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SMC Volatility Liquidity Prothis one’s a confluence signaler. it fires “BUY CALL” / “BUY PUT” labels only when four things line up at once: trend, volatility squeeze, a liquidity sweep, and MACD momentum. quick breakdown: what each block does Trend filter (context) ema50 > ema200 ⇒ trendUp ema50 < ema200 ⇒ trendDn Plots both EMAs for visual context. Volatility compression (setup) 20-period Bollinger Bands (stdev 2). bb_squeeze is true when current band width < its 20-SMA ⇒ price is compressed (potential energy building). Liquidity sweep (trigger) Tracks 20-bar swing high/low. Long sweep: high > swingHigh ⇒ price just poked above the prior 20-bar high (took buy-side liquidity). Short sweep: low < swingLow ⇒ price just poked below the prior 20-bar low (took sell-side liquidity). MACD momentum (confirmation) Standard MACD(12,26,9) histogram. Bullish: hist > 0 and rising versus previous bar. Bearish: hist < 0 and falling. the actual entry signals LongEntry = trendUp AND bb_squeeze AND liquiditySweepLong AND macdBullish → prints a green “BUY CALL” label below the bar. ShortEntry = trendDn AND bb_squeeze AND liquiditySweepShort AND macdBearish → prints a red “BUY PUT” label above the bar. alerts & dashboard Alerts: fires when those long/short conditions hit so you can set TradingView alerts on them. On-chart dashboard (bottom-right): Trend (Bullish/Bearish/Neutral) Squeeze (Yes/No) Liquidity (Long/Short/None) Momentum (Bullish/Bearish/Neutral) Current Signal (BUY CALL / BUY PUT / WAIT) (btw the comment says “2 columns × 5 rows” but the table is actually 5 columns × 2 rows—values under each label across the row.) what it’s trying to capture (in plain english) Trade with the higher-timeframe bias (EMA 50 over 200). Enter as volatility compresses (bands tight) and a sweep grabs stops beyond a 20-bar extreme. Only pull the trigger when momentum agrees (MACD hist direction & side of zero). caveats / tips It’s an indicator, not a strategy—no entries/exits/backtests baked in. Signals are strict (4 filters), so you’ll get fewer but “cleaner” prints; still not magical. The liquidity-sweep check uses the prior bar’s 20-bar high/low ( ), so on bar close it won’t repaint; intrabar alerts may feel jumpy if you alert “on every tick.” Consider adding: Exit logic (e.g., ATR stop + take-profit, or opposite signal). Minimum squeeze duration (e.g., bb_squeeze true for N bars) to avoid one-bar dips in width. Cool-down after a signal to prevent clustering. Session/time or volume filter if you only want liquid hours. if you want, I can convert this into a backtestable strategy() version with ATR-based stops/targets and a few toggles, so you can see stats right away.
Wskaźnik Pine Script®
od lessandoval617
Whole number highlightsThis very simple indicator provides what should be a built-in TradingView feature: it highlights the whole number currency amounts (dollar, pound, euro, etc.) on your chart with a simple and unobtrusive dotted line. By default, a slightly thicker dotted line is used on whole number multiples of ten. These are important to highlight because they often act as "psychological levels" in the marketplace, especially when they coincide with more significant levels of support or resistance. They can also help provide a sense of scale to the chart, which is useful when switching between various zoom levels. It's open-source, so it can be easily combined into other indicators, which should especially be useful for those with limited plans who are allowed a limited number of indicators. Disclaimer : Use at your own risk. This indicator and the strategy described herein are not in any way financial advice, nor does the author of this script make any claims about the effectiveness of this indicator or of any related strategy, which may depend highly on the discretion and skill of the trader executing it, among many other factors outside of the author's control. The author of this script accepts no liability, and is not responsible for any trading decisions that you may or may not make as a result of this indicator. You should expect to lose money if using this indicator.
