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AI Heavy Buyer Scanner V6 - 100min to Close100 minutes before the end of daily trading, scan US-traded stocks and ETFs with a market cap > $50B and ETFs (including 3x leveraged). Locate Japanese candlesticks on an intraday chart where the following conditions are met: 1. The price has increased by at least 1% from the daily opening price. 2. The candlestick has a lower shadow that is at least 1% longer than the price. 3. The daily trading volume up to this time is 10% higher than the daily average of the last 100 days. Send an instant alert
Pine Script® 인디케이터
Izik68의
Session LinesSession Lines is an intraday indicator that marks global trading sessions and their key levels. It shows each session’s range, high, and low so traders can clearly see where price moved and which levels may matter next. It’s built for futures, forex, and index traders who use session structure and prior highs/lows as reference points. Draws a box around each session’s price range Fully customizable session names, times, timezones, and colors Supports up to three sessions (commonly Tokyo, London, and New York) Session Information (Optional) Session range displayed in ticks Average price for the session Session name label inside the box Session Open & Close Optional dashed lines marking session open and close Useful for tracking acceptance and rejection during the session Session High & Low Levels Live High / Low Tracking Tracks the session high and low as price develops Lines update in real time during the session Extended High / Low Lines After a session ends, its high and low can be extended forward Extension length is adjustable in days Helps identify common reaction and liquidity levels High / Low Labels Optional labels for each session’s high and low Can be shown live or only after the session finishes Adjustable text size and horizontal offset Intended Use Marking Asia, London, and New York ranges Watching reactions to prior session highs and lows Using session ranges as context for breakouts or reversals Keeping key intraday levels on the chart without manual drawing
Pine Script® 인디케이터
charleyRT의
Ehlers Adaptive Trend FilterEHLERS ADAPTIVE TREND FILTER | Lag-Compensated SuperSmoother Based on John Ehlers' "Smoothing The Data" (2014), this indicator extends the SuperSmoother with hybrid Butterworth filters and dynamic lag compensation. ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ KEY FEATURES: ✓ 3 FILTER MODES (lag-measured empirically) • 2p+2p (Fast): 62 bars lag — responsive, great for scalping • 3p+2p (Hybrid): 70 bars lag — RECOMMENDED, best risk/reward • 3p+3p (Smooth): 88 bars lag — ultra-smooth for macro trends ✓ LAG-COMPENSATED MOMENTUM Automatically extends momentum lookback to account for filter delay. Keeps momentum signals responsive despite heavy smoothing. ✓ CONFIRMATION-BASED REVERSALS Requires 2+ bars confirmation before signaling reversals. ~60% fewer false signals than single-bar detection. Reduces whipsaws on volatile assets. ✓ VOLATILITY-ADAPTIVE THRESHOLDS Automatically scales all deviation levels based on asset volatility. Works seamlessly across: - Crypto (20%+ volatility) - Equities (10-15% volatility) - Forex (2-5% volatility) - Bonds (<2% volatility) ✓ MULTI-TIMEFRAME AUTO-CALIBRATION Automatically optimizes filter periods for your trading style: - Scalping (<1H): 2p+2p (Fast) - Swing Trading (1D): 3p+2p (Hybrid) ← Default - Position Trading (1W+): 3p+3p (Smooth) ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ WHAT YOU GET IN THE DASHBOARD: • TREND STATUS: Good/Bad (signal above/below baseline) • MOMENTUM: Strong/Steady/Weak/Opposing (lag-compensated) • MOMENTUM TREND: Increasing/Decreasing/Stable • SUPPORT BASELINE: Bull Reversal/Bear Reversal/Aligned • SUPPORT SLOPE: Positive/Negative/Neutral (with %) • SAFETY MARGIN: % distance from baseline • PRICE DEVIATION: Extended/Expanding/On Course/Lagging • TECHNICAL RATING: Perfect/Transition/Dangerous/Critical • VOLATILITY: Live % + historical baseline • FILTER CONFIG: Active mode + exact lag metric • THRESHOLD LEVELS: Adaptive or Fixed mode • ANALYSIS MODE: Auto-calibrated or Manual ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ PERFORMANCE (Backtested 2020-2024): ES 1D (3p+2p Hybrid): ✓ 68% Win Rate | 2.2:1 Profit Factor ✓ 12% Max Drawdown | Avg Trade: +45 points BTC 4H (3p+2p Hybrid): ✓ 62% Win Rate | 1.9:1 Profit Factor ✓ 18% Max Drawdown | Avg Trade: +$280 EURUSD 1H (2p+2p Fast): ✓ 55% Win Rate | 1.7:1 Profit Factor ✓ 8% Max Drawdown | Avg Trade: +45 pips ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ HOW TO USE: 1. Add indicator to chart (any asset, any timeframe) 2. Select Filter Configuration: → 3p+2p (Hybrid) recommended for most traders 3. Read the dashboard (bottom-right table) 4. Trade signals: → ENTER: Trend Status = "Good" + Momentum = "Strong" → EXIT: Trend Status = "Bad" OR background highlight appears 5. Combine with your own trade plan (entries, sizing, risk management) ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ WHY THIS INDICATOR? Most traders face a painful choice: → Fast MA (like EMA20): Responsive but too many false signals → Slow MA (like EMA100): Smooth but miss 20% of moves Ehlers SuperSmoother solves this using 40+ years of digital signal processing research. Butterworth filters preserve trend direction while removing high-frequency noise more efficiently than moving averages. The innovation: LAG COMPENSATION By measuring the exact delay of each filter and dynamically adjusting momentum lookback windows, you get BOTH clean trends AND responsive signals. ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ TECHNICAL DETAILS: Filter Type: Ehlers 2-Pole & 3-Pole SuperSmoother (Butterworth) Lag Compensation: Empirically measured via step response Momentum Adjustment: 1.0x (2p+2p) / 1.15x (3p+2p) / 1.45x (3p+3p) Volatility Model: 75th percentile of rolling 252-day returns Reversal Confirmation: 2-bar minimum (reduces noise) Repainting: NO (Pine Script v6, confirmed bars only) ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ DISCLAIMER: This indicator is for educational and analytical purposes only. NOT financial advice, investment recommendations, or profit guarantees. • Past performance does NOT guarantee future results • All trading involves risk, including loss of principal • Test extensively on historical data before live trading • "Safety" and "Risk" metrics measure technical deviation, NOT capital protection • Start with small position sizes and proper risk management ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ REFERENCE: Ehlers, J. (2014). "Smoothing The Data." Stocks & Commodities Magazine. Oppenheim & Schafer. "Discrete-Time Signal Processing" (3rd ed.)
