, Delta). When multiple metrics trigger at similar price levels, they are clustered together into a single combined label showing all contributing metrics. Persistence: Z-Lines persist for the entire analysis window (Period × Groups bars) and are NOT removed when price touches them. This allows traders to see historical support/resistance levels that may still be relevant. Anti-Overlap System: Labels are automatically repositioned to prevent overlap. The "Label Min Gap (%)" setting controls minimum vertical separation between ALL labels (both upper and lower), ensuring readability even when multiple levels cluster together. ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ EVENT DETECTION ENGINE (60 SCENARIOS) The system analyzes 60 distinct market scenarios based on Z-Score combinations. Each scenario is derived from academic research and assigned a confidence score based on signal strength and alignment. Notation: • Zp = Price Z-Score • Zv = Total Volume Z-Score • Zbuy = Buy Volume Z-Score • Zsell = Sell Volume Z-Score • ZΔ = Delta Z-Score • dirP = Price direction (+1 if Zp > 0.5, -1 if Zp < -0.5, else 0) • = Previous bar value • ZH = 2.0 (High threshold) • ZM = 1.0 (Medium threshold) • Z0 = 0.5 (Zero threshold) ───────────────────────────────────────────────────────────── CATEGORY A: PRICE-VOLUME (Events 1-10) Based on: Karpoff (1987), Tauchen-Pitts (1983), Clark (1973) ───────────────────────────────────────────────────────────── Event 1: Breakout Confirmed |Zp| ≥ ZH AND Zv ≥ ZH AND sign(ZΔ) = dirP AND dirP ≠ 0 Direction: Bullish/Bearish (follows price direction) Event 2: Trend Strength Confirmed |Zp| ≥ ZH AND Zv ≥ ZH Direction: Follows price direction Event 3: Fragile Move |Zp| ≥ ZH AND Zv ≤ -ZM Direction: Warning (price move without volume support) Event 4: Weak Rally Zp ≥ ZH AND Zv ≤ -ZH Direction: Warning (price up without volume) Event 5: Weak Selloff Zp ≤ -ZH AND Zv ≤ -ZH Direction: Warning (price down without volume) Event 6: Momentum Build ZM ≤ |Zp| < ZH AND Zv ≥ ZH Direction: Follows price direction Event 7: Churn |Zp| ≤ Z0 AND Zv ≥ ZH Direction: Neutral (high volume, low price movement) Event 8: Quiet Compression |Zp| ≤ Z0 AND Zv ≤ -ZH Direction: Neutral (low volume, low price movement) Event 9: High Volume Regime Zv ≥ ZH Direction: Neutral Event 10: Low Volume Regime Zv ≤ -ZH Direction: Neutral ───────────────────────────────────────────────────────────── CATEGORY B: ORDER-FLOW / DELTA (Events 11-16) Based on: Cont, Kukanov, Stoikov (2014), Easley, Kiefer, O'Hara, Paperman (1996) ───────────────────────────────────────────────────────────── Event 11: Imbalance Drives Price |ZΔ| ≥ ZH AND sign(ZΔ) = dirP AND dirP ≠ 0 Direction: Follows price direction (dirP), with delta alignment required Event 12: Divergence Top Zp ≥ ZH AND ZΔ ≤ -ZH Direction: Warning (distribution at top) Event 13: Divergence Bottom Zp ≤ -ZH AND ZΔ ≥ ZH Direction: Warning (accumulation at bottom) Event 14: Absorption Positive |Zp| ≤ Z0 AND Zv ≥ ZH AND ZΔ ≥ ZH Direction: Bullish (buy absorption, support forming) Event 15: Absorption Negative |Zp| ≤ Z0 AND Zv ≥ ZH AND ZΔ ≤ -ZH Direction: Bearish (sell absorption, resistance forming) Event 16: Depth Wall Zv ≥ ZH AND |ZΔ| ≥ ZH AND |Zp| ≤ Z0 Direction: Neutral (market depth absorbing) ───────────────────────────────────────────────────────────── CATEGORY C: BUY VS SELL (Events 17-23) Based on: Easley, Kiefer, O'Hara, Paperman (1996), Chordia, Roll, Subrahmanyam (2002) ───────────────────────────────────────────────────────────── Event 17: Aggressive Buy Dominance Zbuy ≥ ZH AND ZΔ ≥ ZH AND Zsell ≤ -ZM Direction: Bullish Event 18: Aggressive Sell Dominance Zsell ≥ ZH AND ZΔ ≤ -ZH AND Zbuy ≤ -ZM Direction: Bearish Event 