Wskaźnik Pine Script®
od KingSpork
TA█ TA Library 📊 OVERVIEW TA is a Pine Script technical analysis library. This library provides 25+ moving averages and smoothing filters , from classic SMA/EMA to Kalman Filters and adaptive algorithms, implemented based on academic research. 🎯 Core Features Academic Based - Algorithms follow original papers and formulas Performance Optimized - Pre-calculated constants for faster response Unified Interface - Consistent function design Research Based - Integrates technical analysis research 🎯 CONCEPTS Library Design Philosophy This technical analysis library focuses on providing: Academic Foundation Algorithms based on published research papers and academic standards Implementations that follow original mathematical formulations Clear documentation with research references Developer Experience Unified interface design for consistent usage patterns Pre-calculated constants for optimal performance Comprehensive function collection to reduce development time Single import statement for immediate access to all functions Each indicator encapsulated as a simple function call - one line of code simplifies complexity Technical Excellence 25+ carefully implemented moving averages and filters Support for advanced algorithms like Kalman Filter and MAMA/FAMA Optimized code structure for maintainability and reliability Regular updates incorporating latest research developments 🚀 USING THIS LIBRARY Import Library //@version=6 import DCAUT/TA/1 as dta indicator("Advanced Technical Analysis", overlay=true) Basic Usage Example // Classic moving average combination ema20 = ta.ema(close, 20) kama20 = dta.kama(close, 20) plot(ema20, "EMA20", color.red, 2) plot(kama20, "KAMA20", color.green, 2) Advanced Trading System // Adaptive moving average system kama = dta.kama(close, 20, 2, 30) = dta.mamaFama(close, 0.5, 0.05) // Trend confirmation and entry signals bullTrend = kama > kama and mamaValue > famaValue bearTrend = kama < kama and mamaValue < famaValue longSignal = ta.crossover(close, kama) and bullTrend shortSignal = ta.crossunder(close, kama) and bearTrend plot(kama, "KAMA", color.blue, 3) plot(mamaValue, "MAMA", color.orange, 2) plot(famaValue, "FAMA", color.purple, 2) plotshape(longSignal, "Buy", shape.triangleup, location.belowbar, color.green) plotshape(shortSignal, "Sell", shape.triangledown, location.abovebar, color.red) 📋 FUNCTIONS REFERENCE ewma(source, alpha) Calculates the Exponentially Weighted Moving Average with dynamic alpha parameter. Parameters: source (series float) : Series of values to process. alpha (series float) : The smoothing parameter of the filter. Returns: (float) The exponentially weighted moving average value. dema(source, length) Calculates the Double Exponential Moving Average (DEMA) of a given data series. Parameters: source (series float) : Series of values to process. length (simple int) : Number of bars for the moving average calculation. Returns: (float) The calculated Double Exponential Moving Average value. tema(source, length) Calculates the Triple Exponential Moving Average (TEMA) of a given data series. Parameters: source (series float) : Series of values to process. length (simple int) : Number of bars for the moving average calculation. Returns: (float) The calculated Triple Exponential Moving Average value. zlema(source, length) Calculates the Zero-Lag Exponential Moving Average (ZLEMA) of a given data series. This indicator attempts to eliminate the lag inherent in all moving averages. Parameters: source (series float) : Series of values to process. length (simple int) : Number of bars for the moving average calculation. Returns: (float) The calculated Zero-Lag Exponential Moving Average value. tma(source, length) Calculates the Triangular Moving Average (TMA) of a given data series. TMA is a double-smoothed simple moving average that reduces noise. Parameters: source (series float) : Series of values to process. length (simple int) : Number of bars for the moving average calculation. Returns: (float) The calculated Triangular Moving Average value. frama(source, length) Calculates the Fractal Adaptive Moving Average (FRAMA) of a given data series. FRAMA adapts its smoothing factor based on fractal geometry to reduce lag. Developed by John Ehlers. Parameters: source (series float) : Series of values to process. length (simple int) : Number of bars for the moving average calculation. Returns: (float) The calculated Fractal Adaptive Moving Average value. kama(source, length, fastLength, slowLength) Calculates Kaufman's Adaptive Moving Average (KAMA) of a given data series. KAMA adjusts its smoothing based on market efficiency ratio. Developed by Perry J. Kaufman. Parameters: source (series float) : Series of values to process. length (simple int) : Number of bars for the efficiency