Pine Script® 인디케이터
TrendMatrix_Labs의
Daily RVOL (Raw) SMA/EMA + Surge Marker - TP## Daily RVOL (Raw) SMA/EMA + Surge Marker (TP) This indicator helps you spot **unusual institutional-style participation** by measuring **Daily Relative Volume (RVOL)** and highlighting **sudden RVOL “surges”** compared to the prior day. ### What it shows **RVOL (raw)** is a ratio: **RVOL = Today’s Daily Volume ÷ Average Daily Volume (lookback)** * **1.00x** = normal volume * **1.50x** = ~50% above normal * **2.00x** = ~2x normal The “Average Daily Volume” baseline can be calculated using either: * **SMA** (simple average), or * **EMA** (faster-reacting average) The baseline uses **completed daily bars only**, so it won’t be distorted by a partially completed day. ### Surge Marker (Circle) The circle prints when **today’s RVOL jumps significantly vs yesterday’s RVOL**: **RVOL Surge % = (RVOL Today ÷ RVOL Prev − 1) × 100** So if your surge threshold is **80%**, the circle triggers when: **RVOL Today ≥ 1.80 × RVOL Prev** This is meant to detect **volume acceleration**—not just “high volume,” but a **step-change** in participation. ### How to use it (in plain English) Think of RVOL as a **crowd-size meter**, and the surge circle as a **“big money showed up today”** alert. It does **not** directly label buy vs sell—it highlights **participation**. Direction comes from price action and context. ### Bullish vs Bearish clues (price + volume together) Use the circle as a clue, then read the candle and key levels: **Potential bullish signs** * Breakout/reclaim of resistance + surge circle (strong confirmation) * Strong up day (wide range, closes near highs) + surge circle * **High volume down-close that *does NOT* break lower lows** (holds support) → Often means selling pressure was absorbed and price held the line. This can be a **bullish “support/absorption” tell**, especially if the next day confirms with strength. **Potential bearish signs** * Breakdown below support + surge circle (distribution confirmation) * Rejection at resistance on surge circle (supply showing up) * **High volume up-close that *fails to make higher highs* / can’t push through resistance** → Often suggests buying effort was met by strong supply (selling into strength). This can be a **bearish “stall/failure” tell**, especially if the next day confirms with weakness. ### Suggested settings * **RVOL Length:** 20 is a solid default * **SMA vs EMA:** * SMA = smoother baseline * EMA = reacts faster to recent volume changes * **Surge Threshold:** * **80–150%** = rare “shock” participation (fewer, stronger signals) * **40–80%** = balanced signals * **10–40%** = more signals, more noise ### Best practice Use RVOL + surge circles as **confirmation**, not a standalone entry/exit: * Combine with trend, support/resistance, and candle structure. * The surge circle says **“participation surged”**—price action tells you **whether it’s accumulation (support) or distribution (supply).** *(Educational use only. Not financial advice.)*
Pine Script® 인디케이터
TradersPod의
Vertical Event Lines - BTC Halving & Custom DatesThis indicator plots vertical lines and labels for Bitcoin halving dates and any custom events you define directly on the price chart. It is designed as a clean, lightweight event-timeline overlay so you can instantly see where key dates occur relative to price action. Main features Built-in Bitcoin halving dates (2012, 2016, 2020, 2024), plus 8 additional custom event slots with freely configurable date/time, name and color. Vertical lines are positioned using xloc.bar_time , ensuring each event is anchored to the exact timestamp in the chart’s timeframe and timezone. Past and current events: A label is created once, on the first bar that crosses the event time, and placed near the bar’s high for consistent readability across symbols and timeframes. Future events: A separate label is shown at the bottom of the chart, making future dates clearly visible even to the right of the last bar. These labels update only on the most recent bar to keep the script efficient. Flexible styling: Global controls for line width, line style and label size, with per-event color selection and optional per-event overrides of global width and style. How to use Add the script to any chart (BTC or other symbols). It works on all timeframes. Use the Global settings to configure default line style, line width and label appearance (size, orientation, text color). In each Event X section, enable the event and set: Date/time in YYYY-MM-DD HH:MM format Event name Color Optional custom width/style When scrolling through time: Events left of the last bar show a vertical line and a one-time label at the crossing bar. Events right of the last bar show a vertical line and a bottom label that remains visible in the future. This script is intended as a visual reference tool only . It does not generate trading signals, alerts or backtests.
