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FNGAdataLow“Low prices for FNGA ETF (Dec 2018–May 2025) The Low prices for FNGA ETF (December 2018 – May 2025) capture the lowest trading price reached during each regular U.S. market session over the entire lifespan of this leveraged exchange-traded note. Initially launched under the ticker FNGU, and later rebranded as FNGA in March 2025 before its eventual redemption, the fund was structured to deliver 3x daily leveraged exposure to the MicroSectors FANG+™ Index. This index concentrated on a small basket of leading technology and tech-enabled growth companies such as Meta (Facebook), Amazon, Apple, Netflix, and Alphabet (Google), along with a few other innovators. The Low price is particularly important in the study of FNGA because it highlights the intraday downside extremes of a highly volatile, leveraged product. Since FNGA was designed to reset leverage daily, its lows often reflected moments of amplified market stress, when declines in the underlying FANG+™ stocks were multiplied through the 3x leverage structure.
مكتبة Pine Script®
من ‎bsouthhh‎
Low volatility Buy w/ TP & SL (Coinrule)The compression of volatility usually leads to expansion. When the breakout comes, it can ignite strong trends. One way to catch a coin trading in an accumulation area is to spot three moving averages with values close to each other. The strategy uses a combination of Moving Averages to spot the best time to buy a coin before its breakout. Buy Condition The MA200 is greater than the MA100 The MA50 is greater than the MA100 According to backtesting results, the 1-hour time frame is the best to run this strategy. Sell Condition Take Profit: the price increases 8% from the entry price Stop Loss: the price drops 4% from the entry price The strategy has a profitability of 40-60% (depending on the market conditions). Having a ratio of two between Take profit and Stop Loss helps keeping the strategy profitable in the long term.
استراتيجية Pine Script®
من ‎Coinrule‎
Price Action [False Break+BreakOut]⚙️ Core Features Pivot Point Detection Customizable Pivot Detection: Set left and right length for pivot identification Pivot Classification: Higher High (HH): New high higher than previous high Lower High (LH): New high but lower than previous high Higher Low (HL): New low but higher than previous low Lower Low (LL): New low lower than previous low Visual Display Options Triangle Markers: ▲/▼ symbols at pivot points Price Labels: Display exact price values at pivot points Support/Resistance Lines: Horizontal lines from pivot points Fractal Chaos Channel: Display as channel lines Breakout Detection Breakout: Close above Pivot High Breakdown: Close below Pivot Low Visual Signals: Arrow icons and text labels ⬆️/⬇️ 🚨 Special Feature: False Break Detection How False Break Works Tracks Recent Breakouts/Breakdowns Monitors Reversals within specified number of bars Uses Engulfing Conditions to confirm False Break signals False Break Settings Validation Bars: Configurable 1-10 bars for confirmation Engulfing Check Options: Include Candle Shadows: Check entire candle (body + shadows) Body Only: Check only candle body Customizable Colors and Text Sizes False Break Signals 💥FalseB!!: False Break upward (Price breaks out then reverses down) 🚀FalseB!!: False Break downward (Price breaks down then reverses up) 📊 Trading Applications For Price Action Traders Identify market structure and trends Locate key support/resistance from pivot points Detect trend change patterns For Breakout Trading Distinguish between genuine breakouts and false breaks Enter trades on confirmed breakouts Set stop losses for false break trades Risk Management False Break Trading: Enter positions when false break detected Genuine Breakouts: Wait for confirmation before entering Use Pivot Levels for TP/SL placement 🎨 Customization Options Selective Pivot Display: Choose which pivots to show (HH, LH, HL, LL) Color and Style Adjustments Bar Limit Settings: Control how many bars to display Label and Text Size customization
مؤشر Pine Script®
من ‎titakunna_tk‎
MTF EMA Trading SystemHere's a comprehensive description and usage guide for publishing your MTF EMA Trading System indicator on TradingView: MTF EMA Trading System - Pro Edition 📊 Indicator Overview The MTF EMA Trading System is an advanced multi-timeframe exponential moving average indicator designed for traders seeking high-probability setups with multiple confirmations. Unlike simple EMA crossover systems, this indicator combines trend alignment, momentum, volume analysis, and previous day confluence to generate reliable long and short signals with optimal risk-reward ratios. ✨ Key Features 1. Multi-Timeframe EMA Analysis Configure 5 independent EMAs (default: 9, 21, 50, 100, 200) Each EMA can pull data from ANY timeframe (5m, 15m, 1H, 4H, 1D, etc.) Color-coded lines with customizable widths End-of-line labels showing EMA period and timeframe (e.g., "EMA200 ") Perfect for analyzing higher timeframe trends on lower timeframe charts 2. Advanced Signal Generation (Beyond Simple Crosses) The system requires MULTIPLE confirmations before generating a signal: LONG Signals Require: ✅ Price action trigger (EMA cross, bounce from key EMA, or pullback setup) ✅ Bullish EMA alignment (EMAs in proper ascending order) ✅ Volume spike confirmation (configurable threshold) ✅ RSI momentum confirmation (bullish but not overbought) ✅ Sufficient EMA separation (avoids choppy/whipsaw conditions) ✅ Price above previous day's low (confluence with support) SHORT Signals Require: ✅ Price action trigger (EMA cross, rejection from key EMA, or pullback setup) ✅ Bearish EMA alignment (EMAs in proper descending order) ✅ Volume spike confirmation ✅ RSI momentum confirmation (bearish but not oversold) ✅ Sufficient EMA separation ✅ Price below previous day's high (confluence with resistance) 3. Real-Time Dashboard Displays critical market conditions at a glance: Overall trend direction (Bullish/Bearish/Neutral) Price position relative to all EMAs Volume status (spike or normal) RSI momentum reading EMA confluence strength EMA separation quality Current ATR value Previous day high/low levels Current signal status (LONG/SHORT/WAIT) Risk-reward ratio 4. Clean Visual Design Large, clear trade signal markers (green triangles for LONG, red triangles for SHORT) No chart clutter - only essential information displayed Customizable signal sizes Professional color-coded dashboard 5. Built-In Risk Management ATR-based calculations for stop loss placement 1:2 risk-reward ratio by default All levels displayed in dashboard for easy reference 🎯 How to Use This Indicator Step 1: Initial Setup Add the indicator to your TradingView chart Configure your preferred timeframes for each EMA: EMA 9: Leave blank (uses chart timeframe) - Fast reaction to price EMA 21: Leave blank or set to 15m - Key pivot level EMA 50: Set to 1H - Intermediate trend EMA 100: Set to 4H - Major trend filter EMA 200: Set to 1D - Overall market bias Adjust signal settings based on your trading style: Conservative: Keep all confirmations enabled Aggressive: Disable volume or momentum requirements Scalping: Reduce min EMA separation to 0.2-0.3% Step 2: Reading the Dashboard Before taking any trade, check the dashboard: Trend: Only take LONG signals in bullish trends, SHORT signals in bearish trends Position: Confirm price is on the correct side of EMAs Volume: Green spike = strong confirmation RSI: Avoid extremes (>70 or <30) Confluence: "Strong" = high probability setup Separation: "Good" = trending market, avoid "Low" separation Step 3: Trade Entry For LONG Trades: Wait for green triangle to appear below price Verify dashboard shows: Bullish or Neutral trend Volume spike (preferred) RSI between 50-70 Good separation Enter at market or on next bar Set stop loss at: Entry - (ATR × 2) Set target at: Entry + (ATR × 4) For SHORT Trades: Wait for red triangle to appear above price Verify dashboard shows: Bearish or Neutral trend Volume spike (preferred) RSI between 30-50 Good separation Enter at market or on next bar Set stop loss at: Entry + (ATR × 2) Set target at: Entry - (ATR × 4) Step 4: Trade Management Use the ATR values from dashboard for position sizing Trail stops using the fastest EMA (EMA 9) as price moves in your favor Exit partial position at 1:1 risk-reward, let remainder run to target Exit immediately if dashboard trend changes against your position 💡 Best Practices Timeframe Recommendations: Scalping: 1m-5m chart with 5m, 15m, 1H, 4H, 1D EMAs Day Trading: 5m-15m chart with 15m, 1H, 4H, 1D EMAs Swing Trading: 1H-4H chart with 4H, 1D, 1W EMAs Position Trading: 1D chart with 1D, 1W, 1M EMAs Market Conditions: Best in: Trending markets with clear direction Avoid: Tight consolidation, low volume periods, major news events Filter trades: Only take signals aligned with higher timeframe trend Risk Management: Never risk more than 1-2% per trade Use ATR from dashboard to calculate position size Respect the stop loss levels Don't force trades when dashboard shows weak conditions ⚙️ Customization Options EMA Settings (for each of 5 EMAs): Length (period) Timeframe (multi-timeframe capability) Color Line width Show/hide toggle Signal Settings: Volume confirmation (on/off) Volume spike threshold (1.0-3.0x) Momentum confirmation (on/off) RSI overbought/oversold levels Minimum EMA separation percentage ATR period and stop multiplier Display Settings: Show/hide EMA labels Show/hide trade signals Signal marker size (tiny/small/normal/large) Show/hide dashboard 🔔 Alert Setup The indicator includes 4 alert conditions: LONG Signal - Fires when all long confirmations are met SHORT Signal - Fires when all short confirmations are met Bullish Setup - Early warning when trend aligns bullish with volume Bearish Setup - Early warning when trend aligns bearish with volume To set up alerts: Right-click on chart → Add Alert Select "MTF EMA Trading System" Choose your desired alert condition Configure notification method (popup, email, SMS, webhook) 📈 Performance Tips Increase Win Rate: Only trade in direction of higher timeframe trend Wait for volume spike confirmation Avoid trades during first 30 minutes and last 15 minutes of session Skip trades when separation is "Low" Reduce False Signals: Increase minimum EMA separation to 0.7-1.0% Enable all confirmation requirements Only trade when confluence shows "Strong" Combine with support/resistance levels Optimize for Your Market: Stocks: Use 9, 21, 50, 100, 200 EMAs Forex: Consider 8, 13, 21, 55, 89 EMAs (Fibonacci) Crypto: May need wider ATR multiplier (2.5-3.0x) for volatility ⚠️ Important Notes This indicator is designed to reduce false signals by requiring multiple confirmations No indicator is 100% accurate - always use proper risk management Backtesting recommended before live trading Market conditions change - adjust settings as needed Works best in liquid markets with clear price action 🎓 Conclusion The MTF EMA Trading System transforms simple moving average analysis into a sophisticated, multi-confirmation trading strategy. By combining trend alignment, momentum, volume, and confluence, it helps traders identify high-probability setups while filtering out noise and false signals. The clean interface and comprehensive dashboard make it suitable for both beginners and experienced traders across all markets and timeframes.
مؤشر Pine Script®
من ‎karanKM‎
Flow_RSI_StochRSI_Volume//@version=5 indicator("Flow + RSI + StochRSI + Volume - Panel", overlay=false) // ---- Inputs cmfLen = input.int(20, "CMF Length", minval=2) rsiLen = input.int(14, "RSI Length", minval=2) srsiLen = input.int(14, "StochRSI Base Length", minval=2) kLen = input.int(3, "%K Smoothing", minval=1) dLen = input.int(3, "%D Smoothing", minval=1) // ---- CMF (세력 유입) rng = high - low mfm = rng != 0 ? ((close - low) - (high - close)) / rng : 0.0 mfv = mfm * volume cmf = ta.sma(mfv, cmfLen) / ta.sma(volume, cmfLen) // ---- RSI rsi = ta.rsi(close, rsiLen) // ---- StochRSI (%K, %D) rsiLL = ta.lowest(rsi, srsiLen) rsiHH = ta.highest(rsi, srsiLen) base = (rsiHH - rsiLL) != 0 ? (rsi - rsiLL) / (rsiHH - rsiLL) * 100.0 : 0.0 k = ta.sma(base, kLen) d = ta.sma(k, dLen) // ---- Volume (거래량) vol = volume vma20 = ta.sma(volume, 20) // ---- Plots (색상 지정 없이 기본값 사용) plot(cmf, title="CMF (Flow)") hline(0, "CMF Zero") plot(rsi, title="RSI") hline(30, "RSI 30") hline(50, "RSI 50") hline(70, "RSI 70") plot(k, title="StochRSI %K") plot(d, title="StochRSI %D") plot(vol, title="Volume", style=plot.style_histogram) plot(vma20, title="Vol MA20")
مؤشر Pine Script®
من ‎jongok3111‎
Fibonacci Retracement (Tita)⚙️ Key Features Core Functionality Automatic Swing Detection: Uses ZigZag indicator to identify significant highs and lows Multiple Fibonacci Modes: Supports both Retracement levels and Timezone projections Customizable Timeframe: Analyze Fibonacci levels on different timeframes than the current chart Customization Options 11 Fibonacci Levels: From 0% to 300% with individual color and visibility controls Flexible Display: Customize line thickness, style, and colors Label Options: Choose position (Left/Right/Both/Auto) and visibility for both Fibonacci percentages and price levels ZigZag Visualization: Option to show/hide the underlying ZigZag line 📊 How It Works Swing Detection: The ZigZag algorithm identifies significant swing highs and lows based on depth, deviation, and backstep parameters Level Calculation: Draws Fibonacci levels between the last two significant ZigZag points Dynamic Updates: Automatically updates when new swings are detected and cleans up previous drawings Visual Enhancement: Uses background coloring to indicate market direction (bullish/bearish) 🎨 Visual Elements Colored Horizontal Lines: Each Fibonacci level has customizable colors Percentage Labels: Shows retracement percentages (23.6%, 38.2%, etc.) Price Labels: Displays exact price levels ZigZag Connection Line: Visual connection between swing points Direction-based Background: Subtle background tint indicating trend direction 💡 Trading Applications Identify potential entry points at key Fibonacci levels Set profit targets using extension levels (1.618, 2.0, 3.0, etc.) Determine stop-loss placement below/above Fibonacci support/resistance Analyze retracement depth for trend strength assessment
مؤشر Pine Script®
من ‎titakunna_tk‎
PubLibCandleTrendLibrary "PubLibCandleTrend" candle trend, multi-part candle trend, multi-part green/red candle trend, double candle trend and multi-part double candle trend conditions for indicator and strategy development chh()   candle higher high condition   Returns: bool chl()   candle higher low condition   Returns: bool clh()   candle lower high condition   Returns: bool cll()   candle lower low condition   Returns: bool cdt()   candle double top condition   Returns: bool cdb()   candle double bottom condition   Returns: bool gc()   green candle condition   Returns: bool gchh()   green candle higher high condition   Returns: bool gchl()   green candle higher low condition   Returns: bool gclh()   green candle lower high condition   Returns: bool gcll()   green candle lower low condition   Returns: bool gcdt()   green candle double top condition   Returns: bool gcdb()   green candle double bottom condition   Returns: bool rc()   red candle condition   Returns: bool rchh()   red candle higher high condition   Returns: bool rchl()   red candle higher low condition   Returns: bool rclh()   red candle lower high condition   Returns: bool rcll()   red candle lower low condition   Returns: bool rcdt()   red candle double top condition   Returns: bool rcdb()   red candle double bottom condition   Returns: bool chh_1p()   1-part candle higher high condition   Returns: bool chh_2p()   2-part candle higher high condition   Returns: bool chh_3p()   3-part candle higher high condition   Returns: bool chh_4p()   4-part candle higher high condition   Returns: bool chh_5p()   5-part candle higher high condition   Returns: bool chh_6p()   6-part candle higher high condition   Returns: bool chh_7p()   7-part candle higher high condition   Returns: bool chh_8p()   8-part candle higher high condition   Returns: bool chh_9p()   9-part candle higher high condition   Returns: bool chh_10p()   10-part candle higher high condition   Returns: bool chh_11p()   11-part candle higher high condition   Returns: bool chh_12p()   12-part candle higher high condition   Returns: bool chh_13p()   13-part candle higher high condition   Returns: bool chh_14p()   14-part candle higher high condition   Returns: bool chh_15p()   15-part candle higher high condition   Returns: bool chh_16p()   16-part candle higher high condition   Returns: bool chh_17p()   17-part candle higher high condition   Returns: bool chh_18p()   18-part candle higher high condition   Returns: bool chh_19p()   19-part candle higher high condition   Returns: bool chh_20p()   20-part candle higher high condition   Returns: bool chh_21p()   21-part candle higher high condition   Returns: bool chh_22p()   22-part candle higher high condition   Returns: bool chh_23p()   23-part candle higher high condition   Returns: bool chh_24p()   24-part candle higher high condition   Returns: bool chh_25p()   25-part candle higher high condition   Returns: bool chh_26p()   26-part candle higher high condition   Returns: bool chh_27p()   27-part candle higher high condition   Returns: bool chh_28p()   28-part candle higher high condition   Returns: bool chh_29p()   29-part candle higher high condition   Returns: bool chh_30p()   30-part candle higher high condition   Returns: bool chl_1p()   1-part candle higher low condition   Returns: bool chl_2p()   2-part candle higher low condition   Returns: bool chl_3p()   3-part candle higher low condition   Returns: bool chl_4p()   4-part candle higher low condition   Returns: bool chl_5p()   5-part candle higher low condition   Returns: bool chl_6p()   6-part candle higher low condition   Returns: bool chl_7p()   7-part candle higher low condition   Returns: bool chl_8p()   8-part candle higher low condition   Returns: bool chl_9p()   9-part candle higher low condition   Returns: bool chl_10p()   10-part candle higher low condition   Returns: bool chl_11p()   11-part candle higher low condition   Returns: bool chl_12p()   12-part candle higher low condition   Returns: bool chl_13p()   13-part candle higher low condition   Returns: bool chl_14p()   14-part candle higher low condition   Returns: bool chl_15p()   15-part candle higher low condition   Returns: bool chl_16p()   16-part candle higher low condition   Returns: bool chl_17p()   17-part candle higher low condition   Returns: bool chl_18p()   18-part candle higher low condition   Returns: bool chl_19p()   19-part candle higher low condition   Returns: bool chl_20p()   20-part candle higher low condition   Returns: bool chl_21p()   21-part candle higher low condition   Returns: bool chl_22p()   22-part candle higher low condition   Returns: bool chl_23p()   23-part candle higher low condition   Returns: bool chl_24p()   24-part candle higher low condition   Returns: bool chl_25p()   25-part candle higher low condition   Returns: bool chl_26p()   26-part candle higher low condition   Returns: bool chl_27p()   27-part candle higher low condition   Returns: bool chl_28p()   28-part candle higher low condition   Returns: bool chl_29p()   29-part candle higher low condition   Returns: bool chl_30p()   30-part candle higher low condition   Returns: bool clh_1p()   1-part candle lower high condition   Returns: bool clh_2p()   2-part candle lower high condition   Returns: bool clh_3p()   3-part candle lower high condition   Returns: bool clh_4p()   4-part candle lower high condition   Returns: bool clh_5p()   5-part candle lower high condition   Returns: bool clh_6p()   6-part candle lower high condition   Returns: bool clh_7p()   7-part candle lower high condition   Returns: bool clh_8p()   8-part candle lower high condition   Returns: bool clh_9p()   9-part candle lower high condition   Returns: bool clh_10p()   10-part candle lower high condition   Returns: bool clh_11p()   11-part candle lower high condition   Returns: bool clh_12p()   12-part candle lower high condition   Returns: bool clh_13p()   13-part candle lower high condition   Returns: bool clh_14p()   14-part candle lower high condition   Returns: bool clh_15p()   15-part candle lower high condition   Returns: bool clh_16p()   16-part candle lower high condition   Returns: bool clh_17p()   17-part candle lower high condition   Returns: bool clh_18p()   18-part candle lower high condition   Returns: bool clh_19p()   19-part candle lower high condition   Returns: bool clh_20p()   20-part candle lower high condition   Returns: bool clh_21p()   21-part candle lower high condition   Returns: bool clh_22p()   22-part candle lower high condition   Returns: bool clh_23p()   23-part candle lower high condition   Returns: bool clh_24p()   24-part candle lower high condition   Returns: bool clh_25p()   25-part candle lower high condition   Returns: bool clh_26p()   26-part candle lower high condition   Returns: bool clh_27p()   27-part candle lower high condition   Returns: bool clh_28p()   28-part candle lower high condition   Returns: bool clh_29p()   29-part candle lower high condition   Returns: bool clh_30p()   30-part candle lower high condition   Returns: bool cll_1p()   1-part candle lower low condition   Returns: bool cll_2p()   2-part candle lower low condition   Returns: bool cll_3p()   3-part candle lower low condition   Returns: bool cll_4p()   4-part candle lower low condition   Returns: bool cll_5p()   5-part candle lower low condition   Returns: bool cll_6p()   6-part candle lower low condition   Returns: bool cll_7p()   7-part candle lower low condition   Returns: bool cll_8p()   8-part candle lower low condition   Returns: bool cll_9p()   9-part candle lower low condition   Returns: bool cll_10p()   10-part candle lower low condition   Returns: bool cll_11p()   11-part candle lower low condition   Returns: bool cll_12p()   12-part candle lower low condition   Returns: bool cll_13p()   13-part candle lower low condition   Returns: bool cll_14p()   14-part candle lower low condition   Returns: bool cll_15p()   15-part candle lower low condition   Returns: bool cll_16p()   16-part candle lower low condition   Returns: bool cll_17p()   17-part candle lower low condition   Returns: bool cll_18p()   18-part candle lower low condition   Returns: bool cll_19p()   19-part candle lower low condition   Returns: bool cll_20p()   20-part candle lower low condition   Returns: bool cll_21p()   21-part candle lower low condition   Returns: bool cll_22p()   22-part candle lower low condition   Returns: bool cll_23p()   23-part candle lower low condition   Returns: bool cll_24p()   24-part candle lower low condition   Returns: bool cll_25p()   25-part candle lower low condition   Returns: bool cll_26p()   26-part candle lower low condition   Returns: bool cll_27p()   27-part candle lower low condition   Returns: bool cll_28p()   28-part candle lower low condition   Returns: bool cll_29p()   29-part candle lower low condition   Returns: bool cll_30p()   30-part candle lower low condition   Returns: bool gc_1p()   1-part green candle condition   Returns: bool gc_2p()   2-part green candle condition   Returns: bool gc_3p()   3-part green candle condition   Returns: bool gc_4p()   4-part green candle condition   Returns: bool gc_5p()   5-part green candle condition   Returns: bool gc_6p()   6-part green candle condition   Returns: bool gc_7p()   7-part green candle condition   Returns: bool gc_8p()   8-part green candle condition   Returns: bool gc_9p()   9-part green candle condition   Returns: bool gc_10p()   10-part green candle condition   Returns: bool gc_11p()   11-part green candle condition   Returns: bool gc_12p()   12-part green candle condition   Returns: bool gc_13p()   13-part green candle condition   Returns: bool gc_14p()   14-part green candle condition   Returns: bool gc_15p()   15-part green candle condition   Returns: bool gc_16p()   16-part green candle condition   Returns: bool gc_17p()   17-part green candle condition   Returns: bool gc_18p()   18-part green candle condition   Returns: bool gc_19p()   19-part green candle condition   Returns: bool gc_20p()   20-part green candle condition   Returns: bool gc_21p()   21-part green candle condition   Returns: bool gc_22p()   22-part green candle condition   Returns: bool gc_23p()   23-part green candle condition   Returns: bool gc_24p()   24-part green candle condition   Returns: bool gc_25p()   25-part green candle condition   Returns: bool gc_26p()   26-part green candle condition   Returns: bool gc_27p()   27-part green candle condition   Returns: bool gc_28p()   28-part green candle condition   Returns: bool gc_29p()   29-part green candle condition   Returns: bool gc_30p()   30-part green candle condition   Returns: bool rc_1p()   1-part red candle condition   Returns: bool rc_2p()   2-part red candle condition   Returns: bool rc_3p()   3-part red candle condition   Returns: bool rc_4p()   4-part red candle condition   Returns: bool rc_5p()   5-part red candle condition   Returns: bool rc_6p()   6-part red candle condition   Returns: bool rc_7p()   7-part red candle condition   Returns: bool rc_8p()   8-part red candle condition   Returns: bool rc_9p()   9-part red candle condition   Returns: bool rc_10p()   10-part red candle condition   Returns: bool rc_11p()   11-part red candle condition   Returns: bool rc_12p()   12-part red candle condition   Returns: bool rc_13p()   13-part red candle condition   Returns: bool rc_14p()   14-part red candle condition   Returns: bool rc_15p()   15-part red candle condition   Returns: bool rc_16p()   16-part red candle condition   Returns: bool rc_17p()   17-part red candle condition   Returns: bool rc_18p()   18-part red candle condition   Returns: bool rc_19p()   19-part red candle condition   Returns: bool rc_20p()   20-part red candle condition   Returns: bool rc_21p()   21-part red candle condition   Returns: bool rc_22p()   22-part red candle condition   Returns: bool rc_23p()   23-part red candle condition   Returns: bool rc_24p()   24-part red candle condition   Returns: bool rc_25p()   25-part red candle condition   Returns: bool rc_26p()   26-part red candle condition   Returns: bool rc_27p()   27-part red candle condition   Returns: bool rc_28p()   28-part red candle condition   Returns: bool rc_29p()   29-part red candle condition   Returns: bool rc_30p()   30-part red candle condition   Returns: bool cdut()   candle double uptrend condition   Returns: bool cddt()   candle double downtrend condition   Returns: bool cdut_1p()   1-part candle double uptrend condition   Returns: bool cdut_2p()   2-part candle double uptrend condition   Returns: bool cdut_3p()   3-part candle double uptrend condition   Returns: bool cdut_4p()   4-part candle double uptrend condition   Returns: bool cdut_5p()   5-part candle double uptrend condition   Returns: bool cdut_6p()   6-part candle double uptrend condition   Returns: bool cdut_7p()   7-part candle double uptrend condition   Returns: bool cdut_8p()   8-part candle double uptrend condition   Returns: bool cdut_9p()   9-part candle double uptrend condition   Returns: bool cdut_10p()   10-part candle double uptrend condition   Returns: bool cdut_11p()   11-part candle double uptrend condition   Returns: bool cdut_12p()   12-part candle double uptrend condition   Returns: bool cdut_13p()   13-part candle double uptrend condition   Returns: bool cdut_14p()   14-part candle double uptrend condition   Returns: bool cdut_15p()   15-part candle double uptrend condition   Returns: bool cdut_16p()   16-part candle double uptrend condition   Returns: bool cdut_17p()   17-part candle double uptrend condition   Returns: bool cdut_18p()   18-part candle double uptrend condition   Returns: bool cdut_19p()   19-part candle double uptrend condition   Returns: bool cdut_20p()   20-part candle double uptrend condition   Returns: bool cdut_21p()   21-part candle double uptrend condition   Returns: bool cdut_22p()   22-part candle double uptrend condition   Returns: bool cdut_23p()   23-part candle double uptrend condition   Returns: bool cdut_24p()   24-part candle double uptrend condition   Returns: bool cdut_25p()   25-part candle double uptrend condition   Returns: bool cdut_26p()   26-part candle double uptrend condition   Returns: bool cdut_27p()   27-part candle double uptrend condition   Returns: bool cdut_28p()   28-part candle double uptrend condition   Returns: bool cdut_29p()   29-part candle double uptrend condition   Returns: bool cdut_30p()   30-part candle double uptrend condition   Returns: bool cddt_1p()   1-part candle double downtrend condition   Returns: bool cddt_2p()   2-part candle double downtrend condition   Returns: bool cddt_3p()   3-part candle double downtrend condition   Returns: bool cddt_4p()   4-part candle double downtrend condition   Returns: bool cddt_5p()   5-part candle double downtrend condition   Returns: bool cddt_6p()   6-part candle double downtrend condition   Returns: bool cddt_7p()   7-part candle double downtrend condition   Returns: bool cddt_8p()   8-part candle double downtrend condition   Returns: bool cddt_9p()   9-part candle double downtrend condition   Returns: bool cddt_10p()   10-part candle double downtrend condition   Returns: bool cddt_11p()   11-part candle double downtrend condition   Returns: bool cddt_12p()   12-part candle double downtrend condition   Returns: bool cddt_13p()   13-part candle double downtrend condition   Returns: bool cddt_14p()   14-part candle double downtrend condition   Returns: bool cddt_15p()   15-part candle double downtrend condition   Returns: bool cddt_16p()   16-part candle double downtrend condition   Returns: bool cddt_17p()   17-part candle double downtrend condition   Returns: bool cddt_18p()   18-part candle double downtrend condition   Returns: bool cddt_19p()   19-part candle double downtrend condition   Returns: bool cddt_20p()   20-part candle double downtrend condition   Returns: bool cddt_21p()   21-part candle double downtrend condition   Returns: bool cddt_22p()   22-part candle double downtrend condition   Returns: bool cddt_23p()   23-part candle double downtrend condition   Returns: bool cddt_24p()   24-part candle double downtrend condition   Returns: bool cddt_25p()   25-part candle double downtrend condition   Returns: bool cddt_26p()   26-part candle double downtrend condition   Returns: bool cddt_27p()   27-part candle double downtrend condition   Returns: bool cddt_28p()   28-part candle double downtrend condition   Returns: bool cddt_29p()   29-part candle double downtrend condition   Returns: bool cddt_30p()   30-part candle double downtrend condition   Returns: bool
مكتبة Pine Script®
من ‎theEccentricTrader‎
2
Inside SwingsOverview The Inside Swings indicator identifies and visualizes "inside swing" patterns in price action. These patterns occur when price creates a series of pivots that form overlapping ranges, indicating potential consolidation or reversal zones. What are Inside Swings? Inside swings are specific pivot patterns where: - HLHL Pattern: High-Low-High-Low sequence where the first high is higher than the second high, and the first low is lower than the second low - LHLH Pattern: Low-High-Low-High sequence where the first low is lower than the second low, and the first high is higher than the second high Here an Example These patterns create overlapping price ranges that often act as: - Support/Resistance zones - Consolidation areas - Potential reversal points - Breakout levels Levels From the Created Range Input Parameters Core Settings - Pivot Lookback Length (default: 5): Number of bars on each side to confirm a pivot high/low - Max Boxes (default: 100): Maximum number of patterns to display on chart Extension Settings - Extend Lines: Enable/disable line extensions - this extends the Extremes of the Swings to where a new Swing Started or Extended Right for the Latest Inside Swings - Show High 1 Line: Display first high/low extension line - Show High 2 Line: Display second high/low extension line - Show Low 1 Line: Display first low/high extension line - Show Low 2 Line: Display second low/high extension line Visual Customization Box Colors - HLHL Box Color: Color for HLHL pattern boxes (default: green) - HLHL Border Color: Border color for HLHL boxes - LHLH Box Color: Color for LHLH pattern boxes (default: red) - LHLH Border Color: Border color for LHLH boxes Line Colors - HLHL Line Color: Extension line color for HLHL patterns - LHLH Line Color: Extension line color for LHLH patterns - Line Width: Thickness of extension lines (1-5) Pattern Detection Logic HLHL Pattern (Bullish Inside Swing) Condition: High1 > High2 AND Low1 < Low2 Sequence: High → Low → High → Low Visual: Two overlapping boxes with first range encompassing second Detection Criteria: 1. Last 4 pivots form High-Low-High-Low sequence 2. Fourth pivot (first high) > Second pivot (second high) 3. Third pivot (first low) < Last pivot (second low) LHLH Pattern (Bearish Inside Swing) Condition: Low1 < Low2 AND High1 > High2 Sequence: Low → High → Low → High Visual: Two overlapping boxes with first range encompassing second Detection Criteria: 1. Last 4 pivots form Low-High-Low-High sequence 2. Fourth pivot (first low) < Second pivot (second low) 3. Third pivot (first high) > Last pivot (second high) Visual Elements Boxes - Box 1: Spans from first pivot to last pivot (larger range) - Box 2: Spans from third pivot to last pivot (smaller range) - Overlap: The intersection of both boxes represents the inside swing zone Extension Lines - High 1 Line: Horizontal line at first high/low level - High 2 Line: Horizontal line at second high/low level - Low 1 Line: Horizontal line at first low/high level - Low 2 Line: Horizontal line at second low/high level Line Extension Behavior - Historical Patterns: Lines extend until the next pattern starts - Latest Pattern: Lines extend to the right edge of chart - Dynamic Updates: All lines are redrawn on each bar for accuracy Trading Applications Support/Resistance Levels Inside swing levels often act as: - Dynamic support/resistance - Breakout confirmation levels - Reversal entry points Pattern Interpretation - HLHL Patterns: Potential bullish continuation or reversal - LHLH Patterns: Potential bearish continuation or reversal - Overlap Zone: Key area for price interaction Entry Strategies 1. Breakout Strategy: Enter on break above/below inside swing levels 2. Reversal Strategy: Enter on bounce from inside swing levels 3. Range Trading: Trade between inside swing levels Technical Implementation Data Structures type InsideSwing int startBar // First pivot bar int endBar // Last pivot bar string patternType // "HLHL" or "LHLH" float high1 // First high/low float low1 // First low/high float high2 // Second high/low float low2 // Second low/high box box1 // First box box box2 // Second box line high1Line // High 1 extension line line high2Line // High 2 extension line line low1Line // Low 1 extension line line low2Line // Low 2 extension line bool isLatest // Latest pattern flag Memory Management - Pattern Storage: Array-based storage with automatic cleanup - Pivot Tracking: Maintains last 4 pivots for pattern detection - Resource Cleanup: Automatically removes oldest patterns when limit exceeded Performance Optimization - Duplicate Prevention: Checks for existing patterns before creation - Efficient Redraw: Only redraws lines when necessary - Memory Limits: Configurable maximum pattern count Usage Tips Best Practices 1. Combine with Volume: Use volume confirmation for breakouts 2. Multiple Timeframes: Check higher timeframes for context 3. Risk Management: Set stops beyond inside swing levels 4. Pattern Validation: Wait for confirmation before entering Common Scenarios - Consolidation Breakouts: Inside swings often precede significant moves - Reversal Zones: Failed breakouts at inside swing levels - Trend Continuation: Inside swings in trending markets Limitations - Lagging Indicator: Patterns form after completion - False Signals: Not all inside swings lead to significant moves - Market Dependent: Effectiveness varies by market conditions Customization Options Visual Adjustments - Modify colors for different market conditions - Adjust line widths for visibility - Enable/disable specific elements Detection Sensitivity - Increase pivot length for smoother patterns - Decrease for more sensitive detection - Balance between noise and signal Display Management - Control maximum pattern count - Adjust cleanup frequency - Manage memory usage Conclusion The Inside Swings indicator provides a systematic approach to identifying consolidation and potential reversal zones in price action. By visualizing overlapping pivot ranges The indicator's strength lies in its ability to: - Identify key price levels automatically - Provide visual context for market structure - Offer flexible customization options - Maintain performance through efficient memory management
مؤشر Pine Script®
من ‎mindyourbuisness‎
4