19: Two-Sided Battle Zbuy ≥ ZH AND Zsell ≥ ZH AND |ZΔ| ≤ Z0 Direction: Neutral (buyers and sellers equally strong) Event 20: Battle with Buy Edge Zbuy ≥ ZH AND Zsell ≥ ZH AND ZM ≤ ZΔ < ZH Direction: Bullish Event 21: Battle with Sell Edge Zbuy ≥ ZH AND Zsell ≥ ZH AND -ZH < ZΔ ≤ -ZM Direction: Bearish Event 22: Hidden Accumulation Zbuy ≥ ZH AND |Zp| ≤ Z0 AND Zv ≥ ZH Direction: Bullish (buy shock without price movement) Event 23: Hidden Distribution Zsell ≥ ZH AND |Zp| ≤ Z0 AND Zv ≥ ZH Direction: Bearish (sell shock without price movement) ───────────────────────────────────────────────────────────── CATEGORY D: PREDICTABILITY (Events 24-26) Based on: Gervais, Kaniel, Mingelgrin (2001), Karpoff (1987) ───────────────────────────────────────────────────────────── Event 24: Volume Shock Positive Drift Zv ≥ ZH AND |Zp| ≤ ZM Direction: Follows price direction Event 25: Volume Shock Negative Drift Zv ≤ -ZH AND |Zp| ≤ ZM Direction: Opposite to price direction Event 26: Abnormal Volume Info Arrival Zv ≥ ZH Direction: Neutral ───────────────────────────────────────────────────────────── CATEGORY E: REVERSAL VS CONTINUATION (Events 27-30) Based on: Campbell, Grossman, Wang (MIT), Llorente, Michaely, Saar, Wang (2002) ───────────────────────────────────────────────────────────── Event 27: High Vol Reversal Risk Zv ≥ ZH Direction: Warning (high volume implies lower positive autocorrelation) Event 28: Low Vol Continuation Risk Zv ≤ -ZH Direction: Follows price direction (trend likely continues) Event 29: Speculation Continuation Zv ≥ ZH AND |ZΔ| ≥ ZM AND sign(ZΔ) = dirP AND dirP ≠ 0 Direction: Follows price direction Event 30: Risk Sharing Reversal Zv ≥ ZH AND |ZΔ| ≤ Z0 Direction: Warning (potential reversal) ───────────────────────────────────────────────────────────── CATEGORY F: IMBALANCE LAG (Events 31-33) Based on: Chordia, Roll, Subrahmanyam (2002) ───────────────────────────────────────────────────────────── Event 31: Persistent Imbalance Push |ZΔ| ≥ ZM AND |ZΔ | ≥ ZM AND sign(ZΔ) = sign(ZΔ ) Direction: Follows delta direction (persistent pressure) Event 32: Imbalance Pressure Decay (ZΔ ≥ ZM AND ZΔ ≤ -ZM) OR (ZΔ ≤ -ZM AND ZΔ ≥ ZM) Direction: Warning (imbalance sign flip) Event 33: Intraday Imbalance Predicts |ZΔ| ≥ ZM Direction: Follows delta direction ───────────────────────────────────────────────────────────── CATEGORY G: SUPPORT/RESISTANCE (Events 34-36) Based on: Peskir (Manchester) ───────────────────────────────────────────────────────────── Event 34: SR Barrier Event |Zp| ≤ Z0 AND Zv ≥ ZH Direction: Neutral (price stalls with high volume) Event 35: Volume Backed SR Level |Zp| ≤ Z0 AND Zv ≥ ZH AND |ZΔ| ≥ ZM Direction: Follows delta direction Event 36: Volume Poor SR Level |Zp| ≤ Z0 AND Zv ≤ -ZM Direction: Warning (weak S/R without volume) ───────────────────────────────────────────────────────────── CATEGORY H: EXTENDED ANALYSIS (Events 37-50) Based on: Extended market microstructure analysis ───────────────────────────────────────────────────────────── Event 37: Climax Buy Zbuy ≥ ZH AND Zp ≥ ZH AND Zv ≥ ZH Direction: Warning (extreme buying exhaustion, potential top) Event 38: Climax Sell Zsell ≥ ZH AND Zp ≤ -ZH AND Zv ≥ ZH Direction: Warning (extreme selling exhaustion, potential bottom) Event 39: Stealth Accumulation Zbuy ≥ ZM AND |Zp| ≤ Z0 AND Zv ≤ Z0 Direction: Bullish (quiet buying) Event 40: Stealth Distribution Zsell ≥ ZM AND |Zp| ≤ Z0 AND Zv ≤ Z0 Direction: Bearish (quiet selling) Event 41: Volume Divergence Bull Zp ≤ -ZM AND Zv ≤ -ZM Direction: Bullish (price down but volume declining) Event 42: Volume Divergence Bear Zp ≥ ZM AND Zv ≤ -ZM Direction: Bearish (price up but volume declining) Event 43: Delta Price Alignment |Zp| ≥ ZM AND |ZΔ| ≥ ZM AND sign(Zp) = sign(ZΔ) Direction: Follows price direction (strong trend confirmation) Event 44: Extreme Compression |Zp| ≤ Z0 AND Zv ≤ -ZH Direction: Neutral (very low volatility) Event 45: Volatility Expansion |Zp| ≥ ZH AND Zv ≥ ZH Direction: Follows price direction (breakout from compression) Event 46: Buy Exhaustion Zbuy ≥ ZH AND Zp ≤ Z0 Direction: Warning (high buy but price fails) Event 47: Sell Exhaustion Zsell ≥ ZH AND Zp ≥ -Z0 Direction: Warning (high sell but price holds) Event 48: Trend Acceleration |Zp| ≥ ZM AND |Zp| > |Zp | AND Zv ≥ ZM Direction: Follows price direction (increasing momentum) Event 49: Trend Deceleration |Zp| ≥ ZM AND |Zp| < |Zp | AND sign(Zp) = sign(Zp ) Direction: Warning (decreasing momentum) Event 50: Multi Divergence (Zp ≥ ZM AND ZΔ ≤ -ZM) OR (Zp ≤ -ZM AND ZΔ ≥ ZM) + |Zp| ≥ ZM AND Zv ≤ -ZM Direction: Warning (multiple divergence signals) ───────────────────────────────────────────────────────────── CATEGORY I: TREND-INTEGRATED (Events 51-60) Based on: Combined price-volume-delta trend analysis ───────────────────────────────────────────────────────────── Event 51: Trend Breakout Confirmed |Zp| ≥ ZH AND Zv ≥ ZH AND |ZΔ| ≥ ZM AND sign(ZΔ) = dirP AND dirP ≠ 0 Direction: Follows price direction Event 52: Trend Support Test Zp ≥ ZM AND Z0 ≤ Zp < ZM AND ZΔ ≥ Z0 Direction: Bullish (pullback in uptrend) Event 53: Trend Resistance Test Zp ≤ -ZM AND -ZM < Zp ≤ -Z0 AND ZΔ ≤ -Z0 Direction: Bearish (rally in downtrend) Event 54: Trend Reversal Signal sign(Zp) ≠ sign(Zp ) AND |Zp| ≥ ZM AND |Zp | ≥ ZM Direction: Follows new price direction (momentum flip) Event 55: Channel Absorption |Zp| ≤ Z0 AND Zv ≥ ZH Direction: Neutral (range-bound with volume) Event 56: Trend Continuation Volume |Zp| ≥ ZM AND Zv ≥ ZM AND sign(ZΔ) = dirP AND dirP ≠ 0 Direction: Follows price direction (healthy trend with volume) Event 57: Trend Exhaustion |Zp| ≥ ZM AND Zv ≤ -ZM AND |Zp| < |Zp | Direction: Warning (trend losing steam) Event 58: Range Breakout Pending |Zp| ≤ Z0 AND Zv ≤ -ZH AND |ZΔ| ≥ ZM Direction: Follows delta direction (compression with imbalance) Event 59: Trend Quality High |Zp| ≥ ZM AND sign(ZΔ) = dirP AND Zv ≥ Z0 AND dirP ≠ 0 Direction: Follows price direction (strong aligned signals) Event 60: Trend Quality Low |Zp| ≥ ZM AND sign(ZΔ) ≠ dirP AND dirP ≠ 0 Direction: Warning (conflicting signals) ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ TREND CHANNEL SYSTEM The trend channel system is adapted from Smart Trader Episode 03 to provide consistent visual context for price action analysis. How It Works: • Divides the chart into blocks based on Z-Score groups • Calculates OHLC (Open, High, Low, Close) for each block • Detects Higher Highs/Higher Lows (uptrend) or Lower Highs/Lower Lows (downtrend) patterns • Draws channel lines connecting block extremes • Classifies by angle: steep angles indicate trends, flat angles indicate ranges Channel Classifications: • UPTREND: Higher highs and higher lows detected • DOWNTREND: Lower highs and lower lows detected • RANGE: Channel angle below threshold (default 10 degrees) Label Information: • Trend direction (UPTREND/DOWNTREND/RANGE) • Channel boundary prices • Distance from current price (absolute and percentage) • Channel angle in degrees ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ DASHBOARD The dashboard provides a comprehensive real-time view of all Z-Score metrics and detected events. Dashboard Sections: 1. Header Row Displays indicator name and current calculation mode (CLOSED or LIVE). 