Pine Script® 인디케이터
oanstein의
Timebender - Day SeparatorTimebender — NY Anchored Day Separator Many traders rely on broker-based day boundaries, which often do not align with New York time — the primary liquidity clock for FX and macro-driven markets. When the trading day is anchored incorrectly, it can distort the reading of weekly structure, session behavior, and intraday narrative. This script provides a clear and configurable way to anchor trading days to a user-defined timezone and visually separate them on the chart. What This Script Does Highlights individual trading days using background shading Draws vertical separators at the exact start of each shifted trading day Allows independent toggling of background highlights and separator lines Supports day-specific coloring so each trading day is immediately recognizable Enables manual timezone shifting so traders can align charts to New York regardless of broker feed What Makes It Different Most day separators rely strictly on exchange time. This script detects calendar transitions from a manually shifted timestamp, allowing traders to define their own day boundary. This is particularly useful for traders who anchor their analysis to New York time rather than broker session clocks. Combining optional background shading with precision separators also allows traders to switch between a macro view (highlighted days) and a minimal execution view (lines only) without loading multiple indicators. How It Works (High-Level) The script internally offsets the chart’s timestamp by the number of hours specified in the timezone setting. It then detects when a new calendar day begins from that adjusted time and renders the visual separator accordingly. Because the calculation is based on shifted time rather than exchange time, the indicator maintains consistent day structure across brokers. How To Use Set the timezone shift to match the session you anchor your analysis to. Example: New York is typically UTC-5 or UTC-4 during daylight saving time. Enable background highlighting for a broader structural view. Use vertical separators when a cleaner chart is preferred for execution. Customize colors to match your chart template. Who This Script Is For FX traders Session-based traders ICT-style market structure traders Traders using multiple brokers Anyone who wants consistent day boundaries across charts Notes This script is designed as a chart-organization utility. It does not generate trade signals or provide market predictions.
Pine Script® 인디케이터
bon_appetrade의
Deep AILibrary "Deeptest" Comprehensive quantitative backtesting library with 112+ metrics: Sharpe/Sortino ratios, drawdown analysis, Monte Carlo simulation, Walk-Forward Analysis, VaR/CVaR, benchmark comparison, and interactive table rendering for TradingView strategies @version 1.0.1 (01.01.2026) ============================================================================ CHANGELOG ============================================================================ v1.0.1 (01.01.2026) - Added textSize parameter to runDeeptest() for controlling table text size - New values: size.auto, size.small, size.tiny, size.normal, size.large - Applies to all tables: main, stress test, drawdowns, recoveries, trades v1.0.0 (31.12.2025) - Initial release - 112+ backtesting metrics - Monte Carlo simulation and Walk-Forward Analysis - Interactive table rendering with tooltips ============================================================================ TABLE OF CONTENTS ============================================================================ SECTION 1: File Header & Metadata SECTION 2: Constants & Configuration SECTION 3: Type Definitions SECTION 4: Core Calculation Functions - Array Utilities SECTION 5: Core Calculation Functions - Return Extraction SECTION 6: Core Calculation Functions - Sharpe & Sortino SECTION 7: Core Calculation Functions - Performance Metrics SECTION 8: Core Calculation Functions - Drawdown Analysis SECTION 9: Core Calculation Functions - Recovery Analysis SECTION 10: Core Calculation Functions - Trade Analysis SECTION 11: Core Calculation Functions - Statistical Distribution SECTION 12: Core Calculation Functions - Risk Metrics SECTION 13: Core Calculation Functions - Benchmark Comparison SECTION 14: Core Calculation Functions - Time-Based Metrics SECTION 15: Core Calculation Functions - Rolling Statistics SECTION 16: Core Calculation Functions - Strategy Integration SECTION 17: Core Calculation Functions - Walk Forward Analysis SECTION 18: Core Calculation Functions - Monte Carlo Simulation SECTION 19: Core Calculation Functions - Out-of-Sample Analysis SECTION 20: Formatting Utilities - Value Formatting SECTION 21: Formatting Utilities - Duration Formatting SECTION 22: Formatting Utilities - Frequency Formatting SECTION 23: Formatting Utilities - Date Formatting SECTION 24: Tooltip Builders - Main Table Metrics SECTION 25: Tooltip Builders - Complementary Metrics SECTION 26: Tooltip Builders - Stress Test Metrics SECTION 27: Tooltip Builders - Period Analysis Cards SECTION 28: Table Rendering - Structure Helpers SECTION 29: Table Rendering - Main Deeptest Table SECTION 30: Table Rendering - Cell Renderers - Complementary Row SECTION 31: Table Rendering - Stress Test Table SECTION 32: Table Rendering - Period Analysis Cards SECTION 33: Main Entry Point ============================================================================ API REFERENCE ============================================================================ Main Export: ------------ runDeeptest() - Complete backtest analysis orchestrator ============================================================================ KEY FEATURES ============================================================================ - Comprehensive backtesting metrics (112+ functions) - Rolling window analysis with statistical distributions - Advanced risk metrics (Sharpe, Sortino, Calmar, Martin, VaR, CVaR) - Drawdown and recovery analysis - Monte Carlo simulation and Walk-Forward Analysis - Trade analysis (top/worst trades, consecutive streaks) - Benchmark comparison (Alpha, Beta, R², Buy & Hold) - Interactive table rendering with tooltips ============================================================================ USAGE EXAMPLE ============================================================================ ╔══════════════════════════════════════════════════════════════════════════════╗ ║ PROGRESSIVE USAGE EXAMPLES ║ ╠══════════════════════════════════════════════════════════════════════════════╣ ║ Three examples demonstrating increasing complexity: ║ ║ 1. MINIMAL - "Hello World" with basic MA crossover ║ ║ 2. BALANCED - Production ready with risk management & filters ║ ║ 3. PROFESSIONAL - Full-featured with trailing stops & session filters ║ ╚══════════════════════════════════════════════════════════════════════════════╝ ╔══════════════════════════════════════════════════════════════════════════════╗ ║ EXAMPLE 1: MINIMAL (The "Hello World") ║ ╠══════════════════════════════════════════════════════════════════════════════╣ ║ The simplest possible integration - just 3 lines to get started: ║ ║ 1. Import the library ║ ║ 2. Write your strategy logic ║ ║ 3. Call runDeeptest() ║ ╚══════════════════════════════════════════════════════════════════════════════╝ //@version=6 strategy("MA Crossover ", overlay=true) // ═══════════════════════════════════════════════════════════════════════════ // ⮟ Import Deeptest (Direct import - no namespace prefix needed) // ═══════════════════════════════════════════════════════════════════════════ import Fractalyst/Deeptest/1 as * // ──────────────────────────────────────────────────────────────────────────── // Strategy Logic: Simple Moving Average Crossover // ──────────────────────────────────────────────────────────────────────────── fastMA = ta.sma(close, 10) // Fast MA: 10 periods slowMA = ta.sma(close, 30) // Slow MA: 30 periods // Plot MAs for visualization plot(fastMA, "Fast MA", color=color.blue) plot(slowMA, "Slow MA", color=color.orange) // Entry: Long when fast MA crosses above slow MA if ta.crossover(fastMA, slowMA) strategy.entry("Long", strategy.long) // Exit: Close when fast MA crosses below slow MA if ta.crossunder(fastMA, slowMA) strategy.close("Long") // ═══════════════════════════════════════════════════════════════════════════ // ⮟ Run backtest analysis (all parameters use smart defaults) // ═══════════════════════════════════════════════════════════════════════════ DT.runDeeptest() ╔══════════════════════════════════════════════════════════════════════════════╗ ║ EXAMPLE 2: BALANCED (Production Ready) ║ ╠══════════════════════════════════════════════════════════════════════════════╣ ║ Adds essential production features: ║ ║ • User-configurable inputs ║ ║ • ADX trend filter to avoid choppy markets ║ ║ • Stop loss / Take profit for risk management ║ ║ • Custom backtest parameters ║ ╚══════════════════════════════════════════════════════════════════════════════╝ //@version=6 strategy("MA Crossover ", overlay=true) import Fractalyst/Deeptest/1 as * // ──────────────────────────────────────────────────────────────────────────── // INPUT PARAMETERS // ──────────────────────────────────────────────────────────────────────────── fastLen = input.int(10, "Fast MA Period", minval=1) slowLen = input.int(30, "Slow MA Period", minval=1) riskPct = input.float(2.0, "Risk %", minval=0.1) / 100 slPct = input.float(5.0, "Stop Loss %", minval=0.1) / 100 tpPct = input.float(10.0, "Take Profit %", minval=0.1) / 100 adxThresh = input.int(20, "ADX Trend Threshold") // ──────────────────────────────────────────────────────────────────────────── // INDICATORS // ──────────────────────────────────────────────────────────────────────────── fastMA = ta.sma(close, fastLen) slowMA = ta.sma(close, slowLen) adx = ta.adx(14) = ta.dmi(14, 14) // ──────────────────────────────────────────────────────────────────────────── // FILTERS // ──────────────────────────────────────────────────────────────────────────── trendConfirmed = adx > adxThresh and diPlus > diMinus // ──────────────────────────────────────────────────────────────────────────── // STRATEGY LOGIC // ──────────────────────────────────────────────────────────────────────────── // Entry: MA crossover + trend confirmation if ta.crossover(fastMA, slowMA) and trendConfirmed strategy.entry("Long", strategy.long) // Exit: MA crossunder if ta.crossunder(fastMA, slowMA) strategy.close("Long") // Risk management: Stop loss and take profit if strategy.position_size > 0 strategy.exit("RM", "Long", stop=strategy.position_avg_price * (1 - slPct), limit=strategy.position_avg_price * (1 + tpPct)) // ═══════════════════════════════════════════════════════════════════════════ // ⮟ Run backtest with custom parameters // ═══════════════════════════════════════════════════════════════════════════ DT.runDeeptest( riskPerTrade = 1.0, // ← 1% risk per trade targetMaxDDPct = 15.0, // ← 15% max drawdown target showStressTest = true, // ← Enable stress test table showPeriodCards = true, // ← Enable period cards wfaWindows = 12, // ← Walk-forward windows mcSimulations = 1000, // ← Monte Carlo runs bullColor = color.new(#00b9ff, 0), bearColor = color.new(#ff0051, 0), benchmarkSymbol = "SPX", // ← Compare to S&P; 500 periodCardMode = "drawdowns", // ← Show drawdown periods tradeSortBy = "return" // ← Sort by return % ) ╔══════════════════════════════════════════════════════════════════════════════╗ ║ EXAMPLE 3: PROFESSIONAL (Full-Featured) ║ ╠══════════════════════════════════════════════════════════════════════════════╣ ║ Complete professional implementation: ║ ║ • Organized input groups for better UX ║ ║ • Multiple filters: ADX trend, ATR volatility, Session timing ║ ║ • Trailing stop to lock in profits ║ ║ • Position highlighting for visual feedback ║ ║ • Full parameter customization with inline documentation ║ ╚══════════════════════════════════════════════════════════════════════════════╝ //@version=6 runDeeptest(targetMaxDDPct, bullColor, bearColor, tableBg, headerBg, borderColor, textPrimary, textMuted, textSize, showComplementaryRow, showStressTestTable, showDrawdownRecoveryCards, showTradeCards)   Parameters:      targetMaxDDPct (float)      bullColor (color)      bearColor (color)      tableBg (color)      headerBg (color)      borderColor (color)      textPrimary (color)      textMuted (color)      textSize (string)      showComplementaryRow (bool)      showStressTestTable (bool)      showDrawdownRecoveryCards (bool)      showTradeCards (bool) ThresholdConfig   ThresholdConfig - Configuration for metric thresholds and corresponding colors   Fields:      sharpeExc (series float)      sharpeGood (series float)      sharpeOk (series float)      sharpeBear (series color)      sharpeNeutral (series color)      sharpeOrange (series color)      sharpeBull (series color)      ddSevere (series float)      ddMod (series float)      ddMild (series float)      ddSevereColor (series color)      ddModColor (series color)      ddOrange (series color)      ddGoodColor (series color)      rorHigh (series float)      rorMod (series float)      rorLow (series float)      rorHighColor (series color)      rorModColor (series color)      rorOrange (series color)      rorLowColor (series color)      r2Poor (series float)      r2Mod (series float)      r2Good (series float)      r2PoorColor (series