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KeyLevel - AOCKeyLevel - AOC ✨ Features📈 Session Levels: Tracks high, low, and open prices for Asian, London, and New York sessions.📅 Multi-Timeframe Levels: Plots previous day, week, month, quarter, and yearly open/high/low levels.⚙️ Preset Modes: Choose Scalp, Intraday, or Swing presets for tailored level displays.🎨 Customizable Visuals: Adjust colors, line styles, and label abbreviations for clarity.🖼️ Legend Table: Displays a color-coded legend for quick reference to session and period levels.🔧 Flexible Settings: Enable/disable specific sessions or levels and customize UTC offsets. 🛠️ How to Use Add to Chart: Apply the "KeyLevel - AOC" indicator on TradingView. Configure Inputs: Preset: Select Scalp, Intraday, or Swing, or use custom settings. Session Levels: Toggle Asian, London, NY sessions and their open/high/low lines. Period Levels: Enable/disable previous day, week, month, quarter, or yearly levels. Visuals: Adjust colors, line widths, and label abbreviations. Legend: Show/hide the legend table for level identification. Analyze: Monitor key levels for support/resistance and session-based price action. Track Trends: Use levels to identify breakouts, reversals, or consolidation zones. 🎯 Why Use It? Dynamic Levels: Tracks critical price levels across multiple timeframes for comprehensive analysis. Session Focus: Highlights key session price points for intraday trading strategies. Customizable: Tailor displayed levels and visuals to match your trading style. User-Friendly: Clear lines, labels, and legend table simplify price level tracking. 📝 Notes Ensure timeframe compatibility (e.g., avoid daily charts for session levels). Use M5 or higher timeframes for accurate session tracking; some levels disabled on M5. Combine with indicators like RSI or MACD for enhanced trading signals. Adjust UTC offset if session times misalign with your broker’s timezone.
Indicador Pine Script®
por AlchimistOfCrypto
Smart Money Concepts Probability (Expo) RitSmart Money Concepts Probability (Expo) — v2 Overview This indicator maps market structure using confirmed swing pivots and quantifies the follow-through of SMC events—CHoCH, SMS, and BMS—as real-time probabilities. It adds robust filters (ATR swing size, multi-timeframe bias) and statistically honest display (Laplace smoothing and Wilson confidence bands) to reduce noise and make the stats you see on the chart closer to what actually plays out. How it works Detects confirmed swing highs/lows with ta.pivothigh/ta.pivotlow. Tracks a structure state machine: bias flips to CHoCH (±1), confirms to SMS (±2), then BMS/continuations (>|±2|). Logs every transition as a success (continuation) or failure (reversion) and computes: Raw Win%, Laplace-smoothed probability, and Wilson confidence interval. Draws Premium/Discount/Mid zones between the latest swing high/low and shows contextual probability labels at the extremes. Filters & Upgrades ATR swing filter: ignores tiny breaks; only counts pivots that exceed a user-set multiple of ATR. MTF bias gate: only allows bullish sequences when price is above an HTF moving average (and vice-versa). Label throttle: minimum bar spacing between plotted events to keep charts readable. Response vs. Period: choose short-term or long-term structure resolution. Outputs & Visuals On-chart labels/lines for CHoCH/SMS/BMS (bull/bear colors). Top-right table with Wins, Losses, Profitability, Laplace p̂, and Wilson CI (with sample-size guard). Probability labels near current Up/Dn extremes. Optional alerts containing ticker, timeframe, and the current probability summary. Using the stats Profitability = all-time raw follow-through rate. Laplace p̂ stabilizes small-N swings. Wilson CI shows a conservative range; the lower bound is a practical “floor.” For best results, align entries with MTF bias, ensure swings pass the ATR filter, and favor entries in Discount (for longs) / Premium (for shorts) when the structure agrees. Notes This is an analytical tool, not a signal service. Always validate on your markets/timeframes and combine with risk management.