2. Metric Rows (Price, Total Volume, Buy Volume, Sell Volume, Delta) Each row displays: • Value: Current metric value • Z: Calculated Z-Score • Visual: Graphical Z-bar showing position relative to mean • Status: Interpretation (Extreme High, Above Avg, Normal, Below Avg, Extreme Low) • Upper: Oldest active upper Z-Line in window (Label Mirror) • Lower: Oldest active lower Z-Line in window (Label Mirror) 3. Event Detection Section • Count of triggered events out of 60 total scenarios • Market Bias: Bull/Bear/Neutral percentage with visual bar • Strongest Event: Highest confidence event currently triggered • #2 Event: Second highest confidence event 4. Footer Shows engine type (Geometry/Intrabar), Z-Score period, calculation basis, and number of valid bars. ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ ALERT SYSTEM The indicator uses native alertcondition() functions, keeping the settings menu clean while providing comprehensive alert options in TradingView's alert dialog. Available Alert Categories: • Master Alerts: Any event, Any bullish, Any bearish, Any warning • Single Event Alerts: Individual alerts for key events (Breakout, Climax, Divergence, etc.) • Category Alerts: Alerts by event category (Price-Volume, Order-Flow, etc.) • Confluence Alerts: 2+, 3+, 4+, or 5+ aligned events • Bias Shift Alerts: 10%, 20%, or 30% shifts in market bias • High Confidence Alerts: Events with 60%+, 70%+, 80%+, or 90%+ confidence • Divergence Alerts: Price vs Volume or Price vs Delta divergences ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ DATA ACCURACY AND LIMITATIONS This indicator is 100% VOLUME-BASED and requires Lower Timeframe (LTF) intrabar data for accurate calculations when using the Intrabar method. Data Accuracy Levels: • 1T (Tick): Most accurate, real volume distribution per tick • 1S (1 Second): Reasonably accurate approximation • 15S (15 Seconds): Good approximation, longer historical data available • 1M (1 Minute): Rough approximation, maximum historical data range Backtest and Replay Limitations: • Replay mode results may differ from live trading due to data availability • For longer backtest periods, use higher LTF settings (15S or 1M) • Not all symbols/exchanges support tick-level data • Crypto and Forex typically have better LTF data availability than stocks A Note on Data Access: Higher TradingView plans provide access to more historical intrabar data, which directly impacts the accuracy of volume-based calculations. More precise volume data leads to more reliable calculations. ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ LANGUAGE SUPPORT (TRI-LINGUAL UI) This indicator includes a built-in language switch with three interface languages : • English (EN) • Türkçe (TR) • 한국어 (KO) The selected language updates key interface text such as the Dashboard headers/rows , tooltips , and the Event Engine outputs (event names, category names, and direction labels). Turkish diacritics and Korean Hangul are supported for clean, native readability. Why only three languages? Each additional language requires duplicating strings throughout the code, which increases script size/memory usage and compilation time. To keep the indicator optimized and responsive, language options are intentionally limited to three. ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ ⚠️ DISCLAIMER FOR EDUCATIONAL AND RESEARCH PURPOSES ONLY This indicator is designed as an educational and research tool based on academic market microstructure literature. It is NOT financial advice and should NOT be used as the sole basis for trading decisions. Important Notices: • Past performance does not guarantee future results • All trading involves risk of substantial loss • The indicator's signals are statistical probabilities, not certainties • Always conduct your own research and consult qualified financial advisors • The creator assumes no responsibility for trading losses Research Sources: This indicator is built upon peer-reviewed academic research from: • Journal of Financial and Quantitative Analysis (Cambridge University Press) • Journal of Finance • Journal of Financial Econometrics • MIT Working Papers • arXiv Financial Mathematics