[Defaust] Fractals Fractals Indicator Overview The Fractals Indicator is a technical analysis tool designed to help traders identify potential reversal points in the market by detecting fractal patterns. This indicator is a fork of the original fractals indicator, with adjustments made to the plotting for enhanced visual clarity and usability. What Are Fractals? In trading, a fractal is a pattern consisting of five consecutive bars (candlesticks) that meet specific conditions: Up Fractal (Potential Sell Signal): Occurs when a high point is surrounded by two lower highs on each side. Down Fractal (Potential Buy Signal): Occurs when a low point is surrounded by two higher lows on each side. Fractals help traders identify potential tops and bottoms in the market, signaling possible entry or exit points. Features of the Indicator Customizable Periods (n): Allows you to define the number of periods to consider when detecting fractals, offering flexibility to adapt to different trading strategies and timeframes. Enhanced Plotting Adjustments: This fork introduces adjustments to the plotting of fractal signals for better visual representation on the chart. Visual Signals: Plots up and down triangles on the chart to signify down fractals (potential bullish signals) and up fractals (potential bearish signals), respectively. Overlay on Chart: The fractal signals are overlaid directly on the price chart for immediate visualization. Adjustable Precision: You can set the precision of the plotted values according to your needs. Pine Script Code Explanation Below is the Pine Script code for the Fractals Indicator: //@version=5 indicator(" Fractals", shorttitle=" Fractals", format=format.price, precision=0, overlay=true) // User input for the number of periods to consider for fractal detection n = input.int(title="Periods", defval=2, minval=2) // Initialize flags for up fractal detection bool upflagDownFrontier = true bool upflagUpFrontier0 = true bool upflagUpFrontier1 = true bool upflagUpFrontier2 = true bool upflagUpFrontier3 = true bool upflagUpFrontier4 = true // Loop through previous and future bars to check conditions for up fractals for i = 1 to n // Check if the highs of previous bars are less than the current bar's high upflagDownFrontier := upflagDownFrontier and (high < high ) // Check various conditions for future bars upflagUpFrontier0 := upflagUpFrontier0 and (high < high ) upflagUpFrontier1 := upflagUpFrontier1 and (high <= high and high < high ) upflagUpFrontier2 := upflagUpFrontier2 and (high <= high and high <= high and high < high ) upflagUpFrontier3 := upflagUpFrontier3 and (high <= high and high <= high and high <= high and high < high ) upflagUpFrontier4 := upflagUpFrontier4 and (high <= high and high <= high and high <= high and high <= high and high < high ) // Combine the flags to determine if an up fractal exists flagUpFrontier = upflagUpFrontier0 or upflagUpFrontier1 or upflagUpFrontier2 or upflagUpFrontier3 or upflagUpFrontier4 upFractal = (upflagDownFrontier and flagUpFrontier) // Initialize flags for down fractal detection bool downflagDownFrontier = true bool downflagUpFrontier0 = true bool downflagUpFrontier1 = true bool downflagUpFrontier2 = true bool downflagUpFrontier3 = true bool downflagUpFrontier4 = true // Loop through previous and future bars to check conditions for down fractals for i = 1 to n // Check if the lows of previous bars are greater than the current bar's low downflagDownFrontier := downflagDownFrontier and (low > low ) // Check various conditions for future bars downflagUpFrontier0 := downflagUpFrontier0 and (low > low ) downflagUpFrontier1 := downflagUpFrontier1 and (low >= low and low > low ) downflagUpFrontier2 := downflagUpFrontier2 and (low >= low and low >= low and low > low ) downflagUpFrontier3 := downflagUpFrontier3 and (low >= low and low >= low and low >= low and low > low ) downflagUpFrontier4 := downflagUpFrontier4 and (low >= low and low >= low and low >= low and low >= low and low > low ) // Combine the flags to determine if a down fractal exists flagDownFrontier = downflagUpFrontier0 or downflagUpFrontier1 or downflagUpFrontier2 or downflagUpFrontier3 or downflagUpFrontier4 downFractal = (downflagDownFrontier and flagDownFrontier) // Plot the fractal symbols on the chart with adjusted plotting plotshape(downFractal, style=shape.triangleup, location=location.belowbar, offset=-n, color=color.gray, size=size.auto) plotshape(upFractal, style=shape.triangledown, location=location.abovebar, offset=-n, color=color.gray, size=size.auto) Explanation: Input Parameter (n): Sets the number of periods for fractal detection. The default value is 2, and it must be at least 2 to ensure valid fractal patterns. Flag Initialization: Boolean variables are used to store intermediate conditions during fractal detection. Loops: Iterate through the specified number of periods to evaluate the conditions for fractal formation. Conditions: Up Fractals: Checks if the current high is greater than previous highs and if future highs are lower or equal to the current high. Down Fractals: Checks if the current low is lower than previous lows and if future lows are higher or equal to the current low. Flag Combination: Logical and and or operations are used to combine the flags and determine if a fractal exists. Adjusted Plotting: The plotting of fractal symbols has been adjusted for better alignment and visual clarity. The offset parameter is set to -n to align the plotted symbols with the correct bars. The color and size have been fine-tuned for better visibility. How to Use the Indicator Adding the Indicator to Your Chart Open TradingView: Go to TradingView. Access the Chart: Click on "Chart" to open the main charting interface. Add the Indicator: Click on the "Indicators" button at the top. Search for " Fractals". Select the indicator from the list to add it to your chart. Configuring the Indicator Periods (n): Default value is 2. Adjust this parameter based on your preferred timeframe and sensitivity. A higher value of n considers more bars for fractal detection, potentially reducing the number of signals but increasing their significance. Interpreting the Signals – Up Fractal (Downward Triangle): Indicates a potential price reversal to the downside. May be used as a signal to consider exiting long positions or tightening stop-loss orders. – Down Fractal (Upward Triangle): Indicates a potential price reversal to the upside. May be used as a signal to consider entering long positions or setting stop-loss orders for short positions. Trading Strategy Suggestions Up Fractal Detection: The high of the current bar (n) is higher than the highs of the previous two bars (n - 1, n - 2). The highs of the next bars meet certain conditions to confirm the fractal pattern. An up fractal symbol (downward triangle) is plotted above the bar at position n - n (due to the offset). Down Fractal Detection: The low of the current bar (n) is lower than the lows of the previous two bars (n - 1, n - 2). The lows of the next bars meet certain conditions to confirm the fractal pattern. A down fractal symbol (upward triangle) is plotted below the bar at position n - n. Benefits of Using the Fractals Indicator Early Signals: Helps in identifying potential reversal points in price movements. Customizable Sensitivity: Adjusting the n parameter allows you to fine-tune the indicator based on different market conditions. Enhanced Visuals: Adjustments to plotting improve the clarity and readability of fractal signals on the chart. Limitations and Considerations Lagging Indicator: Fractals require future bars to confirm the pattern, which may introduce a delay in the signals. False Signals: In volatile or ranging markets, fractals may produce false signals. It's advisable to use them in conjunction with other analysis tools. Not a Standalone Tool: Fractals should be part of a broader trading strategy that includes other indicators and fundamental analysis. Best Practices for Using This Indicator Combine with Other Indicators: Use in combination with trend indicators, oscillators, or volume analysis to confirm signals. Backtesting: Before applying the indicator in live trading, backtest it on historical data to understand its performance. Adjust Periods Accordingly: Experiment with different values of n to find the optimal setting for the specific asset and timeframe you are trading. Disclaimer The Fractals Indicator is intended for educational and informational purposes only. Trading involves significant risk, and you should be aware of the risks involved before proceeding. Past performance is not indicative of future results. Always conduct your own analysis and consult with a professional financial advisor before making any investment decisions. Credits This indicator is a fork of the original fractals indicator, with adjustments made to the plotting for improved visual representation. It is based on standard fractal patterns commonly used in technical analysis and has been developed to provide traders with an effective tool for detecting potential reversal points in the market.
مؤشر Pine Script®
من ‎defaustofficial‎
Trading IQ - ICT LibraryLibrary "ICTlibrary" Used to calculate various ICT related price levels and strategies. An ongoing project. Hello Coders! This library is meant for sourcing ICT related concepts. While some functions might generate more output than you require, you can specify "Lite Mode" as "true" in applicable functions to slim down necessary inputs. isLastBar(userTF)   Identifies the last bar on the chart before a timeframe change   Parameters:      userTF (simple int) : the timeframe you wish to calculate the last bar for, must be converted to integer using 'timeframe.in_seconds()'   Returns: bool true if bar on chart is last bar of higher TF, dalse if bar on chart is not last bar of higher TF necessaryData(atrTF)   returns necessaryData UDT for historical data access   Parameters:      atrTF (float) : user-selected timeframe ATR value.   Returns: logZ. log return Z score, used for calculating order blocks. method gradBoxes(gradientBoxes, idColor, timeStart, bottom, top, rightCoordinate)   creates neon like effect for box drawings   Namespace types: array   Parameters:      gradientBoxes (array) : an array.new() to store the gradient boxes      idColor (color)      timeStart (int) : left point of box      bottom (float) : bottom of box price point      top (float) : top of box price point      rightCoordinate (int) : right point of box   Returns: void checkIfTraded(tradeName)   checks if recent trade is of specific name   Parameters:      tradeName (string)   Returns: bool true if recent trade id matches target name, false otherwise checkIfClosed(tradeName)   checks if recent closed trade is of specific name   Parameters:      tradeName (string)   Returns: bool true if recent closed trade id matches target name, false otherwise IQZZ(atrMult, finalTF)   custom ZZ to quickly determine market direction.   Parameters:      atrMult (float) : an atr multiplier used to determine the required price move for a ZZ direction change      finalTF (string) : the timeframe used for the atr calcuation   Returns: dir market direction. Up => 1, down => -1 method drawBos(id, startPoint, getKeyPointTime, getKeyPointPrice, col, showBOS, isUp)   calculates and draws Break Of Structure   Namespace types: array   Parameters:      id (array)      startPoint (chart.point)      getKeyPointTime (int) : the actual time of startPoint, simplystartPoint.time      getKeyPointPrice (float) : the actual time of startPoint, simplystartPoint.price      col (color) : color of the BoS line / label      showBOS (bool) : whether to show label/line. This function still calculates internally for other ICT related concepts even if not drawn.      isUp (bool) : whether BoS happened during price increase or price decrease.   Returns: void method drawMSS(id, startPoint, getKeyPointTime, getKeyPointPrice, col, showMSS, isUp, upRejections, dnRejections, highArr, lowArr, timeArr, closeArr, openArr, atrTFarr, upRejectionsPrices, dnRejectionsPrices)   calculates and draws Market Structure Shift. This data is also used to calculate Rejection Blocks.   Namespace types: array   Parameters:      id (array)      startPoint (chart.point)      getKeyPointTime (int) : the actual time of startPoint, simplystartPoint.time      getKeyPointPrice (float) : the actual time of startPoint, simplystartPoint.price      col (color) : color of the MSS line / label      showMSS (bool) : whether to show label/line. This function still calculates internally for other ICT related concepts even if not drawn.      isUp (bool) : whether MSS happened during price increase or price decrease.      upRejections (array)      dnRejections (array)      highArr (array) : array containing historical highs, should be taken from the UDT "necessaryData" defined above      lowArr (array) : array containing historical lows, should be taken from the UDT "necessaryData" defined above      timeArr (array) : array containing historical times, should be taken from the UDT "necessaryData" defined above      closeArr (array) : array containing historical closes, should be taken from the UDT "necessaryData" defined above      openArr (array) : array containing historical opens, should be taken from the UDT "necessaryData" defined above      atrTFarr (array) : array containing historical atr values (of user-selected TF), should be taken from the UDT "necessaryData" defined above      upRejectionsPrices (array) : array containing up rejections prices. Is sorted and used to determine selective looping for invalidations.      dnRejectionsPrices (array) : array containing down rejections prices. Is sorted and used to determine selective looping for invalidations.   Returns: void method getTime(id, compare, timeArr)   gets time of inputted price (compare) in an array of data this is useful when the user-selected timeframe for ICT concepts is greater than the chart's timeframe   Namespace types: array   Parameters:      id (array) : the array of data to search through, to find which index has the same value as "compare"      compare (float) : the target data point to find in the array      timeArr (array) : array of historical times   Returns: the time that the data point in the array was recorded method OB(id, highArr, signArr, lowArr, timeArr, sign)   store bullish orderblock data   Namespace types: array   Parameters:      id (array)      highArr (array) : array of historical highs      signArr (array) : array of historical price direction "math.sign(close - open)"      lowArr (array) : array of historical lows      timeArr (array) : array of historical times      sign (int) : orderblock direction, -1 => bullish, 1 => bearish   Returns: void OTEstrat(OTEstart, future, closeArr, highArr, lowArr, timeArr, longOTEPT, longOTESL, longOTElevel, shortOTEPT, shortOTESL, shortOTElevel, structureDirection, oteLongs, atrTF, oteShorts)   executes the OTE strategy   Parameters:      OTEstart (chart.point)      future (int) : future time point for drawings      closeArr (array) : array of historical closes      highArr (array) : array of historical highs      lowArr (array) : array of historical lows      timeArr (array) : array of historical times      longOTEPT (string) : user-selected long OTE profit target, please create an input.string() for this using the example below      longOTESL (int) : user-selected long OTE stop loss, please create an input.string() for this using the example below      longOTElevel (float) : long entry price of selected retracement ratio for OTE      shortOTEPT (string) : user-selected short OTE profit target, please create an input.string() for this using the example below      shortOTESL (int) : user-selected short OTE stop loss, please create an input.string() for this using the example below      shortOTElevel (float) : short entry price of selected retracement ratio for OTE      structureDirection (string) : current market structure direction, this should be "Up" or "Down". This is used to cancel pending orders if market structure changes      oteLongs (bool) : input.bool() for whether OTE longs can be executed      atrTF (float) : atr of the user-seleceted TF      oteShorts (bool) : input.bool() for whether OTE shorts can be executed @exampleInputs oteLongs = input.bool(defval = false, title = "OTE Longs", group = "Optimal Trade Entry") longOTElevel = input.float(defval = 0.79, title = "Long Entry Retracement Level", options = , group = "Optimal Trade Entry") longOTEPT = input.string(defval = "-0.5", title = "Long TP", options = , group = "Optimal Trade Entry") longOTESL = input.int(defval = 0, title = "How Many Ticks Below Swing Low For Stop Loss", group = "Optimal Trade Entry") oteShorts = input.bool(defval = false, title = "OTE Shorts", group = "Optimal Trade Entry") shortOTElevel = input.float(defval = 0.79, title = "Short Entry Retracement Level", options = , group = "Optimal Trade Entry") shortOTEPT = input.string(defval = "-0.5", title = "Short TP", options = , group = "Optimal Trade Entry") shortOTESL = input.int(defval = 0, title = "How Many Ticks Above Swing Low For Stop Loss", group = "Optimal Trade Entry")   Returns: void (0) displacement(logZ, atrTFreg, highArr, timeArr, lowArr, upDispShow, dnDispShow, masterCoords, labelLevels, dispUpcol, rightCoordinate, dispDncol, noBorders)   calculates and draws dispacements   Parameters:      logZ (float) : log return of current price, used to determine a "significant price move" for a displacement      atrTFreg (float) : atr of user-seleceted timeframe      highArr (array) : array of historical highs      timeArr (array) : array of historical times      lowArr (array) : array of historical lows      upDispShow (int) : amount of historical upside displacements to show      dnDispShow (int) : amount of historical downside displacements to show      masterCoords (map) : a map to push the most recent displacement prices into, useful for having key levels in one data structure      labelLevels (string) : used to determine label placement for the displacement, can be inside box, outside box, or none, example below      dispUpcol (color) : upside displacement color      rightCoordinate (int) : future time for displacement drawing, best is "last_bar_time"      dispDncol (color) : downside displacement color      noBorders (bool) : input.bool() to remove box borders, example below @exampleInputs labelLevels = input.string(defval = "Inside" , title = "Box Label Placement", options = ) noBorders = input.bool(defval = false, title = "No Borders On Levels")   Returns: void method getStrongLow(id, startIndex, timeArr, lowArr, strongLowPoints)   unshift strong low data to array id   Namespace types: array   Parameters:      id (array)      startIndex (int) : the starting index for the timeArr array of the UDT "necessaryData". this point should start from at least 1 pivot prior to find the low before an upside BoS      timeArr (array) : array of historical times      lowArr (array) : array of historical lows      strongLowPoints (array) : array of strong low prices. Used to retrieve highest strong low price and see if need for removal of invalidated strong lows   Returns: void method getStrongHigh(id, startIndex, timeArr, highArr, strongHighPoints)   unshift strong high data to array id   Namespace types: array   Parameters:      id (array)      startIndex (int) : the starting index for the timeArr array of the UDT "necessaryData". this point should start from at least 1 pivot prior to find the high before a downside BoS      timeArr (array) : array of historical times      highArr (array) : array of historical highs      strongHighPoints (array)   Returns: void equalLevels(highArr, lowArr, timeArr, rightCoordinate, equalHighsCol, equalLowsCol, liteMode)   used to calculate recent equal highs or equal lows   Parameters:      highArr (array) : array of historical highs      lowArr (array) : array of historical lows      timeArr (array) : array of historical times      rightCoordinate (int) : a future time (right for boxes, x2 for lines)      equalHighsCol (color) : user-selected color for equal highs drawings      equalLowsCol (color) : user-selected color for equal lows drawings      liteMode (bool) : optional for a lite mode version of an ICT strategy. For more control over drawings leave as "True", "False" will apply neon effects   Returns: void quickTime(timeString)   used to quickly determine if a user-inputted time range is currently active in NYT time   Parameters:      timeString (string) : a time range   Returns: true if session is active, false if session is inactive macros(showMacros, noBorders)   used to calculate and draw session macros   Parameters:      showMacros (bool) : an input.bool() or simple bool to determine whether to activate the function      noBorders (bool) : an input.bool() to determine whether the box anchored to the session should have borders   Returns: void po3(tf, left, right, show)   use to calculate HTF po3 candle @tip only call this function on "barstate.islast"   Parameters:      tf (simple string)      left (int) : the left point of the candle, calculated as bar_index + left,      right (int) : :the right point of the candle, calculated as bar_index + right,      show (bool) : input.bool() whether to show the po3 candle or not   Returns: void silverBullet(silverBulletStratLong, silverBulletStratShort, future, userTF, H, L, H2, L2, noBorders, silverBulletLongTP, historicalPoints, historicalData, silverBulletLongSL, silverBulletShortTP, silverBulletShortSL)   used to execute the Silver Bullet Strategy   Parameters:      silverBulletStratLong (simple bool)      silverBulletStratShort (simple bool)      future (int) : a future time, used for drawings, example "last_bar_time"      userTF (simple int)      H (float) : the high price of the user-selected TF      L (float) : the low price of the user-selected TF      H2 (float) : the high price of the user-selected TF      L2 (float) : the low price of the user-selected TF      noBorders (bool) : an input.bool() used to remove the borders from box drawings      silverBulletLongTP (series silverBulletLevels)      historicalPoints (array)      historicalData (necessaryData)      silverBulletLongSL (series silverBulletLevels)      silverBulletShortTP (series silverBulletLevels)      silverBulletShortSL (series silverBulletLevels)   Returns: void method invalidFVGcheck(FVGarr, upFVGpricesSorted, dnFVGpricesSorted)   check if existing FVGs are still valid   Namespace types: array   Parameters:      FVGarr (array)      upFVGpricesSorted (array) : an array of bullish FVG prices, used to selective search through FVG array to remove invalidated levels      dnFVGpricesSorted (array) : an array of bearish FVG prices, used to selective search through FVG array to remove invalidated levels   Returns: void (0) method drawFVG(counter, FVGshow, FVGname, FVGcol, data, masterCoords, labelLevels, borderTransp, liteMode, rightCoordinate)   draws FVGs on last bar   Namespace types: map   Parameters:      counter (map) : a counter, as map, keeping count of the number of FVGs drawn, makes sure that there aren't more FVGs drawn than int FVGshow      FVGshow (int) : the number of FVGs to show. There should be a bullish FVG show and bearish FVG show. This function "drawFVG" is used separately for bearish FVG and bullish FVG.      FVGname (string) : the name of the FVG, "FVG Up" or "FVG Down"      FVGcol (color) : desired FVG color      data (FVG)      masterCoords (map) : a map containing the names and price points of key levels. Used to define price ranges.      labelLevels (string) : an input.string with options "Inside", "Outside", "Remove". Determines whether FVG labels should be inside box, outside, or na.      borderTransp (int)      liteMode (bool)      rightCoordinate (int) : the right coordinate of any drawings. Must be a time point.   Returns: void invalidBlockCheck(bullishOBbox, bearishOBbox, userTF)   check if existing order blocks are still valid   Parameters:      bullishOBbox (array) : an array declared using the UDT orderBlock that contains bullish order block related data      bearishOBbox (array) : an array declared using the UDT orderBlock that contains bearish order block related data      userTF (simple int)   Returns: void (0) method lastBarRejections(id, rejectionColor, idShow, rejectionString, labelLevels, borderTransp, liteMode, rightCoordinate, masterCoords)   draws rejectionBlocks on last bar   Namespace types: array   Parameters:      id (array) : the array, an array of rejection block data declared using the UDT rejection block      rejectionColor (color) : the desired color of the rejection box      idShow (int)      rejectionString (string) : the desired name of the rejection blocks      labelLevels (string) : an input.string() to determine if labels for the block should be inside the box, outside, or none.      borderTransp (int)      liteMode (bool) : an input.bool(). True = neon effect, false = no neon.      rightCoordinate (int) : atime for the right coordinate of the box      masterCoords (map) : a map that stores the price of key levels and assigns them a name, used to determine price ranges   Returns: void method OBdraw(id, OBshow, BBshow, OBcol, BBcol, bullishString, bearishString, isBullish, labelLevels, borderTransp, liteMode, rightCoordinate, masterCoords)   draws orderblocks and breaker blocks for data stored in UDT array()   Namespace types: array   Parameters:      id (array) : the array, an array of order block data declared using the UDT orderblock      OBshow (int) : the number of order blocks to show      BBshow (int) : the number of breaker blocks to show      OBcol (color) : color of order blocks      BBcol (color) : color of breaker blocks      bullishString (string) : the title of bullish blocks, which is a regular bullish orderblock or a bearish orderblock that's converted to breakerblock      bearishString (string) : the title of bearish blocks, which is a regular bearish orderblock or a bullish orderblock that's converted to breakerblock      isBullish (bool) : whether the array contains bullish orderblocks or bearish orderblocks. If bullish orderblocks, the array will naturally contain bearish BB, and if bearish OB, the array will naturally contain bullish BB      labelLevels (string) : an input.string() to determine if labels for the block should be inside the box, outside, or none.      borderTransp (int)      liteMode (bool) : an input.bool(). True = neon effect, false = no neon.      rightCoordinate (int) : atime for the right coordinate of the box      masterCoords (map) : a map that stores the price of key levels and assigns them a name, used to determine price ranges   Returns: void FVG   UDT for FVG calcualtions   Fields:      H (series float) : high price of user-selected timeframe      L (series float) : low price of user-selected timeframe      direction (series string) : FVG direction => "Up" or "Down"      T (series int) : => time of bar on user-selected timeframe where FVG was created      fvgLabel (series label) : optional label for FVG      fvgLineTop (series line) : optional line for top of FVG      fvgLineBot (series line) : optional line for bottom of FVG      fvgBox (series box) : optional box for FVG labelLine   quickly pair a line and label together as UDT   Fields:      lin (series line) : Line you wish to pair with label      lab (series label) : Label you wish to pair with line orderBlock   UDT for order block calculations   Fields:      orderBlockData (array) : array containing order block x and y points      orderBlockBox (series box) : optional order block box      vioCount (series int) : = 0 violation count of the order block. 0 = Order Block, 1 = Breaker Block      traded (series bool)      status (series string) : = "OB" status == "OB" => Level is order block. status == "BB" => Level is breaker block.      orderBlockLab (series label) : options label for the order block / breaker block. strongPoints   UDT for strong highs and strong lows   Fields:      price (series float) : price of the strong high or strong low      timeAtprice (series int) : time of the strong high or strong low      strongPointLabel (series label) : optional label for strong point      strongPointLine (series line) : optional line for strong point      overlayLine (series line) : optional lines for strong point to enhance visibility      overlayLine2 (series line) : optional lines for strong point to enhance visibility displacement   UDT for dispacements   Fields:      highPrice (series float) : high price of displacement      lowPrice (series float) : low price of displacement      timeAtPrice (series int) : time of bar where displacement occurred      displacementBox (series box) : optional box to draw displacement      displacementLab (series label) : optional label for displacement po3data   UDT for po3 calculations   Fields:      dHigh (series float) : higher timeframe high price      dLow (series float) : higher timeframe low price      dOpen (series float) : higher timeframe open price      dClose (series float) : higher timeframe close price      po3box (series box) : box to draw po3 candle body      po3line (array) : line array to draw po3 wicks      po3Labels (array) : label array to label price points of po3 candle macros   UDT for session macros   Fields:      sessions (array) : Array of sessions, you can populate this array using the "quickTime" function located above "export macros".      prices (matrix) : Matrix of session data -> open, high, low, close, time      sessionTimes (array) : Array of session names. Pairs with array sessions.      sessionLines (matrix) : Optional array for sesion drawings. OTEtimes   UDT for data storage and drawings associated with OTE strategy   Fields:      upTimes (array) : time of highest point before trade is taken      dnTimes (array) : time of lowest point before trade is taken      tpLineLong (series line) : line to mark tp level long      tpLabelLong (series label) : label to mark tp level long      slLineLong (series line) : line to mark sl level long      slLabelLong (series label) : label to mark sl level long      tpLineShort (series line) : line to mark tp level short      tpLabelShort (series label) : label to mark tp level short      slLineShort (series line) : line to mark sl level short      slLabelShort (series label) : label to mark sl level short sweeps   UDT for data storage and drawings associated with liquidity sweeps   Fields:      upSweeps (matrix) : matrix containing liquidity sweep price points and time points for up sweeps      dnSweeps (matrix) : matrix containing liquidity sweep price points and time points for down sweeps      upSweepDrawings (array) : optional up sweep box array. Pair the size of this array with the rows or columns,      dnSweepDrawings (array) : optional up sweep box array. Pair the size of this array with the rows or columns, raidExitDrawings   UDT for drawings associated with the Liquidity Raid Strategy   Fields:      tpLine (series line) : tp line for the liquidity raid entry      tpLabel (series label) : tp label for the liquidity raid entry      slLine (series line) : sl line for the liquidity raid entry      slLabel (series label) : sl label for the liquidity raid entry m2022   UDT for data storage and drawings associated with the Model 2022 Strategy   Fields:      mTime (series int) : time of the FVG where entry limit order is placed      mIndex (series int) : array index of FVG where entry limit order is placed. This requires an array of FVG data, which is defined above.      mEntryDistance (series float) : the distance of the FVG to the 50% range. M2022 looks for the fvg closest to 50% mark of range.      mEntry (series float) : the entry price for the most eligible fvg      fvgHigh (series float) : the high point of the eligible fvg      fvgLow (series float) : the low point of the eligible fvg      longFVGentryBox (series box) : long FVG box, used to draw the eligible FVG      shortFVGentryBox (series box) : short FVG box, used to draw the eligible FVG      line50P (series line) : line used to mark 50% of the range      line100P (series line) : line used to mark 100% (top) of the range      line0P (series line) : line used to mark 0% (bottom) of the range      label50P (series label) : label used to mark 50% of the range      label100P (series label) : label used to mark 100% (top) of the range      label0P (series label) : label used to mark 0% (bottom) of the range      sweepData (array) silverBullet   UDT for data storage and drawings associated with the Silver Bullet Strategy   Fields:      session (series bool)      sessionStr (series string) : name of the session for silver bullet      sessionBias (series string)      sessionHigh (series float) : = high high of session // use math.max(silverBullet.sessionHigh, high)      sessionLow (series float) : = low low of session // use math.min(silverBullet.sessionLow, low)      sessionFVG (series float) : if applicable, the FVG created during the session      sessionFVGdraw (series box) : if applicable, draw the FVG created during the session      traded (series bool)      tp (series float) : tp of trade entered at the session FVG      sl (series float) : sl of trade entered at the session FVG      sessionDraw (series box) : optional draw session with box      sessionDrawLabel (series label) : optional label session with label silverBulletDrawings   UDT for trade exit drawings associated with the Silver Bullet Strategy   Fields:      tpLine (series line) : tp line drawing for strategy      tpLabel (series label) : tp label drawing for strategy      slLine (series line) : sl line drawing for strategy      slLabel (series label) : sl label drawing for strategy unicornModel   UDT for data storage and drawings associated with the Unicorn Model Strategy   Fields:      hPoint (chart.point)      hPoint2 (chart.point)      hPoint3 (chart.point)      breakerBlock (series box) : used to draw the breaker block required for the Unicorn Model      FVG (series box) : used to draw the FVG required for the Unicorn model      topBlock (series float) : price of top of breaker block, can be used to detail trade entry      botBlock (series float) : price of bottom of breaker block, can be used to detail trade entry      startBlock (series int) : start time of the breaker block, used to set the "left = " param for the box      includes (array) : used to store the time of the breaker block, or FVG, or the chart point sequence that setup the Unicorn Model.      entry (series float) : // eligible entry price, for longs"math.max(topBlock, FVG.get_top())",      tpLine (series line) : optional line to mark PT      tpLabel (series label) : optional label to mark PT      slLine (series line) : optional line to mark SL      slLabel (series label) : optional label to mark SL rejectionBlocks   UDT for data storage and drawings associated with rejection blocks   Fields:      rejectionPoint (chart.point)      bodyPrice (series float) : candle body price closest to the rejection point, for "Up" rejections => math.max(open, close),      rejectionBox (series box) : optional box drawing of the rejection block      rejectionLabel (series label) : optional label for the rejection block equalLevelsDraw   UDT for data storage and drawings associated with equal highs / equal lows   Fields:      connector (series line) : single line placed at the first high or low, y = avgerage of distinguished equal highs/lows      connectorLab (series label) : optional label to be placed at the highs or lows      levels (array) : array containing the equal highs or lows prices      times (array) : array containing the equal highs or lows individual times      startTime (series int) : the time of the first high or low that forms a sequence of equal highs or lows      radiate (array) : options label to "radiate" the label in connector lab. Can be used for anything necessaryData   UDT for data storage of historical price points.   Fields:      highArr (array) : array containing historical high points      lowArr (array) : array containing historical low points      timeArr (array) : array containing historical time points      logArr (array) : array containing historical log returns      signArr (array) : array containing historical price directions      closeArr (array) : array containing historical close points      binaryTimeArr (array) : array containing historical time points, uses "push" instead of "unshift" to allow for binary search      binaryCloseArr (array) : array containing historical close points, uses "push" instead of "unshift" to allow the correct      binaryOpenArr (array) : array containing historical optn points, uses "push" instead of "unshift" to allow the correct      atrTFarr (array) : array containing historical user-selected TF atr points      openArr (array) : array containing historical open points
مكتبة Pine Script®
من ‎Trading-IQ‎
1
Smart Market Structure and Swing Points, version 1.0Smart Market Structure and Swing Points, Version 1.0 Overview The Smart Market Structure and Swing Points script is designed to provide advanced insights into market structure and key swing points. This script helps identify important highs and lows, trend direction changes (structure breaks), and swing points, enhancing decision-making for both trend-following and reversal strategies. See below for detail presentation and why it has unique features. Unique Features of the New Script Market Structure Identification : Analyzes and marks key highs and lows to determine market structure, including higher highs, lower highs, higher lows, and lower lows. Customizable Detection Length : Allows users to set the length for detecting highs and lows, providing flexibility to adapt to different market conditions and timeframes. Default value is 5 bars, but can be changed if needed. Visual Signal Indicators (Labels) : Plots labels on the chart to indicate higher highs (HH), lower highs (LH), higher lows (HL), and lower lows (LL), along with corresponding RSI values, offering clear visual cues for market structure analysis. The indication of RSI values directly on high and low points enables to better judge whether the points are strong references (extreme RSI values) or weak references (middle RSI values) Dynamic Trend Lines : Draws solid and dotted lines to connect significant highs and lows, visually representing the current trend direction and potential trend changes. Dashed lines indicates structure breaks. Swing High and Swing Low Detection : Identifies and marks the most recent swing highs and swing lows, helping traders spot potential reversal points and key levels for setting stop losses or take profit targets . Originality and Usefulness This script combines market structure, trend breaks and RSI to provide a more robust view of market dynamic by indicating the strength or weakness of swing points , in that way the script is unique. Signal Description The script includes various signal features that highlight potential trading opportunities based on market structure: Higher Highs (HH) and Higher Lows (HL) : These labels are plotted when new highs or lows are formed, indicating a continuation of an uptrend. The labels are positioned with consideration of the Average True Range (ATR) for better visibility. Lower Highs (LH) and Lower Lows (LL) : These labels are plotted when new highs or lows are formed, indicating a continuation of a downtrend. The labels include RSI values to provide additional information on the strength or weakness of the points. Trend Direction Change : Dotted lines are drawn to indicate potential trend direction changes when the script detects significant shifts in market structure. Swing Highs and Swing Lows : These are identified based on a customizable swing length, marking recent significant highs and lows to highlight potential reversal points. These signals help identify high-probability turning points and confirm trend direction by ensuring that the market structure aligns with the trading strategy. Detailed Description Input Variables Length for High/Low Detection (`length`) : Defines the range to check for highs and lows. Default is 5. RSI Length (`rsilength`) : The number of periods to calculate the RSI. Default is 14. Functionality Market Structure Calculation : The script determines the highest high and lowest low within the specified range to identify key points in market structure. ```pine h = ta.highest(high, length * 2 + 1) l = ta.lowest(low, length * 2 + 1) ``` Directional Logic : Variables and functions manage the state of the indicator, updating highs and lows based on the current trend direction. ```pine var bool dirUp = false var float lastLow = high * 100 var float lastHigh = 0.0 // Additional variables for tracking state ``` Drawing Lines and Labels : Functions draw lines and labels on the chart to visualize market structure and trend changes. ```pine f_drawLine() => _li_color = dirUp ? color.red : color.lime line.new(x1=timeHigh - length, y1=lastHigh, x2=timeLow - length, y2=lastLow, color=_li_color, width=3, style=line.style_solid, xloc=xloc.bar_index) f_drawLastLine() => _li_color = dirUp ? color.blue : color.blue if timeHigh > timeLow line.new(x1=timeHigh - length, y1=lastHigh, x2=bar_index, y2=low, color=_li_color, width=2, style=line.style_dotted, xloc=xloc.bar_index) else line.new(x1=timeLow - length, y1=lastLow, x2=bar_index, y2=high, color=_li_color, width=2, style=line.style_dotted, xloc=xloc.bar_index) ``` Updating Highs and Lows : The main logic updates highs and lows based on the current trend direction, adding labels for new higher highs, lower highs, higher lows, and lower lows. ```pine if dirUp if f_isMin(length) lastLow := low // Additional logic for updating lows and labels if f_isMax(length) and high > lastLow lastHigh := high // Additional logic for updating highs and labels dirUp := false li := f_drawLine() ``` Swing Highs and Lows : The script identifies recent swing highs and swing lows based on a customizable swing length, drawing lines to mark these points. ```pine swingLength = 3 * length isSwingHigh = ta.highestbars(high, swingLength) == 0 isSwingLow = ta.lowestbars(low, swingLength) == 0 if (isSwingHigh) if (na(highLine)) highLine := line.new(bar_index, high, bar_index, high, color=color.green, style=line.style_solid, width=1) else line.set_xy1(highLine, bar_index, high) line.set_xy2(highLine, bar_index + swingLength, high) if (isSwingLow) if (na(lowLine)) lowLine := line.new(bar_index, low, bar_index, low, color=color.red, style=line.style_solid, width=1) else line.set_xy1(lowLine, bar_index, low) line.set_xy2(lowLine, bar_index + swingLength, low) ``` How to Use Configuring Inputs : Adjust the detection length and RSI length as needed. Modify the lookback periods to suit your trading strategy. The indicator is adaptable and can be used on any timeframe. Interpreting the Indicator : Use the labels and lines to gauge market structure and trend direction. Look for higher highs, lower highs, higher lows, and lower lows to confirm market structure. Signal Confirmation : Pay attention to the labels and lines that provide signals for potential trend changes and swing points. Use these signals to better time entries and exits. This script provides a detailed view of market structure and swing points, helping make more informed decisions by considering key highs and lows, trend direction changes, and the strength or weakness of swing points.