Indicador Pine Script®
por yuji52289
Savitzky-Golay Hampel Filter | AlphaNattSavitzky-Golay Hampel Filter | AlphaNatt A revolutionary indicator combining NASA's satellite data processing algorithms with robust statistical outlier detection to create the most scientifically advanced trend filter available on TradingView. "This is the same mathematics that processes signals from the Hubble Space Telescope and analyzes data from the Large Hadron Collider - now applied to financial markets." ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 🚀 SCIENTIFIC PEDIGREE Savitzky-Golay Filter Applications: NASA: Satellite telemetry and space probe data processing CERN: Particle physics data analysis at the LHC Pharmaceutical: Chromatography and spectroscopy analysis Astronomy: Processing signals from radio telescopes Medical: ECG and EEG signal processing Hampel Filter Usage: Aerospace: Cleaning sensor data from aircraft and spacecraft Manufacturing: Quality control in precision engineering Seismology: Earthquake detection and analysis Robotics: Sensor fusion and noise reduction ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 🧬 THE MATHEMATICS 1. Savitzky-Golay Filter The SG filter performs local polynomial regression on data points: Fits a polynomial of degree n to a sliding window of data Evaluates the polynomial at the center point Preserves higher moments (peaks, valleys) unlike moving averages Maintains derivative information for true momentum analysis Originally published in Analytical Chemistry (1964) Mathematical Properties: Optimal smoothing in the least-squares sense Preserves statistical moments up to polynomial order Exact derivative calculation without additional lag Superior frequency response vs traditional filters 2. Hampel Filter A robust outlier detector based on Median Absolute Deviation (MAD): Identifies outliers using robust statistics Replaces spurious values with polynomial-fitted estimates Resistant to up to 50% contaminated data MAD is 1.4826 times more robust than standard deviation Outlier Detection Formula: |x - median| > k × 1.4826 × MAD Where k is the threshold parameter (typically 3 for 99.7% confidence) ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 💎 WHY THIS IS SUPERIOR vs Moving Averages: Preserves peaks and valleys (critical for catching tops/bottoms) No lag penalty for smoothness Maintains derivative information Polynomial fitting > simple averaging vs Other Filters: Outlier immunity (Hampel component) Scientifically optimal smoothing Preserves higher-order features Used in billion-dollar research projects Unique Advantages: Feature Preservation: Maintains market structure while smoothing Spike Immunity: Ignores false breakouts and stop hunts Derivative Accuracy: True momentum without additional indicators Scientific Validation: 60+ years of academic research ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ ⚙️ PARAMETER OPTIMIZATION 1. Polynomial Order (2-5) 2 (Quadratic): Maximum smoothing, gentle curves 3 (Cubic): Balanced smoothing and responsiveness (recommended) 4-5 (Higher): More responsive, preserves more features 2. Window Size (7-51) Must be odd number Larger = smoother but more lag Formula: 2×(desired smoothing period) + 1 Default 21 = analyzes 10 bars each side 3. Hampel Threshold (1.0-5.0) 1.0: Aggressive outlier removal (68% confidence) 2.0: Moderate outlier removal (95% confidence) 3.0: Conservative outlier removal (99.7% confidence) (default) 4.0+: Only extreme outliers removed 4. Final Smoothing (1-7) Additional WMA smoothing after filtering 1 = No additional smoothing 3-5 = Recommended for most timeframes 7 = Ultra-smooth for position trading ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 📊 TRADING STRATEGIES Signal Recognition: Cyan Line: Bullish trend with positive derivative Pink Line: Bearish trend with negative derivative Color Change: Trend reversal with polynomial confirmation 1. Trend Following Strategy Enter when price crosses above cyan filter Exit when filter turns pink Use filter as dynamic stop loss Best in trending markets 2. Mean Reversion Strategy Enter long when price touches filter from below in uptrend Enter short when price touches filter from above in downtrend Exit at opposite band or filter color change Excellent for range-bound markets 3. Derivative Strategy (Advanced) The SG filter preserves derivative information Acceleration = second derivative > 0 Enter on positive first derivative + positive acceleration Exit on negative second derivative (momentum slowing) ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 📈 PERFORMANCE CHARACTERISTICS Strengths: Outlier Immunity: Ignores stop hunts and flash crashes Feature Preservation: Catches tops/bottoms better than MAs Smooth