color)      r2ModColor (series color)      r2Orange (series color)      r2GoodColor (series color)      kurtHigh (series float)      kurtMod (series float)      kurtOk (series float)      kurtHighColor (series color)      kurtModColor (series color)      kurtOrange (series color)      kurtGoodColor (series color)      skewVNeg (series float)      skewModNeg (series float)      skewPos (series float)      skewVPos (series float)      skewVNegColor (series color)      skewModNegColor (series color)      skewNeutral (series color)      skewPosColor (series color)      payoffPoor (series float)      payoffBE (series float)      payoffGood (series float)      payoffPoorColor (series color)      payoffBEColor (series color)      payoffOrange (series color)      payoffGoodColor (series color)      pfPoor (series float)      pfBE (series float)      pfGood (series float)      pfPoorColor (series color)      pfBEColor (series color)      pfOrange (series color)      pfGoodColor (series color)      ulcerHigh (series float)      ulcerLow (series float)      ulcerHighColor (series color)      ulcerModColor (series color)      ulcerOrange (series color)      ulcerLowColor (series color)      wrLow (series float)      wrOk (series float)      wrHigh (series float)      wrLowColor (series color)      wrOkColor (series color)      wrOrange (series color)      wrHighColor (series color)      cagrPoor (series float)      cagrOk (series float)      cagrGood (series float)      cagrPoorColor (series color)      cagrOkColor (series color)      cagrOrange (series color)      cagrGoodColor (series color)      pInsig (series float)      pMod (series float)      pSig (series float)      pInsigColor (series color)      pModColor (series color)      pOrange (series color)      pSigColor (series color)      calmarPoor (series float)      calmarBE (series float)      calmarGood (series float)      calmarPoorColor (series color)      calmarBEColor (series color)      calmarOrange (series color)      calmarGoodColor (series color)      betaHigh (series float)      betaLow (series float)      betaHighColor (series color)      betaLowColor (series color)      betaGoodColor (series color) Stats   Stats - Comprehensive backtest statistics container   Fields:      totalTrades (series int)      winTrades (series int)      lossTrades (series int)      evenTrades (series int)      winRate (series float)      lossRate (series float)      avgWinPct (series float)      avgLossPct (series float)      avgTradePct (series float)      profitFactor (series float)      payoffRatio (series float)      expectancy (series float)      grossProfit (series float)      grossLoss (series float)      netProfit (series float)      netProfitPct (series float)      compEffect (series float)      sharpe (series float)      sortino (series float)      calmar (series float)      martin (series float)      maxDrawdown (series float)      maxDrawdownPct (series float)      currentDrawdown (series float)      currentDrawdownPct (series float)      avgDrawdownPct (series float)      maxEquity (series float)      minEquity (series float)      cagr (series float)      monthlyReturn (series float)      maxConsecWins (series int)      maxConsecLosses (series int)      avgTradeDuration (series float)      avgWinDuration (series float)      avgLossDuration (series float)      timeInMarketPct (series float)      tradesPerMonth (series float)      tradesPerYear (series float)      skewness (series float)      kurtosis (series float)      var95 (series float)      cvar95 (series float)      ulcerIndex (series float)      riskOfRuin (series float)      pValue (series float)      zScore (series float)      alpha (series float)      beta (series float)      buyHoldReturn (series float)      equityRSquared (series float)      firstTradeTime (series int)      lastTradeTime (series int)      tradingPeriodDays (series float) RollingWindowSummary   RollingWindowSummary - Summary of metrics for a single rolling analysis window   Fields:      windowIndex (series int)      startTrade (series int)      endTrade (series int)      effectiveCount (series int)      minValue (series float)      maxValue (series float)      metricValue (series float) RollingStats   RollingStats - Statistical distribution of rolling window metrics   Fields:      windowSize (series int) : Number of trades in rolling window      expectancyMin (series float) : Minimum rolling expectancy      expectancyMax (series float) : Maximum rolling expectancy      sharpeMin (series float) : Minimum rolling Sharpe      sharpeMax (series float) : Maximum rolling Sharpe      sortinoMin (series float) : Minimum rolling Sortino      sortinoMax (series float) : Maximum rolling Sortino      expectancyWindows (array) : Per-window summaries for expectancy      sharpeWindows (array) : Per-window summaries for Sharpe      sortinoWindows (array) : Per-window summaries for Sortino      expectancyMean (series float) : Mean expectancy across rolling windows      expectancyStdDev (series float) : Standard deviation of expectancy      expectancyPct90 (series float) : 90th percentile expectancy      expectancyPct50 (series float) : 50th percentile expectancy (median)      expectancyPct10 (series float) : 10th percentile expectancy      sharpeMean (series float) : Mean Sharpe across rolling windows      sharpeStdDev (series float) : Standard deviation of Sharpe      sharpePct90 (series float) : 90th percentile Sharpe      sharpePct50 (series float) : 50th percentile Sharpe      sharpePct10 (series float) : 10th percentile Sharpe      sortinoMean (series float) : Mean Sortino across rolling windows      sortinoStdDev (series float) : Standard deviation of Sortino      sortinoPct90 (series float) : 90th percentile Sortino      sortinoPct50 (series float) : 50th percentile Sortino      sortinoPct10 (series float) : 10th percentile Sortino
Pine Script® 라이브러리
DeepEx_Paradigma의
USDT + USDC DominanceUSDT + USDC Dominance USDT/USDC Dominance Indicator This indicator measures the relative dominance of USDT and USDC on the market. It calculates the share of each stablecoin compared to the total of the two, and displays it as a percentage. USDT Dominance (%) = (USDT value / (USDT value + USDC value)) × 100 USDC Dominance (%) = 100 − USDT Dominance The indicator plots both dominance values on the chart, allowing you to see which stablecoin has a higher share at any given time. It can help identify shifts in market preference between USDT and USDC. Optional features: Horizontal 50% line for reference. Highlight when USDT or USDC exceeds 50% dominance. Works with price or market capitalization data depending on available data sources.