مؤشر Pine Script®
من ‎adridem‎
3
MarketStructureLibrary "MarketStructure" This library contains functions for identifying Lows and Highs in a rule-based way, and deriving useful information from them. f_simpleLowHigh() This function finds Local Lows and Highs, but NOT in order. A Local High is any candle that has its Low taken out on close by a subsequent candle (and vice-versa for Local Lows). The Local High does NOT have to be the candle with the highest High out of recent candles. It does NOT have to be a Williams High. It is not necessarily a swing high or a reversal or anything else. It doesn't have to be "the" high, so don't be confused. By the rules, Local Lows and Highs must alternate. In this function they do not, so I'm calling them Simple Lows and Highs. Simple Highs and Lows, by the above definition, can be useful for entries and stops. Because I intend to use them for stops, I want them all, not just the ones that alternate in strict order. @param - there are no parameters. The function uses the chart OHLC. @returns boolean values for whether this bar confirms a Simple Low/High, and ints for the bar_index of that Low/High. f_localLowHigh() This function finds Local Lows and Highs, in order. A Local High is any candle that has its Low taken out on close by a subsequent candle (and vice-versa for Local Lows). The Local High does NOT have to be the candle with the highest High out of recent candles. It does NOT have to be a Williams High. It is not necessarily a swing high or a reversal or anything else. By the rules, Local Lows and Highs must alternate, and in this function they do. @param - there are no parameters. The function uses the chart OHLC. @returns boolean values for whether this bar confirms a Local Low/High, and ints for the bar_index of that Low/High. f_enhancedSimpleLowHigh() This function finds Local Lows and Highs, but NOT in order. A Local High is any candle that has its Low taken out on close by a subsequent candle (and vice-versa for Local Lows). The Local High does NOT have to be the candle with the highest High out of recent candles. It does NOT have to be a Williams High. It is not necessarily a swing high or a reversal or anything else. By the rules, Local Lows and Highs must alternate. In this function they do not, so I'm calling them Simple Lows and Highs. Simple Highs and Lows, by the above definition, can be useful for entries and stops. Because I intend to use them for trailing stops, I want them all, not just the ones that alternate in strict order. The difference between this function and f_simpleLowHigh() is that it also tracks the lowest/highest recent level. This level can be useful for trailing stops. In effect, these are like more "normal" highs and lows that you would pick by eye, but confirmed faster in many cases than by waiting for the low/high of that particular candle to be taken out on close, because they are instead confirmed by ANY subsequent candle having its low/high exceeded. Hence, I call these Enhanced Simple Lows/Highs. The levels are taken from the extreme highs/lows, but the bar indexes are given for the candles that were actually used to confirm the Low/High. This is by design, because it might be misleading to label the extreme, since we didn't use that candle to confirm the Low/High.. @param - there are no parameters. The function uses the chart OHLC. @returns - boolean values for whether this bar confirms an Enhanced Simple Low/High ints for the bar_index of that Low/High floats for the values of the recent high/low levels floats for the trailing high/low levels (for debug/post-processing) bools for market structure bias f_trueLowHigh() This function finds True Lows and Highs. A True High is the candle with the highest recent high, which then has its low taken out on close by a subsequent candle (and vice-versa for True Lows). The difference between this and an Enhanced High is that confirmation requires not just any Simple High, but confirmation of the very candle that has the highest high. Because of this, confirmation is often later, and multiple Simple Highs and Lows can develop within ranges formed by a single big candle without any of them being confirmed. This is by design. A True High looks like the intuitive "real high" when you look at the chart. True Lows and Highs must alternate. @param - there are no parameters. The function uses the chart OHLC. @returns - boolean values for whether this bar confirms an Enhanced Simple Low/High ints for the bar_index of that Low/High floats for the values of the recent high/low levels floats for the trailing high/low levels (for debug/post-processing) bools for market structure bias
مكتبة Pine Script®
من ‎SimpleCryptoLife‎
13
TR_HighLow_LibLibrary "TR_HighLow_Lib" TODO: add library description here ShowLabel(_Text, _X, _Y, _Style, _Size, _Yloc, _Color)   TODO: Function to display labels   Parameters:      _Text : TODO: text (series string) Label text.      _X : TODO: x (series int) Bar index.      _Y : TODO: y (series int/float) Price of the label position.      _Style : TODO: style (series string) Label style.      _Size : TODO: size (series string) Label size.      _Yloc : TODO: yloc (series string) Possible values are yloc.price, yloc.abovebar, yloc.belowbar.      _Color : TODO: color (series color) Color of the label border and arrow   Returns: TODO: No return values GetColor(_Index)   TODO: Function to take out 12 colors in order   Parameters:      _Index : TODO: color number.   Returns: TODO: color code Tbl_position(_Pos)   TODO: Table display position function   Parameters:      _Pos : TODO: position.   Returns: TODO: Table position DeleteLine()   TODO: Delete Line   Parameters:      : TODO: No parameter   Returns: TODO: No return value DeleteLabel()   TODO: Delete Label   Parameters:      : TODO: No parameter   Returns: TODO: No return value ZigZag(_a_PHiLo, _a_IHiLo, _a_FHiLo, _a_DHiLo, _Histories, _Provisional_PHiLo, _Provisional_IHiLo, _Color1, _Width1, _Color2, _Width2, _ShowLabel, _ShowHighLowBar, _HighLowBarWidth, _HighLow_LabelSize)   TODO: Draw a zig-zag line.   Parameters:      _a_PHiLo : TODO: High-Low price array      _a_IHiLo : TODO: High-Low INDEX array      _a_FHiLo : TODO: High-Low flag array sequence 1:High 2:Low      _a_DHiLo : TODO: High-Low Price Differential Array      _Histories : TODO: Array size (High-Low length)      _Provisional_PHiLo : TODO: Provisional High-Low Price      _Provisional_IHiLo : TODO: Provisional High-Low INDEX      _Color1 : TODO: Normal High-Low color      _Width1 : TODO: Normal High-Low width      _Color2 : TODO: Provisional High-Low color      _Width2 : TODO: Provisional High-Low width      _ShowLabel : TODO: Label display flag True: Displayed False: Not displayed      _ShowHighLowBar : TODO: High-Low bar display flag True:Show False:Hide      _HighLowBarWidth : TODO: High-Low bar width      _HighLow_LabelSize : TODO: Label Size   Returns: TODO: No return value TrendLine(_a_PHiLo, _a_IHiLo, _Histories, _MultiLine, _StartWidth, _EndWidth, _IncreWidth, _StartTrans, _EndTrans, _IncreTrans, _ColorMode, _Color1_1, _Color1_2, _Color2_1, _Color2_2, _Top_High, _Top_Low, _Bottom_High, _Bottom_Low)   TODO: Draw a Trend Line   Parameters:      _a_PHiLo : TODO: High-Low price array      _a_IHiLo : TODO: High-Low INDEX array      _Histories : TODO: Array size (High-Low length)      _MultiLine : TODO: Draw a multiple Line.      _StartWidth : TODO: Line width start value      _EndWidth : TODO: Line width end value      _IncreWidth : TODO: Line width increment value      _StartTrans : TODO: Transparent rate start value      _EndTrans : TODO: Transparent rate finally      _IncreTrans : TODO: Transparent rate increase value      _ColorMode : TODO: 0:Nomal 1:Gradation      _Color1_1 : TODO: Gradation Color 1_1      _Color1_2 : TODO: Gradation Color 1_2      _Color2_1 : TODO: Gradation Color 2_1      _Color2_2 : TODO: Gradation Color 2_2      _Top_High : TODO: _Top_High Value for Gradation      _Top_Low : TODO: _Top_Low Value for Gradation      _Bottom_High : TODO: _Bottom_High Value for Gradation      _Bottom_Low : TODO: _Bottom_Low Value for Gradation   Returns: TODO: No return value Fibonacci(_a_Fibonacci, _a_PHiLo, _Provisional_PHiLo, _Index, _FrontMargin, _BackMargin)   TODO: Draw a Fibonacci line   Parameters:      _a_Fibonacci : TODO: Fibonacci Percentage Array      _a_PHiLo : TODO: High-Low price array      _Provisional_PHiLo : TODO: Provisional High-Low price (when _Index is 0)      _Index : TODO: Where to draw the Fibonacci line      _FrontMargin : TODO: Fibonacci line front-margin      _BackMargin : TODO: Fibonacci line back-margin   Returns: TODO: No return value Fibonacci(_a_Fibonacci, _a_PHiLo, _Provisional_PHiLo, _Index1, _FrontMargin1, _BackMargin1, _Transparent1, _Index2, _FrontMargin2, _BackMargin2, _Transparent2)   TODO: Draw a Fibonacci line   Parameters:      _a_Fibonacci : TODO: Fibonacci Percentage Array      _a_PHiLo : TODO: High-Low price array      _Provisional_PHiLo : TODO: Provisional High-Low price (when _Index is 0)      _Index1 : TODO: Where to draw the Fibonacci line 1      _FrontMargin1 : TODO: Fibonacci line front-margin 1      _BackMargin1 : TODO: Fibonacci line back-margin 1      _Transparent1 : TODO: Transparent rate 1      _Index2 : TODO: Where to draw the Fibonacci line 2      _FrontMargin2 : TODO: Fibonacci line front-margin 2      _BackMargin2 : TODO: Fibonacci line back-margin 2      _Transparent2 : TODO: Transparent rate 2   Returns: TODO: No return value High_Low_Judgment(_Length, _Extension, _Difference)   TODO: Judges High-Low   Parameters:      _Length : TODO: High-Low Confirmation Length      _Extension : TODO: Length of extension when the difference did not open      _Difference : TODO: Difference size   Returns: TODO: _HiLo=High-Low flag 0:Neither high nor low、1:High、2:Low、3:High-Low _PHi=high price、_PLo=low price、_IHi=High Price Index、_ILo=Low Price Index、 _Cnt=count、_ECnt=Extension count、 _DiffHi=Difference from Start(High)、_DiffLo=Difference from Start(Low)、 _StartHi=Start value(High)、_StartLo=Start value(Low) High_Low_Data_AddedAndUpdated(_HiLo, _Histories, _PHi, _PLo, _IHi, _ILo, _DiffHi, _DiffLo, _a_PHiLo, _a_IHiLo, _a_FHiLo, _a_DHiLo)   TODO: Adds and updates High-Low related arrays from given parameters   Parameters:      _HiLo : TODO: High-Low flag      _Histories : TODO: Array size (High-Low length)      _PHi : TODO: Price Hi      _PLo : TODO: Price Lo      _IHi : TODO: Index Hi      _ILo : TODO: Index Lo      _DiffHi : TODO: Difference in High      _DiffLo : TODO: Difference in Low      _a_PHiLo : TODO: High-Low price array      _a_IHiLo : TODO: High-Low INDEX array      _a_FHiLo : TODO: High-Low flag array 1:High 2:Low      _a_DHiLo : TODO: High-Low Price Differential Array   Returns: TODO: _PHiLo price array、_IHiLo indexed array、_FHiLo flag array、_DHiLo price-matching array、 Provisional_PHiLo Provisional price、Provisional_IHiLo 暫定インデックス High_Low(_a_PHiLo, _a_IHiLo, _a_FHiLo, _a_DHiLo, _a_Fibonacci, _Length, _Extension, _Difference, _Histories, _ShowZigZag, _ZigZagColor1, _ZigZagWidth1, _ZigZagColor2, _ZigZagWidth2, _ShowZigZagLabel, _ShowHighLowBar, _ShowTrendLine, _TrendMultiLine, _TrendStartWidth, _TrendEndWidth, _TrendIncreWidth, _TrendStartTrans, _TrendEndTrans, _TrendIncreTrans, _TrendColorMode, _TrendColor1_1, _TrendColor1_2, _TrendColor2_1, _TrendColor2_2, _ShowFibonacci1, _FibIndex1, _FibFrontMargin1, _FibBackMargin1, _FibTransparent1, _ShowFibonacci2, _FibIndex2, _FibFrontMargin2, _FibBackMargin2, _FibTransparent2, _ShowInfoTable1, _TablePosition1, _ShowInfoTable2, _TablePosition2)   TODO: Draw the contents of the High-Low array.   Parameters:      _a_PHiLo : TODO: High-Low price array      _a_IHiLo : TODO: High-Low INDEX array      _a_FHiLo : TODO: High-Low flag sequence 1:High 2:Low      _a_DHiLo : TODO: High-Low Price Differential Array      _a_Fibonacci : TODO: Fibonacci Gnar Matching      _Length : TODO: Length of confirmation      _Extension : TODO: Extension Length of extension when the difference did not open      _Difference : TODO: Difference size      _Histories : TODO: High-Low Length      _ShowZigZag : TODO: ZigZag Display      _ZigZagColor1 : TODO: Colors of ZigZag1      _ZigZagWidth1 : TODO: Width of ZigZag1      _ZigZagColor2 : TODO: Colors of ZigZag2      _ZigZagWidth2 : TODO: Width of ZigZag2      _ShowZigZagLabel : TODO: ZigZagLabel Display      _ShowHighLowBar : TODO: High-Low Bar Display      _ShowTrendLine : TODO: Trend Line Display      _TrendMultiLine : TODO: Trend Multi Line Display      _TrendStartWidth : TODO: Line width start value      _TrendEndWidth : TODO: Line width end value      _TrendIncreWidth : TODO: Line width increment value      _TrendStartTrans : TODO: Starting transmittance value      _TrendEndTrans : TODO: Transmittance End Value      _TrendIncreTrans : TODO: Increased transmittance value      _TrendColorMode : TODO: color mode      _TrendColor1_1 : TODO: Trend Color 1_1      _TrendColor1_2 : TODO: Trend Color 1_2      _TrendColor2_1 : TODO: Trend Color 2_1      _TrendColor2_2 : TODO: Trend Color 2_2      _ShowFibonacci1 : TODO: Fibonacci1 Display      _FibIndex1 : TODO: Fibonacci1 Index No.      _FibFrontMargin1 : TODO: Fibonacci1 Front margin      _FibBackMargin1 : TODO: Fibonacci1 Back Margin      _FibTransparent1 : TODO: Fibonacci1 Transmittance      _ShowFibonacci2 : TODO: Fibonacci2 Display      _FibIndex2 : TODO: Fibonacci2 Index No.      _FibFrontMargin2 : TODO: Fibonacci2 Front margin      _FibBackMargin2 : TODO: Fibonacci2 Back Margin      _FibTransparent2 : TODO: Fibonacci2 Transmittance      _ShowInfoTable1 : TODO: InfoTable1 Display      _TablePosition1 : TODO: InfoTable1 position      _ShowInfoTable2 : TODO: InfoTable2 Display      _TablePosition2 : TODO: InfoTable2 position   Returns: TODO: 無し
مكتبة Pine Script®
من ‎Tommy_Rich‎
1
TR_HighLowLibrary "TR_HighLow" TODO: add library description here ShowLabel(_Text, _X, _Y, _Style, _Size, _Yloc, _Color)   TODO: Function to display labels   Parameters:      _Text : TODO: text (series string) Label text.      _X : TODO: x (series int) Bar index.      _Y : TODO: y (series int/float) Price of the label position.      _Style : TODO: style (series string) Label style.      _Size : TODO: size (series string) Label size.      _Yloc : TODO: yloc (series string) Possible values are yloc.price, yloc.abovebar, yloc.belowbar.      _Color : TODO: color (series color) Color of the label border and arrow   Returns: TODO: No return values GetColor(_Index)   TODO: Function to take out 12 colors in order   Parameters:      _Index : TODO: color number.   Returns: TODO: color code Tbl_position(_Pos)   TODO: Table display position function   Parameters:      _Pos : TODO: position.   Returns: TODO: Table position DeleteLine()   TODO: Delete Line   Parameters:      : TODO: No parameter   Returns: TODO: No return value DeleteLabel()   TODO: Delete Label   Parameters:      : TODO: No parameter   Returns: TODO: No return value ZigZag(_a_PHiLo, _a_IHiLo, _a_FHiLo, _a_DHiLo, _Histories, _Provisional_PHiLo, _Provisional_IHiLo, _Color1, _Width1, _Color2, _Width2, _ShowLabel, _ShowHighLowBar, _HighLowBarWidth, _HighLow_LabelSize)   TODO: Draw a zig-zag line.   Parameters:      _a_PHiLo : TODO: High-Low price array      _a_IHiLo : TODO: High-Low INDEX array      _a_FHiLo : TODO: High-Low flag array sequence 1:High 2:Low      _a_DHiLo : TODO: High-Low Price Differential Array      _Histories : TODO: Array size (High-Low length)      _Provisional_PHiLo : TODO: Provisional High-Low Price      _Provisional_IHiLo : TODO: Provisional High-Low INDEX      _Color1 : TODO: Normal High-Low color      _Width1 : TODO: Normal High-Low width      _Color2 : TODO: Provisional High-Low color      _Width2 : TODO: Provisional High-Low width      _ShowLabel : TODO: Label display flag True: Displayed False: Not displayed      _ShowHighLowBar : TODO: High-Low bar display flag True:Show False:Hide      _HighLowBarWidth : TODO: High-Low bar width      _HighLow_LabelSize : TODO: Label Size   Returns: TODO: No return value TrendLine(_a_PHiLo, _a_IHiLo, _Histories, _MultiLine, _StartWidth, _EndWidth, _IncreWidth, _StartTrans, _EndTrans, _IncreTrans, _ColorMode, _Color1_1, _Color1_2, _Color2_1, _Color2_2, _Top_High, _Top_Low, _Bottom_High, _Bottom_Low)   TODO: Draw a Trend Line   Parameters:      _a_PHiLo : TODO: High-Low price array      _a_IHiLo : TODO: High-Low INDEX array      _Histories : TODO: Array size (High-Low length)      _MultiLine : TODO: Draw a multiple Line.      _StartWidth : TODO: Line width start value      _EndWidth : TODO: Line width end value      _IncreWidth : TODO: Line width increment value      _StartTrans : TODO: Transparent rate start value      _EndTrans : TODO: Transparent rate finally      _IncreTrans : TODO: Transparent rate increase value      _ColorMode : TODO: 0:Nomal 1:Gradation      _Color1_1 : TODO: Gradation Color 1_1      _Color1_2 : TODO: Gradation Color 1_2      _Color2_1 : TODO: Gradation Color 2_1      _Color2_2 : TODO: Gradation Color 2_2      _Top_High : TODO: _Top_High Value for Gradation      _Top_Low : TODO: _Top_Low Value for Gradation      _Bottom_High : TODO: _Bottom_High Value for Gradation      _Bottom_Low : TODO: _Bottom_Low Value for Gradation   Returns: TODO: No return value Fibonacci(_a_Fibonacci, _a_PHiLo, _Provisional_PHiLo, _Index, _FrontMargin, _BackMargin)   TODO: Draw a Fibonacci line   Parameters:      _a_Fibonacci : TODO: Fibonacci Percentage Array      _a_PHiLo : TODO: High-Low price array      _Provisional_PHiLo : TODO: Provisional High-Low price (when _Index is 0)      _Index : TODO: Where to draw the Fibonacci line      _FrontMargin : TODO: Fibonacci line front-margin      _BackMargin : TODO: Fibonacci line back-margin   Returns: TODO: No return value Fibonacci(_a_Fibonacci, _a_PHiLo, _Provisional_PHiLo, _Index1, _FrontMargin1, _BackMargin1, _Transparent1, _Index2, _FrontMargin2, _BackMargin2, _Transparent2)   TODO: Draw a Fibonacci line   Parameters:      _a_Fibonacci : TODO: Fibonacci Percentage Array      _a_PHiLo : TODO: High-Low price array      _Provisional_PHiLo : TODO: Provisional High-Low price (when _Index is 0)      _Index1 : TODO: Where to draw the Fibonacci line 1      _FrontMargin1 : TODO: Fibonacci line front-margin 1      _BackMargin1 : TODO: Fibonacci line back-margin 1      _Transparent1 : TODO: Transparent rate 1      _Index2 : TODO: Where to draw the Fibonacci line 2      _FrontMargin2 : TODO: Fibonacci line front-margin 2      _BackMargin2 : TODO: Fibonacci line back-margin 2      _Transparent2 : TODO: Transparent rate 2   Returns: TODO: No return value High_Low_Judgment(_Length, _Extension, _Difference)   TODO: Judges High-Low   Parameters:      _Length : TODO: High-Low Confirmation Length      _Extension : TODO: Length of extension when the difference did not open      _Difference : TODO: Difference size   Returns: TODO: _HiLo=High-Low flag 0:Neither high nor low、1:High、2:Low、3:High-Low _PHi=high price、_PLo=low price、_IHi=High Price Index、_ILo=Low Price Index、 _Cnt=count、_ECnt=Extension count、 _DiffHi=Difference from Start(High)、_DiffLo=Difference from Start(Low)、 _StartHi=Start value(High)、_StartLo=Start value(Low) High_Low_Data_AddedAndUpdated(_HiLo, _Histories, _PHi, _PLo, _IHi, _ILo, _DiffHi, _DiffLo, _a_PHiLo, _a_IHiLo, _a_FHiLo, _a_DHiLo)   TODO: Adds and updates High-Low related arrays from given parameters   Parameters:      _HiLo : TODO: High-Low flag      _Histories : TODO: Array size (High-Low length)      _PHi : TODO: Price Hi      _PLo : TODO: Price Lo      _IHi : TODO: Index Hi      _ILo : TODO: Index Lo      _DiffHi : TODO: Difference in High      _DiffLo : TODO: Difference in Low      _a_PHiLo : TODO: High-Low price array      _a_IHiLo : TODO: High-Low INDEX array      _a_FHiLo : TODO: High-Low flag array 1:High 2:Low      _a_DHiLo : TODO: High-Low Price Differential Array   Returns: TODO: _PHiLo price array、_IHiLo indexed array、_FHiLo flag array、_DHiLo price-matching array、 Provisional_PHiLo Provisional price、Provisional_IHiLo 暫定インデックス High_Low(_a_PHiLo, _a_IHiLo, _a_FHiLo, _a_DHiLo, _a_Fibonacci, _Length, _Extension, _Difference, _Histories, _ShowZigZag, _ZigZagColor1, _ZigZagWidth1, _ZigZagColor2, _ZigZagWidth2, _ShowZigZagLabel, _ShowHighLowBar, _ShowTrendLine, _TrendMultiLine, _TrendStartWidth, _TrendEndWidth, _TrendIncreWidth, _TrendStartTrans, _TrendEndTrans, _TrendIncreTrans, _TrendColorMode, _TrendColor1_1, _TrendColor1_2, _TrendColor2_1, _TrendColor2_2, _ShowFibonacci1, _FibIndex1, _FibFrontMargin1, _FibBackMargin1, _FibTransparent1, _ShowFibonacci2, _FibIndex2, _FibFrontMargin2, _FibBackMargin2, _FibTransparent2, _ShowInfoTable1, _TablePosition1, _ShowInfoTable2, _TablePosition2)   TODO: Draw the contents of the High-Low array.   Parameters:      _a_PHiLo : TODO: High-Low price array      _a_IHiLo : TODO: High-Low INDEX array      _a_FHiLo : TODO: High-Low flag sequence 1:High 2:Low      _a_DHiLo : TODO: High-Low Price Differential Array      _a_Fibonacci : TODO: Fibonacci Gnar Matching      _Length : TODO: Length of confirmation      _Extension : TODO: Extension Length of extension when the difference did not open      _Difference : TODO: Difference size      _Histories : TODO: High-Low Length      _ShowZigZag : TODO: ZigZag Display      _ZigZagColor1 : TODO: Colors of ZigZag1      _ZigZagWidth1 : TODO: Width of ZigZag1      _ZigZagColor2 : TODO: Colors of ZigZag2      _ZigZagWidth2 : TODO: Width of ZigZag2      _ShowZigZagLabel : TODO: ZigZagLabel Display      _ShowHighLowBar : TODO: High-Low Bar Display      _ShowTrendLine : TODO: Trend Line Display      _TrendMultiLine : TODO: Trend Multi Line Display      _TrendStartWidth : TODO: Line width start value      _TrendEndWidth : TODO: Line width end value      _TrendIncreWidth : TODO: Line width increment value      _TrendStartTrans : TODO: Starting transmittance value      _TrendEndTrans : TODO: Transmittance End Value      _TrendIncreTrans : TODO: Increased transmittance value      _TrendColorMode : TODO: color mode      _TrendColor1_1 : TODO: Trend Color 1_1      _TrendColor1_2 : TODO: Trend Color 1_2      _TrendColor2_1 : TODO: Trend Color 2_1      _TrendColor2_2 : TODO: Trend Color 2_2      _ShowFibonacci1 : TODO: Fibonacci1 Display      _FibIndex1 : TODO: Fibonacci1 Index No.      _FibFrontMargin1 : TODO: Fibonacci1 Front margin      _FibBackMargin1 : TODO: Fibonacci1 Back Margin      _FibTransparent1 : TODO: Fibonacci1 Transmittance      _ShowFibonacci2 : TODO: Fibonacci2 Display      _FibIndex2 : TODO: Fibonacci2 Index No.      _FibFrontMargin2 : TODO: Fibonacci2 Front margin      _FibBackMargin2 : TODO: Fibonacci2 Back Margin      _FibTransparent2 : TODO: Fibonacci2 Transmittance      _ShowInfoTable1 : TODO: InfoTable1 Display      _TablePosition1 : TODO: InfoTable1 position      _ShowInfoTable2 : TODO: InfoTable2 Display      _TablePosition2 : TODO: InfoTable2 position   Returns: TODO: 無し
مكتبة Pine Script®
من ‎Tommy_Rich‎
ICT Killzones & FVG// This source code is subject to the terms of the Mozilla Public License 2.0 at mozilla.org // © Mutharasan12 //@version=5 indicator("ICT Killzones & FVG", "ICT Killzones & FVG", overlay = true, max_labels_count = 500, max_lines_count = 500, max_boxes_count = 500) // ---------------------------------------- Constant Functions -------------------------------------------------- get_line_type(_style) => result = switch _style 'Solid' => line.style_solid 'Dotted' => line.style_dotted 'Dashed' => line.style_dashed result get_size(x) => result = switch x 'Auto' => size.auto 'Tiny' => size.tiny 'Small' => size.small 'Normal' => size.normal 'Large' => size.large 'Huge' => size.huge get_table_pos(pos) => result = switch pos "Bottom Center" => position.bottom_center "Bottom Left" => position.bottom_left "Bottom Right" => position.bottom_right "Middle Center" => position.middle_center "Middle Left" => position.middle_left "Middle Right" => position.middle_right "Top Center" => position.top_center "Top Left" => position.top_left "Top Right" => position.top_right get_font_style(s) => result = switch s 'Monospace' => font.family_monospace 'Default' => font.family_default // ---------------------------------------- Constant Functions -------------------------------------------------- // ---------------------------------------- Inputs -------------------------------------------------- gmt_tz = input.string('America/New_York', "Timezone", options = , tooltip = "Note GMT is not adjusted to reflect Daylight Saving Time changes", group = 'Time Zone') DWM_profile = input.bool(true,"Show All Profile",inline="Show",group = 'Profile') D_profile = input.bool(true,"Show Daily",inline = "Show",group = 'Profile') hide_lines_DO = input.timeframe("60","Daily:",inline = "Hide",group = 'Hide Above') W_profile = input.bool(true,"Weekly",inline="Show",group = 'Profile') hide_lines_WO = input.timeframe("240","Weekly:",inline="Hide",group = 'Hide Above') M_profile = input.bool(true,"Monthly",inline="Show",group = 'Profile') hide_lines_MO = input.timeframe("1D","Monthly:",inline="Hide",group = 'Hide Above') show_kz = input.bool(false, "Show Killzone Boxes", inline = "skz", group = 'Hide KillZone') var g_SETTINGS = "Settings" max_days = input.int(60, "Drawing Limit", 1, inline = 'dl', tooltip = "Only this many drawings will be kept on the chart, for each selected drawing type (killzone boxes, pivot lines, open lines, etc.)", group = g_SETTINGS) tf_limit = input.timeframe("30", "Timeframe Limit", inline = 'dl', tooltip = "Drawings will not appear on timeframes greater than or equal to this", group = g_SETTINGS) lbl_size = get_size(input.string('Tiny', "Label Size", inline = 'sc', options = , tooltip = "The size of all labels", group = g_SETTINGS)) font_style = get_font_style(input.string('Monospace', "Font Style", inline = 'sc', group = g_SETTINGS, options = )) txt_color = input.color(#000000, "Text Color", inline = 'sc', tooltip = "The color of all label and table text", group = g_SETTINGS) use_cutoff = input.bool(true, "Drawing Cutoff Time", inline = "CO", tooltip = "When enabled, all pivots and open price lines will stop extending at this time", group = g_SETTINGS) cutoff = input.session("1700-1701", "", inline = "CO", group = g_SETTINGS) var g_KZ = "Killzones" show_kz_text = input.bool(false, "Display Text", inline = "KZ", group = g_KZ) box_transparency = input.int(85, "Box Transparency", 0, 100, group = g_KZ) text_transparency = input.int(50, "Text Transparency", 0, 100, group = g_KZ) use_asia = input.bool(true, "", inline = "ASIA", group = g_KZ) as_txt = input.string("ASIA", "", inline = "ASIA", group = g_KZ) asia = input.session("2000-0000", "", inline = "ASIA", group = g_KZ) as_color = input.color(#9598a1, "", inline = "ASIA", group = g_KZ) use_london = input.bool(true, "", inline = "LONDON", group = g_KZ) lo_txt = input.string("OPEN", "", inline = "LONDON", group = g_KZ) london = input.session("0200-0500", "", inline = "LONDON", group = g_KZ) lo_color = input.color(#9598a1, "", inline = "LONDON", group = g_KZ) use_nyam = input.bool(true, "", inline = "NYAM", group = g_KZ) na_txt = input.string("NYAM", "", inline = "NYAM", group = g_KZ) nyam = input.session("0700-1000", "", inline = "NYAM", group = g_KZ) na_color = input.color(#9598a1, "", inline = "NYAM", group = g_KZ) use_nylu = input.bool(false, "", inline = "NYLU", group = g_KZ) nl_txt = input.string("Lunch", "", inline = "NYLU", group = g_KZ) nylu = input.session("1200-1300", "", inline = "NYLU", group = g_KZ) nl_color = input.color(#9598a1, "", inline = "NYLU", group = g_KZ) use_nypm = input.bool(false, "", inline = "NYPM", group = g_KZ) np_txt = input.string("NYPM", "", inline = "NYPM", group = g_KZ) nypm = input.session("1300-1600", "", inline = "NYPM", group = g_KZ) np_color = input.color(#9598a1, "", inline = "NYPM", group = g_KZ) use_loop = input.bool(true, "", inline = "LOOP", group = g_KZ) op_txt = input.string("CBDR", "", inline = "LOOP", group = g_KZ) loop = input.session("1400-2000", "", inline = "LOOP", group = g_KZ) op_color = input.color(#9598a1, "", inline = "LOOP", group = g_KZ) use_locl = input.bool(true, "", inline = "LOCL", group = g_KZ) cl_txt = input.string("CLOSE", "", inline = "LOCL", group = g_KZ) locl = input.session("1000-1200", "", inline = "LOCL", group = g_KZ) cl_color = input.color(#9598a1, "", inline = "LOCL", group = g_KZ) use_sb1 = input.bool(false, "", inline = "SB1", group = g_KZ) m1_txt = input.string("London SB", "", inline = "SB1", group = g_KZ) sb1 = input.session("0300-0400", "", inline = "SB1", group = g_KZ) m1_color = input.color(#9598a1, "", inline = "SB1", group = g_KZ) use_sb2 = input.bool(false, "", inline = "SB2", group = g_KZ) m2_txt = input.string("NewYork AM SB", "", inline = "SB2", group = g_KZ) sb2 = input.session("1000-1100", "", inline = "SB2", group = g_KZ) m2_color = input.color(#9598a1, "", inline = "SB2", group = g_KZ) use_sb3 = input.bool(false, "", inline = "SB3", group = g_KZ) m3_txt = input.string("NewYork PM SB", "", inline = "SB3", group = g_KZ) sb3 = input.session("1400-1500", "", inline = "SB3", group = g_KZ) m3_color = input.color(#9598a1, "", inline = "SB3", group = g_KZ) var g_LABELS = "Killzone Pivots" use_alerts = input.bool(false, "Alert Broken Pivots", inline = "PV", group = g_LABELS) show_pivots = input.bool(false, "Show Pivots", inline = "SV", group = g_LABELS) show_labels = input.bool(false, "Pivots Labels", inline = "SV", group = g_LABELS) show_midpoints = input.bool(false, "Pivots Midpoints",inline = "SV", group = g_LABELS) ext_pivots = input.string("Until Mitigated", "Extend Pivots...", options = , group = g_LABELS) ext_which = input.string("Most Recent", "...From Which Sessions", options = , group = g_LABELS) ash_str = input.string("AS.H", "Killzone 01 Labels", inline = "L_AS", group = g_LABELS) asl_str = input.string("AS.L", "", inline = "L_AS", group = g_LABELS) loh_str = input.string("LO.H", "Killzone 02 Labels", inline = "L_LO", group = g_LABELS) lol_str = input.string("LO.L", "", inline = "L_LO", group = g_LABELS) nah_str = input.string("NYAM.H", "Killzone 03 Labels", inline = "L_NA", group = g_LABELS) nal_str = input.string("NYAM.L", "", inline = "L_NA", group = g_LABELS) nlh_str = input.string("NYL.H", "Killzone 04 Labels", inline = "L_NL", group = g_LABELS) nll_str = input.string("NYL.L", "", inline = "L_NL", group = g_LABELS) nph_str = input.string("NYPM.H", "Killzone 05 Labels", inline = "L_NP", group = g_LABELS) npl_str = input.string("NYPM.L", "", inline = "L_NP", group = g_LABELS) oph_str = input.string("LOOP.H", "Killzone 06 Labels", inline = "L_OP", group = g_LABELS) opl_str = input.string("LOOP.L", "", inline = "L_OP", group = g_LABELS) clh_str = input.string("LOCL.H", "Killzone 07 Labels", inline = "L_CL", group = g_LABELS) cll_str = input.string("LOCL.L", "", inline = "L_CL", group = g_LABELS) m1h_str = input.string("SB1.H", "Killzone 08 Labels", inline = "L_M1", group = g_LABELS) m1l_str = input.string("SB1.L", "", inline = "L_M1", group = g_LABELS) m2h_str = input.string("SB2.H", "Killzone 09 Labels", inline = "L_M2", group = g_LABELS) m2l_str = input.string("SB2.L", "", inline = "L_M2", group = g_LABELS) m3h_str = input.string("SB3.H", "Killzone 10 Labels", inline = "L_M3", group = g_LABELS) m3l_str = input.string("SB3.L", "", inline = "L_M3", group = g_LABELS) kzp_style = get_line_type(input.string(defval = 'Solid', title = "Pivot Style", options = , inline = "KZP", group = g_LABELS)) kzp_width = input.int(1, "", inline = "KZP", group = g_LABELS) kzm_style = get_line_type(input.string(defval = 'Dotted', title = "Midpoint Style", options = , inline = "KZM", group = g_LABELS)) kzm_width = input.int(1, "", inline = "KZM", group = g_LABELS) var g_RNG = "Killzone Range" show_range = input.bool(false, "Show Killzone Range", tooltip = "Show the most recent ranges of each selected killzone, from high to low", group = g_RNG) show_range_avg = input.bool(true, "Show Average", tooltip = "Show the average range of each selected killzone", group = g_RNG) range_avg = input.int(5, "Average Length", 0, tooltip = "This many previous sessions will be used to calculate the average. If there isn't enough data on the current chart, it will use as many sessions as possible", group = g_RNG) range_pos = get_table_pos(input.string('Top Right', "Table Position", options = , group = g_RNG)) range_size = get_size(input.string('Normal', "Table Size", options = , group = g_RNG)) var g_DWM = "Day - Week - Month" dow_labels = input.bool(false, "Day of Week Labels", inline = "DOW", group = g_DWM) dow_yloc = input.string('Bottom', "", options = , inline = "DOW", group = g_DWM) dow_xloc = input.string('Midnight', "", options = , inline = "DOW", group = g_DWM) sep_unlimited = input.bool(true, "Unlimited", tooltip = "Unlimited will show as many of the selected lines as possible. Otherwise, the session drawing limit will be used", group = g_DWM) show_d_open = input.bool(true, "D Open", inline = "DO", group = g_DWM) dhl = input.bool(true, "High/Low", inline = "DO", tooltip = "", group = g_DWM) ds = input.bool(true, "Separators", inline = "DO", tooltip = "Mark where a new day begins", group = g_DWM) d_color = input.color(color.blue, "", inline = "DO", group = g_DWM) show_w_open = input.bool(true, "W Open", inline = "WO", group = g_DWM) whl = input.bool(true, "High/Low", inline = "WO", tooltip = "", group = g_DWM) ws = input.bool(true, "Separators", inline = "WO", tooltip = "Mark where a new week begins", group = g_DWM) w_color = input.color(#089981, "", inline = "WO", group = g_DWM) show_m_open = input.bool(true, "M Open", inline = "MO", group = g_DWM) mhl = input.bool(true, "High/Low", inline = "MO", tooltip = "", group = g_DWM) ms = input.bool(true, "Separators", inline = "MO", tooltip = "Mark where a new month begins", group = g_DWM) m_color = input.color(color.red, "", inline = "MO", group = g_DWM) htf_style = get_line_type(input.string(defval = 'Dotted', title = "Style", options = , inline = "D0", group = g_DWM)) htf_width = input.int(1, "", inline = "D0", group = g_DWM) var g_OPEN = "Opening Prices" open_unlimited = input.bool(true, "Unlimited", tooltip = "Unlimited will show as many of the selected lines as possible. Otherwise, the session drawing limit will be used", group = g_OPEN) hide_hline = input.bool(true,"Show Opening Price",group = g_OPEN) hide_lines_h = input.timeframe("60","Hide Above Time Frame",group = g_OPEN) use_h1 = input.bool(true, "", inline = "H1", group = g_OPEN) h1_text = input.string("00:00", "", inline = "H1", group = g_OPEN) h1 = input.session("0000-0001", "", inline = "H1", group = g_OPEN) h1_color = input.color(#000000, "", inline = "H1", group = g_OPEN) use_h2 = input.bool(true, "", inline = "H2", group = g_OPEN) h2_text = input.string("08:30", "", inline = "H2", group = g_OPEN) h2 = input.session("0830-0831", "", inline = "H2", group = g_OPEN) h2_color = input.color(#000000, "", inline = "H2", group = g_OPEN) use_h3 = input.bool(false, "", inline = "H3", group = g_OPEN) h3_text = input.string("10:00", "", inline = "H3", group = g_OPEN) h3 = input.session("1000-1001", "", inline = "H3", group = g_OPEN) h3_color = input.color(#000000, "", inline = "H3", group = g_OPEN) use_h4 = input.bool(false, "", inline = "H4", group = g_OPEN) h4_text = input.string("14:00", "", inline = "H4", group = g_OPEN) h4 = input.session("1400-1401", "", inline = "H4", group = g_OPEN) h4_color = input.color(#000000, "", inline = "H4", group = g_OPEN) hz_style = get_line_type(input.string(defval = 'Dotted', title = "Style", options = , inline = "H0", group = g_OPEN)) hz_width = input.int(1, "", inline = "H0", group = g_OPEN) var g_VERTICAL = "Timestamps" hide_vline = input.bool(true,"Show Timestamp",group = g_VERTICAL) hide_lines_v = input.timeframe("60","Hide Above Time Frame",group = g_VERTICAL) use_v1 = input.bool(true, "", inline = "V1", group = g_VERTICAL) v1 = input.session("0000-0001", "", inline = "V1", group = g_VERTICAL) v1_color = input.color(#000000, "", inline = "V1", group = g_VERTICAL) use_v2 = input.bool(false, "", inline = "V2", group = g_VERTICAL) v2 = input.session("0800-0801", "", inline = "V2", group = g_VERTICAL) v2_color = input.color(#000000, "", inline = "V2", group = g_VERTICAL) use_v3 = input.bool(false, "", inline = "V3", group = g_VERTICAL) v3 = input.session("1000-1001", "", inline = "V3", group = g_VERTICAL) v3_color = input.color(#000000, "", inline = "V3", group = g_VERTICAL) use_v4 = input.bool(false, "", inline = "V4", group = g_VERTICAL) v4 = input.session("1200-1201", "", inline = "V4", group = g_VERTICAL) v4_color = input.color(#000000, "", inline = "V4", group = g_VERTICAL) vl_style = get_line_type(input.string(defval = 'Dotted', title = "Style", options = , inline = "V0", group = g_VERTICAL)) vl_width = input.int(1, "", inline = "V0", group = g_VERTICAL) // ---------------------------------------- Inputs -------------------------------------------------- // ---------------------------------------- Variables & Constants -------------------------------------------------- type kz string _title box _box line _hi_line line _md_line line _lo_line label _hi_label label _lo_label bool _hi_valid bool _md_valid bool _lo_valid float _range_store float _range_current type hz line LN label LB bool CO type dwm_hl line hi_line line lo_line label hi_label label lo_label type dwm_info string tf float o = na float h = na float l = na float ph = na float pl = na var as_kz = kz.new(as_txt, array.new_box(), array.new_line(), array.new_line(), array.new_line(), array.new_label(), array.new_label(), array.new_bool(), array.new_bool(), array.new_bool(), array.new_float()) var lo_kz = kz.new(lo_txt, array.new_box(), array.new_line(), array.new_line(), array.new_line(), array.new_label(), array.new_label(), array.new_bool(), array.new_bool(), array.new_bool(), array.new_float()) var na_kz = kz.new(na_txt, array.new_box(), array.new_line(), array.new_line(), array.new_line(), array.new_label(), array.new_label(), array.new_bool(), array.new_bool(), array.new_bool(), array.new_float()) var nl_kz = kz.new(nl_txt, array.new_box(), array.new_line(), array.new_line(), array.new_line(), array.new_label(), array.new_label(), array.new_bool(), array.new_bool(), array.new_bool(), array.new_float()) var np_kz = kz.new(np_txt, array.new_box(), array.new_line(), array.new_line(), array.new_line(), array.new_label(), array.new_label(), array.new_bool(), array.new_bool(), array.new_bool(), array.new_float()) var op_kz = kz.new(op_txt, array.new_box(), array.new_line(), array.new_line(), array.new_line(), array.new_label(), array.new_label(), array.new_bool(), array.new_bool(), array.new_bool(), array.new_float()) var cl_kz = kz.new(cl_txt, array.new_box(), array.new_line(), array.new_line(), array.new_line(), array.new_label(), array.new_label(), array.new_bool(), array.new_bool(), array.new_bool(), array.new_float()) var m1_kz = kz.new(m1_txt, array.new_box(), array.new_line(), array.new_line(), array.new_line(), array.new_label(), array.new_label(), array.new_bool(), array.new_bool(), array.new_bool(), array.new_float()) var m2_kz = kz.new(m2_txt, array.new_box(), array.new_line(), array.new_line(), array.new_line(), array.new_label(), array.new_label(), array.new_bool(), array.new_bool(), array.new_bool(), array.new_float()) var m3_kz = kz.new(m3_txt, array.new_box(), array.new_line(), array.new_line(), array.new_line(), array.new_label(), array.new_label(), array.new_bool(), array.new_bool(), array.new_bool(), array.new_float()) var hz_1 = hz.new(array.new_line(), array.new_label(), array.new_bool()) var hz_2 = hz.new(array.new_line(), array.new_label(), array.new_bool()) var hz_3 = hz.new(array.new_line(), array.new_label(), array.new_bool()) var hz_4 = hz.new(array.new_line(), array.new_label(), array.new_bool()) var d_hl = dwm_hl.new(array.new_line(), array.new_line(), array.new_label(), array.new_label()) var w_hl = dwm_hl.new(array.new_line(), array.new_line(), array.new_label(), array.new_label()) var m_hl = dwm_hl.new(array.new_line(), array.new_line(), array.new_label(), array.new_label()) var d_info = dwm_info.new("D") var w_info = dwm_info.new("W") var m_info = dwm_info.new("M") t_as = not na(time("", asia, gmt_tz)) t_lo = not na(time("", london, gmt_tz)) t_na = not na(time("", nyam, gmt_tz)) t_nl = not na(time("", nylu, gmt_tz)) t_np = not na(time("", nypm, gmt_tz)) t_op = not na(time("", loop, gmt_tz)) t_cl = not na(time("", locl, gmt_tz)) t_m1 = not na(time("", sb1, gmt_tz)) t_m2 = not na(time("", sb2, gmt_tz)) t_m3 = not na(time("", sb3, gmt_tz)) t_co = not na(time("", cutoff, gmt_tz)) t_h1 = not na(time("", h1, gmt_tz)) t_h2 = not na(time("", h2, gmt_tz)) t_h3 = not na(time("", h3, gmt_tz)) t_h4 = not na(time("", h4, gmt_tz)) t_v1 = not na(time("", v1, gmt_tz)) t_v2 = not na(time("", v2, gmt_tz)) t_v3 = not na(time("", v3, gmt_tz)) t_v4 = not na(time("", v4, gmt_tz)) var d_sep_line = array.new_line() var w_sep_line = array.new_line() var m_sep_line = array.new_line() var d_line = array.new_line() var w_line = array.new_line() var m_line = array.new_line() var d_label = array.new_label() var w_label = array.new_label() var m_label = array.new_label() var v1_line = array.new_line() var v2_line = array.new_line() var v3_line = array.new_line() var v4_line = array.new_line() var transparent = #ffffff00 var ext_current = ext_which == 'Most Recent' var ext_past = ext_pivots == 'Past Mitigation' update_dwm_info(dwm_info n) => if timeframe.change(n.tf) n.ph := n.h n.pl := n.l n.o := open n.h := high n.l := low else n.h := math.max(high, n.h) n.l := math.min(low, n.l) if dhl or show_d_open update_dwm_info(d_info) if whl or show_w_open update_dwm_info(w_info) if mhl or show_m_open update_dwm_info(m_info) // ---------------------------------------- Variables & Constants -------------------------------------------------- // ---------------------------------------- Functions -------------------------------------------------- get_box_color(color c) => result = color.new(c, box_transparency) get_text_color(color c) => result = color.new(c, text_transparency) // ---------------------------------------- Functions -------------------------------------------------- // ---------------------------------------- Core Logic -------------------------------------------------- dwm_sep(string tf, bool use, line arr, color col) => if use if timeframe.change(tf) arr.unshift(line.new(bar_index, high*1.0001, bar_index, low, style = htf_style, width = htf_width, extend = extend.both, color = col)) if not sep_unlimited and arr.size() > max_days arr.pop().delete() dwm_open(string tf, bool use, line lns, label lbls, dwm_info n, color col) => if use if timeframe.change(tf) lns.unshift(line.new(time, n.o, time, n.o, xloc = xloc.bar_time, style = htf_style, width = htf_width, color = col)) lbls.unshift(label.new(time, n.o, tf + " OPEN", xloc = xloc.bar_time, style = label.style_label_left, color = transparent, textcolor = txt_color, size = lbl_size, text_font_family = font_style)) if not sep_unlimited and lns.size() > max_days lns.pop().delete() lbls.pop().delete() else if lns.size() > 0 lns.get(0).set_x2(time) lbls.get(0).set_x(time) dwm_hl(string tf, bool use, dwm_hl hl, dwm_info n, color col) => if use if timeframe.change(tf) hl.hi_line.unshift(line.new(time, n.ph, time, n.ph, xloc = xloc.bar_time, style = htf_style, width = htf_width, color = col)) hl.lo_line.unshift(line.new(time, n.pl, time, n.pl, xloc = xloc.bar_time, style = htf_style, width = htf_width, color = col)) hl.hi_label.unshift(label.new(time, n.ph, "P"+tf+"H", xloc = xloc.bar_time, style = label.style_label_left, color = transparent, textcolor = txt_color, size = lbl_size, text_font_family = font_style)) hl.lo_label.unshift(label.new(time, n.pl, "P"+tf+"L", xloc = xloc.bar_time, style = label.style_label_left, color = transparent, textcolor = txt_color, size = lbl_size, text_font_family = font_style)) if not sep_unlimited and hl.hi_line.size() > max_days hl.hi_line.pop().delete() hl.lo_line.pop().delete() hl.hi_label.pop().delete() hl.lo_label.pop().delete() else if hl.hi_line.size() > 0 hl.hi_line.get(0).set_x2(time) hl.lo_line.get(0).set_x2(time) hl.hi_label.get(0).set_x(time) hl.lo_label.get(0).set_x(time) dwm() => //if timeframe.in_seconds() <= hide_lines_sessions *60 if DWM_profile if D_profile and timeframe.in_seconds("") <= timeframe.in_seconds(hide_lines_DO) // Draw Daily separators, open lines, and high/low lines dwm_sep("D", ds, d_sep_line, d_color) dwm_open("D", show_d_open, d_line, d_label, d_info, d_color) dwm_hl("D", dhl, d_hl, d_info, d_color) // Draw Weekly and Monthly only if Daily profile allows it if W_profile and timeframe.in_seconds("") <= timeframe.in_seconds(hide_lines_WO) dwm_sep("W", ws, w_sep_line, w_color) dwm_open("W", show_w_open, w_line, w_label, w_info, w_color) dwm_hl("W", whl, w_hl, w_info, w_color) if M_profile and timeframe.in_seconds("") <= timeframe.in_seconds(hide_lines_MO) dwm_sep("M", ms, m_sep_line, m_color) dwm_open("M", show_m_open, m_line, m_label, m_info, m_color) dwm_hl("M", mhl, m_hl, m_info, m_color) else if W_profile and timeframe.in_seconds("") <= timeframe.in_seconds(hide_lines_WO) // Draw Weekly separators, open lines, and high/low lines dwm_sep("W", ws, w_sep_line, w_color) dwm_open("W", show_w_open, w_line, w_label, w_info, w_color) dwm_hl("W", whl, w_hl, w_info, w_color) // Draw Monthly only if Weekly profile allows it if M_profile and timeframe.in_seconds("") <= timeframe.in_seconds(hide_lines_MO) dwm_sep("M", ms, m_sep_line, m_color) dwm_open("M", show_m_open, m_line, m_label, m_info, m_color) dwm_hl("M", mhl, m_hl, m_info, m_color) else if M_profile and timeframe.in_seconds("") <= timeframe.in_seconds(hide_lines_MO) // Draw Monthly separators, open lines, and high/low lines dwm_sep("M", ms, m_sep_line, m_color) dwm_open("M", show_m_open, m_line, m_label, m_info, m_color) dwm_hl("M", mhl, m_hl, m_info, m_color) vline(bool use, bool t, line arr, color col) => if use if t and not t arr.unshift(line.new(bar_index, high*1.0001, bar_index, low, style = vl_style, width = vl_width, extend = extend.both, color = col)) vlines() => if hide_vline if timeframe.in_seconds("") <= timeframe.in_seconds(hide_lines_v) vline(use_v1, t_v1, v1_line, v1_color) vline(use_v2, t_v2, v2_line, v2_color) vline(use_v3, t_v3, v3_line, v3_color) vline(use_v4, t_v4, v4_line, v4_color) hz_line(bool use, bool t, hz hz, string txt, color col) => if use if t and not t hz.LN.unshift(line.new(bar_index, open, bar_index, open, style = hz_style, width = hz_width, color = col)) hz.LB.unshift(label.new(bar_index, open, txt, style = label.style_label_left, color = transparent, textcolor = txt_color, size = lbl_size, text_font_family = font_style)) array.unshift(hz.CO, false) if not open_unlimited and hz.LN.size() > max_days hz.LN.pop().delete() hz.LB.pop().delete() hz.CO.pop() if not t and hz.CO.size() > 0 if not hz.CO.get(0) hz.LN.get(0).set_x2(bar_index) hz.LB.get(0).set_x(bar_index) if (use_cutoff ? t_co : false) hz.CO.set(0, true) hz_lines() => if hide_hline if timeframe.in_seconds("") <= timeframe.in_seconds(hide_lines_h) hz_line(use_h1, t_h1, hz_1, h1_text, h1_color) hz_line(use_h2, t_h2, hz_2, h2_text, h2_color) hz_line(use_h3, t_h3, hz_3, h3_text, h3_color) hz_line(use_h4, t_h4, hz_4, h4_text, h4_color) del_kz(kz k) => if k._box.size() > max_days k._box.pop().delete() if k._hi_line.size() > max_days k._hi_line.pop().delete() k._lo_line.pop().delete() k._hi_valid.pop() k._lo_valid.pop() if show_midpoints k._md_line.pop().delete() k._md_valid.pop() if k._hi_label.size() > max_days k._hi_label.pop().delete() k._lo_label.pop().delete() adjust_in_kz(kz kz, bool t) => if t kz._box.get(0).set_right(time) kz._box.get(0).set_top(math.max(kz._box.get(0).get_top(), high)) kz._box.get(0).set_bottom(math.min(kz._box.get(0).get_bottom(), low)) kz._range_current := kz._box.get(0).get_top() - kz._box.get(0).get_bottom() if show_pivots and kz._hi_line.size() > 0 if high > kz._hi_line.get(0).get_y1() kz._hi_line.get(0).set_xy1(time, high) kz._hi_line.get(0).set_xy2(time, high) if low < kz._lo_line.get(0).get_y1() kz._lo_line.get(0).set_xy1(time, low) kz._lo_line.get(0).set_xy2(time, low) if show_midpoints kz._md_line.get(0).set_xy1(time, math.avg(kz._hi_line.get(0).get_y2(), kz._lo_line.get(0).get_y2())) kz._md_line.get(0).set_xy2(time, math.avg(kz._hi_line.get(0).get_y2(), kz._lo_line.get(0).get_y2())) if show_labels and kz._hi_label.size() > 0 if high > kz._hi_label.get(0).get_y() kz._hi_label.get(0).set_xy(time, high) if low < kz._lo_label.get(0).get_y() kz._lo_label.get(0).set_xy(time, low) adjust_out_kz(kz kz, bool t) => if not t and kz._box.size() > 0 if t array.unshift(kz._range_store, kz._range_current) if kz._range_store.size() > range_avg kz._range_store.pop() if kz._box.size() > 0 and show_pivots for i = 0 to kz._box.size() - 1 if not ext_current or (ext_current and i == 0) if ext_past ? true : (kz._hi_valid.get(i) == true) kz._hi_line.get(i).set_x2(time) if high > kz._hi_line.get(i).get_y1() and kz._hi_valid.get(i) == true if use_alerts and i == 0 alert("Broke "+kz._title+" High", alert.freq_once_per_bar) kz._hi_valid.set(i, false) else if (use_cutoff ? t_co : false) kz._hi_valid.set(i, false) if ext_past ? true : (kz._lo_valid.get(i) == true) kz._lo_line.get(i).set_x2(time) if low < kz._lo_line.get(i).get_y1() and kz._lo_valid.get(i) == true if use_alerts and i == 0 alert("Broke "+kz._title+" Low", alert.freq_once_per_bar) kz._lo_valid.set(i, false) else if (use_cutoff ? t_co : false) kz._lo_valid.set(i, false) if show_midpoints kz._md_line.get(i).set_x2(time) else break manage_kz(kz kz, bool use, bool t, color c, string box_txt, string hi_txt, string lo_txt) => if timeframe.in_seconds("") <= timeframe.in_seconds(tf_limit) and use if t and not t _c = get_box_color(c) _t = get_text_color(c) kz._box.unshift(box.new(time, high, time, low, xloc = xloc.bar_time, border_color = show_kz ? _c : na, bgcolor = show_kz ? _c : na, text = (show_kz and show_kz_text) ? box_txt : na, text_color = _t)) if show_pivots kz._hi_line.unshift(line.new(time, high, time, high, xloc = xloc.bar_time, style = kzp_style, color = c, width = kzp_width)) kz._lo_line.unshift(line.new(time, low, time, low, xloc = xloc.bar_time, style = kzp_style, color = c, width = kzp_width)) if show_midpoints kz._md_line.unshift(line.new(time, math.avg(high, low), time, math.avg(high, low), xloc = xloc.bar_time, style = kzm_style, color = c, width = kzm_width)) array.unshift(kz._md_valid, true) array.unshift(kz._hi_valid, true) array.unshift(kz._lo_valid, true) if show_labels kz._hi_label.unshift(label.new(time, high, hi_txt, xloc = xloc.bar_time, color = transparent, textcolor = txt_color, style = label.style_label_down, size = lbl_size)) kz._lo_label.unshift(label.new(time, low, lo_txt, xloc = xloc.bar_time, color = transparent, textcolor = txt_color, style = label.style_label_up, size = lbl_size)) del_kz(kz) adjust_in_kz(kz, t) adjust_out_kz(kz, t) manage_kz(as_kz, use_asia, t_as, as_color, as_txt, ash_str, asl_str) manage_kz(lo_kz, use_london, t_lo, lo_color, lo_txt, loh_str, lol_str) manage_kz(na_kz, use_nyam, t_na, na_color, na_txt, nah_str, nal_str) manage_kz(nl_kz, use_nylu, t_nl, nl_color, nl_txt, nlh_str, nll_str) manage_kz(np_kz, use_nypm, t_np, np_color, np_txt, nph_str, npl_str) manage_kz(op_kz, use_loop, t_op, op_color, op_txt, oph_str, opl_str) manage_kz(cl_kz, use_locl, t_cl, cl_color, cl_txt, clh_str, cll_str) manage_kz(m1_kz, use_sb1, t_m1, m1_color, m1_txt, m1h_str, m1l_str) manage_kz(m2_kz, use_sb2, t_m2, m2_color, m2_txt, m2h_str, m2l_str) manage_kz(m3_kz, use_sb3, t_m3, m3_color, m3_txt, m3h_str, m3l_str) dwm() vlines() hz_lines() new_dow_time = dow_xloc == 'Midday' ? time - timeframe.in_seconds("D") / 2 * 1000 : time new_day = dayofweek(new_dow_time, gmt_tz) != dayofweek(new_dow_time, gmt_tz) var dow_top = dow_yloc == 'Top' var sunday = "SUNDAY" var monday = "MONDAY" var tuesday = "TUESDAY" var wednesday = "WEDNESDAY" var thursday = "THURSDAY" var friday = "FRIDAY" plotchar(dow_labels and timeframe.isintraday and dayofweek(new_dow_time, gmt_tz) == 1 and new_day, location = dow_top ? location.top : location.bottom, char = "", textcolor = txt_color, text = sunday) plotchar(dow_labels and timeframe.isintraday and dayofweek(new_dow_time, gmt_tz) == 2 and new_day, location = dow_top ? location.top : location.bottom, char = "", textcolor = txt_color, text = monday) plotchar(dow_labels and timeframe.isintraday and dayofweek(new_dow_time, gmt_tz) == 3 and new_day, location = dow_top ? location.top : location.bottom, char = "", textcolor = txt_color, text = tuesday) plotchar(dow_labels and timeframe.isintraday and dayofweek(new_dow_time, gmt_tz) == 4 and new_day, location = dow_top ? location.top : location.bottom, char = "", textcolor = txt_color, text = wednesday) plotchar(dow_labels and timeframe.isintraday and dayofweek(new_dow_time, gmt_tz) == 5 and new_day, location = dow_top ? location.top : location.bottom, char = "", textcolor = txt_color, text = thursday) plotchar(dow_labels and timeframe.isintraday and dayofweek(new_dow_time, gmt_tz) == 6 and new_day, location = dow_top ? location.top : location.bottom, char = "", textcolor = txt_color, text = friday) get_min_days_stored() => store = array.new_int() if as_kz._range_store.size() > 0 store.push(as_kz._range_store.size()) if lo_kz._range_store.size() > 0 store.push(lo_kz._range_store.size()) if na_kz._range_store.size() > 0 store.push(na_kz._range_store.size()) if nl_kz._range_store.size() > 0 store.push(nl_kz._range_store.size()) if np_kz._range_store.size() > 0 store.push(np_kz._range_store.size()) if op_kz._range_store.size() > 0 store.push(op_kz._range_store.size()) if cl_kz._range_store.size() > 0 store.push(cl_kz._range_store.size()) if m1_kz._range_store.size() > 0 store.push(m1_kz._range_store.size()) if m2_kz._range_store.size() > 0 store.push(m2_kz._range_store.size()) if m3_kz._range_store.size() > 0 store.push(m3_kz._range_store.size()) result = store.min() set_table(table tbl, kz kz, int row, string txt, bool use, bool t, color col) => if use table.cell(tbl, 0, row, txt, text_size = range_size, bgcolor = get_box_color(col), text_color = txt_color) table.cell(tbl, 1, row, str.tostring(kz._range_current), text_size = range_size, bgcolor = t ? get_box_color(col) : na, text_color = txt_color) if show_range_avg table.cell(tbl, 2, row, str.tostring(kz._range_store.avg()), text_size = range_size, text_color = txt_color) if show_range and barstate.islast var tbl = table.new(range_pos, 10, 10, chart.bg_color, chart.fg_color, 2, chart.fg_color, 1) table.cell(tbl, 0, 0, "Killzone", text_size = range_size, text_color = txt_color) table.cell(tbl, 1, 0, "Range", text_size = range_size, text_color = txt_color) if show_range_avg table.cell(tbl, 2, 0, "Avg ("+str.tostring(get_min_days_stored())+")", text_size = range_size, text_color = txt_color) set_table(tbl, as_kz, 1, as_txt, use_asia, t_as, as_color) set_table(tbl, lo_kz, 2, lo_txt, use_london, t_lo, lo_color) set_table(tbl, na_kz, 3, na_txt, use_nyam, t_na, na_color) set_table(tbl, nl_kz, 4, nl_txt, use_nylu, t_nl, nl_color) set_table(tbl, np_kz, 5, np_txt, use_nypm, t_np, np_color) set_table(tbl, op_kz, 6, op_txt, use_loop, t_op, op_color) set_table(tbl, cl_kz, 7, cl_txt, use_locl, t_cl, cl_color) set_table(tbl, m1_kz, 8, m1_txt, use_sb1, t_m1, m1_color) set_table(tbl, m2_kz, 9, m2_txt, use_sb2, t_m2, m2_color) set_table(tbl, m3_kz, 10, m3_txt, use_sb3, t_m3, m3_color) // ---------------------------------------- Core Logic -------------------------------------------------- //-----------------------------------------------------------------------------------------------------------------------------------------------// // This source code is subject to the terms of the Mozilla Public License 2.0 at mozilla.org // ©Mutharasan2 // Prev Published: 608 // Curr Published: 907 //@version=5 //2nd indicator("ICT HTF Candles (fadi)", overlay=true, max_boxes_count = 500, max_lines_count = 500, max_bars_back = 5000) type Candle float o float c float h float l int o_idx int c_idx int h_idx int l_idx box body line wick_up line wick_down type Trace line o line c line h line l label o_l label c_l label h_l label l_l type Imbalance box b int idx type CandleSettings bool show string htf int max_display type Settings int max_sets color bull_body color bull_border color bull_wick color bear_body color bear_border color bear_wick int offset int buffer int htf_buffer int width bool trace_show color trace_o_color string trace_o_style int trace_o_size color trace_c_color string trace_c_style int trace_c_size color trace_h_color string trace_h_style int trace_h_size color trace_l_color string trace_l_style int trace_l_size string trace_anchor bool label_show color label_color string label_size bool fvg_show color fvg_color bool vi_show color vi_color bool htf_label_show color htf_label_color string htf_label_size bool htf_timer_show color htf_timer_color string htf_timer_size string level string liquidity_open_style string liquidity_claimed_style color liquidity_open_color color liquidity_claimed_color int liquidity_open_size int liquidity_claimed_size int max_lines int extend type CandleSet Candle candles Imbalance imbalances CandleSettings settings label tfName label tfTimer type Helper string name = "Helper" Settings settings = Settings.new() var CandleSettings SettingsHTF1 = CandleSettings.new() var CandleSettings SettingsHTF2 = CandleSettings.new() var CandleSettings SettingsHTF3 = CandleSettings.new() var CandleSettings SettingsHTF4 = CandleSettings.new() var CandleSettings SettingsHTF5 = CandleSettings.new() var CandleSettings SettingsHTF6 = CandleSettings.new() var Candle candles_1 = array.new(0) var Candle candles_2 = array.new(0) var Candle candles_3 = array.new(0) var Candle candles_4 = array.new(0) var Candle candles_5 = array.new(0) var Candle candles_6 = array.new(0) var Imbalance imbalances_1 = array.new() var Imbalance imbalances_2 = array.new() var Imbalance imbalances_3 = array.new() var Imbalance imbalances_4 = array.new() var Imbalance imbalances_5 = array.new() var Imbalance imbalances_6 = array.new() var CandleSet htf1 = CandleSet.new() htf1.settings := SettingsHTF1 htf1.candles := candles_1 htf1.imbalances := imbalances_1 var CandleSet htf2 = CandleSet.new() htf2.settings := SettingsHTF2 htf2.candles := candles_2 htf2.imbalances := imbalances_2 var CandleSet htf3 = CandleSet.new() htf3.settings := SettingsHTF3 htf3.candles := candles_3 htf3.imbalances := imbalances_3 var CandleSet htf4 = CandleSet.new() htf4.settings := SettingsHTF4 htf4.candles := candles_4 htf4.imbalances := imbalances_4 var CandleSet htf5 = CandleSet.new() htf5.settings := SettingsHTF5 htf5.candles := candles_5 htf5.imbalances := imbalances_5 var CandleSet htf6 = CandleSet.new() htf6.settings := SettingsHTF6 htf6.candles := candles_6 htf6.imbalances := imbalances_6 //+------------------------------------------------------------------------------------------------------------+// //+--- Settings ---+// //+------------------------------------------------------------------------------------------------------------+// htf1.settings.show := input.bool(false, "HTF 1      ", inline="htf1") htf_1 = input.timeframe("60", "", inline="htf1") htf1.settings.htf := htf_1 htf1.settings.max_display := input.int(1, "", inline="htf1") htf2.settings.show := input.bool(false, "HTF 2      ", inline="htf2") htf_2 = input.timeframe("240", "", inline="htf2") htf2.settings.htf := htf_2 htf2.settings.max_display := input.int(1, "", inline="htf2") htf3.settings.show := input.bool(true, "HTF 3      ", inline="htf3") htf_3 = input.timeframe("1D", "", inline="htf3") htf3.settings.htf := htf_3 htf3.settings.max_display := input.int(1, "", inline="htf3") htf4.settings.show := input.bool(true, "HTF 4      ", inline="htf4") htf_4 = input.timeframe("1W", "", inline="htf4") htf4.settings.htf := htf_4 htf4.settings.max_display := input.int(1, "", inline="htf4") htf5.settings.show := input.bool(true, "HTF 5      ", inline="htf5") htf_5 = input.timeframe("1M", "", inline="htf5") htf5.settings.htf := htf_5 htf5.settings.max_display := input.int(1, "", inline="htf5") htf6.settings.show := input.bool(false, "HTF 6      ", inline="htf6") htf_6 = input.timeframe("3M", "", inline="htf6") htf6.settings.htf := htf_6 htf6.settings.max_display := input.int(1, "", inline="htf6") settings.max_sets := input.int(6, "Limit to next HTFs only", minval=1, maxval=6) settings.bull_body := input.color(color.rgb(76, 175, 80), "Body  ", inline="body") settings.bear_body := input.color(color.rgb(0, 0, 0), "", inline="body") settings.bull_border := input.color(color.rgb(93, 96, 107), "Borders", inline="borders") settings.bear_border := input.color(color.rgb(0, 0, 0), "", inline="borders") settings.bull_wick := input.color(color.rgb(93, 96, 107), "Wick  ", inline="wick") settings.bear_wick := input.color(color.rgb(93, 96, 107), "", inline="wick") settings.offset := input.int(10, "padding from current candles", minval = 1) settings.buffer := input.int(1, "space between candles", minval = 1, maxval = 4) settings.htf_buffer := input.int(10, "space between Higher Timeframes", minval = 1, maxval = 10) settings.width := input.int(4, "Candle Width", minval = 1, maxval = 10)*2 settings.htf_label_show := input.bool(false, "HTF Label           ", inline="HTFlabel") settings.htf_label_color := input.color(color.rgb(0, 0, 0), "", inline='HTFlabel') settings.htf_label_size := input.string(size.tiny, "", , inline="HTFlabel") settings.htf_timer_show := input.bool(false, "Remaining time      ", inline="timer") settings.htf_timer_color := input.color(color.rgb(0, 0, 0), "", inline='timer') settings.htf_timer_size := input.string(size.tiny, "", , inline="timer") settings.fvg_show := input.bool(true, "Fair Value Gap   ", group="Imbalance", inline="fvg") settings.fvg_color := input.color(color.new(color.gray, 80), "", inline='fvg', group="Imbalance") settings.vi_show := input.bool(true, "Volume Imbalance", group="Imbalance", inline="vi") settings.vi_color := input.color(color.new(color.red, 50), "", inline='vi', group="Imbalance") settings.trace_show := input.bool(false, "Trace lines", group="trace") settings.trace_o_color := input.color(color.rgb(0, 0, 0), "Open    ", inline='1', group="trace") settings.trace_o_style := input.string('····', '', options = , inline='1', group="trace") settings.trace_o_size := input.int(1, '', options = , inline='1', group="trace") settings.trace_c_color := input.color(color.rgb(0, 0, 0), "Close    ", inline='2', group="trace") settings.trace_c_style := input.string('····', '', options = , inline='2', group="trace") settings.trace_c_size := input.int(1, '', options = , inline='2', group="trace") settings.trace_h_color := input.color(color.rgb(0, 0, 0), "High     ", inline='3', group="trace") settings.trace_h_style := input.string('····', '', options = , inline='3', group="trace") settings.trace_h_size := input.int(1, '', options = , inline='3', group="trace") settings.trace_l_color := input.color(color.rgb(0, 0, 0), "Low     ", inline='4', group="trace") settings.trace_l_style := input.string('····', '', options = , inline='4', group="trace") settings.trace_l_size := input.int(1, '', options = , inline='4', group="trace") settings.trace_anchor := input.string("First Timeframe", "Anchor to", options= , group="trace") settings.label_show := input.bool(false, "Price Label           ", inline="label") settings.label_color := input.color(color.rgb(0, 0, 0), "", inline='label') settings.label_size := input.string(size.small, "", , inline="label") //+------------------------------------------------------------------------------------------------------------+// //+--- Variables ---+// //+------------------------------------------------------------------------------------------------------------+// Helper helper = Helper.new() var Trace trace = Trace.new() color color_transparent = #ffffff00 //+------------------------------------------------------------------------------------------------------------+// //+--- Internal Functions ---+// //+------------------------------------------------------------------------------------------------------------+// method LineStyle(Helper helper, string style) => helper.name := style out = switch style '----' => line.style_dashed '····' => line.style_dotted => line.style_solid method ValidTimeframe(Helper helper, string HTF) => helper.name := HTF if timeframe.in_seconds(HTF) >= timeframe.in_seconds("D") and timeframe.in_seconds(HTF) > timeframe.in_seconds() true else n1 = timeframe.in_seconds() n2 = timeframe.in_seconds(HTF) n3 = n1 % n2 (n1 < n2 and math.round(n2/n1) == n2/n1) method RemainingTime(Helper helper, string HTF) => helper.name := HTF if barstate.isrealtime timeRemaining = (time_close(HTF) - timenow)/1000 days = math.floor(timeRemaining / 86400) hours = math.floor((timeRemaining - (days*86400)) / 3600) minutes = math.floor((timeRemaining - (days*86400) - (hours*3600))/ 60) seconds = math.floor(timeRemaining - (days*86400) - (hours*3600) - (minutes*60)) r = str.tostring(seconds, "00") if minutes > 0 or hours > 0 or days > 0 r := str.tostring(minutes, "00") + ":" + r if hours > 0 or days > 0 r := str.tostring(hours, "00") + ":" + r if days > 0 r := str.tostring(days) + "D " + r r else "n/a" method HTFName(Helper helper, string HTF) => helper.name := "HTFName" formatted = HTF seconds = timeframe.in_seconds(HTF) if seconds < 60 formatted := str.tostring(seconds) + "s" else if (seconds / 60) < 60 formatted := str.tostring((seconds/60)) + "m" else if (seconds/60/60) < 24 formatted := str.tostring((seconds/60/60)) + "H" formatted method HTFEnabled(Helper helper) => helper.name := "HTFEnabled" int enabled =0 enabled += htf1.settings.show ? 1 : 0 enabled += htf2.settings.show ? 1 : 0 enabled += htf3.settings.show ? 1 : 0 enabled += htf4.settings.show ? 1 : 0 enabled += htf5.settings.show ? 1 : 0 enabled += htf6.settings.show ? 1 : 0 int last = math.min(enabled, settings.max_sets) last method CandleSetHigh(Helper helper, Candle candles, float h) => helper.name := "CandlesSetHigh" float _h = h if array.size(candles) > 0 for i = 0 to array.size(candles)-1 Candle c = array.get(candles, i) if c.h > _h _h := c.h _h method CandlesHigh(Helper helper, Candle candles) => helper.name := "CandlesHigh" h = 0.0 int cnt = 0 int last = helper.HTFEnabled() if htf1.settings.show and helper.ValidTimeframe(htf1.settings.htf) h := helper.CandleSetHigh(htf1.candles, h) cnt += 1 if htf2.settings.show and helper.ValidTimeframe(htf2.settings.htf) and cnt < last h := helper.CandleSetHigh(htf2.candles, h) cnt +=1 if htf3.settings.show and helper.ValidTimeframe(htf3.settings.htf) and cnt < last h := helper.CandleSetHigh(htf3.candles, h) cnt += 1 if htf4.settings.show and helper.ValidTimeframe(htf4.settings.htf) and cnt < last h := helper.CandleSetHigh(htf4.candles, h) cnt += 1 if htf5.settings.show and helper.ValidTimeframe(htf5.settings.htf) and cnt < last h := helper.CandleSetHigh(htf5.candles, h) cnt += 1 if htf6.settings.show and helper.ValidTimeframe(htf6.settings.htf) and cnt < last h := helper.CandleSetHigh(htf6.candles, h) h if array.size(candles) > 0 for i = 0 to array.size(candles)-1 Candle c = array.get(candles, i) if c.h > h h := c.h h method Reorder(CandleSet candleSet, int offset) => size = candleSet.candles.size() if size > 0 for i = size-1 to 0 Candle candle = candleSet.candles.get(i) t_buffer = offset + ((settings.width+settings.buffer)*(size-i-1)) box.set_left(candle.body, bar_index + t_buffer) box.set_right(candle.body, bar_index + settings.width + t_buffer) line.set_x1(candle.wick_up, bar_index+((settings.width)/2) + t_buffer) line.set_x2(candle.wick_up, bar_index+((settings.width)/2) + t_buffer) line.set_x1(candle.wick_down, bar_index+((settings.width)/2) + t_buffer) line.set_x2(candle.wick_down, bar_index+((settings.width)/2) + t_buffer) candleSet top = helper.CandlesHigh(candleSet.candles) left = bar_index + offset + ((settings.width+settings.buffer)*(size-1))/2 if settings.htf_label_show var label l = candleSet.tfName string lbl = helper.HTFName(candleSet.settings.htf) if settings.htf_timer_show lbl += "\n" if not na(l) label.set_xy(l, left, top) else l := label.new(left, top, lbl, color=color_transparent, textcolor = settings.htf_label_color, style=label.style_label_down, size = settings.htf_label_size) if settings.htf_timer_show var label t = candleSet.tfTimer string tmr = "(" + helper.RemainingTime(candleSet.settings.htf) + ")" if not na(t) label.set_xy(t, left, top) else t := label.new(left, top, tmr, color=color_transparent, textcolor = settings.htf_timer_color, style=label.style_label_down, size = settings.htf_timer_size) candleSet method FindImbalance(CandleSet candleSet) => if barstate.isrealtime or barstate.islast if candleSet.imbalances.size() > 0 for i = candleSet.imbalances.size()-1 to 0 Imbalance del = candleSet.imbalances.get(i) box.delete(del.b) candleSet.imbalances.pop() if candleSet.candles.size() > 3 and settings.fvg_show for i = 1 to candleSet.candles.size() -3 candle1 = candleSet.candles.get(i) candle2 = candleSet.candles.get(i+2) candle3 = candleSet.candles.get(i+1) if (candle1.l > candle2.h and math.min(candle1.o, candle1.c) > math.max(candle2.o, candle2.c)) Imbalance imb = Imbalance.new() imb.b := box.new(box.get_left(candle2.body), candle2.h, box.get_right(candle1.body), candle1.l, bgcolor=settings.fvg_color, border_color = color_transparent, xloc=xloc.bar_index) candleSet.imbalances.push(imb) if (candle1.h < candle2.l and math.max(candle1.o, candle1.c) < math.min(candle2.o, candle2.c)) Imbalance imb = Imbalance.new() imb.b := box.new(box.get_right(candle1.body), candle1.h, box.get_left(candle2.body), candle2.l, bgcolor=settings.fvg_color, border_color = color_transparent) candleSet.imbalances.push(imb) box temp = box.copy(candle3.body) box.delete(candle3.body) candle3.body := temp if candleSet.candles.size() > 2 and settings.vi_show for i = 1 to candleSet.candles.size() -2 candle1 = candleSet.candles.get(i) candle2 = candleSet.candles.get(i+1) if (candle1.l < candle2.h and math.min(candle1.o, candle1.c) > math.max(candle2.o, candle2.c)) Imbalance imb = Imbalance.new() imb.b := box.new(box.get_left(candle2.body), math.min(candle1.o, candle1.c), box.get_right(candle1.body), math.max(candle2.o, candle2.c), bgcolor=settings.vi_color, border_color = color_transparent) candleSet.imbalances.push(imb) if (candle1.h > candle2.l and math.max(candle1.o, candle1.c) < math.min(candle2.o, candle2.c)) Imbalance imb = Imbalance.new() imb.b := box.new(box.get_right(candle1.body), math.min(candle2.o, candle2.c), box.get_left(candle2.body), math.max(candle1.o, candle1.c), bgcolor=settings.vi_color, border_color = color_transparent) candleSet.imbalances.push(imb) candleSet method Monitor(CandleSet candleSet) => HTFBarTime = time(candleSet.settings.htf) isNewHTFCandle = ta.change(HTFBarTime) if isNewHTFCandle Candle candle = Candle.new() candle.o := open candle.c := close candle.h := high candle.l := low candle.o_idx := bar_index candle.c_idx := bar_index candle.h_idx := bar_index candle.l_idx := bar_index bull = candle.c > candle.o candle.body := box.new(bar_index, math.max(candle.o, candle.c), bar_index+2, math.min(candle.o, candle.c), bull ? settings.bull_border : settings.bear_border, 1, bgcolor = bull ? settings.bull_body : settings.bear_body) candle.wick_up := line.new(bar_index+1, candle.h, bar_index, math.max(candle.o, candle.c), color=bull ? settings.bull_wick : settings.bear_wick) candle.wick_down := line.new(bar_index+1, math.min(candle.o, candle.c), bar_index, candle.l, color=bull ? settings.bull_wick : settings.bear_wick) candleSet.candles.unshift(candle) if candleSet.candles.size() > candleSet.settings.max_display Candle delCandle = array.pop(candleSet.candles) box.delete(delCandle.body) line.delete(delCandle.wick_up) line.delete(delCandle.wick_down) candleSet method Update(CandleSet candleSet, int offset, bool showTrace) => if candleSet.candles.size() > 0 Candle candle = candleSet.candles.first() candle.h_idx := high > candle.h ? bar_index : candle.h_idx candle.h := high > candle.h ? high : candle.h candle.l_idx := low < candle.l ? bar_index : candle.l_idx candle.l := low < candle.l ? low : candle.l candle.c := close candle.c_idx := bar_index bull = candle.c > candle.o box.set_top(candle.body, candle.o) box.set_bottom(candle.body, candle.c) box.set_bgcolor(candle.body, bull ? settings.bull_body : settings.bear_body) box.set_border_color(candle.body, bull ? settings.bull_border : settings.bear_border) line.set_color(candle.wick_up, bull ? settings.bull_wick : settings.bear_wick) line.set_color(candle.wick_down, bull ? settings.bull_wick : settings.bear_wick) line.set_y1(candle.wick_up, candle.h) line.set_y2(candle.wick_up, math.max(candle.o, candle.c)) line.set_y1(candle.wick_down, candle.l) line.set_y2(candle.wick_down, math.min(candle.o, candle.c)) if barstate.isrealtime or barstate.islast candleSet.Reorder(offset) if settings.trace_show and showTrace if bar_index - candle.o_idx < 5000 if na(trace.o) trace.o := line.new(candle.o_idx, candle.o, box.get_left(candle.body), candle.o, xloc= xloc.bar_index, color=settings.trace_o_color, style= helper.LineStyle(settings.trace_o_style), width=settings.trace_o_size) else line.set_xy1(trace.o, candle.o_idx, candle.o) line.set_xy2(trace.o, box.get_left(candle.body), candle.o) if settings.label_show if na(trace.o_l) trace.o_l := label.new(box.get_right(candle.body), candle.o, str.tostring(candle.o), textalign = text.align_center, style=label.style_label_left, size=settings.label_size, color=color_transparent, textcolor=settings.label_color) else label.set_xy(trace.o_l, box.get_right(candle.body), candle.o) label.set_text(trace.o_l, str.tostring(candle.o)) if bar_index - candle.c_idx < 5000 if na(trace.c) trace.c := line.new(candle.c_idx, candle.c, box.get_left(candle.body), candle.c, xloc= xloc.bar_index, color=settings.trace_c_color, style=helper.LineStyle(settings.trace_c_style), width=settings.trace_c_size) else line.set_xy1(trace.c, candle.c_idx, candle.c) line.set_xy2(trace.c, box.get_left(candle.body), candle.c) if settings.label_show if na(trace.c_l) trace.c_l := label.new(box.get_right(candle.body), candle.c, str.tostring(candle.c), textalign = text.align_center, style=label.style_label_left, size=settings.label_size, color=color_transparent, textcolor=settings.label_color) else label.set_xy(trace.c_l, box.get_right(candle.body), candle.c) label.set_text(trace.c_l, str.tostring(candle.c)) if bar_index - candle.h_idx < 5000 if na(trace.h) trace.h := line.new(candle.h_idx, candle.h, line.get_x1(candle.wick_up), candle.h, xloc= xloc.bar_index, color=settings.trace_h_color, style=helper.LineStyle(settings.trace_h_style), width=settings.trace_h_size) else line.set_xy1(trace.h, candle.h_idx, candle.h) line.set_xy2(trace.h, line.get_x1(candle.wick_up), candle.h) if settings.label_show if na(trace.h_l) trace.h_l := label.new(box.get_right(candle.body), candle.h, str.tostring(candle.h), textalign = text.align_center, style=label.style_label_left, size=settings.label_size, color=color_transparent, textcolor=settings.label_color) else label.set_xy(trace.h_l, box.get_right(candle.body), candle.h) label.set_text(trace.h_l, str.tostring(candle.o)) if bar_index - candle.l_idx < 5000 if na(trace.l) trace.l := line.new(candle.l_idx, candle.l, line.get_x1(candle.wick_down), candle.l, xloc= xloc.bar_index, color=settings.trace_l_color, style=helper.LineStyle(settings.trace_l_style), width=settings.trace_l_size) else line.set_xy1(trace.l, candle.l_idx, candle.l) line.set_xy2(trace.l, line.get_x1(candle.wick_down), candle.l) if settings.label_show if na(trace.l_l) trace.l_l := label.new(box.get_right(candle.body), candle.l, str.tostring(candle.l), textalign = text.align_center, style=label.style_label_left, size=settings.label_size, color=color_transparent, textcolor=settings.label_color) else label.set_xy(trace.l_l, box.get_right(candle.body), candle.l) label.set_text(trace.l_l, str.tostring(candle.o)) candleSet int cnt = 0 int last = helper.HTFEnabled() int offset = settings.offset if htf1.settings.show and helper.ValidTimeframe(htf1.settings.htf) bool showTrace = false if settings.trace_anchor == "First Timeframe" showTrace := true if settings.trace_anchor == "Last Timeframe" and settings.max_sets == 1 showTrace := true htf1.Monitor().Update(offset, showTrace).FindImbalance() cnt +=1 offset += cnt > 0 ? (htf1.candles.size() * settings.width) + (htf1.candles.size() > 0 ? htf1.candles.size()-1 * settings.buffer : 0) + settings.htf_buffer : 0 if htf2.settings.show and helper.ValidTimeframe(htf2.settings.htf) and cnt < last bool showTrace = false if settings.trace_anchor == "First Timeframe" and cnt == 0 showTrace := true if settings.trace_anchor == "Last Timeframe" and cnt == last-1 showTrace := true htf2.Monitor().Update(offset, showTrace).FindImbalance() cnt+=1 offset += cnt > 0 ? (htf2.candles.size() * settings.width) + (htf2.candles.size() > 0 ? htf2.candles.size()-1 * settings.buffer : 0) + settings.htf_buffer : 0 if htf3.settings.show and helper.ValidTimeframe(htf3.settings.htf) and cnt < last bool showTrace = false if settings.trace_anchor == "First Timeframe" and cnt == 0 showTrace := true if settings.trace_anchor == "Last Timeframe" and cnt == last-1 showTrace := true htf3.Monitor().Update(offset, showTrace).FindImbalance() cnt+=1 offset += cnt > 0 ? (htf3.candles.size() * settings.width) + (htf3.candles.size() > 0 ? htf3.candles.size()-1 * settings.buffer : 0) + settings.htf_buffer : 0 if htf4.settings.show and helper.ValidTimeframe(htf4.settings.htf) and cnt < last bool showTrace = false if settings.trace_anchor == "First Timeframe" and cnt == 0 showTrace := true if settings.trace_anchor == "Last Timeframe" and cnt == last-1 showTrace := true htf4.Monitor().Update(offset, showTrace).FindImbalance() cnt+=1 offset += cnt > 0 ? (htf4.candles.size() * settings.width) + (htf4.candles.size() > 0 ? htf4.candles.size()-1 * settings.buffer : 0) + settings.htf_buffer : 0 if htf5.settings.show and helper.ValidTimeframe(htf5.settings.htf) and cnt < last bool showTrace = false if settings.trace_anchor == "First Timeframe" and cnt == 0 showTrace := true if settings.trace_anchor == "Last Timeframe" and cnt == last-1 showTrace := true htf5.Monitor().Update(offset, showTrace).FindImbalance() cnt+=1 offset += cnt > 0 ? (htf5.candles.size() * settings.width) + (htf5.candles.size() > 0 ? htf5.candles.size()-1 * settings.buffer : 0) + settings.htf_buffer : 0 if htf6.settings.show and helper.ValidTimeframe(htf6.settings.htf) and cnt < last bool showTrace = false if settings.trace_anchor == "First Timeframe" and cnt == 0 showTrace := true if settings.trace_anchor == "Last Timeframe" showTrace := true htf6.Monitor().Update(offset, showTrace).FindImbalance() //------------------------------------------------------------------------------------------------// // This Pine Script™ code is subject to the terms of the Mozilla Public License 2.0 at mozilla.org // ©Mutharasan12 //@version=5 //indicator("Notes, Watermark",overlay = true) // STICKY NOTES #BEGIN --------------------------------------------------------------------------------------------------------------------------------------------------------// var StickyNote_settings = "STICKY NOTES --------------------------------------------------" showStickyNotes = input.bool(false, "Show Sticky Notes?", group = StickyNote_settings) if showStickyNotes stickynote01 = input.text_area("Your Note Here","NOTES",group = StickyNote_settings) tl1 = input.string("top", title = "Sticky Note Position (Vertical)", options = , group = StickyNote_settings) tl2 = input.string("right", title = "Sticky Note Position (Horizontal)", options = , group = StickyNote_settings) font_size = input.string("Normal", title = "Sticky Note Text Size", options = , group = StickyNote_settings) font_type = input.string("Default", title = "Font Type", options = , group = StickyNote_settings) font_color = input.color(color.rgb(0,0,0,0), title = "Note Color", inline = 'nc', group = StickyNote_settings) note_color = input.color(color (color.rgb(0,0,0,100)), title = "Note Background", inline='nc', group = StickyNote_settings) selected_font = font_type == "Default" ? font.family_default : font.family_monospace selected_size = font_size == "Auto" ? size.auto : font_size == "Huge" ? size.huge : font_size == "Large" ? size.large : font_size == "Normal" ? size.normal : font_size == "Small" ? size.small : font_size == "Tiny" ? size.tiny : na var table t1 = table.new(tl1 + "_" + tl2, 1, 10) if barstate.islast if not na(stickynote01) and stickynote01 != "" table.cell(t1,0,0, text = stickynote01 , bgcolor = note_color, text_color = font_color, text_halign = text.align_left, text_size = selected_size, text_font_family = selected_font) // STICKY NOTES #END ----------------------------------------------------------------------------------------------------------------------------------------------------------// // WATERMARK #BEGIN --
مؤشر Pine Script®
من ‎maatsfx‎
Quantum Rotational Field MappingQuantum Rotational Field Mapping (QRFM): Phase Coherence Detection Through Complex-Plane Oscillator Analysis Quantum Rotational Field Mapping applies complex-plane mathematics and phase-space analysis to oscillator ensembles, identifying high-probability trend ignition points by measuring when multiple independent oscillators achieve phase coherence. Unlike traditional multi-oscillator approaches that simply stack indicators or use boolean AND/OR logic, this system converts each oscillator into a rotating phasor (vector) in the complex plane and calculates the Coherence Index (CI) —a mathematical measure of how tightly aligned the ensemble has become—then generates signals only when alignment, phase direction, and pairwise entanglement all converge. The indicator combines three mathematical frameworks: phasor representation using analytic signal theory to extract phase and amplitude from each oscillator, coherence measurement using vector summation in the complex plane to quantify group alignment, and entanglement analysis that calculates pairwise phase agreement across all oscillator combinations. This creates a multi-dimensional confirmation system that distinguishes between random oscillator noise and genuine regime transitions. What Makes This Original Complex-Plane Phasor Framework This indicator implements classical signal processing mathematics adapted for market oscillators. Each oscillator—whether RSI, MACD, Stochastic, CCI, Williams %R, MFI, ROC, or TSI—is first normalized to a common scale, then converted into a complex-plane representation using an in-phase (I) and quadrature (Q) component. The in-phase component is the oscillator value itself, while the quadrature component is calculated as the first difference (derivative proxy), creating a velocity-aware representation. From these components, the system extracts: Phase (φ) : Calculated as φ = atan2(Q, I), representing the oscillator's position in its cycle (mapped to -180° to +180°) Amplitude (A) : Calculated as A = √(I² + Q²), representing the oscillator's strength or conviction This mathematical approach is fundamentally different from simply reading oscillator values. A phasor captures both where an oscillator is in its cycle (phase angle) and how strongly it's expressing that position (amplitude). Two oscillators can have the same value but be in opposite phases of their cycles—traditional analysis would see them as identical, while QRFM sees them as 180° out of phase (contradictory). Coherence Index Calculation The core innovation is the Coherence Index (CI) , borrowed from physics and signal processing. When you have N oscillators, each with phase φₙ, you can represent each as a unit vector in the complex plane: e^(iφₙ) = cos(φₙ) + i·sin(φₙ). The CI measures what happens when you sum all these vectors: Resultant Vector : R = Σ e^(iφₙ) = Σ cos(φₙ) + i·Σ sin(φₙ) Coherence Index : CI = |R| / N Where |R| is the magnitude of the resultant vector and N is the number of active oscillators. The CI ranges from 0 to 1: CI = 1.0 : Perfect coherence—all oscillators have identical phase angles, vectors point in the same direction, creating maximum constructive interference CI = 0.0 : Complete decoherence—oscillators are randomly distributed around the circle, vectors cancel out through destructive interference 0 < CI < 1 : Partial alignment—some clustering with some scatter This is not a simple average or correlation. The CI captures phase synchronization across the entire ensemble simultaneously. When oscillators phase-lock (align their cycles), the CI spikes regardless of their individual values. This makes it sensitive to regime transitions that traditional indicators miss. Dominant Phase and Direction Detection Beyond measuring alignment strength, the system calculates the dominant phase of the ensemble—the direction the resultant vector points: Dominant Phase : φ_dom = atan2(Σ sin(φₙ), Σ cos(φₙ)) This gives the "average direction" of all oscillator phases, mapped to -180° to +180°: +90° to -90° (right half-plane): Bullish phase dominance +90° to +180° or -90° to -180° (left half-plane): Bearish phase dominance The combination of CI magnitude (coherence strength) and dominant phase angle (directional bias) creates a two-dimensional signal space. High CI alone is insufficient—you need high CI plus dominant phase pointing in a tradeable direction. This dual requirement is what separates QRFM from simple oscillator averaging. Entanglement Matrix and Pairwise Coherence While the CI measures global alignment, the entanglement matrix measures local pairwise relationships. For every pair of oscillators (i, j), the system calculates: E(i,j) = |cos(φᵢ - φⱼ)| This represents the phase agreement between oscillators i and j: E = 1.0 : Oscillators are in-phase (0° or 360° apart) E = 0.0 : Oscillators are in quadrature (90° apart, orthogonal) E between 0 and 1 : Varying degrees of alignment The system counts how many oscillator pairs exceed a user-defined entanglement threshold (e.g., 0.7). This entangled pairs count serves as a confirmation filter: signals require not just high global CI, but also a minimum number of strong pairwise agreements. This prevents false ignitions where CI is high but driven by only two oscillators while the rest remain scattered. The entanglement matrix creates an N×N symmetric matrix that can be visualized as a web—when many cells are bright (high E values), the ensemble is highly interconnected. When cells are dark, oscillators are moving independently. Phase-Lock Tolerance Mechanism A complementary confirmation layer is the phase-lock detector . This calculates the maximum phase spread across all oscillators: For all pairs (i,j), compute angular distance: Δφ = |φᵢ - φⱼ|, wrapping at 180° Max Spread = maximum Δφ across all pairs If max spread < user threshold (e.g., 35°), the ensemble is considered phase-locked —all oscillators are within a narrow angular band. This differs from entanglement: entanglement measures pairwise cosine similarity (magnitude of alignment), while phase-lock measures maximum angular deviation (tightness of clustering). Both must be satisfied for the highest-conviction signals. Multi-Layer Visual Architecture QRFM includes six visual components that represent the same underlying mathematics from different perspectives: Circular Orbit Plot : A polar coordinate grid showing each oscillator as a vector from origin to perimeter. Angle = phase, radius = amplitude. This is a real-time snapshot of the complex plane. When vectors converge (point in similar directions), coherence is high. When scattered randomly, coherence is low. Users can see phase alignment forming before CI numerically confirms it. Phase-Time Heat Map : A 2D matrix with rows = oscillators and columns = time bins. Each cell is colored by the oscillator's phase at that time (using a gradient where color hue maps to angle). Horizontal color bands indicate sustained phase alignment over time. Vertical color bands show moments when all oscillators shared the same phase (ignition points). This provides historical pattern recognition. Entanglement Web Matrix : An N×N grid showing E(i,j) for all pairs. Cells are colored by entanglement strength—bright yellow/gold for high E, dark gray for low E. This reveals which oscillators are driving coherence and which are lagging. For example, if RSI and MACD show high E but Stochastic shows low E with everything, Stochastic is the outlier. Quantum Field Cloud : A background color overlay on the price chart. Color (green = bullish, red = bearish) is determined by dominant phase. Opacity is determined by CI—high CI creates dense, opaque cloud; low CI creates faint, nearly invisible cloud. This gives an atmospheric "feel" for regime strength without looking at numbers. Phase Spiral : A smoothed plot of dominant phase over recent history, displayed as a curve that wraps around price. When the spiral is tight and rotating steadily, the ensemble is in coherent rotation (trending). When the spiral is loose or erratic, coherence is breaking down. Dashboard : A table showing real-time metrics: CI (as percentage), dominant phase (in degrees with directional arrow), field strength (CI × average amplitude), entangled pairs count, phase-lock status (locked/unlocked), quantum state classification ("Ignition", "Coherent", "Collapse", "Chaos"), and collapse risk (recent CI change normalized to 0-100%). Each component is independently toggleable, allowing users to customize their workspace. The orbit plot is the most essential—it provides intuitive, visual feedback on phase alignment that no numerical dashboard can match. Core Components and How They Work Together 1. Oscillator Normalization Engine The foundation is creating a common measurement scale. QRFM supports eight oscillators: RSI : Normalized from to using overbought/oversold levels (70, 30) as anchors MACD Histogram : Normalized by dividing by rolling standard deviation, then clamped to Stochastic %K : Normalized from using (80, 20) anchors CCI : Divided by 200 (typical extreme level), clamped to Williams %R : Normalized from using (-20, -80) anchors MFI : Normalized from using (80, 20) anchors ROC : Divided by 10, clamped to TSI : Divided by 50, clamped to Each oscillator can be individually enabled/disabled. Only active oscillators contribute to phase calculations. The normalization removes scale differences—a reading of +0.8 means "strongly bullish" regardless of whether it came from RSI or TSI. 2. Analytic Signal Construction For each active oscillator at each bar, the system constructs the analytic signal: In-Phase (I) : The normalized oscillator value itself Quadrature (Q) : The bar-to-bar change in the normalized value (first derivative approximation) This creates a 2D representation: (I, Q). The phase is extracted as: φ = atan2(Q, I) × (180 / π) This maps the oscillator to a point on the unit circle. An oscillator at the same value but rising (positive Q) will have a different phase than one that is falling (negative Q). This velocity-awareness is critical—it distinguishes between "at resistance and stalling" versus "at resistance and breaking through." The amplitude is extracted as: A = √(I² + Q²) This represents the distance from origin in the (I, Q) plane. High amplitude means the oscillator is far from neutral (strong conviction). Low amplitude means it's near zero (weak/transitional state). 