Output: Reduces whipsaws significantly Scientific Basis: Not curve-fitted or optimized to markets Considerations: Slight lag in extreme volatility (all filters have this) Requires odd window sizes (mathematical requirement) More complex than simple moving averages Best with liquid instruments ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 🔬 SCIENTIFIC BACKGROUND Savitzky-Golay Publication: "Smoothing and Differentiation of Data by Simplified Least Squares Procedures" - Abraham Savitzky & Marcel Golay - Analytical Chemistry, Vol. 36, No. 8, 1964 Hampel Filter Origin: "Robust Statistics: The Approach Based on Influence Functions" - Frank Hampel et al., 1986 - Princeton University Press These techniques have been validated in thousands of scientific papers and are standard tools in: NASA's Jet Propulsion Laboratory European Space Agency CERN (Large Hadron Collider) MIT Lincoln Laboratory Max Planck Institutes ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 💡 ADVANCED TIPS News Trading: Lower Hampel threshold before major events to catch spikes Scalping: Use Order=2 for maximum smoothness, Window=11 for responsiveness Position Trading: Increase Window to 31+ for long-term trends Combine with Volume: Strong trends need volume confirmation Multiple Timeframes: Use daily for trend, hourly for entry Watch the Derivative: Filter color changes when first derivative changes sign ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ ⚠️ IMPORTANT NOTICES Not financial advice - educational purposes only Past performance does not guarantee future results Always use proper risk management Test settings on your specific instrument and timeframe No indicator is perfect - part of complete trading system ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 🏆 CONCLUSION The Savitzky-Golay Hampel Filter represents the pinnacle of scientific signal processing applied to financial markets. By combining polynomial regression with robust outlier detection, traders gain access to the same mathematical tools that: Guide spacecraft to other planets Detect gravitational waves from black holes Analyze particle collisions at near light-speed Process signals from deep space This isn't just another indicator - it's rocket science for trading . "When NASA needs to separate signal from noise in billion-dollar missions, they use these exact algorithms. Now you can too." ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ Developed by AlphaNatt Version: 1.0 Release: 2025 Pine Script: v6 "Where Space Technology Meets Market Analysis" Not financial advice. Always DYOR
Indicador Pine Script®
por AlphaNatt
1
Laguerre-Kalman Adaptive Filter | AlphaNattLaguerre-Kalman Adaptive Filter |AlphaNatt A sophisticated trend-following indicator that combines Laguerre polynomial filtering with Kalman optimal estimation to create an ultra-smooth, low-lag trend line with exceptional noise reduction capabilities. "The perfect trend line adapts to market conditions while filtering out noise - this indicator achieves both through advanced mathematical techniques rarely seen in retail trading." ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 🎯 KEY FEATURES Dual-Filter Architecture: Combines two powerful filtering methods for superior performance Adaptive Volatility Adjustment: Automatically adapts to market conditions Minimal Lag: Laguerre polynomials provide faster response than traditional moving averages Optimal Noise Reduction: Kalman filtering removes market noise while preserving trend Clean Visual Design: Color-coded trend visualization (cyan/pink) ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 📊 THE MATHEMATICS 1. Laguerre Filter Component The Laguerre filter uses a cascade of four all-pass filters with a single gamma parameter: 4th order IIR (Infinite Impulse Response) filter Single parameter (gamma) controls all filter characteristics Provides smoother output than EMA with similar lag Based on Laguerre polynomials from quantum mechanics 2. Kalman Filter Component Implements a simplified Kalman filter for optimal estimation: Prediction-correction algorithm from aerospace engineering Dynamically adjusts based on estimation error Provides mathematically optimal estimate of true price trend Reduces noise while maintaining responsiveness 3. Adaptive Mechanism Monitors market volatility in real-time Adjusts filter parameters based on current conditions More responsive in trending markets More stable in ranging markets ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ ⚙️ INDICATOR SETTINGS Laguerre Gamma (0.1-0.99): Controls filter smoothness. Higher = smoother but more lag Adaptive Period (5-100): Lookback for volatility calculation Kalman Noise Reduction (0.1-2.0): Higher = more noise filtering