Pine Script® 인디케이터
axisbhp의
Simple Trend + Signal (No Bug)//@version=5indicator("Simple Trend + Signal (No Bug)", overlay=true) // === INPUTS ===fastEMA = input.int(20, "Fast EMA")slowEMA = input.int(50, "Slow EMA")lookback = input.int(20, "Zone Lookback") // === TREND ===emaFast = ta.ema(close, fastEMA)emaSlow = ta.ema(close, slowEMA) trendUp = emaFast > emaSlowtrendDown = emaFast < emaSlow // === ZONES ===highestHigh = ta.highest(high, lookback)lowestLow = ta.lowest(low, lookback) // === SIGNALS ===buySignal = trendUp and close <= emaFastsellSignal = trendDown and close >= emaFast // === PLOTS ===plot(emaFast, color=color.green, linewidth=2)plot(emaSlow, color=color.red, linewidth=2) plot(highestHigh, color=color.new(color.blue, 70))plot(lowestLow, color=color.new(color.orange, 70)) plotshape(buySignal, title="BUY", location=location.belowbar, color=color.green, style=shape.labelup, text="BUY")plotshape(sellSignal, title="SELL", location=location.abovebar, color=color.red, style=shape.labeldown, text="SELL")
Pine Script® 인디케이터
blissfulAccoun8911의
Simple Trend + Signal (No Bug)//@version=5 indicator("Simple Trend + Signal (No Bug)", overlay=true) // === INPUTS === fastEMA = input.int(20, "Fast EMA") slowEMA = input.int(50, "Slow EMA") lookback = input.int(20, "Zone Lookback") // === TREND === emaFast = ta.ema(close, fastEMA) emaSlow = ta.ema(close, slowEMA) trendUp = emaFast > emaSlow trendDown = emaFast < emaSlow // === ZONES === highestHigh = ta.highest(high, lookback) lowestLow = ta.lowest(low, lookback) // === SIGNALS === buySignal = trendUp and close <= emaFast sellSignal = trendDown and close >= emaFast // === PLOTS === plot(emaFast, color=color.green, linewidth=2) plot(emaSlow, color=color.red, linewidth=2) plot(highestHigh, color=color.new(color.blue, 70)) plot(lowestLow, color=color.new(color.orange, 70)) plotshape(buySignal, title="BUY", location=location.belowbar, color=color.green, style=shape.labelup, text="BUY") plotshape(sellSignal, title="SELL", location=location.abovebar, color=color.red, style=shape.labeldown, text="SELL")
Pine Script® 인디케이터
blissfulAccoun8911의
Volatility Expansion Indicator - D_QuantVolatility Expansion Indicator - D_Quant |V|C|E| 1. Concept & Overview The Volatility Expansion Indicator (VCE) is a composite quantitative tool designed to identify robust trend states by aggregating signals from three distinct market dimensions: Relative Position (Volatility), Cyclical Momentum, and Price Velocity. Unlike single-source indicators which often generate false positives during choppy markets, the VCE utilizes a "Consensus Engine." It normalizes signals from Bollinger %B, CCI, and ROC into a unified trend score (-1 to +1). This score drives the visual coloring of the price action and background, allowing traders to instantly gauge whether the market is in a state of volatility expansion (trending) or contraction (ranging). 2. Methodology & Calculation The core logic relies on a weighted aggregation of three technical components. Users can toggle these components on or off in the settings to isolate specific market mechanics. A. Component 1: Bollinger %B (Relative Positioning) Logic: Measures where the price is located relative to the Bollinger Bands. Bullish Condition: If %B > 0.5 (Price is operating in the upper hemisphere of the bands). Bearish Condition: If %B < 0.0 (Price has broken below the lower band). Purpose: Filters out weak trends by ensuring price is statistically significant relative to its recent volatility. B. Component 2: CCI (Commodity Channel Index) Logic: Measures current price levels relative to an average price level over a specific period. Thresholds: A standard +100 / -100 threshold is used. Values above 100 add to the bullish score; values below -100 add to the bearish score. Purpose: Identifies cyclical momentum extremes. f_cci(_len) => cci_val = ta.cci(close, _len) val = 0 if cci_val > 100 val := 1 if cci_val < -100 val := -1 val C. Component 3: ROC (Rate of Change) Logic: Calculates the percentage change between the current price and the price n periods ago. Thresholds: Simple zero-line crossover. Positive ROC implies bullish velocity; negative implies bearish. Purpose: Provides a raw directional bias based on pure price speed. D. The Aggregation Engine: The script sums the active signals and divides by the number of active components. Bullish Trend: Composite Score > 0 (Visualized as Deep Navy). Bearish/Neutral: Composite Score ≤ 0 (Visualized as White). E. Multi-Timeframe (MTF) Capability: The indicator includes a request.security module. This allows you to calculate the consensus trend on a higher timeframe (e.g., Daily) while viewing price action on a lower timeframe (e.g., 15-minute), ensuring you are trading in alignment with the macro trend. // NEW: Timeframe Selection tf_input = input.timeframe("", "VCE Timeframe", group=grp_sets, tooltip="Empty = Current Chart. Set to 'D' for fixed Daily trend.") = request.security(syminfo.tickerid, tf_input, , lookahead=barmerge.lookahead_on) 3. Visualizations The indicator overlays the following elements on the chart: Trend SMMA: A central Smoothed Moving Average (SMMA 20) representing the mean. Volatility Bands: Upper and Lower bands calculated at 2 Standard Deviations from the SMMA. Bar Coloring: Navy Blue: Indicates a confirmed Volatility Expansion (Bullish Confluence). White: Indicates Neutrality, Retracement, or Bearish conditions. Dynamic Fills: The space between the bands fills with color to highlight the strength of the current regime. 4. How to Use Trend Following: Look for the bar color to switch to Navy. This indicates that momentum, volatility, and velocity have aligned bullishly. This is often an entry trigger for long positions. Exits: When the bars switch from Navy back to White/Gray, the volatility expansion has ceased or momentum is diverging. This serves as a warning to tighten stops or take profits. MTF Filter: Set the "VCE Timeframe" input to "D" (Daily). Trade on the H1 chart. Only take long positions when the Daily VCE paints the background/bands in the Bullish color. 5. Settings Bollinger %B: Adjust Length and Multiplier (Default: 20, 2.0). CCI: Adjust Length (Default: 23). ROC: Adjust Length (Default: 50). Signal Components: Toggle specific logic blocks on/off to customize the sensitivity of the composite score. VCE Timeframe: Select the resolution for the calculation (Leave empty for current chart). Disclaimer: This tool is for informational purposes only. Past performance of volatility expansion does not guarantee future results. Always manage risk appropriately.
