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MC WITH ALERTS DINESH SETHIYAManipulation Candle (MC): A candlestick that initially suggests price movement in one direction but then reverses, manipulating liquidity and closing in the opposite direction. Types of MCs: Bullish MC: Takes out the previous candle's low, reverses, takes out the previous candle's high, and closes above it. Bearish MC: Takes out the previous candle's high, reverses, takes out the previous candle's low, and closes below it. Ideal MC Characteristic: The rejection wick (bottom wick for bullish MC, top wick for bearish MC) should be larger than the directional wick.
Pine Script® 인디케이터
astatrader24의
Stochastic 6TF by jjuiiStochastic 6TF by J is a Multi-Timeframe (MTF) Stochastic indicator that displays %K values from up to 6 different timeframes in a single window. This helps traders analyze momentum across short, medium, and long-term perspectives simultaneously. Features: - Supports 6 customizable timeframes (e.g., 5m, 15m, 1h, 4h, 1D, 1W) - Option to show/hide each timeframe line - Standard reference levels (20 / 50 / 80) with background shading - Smoothed %K for clearer visualization Best for: - Cross-timeframe momentum analysis - Spotting aligned Overbought / Oversold signals - Confirming market trends and timing entries/exits ------------------------------------------------------------- Stochastic 6TF by J คืออินดิเคเตอร์ Stochastic Multi Timeframe (MTF) ที่สามารถแสดงค่า %K จากหลายกรอบเวลา (สูงสุด 6 TF) ไว้ในหน้าต่างเดียว ช่วยให้นักเทรดมองเห็นโมเมนตัมของราคา ทั้งระยะสั้น กลาง และยาว พร้อมกัน คุณสมบัติ: - เลือกกรอบเวลาได้ 6 ชุด (เช่น 5m, 15m, 1h, 4h, 1D, 1W) - สามารถเปิด/ปิดการแสดงผลแต่ละ TF ได้ - มีเส้นแนวรับ/แนวต้านมาตรฐาน (20 / 50 / 80) - ใช้เส้น %K ที่ถูกปรับค่าเฉลี่ยให้เรียบขึ้นเพื่ออ่านง่าย เหมาะสำหรับ: - การดูโมเมนตัมข้ามกรอบเวลา - หาจังหวะ Overbought / Oversold ที่สอดคล้องกันหลาย TF - ใช้ยืนยันแนวโน้มและหาจังหวะเข้า-ออกอย่างแม่นยำมากขึ้น
Pine Script® 인디케이터
jjuii의
Key Levels: Open & Midday🔹 Opening Candle (9:30 AM New York Time) Plots the high and low of the first 5-minute candle after the market opens. 🔹 12:30 PM Candle (3 hours after open) Plots the high and low of the candle formed exactly 3 hours after the market opens. These levels are useful for: Identifying support/resistance zones. Creating breakout or reversal strategies. Tracking intraday momentum shifts. 📌 Important Notes: Designed for 5-minute charts. Make sure your chart is set to New York time (exchange time) for accurate levels. Happy Trading!