3. Coherence Calculation Pipeline For each bar (or every Nth bar if phase sample rate > 1 for performance): Step 1 : Extract phase φₙ for each of the N active oscillators Step 2 : Compute complex exponentials: Zₙ = e^(i·φₙ·π/180) = cos(φₙ·π/180) + i·sin(φₙ·π/180) Step 3 : Sum the complex exponentials: R = Σ Zₙ = (Σ cos φₙ) + i·(Σ sin φₙ) Step 4 : Calculate magnitude: |R| = √ Step 5 : Normalize by count: CI_raw = |R| / N Step 6 : Smooth the CI: CI = SMA(CI_raw, smoothing_window) The smoothing step (default 2 bars) removes single-bar noise spikes while preserving structural coherence changes. Users can adjust this to control reactivity versus stability. The dominant phase is calculated as: φ_dom = atan2(Σ sin φₙ, Σ cos φₙ) × (180 / π) This is the angle of the resultant vector R in the complex plane. 4. Entanglement Matrix Construction For all unique pairs of oscillators (i, j) where i < j: Step 1 : Get phases φᵢ and φⱼ Step 2 : Compute phase difference: Δφ = φᵢ - φⱼ (in radians) Step 3 : Calculate entanglement: E(i,j) = |cos(Δφ)| Step 4 : Store in symmetric matrix: matrix = matrix = E(i,j) The matrix is then scanned: count how many E(i,j) values exceed the user-defined threshold (default 0.7). This count is the entangled pairs metric. For visualization, the matrix is rendered as an N×N table where cell brightness maps to E(i,j) intensity. 5. Phase-Lock Detection Step 1 : For all unique pairs (i, j), compute angular distance: Δφ = |φᵢ - φⱼ| Step 2 : Wrap angles: if Δφ > 180°, set Δφ = 360° - Δφ Step 3 : Find maximum: max_spread = max(Δφ) across all pairs Step 4 : Compare to tolerance: phase_locked = (max_spread < tolerance) If phase_locked is true, all oscillators are within the specified angular cone (e.g., 35°). This is a boolean confirmation filter. 6. Signal Generation Logic Signals are generated through multi-layer confirmation: Long Ignition Signal : CI crosses above ignition threshold (e.g., 0.80) AND dominant phase is in bullish range (-90° < φ_dom < +90°) AND phase_locked = true AND entangled_pairs >= minimum threshold (e.g., 4) Short Ignition Signal : CI crosses above ignition threshold AND dominant phase is in bearish range (φ_dom < -90° OR φ_dom > +90°) AND phase_locked = true AND entangled_pairs >= minimum threshold Collapse Signal : CI at bar minus CI at current bar > collapse threshold (e.g., 0.55) AND CI at bar was above 0.6 (must collapse from coherent state, not from already-low state) These are strict conditions. A high CI alone does not generate a signal—dominant phase must align with direction, oscillators must be phase-locked, and sufficient pairwise entanglement must exist. This multi-factor gating dramatically reduces false signals compared to single-condition triggers. Calculation Methodology Phase 1: Oscillator Computation and Normalization On each bar, the system calculates the raw values for all enabled oscillators using standard Pine Script functions: RSI: ta.rsi(close, length) MACD: ta.macd() returning histogram component Stochastic: ta.stoch() smoothed with ta.sma() CCI: ta.cci(close, length) Williams %R: ta.wpr(length) MFI: ta.mfi(hlc3, length) ROC: ta.roc(close, length) TSI: ta.tsi(close, short, long) Each raw value is then passed through a normalization function: normalize(value, overbought_level, oversold_level) = 2 × (value - oversold) / (overbought - oversold) - 1 This maps the oscillator's typical range to , where -1 represents extreme bearish, 0 represents neutral, and +1 represents extreme bullish. For oscillators without fixed ranges (MACD, ROC, TSI), statistical normalization is used: divide by a rolling standard deviation or fixed divisor, then clamp to . Phase 2: Phasor Extraction For each normalized oscillator value val: I = val (in-phase component) Q = val - val (quadrature component, first difference) Phase calculation: phi_rad = atan2(Q, I) phi_deg = phi_rad × (180 / π) Amplitude calculation: A = √(I² + Q²) These values are stored in arrays: osc_phases and osc_amps for each oscillator n. Phase 3: Complex Summation and Coherence Initialize accumulators: sum_cos = 0 sum_sin = 0 For each oscillator n = 0 to N-1: phi_rad = osc_phases × (π / 180) sum_cos += cos(phi_rad) sum_sin += sin(phi_rad) Resultant magnitude: resultant_mag = √(sum_cos² + sum_sin²) Coherence Index (raw): CI_raw = resultant_mag / N Smoothed CI: CI = SMA(CI_raw, smoothing_window) Dominant phase: phi_dom_rad = atan2(sum_sin, sum_cos) phi_dom_deg = phi_dom_rad × (180 / π) Phase 4: Entanglement Matrix Population For i = 0 to N-2: For j = i+1 to N-1: phi_i = osc_phases × (π / 180) phi_j = osc_phases × (π / 180) delta_phi = phi_i - phi_j E = |cos(delta_phi)| matrix_index_ij = i × N + j matrix_index_ji = j × N + i entangle_matrix = E entangle_matrix = E if E >= threshold: entangled_pairs += 1 The matrix uses flat array storage with index mapping: index(row, col) = row × N + col. Phase 5: Phase-Lock Check max_spread = 0 For i = 0 to N-2: For j = i+1 to N-1: delta = |osc_phases - osc_phases | if delta > 180: delta = 360 - delta max_spread = max(max_spread, delta) phase_locked = (max_spread < tolerance) Phase 6: Signal Evaluation Ignition Long : ignition_long = (CI crosses above threshold) AND (phi_dom > -90 AND phi_dom < 90) AND phase_locked AND (entangled_pairs >= minimum) Ignition Short : ignition_short = (CI crosses above threshold) AND (phi_dom < -90 OR phi_dom > 90) AND phase_locked AND (entangled_pairs >= minimum) Collapse : CI_prev = CI collapse = (CI_prev - CI > collapse_threshold) AND (CI_prev > 0.6) All signals are evaluated on bar close. The crossover and crossunder functions ensure signals fire only once when conditions transition from false to true. Phase 7: Field Strength and Visualization Metrics Average Amplitude : avg_amp = (Σ osc_amps ) / N Field Strength : field_strength = CI × avg_amp Collapse Risk (for dashboard): collapse_risk = (CI - CI) / max(CI , 0.1) collapse_risk_pct = clamp(collapse_risk × 100, 0, 100) Quantum State Classification : if (CI > threshold AND phase_locked): state = "Ignition" else if (CI > 0.6): state = "Coherent" else if (collapse): state = "Collapse" else: state = "Chaos" Phase 8: Visual Rendering Orbit Plot : For each oscillator, convert polar (phase, amplitude) to Cartesian (x, y) for grid placement: radius = amplitude × grid_center × 0.8 x = radius × cos(phase × π/180) y = radius × sin(phase × π/180) col = center + x (mapped to grid coordinates) row = center - y Heat Map : For each oscillator row and time column, retrieve historical phase value at lookback = (columns - col) × sample_rate, then map phase to color using a hue gradient. Entanglement Web : Render matrix as table cell with background color opacity = E(i,j). Field Cloud : Background color = (phi_dom > -90 AND phi_dom < 90) ? green : red, with opacity = mix(min_opacity, max_opacity, CI). All visual components render only on the last bar (barstate.islast) to minimize computational overhead. How to Use This Indicator Step 1 : Apply QRFM to your chart. It works on all timeframes and asset classes, though 15-minute to 4-hour timeframes provide the best balance of responsiveness and noise reduction. Step 2 : Enable the dashboard (default: top right) and the circular orbit plot (default: middle left). These are your primary visual feedback tools. Step 3 : Optionally enable the heat map, entanglement web, and field cloud based on your preference. New users may find all visuals overwhelming; start with dashboard + orbit plot. Step 4 : Observe for 50-100 bars to let the indicator establish baseline coherence patterns. Markets have different "normal" CI ranges—some instruments naturally run higher or lower coherence. Understanding the Circular Orbit Plot The orbit plot is a polar grid showing oscillator vectors in real-time: Center point : Neutral (zero phase and amplitude) Each vector : A line from center to a point on the grid Vector angle : The oscillator's phase (0° = right/east, 90° = up/north, 180° = left/west, -90° = down/south) Vector length : The oscillator's amplitude (short = weak signal, long = strong signal) Vector label : First letter of oscillator name (R = RSI, M = MACD, etc.) What to watch : Convergence : When all vectors cluster in one quadrant or sector, CI is rising and coherence is forming. This is your pre-signal warning. Scatter : When vectors point in random directions (360° spread), CI is low and the market is in a non-trending or transitional regime. Rotation : When the cluster rotates smoothly around the circle, the ensemble is in coherent oscillation—typically seen during steady trends. Sudden flips : When the cluster rapidly jumps from one side to the opposite (e.g., +90° to -90°), a phase reversal has occurred—often coinciding with trend reversals. Example: If you see RSI, MACD, and Stochastic all pointing toward 45° (northeast) with long vectors, while CCI, TSI, and ROC point toward 40-50° as well, coherence is high and dominant phase is bullish. Expect an ignition signal if CI crosses threshold. Reading Dashboard Metrics The dashboard provides numerical confirmation of what the orbit plot shows visually: CI : Displays as 0-100%. Above 70% = high coherence (strong regime), 40-70% = moderate, below 40% = low (poor conditions for trend entries). Dom Phase : Angle in degrees with directional arrow. ⬆ = bullish bias, ⬇ = bearish bias, ⬌ = neutral. Field Strength : CI weighted by amplitude. High values (> 0.6) indicate not just alignment but strong alignment. Entangled Pairs : Count of oscillator pairs with E > threshold. Higher = more confirmation. If minimum is set to 4, you need at least 4 pairs entangled for signals. Phase Lock : 🔒 YES (all oscillators within tolerance) or 🔓 NO (spread too wide). State : Real-time classification: 🚀 IGNITION: CI just crossed threshold with phase-lock ⚡ COHERENT: CI is high and stable 💥 COLLAPSE: CI has dropped sharply 🌀 CHAOS: Low CI, scattered phases Collapse Risk : 0-100% scale based on recent CI change. Above 50% warns of imminent breakdown. Interpreting Signals Long Ignition (Blue Triangle Below Price) : Occurs when CI crosses above threshold (e.g., 0.80) Dominant phase is in bullish range (-90° to +90°) All oscillators are phase-locked (within tolerance) Minimum entangled pairs requirement met Interpretation : The oscillator ensemble has transitioned from disorder to coherent bullish alignment. This is a high-probability long entry point. The multi-layer confirmation (CI + phase direction + lock + entanglement) ensures this is not a single-oscillator whipsaw. Short Ignition (Red Triangle Above Price) : Same conditions as long, but dominant phase is in bearish range (< -90° or > +90°) Interpretation : Coherent bearish alignment has formed. High-probability short entry. Collapse (Circles Above and Below Price) : CI has dropped by more than the collapse threshold (e.g., 0.55) over a 5-bar window CI was previously above 0.6 (collapsing from coherent state) Interpretation : Phase coherence has broken down. If you are in a position, this is an exit warning. If looking to enter, stand aside—regime is transitioning. Phase-Time Heat Map Patterns Enable the heat map and position it at bottom right. The rows represent individual oscillators, columns represent time bins (most recent on left). Pattern: Horizontal Color Bands If a row (e.g., RSI) shows consistent color across columns (say, green for several bins), that oscillator has maintained stable phase over time. If all rows show horizontal bands of similar color, the entire ensemble has been phase-locked for an extended period—this is a strong trending regime. Pattern: Vertical Color Bands If a column (single time bin) shows all cells with the same or very similar color, that moment in time had high coherence. These vertical bands often align with ignition signals or major price pivots. Pattern: Rainbow Chaos If cells are random colors (red, green, yellow mixed with no pattern), coherence is low. The ensemble is scattered. Avoid trading during these periods unless you have external confirmation. Pattern: Color Transition If you see a row transition from red to green (or vice versa) sharply, that oscillator has phase-flipped. If multiple rows do this simultaneously, a regime change is underway. Entanglement Web Analysis Enable the web matrix (default: opposite corner from heat map). It shows an N×N grid where N = number of active oscillators. Bright Yellow/Gold Cells : High pairwise entanglement. For example, if the RSI-MACD cell is bright gold, those two oscillators are moving in phase. If the RSI-Stochastic cell is bright, they are entangled as well. Dark Gray Cells : Low entanglement. Oscillators are decorrelated or in quadrature. Diagonal : Always marked with "—" because an oscillator is always perfectly entangled with itself. How to use : Scan for clustering: If most cells are bright, coherence is high across the board. If only a few cells are bright, coherence is driven by a subset (e.g., RSI and MACD are aligned, but nothing else is—weak signal). Identify laggards: If one row/column is entirely dark, that oscillator is the outlier. You may choose to disable it or monitor for when it joins the group (late confirmation). Watch for web formation: During low-coherence periods, the matrix is mostly dark. As coherence builds, cells begin lighting up. A sudden "web" of connections forming visually precedes ignition signals. Trading Workflow Step 1: Monitor Coherence Level Check the dashboard CI metric or observe the orbit plot. If CI is below 40% and vectors are scattered, conditions are poor for trend entries. Wait. Step 2: Detect Coherence Building When CI begins rising (say, from 30% to 50-60%) and you notice vectors on the orbit plot starting to cluster, coherence is forming. This is your alert phase—do not enter yet, but prepare. Step 3: Confirm Phase Direction Check the dominant phase angle and the orbit plot quadrant where clustering is occurring: Clustering in right half (0° to ±90°): Bullish bias forming Clustering in left half (±90° to 180°): Bearish bias forming Verify the dashboard shows the corresponding directional arrow (⬆ or ⬇). Step 4: Wait for Signal Confirmation Do not enter based on rising CI alone. Wait for the full ignition signal: CI crosses above threshold Phase-lock indicator shows 🔒 YES Entangled pairs count >= minimum Directional triangle appears on chart This ensures all layers have aligned. Step 5: Execute Entry Long : Blue triangle below price appears → enter long Short : Red triangle above price appears → enter short Step 6: Position Management Initial Stop : Place stop loss based on your risk management rules (e.g., recent swing low/high, ATR-based buffer). Monitoring : Watch the field cloud density. If it remains opaque and colored in your direction, the regime is intact. Check dashboard collapse risk. If it rises above 50%, prepare for exit. Monitor the orbit plot. If vectors begin scattering or the cluster flips to the opposite side, coherence is breaking. Exit Triggers : Collapse signal fires (circles appear) Dominant phase flips to opposite half-plane CI drops below 40% (coherence lost) Price hits your profit target or trailing stop Step 7: Post-Exit Analysis After exiting, observe whether a new ignition forms in the opposite direction (reversal) or if CI remains low (transition to range). Use this to decide whether to re-enter, reverse, or stand aside. Best Practices Use Price Structure as Context QRFM identifies when coherence forms but does not specify where price will go. Combine ignition signals with support/resistance levels, trendlines, or chart patterns. For example: Long ignition near a major support level after a pullback: high-probability bounce Long ignition in the middle of a range with no structure: lower probability Multi-Timeframe Confirmation Open QRFM on two timeframes simultaneously: Higher timeframe (e.g., 4-hour): Use CI level to determine regime bias. If 4H CI is above 60% and dominant phase is bullish, the market is in a bullish regime. Lower timeframe (e.g., 15-minute): Execute entries on ignition signals that align with the higher timeframe bias. This prevents counter-trend trades and increases win rate. Distinguish Between Regime Types High CI, stable dominant phase (State: Coherent) : Trending market. Ignitions are continuation signals; collapses are profit-taking or reversal warnings. Low CI, erratic dominant phase (State: Chaos) : Ranging or choppy market. Avoid ignition signals or reduce position size. Wait for coherence to establish. Moderate CI with frequent collapses : Whipsaw environment. Use wider stops or stand aside. Adjust Parameters to Instrument and Timeframe Crypto/Forex (high volatility) : Lower ignition threshold (0.65-0.75), lower CI smoothing (2-3), shorter oscillator lengths (7-10). Stocks/Indices (moderate volatility) : Standard settings (threshold 0.75-0.85, smoothing 5-7, oscillator lengths 14). Lower timeframes (5-15 min) : Reduce phase sample rate to 1-2 for responsiveness. Higher timeframes (daily+) : Increase CI smoothing and oscillator lengths for noise reduction. Use Entanglement Count as Conviction Filter The minimum entangled pairs setting controls signal strictness: Low (1-2) : More signals, lower quality (acceptable if you have other confirmation) Medium (3-5) : Balanced (recommended for most traders) High (6+) : Very strict, fewer signals, highest quality Adjust based on your trade frequency preference and risk tolerance. Monitor Oscillator Contribution Use the entanglement web to see which oscillators are driving coherence. If certain oscillators are consistently dark (low E with all others), they may be adding noise. Consider disabling them. For example: On low-volume instruments, MFI may be unreliable → disable MFI On strongly trending instruments, mean-reversion oscillators (Stochastic, RSI) may lag → reduce weight or disable Respect the Collapse Signal Collapse events are early warnings. Price may continue in the original direction for several bars after collapse fires, but the underlying regime has weakened. Best practice: If in profit: Take partial or full profit on collapse If at breakeven/small loss: Exit immediately If collapse occurs shortly after entry: Likely a false ignition; exit to avoid drawdown Collapses do not guarantee immediate reversals—they signal uncertainty . Combine with Volume Analysis If your instrument has reliable volume: Ignitions with expanding volume: Higher conviction Ignitions with declining volume: Weaker, possibly false Collapses with volume spikes: Strong reversal signal Collapses with low volume: May just be consolidation Volume is not built into QRFM (except via MFI), so add it as external confirmation. Observe the Phase Spiral The spiral provides a quick visual cue for rotation consistency: Tight, smooth spiral : Ensemble is rotating coherently (trending) Loose, erratic spiral : Phase is jumping around (ranging or transitional) If the spiral tightens, coherence is building. If it loosens, coherence is dissolving. Do Not Overtrade Low-Coherence Periods When CI is persistently below 40% and the state is "Chaos," the market is not in a regime where phase analysis is predictive. During these times: Reduce position size Widen stops Wait for coherence to return QRFM's strength is regime detection. If there is no regime, the tool correctly signals "stand aside." Use Alerts Strategically Set alerts for: Long Ignition Short Ignition Collapse Phase Lock (optional) Configure alerts to "Once per bar close" to avoid intrabar repainting and noise. When an alert fires, manually verify: Orbit plot shows clustering Dashboard confirms all conditions Price structure supports the trade Do not blindly trade alerts—use them as prompts for analysis. Ideal Market Conditions Best Performance Instruments : Liquid, actively traded markets (major forex pairs, large-cap stocks, major indices, top-tier crypto) Instruments with clear cyclical oscillator behavior (avoid extremely illiquid or manipulated markets) Timeframes : 15-minute to 4-hour: Optimal balance of noise reduction and responsiveness 1-hour to daily: Slower, higher-conviction signals; good for swing trading 5-minute: Acceptable for scalping if parameters are tightened and you accept more noise Market Regimes : Trending markets with periodic retracements (where oscillators cycle through phases predictably) Breakout environments (coherence forms before/during breakout; collapse occurs at exhaustion) Rotational markets with clear swings (oscillators phase-lock at turning points) Volatility : Moderate to high volatility (oscillators have room to move through their ranges) Stable volatility regimes (sudden VIX spikes or flash crashes may create false collapses) Challenging Conditions Instruments : Very low liquidity markets (erratic price action creates unstable oscillator phases) Heavily news-driven instruments (fundamentals may override technical coherence) Highly correlated instruments (oscillators may all reflect the same underlying factor, reducing independence) Market Regimes : Deep, prolonged consolidation (oscillators remain near neutral, CI is chronically low, few signals fire) Extreme chop with no directional bias (oscillators whipsaw, coherence never establishes) Gap-driven markets (large overnight gaps create phase discontinuities) Timeframes : Sub-5-minute charts: Noise dominates; oscillators flip rapidly; coherence is fleeting and unreliable Weekly/monthly: Oscillators move extremely slowly; signals are rare; better suited for long-term positioning than active trading Special Cases : During major economic releases or earnings: Oscillators may lag price or become decorrelated as fundamentals overwhelm technicals. Reduce position size or stand aside. In extremely low-volatility environments (e.g., holiday periods): Oscillators compress to neutral, CI may be artificially high due to lack of movement, but signals lack follow-through. Adaptive Behavior QRFM is designed to self-adapt to poor conditions: When coherence is genuinely absent, CI remains low and signals do not fire When only a subset of oscillators aligns, entangled pairs count stays below threshold and signals are filtered out When phase-lock cannot be achieved (oscillators too scattered), the lock filter prevents signals This means the indicator will naturally produce fewer (or zero) signals during unfavorable conditions, rather than generating false signals. This is a feature —it keeps you out of low-probability trades. Parameter Optimization by Trading Style Scalping (5-15 Minute Charts) Goal : Maximum responsiveness, accept higher noise Oscillator Lengths : RSI: 7-10 MACD: 8/17/6 Stochastic: 8-10, smooth 2-3 CCI: 14-16 Others: 8-12 Coherence Settings : CI Smoothing Window: 2-3 bars (fast reaction) Phase Sample Rate: 1 (every bar) Ignition Threshold: 0.65-0.75 (lower for more signals) Collapse Threshold: 0.40-0.50 (earlier exit warnings) Confirmation : Phase Lock Tolerance: 40-50° (looser, easier to achieve) Min Entangled Pairs: 2-3 (fewer oscillators required) Visuals : Orbit Plot + Dashboard only (reduce screen clutter for fast decisions) Disable heavy visuals (heat map, web) for performance Alerts : Enable all ignition and collapse alerts Set to "Once per bar close" Day Trading (15-Minute to 1-Hour Charts) Goal : Balance between responsiveness and reliability Oscillator Lengths : RSI: 14 (standard) MACD: 12/26/9 (standard) Stochastic: 14, smooth 3 CCI: 20 Others: 10-14 Coherence Settings : CI Smoothing Window: 3-5 bars (balanced) Phase Sample Rate: 2-3 Ignition Threshold: 0.75-0.85 (moderate selectivity) Collapse Threshold: 0.50-0.55 (balanced exit timing) Confirmation : Phase Lock Tolerance: 30-40° (moderate tightness) Min Entangled Pairs: 4-5 (reasonable confirmation) Visuals : Orbit Plot + Dashboard + Heat Map or Web (choose one) Field Cloud for regime backdrop Alerts : Ignition and collapse alerts Optional phase-lock alert for advance warning Swing Trading (4-Hour to Daily Charts) Goal : High-conviction signals, minimal noise, fewer trades Oscillator Lengths : RSI: 14-21 MACD: 12/26/9 or 19/39/9 (longer variant) Stochastic: 14-21, smooth 3-5 CCI: 20-30 Others: 14-20 Coherence Settings : CI Smoothing Window: 5-10 bars (very smooth) Phase Sample Rate: 3-5 Ignition Threshold: 0.80-0.90 (high bar for entry) Collapse Threshold: 0.55-0.65 (only significant breakdowns) Confirmation : Phase Lock Tolerance: 20-30° (tight clustering required) Min Entangled Pairs: 5-7 (strong confirmation) Visuals : All modules enabled (you have time to analyze) Heat Map for multi-bar pattern recognition Web for deep confirmation analysis Alerts : Ignition and collapse Review manually before entering (no rush) Position/Long-Term Trading (Daily to Weekly Charts) Goal : Rare, very high-conviction regime shifts Oscillator Lengths : RSI: 21-30 MACD: 19/39/9 or 26/52/12 Stochastic: 21, smooth 5 CCI: 30-50 Others: 20-30 Coherence Settings : CI Smoothing Window: 10-14 bars Phase Sample Rate: 5 (every 5th bar to reduce computation) Ignition Threshold: 0.85-0.95 (only extreme alignment) Collapse Threshold: 0.60-0.70 (major regime breaks only) Confirmation : Phase Lock Tolerance: 15-25° (very tight) Min Entangled Pairs: 6+ (broad consensus required) Visuals : Dashboard + Orbit Plot for quick checks Heat Map to study historical coherence patterns Web to verify deep entanglement Alerts : Ignition only (collapses are less critical on long timeframes) Manual review with fundamental analysis overlay Performance Optimization (Low-End Systems) If you experience lag or slow rendering: Reduce Visual Load : Orbit Grid Size: 8-10 (instead of 12+) Heat Map Time Bins: 5-8 (instead of 10+) Disable Web Matrix entirely if not needed Disable Field Cloud and Phase Spiral Reduce Calculation Frequency : Phase Sample Rate: 5-10 (calculate every 5-10 bars) Max History Depth: 100-200 (instead of 500+) Disable Unused Oscillators : If you only want RSI, MACD, and Stochastic, disable the other five. Fewer oscillators = smaller matrices, faster loops. Simplify Dashboard : Choose "Small" dashboard size Reduce number of metrics displayed These settings will not significantly degrade signal quality (signals are based on bar-close calculations, which remain accurate), but will improve chart responsiveness. Important Disclaimers This indicator is a technical analysis tool designed to identify periods of phase coherence across an ensemble of oscillators. It is not a standalone trading system and does not guarantee profitable trades. The Coherence Index, dominant phase, and entanglement metrics are mathematical calculations applied to historical price data—they measure past oscillator behavior and do not predict future price movements with certainty. No Predictive Guarantee : High coherence indicates that oscillators are currently aligned, which historically has coincided with trending or directional price movement. However, past alignment does not guarantee future trends. Markets can remain coherent while prices consolidate, or lose coherence suddenly due to news, liquidity changes, or other factors not captured by oscillator mathematics. Signal Confirmation is Probabilistic : The multi-layer confirmation system (CI threshold + dominant phase + phase-lock + entanglement) is designed to filter out low-probability setups. This increases the proportion of valid signals relative to false signals, but does not eliminate false signals entirely. Users should combine QRFM with additional analysis—support and resistance levels, volume confirmation, multi-timeframe alignment, and fundamental context—before executing trades. Collapse Signals are Warnings, Not Reversals : A coherence collapse indicates that the oscillator ensemble has lost alignment. This often precedes trend exhaustion or reversals, but can also occur during healthy pullbacks or consolidations. Price may continue in the original direction after a collapse. Use collapses as risk management cues (tighten stops, take partial profits) rather than automatic reversal entries. Market Regime Dependency : QRFM performs best in markets where oscillators exhibit cyclical, mean-reverting behavior and where trends are punctuated by retracements. In markets dominated by fundamental shocks, gap openings, or extreme low-liquidity conditions, oscillator coherence may be less reliable. During such periods, reduce position size or stand aside. Risk Management is Essential : All trading involves risk of loss. Use appropriate stop losses, position sizing, and risk-per-trade limits. The indicator does not specify stop loss or take profit levels—these must be determined by the user based on their risk tolerance and account size. Never risk more than you can afford to lose. Parameter Sensitivity : The indicator's behavior changes with input parameters. Aggressive settings (low thresholds, loose tolerances) produce more signals with lower average quality. Conservative settings (high thresholds, tight tolerances) produce fewer signals with higher average quality. Users should backtest and forward-test parameter sets on their specific instruments and timeframes before committing real capital. No Repainting by Design : All signal conditions are evaluated on bar close using bar-close values. However, the visual components (orbit plot, heat map, dashboard) update in real-time during bar formation for monitoring purposes. For trade execution, rely on the confirmed signals (triangles and circles) that appear only after the bar closes. Computational Load : QRFM performs extensive calculations, including nested loops for entanglement matrices and real-time table rendering. On lower-powered devices or when running multiple indicators simultaneously, users may experience lag. Use the performance optimization settings (reduce visual complexity, increase phase sample rate, disable unused oscillators) to improve responsiveness. This system is most effective when used as one component within a broader trading methodology that includes sound risk management, multi-timeframe analysis, market context awareness, and disciplined execution. It is a tool for regime detection and signal confirmation, not a substitute for comprehensive trade planning. Technical Notes Calculation Timing : All signal logic (ignition, collapse) is evaluated using bar-close values. The barstate.isconfirmed or implicit bar-close behavior ensures signals do not repaint. Visual components (tables, plots) render on every tick for real-time feedback but do not affect signal generation. Phase Wrapping : Phase angles are calculated in the range -180° to +180° using atan2. Angular distance calculations account for wrapping (e.g., the distance between +170° and -170° is 20°, not 340°). This ensures phase-lock detection works correctly across the ±180° boundary. Array Management : The indicator uses fixed-size arrays for oscillator phases, amplitudes, and the entanglement matrix. The maximum number of oscillators is 8. If fewer oscillators are enabled, array sizes shrink accordingly (only active oscillators are processed). Matrix Indexing : The entanglement matrix is stored as a flat array with size N×N, where N is the number of active oscillators. Index mapping: index(row, col) = row × N + col. Symmetric pairs (i,j) and (j,i) are stored identically. Normalization Stability : Oscillators are normalized to using fixed reference levels (e.g., RSI overbought/oversold at 70/30). For unbounded oscillators (MACD, ROC, TSI), statistical normalization (division by rolling standard deviation) is used, with clamping to prevent extreme outliers from distorting phase calculations. Smoothing and Lag : The CI smoothing window (SMA) introduces lag proportional to the window size. This is intentional—it filters out single-bar noise spikes in coherence. Users requiring faster reaction can reduce the smoothing window to 1-2 bars, at the cost of increased sensitivity to noise. Complex Number Representation : Pine Script does not have native complex number types. Complex arithmetic is implemented using separate real and imaginary accumulators (sum_cos, sum_sin) and manual calculation of magnitude (sqrt(real² + imag²)) and argument (atan2(imag, real)). Lookback Limits : The indicator respects Pine Script's maximum lookback constraints. Historical phase and amplitude values are accessed using the operator, with lookback limited to the chart's available bar history (max_bars_back=5000 declared). Visual Rendering Performance : Tables (orbit plot, heat map, web, dashboard) are conditionally deleted and recreated on each update using table.delete() and table.new(). This prevents memory leaks but incurs redraw overhead. Rendering is restricted to barstate.islast (last bar) to minimize computational load—historical bars do not render visuals. Alert Condition Triggers : alertcondition() functions evaluate on bar close when their boolean conditions transition from false to true. Alerts do not fire repeatedly while a condition remains true (e.g., CI stays above threshold for 10 bars fires only once on the initial cross). Color Gradient Functions : The phaseColor() function maps phase angles to RGB hues using sine waves offset by 120° (red, green, blue channels). This creates a continuous spectrum where -180° to +180° spans the full color wheel. The amplitudeColor() function maps amplitude to grayscale intensity. The coherenceColor() function uses cos(phase) to map contribution to CI (positive = green, negative = red). No External Data Requests : QRFM operates entirely on the chart's symbol and timeframe. It does not use request.security() or access external data sources. All calculations are self-contained, avoiding lookahead bias from higher-timeframe requests. Deterministic Behavior : Given identical input parameters and price data, QRFM produces identical outputs. There are no random elements, probabilistic sampling, or time-of-day dependencies. — Dskyz, Engineering precision. Trading coherence.