אינדיקטור Pine Script®
מאת ‎ata_sabanci‎
4
Whale OBV Hunter [Divergence]ENGLISH: How it works This indicator automatically compares price action against volume flow (OBV). It hunts for "Divergences". Normally, if price drops, OBV should drop. If price drops but OBV rises, it means "Whales" are absorbing the selling pressure (Accumulation). How to use it Buy Signal (Accumulation): Look for Green Lines and the label "Whale Accumulation". Meaning: Price made a lower low, but OBV made a higher low (Bullish Divergence). This is a strong signal for an upward reversal. Action: Look for a LONG entry. Sell Signal (Distribution): Look for Red Lines and the label "Whale Distribution". Meaning: Price is making higher highs, but OBV is dropping (Bearish Divergence). Smart money is leaving. Action: Take profits or look for a SHORT entry. Settings (Lookback): Default is 5. If you see too much noise (too many signals), increase this number to 10 in the settings to spot only major institutional movements.
אינדיקטור Pine Script®
מאת ‎Saletrader1‎
Wyckoff Schematic by Kingshuk GhoshThe "Wyckoff Schematic" is a Pine Script indicator that automatically detects and visualizes Wyckoff Method accumulation and distribution patterns in real-time. This professional tool helps traders identify smart money movements, phase transitions, and critical market structure points. Key Features- 1. Wyckoff Pattern Detection Auto-detection of all Wyckoff phases (A through E) Accumulation patterns: SC, AR, Spring, SOS, LPS Distribution patterns: BC, UTAD, LPSY Real-time phase identification with color-coded visualization 2. Multi-Timeframe Analysis- Main chart analysis with customizable lookback period 1M Wave View showing monthly perspective in a compact overlay Daily data integration for current month analysis Swing point detection with trend lines 3. Advanced Visualization- Phase boxes with semi-transparent overlays Critical event labels with anti-clutter spacing Horizontal support/resistance lines (dynamic) Zigzag trend lines for price structure Comprehensive table showing current status and key events 4. Customizable Parameters- Adjustable lookback period (20-300 bars) Configurable volume spike multiplier Customizable display options (labels, boxes, lines) Adjustable zigzag sensitivity Configurable wave view height and swing legs Display Settings: Event labels, phase boxes, support/resistance lines Visual Settings: Label size, transparency, offset percentage Zigzag Settings: High/low length Wave View Settings: Toggle, height percentage, swing legs Color Scheme: Phase A: Red Phase B: Teal Phase C: Blue Phase D: Green Phase E: Yellow Bullish: Green Bearish: Red Alert System: Critical event alerts: SC, AR, Spring, SOS, LPS, BC, UTAD, LPSY Phase transition alerts: Markup phase entry ,Customizable alert conditions How to Use- For Beginners: Apply the indicator to any chart Enable "Auto-Detect Wyckoff Patterns" Look for colored phase boxes (A-E) Watch for critical event labels (SC, AR, Spring, etc.) Check the table in top-right corner for current status For Advanced Users: Adjust lookback period based on trading timeframe Modify volume multiplier for sensitivity Customize display to reduce clutter Use wave view for higher timeframe context Set alerts for specific Wyckoff events Unique Selling Points: Comprehensive Detection: Covers all Wyckoff phases and critical events Clean Visualization: Anti-overlap labeling, organized display Multi-Timeframe: Combines current chart with monthly perspective Educational: Helps learn Wyckoff methodology through visualization Professional: Suitable for both retail and institutional analysis Performance Notes: Uses dynamic requests for multi-timeframe data Includes max object limits to prevent performance issues Efficient calculation methods for real-time analysis Intended Users: Price action traders Wyckoff method practitioners Market structure analysts Swing traders and position traders Educational purposes for learning market manipulation patterns Works best on 4H,Daily,Weekly & Monthly Time frame Suitable for all markets (stocks, forex, crypto, futures) Support: The indicator includes comprehensive tooltips and visual cues to help users understand each Wyckoff event and phase. The table provides quick reference to current market conditions and detected patterns. This indicator transforms complex Wyckoff methodology into actionable visual signals, making institutional accumulation/distribution patterns accessible to all traders. Disclaimer: This indicator is for educational purposes only. Always practice proper risk management and combine with your own analysis before making trading decisions. Happy trading.
אינדיקטור Pine Script®
מאת ‎kingshukghosh71‎
8
Fractal Market Geometry [JOAT] Fractal Market Geometry Overview Fractal Market Geometry is an open-source overlay indicator that combines fractal analysis with harmonic pattern detection, Fibonacci retracements and extensions, Elliott Wave concepts, and Wyckoff phase identification. It provides traders with a geometric framework for understanding market structure and identifying potential reversal patterns with multi-factor signal confirmation. What This Indicator Does The indicator calculates and displays: Fractal Detection - Identifies fractal highs and lows using Williams-style pivot analysis with configurable period Fractal Dimension - Calculates market complexity using range-based dimension estimation Harmonic Patterns - Detects Gartley, Butterfly, Bat, Crab, Shark, Cypher, and ABCD patterns using Fibonacci ratios Fibonacci Retracements - Key levels at 38.2%, 50%, and 61.8% Fibonacci Extensions - Projection level at 161.8% Elliott Wave Count - Simplified wave counting based on pivot detection (1-5) Wyckoff Phase - Volume-based phase identification (Accumulation, Markup, Distribution, Neutral) Golden Spiral Levels - ATR-based support and resistance levels using phi (1.618) ratio Trend Detection - EMA crossover trend identification (20/50 EMA) How It Works Fractal detection uses a configurable period to identify swing points: detectFractalHigh(simple int period) => bool result = true float centerVal = high for i = 0 to period - 1 if high >= centerVal or high >= centerVal result := false break Harmonic pattern detection uses Fibonacci ratio analysis between swing points. Each pattern has specific ratio requirements: Gartley: AB 0.382-0.618, BC 0.382-0.886, CD 1.27-1.618 Butterfly: AB 0.382-0.5, BC 0.382-0.886, CD 1.618-2.24 Bat: AB 0.5-0.618, BC 1.13-1.618, CD 1.618-2.24 Crab: AB 0.382-0.618, BC 0.382-0.886, CD 2.24-3.618 Shark: AB 0.382-0.618, BC 1.13-1.618, CD 1.618-2.24 Cypher: AB 0.382-0.618, BC 1.13-1.414, CD 0.786-0.886 Wyckoff phase detection analyzes volume relative to price movement: wyckoffPhase(simple int period) => float avgVol = ta.sma(volume, period) float priceChg = ta.change(close, period) string phase = "NEUTRAL" if volume > avgVol * 1.5 and math.abs(priceChg) < close * 0.02 phase := "ACCUMULATION" else if volume > avgVol * 1.5 and math.abs(priceChg) > close * 0.05 phase := "MARKUP" else if volume < avgVol * 0.7 phase := "DISTRIBUTION" phase Signal Generation Signals use multi-factor confirmation for accuracy: BUY Signal: Fractal low + Uptrend (EMA20 > EMA50) + RSI 30-55 + Bullish candle + Volume confirmation SELL Signal: Fractal high + Downtrend (EMA20 < EMA50) + RSI 45-70 + Bearish candle + Volume confirmation Pattern Detection: Label appears when harmonic pattern completes at current bar Dashboard Panel (Top-Right) Dimension - Fractal dimension value (market complexity measure) Last High - Most recent fractal high price Last Low - Most recent fractal low price Pattern - Current harmonic pattern name or NONE Elliott Wave - Current wave count (Wave 1-5) or OFF Wyckoff - Current market phase or OFF Trend - BULLISH, BEARISH, or NEUTRAL based on EMA crossover Signal - BUY, SELL, or WAIT status Visual Elements Fractal Markers - Small triangles at fractal highs (down arrow) and lows (up arrow) Geometry Lines - Dashed lines connecting the most recent fractal high and low Fibonacci Levels - Clean horizontal lines at 38.2%, 50%, and 61.8% retracement levels Fibonacci Extension - Horizontal line at 161.8% extension level Golden Spiral Levels - Support and resistance lines based on ATR x 1.618 3D Fractal Field - Optional depth layers around swing levels (OFF by default) Harmonic Pattern Markers - Small diamond shapes when Crab, Shark, or Cypher patterns detected Pattern Labels - Text label showing pattern name when detected Signal Labels - BUY/SELL labels on confirmed multi-factor signals Input Parameters Fractal Period (default: 5) - Bars on each side for fractal detection Geometry Depth (default: 3) - Complexity of geometric calculations Pattern Sensitivity (default: 0.8) - Tolerance for pattern ratio matching Show Fibonacci Levels (default: true) - Display retracement levels Show Fibonacci Extensions (default: true) - Display extension level Elliott Wave Detection (default: true) - Enable wave counting Wyckoff Analysis (default: true) - Enable phase detection Golden Spiral Levels (default: true) - Display spiral support/resistance Show Fractal Points (default: true) - Display fractal markers Show Geometry Lines (default: true) - Display connecting lines Show Pattern Labels (default: true) - Display pattern name labels Show 3D Fractal Field (default: false) - Display depth layers Show Harmonic Patterns (default: true) - Display pattern markers Show Buy/Sell Signals (default: true) - Display signal labels Suggested Use Cases Identify potential reversal zones using harmonic pattern completion Use Fibonacci levels for entry, stop-loss, and target planning Monitor Wyckoff phases for accumulation/distribution awareness Track Elliott Wave counts for trend structure analysis Use fractal dimension to gauge market complexity Wait for multi-factor signal confirmation before entering trades Timeframe Recommendations Best on 1H to Daily charts. Lower timeframes produce more fractals but with less significance. Higher timeframes provide stronger levels and more reliable signals. Limitations Harmonic pattern detection uses simplified ratio ranges and may not match all textbook definitions Elliott Wave counting is basic and does not include all wave rules Wyckoff phase detection is volume-based approximation Fractal dimension calculation is simplified Signals require fractal confirmation which has inherent lag equal to the fractal period Open-Source and Disclaimer This script is published as open-source under the Mozilla Public License 2.0 for educational purposes. It does not constitute financial advice. Past performance does not guarantee future results. Always use proper risk management. - Made with passion by officialjackofalltrades
אינדיקטור Pine Script®
מאת ‎officialjackofalltrades‎