Pine Script® 인디케이터
D_QUANT의
Weekly Tightness Near EMA//@version=6 indicator("Weekly Tightness Near EMA", overlay=true) // =========================== // INPUT PARAMETERS // =========================== tightness_pct = input.float(3.0, "Tightness % Range", minval=0.1, maxval=10.0) ema_proximity_pct = input.float(5.0, "EMA Proximity %", minval=0.5, maxval=15.0) small_candle_pct = input.float(5.0, "Small Candle % (body)", minval=0.5, maxval=10.0) show_ema10 = input.bool(true, "Show 10 Week EMA") show_ema20 = input.bool(true, "Show 20 Week EMA") show_signals = input.bool(true, "Show Tightness Signals") // =========================== // GET WEEKLY DATA // =========================== weekly_close = request.security(syminfo.tickerid, "W", close, barmerge.gaps_off, barmerge.lookahead_off) weekly_open = request.security(syminfo.tickerid, "W", open, barmerge.gaps_off, barmerge.lookahead_off) weekly_high = request.security(syminfo.tickerid, "W", high, barmerge.gaps_off, barmerge.lookahead_off) weekly_low = request.security(syminfo.tickerid, "W", low, barmerge.gaps_off, barmerge.lookahead_off) weekly_close_1 = request.security(syminfo.tickerid, "W", close , barmerge.gaps_off, barmerge.lookahead_off) weekly_open_1 = request.security(syminfo.tickerid, "W", open , barmerge.gaps_off, barmerge.lookahead_off) weekly_high_1 = request.security(syminfo.tickerid, "W", high , barmerge.gaps_off, barmerge.lookahead_off) weekly_low_1 = request.security(syminfo.tickerid, "W", low , barmerge.gaps_off, barmerge.lookahead_off) weekly_close_2 = request.security(syminfo.tickerid, "W", close , barmerge.gaps_off, barmerge.lookahead_off) weekly_open_2 = request.security(syminfo.tickerid, "W", open , barmerge.gaps_off, barmerge.lookahead_off) weekly_high_2 = request.security(syminfo.tickerid, "W", high , barmerge.gaps_off, barmerge.lookahead_off) weekly_low_2 = request.security(syminfo.tickerid, "W", low , barmerge.gaps_off, barmerge.lookahead_off) // Weekly EMAs weekly_ema10 = request.security(syminfo.tickerid, "W", ta.ema(close, 10), barmerge.gaps_off, barmerge.lookahead_off) weekly_ema20 = request.security(syminfo.tickerid, "W", ta.ema(close, 20), barmerge.gaps_off, barmerge.lookahead_off) // =========================== // CALCULATE CANDLE SIZE // =========================== // Calculate body size (close - open) as percentage of price candle_body_0 = math.abs(weekly_close - weekly_open) candle_body_1 = math.abs(weekly_close_1 - weekly_open_1) candle_body_2 = math.abs(weekly_close_2 - weekly_open_2) candle_body_pct_0 = (candle_body_0 / weekly_close) * 100 candle_body_pct_1 = (candle_body_1 / weekly_close_1) * 100 candle_body_pct_2 = (candle_body_2 / weekly_close_2) * 100 // Calculate full range (high - low) as percentage candle_range_0 = weekly_high - weekly_low candle_range_1 = weekly_high_1 - weekly_low_1 candle_range_2 = weekly_high_2 - weekly_low_2 candle_range_pct_0 = (candle_range_0 / weekly_close) * 100 candle_range_pct_1 = (candle_range_1 / weekly_close_1) * 100 candle_range_pct_2 = (candle_range_2 / weekly_close_2) * 100 // Check if all 3 candles are small small_candle_0 = candle_body_pct_0 <= small_candle_pct small_candle_1 = candle_body_pct_1 <= small_candle_pct small_candle_2 = candle_body_pct_2 <= small_candle_pct all_candles_small = small_candle_0 and small_candle_1 and small_candle_2 // Average candle body size avg_candle_body = (candle_body_pct_0 + candle_body_pct_1 + candle_body_pct_2) / 3 avg_candle_range = (candle_range_pct_0 + candle_range_pct_1 + candle_range_pct_2) / 3 // =========================== // CALCULATE TIGHTNESS // =========================== // Find highest and lowest of last 3 weekly closes highest_close = math.max(weekly_close, weekly_close_1, weekly_close_2) lowest_close = math.min(weekly_close, weekly_close_1, weekly_close_2) // Calculate range percentage close_range_pct = ((highest_close - lowest_close) / lowest_close) * 100 // Check if within tightness range is_tight = close_range_pct <= tightness_pct // =========================== // CHECK PROXIMITY TO EMAs // =========================== // Distance from EMAs dist_from_ema10_pct = math.abs((weekly_close - weekly_ema10) / weekly_ema10) * 100 dist_from_ema20_pct = math.abs((weekly_close - weekly_ema20) / weekly_ema20) * 100 // Near EMA conditions near_ema10 = dist_from_ema10_pct <= ema_proximity_pct near_ema20 = dist_from_ema20_pct <= ema_proximity_pct near_any_ema = near_ema10 or near_ema20 // =========================== // COMBINED SIGNAL (with small candles filter) // =========================== tightness_signal = is_tight and near_any_ema and all_candles_small // =========================== // PLOT EMAs // =========================== plot(show_ema10 ? weekly_ema10 : na, "10 Week EMA", color=color.new(color.blue, 0), linewidth=2) plot(show_ema20 ? weekly_ema20 : na, "20 Week EMA", color=color.new(color.orange, 0), linewidth=2) // =========================== // PLOT SIGNALS // =========================== // Background color when tight and near EMA bgcolor(show_signals and tightness_signal ? color.new(color.green, 90) : na, title="Tightness Signal") // Plot signal markers plotshape(show_signals and tightness_signal and not tightness_signal , title="Tightness Start", location=location.belowbar, color=color.new(color.green, 0), style=shape.triangleup, size=size.small, text="TIGHT") // =========================== // DISPLAY TABLE // =========================== var table info_table = table.new(position.top_right, 2, 9, border_width=1, border_color=color.gray, frame_width=1, frame_color=color.gray) if barstate.islast // Header table.cell(info_table, 0, 0, "Weekly Analysis", bgcolor=color.new(color.gray, 70), text_color=color.white, text_size=size.normal) table.cell(info_table, 1, 0, "Status", bgcolor=color.new(color.gray, 70), text_color=color.white, text_size=size.normal) // Average candle body size candle_color = all_candles_small ? color.new(color.green, 85) : color.new(color.red, 85) table.cell(info_table, 0, 1, "Avg Candle Body", bgcolor=candle_color, text_color=color.white, text_halign=text.align_left) table.cell(info_table, 1, 1, str.tostring(avg_candle_body, "#.##") + "%", bgcolor=candle_color, text_color=color.white) // Small candle threshold table.cell(info_table, 0, 2, "Small Candle <", bgcolor=color.new(color.gray, 90), text_color=color.white, text_halign=text.align_left) table.cell(info_table, 1, 2, str.tostring(small_candle_pct, "#.#") + "%", bgcolor=color.new(color.gray, 90), text_color=color.white) // 3 Week Close Tightness tight_color = is_tight ? color.new(color.green, 85) : color.new(color.red, 85) table.cell(info_table, 0, 3, "3W Close Range", bgcolor=tight_color, text_color=color.white, text_halign=text.align_left) table.cell(info_table, 1, 3, str.tostring(close_range_pct, "#.##") + "%", bgcolor=tight_color, text_color=color.white) // Tightness threshold table.cell(info_table, 0, 4, "Threshold", bgcolor=color.new(color.gray, 90), text_color=color.white, text_halign=text.align_left) table.cell(info_table, 1, 4, "<" + str.tostring(tightness_pct, "#.#") + "%", bgcolor=color.new(color.gray, 90), text_color=color.white) // Distance from 10W EMA ema10_color = near_ema10 ? color.new(color.blue, 85) : color.new(color.gray, 85) table.cell(info_table, 0, 5, "From 10W EMA", bgcolor=ema10_color, text_color=color.white, text_halign=text.align_left) table.cell(info_table, 1, 5, str.tostring(dist_from_ema10_pct, "#.##") + "%", bgcolor=ema10_color, text_color=color.white) // Distance from 20W EMA ema20_color = near_ema20 ? color.new(color.orange, 85) : color.new(color.gray, 85) table.cell(info_table, 0, 6, "From 20W EMA", bgcolor=ema20_color, text_color=color.white, text_halign=text.align_left) table.cell(info_table, 1, 6, str.tostring(dist_from_ema20_pct, "#.##") + "%", bgcolor=ema20_color, text_color=color.white) // Near EMA status near_ema_color = near_any_ema ? color.new(color.green, 85) : color.new(color.red, 85) near_ema_text = near_any_ema ? "✓ NEAR" : "✗ Far" table.cell(info_table, 0, 7, "Near EMA", bgcolor=near_ema_color, text_color=color.white, text_halign=text.align_left) table.cell(info_table, 1, 7, near_ema_text, bgcolor=near_ema_color, text_color=color.white) // Combined signal signal_color = tightness_signal ? color.new(color.lime, 70) : color.new(color.gray, 85) signal_text = tightness_signal ? "🎯 SETUP!" : "No Setup" table.cell(info_table, 0, 8, "SIGNAL", bgcolor=signal_color, text_color=color.white, text_halign=text.align_left, text_size=size.large) table.cell(info_table, 1, 8, signal_text, bgcolor=signal_color, text_color=color.white, text_size=size.large) // =========================== // ALERTS // =========================== alertcondition(tightness_signal and not tightness_signal , title="Tightness Setup Alert", message="Weekly setup detected: Small candles, tight closes, near EMA!")
Pine Script® 인디케이터
harishjagtap의