calculation. fastLength (simple int) : Fast EMA length for smoothing calculation. Optional. Default is 2. slowLength (simple int) : Slow EMA length for smoothing calculation. Optional. Default is 30. Returns: (float) The calculated Kaufman's Adaptive Moving Average value. t3(source, length, volumeFactor) Calculates the Tilson Moving Average (T3) of a given data series. T3 is a triple-smoothed exponential moving average with improved lag characteristics. Developed by Tim Tillson. Parameters: source (series float) : Series of values to process. length (simple int) : Number of bars for the moving average calculation. volumeFactor (simple float) : Volume factor affecting responsiveness. Optional. Default is 0.7. Returns: (float) The calculated Tilson Moving Average value. ultimateSmoother(source, length) Calculates the Ultimate Smoother of a given data series. Uses advanced filtering techniques to reduce noise while maintaining responsiveness. Based on digital signal processing principles by John Ehlers. Parameters: source (series float) : Series of values to process. length (simple int) : Number of bars for the smoothing calculation. Returns: (float) The calculated Ultimate Smoother value. kalmanFilter(source, processNoise, measurementNoise) Calculates the Kalman Filter of a given data series. Optimal estimation algorithm that estimates true value from noisy observations. Based on the Kalman Filter algorithm developed by Rudolf Kalman (1960). Parameters: source (series float) : Series of values to process. processNoise (simple float) : Process noise variance (Q). Controls adaptation speed. Optional. Default is 0.05. measurementNoise (simple float) : Measurement noise variance (R). Controls smoothing. Optional. Default is 1.0. Returns: (float) The calculated Kalman Filter value. mcginleyDynamic(source, length) Calculates the McGinley Dynamic of a given data series. McGinley Dynamic is an adaptive moving average that adjusts to market speed changes. Developed by John R. McGinley Jr. Parameters: source (series float) : Series of values to process. length (simple int) : Number of bars for the dynamic calculation. Returns: (float) The calculated McGinley Dynamic value. mama(source, fastLimit, slowLimit) Calculates the Mesa Adaptive Moving Average (MAMA) of a given data series. MAMA uses Hilbert Transform Discriminator to adapt to market cycles dynamically. Developed by John F. Ehlers. Parameters: source (series float) : Series of values to process. fastLimit (simple float) : Maximum alpha (responsiveness). Optional. Default is 0.5. slowLimit (simple float) : Minimum alpha (smoothing). Optional. Default is 0.05. Returns: (float) The calculated Mesa Adaptive Moving Average value. fama(source, fastLimit, slowLimit) Calculates the Following Adaptive Moving Average (FAMA) of a given data series. FAMA follows MAMA with reduced responsiveness for crossover signals. Developed by John F. Ehlers. Parameters: source (series float) : Series of values to process. fastLimit (simple float) : Maximum alpha (responsiveness). Optional. Default is 0.5. slowLimit (simple float) : Minimum alpha (smoothing). Optional. Default is 0.05. Returns: (float) The calculated Following Adaptive Moving Average value. mamaFama(source, fastLimit, slowLimit) Calculates Mesa Adaptive Moving Average (MAMA) and Following Adaptive Moving Average (FAMA). Parameters: source (series float) : Series of values to process. fastLimit (simple float) : Maximum alpha (responsiveness). Optional. Default is 0.5. slowLimit (simple float) : Minimum alpha (smoothing). Optional. Default is 0.05. Returns: ( ) Tuple containing values. laguerreFilter(source, length, gamma, order) Calculates the standard N-order Laguerre Filter of a given data series. Standard Laguerre Filter uses uniform weighting across all polynomial terms. Developed by John F. Ehlers. Parameters: source (series float) : Series of values to process. length (simple int) : Length for UltimateSmoother preprocessing. gamma (simple float) : Feedback coefficient (0-1). Lower values reduce lag. Optional. Default is 0.8. order (simple int) : The order of the Laguerre filter (1-10). Higher order increases lag. Optional. Default is 8. Returns: (float) The calculated standard Laguerre Filter value. laguerreBinomialFilter(source, length, gamma) Calculates the Laguerre Binomial Filter of a given data series. Uses 6-pole feedback with binomial weighting coefficients. Developed by John F. Ehlers. Parameters: source (series float) : Series of values to process. length (simple int) : Length for UltimateSmoother preprocessing. gamma (simple float) : Feedback coefficient (0-1). Lower values reduce lag. Optional. Default is 0.5. Returns: (float) The calculated Laguerre Binomial Filter value. superSmoother(source, length) Calculates the Super Smoother