Trend Threshold (0.0001-0.01): Minimum change to register trend shift Recommended Settings: Scalping: Gamma: 0.6, Period: 10, Noise: 0.3 Day Trading: Gamma: 0.8, Period: 20, Noise: 0.5 (default) Swing Trading: Gamma: 0.9, Period: 30, Noise: 0.8 Position Trading: Gamma: 0.95, Period: 50, Noise: 1.2 ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 📈 TRADING SIGNALS Primary Signals: Cyan Line: Bullish trend - price above filter and filter ascending Pink Line: Bearish trend - price below filter or filter descending Color Change: Potential trend reversal point Entry Strategies: Trend Continuation: Enter on pullback to filter line in trending market Trend Reversal: Enter on color change with volume confirmation Breakout: Enter when price crosses filter with momentum Exit Strategies: Exit long when line turns from cyan to pink Exit short when line turns from pink to cyan Use filter as trailing stop in strong trends ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ ✨ ADVANTAGES OVER TRADITIONAL INDICATORS Vs. Moving Averages: Significantly less lag while maintaining smoothness Adaptive to market conditions Better noise filtering Vs. Standard Filters: Dual-filter approach provides optimal estimation Mathematical foundation from signal processing Self-adjusting parameters Vs. Other Trend Indicators: Cleaner signals with fewer whipsaws Works across all timeframes No repainting or lookahead bias ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 🎓 MATHEMATICAL BACKGROUND The Laguerre filter was developed by John Ehlers, applying Laguerre polynomials (used in quantum mechanics) to financial markets. These polynomials provide an elegant solution to the lag-smoothness tradeoff that plagues traditional moving averages. The Kalman filter, developed by Rudolf Kalman in 1960, is used in everything from GPS systems to spacecraft navigation. It provides the mathematically optimal estimate of a system's state given noisy measurements. By combining these two approaches, this indicator achieves what neither can alone: a smooth, responsive trend line that adapts to market conditions while filtering out noise. ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 💡 TIPS FOR BEST RESULTS Confirm with Volume: Strong trends should have increasing volume Multiple Timeframes: Use higher timeframe for trend, lower for entry Combine with Momentum: RSI or MACD can confirm filter signals Market Conditions: Adjust noise parameter based on market volatility Backtesting: Always test settings on your specific instrument ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ ⚠️ IMPORTANT NOTES No indicator is perfect - always use proper risk management Best suited for trending markets May produce false signals in choppy/ranging conditions Not financial advice - for educational purposes only ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 🚀 CONCLUSION The Laguerre-Kalman Adaptive Filter represents a significant advancement in technical analysis, bringing institutional-grade mathematical techniques to retail traders. Its unique combination of polynomial filtering and optimal estimation provides a clean, reliable trend-following tool that adapts to changing market conditions. Whether you're scalping on the 1-minute chart or position trading on the daily, this indicator provides clear, actionable signals with minimal false positives. "In the world of technical analysis, the edge comes from using better mathematics. This indicator delivers that edge." ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ Developed by AlphaNatt | Professional Quantitative Trading Tools Version: 1.0 Last Updated: 2025 Pine Script: v6 License: Open Source Not financial advice. Always DYOR
Indicador Pine Script®
por AlphaNatt
2
Commodity Channel Index DualThe CCI Dual is a custom TradingView indicator built in Pine Script v5, designed to help traders identify potential buy and sell signals using two Commodity Channel Index (CCI) oscillators. It combines a shorter-period CCI (default: 14) for quick momentum detection with a longer-period CCI (default: 50) for confirmation, focusing on mean-reversion opportunities in overbought or oversold conditions. This setup is particularly suited for volatile markets like cryptocurrencies on higher timeframes (e.g., 3-day charts), where it highlights reversals by requiring both CCIs to cross out of extreme zones within a short window (default: 3 bars). The indicator plots the CCIs, customizable bands (inner: 100, OB/OS: 175, outer: 200), dynamic fills for visual emphasis, background highlights for signals, and alert conditions for notifications. How It Works The indicator calculates two CCIs based on user-defined lengths and source (default: close price): CCI Calculation: CCI