مؤشر Pine Script®
من ‎DskyzInvestments‎
8
ATAI Volume analysis with price action V 1.00ATAI Volume Analysis with Price Action 1. Introduction 1.1 Overview ATAI Volume Analysis with Price Action is a composite indicator designed for TradingView. It combines per‑side volume data —that is, how much buying and selling occurs during each bar—with standard price‑structure elements such as swings, trend lines and support/resistance. By blending these elements the script aims to help a trader understand which side is in control, whether a breakout is genuine, when markets are potentially exhausted and where liquidity providers might be active. The indicator is built around TradingView’s up/down volume feed accessed via the TradingView/ta/10 library. The following excerpt from the script illustrates how this feed is configured: import TradingView/ta/10 as tvta // Determine lower timeframe string based on user choice and chart resolution string lower_tf_breakout = use_custom_tf_input ? custom_tf_input : timeframe.isseconds ? "1S" : timeframe.isintraday ? "1" : timeframe.isdaily ? "5" : "60" // Request up/down volume (both positive) = tvta.requestUpAndDownVolume(lower_tf_breakout) Lower‑timeframe selection. If you do not specify a custom lower timeframe, the script chooses a default based on your chart resolution: 1 second for second charts, 1 minute for intraday charts, 5 minutes for daily charts and 60 minutes for anything longer. Smaller intervals provide a more precise view of buyer and seller flow but cover fewer bars. Larger intervals cover more history at the cost of granularity. Tick vs. time bars. Many trading platforms offer a tick / intrabar calculation mode that updates an indicator on every trade rather than only on bar close. Turning on one‑tick calculation will give the most accurate split between buy and sell volume on the current bar, but it typically reduces the amount of historical data available. For the highest fidelity in live trading you can enable this mode; for studying longer histories you might prefer to disable it. When volume data is completely unavailable (some instruments and crypto pairs), all modules that rely on it will remain silent and only the price‑structure backbone will operate. Figure caption, Each panel shows the indicator’s info table for a different volume sampling interval. In the left chart, the parentheses “(5)” beside the buy‑volume figure denote that the script is aggregating volume over five‑minute bars; the center chart uses “(1)” for one‑minute bars; and the right chart uses “(1T)” for a one‑tick interval. These notations tell you which lower timeframe is driving the volume calculations. Shorter intervals such as 1 minute or 1 tick provide finer detail on buyer and seller flow, but they cover fewer bars; longer intervals like five‑minute bars smooth the data and give more history. Figure caption, The values in parentheses inside the info table come directly from the Breakout — Settings. The first row shows the custom lower-timeframe used for volume calculations (e.g., “(1)”, “(5)”, or “(1T)”) 2. Price‑Structure Backbone Even without volume, the indicator draws structural features that underpin all other modules. These features are always on and serve as the reference levels for subsequent calculations. 2.1 What it draws • Pivots: Swing highs and lows are detected using the pivot_left_input and pivot_right_input settings. A pivot high is identified when the high recorded pivot_right_input bars ago exceeds the highs of the preceding pivot_left_input bars and is also higher than (or equal to) the highs of the subsequent pivot_right_input bars; pivot lows follow the inverse logic. The indicator retains only a fixed number of such pivot points per side, as defined by point_count_input, discarding the oldest ones when the limit is exceeded. • Trend lines: For each side, the indicator connects the earliest stored pivot and the most recent pivot (oldest high to newest high, and oldest low to newest low). When a new pivot is added or an old one drops out of the lookback window, the line’s endpoints—and therefore its slope—are recalculated accordingly. • Horizontal support/resistance: The highest high and lowest low within the lookback window defined by length_input are plotted as horizontal dashed lines. These serve as short‑term support and resistance levels. • Ranked labels: If showPivotLabels is enabled the indicator prints labels such as “HH1”, “HH2”, “LL1” and “LL2” near each pivot. The ranking is determined by comparing the price of each stored pivot: HH1 is the highest high, HH2 is the second highest, and so on; LL1 is the lowest low, LL2 is the second lowest. In the case of equal prices the newer pivot gets the better rank. Labels are offset from price using ½ × ATR × label_atr_multiplier, with the ATR length defined by label_atr_len_input. A dotted connector links each label to the candle’s wick. 2.2 Key settings • length_input: Window length for finding the highest and lowest values and for determining trend line endpoints. A larger value considers more history and will generate longer trend lines and S/R levels. • pivot_left_input, pivot_right_input: Strictness of swing confirmation. Higher values require more bars on either side to form a pivot; lower values create more pivots but may include minor swings. • point_count_input: How many pivots are kept in memory on each side. When new pivots exceed this number the oldest ones are discarded. • label_atr_len_input and label_atr_multiplier: Determine how far pivot labels are offset from the bar using ATR. Increasing the multiplier moves labels further away from price. • Styling inputs for trend lines, horizontal lines and labels (color, width and line style). Figure caption, The chart illustrates how the indicator’s price‑structure backbone operates. In this daily example, the script scans for bars where the high (or low) pivot_right_input bars back is higher (or lower) than the preceding pivot_left_input bars and higher or lower than the subsequent pivot_right_input bars; only those bars are marked as pivots. These pivot points are stored and ranked: the highest high is labelled “HH1”, the second‑highest “HH2”, and so on, while lows are marked “LL1”, “LL2”, etc. Each label is offset from the price by half of an ATR‑based distance to keep the chart clear, and a dotted connector links the label to the actual candle. The red diagonal line connects the earliest and latest stored high pivots, and the green line does the same for low pivots; when a new pivot is added or an old one drops out of the lookback window, the end‑points and slopes adjust accordingly. Dashed horizontal lines mark the highest high and lowest low within the current lookback window, providing visual support and resistance levels. Together, these elements form the structural backbone that other modules reference, even when volume data is unavailable. 3. Breakout Module 3.1 Concept This module confirms that a price break beyond a recent high or low is supported by a genuine shift in buying or selling pressure. It requires price to clear the highest high (“HH1”) or lowest low (“LL1”) and, simultaneously, that the winning side shows a significant volume spike, dominance and ranking. Only when all volume and price conditions pass is a breakout labelled. 3.2 Inputs • lookback_break_input : This controls the number of bars used to compute moving averages and percentiles for volume. A larger value smooths the averages and percentiles but makes the indicator respond more slowly. • vol_mult_input : The “spike” multiplier; the current buy or sell volume must be at least this multiple of its moving average over the lookback window to qualify as a breakout. • rank_threshold_input (0–100) : Defines a volume percentile cutoff: the current buyer/seller volume must be in the top (100−threshold)%(100−threshold)% of all volumes within the lookback window. For example, if set to 80, the current volume must be in the top 20 % of the lookback distribution. • ratio_threshold_input (0–1) : Specifies the minimum share of total volume that the buyer (for a bullish breakout) or seller (for bearish) must hold on the current bar; the code also requires that the cumulative buyer volume over the lookback window exceeds the seller volume (and vice versa for bearish cases). • use_custom_tf_input / custom_tf_input : When enabled, these inputs override the automatic choice of lower timeframe for up/down volume; otherwise the script selects a sensible default based on the chart’s timeframe. • Label appearance settings : Separate options control the ATR-based offset length, offset multiplier, label size and colors for bullish and bearish breakout labels, as well as the connector style and width. 3.3 Detection logic 1. Data preparation : Retrieve per‑side volume from the lower timeframe and take absolute values. Build rolling arrays of the last lookback_break_input values to compute simple moving averages (SMAs), cumulative sums and percentile ranks for buy and sell volume. 2. Volume spike: A spike is flagged when the current buy (or, in the bearish case, sell) volume is at least vol_mult_input times its SMA over the lookback window. 3. Dominance test: The buyer’s (or seller’s) share of total volume on the current bar must meet or exceed ratio_threshold_input. In addition, the cumulative sum of buyer volume over the window must exceed the cumulative sum of seller volume for a bullish breakout (and vice versa for bearish). A separate requirement checks the sign of delta: for bullish breakouts delta_breakout must be non‑negative; for bearish breakouts it must be non‑positive. 4. Percentile rank: The current volume must fall within the top (100 – rank_threshold_input) percent of the lookback distribution—ensuring that the spike is unusually large relative to recent history. 5. Price test: For a bullish signal, the closing price must close above the highest pivot (HH1); for a bearish signal, the close must be below the lowest pivot (LL1). 6. Labeling: When all conditions above are satisfied, the indicator prints “Breakout ↑” above the bar (bullish) or “Breakout ↓” below the bar (bearish). Labels are offset using half of an ATR‑based distance and linked to the candle with a dotted connector. Figure caption, (Breakout ↑ example) , On this daily chart, price pushes above the red trendline and the highest prior pivot (HH1). The indicator recognizes this as a valid breakout because the buyer‑side volume on the lower timeframe spikes above its recent moving average and buyers dominate the volume statistics over the lookback period; when combined with a close above HH1, this satisfies the breakout conditions. The “Breakout ↑” label appears above the candle, and the info table highlights that up‑volume is elevated relative to its 11‑bar average, buyer share exceeds the dominance threshold and money‑flow metrics support the move. Figure caption, In this daily example, price breaks below the lowest pivot (LL1) and the lower green trendline. The indicator identifies this as a bearish breakout because sell‑side volume is sharply elevated—about twice its 11‑bar average—and sellers dominate both the bar and the lookback window. With the close falling below LL1, the script triggers a Breakout ↓ label and marks the corresponding row in the info table, which shows strong down volume, negative delta and a seller share comfortably above the dominance threshold. 4. Market Phase Module (Volume Only) 4.1 Concept Not all markets trend; many cycle between periods of accumulation (buying pressure building up), distribution (selling pressure dominating) and neutral behavior. This module classifies the current bar into one of these phases without using ATR , relying solely on buyer and seller volume statistics. It looks at net flows, ratio changes and an OBV‑like cumulative line with dual‑reference (1‑ and 2‑bar) trends. The result is displayed both as on‑chart labels and in a dedicated row of the info table. 4.2 Inputs • phase_period_len: Number of bars over which to compute sums and ratios for phase detection. • phase_ratio_thresh : Minimum buyer share (for accumulation) or minimum seller share (for distribution, derived as 1 − phase_ratio_thresh) of the total volume. • strict_mode: When enabled, both the 1‑bar and 2‑bar changes in each statistic must agree on the direction (strict confirmation); when disabled, only one of the two references needs to agree (looser confirmation). • Color customisation for info table cells and label styling for accumulation and distribution phases, including ATR length, multiplier, label size, colors and connector styles. • show_phase_module: Toggles the entire phase detection subsystem. • show_phase_labels: Controls whether on‑chart labels are drawn when accumulation or distribution is detected. 4.3 Detection logic The module computes three families of statistics over the volume window defined by phase_period_len: 1. Net sum (buyers minus sellers): net_sum_phase = Σ(buy) − Σ(sell). A positive value indicates a predominance of buyers. The code also computes the differences between the current value and the values 1 and 2 bars ago (d_net_1, d_net_2) to derive up/down trends. 2. Buyer ratio: The instantaneous ratio TF_buy_breakout / TF_tot_breakout and the window ratio Σ(buy) / Σ(total). The current ratio must exceed phase_ratio_thresh for accumulation or fall below 1 − phase_ratio_thresh for distribution. The first and second differences of the window ratio (d_ratio_1, d_ratio_2) determine trend direction. 3. OBV‑like cumulative net flow: An on‑balance volume analogue obv_net_phase increments by TF_buy_breakout − TF_sell_breakout each bar. Its differences over the last 1 and 2 bars (d_obv_1, d_obv_2) provide trend clues. The algorithm then combines these signals: • For strict mode , accumulation requires: (a) current ratio ≥ threshold, (b) cumulative ratio ≥ threshold, (c) both ratio differences ≥ 0, (d) net sum differences ≥ 0, and (e) OBV differences ≥ 0. Distribution is the mirror case. • For loose mode , it relaxes the directional tests: either the 1‑ or the 2‑bar difference needs to agree in each category. If all conditions for accumulation are satisfied, the phase is labelled “Accumulation” ; if all conditions for distribution are satisfied, it’s labelled “Distribution” ; otherwise the phase is “Neutral” . 4.4 Outputs • Info table row : Row 8 displays “Market Phase (Vol)” on the left and the detected phase (Accumulation, Distribution or Neutral) on the right. The text colour of both cells matches a user‑selectable palette (typically green for accumulation, red for distribution and grey for neutral). • On‑chart labels : When show_phase_labels is enabled and a phase persists for at least one bar, the module prints a label above the bar ( “Accum” ) or below the bar ( “Dist” ) with a dashed or dotted connector. The label is offset using ATR based on phase_label_atr_len_input and phase_label_multiplier and is styled according to user preferences. Figure caption, The chart displays a red “Dist” label above a particular bar, indicating that the accumulation/distribution module identified a distribution phase at that point. The detection is based on seller dominance: during that bar, the net buyer-minus-seller flow and the OBV‑style cumulative flow were trending down, and the buyer ratio had dropped below the preset threshold. These conditions satisfy the distribution criteria in strict mode. The label is placed above the bar using an ATR‑based offset and a dashed connector. By the time of the current bar in the screenshot, the phase indicator shows “Neutral” in the info table—signaling that neither accumulation nor distribution conditions are currently met—yet the historical “Dist” label remains to mark where the prior distribution phase began. Figure caption, In this example the market phase module has signaled an Accumulation phase. Three bars before the current candle, the algorithm detected a shift toward buyers: up‑volume exceeded its moving average, down‑volume was below average, and the buyer share of total volume climbed above the threshold while the on‑balance net flow and cumulative ratios were trending upwards. The blue “Accum” label anchored below that bar marks the start of the phase; it remains on the chart because successive bars continue to satisfy the accumulation conditions. The info table confirms this: the “Market Phase (Vol)” row still reads Accumulation, and the ratio and sum rows show buyers dominating both on the current bar and across the lookback window. 5. OB/OS Spike Module 5.1 What overbought/oversold means here In many markets, a rapid extension up or down is often followed by a period of consolidation or reversal. The indicator interprets overbought (OB) conditions as abnormally strong selling risk at or after a price rally and oversold (OS) conditions as unusually strong buying risk after a decline. Importantly, these are not direct trade signals; rather they flag areas where caution or contrarian setups may be appropriate. 5.2 Inputs • minHits_obos (1–7): Minimum number of oscillators that must agree on an overbought or oversold condition for a label to print. • syncWin_obos: Length of a small sliding window over which oscillator votes are smoothed by taking the maximum count observed. This helps filter out choppy signals. • Volume spike criteria: kVolRatio_obos (ratio of current volume to its SMA) and zVolThr_obos (Z‑score threshold) across volLen_obos. Either threshold can trigger a spike. • Oscillator toggles and periods: Each of RSI, Stochastic (K and D), Williams %R, CCI, MFI, DeMarker and Stochastic RSI can be independently enabled; their periods are adjustable. • Label appearance: ATR‑based offset, size, colors for OB and OS labels, plus connector style and width. 5.3 Detection logic 1. Directional volume spikes: Volume spikes are computed separately for buyer and seller volumes. A sell volume spike (sellVolSpike) flags a potential OverBought bar, while a buy volume spike (buyVolSpike) flags a potential OverSold bar. A spike occurs when the respective volume exceeds kVolRatio_obos times its simple moving average over the window or when its Z‑score exceeds zVolThr_obos. 2. Oscillator votes: For each enabled oscillator, calculate its overbought and oversold state using standard thresholds (e.g., RSI ≥ 70 for OB and ≤ 30 for OS; Stochastic %K/%D ≥ 80 for OB and ≤ 20 for OS; etc.). Count how many oscillators vote for OB and how many vote for OS. 3. Minimum hits: Apply the smoothing window syncWin_obos to the vote counts using a maximum‑of‑last‑N approach. A candidate bar is only considered if the smoothed OB hit count ≥ minHits_obos (for OverBought) or the smoothed OS hit count ≥ minHits_obos (for OverSold). 4. Tie‑breaking: If both OverBought and OverSold spike conditions are present on the same bar, compare the smoothed hit counts: the side with the higher count is selected; ties default to OverBought. 5. Label printing: When conditions are met, the bar is labelled as “OverBought X/7” above the candle or “OverSold X/7” below it. “X” is the number of oscillators confirming, and the bracket lists the abbreviations of contributing oscillators. Labels are offset from price using half of an ATR‑scaled distance and can optionally include a dotted or dashed connector line. Figure caption, In this chart the overbought/oversold module has flagged an OverSold signal. A sell‑off from the prior highs brought price down to the lower trend‑line, where the bar marked “OverSold 3/7 DeM” appears. This label indicates that on that bar the module detected a buy‑side volume spike and that at least three of the seven enabled oscillators—in this case including the DeMarker—were in oversold territory. The label is printed below the candle with a dotted connector, signaling that the market may be temporarily exhausted on the downside. After this oversold print, price begins to rebound towards the upper red trend‑line and higher pivot levels. Figure caption, This example shows the overbought/oversold module in action. In the left‑hand panel you can see the OB/OS settings where each oscillator (RSI, Stochastic, Williams %R, CCI, MFI, DeMarker and Stochastic RSI) can be enabled or disabled, and the ATR length and label offset multiplier adjusted. On the chart itself, price has pushed up to the descending red trendline and triggered an “OverBought 3/7” label. That means the sell‑side volume spiked relative to its average and three out of the seven enabled oscillators were in overbought territory. The label is offset above the candle by half of an ATR and connected with a dashed line, signaling that upside momentum may be overextended and a pause or pullback could follow. 6. Buyer/Seller Trap Module 6.1 Concept A bull trap occurs when price appears to break above resistance, attracting buyers, but fails to sustain the move and quickly reverses, leaving a long upper wick and trapping late entrants. A bear trap is the opposite: price breaks below support, lures in sellers, then snaps back, leaving a long lower wick and trapping shorts. This module detects such traps by looking for price structure sweeps, order‑flow mismatches and dominance reversals. It uses a scoring system to differentiate risk from confirmed traps. 6.2 Inputs • trap_lookback_len: Window length used to rank extremes and detect sweeps. • trap_wick_threshold: Minimum proportion of a bar’s range that must be wick (upper for bull traps, lower for bear traps) to qualify as a sweep. • trap_score_risk: Minimum aggregated score required to flag a trap risk. (The code defines a trap_score_confirm input, but confirmation is actually based on price reversal rather than a separate score threshold.) • trap_confirm_bars: Maximum number of bars allowed for price to reverse and confirm the trap. If price does not reverse in this window, the risk label will expire or remain unconfirmed. • Label settings: ATR length and multiplier for offsetting, size, colours for risk and confirmed labels, and connector style and width. Separate settings exist for bull and bear traps. • Toggle inputs: show_trap_module and show_trap_labels enable the module and control whether labels are drawn on the chart. 6.3 Scoring logic The module assigns points to several conditions and sums them to determine whether a trap risk is present. For bull traps, the score is built from the following (bear traps mirror the logic with highs and lows swapped): 1. Sweep (2 points): Price trades above the high pivot (HH1) but fails to close above it and leaves a long upper wick at least trap_wick_threshold × range. For bear traps, price dips below the low pivot (LL1), fails to close below and leaves a long lower wick. 2. Close break (1 point): Price closes beyond HH1 or LL1 without leaving a long wick. 3. Candle/delta mismatch (2 points): The candle closes bullish yet the order flow delta is negative or the seller ratio exceeds 50%, indicating hidden supply. Conversely, a bearish close with positive delta or buyer dominance suggests hidden demand. 4. Dominance inversion (2 points): The current bar’s buyer volume has the highest rank in the lookback window while cumulative sums favor sellers, or vice versa. 5. Low‑volume break (1 point): Price crosses the pivot but total volume is below its moving average. The total score for each side is compared to trap_score_risk. If the score is high enough, a “Bull Trap Risk” or “Bear Trap Risk” label is drawn, offset from the candle by half of an ATR‑scaled distance using a dashed outline. If, within trap_confirm_bars, price reverses beyond the opposite level—drops back below the high pivot for bull traps or rises above the low pivot for bear traps—the label is upgraded to a solid “Bull Trap” or “Bear Trap” . In this version of the code, there is no separate score threshold for confirmation: the variable trap_score_confirm is unused; confirmation depends solely on a successful price reversal within the specified number of bars. Figure caption, In this example the trap module has flagged a Bear Trap Risk. Price initially breaks below the most recent low pivot (LL1), but the bar closes back above that level and leaves a long lower wick, suggesting a failed push lower. Combined with a mismatch between the candle direction and the order flow (buyers regain control) and a reversal in volume dominance, the aggregate score exceeds the risk threshold, so a dashed “Bear Trap Risk” label prints beneath the bar. The green and red trend lines mark the current low and high pivot trajectories, while the horizontal dashed lines show the highest and lowest values in the lookback window. If, within the next few bars, price closes decisively above the support, the risk label would upgrade to a solid “Bear Trap” label. Figure caption, In this example the trap module has identified both ends of a price range. Near the highs, price briefly pushes above the descending red trendline and the recent pivot high, but fails to close there and leaves a noticeable upper wick. That combination of a sweep above resistance and order‑flow mismatch generates a Bull Trap Risk label with a dashed outline, warning that the upside break may not hold. At the opposite extreme, price later dips below the green trendline and the labelled low pivot, then quickly snaps back and closes higher. The long lower wick and subsequent price reversal upgrade the previous bear‑trap risk into a confirmed Bear Trap (solid label), indicating that sellers were caught on a false breakdown. Horizontal dashed lines mark the highest high and lowest low of the lookback window, while the red and green diagonals connect the earliest and latest pivot highs and lows to visualize the range. 7. Sharp Move Module 7.1 Concept Markets sometimes display absorption or climax behavior—periods when one side steadily gains the upper hand before price breaks out with a sharp move. This module evaluates several order‑flow and volume conditions to anticipate such moves. Users can choose how many conditions must be met to flag a risk and how many (plus a price break) are required for confirmation. 