Pine Script® 인디케이터
l6_5의
1
Adaptive Market Regime Identifier [LuciTech]What it Does: AMRI visually identifies and categorizes the market into six primary regimes directly on your chart using a color-coded background. These regimes are: -Strong Bull Trend: Characterized by robust upward momentum and low volatility. -Weak Bull Trend: Indicates upward momentum with less conviction or higher volatility. -Strong Bear Trend: Defined by powerful downward momentum and low volatility. -Weak Bear Trend: Suggests downward momentum with less force or increased volatility. -Consolidation: Periods of low volatility and sideways price action. -Volatile Chop: High volatility without clear directional bias, often seen during transitions or indecision. By clearly delineating these states, AMRI helps traders quickly grasp the overarching market context, enabling them to apply strategies best suited for the current conditions (e.g., trend-following in strong trends, range-bound strategies in consolidation, or caution in volatile chop). How it Works (The Adaptive Edge) AMRI achieves its adaptive classification by continuously analyzing three core market dimensions, with each component dynamically adjusting to current market conditions: 1.Adaptive Moving Average (KAMA): The indicator utilizes the Kaufman Adaptive Moving Average (KAMA) to gauge trend direction and strength. KAMA is unique because it adjusts its smoothing period based on market efficiency (noise vs. direction). In trending markets, it becomes more responsive, while in choppy markets, it smooths out noise, providing a more reliable trend signal than static moving averages. 2.Adaptive Average True Range (ATR): Volatility is measured using an adaptive version of the Average True Range. Similar to KAMA, this ATR dynamically adjusts its sensitivity to reflect real-time changes in market volatility. This helps AMRI differentiate between calm, ranging markets and highly volatile, directional moves or chaotic periods. 3.Normalized Slope Analysis: The slope of the KAMA is normalized against the Adaptive ATR. This normalization provides a robust measure of trend strength that is relative to the current market volatility, making the thresholds for strong and weak trends more meaningful across different instruments and timeframes. These adaptive components work in concert to provide a nuanced and responsive classification of the market regime, minimizing lag and reducing false signals often associated with fixed-parameter indicators. Key Features & Originality: -Dynamic Regime Classification: AMRI stands out by not just indicating trend or range, but by classifying the type of market regime, offering a higher-level analytical framework. This is a meta-indicator that provides context for all other trading tools. -Adaptive Core Metrics: The use of KAMA and an Adaptive ATR ensures that the indicator remains relevant and responsive across diverse market conditions, automatically adjusting to changes in volatility and trend efficiency. This self-adjusting nature is a significant advantage over indicators with static lookback periods. -Visual Clarity: The color-coded background provides an immediate, at-a-glance understanding of the current market regime, reducing cognitive load and allowing for quicker decision-making. -Contextual Trading: By identifying the prevailing regime, AMRI empowers traders to select and apply strategies that are most effective for that specific environment, helping to avoid costly mistakes of using a trend-following strategy in a ranging market, or vice-versa. -Originality: While components like KAMA and ATR are known, their adaptive integration into a comprehensive, multi-regime classification system, combined with normalized slope analysis for trend strength, offers a novel approach to market analysis not commonly found in publicly available indicators.
Pine Script® 인디케이터
TradesLuci의
Multi-Symbol Volatility Tracker with Range DetectionMulti-Symbol Volatility Tracker with Range Detection 🎯 Main Purpose: This indicator is specifically designed for scalpers to quickly identify symbols with high volatility that are currently in ranging conditions . It helps you spot the perfect opportunities for buying at lows and selling at highs repeatedly within the same trading session. 📊 Table Data Explanation: The indicator displays a comprehensive table with 5 columns for 4 major symbols (GOLD, SILVER, NASDAQ, SP500): SYMBOL: The trading instrument being analyzed VOLATILITY: Color-coded volatility levels (NORMAL/HIGH/EXTREME) based on ATR values Last Candle %: The percentage range of the most recent 5-minute candle Last 5 Candle Avg %: Average percentage range over the last 5 candles RANGE: Shows "YES" (blue) or "NO" (gray) indicating if the symbol is currently ranging 🔍 How to Identify Trading Opportunities: Look for symbols that combine these characteristics: RANGE column shows "YES" (highlighted in blue) - This means the symbol is moving sideways, perfect for range trading VOLATILITY shows "HIGH" or "EXTREME" - Ensures there's enough movement for profitable scalping Higher candlestick percentages - Indicates larger candle ranges, meaning more profit potential per trade ⚡ Optimal Usage: Best Timeframe: Works optimally on 5-minute charts where the ranging patterns are most reliable for scalping Trading Strategy: When you find a symbol with "YES" in the RANGE column, switch to that symbol and look for opportunities to buy near the lows and sell near the highs of the ranging pattern Risk Management: Higher volatility symbols offer more profit potential but require tighter risk management ⚙️ Settings: ATR Length: Adjusts the Average True Range calculation period (default: 14) Range Sensitivity: Fine-tune range detection sensitivity (0.1-2.0, lower = more sensitive) 💡 Pro Tips: The indicator updates in real-time, so monitor for symbols switching from "NO" to "YES" in the RANGE column Combine HIGH/EXTREME volatility with RANGE: YES for the most profitable scalping setups Use the candlestick percentages to gauge potential profit per trade - higher percentages mean more movement The algorithm uses advanced statistical analysis including standard deviation, linear regression slopes, and range efficiency to accurately detect ranging conditions Perfect for day traders and scalpers who want to quickly identify which symbols offer the best ranging opportunities for consistent buy-low, sell-high strategies.