measures price deviation from its average, using the formula: CCI = (Typical Price - Simple Moving Average) / (0.015 * Mean Deviation). The short CCI reacts faster to price changes, while the long CCI provides smoother, trend-aware confirmation. Overbought/Oversold Levels: Customizable thresholds define extremes (Overbought at +175, Oversold at -175 by default). Bands are plotted at inner (±100), mid (±175 dashed), and outer (±200) levels, with gray fills for the outer zones. Dynamic Fills: The longer CCI is used to shade areas beyond OB/OS levels in red (overbought) or green (oversold) for quick visual cues. Signals: Buy Signal: Triggers when both CCIs cross above the Oversold level (-175) within the signal window (3 bars). This suggests a potential upward reversal from an oversold state. Sell Signal: Triggers when both cross below the Overbought level (+175) within the window, indicating a possible downward reversal. Visuals and Alerts: Buy signals highlight the background green, sells red. Separate alertconditions allow setting TradingView alerts for buys or sells independently. Customization: Adjust lengths, levels, and window via inputs to fit your timeframe or asset—e.g., higher OB/OS for crypto volatility. This logic reduces noise by requiring dual confirmation, but like all oscillators, it can produce false signals in strong trends where prices stay extended. To mitigate false signals (e.g., in trending markets), layer the CCI Dual with MACD (default: 12,26,9) and RSI (default: 14) for multi-indicator confirmation: With MACD: Only take CCI buys if the MACD line is above the signal line (or histogram positive), confirming bullish momentum. For sells, require MACD bearish crossover. This filters counter-trend signals by aligning with trend strength—e.g., ignore CCI sells if MACD shows upward momentum. With RSI: Confirm CCI oversold buys only if RSI is below 30 and rising (or shows bullish divergence). For overbought sells, RSI above 70 and falling. This adds overextension validation, reducing whipsaws in crypto trends. I made this customizable for you to find what works best for your asset you are trading. I trade the 6 hour and 3 day timeframe mainly on major cryptocurrency pairs. I hope you enjoy this script and it serves you well.
Indicador Pine Script®
por MonkeyPhone
Student Wyckoff RS Symbol/MarketRelative Strength Indicator STUDENT WYCKOFF RS SYMBOL/MARKET Description The Relative Strength (RS) Indicator compares the price performance of the current financial instrument (e.g., a stock) against another instrument (e.g., an index or another stock). It is calculated by dividing the closing price of the first instrument by the closing price of the second, then multiplying by 100. This provides a percentage ratio that shows how one instrument outperforms or underperforms another. The indicator helps traders identify strong or weak assets, spot market leaders, or evaluate an asset’s performance relative to a benchmark. Key Features Relative Strength Calculation: Divides the closing price of the current instrument by the closing price of the second instrument and multiplies by 100 to express the ratio as a percentage. Simple Moving Average (SMA): Applies a customizable Simple Moving Average (default period: 14) to smooth the data and highlight trends. Visualization: Displays the Relative Strength as a blue line, the SMA as an orange line, and colors bars (blue for rising, red for falling) to indicate changes in relative strength. Flexibility: Allows users to select the second instrument via an input field and adjust the SMA period. Applications Market Comparison: Assess whether a stock is outperforming an index (e.g., S&P 500 or MOEX) to identify strong assets for investment. Sector Analysis: Compare stocks within a sector or against a sector ETF to pinpoint leaders. Trend Analysis: Use the rise or fall of the RS line and its SMA to gauge the strength of an asset’s trend relative to another instrument. Trade Timing: Bar coloring helps quickly identify changes in relative strength, aiding short-term trading decisions. Interpretation Rising RS: Indicates the first instrument is outperforming the second (e.g., a stock growing faster than an index). Falling RS: Suggests the first instrument is underperforming. SMA as a Trend Filter: If the RS line is above the SMA, it may signal strengthening performance; if below, weakening performance. Settings Instrument 2: Ticker of the second instrument (default: QQQ). SMA Period: Period for the Simple Moving Average (default: 14). Notes The indicator works on any timeframe but requires accurate ticker input for the second instrument. Ensure data for both instruments is available on the selected timeframe for precise analysis.