of a given data series. SuperSmoother is a second-order Butterworth filter from aerospace technology. Developed by John F. Ehlers. Parameters: source (series float) : Series of values to process. length (simple int) : Period for the filter calculation. Returns: (float) The calculated Super Smoother value. rangeFilter(source, length, multiplier) Calculates the Range Filter of a given data series. Range Filter reduces noise by filtering price movements within a dynamic range. Parameters: source (series float) : Series of values to process. length (simple int) : Number of bars for the average range calculation. multiplier (simple float) : Multiplier for the smooth range. Higher values increase filtering. Optional. Default is 2.618. Returns: ( ) Tuple containing filtered value, trend direction, upper band, and lower band. qqe(source, rsiLength, rsiSmooth, qqeFactor) Calculates the Quantitative Qualitative Estimation (QQE) of a given data series. QQE is an improved RSI that reduces noise and provides smoother signals. Developed by Igor Livshin. Parameters: source (series float) : Series of values to process. rsiLength (simple int) : Number of bars for the RSI calculation. Optional. Default is 14. rsiSmooth (simple int) : Number of bars for smoothing the RSI. Optional. Default is 5. qqeFactor (simple float) : QQE factor for volatility band width. Optional. Default is 4.236. Returns: ( ) Tuple containing smoothed RSI and QQE trend line. sslChannel(source, length) Calculates the Semaphore Signal Level (SSL) Channel of a given data series. SSL Channel provides clear trend signals using moving averages of high and low prices. Parameters: source (series float) : Series of values to process. length (simple int) : Number of bars for the moving average calculation. Returns: ( ) Tuple containing SSL Up and SSL Down lines. ma(source, length, maType) Calculates a Moving Average based on the specified type. Universal interface supporting all moving average algorithms. Parameters: source (series float) : Series of values to process. length (simple int) : Number of bars for the moving average calculation. maType (simple MaType) : Type of moving average to calculate. Optional. Default is SMA. Returns: (float) The calculated moving average value based on the specified type. atr(length, maType) Calculates the Average True Range (ATR) using the specified moving average type. Developed by J. Welles Wilder Jr. Parameters: length (simple int) : Number of bars for the ATR calculation. maType (simple MaType) : Type of moving average to use for smoothing. Optional. Default is RMA. Returns: (float) The calculated Average True Range value. macd(source, fastLength, slowLength, signalLength, maType, signalMaType) Calculates the Moving Average Convergence Divergence (MACD) with customizable MA types. Developed by Gerald Appel. Parameters: source (series float) : Series of values to process. fastLength (simple int) : Period for the fast moving average. slowLength (simple int) : Period for the slow moving average. signalLength (simple int) : Period for the signal line moving average. maType (simple MaType) : Type of moving average for main MACD calculation. Optional. Default is EMA. signalMaType (simple MaType) : Type of moving average for signal line calculation. Optional. Default is EMA. Returns: ( ) Tuple containing MACD line, signal line, and histogram values. dmao(source, fastLength, slowLength, maType) Calculates the Dual Moving Average Oscillator (DMAO) of a given data series. Uses the same algorithm as the Percentage Price Oscillator (PPO), but can be applied to any data series. Parameters: source (series float) : Series of values to process. fastLength (simple int) : Period for the fast moving average. slowLength (simple int) : Period for the slow moving average. maType (simple MaType) : Type of moving average to use for both calculations. Optional. Default is EMA. Returns: (float) The calculated Dual Moving Average Oscillator value as a percentage. continuationIndex(source, length, gamma, order) Calculates the Continuation Index of a given data series. The index represents the Inverse Fisher Transform of the normalized difference between an UltimateSmoother and an N-order Laguerre filter. Developed by John F. Ehlers, published in TASC 2025.09. Parameters: source (series float) : Series of values to process. length (simple int) : The calculation length. gamma (simple float) : Controls the phase response of the Laguerre filter. Optional. Default is 0.8. order (simple int) : The order of the Laguerre filter (1-10). Optional. Default is 8. Returns: (float) The calculated Continuation Index value. 📚 RELEASE NOTES v1.0 (2025.09.24) ✅ 25+ technical analysis functions ✅ Complete adaptive moving average series (KAMA, FRAMA, MAMA/FAMA) ✅ Advanced signal processing filters (Kalman, Laguerre, SuperSmoother, UltimateSmoother) ✅ Performance optimized with pre-calculated constants and efficient algorithms ✅ Unified function interface design following TradingView best practices ✅ Comprehensive moving average collection (DEMA, TEMA, ZLEMA, T3, etc.) ✅ Volatility and trend detection tools (QQE, SSL Channel, Range Filter) ✅ Continuation Index - Latest research from TASC 2025.09 ✅ MACD and ATR calculations supporting multiple moving average types ✅ Dual Moving Average Oscillator (DMAO) for arbitrary data series analysis