Pine Script® 인디케이터
igaudette의
cd_bsl_ssl_CxGeneral This indicator is designed to show the levels where stop-loss orders from buyers and sellers are most likely clustered. Swing levels formed on the aligned higher time frame (HTF) are displayed on the chart as Buy Side Liquidity (BSL) and Sell Side Liquidity (SSL). ________________________________________ Menu & Usage • HTF Selection: o In “Auto” mode, the HTF is selected automatically. o In “Manual” mode, the user can choose the HTF themselves. • Bar Control: By adjusting the bar control value, the user can define the number of bars required for a valid BSL or SSL sweep. This option helps keep the number of alerts under control. ________________________________________ I’d be happy to hear your feedback and suggestions. Happy trading! 🎉
Pine Script® 인디케이터
cdikici71의
7
Institutional Levels (CNN) - [PhenLabs]📊Institutional Levels (Convolutional Neural Network-inspired) Version : PineScript™v6 📌Description The CNN-IL Institutional Levels indicator represents a breakthrough in automated zone detection technology, combining convolutional neural network principles with advanced statistical modeling. This sophisticated tool identifies high-probability institutional trading zones by analyzing pivot patterns, volume dynamics, and price behavior using machine learning algorithms. The indicator employs a proprietary 9-factor logistic regression model that calculates real-time reaction probabilities for each detected zone. By incorporating CNN-inspired filtering techniques and dynamic zone management, it provides traders with unprecedented accuracy in identifying where institutional money is likely to react to price action. 🚀Points of Innovation ● CNN-Inspired Pivot Analysis - Advanced binning system using convolutional neural network principles for superior pattern recognition ● Real-Time Probability Engine - Live reaction probability calculations using 9-factor logistic regression model ● Dynamic Zone Intelligence - Automatic zone merging using Intersection over Union (IoU) algorithms ● Volume-Weighted Scoring - Time-of-day volume Z-score analysis for enhanced zone strength assessment ● Adaptive Decay System - Intelligent zone lifecycle management based on touch frequency and recency ● Multi-Filter Architecture - Optional gradient, smoothing, and Difference of Gaussians (DoG) convolution filters 🔧Core Components ● Pivot Detection Engine - Advanced pivot identification with configurable left/right bars and ATR-normalized strength calculations ● Neural Network Binning - Price level clustering using CNN-inspired algorithms with ATR-based bin sizing ● Logistic Regression Model - 9-factor probability calculation including distance, width, volume, VWAP deviation, and trend analysis ● Zone Management System - Intelligent creation, merging, and decay algorithms for optimal zone lifecycle control ● Visualization Layer - Dynamic line drawing with opacity-based scoring and optional zone fills 🔥Key Features ● High-Probability Zone Detection - Automatically identifies institutional levels with reaction probabilities above configurable thresholds ● Real-Time Probability Scoring - Live calculation of zone reaction likelihood using advanced statistical modeling ● Session-Aware Analysis - Optional filtering to specific trading sessions for enhanced accuracy during active market hours ● Customizable Parameters - Full control over lookback periods, zone sensitivity, merge thresholds, and probability models ● Performance Optimized - Efficient processing with controlled update frequencies and pivot processing limits ● Non-Repainting Mode - Strict mode available for backtesting accuracy and live trading reliability 🎨Visualization ● Dynamic Zone Lines - Color-coded support and resistance levels with opacity reflecting zone strength and confidence scores ● Probability Labels - Real-time display of reaction probabilities, touch counts, and historical hit rates for active zones ● Zone Fills - Optional semi-transparent zone highlighting for enhanced visual clarity and immediate pattern recognition ● Adaptive Styling - Automatic color and opacity adjustments based on zone scoring and statistical significance 📖Usage Guidelines ● Lookback Bars - Default 500, Range 100-1000, Controls the historical data window for pivot analysis and zone calculation ● Pivot Left/Right - Default 3, Range 1-10, Defines the pivot detection sensitivity and confirmation requirements ● Bin Size ATR units - Default 0.25, Range 0.1-2.0, Controls price level clustering granularity for zone creation ● Base Zone Half-Width ATR units - Default 0.25, Range 0.1-1.0, Sets the minimum zone