Indicador Pine Script®
por StudentWyckoff
Smart Money Footprint & Cost Basis Engine [AlgoPoint]Smart Money Footprint & Cost Basis Engine This indicator is a comprehensive market analysis tool designed to identify the "footprints" of Smart Money (institutions, whales) and pinpoint high-probability reaction zones. Instead of relying on lagging averages, this engine analyzes the very structure of the market to find where large players have shown their hand. How It Works: The Core Logic The indicator operates on a multi-stage confirmation process to identify and validate Smart Money zones: Smart Money Detection (The Trigger): The engine first scans the chart for signs of intense, urgent buying or selling. It does this by identifying Fair Value Gaps (FVGs) created by large, high-volume Displacement Candles. This is our initial Point of Interest (POI). Cost Basis Calculation (The Average Price): Once a potential Smart Money move is detected, the indicator calculates the Volume-Weighted Average Price (VWAP) for that specific move. This gives us a highly accurate estimate of the average price at which the large players entered their positions. Historical Confirmation (The "Memory"): This is the indicator's most unique feature. It checks its historical database to see if a similar Smart Money move (in the same direction) has occurred in the same price area in the past. If a match is found, the zone's significance is confirmed. Verified Cost Basis Zone (The Final Output): A zone that passes all the above checks is drawn on the chart as a high-probability Verified Cost Basis Zone. These are the "memory zones" where the market is likely to react upon a re-visit. How to Use This Indicator Cost Basis Zones (The Boxes): Green Boxes: Bullish zones where Smart Money likely accumulated positions. When the price returns here, a BUY reaction is expected. Red Boxes: Bearish zones where Smart Money likely distributed positions. When the price returns here, a SELL reaction is expected. Zone Strength (★★★): Each zone is created with a star rating. More stars indicate a higher-confidence zone (based on factors like volume intensity and historical confirmation). BUY/SELL Signals: A signal is only generated when the price enters a zone AND the confirmation filters (if enabled in the settings) are passed. Zone Statuses: Green/Red: Active and waiting to be tested. Gray: The zone has been tested, and a signal was produced. Dark Gray (Invalidated): The zone was broken decisively and is no longer considered valid support/resistance. Key Settings Signal Accuracy Filters: You can enable/disable three powerful filters to balance signal quantity and quality: Momentum Confirmation (Stoch): Waits for momentum to align with the zone's direction. Candlestick Confirmation (Engulfing): Waits for a strong reversal candle inside the zone. Lower Timeframe MSS Confirmation: The most advanced filter; waits for a trend shift on a lower timeframe before giving a signal. Historical Confirmation: Require Historical Confirmation: Toggle the "Memory" feature on/off. Turn it off to see all potential SM zones. Tolerance Calculation Method: Choose between a dynamic ATR Multiplier (recommended for all-around use) or a fixed Percentage to define the zone size.
Indicador Pine Script®
por Iamalala
Goldbach Time Indicator🔧 Key Fixes Applied: 1. Time Validation & Bounds Checking: Hour/Minute Bounds: Ensures hours stay 0-23, minutes stay 0-59 Edge Case Handling: Prevents invalid time calculations from causing missing data UTC Conversion Safety: Better handling of timezone edge cases 2. Enhanced Value Validation: NA Checking: Validates all calculated values before using them Goldbach Detection: Only flags valid, non-NA values as Goldbach hits Plot Safety: Prevents plotting invalid or NA values that could cause gaps 3. Improved Plot Logic: Core Level Colors: Blue for core levels (29,35,71,77), yellow/lime/orange for regular hits Debug Mode Enhanced: Shows all calculations with gray dots when enabled Better Filtering: Only plots positive, valid values for minus calculations 4. Background vs Dots Issue: The large green/blue background you see suggests the indicator is detecting Goldbach times correctly, but the dots weren't plotting due to validation issues. This should now be fixed.
Indicador Pine Script®
por RizwanFXCoder
Smart Money Windows- X7Smart Money Windows 📊💰 Unlock the secret moves of the big players! This indicator highlights key liquidity traps, smart money zones, and market kill zones for the Asian, London, and New York sessions. See where the pros hide their orders and spot potential price flips before they happen! 🚀🔥 Features: Visual session boxes with high/low/mid levels 🟪🟫 NY session shifted 60 mins for precise timing 🕒 Perfect for spotting traps, inducements & smart money maneuvers 🎯 Works on Forex, crypto, and stocks 💹 Get in the “Smart Money Window” and trade like the pros! 💸🔑 By HH
Indicador Pine Script®
por hasanhuss2