Biblioteka Pine Script®
od DCAUT
Multi Momentum 10/21/42/63 — Histogram + 2xSMAMY MM INDICATOR INDIRED BY KARADI It averages four rate-of-change snapshots of price, all anchored at today’s close. If “Show as %” is on, the value is multiplied by 100. Each term is a simple momentum/ROC over a different lookback. Combining 10, 21, 42, 63 bars blends short, medium, and intermediate horizons into one number. Positive MM → average upward pressure across those horizons; negative MM → average downward pressure. Why those lengths? They roughly stack into ~2× progression (10→21≈2×10, 21→42=2×21, 63≈1.5×42). That creates a “multi-scale” momentum that’s less noisy than a single fast ROC but more responsive than a long ROC alone. How to read the panel Gray histogram = raw Multi-Momentum value each bar. SMA Fast/Slow lines (defaults 12 & 26 over the MM values) = smoothing of the histogram to show the trend of momentum itself. Typical signals Zero-line context: Above 0 → bullish momentum regime on average. Below 0 → bearish regime. Crosses of SMA Fast & Slow: momentum trend shifts (fast above slow = improving momentum; fast below slow = deteriorating). Histogram vs SMA lines: widening distance suggests strengthening momentum; narrowing suggests momentum is fading. Divergences: price makes a new high/low but MM doesn’t → potential exhaustion. Compared to a classic ROC A single ROC(20) is very sensitive to that one window. MM averages several windows, smoothing idiosyncrasies (e.g., a one-off spike 21 bars ago) and reducing “lookback luck.” Settings & customization Lookbacks (10/21/42/63): you can tweak for your asset/timeframe; the idea is to mix short→medium horizons. Percent vs raw ratio: percent is easier to compare across symbols. SMA lengths: shorter = more reactive but choppier; longer = smoother but slower. Practical tips Use regime + signal: trade longs primarily when MM>0 and fast SMA>slow SMA; consider shorts when MM<0 and fast
Wskaźnik Pine Script®
od yoni7715
Buy & Sell by AnupamKafleThis indicator provides Buy and Sell signals based on a combination of classic technical analysis tools: EMA Crossovers, RSI, MACD, and optional Bollinger Bands. ✅ Buy signals are shown as green arrows below bars ✅ Sell signals are shown as red arrows above bars 📊 Logic Overview: EMA Crossover: Fast EMA crossing over the Slow EMA = Bullish signal RSI Filter: RSI below oversold threshold = Buy condition, above overbought = Sell condition MACD Filter: MACD line crossing above Signal line = Buy, crossing below = Sell Bollinger Bands (optional): Buy when price breaks below lower band, Sell when price breaks above upper band All filters can be turned on or off individually to customize the signal conditions to your strategy. ⚙️ Settings Include: Enable/Disable each indicator (EMA, RSI, MACD, BB) Custom lengths for EMA, RSI, MACD, and BB Adjustable RSI thresholds and Bollinger Band deviation 🔔 Alerts: Built-in alert conditions for Buy and Sell signals allow you to set up real-time notifications.
Wskaźnik Pine Script®
od AnupamKafle
Golden Cross Master Filter by Carlos ChavezForget noisy Golden/Death Cross signals. This is the **Golden Cross Master Filter** – built for traders who demand institutional-level confirmation. ✅ Exact EMA cross points with circle markers ✅ ATR / ADX / DI+ / DI- / Volume filters ✅ Gap% detection ✅ Visual OK/X dashboard ✅ Instant BUY/SELL labels & ready-to-use alerts Cut the noise. Trade only the strongest crosses. 🚀 Golden Cross Master Filter is a professional tool to detect Golden and Death Crosses with institutional-grade filtering. 🚀 Features: - ✅ ATR / ADX / DI+/DI- / Volume conditions - ✅ Gap% detection (daily gap between yesterday’s close and today’s open) - ✅ Visual dashboard with OK/X status - ✅ Exact circle markers at EMA cross points - ✅ Ready-to-use BUY/SELL labels when filters are confirmed - ✅ Built-in alerts for easy automation This indicator is designed for intraday and swing traders who rely on EMA crosses but want to eliminate false signals. It works across multiple timeframes (10m, 1h, 4h, Daily) and adapts to different trading styles. Whether you trade CALLs/PUTs or just want stronger confirmation for Golden/Death Crosses, this filter helps you focus only on high-probability setups.