width in ATR units for institutional level boundaries ● Zone Merge IoU Threshold - Default 0.5, Range 0.1-0.9, Intersection over Union threshold for automatic zone merging algorithms ● Max Active Zones - Default 5, Range 3-20, Maximum number of zones displayed simultaneously to prevent chart clutter ● Probability Threshold for Labels - Default 0.6, Range 0.3-0.9, Minimum reaction probability required for zone label display and alerts ● Distance Weight w1 - Controls influence of price distance from zone center on reaction probability ● Width Weight w2 - Adjusts impact of zone width on probability calculations ● Volume Weight w3 - Modifies volume Z-score influence on zone strength assessment ● VWAP Weight w4 - Controls VWAP deviation impact on institutional level significance ● Touch Count Weight w5 - Adjusts influence of historical zone interactions on probability scoring ● Hit Rate Weight w6 - Controls prior success rate impact on future reaction likelihood predictions ● Wick Penetration Weight w7 - Modifies wick penetration analysis influence on probability calculations ● Trend Weight w8 - Adjusts trend context impact using ADX analysis for directional bias assessment ✅Best Use Cases ● Swing Trading Entries - Enter positions at high-probability institutional zones with 60%+ reaction scores ● Scalping Opportunities - Quick entries and exits around frequently tested institutional levels ● Risk Management - Use zones as dynamic stop-loss and take-profit levels based on institutional behavior ● Market Structure Analysis - Identify key institutional levels that define current market structure and sentiment ● Confluence Trading - Combine with other technical indicators for high-probability trade setups ● Session-Based Strategies - Focus analysis during high-volume sessions for maximum effectiveness ⚠️Limitations ● Historical Pattern Dependency - Algorithm effectiveness relies on historical patterns that may not repeat in changing market conditions ● Computational Intensity - Complex calculations may impact chart performance on lower-end devices or with multiple indicators ● Probability Estimates - Reaction probabilities are statistical estimates and do not guarantee actual market outcomes ● Session Sensitivity - Performance may vary significantly between different market sessions and volatility regimes ● Parameter Sensitivity - Results can be highly dependent on input parameters requiring optimization for different instruments 💡What Makes This Unique ● CNN Architecture - First indicator to apply convolutional neural network principles to institutional-level detection ● Real-Time ML Scoring - Live machine learning probability calculations for each zone interaction ● Advanced Zone Management - Sophisticated algorithms for zone lifecycle management and automatic optimization ● Statistical Rigor - Comprehensive 9-factor logistic regression model with extensive backtesting validation ● Performance Optimization - Efficient processing algorithms designed for real-time trading applications 🔬How It Works ● Multi-timeframe pivot identification - Uses configurable sensitivity parameters for advanced pivot detection ● ATR-normalized strength calculations - Standardizes pivot significance across different volatility regimes ● Volume Z-score integration - Enhanced pivot weighting based on time-of-day volume patterns ● Price level clustering - Neural network binning algorithms with ATR-based sizing for zone creation ● Recency decay applications - Weights recent pivots more heavily than historical data for relevance ● Statistical filtering - Eliminates low-significance price levels and reduces market noise ● Dynamic zone generation - Creates zones from statistically significant pivot clusters with minimum support thresholds ● IoU-based merging algorithms - Combines overlapping zones while maintaining accuracy using Intersection over Union ● Adaptive decay systems - Automatic removal of outdated or low-performing zones for optimal performance ● 9-factor logistic regression - Incorporates distance, width, volume, VWAP, touch history, and trend analysis ● Real-time scoring updates - Zone interaction calculations with configurable threshold filtering ● Optional CNN filters - Gradient detection, smoothing, and Difference of Gaussians processing for enhanced accuracy 💡Note This indicator represents advanced quantitative analysis and should be used by traders familiar with statistical modeling concepts. The probability scores are mathematical estimates based on historical patterns and should be combined with proper risk management and additional technical analysis for optimal trading decisions.