Wskaźnik Pine Script®
od Carlostradercr
2
EMA & VWAP Precision Overlay📢WELCOME TO FUTURE YOU! 📈 This isn’t your grandma’s moving average script. This is pure alpha visualization. We're talking 9, 21, 50, and 200 EMAs. Plus VWAP Session AND Anchored VWAP — all dynamically labeled so you know exactly where price is cooking. 🚀 Features: Toggle lines like a boss Label everything (or nothing, if you’re into minimalist flexing) Anchored VWAP for sniper entries (you pick the start) Labels shift forward so your candles don’t cry Built for traders who actually care about levels and not just vibes. Whether you’re scalping dog coins or trend-riding BTC, this thing keeps your chart clean, informative, and slightly intimidating. I use it. It works. You should probably use it too. If it gives you psychic powers — you're welcome. If it doesn't — still looks cool.
Wskaźnik Pine Script®
od TRUQUANT_
1
QTrade Golden, Bronze & Death, Bubonic Cross AlertsThis indicator highlights key EMA regime shifts with simple, color-coded triangles: - Golden / Death Cross — 50 EMA crossing above/below the 200 EMA. - Bronze / Bubonic Cross — 50 EMA crossing above/below the 100 EMA. - Early-Warning Proxy — tiny triangles for the 4 EMA vs. 200 EMA (4↑200 and 4↓200). These often fire before the 50/100 and 50/200 crosses. No text clutter on the chart—just triangles. Colors: gold (50↑200), red (50↓200), darker-yellow bronze (50↑100), burgundy (50↓100), turquoise (4↑200), purple (4↓200). What it tells you (in order of warning → confirmation) - First warning: 4 EMA crosses the 200 EMA (proxy for price shifting around the 200 line). - Second warning: 50 EMA crosses the 100 EMA (Bronze/Bubonic). - Confirmation: 50 EMA crosses the 200 EMA (Golden/Death). Alerts included - Golden Cross (50↑200) and Death Cross (50↓200) - Bronze Cross (50↑100) and Bubonic Cross (50↓100) - 4 EMA vs. 200 EMA crosses (up & down) — early-warning proxy - Price–100 EMA events (touch/cross, if enabled in settings)
Wskaźnik Pine Script®
od gbeckett
NASDAQ VWAP Distance Histogram (Multi-Symbol)📊 VWAP Distance Histogram (Multi-Symbol) This custom indicator plots a histogram of price strength relative to the VWAP (Volume-Weighted Average Price). The zero line is VWAP. Histogram bars above zero = price trading above VWAP (strength). Histogram bars below zero = price trading below VWAP (weakness). Unlike a standard VWAP overlay, this tool lets you monitor multiple symbols at once and aggregates them into a single, easy-to-read histogram. 🔑 Features Multi-Symbol Support → Track up to 10 different tickers plus the chart symbol. Aggregation Options → Choose between average or median deviation across enabled symbols. Percent or Raw Values → Display distance from VWAP as % of price or raw price points. Smoothing → Apply EMA smoothing to calm intraday noise. Color-Coded Histogram → Green above VWAP, red below. Alerts → Trigger when the aggregate crosses above/below VWAP. Heads-Up Table → Shows number of symbols tracked and current aggregate reading. ⚡ Use Cases Market Breadth via VWAP → Monitor whether your basket of stocks is trading above or below VWAP. Index Substitution → Create your own “mini index” by tracking a hand-picked set of tickers. Intraday Confirmation → Use aggregate VWAP strength/weakness to confirm entries and exits. Relative Strength Spotting → Switch on/off specific tickers to see who’s holding above VWAP vs. breaking down. 🛠️ Settings Include Chart Symbol → Toggle to include the current chart’s ticker. Smoothing → EMA length (set to 0 to disable). Percent Mode → Show results as % of price vs. raw difference. Aggregate Mode → Average or median across all active symbols. Symbol Slots (S1–S10) → Enter tickers to track alongside the chart. ⚠️ Notes Works best on intraday charts since VWAP is session-based. Designed for confirmation, not as a standalone entry/exit signal. Ensure correct symbol format (e.g., NASDAQ:AAPL if needed). ✅ Tip: Combine this with your regular price action strategy. For example, if your setup triggers long and the histogram is well above zero, that’s added confirmation. If it’s below zero, caution — the basket shows weakness.
Wskaźnik Pine Script®
od Marketscope