Pine Script® 인디케이터
PhenLabs의
3
Elliott Wave Auto (Impulse + Correction) — stable deleteAutomatic pivot detection: The script identifies swing highs and swing lows using ta.pivothigh and ta.pivotlow. Impulse wave labeling (1–5): Detects 5 alternating pivots and labels them as waves 1 to 5. Uses green/red labels for impulse and correction legs. Connects waves with blue lines for visual clarity. Corrective wave labeling (A–B–C): Detects the next 3 alternating pivots after wave 5. Labels them as A, B, C with orange lines connecting them. Dynamic cleanup: Stores labels and lines in arrays. Deletes previous drawings automatically before redrawing, keeping the chart clean. Optional pivot markers: Plots tiny triangles for detected pivots (green for lows, red for highs). Information table: Displays the direction (Bullish/Bearish) and percentage move of the 1–5 impulse waves. Pine Script v5 compliant: Uses str.tostring() and array-based deletion to avoid tostring() or line.deleteall() errors. If you want, I can also add an alert feature to notify you when a full impulse + corrective wave pattern completes. This makes it actionable for trading.
Pine Script® 인디케이터
shravanreddy0808의
EMA Cross 99//@version=6 indicator("EMA Strategie (Indikator mit Entry/TP/SL)", overlay=true, max_lines_count=500, max_labels_count=500) // === Inputs === rrRatio = input.float(3.0, "Risk:Reward (TP/SL)", minval=1.0, step=0.5) sess = input.session("0700-1900", "Trading Session (lokal)") // === EMAs === ema9 = ta.ema(close, 9) ema50 = ta.ema(close, 50) ema200 = ta.ema(close, 200) // === Session === inSession = not na(time(timeframe.period, sess)) // === Trend + Cross === bullTrend = (ema9 > ema200) and (ema50 > ema200) bearTrend = (ema9 < ema200) and (ema50 < ema200) crossUp = ta.crossover(ema9, ema50) crossDown = ta.crossunder(ema9, ema50) // === Pullback Confirm === longTouch = bullTrend and crossUp and (low <= ema9) longConfirm = longTouch and (close > open) and (close > ema9) shortTouch = bearTrend and crossDown and (high >= ema9) shortConfirm = shortTouch and (close < open) and (close < ema9) // === Entry Signale === longEntry = longConfirm and inSession shortEntry = shortConfirm and inSession // === SL & TP Berechnung === longSL = ema50 longTP = close + (close - longSL) * rrRatio shortSL = ema50 shortTP = close - (shortSL - close) * rrRatio // === Long Markierungen === if (longEntry) // Entry line.new(bar_index, close, bar_index+20, close, color=color.green, style=line.style_dotted, width=2) label.new(bar_index, close, "Entry", style=label.style_label_left, color=color.green, textcolor=color.white, size=size.tiny) // TP line.new(bar_index, longTP, bar_index+20, longTP, color=color.green, style=line.style_solid, width=2) label.new(bar_index, longTP, "TP", style=label.style_label_left, color=color.green, textcolor=color.white, size=size.tiny) // SL line.new(bar_index, longSL, bar_index+20, longSL, color=color.red, style=line.style_solid, width=2) label.new(bar_index, longSL, "SL", style=label.style_label_left, color=color.red, textcolor=color.white, size=size.tiny) // === Short Markierungen === if (shortEntry) // Entry line.new(bar_index, close, bar_index+20, close, color=color.red, style=line.style_dotted, width=2) label.new(bar_index, close, "Entry", style=label.style_label_left, color=color.red, textcolor=color.white, size=size.tiny) // TP line.new(bar_index, shortTP, bar_index+20, shortTP, color=color.red, style=line.style_solid, width=2) label.new(bar_index, shortTP, "TP", style=label.style_label_left, color=color.red, textcolor=color.white, size=size.tiny) // SL line.new(bar_index, shortSL, bar_index+20, shortSL, color=color.green, style=line.style_solid, width=2) label.new(bar_index, shortSL, "SL", style=label.style_label_left, color=color.green, textcolor=color.white, size=size.tiny) // === EMAs anzeigen === plot(ema9, "EMA 9", color=color.yellow, linewidth=1) plot(ema50, "EMA 50", color=color.orange, linewidth=1) plot(ema200, "EMA 200", color=color.blue, linewidth=1) // === Alerts === alertcondition(longEntry, title="Long Entry", message="EMA Strategie: LONG Einstiegssignal") alertcondition(shortEntry, title="Short Entry", message="EMA Strategie: SHORT Einstiegssignal")
Pine Script® 인디케이터
gepp_german의