7.2 Inputs • sharp Lookback: Number of bars in the window used to compute moving averages, sums, percentile ranks and reference levels. • sharpPercentile: Minimum percentile rank for the current side’s volume; the current buy (or sell) volume must be greater than or equal to this percentile of historical volumes over the lookback window. • sharpVolMult: Multiplier used in the volume climax check. The current side’s volume must exceed this multiple of its average to count as a climax. • sharpRatioThr: Minimum dominance ratio (current side’s volume relative to the opposite side) used in both the instant and cumulative dominance checks. • sharpChurnThr: Maximum ratio of a bar’s range to its ATR for absorption/churn detection; lower values indicate more absorption (large volume in a small range). • sharpScoreRisk: Minimum number of conditions that must be true to print a risk label. • sharpScoreConfirm: Minimum number of conditions plus a price break required for confirmation. • sharpCvdThr: Threshold for cumulative delta divergence versus price change (positive for bullish accumulation, negative for bearish distribution). • Label settings: ATR length (sharpATRlen) and multiplier (sharpLabelMult) for positioning labels, label size, colors and connector styles for bullish and bearish sharp moves. • Toggles: enableSharp activates the module; show_sharp_labels controls whether labels are drawn. 7.3 Conditions (six per side) For each side, the indicator computes six boolean conditions and sums them to form a score: 1. Dominance (instant and cumulative): – Instant dominance: current buy volume ≥ sharpRatioThr × current sell volume. – Cumulative dominance: sum of buy volumes over the window ≥ sharpRatioThr × sum of sell volumes (and vice versa for bearish checks). 2. Accumulation/Distribution divergence: Over the lookback window, cumulative delta rises by at least sharpCvdThr while price fails to rise (bullish), or cumulative delta falls by at least sharpCvdThr while price fails to fall (bearish). 3. Volume climax: The current side’s volume is ≥ sharpVolMult × its average and the product of volume and bar range is the highest in the lookback window. 4. Absorption/Churn: The current side’s volume divided by the bar’s range equals the highest value in the window and the bar’s range divided by ATR ≤ sharpChurnThr (indicating large volume within a small range). 5. Percentile rank: The current side’s volume percentile rank is ≥ sharp Percentile. 6. Mirror logic for sellers: The above checks are repeated with buyer and seller roles swapped and the price break levels reversed. Each condition that passes contributes one point to the corresponding side’s score (0 or 1). Risk and confirmation thresholds are then applied to these scores. 7.4 Scoring and labels • Risk: If scoreBull ≥ sharpScoreRisk, a “Sharp ↑ Risk” label is drawn above the bar. If scoreBear ≥ sharpScoreRisk, a “Sharp ↓ Risk” label is drawn below the bar. • Confirmation: A risk label is upgraded to “Sharp ↑” when scoreBull ≥ sharpScoreConfirm and the bar closes above the highest recent pivot (HH1); for bearish cases, confirmation requires scoreBear ≥ sharpScoreConfirm and a close below the lowest pivot (LL1). • Label positioning: Labels are offset from the candle by ATR × sharpLabelMult (full ATR times multiplier), not half, and may include a dashed or dotted connector line if enabled. Figure caption, In this chart both bullish and bearish sharp‑move setups have been flagged. Earlier in the range, a “Sharp ↓ Risk” label appears beneath a candle: the sell‑side score met the risk threshold, signaling that the combination of strong sell volume, dominance and absorption within a narrow range suggested a potential sharp decline. The price did not close below the lower pivot, so this label remains a “risk” and no confirmation occurred. Later, as the market recovered and volume shifted back to the buy side, a “Sharp ↑ Risk” label prints above a candle near the top of the channel. Here, buy‑side dominance, cumulative delta divergence and a volume climax aligned, but price has not yet closed above the upper pivot (HH1), so the alert is still a risk rather than a confirmed sharp‑up move. Figure caption, In this chart a Sharp ↑ label is displayed above a candle, indicating that the sharp move module has confirmed a bullish breakout. Prior bars satisfied the risk threshold — showing buy‑side dominance, positive cumulative delta divergence, a volume climax and strong absorption in a narrow range — and this candle closes above the highest recent pivot, upgrading the earlier “Sharp ↑ Risk” alert to a full Sharp ↑ signal. The green label is offset from the candle with a dashed connector, while the red and green trend lines trace the high and low pivot trajectories and the dashed horizontals mark the highest and lowest values of the lookback window. 8. Market‑Maker / Spread‑Capture Module 8.1 Concept Liquidity providers often “capture the spread” by buying and selling in almost equal amounts within a very narrow price range. These bars can signal temporary congestion before a move or reflect algorithmic activity. This module flags bars where both buyer and seller volumes are high, the price range is only a few ticks and the buy/sell split remains close to 50%. It helps traders spot potential liquidity pockets. 8.2 Inputs • scalpLookback: Window length used to compute volume averages. • scalpVolMult: Multiplier applied to each side’s average volume; both buy and sell volumes must exceed this multiple. • scalpTickCount: Maximum allowed number of ticks in a bar’s range (calculated as (high − low) / minTick). A value of 1 or 2 captures ultra‑small bars; increasing it relaxes the range requirement. • scalpDeltaRatio: Maximum deviation from a perfect 50/50 split. For example, 0.05 means the buyer share must be between 45% and 55%. • Label settings: ATR length, multiplier, size, colors, connector style and width. • Toggles : show_scalp_module and show_scalp_labels to enable the module and its labels. 8.3 Signal When, on the current bar, both TF_buy_breakout and TF_sell_breakout exceed scalpVolMult times their respective averages and (high − low)/minTick ≤ scalpTickCount and the buyer share is within scalpDeltaRatio of 50%, the module prints a “Spread ↔” label above the bar. The label uses the same ATR offset logic as other modules and draws a connector if enabled. Figure caption, In this chart the spread‑capture module has identified a potential liquidity pocket. Buyer and seller volumes both spiked above their recent averages, yet the candle’s range measured only a couple of ticks and the buy/sell split stayed close to 50 %. This combination met the module’s criteria, so it printed a grey “Spread ↔” label above the bar. The red and green trend lines link the earliest and latest high and low pivots, and the dashed horizontals mark the highest high and lowest low within the current lookback window. 9. Money Flow Module 9.1 Concept To translate volume into a monetary measure, this module multiplies each side’s volume by the closing price. It tracks buying and selling system money default currency on a per-bar basis and sums them over a chosen period. The difference between buy and sell currencies (Δ$) shows net inflow or outflow. 9.2 Inputs • mf_period_len_mf: Number of bars used for summing buy and sell dollars. • Label appearance settings: ATR length, multiplier, size, colors for up/down labels, and connector style and width. • Toggles: Use enableMoneyFlowLabel_mf and showMFLabels to control whether the module and its labels are displayed. 9.3 Calculations • Per-bar money: Buy $ = TF_buy_breakout × close; Sell $ = TF_sell_breakout × close. Their difference is Δ$ = Buy $ − Sell $. • Summations: Over mf_period_len_mf bars, compute Σ Buy $, Σ Sell $ and ΣΔ$ using math.sum(). • Info table entries: Rows 9–13 display these values as texts like “↑ USD 1234 (1M)” or “ΣΔ USD −5678 (14)”, with colors reflecting whether buyers or sellers dominate. • Money flow status: If Δ$ is positive the bar is marked “Money flow in” ; if negative, “Money flow out” ; if zero, “Neutral”. The cumulative status is similarly derived from ΣΔ.Labels print at the bar that changes the sign of ΣΔ, offset using ATR × label multiplier and styled per user preferences. Figure caption, The chart illustrates a steady rise toward the highest recent pivot (HH1) with price riding between a rising green trend‑line and a red trend‑line drawn through earlier pivot highs. A green Money flow in label appears above the bar near the top of the channel, signaling that net dollar flow turned positive on this bar: buy‑side dollar volume exceeded sell‑side dollar volume, pushing the cumulative sum ΣΔ$ above zero. In the info table, the “Money flow (bar)” and “Money flow Σ” rows both read In, confirming that the indicator’s money‑flow module has detected an inflow at both bar and aggregate levels, while other modules (pivots, trend lines and support/resistance) remain active to provide structural context. In this example the Money Flow module signals a net outflow. Price has been trending downward: successive high pivots form a falling red trend‑line and the low pivots form a descending green support line. When the latest bar broke below the previous low pivot (LL1), both the bar‑level and cumulative net dollar flow turned negative—selling volume at the close exceeded buying volume and pushed the cumulative Δ$ below zero. The module reacts by printing a red “Money flow out” label beneath the candle; the info table confirms that the “Money flow (bar)” and “Money flow Σ” rows both show Out, indicating sustained dominance of sellers in this period. 10. Info Table 10.1 Purpose When enabled, the Info Table appears in the lower right of your chart. It summarises key values computed by the indicator—such as buy and sell volume, delta, total volume, breakout status, market phase, and money flow—so you can see at a glance which side is dominant and which signals are active. 10.2 Symbols • ↑ / ↓ — Up (↑) denotes buy volume or money; down (↓) denotes sell volume or money. • MA — Moving average. In the table it shows the average value of a series over the lookback period. • Σ (Sigma) — Cumulative sum over the chosen lookback period. • Δ (Delta) — Difference between buy and sell values. • B / S — Buyer and seller share of total volume, expressed as percentages. • Ref. Price — Reference price for breakout calculations, based on the latest pivot. • Status — Indicates whether a breakout condition is currently active (True) or has failed. 10.3 Row definitions 1. Up volume / MA up volume – Displays current buy volume on the lower timeframe and its moving average over the lookback period. 2. Down volume / MA down volume – Shows current sell volume and its moving average; sell values are formatted in red for clarity. 3. Δ / ΣΔ – Lists the difference between buy and sell volume for the current bar and the cumulative delta volume over the lookback period. 4. Σ / MA Σ (Vol/MA) – Total volume (buy + sell) for the bar, with the ratio of this volume to its moving average; the right cell shows the average total volume. 5. B/S ratio – Buy and sell share of the total volume: current bar percentages and the average percentages across the lookback period. 6. Buyer Rank / Seller Rank – Ranks the bar’s buy and sell volumes among the last (n) bars; lower rank numbers indicate higher relative volume. 7. Σ Buy / Σ Sell – Sum of buy and sell volumes over the lookback window, indicating which side has traded more. 8. Breakout UP / DOWN – Shows the breakout thresholds (Ref. Price) and whether the breakout condition is active (True) or has failed. 9. Market Phase (Vol) – Reports the current volume‑only phase: Accumulation, Distribution or Neutral. 10. Money Flow – The final rows display dollar amounts and status: – ↑ USD / Σ↑ USD – Buy dollars for the current bar and the cumulative sum over the money‑flow period. – ↓ USD / Σ↓ USD – Sell dollars and their cumulative sum. – Δ USD / ΣΔ USD – Net dollar difference (buy minus sell) for the bar and cumulatively. – Money flow (bar) – Indicates whether the bar’s net dollar flow is positive (In), negative (Out) or neutral. – Money flow Σ – Shows whether the cumulative net dollar flow across the chosen period is positive, negative or neutral. The chart above shows a sequence of different signals from the indicator. A Bull Trap Risk appears after price briefly pushes above resistance but fails to hold, then a green Accum label identifies an accumulation phase. An upward breakout follows, confirmed by a Money flow in print. Later, a Sharp ↓ Risk warns of a possible sharp downturn; after price dips below support but quickly recovers, a Bear Trap label marks a false breakdown. The highlighted info table in the center summarizes key metrics at that moment, including current and average buy/sell volumes, net delta, total volume versus its moving average, breakout status (up and down), market phase (volume), and bar‑level and cumulative money flow (In/Out). 11. Conclusion & Final Remarks This indicator was developed as a holistic study of market structure and order flow. It brings together several well‑known concepts from technical analysis—breakouts, accumulation and distribution phases, overbought and oversold extremes, bull and bear traps, sharp directional moves, market‑maker spread bars and money flow—into a single Pine Script tool. Each module is based on widely recognized trading ideas and was implemented after consulting reference materials and example strategies, so you can see in real time how these concepts interact on your chart. A distinctive feature of this indicator is its reliance on per‑side volume: instead of tallying only total volume, it separately measures buy and sell transactions on a lower time frame. This approach gives a clearer view of who is in control—buyers or sellers—and helps filter breakouts, detect phases of accumulation or distribution, recognize potential traps, anticipate sharp moves and gauge whether liquidity providers are active. The money‑flow module extends this analysis by converting volume into currency values and tracking net inflow or outflow across a chosen window. Although comprehensive, this indicator is intended solely as a guide. It highlights conditions and statistics that many traders find useful, but it does not generate trading signals or guarantee results. Ultimately, you remain responsible for your positions. Use the information presented here to inform your analysis, combine it with other tools and risk‑management techniques, and always make your own decisions when trading.
مؤشر Pine Script®
من ‎ata_sabanci‎
16
MERV: Market Entropy & Rhythm Visualizer [BullByte]The MERV (Market Entropy & Rhythm Visualizer) indicator analyzes market conditions by measuring entropy (randomness vs. trend), tradeability (volatility/momentum), and cyclical rhythm. It provides traders with an easy-to-read dashboard and oscillator to understand when markets are structured or choppy, and when trading conditions are optimal. Purpose of the Indicator MERV’s goal is to help traders identify different market regimes. It quantifies how structured or random recent price action is (entropy), how strong and volatile the movement is (tradeability), and whether a repeating cycle exists. By visualizing these together, MERV highlights trending vs. choppy environments and flags when conditions are favorable for entering trades. For example, a low entropy value means prices are following a clear trend line, whereas high entropy indicates a lot of noise or sideways action. The indicator’s combination of measures is original: it fuses statistical trend-fit (entropy), volatility trends (ATR and slope), and cycle analysis to give a comprehensive view of market behavior. Why a Trader Should Use It Traders often need to know when a market trend is reliable vs. when it is just noise. MERV helps in several ways: it shows when the market has a strong direction (low entropy, high tradeability) and when it’s ranging (high entropy). This can prevent entering trend-following strategies during choppy periods, or help catch breakouts early. The “Optimal Regime” marker (a star) highlights moments when entropy is very low and tradeability is very high, typically the best conditions for trend trades. By using MERV, a trader gains an empirical “go/no-go” signal based on price history, rather than guessing from price alone. It’s also adaptable: you can apply it to stocks, forex, crypto, etc., on any timeframe. For example, during a bullish phase of a stock, MERV will turn green (Trending Mode) and often show a star, signaling good follow-through. If the market later grinds sideways, MERV will shift to magenta (Choppy Mode), warning you that trend-following is now risky. Why These Components Were Chosen Market Entropy (via R²) : This measures how well recent prices fit a straight line. We compute a linear regression on the last len_entropy bars and calculate R². Entropy = 1 - R², so entropy is low when prices follow a trend (R² near 1) and high when price action is erratic (R² near 0). This single number captures trend strength vs noise. Tradeability (ATR + Slope) : We combine two familiar measures: the Average True Range (ATR) (normalized by price) and the absolute slope of the regression line (scaled by ATR). Together they reflect how active and directional the market is. A high ATR or strong slope means big moves, making a trend more “tradeable.” We take a simple average of the normalized ATR and slope to get tradeability_raw. Then we convert it to a percentile rank over the lookback window so it’s stable between 0 and 1. Percentile Ranks : To make entropy and tradeability values easy to interpret, we convert each to a 0–100 rank based on the past len_entropy periods. This turns raw metrics into a consistent scale. (For example, an entropy rank of 90 means current entropy is higher than 90% of recent values.) We then divide by 100 to plot them on a 0–1 scale. Market Mode (Regime) : Based on those ranks, MERV classifies the market: Trending (Green) : Low entropy rank (<40%) and high tradeability rank (>60%). This means the market is structurally trending with high activity. Choppy (Magenta) : High entropy rank (>60%) and low tradeability rank (<40%). This is a mostly random, low-momentum market. Neutral (Cyan) : All other cases. This covers mixed regimes not strongly trending or choppy. The mode is shown as a colored bar at the bottom: green for trending, magenta for choppy, cyan for neutral. Optimal Regime Signal : Separately, we mark an “optimal” condition when entropy_norm < 0.3 and tradeability > 0.7 (both normalized 0–1). When this is true, a ★ star appears on the bottom line. This star is colored white when truly optimal, gold when only tradeability is high (but entropy not quite low enough), and black when neither condition holds. This gives a quick visual cue for very favorable conditions. What Makes MERV Stand Out Holistic View : Unlike a single-oscillator, MERV combines trend, volatility, and cycle analysis in one tool. This multi-faceted approach is unique. Visual Dashboard : The fixed on-chart dashboard (shown at your chosen corner) summarizes all metrics in bar/gauge form. Even a non-technical user can glance at it: more “█” blocks = a higher value, colors match the plots. This is more intuitive than raw numbers. Adaptive Thresholds : Using percentile ranks means MERV auto-adjusts to each market’s character, rather than requiring fixed thresholds. Cycle Insight : The rhythm plot adds information rarely found in indicators – it shows if there’s a repeating cycle (and its period in bars) and how strong it is. This can hint at natural bounce or reversal intervals. Modern Look : The neon color scheme and glow effects make the lines easy to distinguish (blue/pink for entropy, green/orange for tradeability, etc.) and the filled area between them highlights when one dominates the other. Recommended Timeframes MERV can be applied to any timeframe, but it will be more reliable on higher timeframes. The default len_entropy = 50 and len_rhythm = 30 mean we use 30–50 bars of history, so on a daily chart that’s ~2–3 months of data; on a 1-hour chart it’s about 2–3 days. In practice: Swing/Position traders might prefer Daily or 4H charts, where the calculations smooth out small noise. Entropy and cycles are more meaningful on longer trends. Day trader s could use 15m or 1H charts if they adjust the inputs (e.g. shorter windows). This provides more sensitivity to intraday cycles. Scalpers might find MERV too “slow” unless input lengths are set very low. In summary, the indicator works anywhere, but the defaults are tuned for capturing medium-term trends. Users can adjust len_entropy and len_rhythm to match their chart’s volatility. The dashboard position can also be moved (top-left, bottom-right, etc.) so it doesn’t cover important chart areas. How the Scoring/Logic Works (Step-by-Step) Compute Entropy : A linear regression line is fit to the last len_entropy closes. We compute R² (goodness of fit). Entropy = 1 – R². So a strong straight-line trend gives low entropy; a flat/noisy set of points gives high entropy. Compute Tradeability : We get ATR over len_entropy bars, normalize it by price (so it’s a fraction of price). We also calculate the regression slope (difference between the predicted close and last close). We scale |slope| by ATR to get a dimensionless measure. We average these (ATR% and slope%) to get tradeability_raw. This represents how big and directional price moves are. Convert to Percentiles : Each new entropy and tradeability value is inserted into a rolling array of the last 50 values. We then compute the percentile rank of the current value in that array (0–100%) using a simple loop. This tells us where the current bar stands relative to history. We then divide by 100 to plot on . Determine Modes and Signal : Based on these normalized metrics: if entropy < 0.4 and tradeability > 0.6 (40% and 60% thresholds), we set mode = Trending (1). If entropy > 0.6 and tradeability < 0.4, mode = Choppy (-1). Otherwise mode = Neutral (0). Separately, if entropy_norm < 0.3 and tradeability > 0.7, we set an optimal flag. These conditions trigger the colored mode bars and the star line. Rhythm Detection : Every bar, if we have enough data, we take the last len_rhythm closes and compute the mean and standard deviation. Then for lags from 5 up to len_rhythm, we calculate a normalized autocorrelation coefficient. We track the lag that gives the maximum correlation (best match). This “best lag” divided by len_rhythm is plotted (a value between 0 and 1). Its color changes with the correlation strength. We also smooth the best correlation value over 5 bars to plot as “Cycle Strength” (also 0 to 1). This shows if there is a consistent cycle length in recent price action. Heatmap (Optional) : The background color behind the oscillator panel can change with entropy. If “Neon Rainbow” style is on, low entropy is blue and high entropy is pink (via a custom color function), otherwise a classic green-to-red gradient can be used. This visually reinforces the entropy value. Volume Regime (Dashboard Only) : We compute vol_norm = volume / sma(volume, len_entropy). If this is above 1.5, it’s considered high volume (neon orange); below 0.7 is low (blue); otherwise normal (green). The dashboard shows this as a bar gauge and percentage. This is for context only. Oscillator Plot – How to Read It The main panel (oscillator) has multiple colored lines on a 0–1 vertical scale, with horizontal markers at 0.2 (Low), 0.5 (Mid), and 0.8 (High). Here’s each element: Entropy Line (Blue→Pink) : This line (and its glow) shows normalized entropy (0 = very low, 1 = very high). It is blue/green when entropy is low (strong trend) and pink/purple when entropy is high (choppy). A value near 0.0 (below 0.2 line) indicates a very well-defined trend. A value near 1.0 (above 0.8 line) means the market is very random. Watch for it dipping near 0: that suggests a strong trend has formed. Tradeability Line (Green→Yellow) : This represents normalized tradeability. It is colored bright green when tradeability is low, transitioning to yellow as tradeability increases. Higher values (approaching 1) mean big moves and strong slopes. Typically in a market rally or crash, this line will rise. A crossing above ~0.7 often coincides with good trend strength. Filled Area (Orange Shade) : The orange-ish fill between the entropy and tradeability lines highlights when one dominates the other. If the area is large, the two metrics diverge; if small, they are similar. This is mostly aesthetic but can catch the eye when the lines cross over or remain close. Rhythm (Cycle) Line : This is plotted as (best_lag / len_rhythm). It indicates the relative period of the strongest cycle. For example, a value of 0.5 means the strongest cycle was about half the window length. The line’s color (green, orange, or pink) reflects how strong that cycle is (green = strong). If no clear cycle is found, this line may be flat or near zero. Cycle Strength Line : Plotted on the same scale, this shows the autocorrelation strength (0–1). A high value (e.g. above 0.7, shown in green) means the cycle is very pronounced. Low values (pink) mean any cycle is weak and unreliable. Mode Bars (Bottom) : Below the main oscillator, thick colored bars appear: a green bar means Trending Mode, magenta means Choppy Mode, and cyan means Neutral. These bars all have a fixed height (–0.1) and make it very easy to see the current regime. Optimal Regime Line (Bottom) : Just below the mode bars is a thick horizontal line at –0.18. Its color indicates regime quality: White (★) means “Optimal Regime” (very low entropy and high tradeability). Gold (★) means not quite optimal (high tradeability but entropy not low enough). Black means neither condition. This star line quickly tells you when conditions are ideal (white star) or simply good (gold star). Horizontal Guides : The dotted lines at 0.2 (Low), 0.5 (Mid), and 0.8 (High) serve as reference lines. For example, an entropy or tradeability reading above 0.8 is “High,” and below 0.2 is “Low,” as labeled on the chart. These help you gauge values at a glance. Dashboard (Fixed Corner Panel) MERV also includes a compact table (dashboard) that can be positioned in any corner. It summarizes key values each bar. Here is how to read its rows: Entropy : Shows a bar of blocks (█ and ░). More █ blocks = higher entropy. It also gives a percentage (rounded). A full bar (10 blocks) with a high % means very chaotic market. The text is colored similarly (blue-green for low, pink for high). Rhythm : Shows the best cycle period in bars (e.g. “15 bars”). If no calculation yet, it shows “n/a.” The text color matches the rhythm line. Cycle Strength : Gives the cycle correlation as a percentage (smoothed, as shown on chart). Higher % (green) means a strong cycle. Tradeability : Displays a 10-block gauge for tradeability. More blocks = more tradeable market. It also shows “gauge” text colored green→yellow accordingly. Market Mode : Simply shows “Trending”, “Choppy”, or “Neutral” (cyan text) to match the mode bar color. Volume Regime : Similar to tradeability, shows blocks for current volume vs. average. Above-average volume gives orange blocks, below-average gives blue blocks. A % value indicates current volume relative to average. This row helps see if volume is abnormally high or low. Optimal Status (Large Row) : In bold, either “★ Optimal Regime” (white text) if the star condition is met, “★ High Tradeability” (gold text) if tradeability alone is high, or “— Not Optimal” (gray text) otherwise. This large row catches your eye when conditions are ripe. In short, the dashboard turns the numeric state into an easy read: filled bars, colors, and text let you see current conditions without reading the plot. For instance, five blue blocks under Entropy and “25%” tells you entropy is low (good), and a row showing “Trending” in green confirms a trend state. Real-Life Example Example : Consider a daily chart of a trending stock (e.g. “AAPL, 1D”). During a strong uptrend, recent prices fit a clear upward line, so Entropy would be low (blue line near bottom, perhaps below the 0.2 line). Volatility and slope are high, so Tradeability is high (green-yellow line near top). In the dashboard, Entropy might show only 1–2 blocks (e.g. 10%) and Tradeability nearly full (e.g. 90%). The Market Mode bar turns green (Trending), and you might see a white ★ on the optimal line if conditions are very good. The Volume row might light orange if volume is above average during the rally. In contrast, imagine the same stock later in a tight range: Entropy will rise (pink line up, more blocks in dashboard), Tradeability falls (fewer blocks), and the Mode bar turns magenta (Choppy). No star appears in that case. Consolidated Use Case : Suppose on XYZ stock the dashboard reads “Entropy: █░░░░░░░░ 20%”, “Tradeability: ██████████ 80%”, Mode = Trending (green), and “★ Optimal Regime.” This tells the trader that the market is in a strong, low-noise trend, and it might be a good time to follow the trend (with appropriate risk controls). If instead it reads “Entropy: ████████░░ 80%”, “Tradeability: ███▒▒▒▒▒▒ 30%”, Mode = Choppy (magenta), the trader knows the market is random and low-momentum—likely best to sit out until conditions improve. Example: How It Looks in Action Screenshot 1: Trending Market with High Tradeability (SOLUSD, 30m) What it means: The market is in a clear, strong trend with excellent conditions for trading. Both trend-following and active strategies are favored, supported by high tradeability and strong volume. Screenshot 2: Optimal Regime, Strong Trend (ETHUSD, 1h) What it means: This is an ideal environment for trend trading. The market is highly organized, tradeability is excellent, and volume supports the move. This is when the indicator signals the highest probability for success. Screenshot 3: Choppy Market with High Volume (BTC Perpetual, 5m) What it means: The market is highly random and choppy, despite a surge in volume. This is a high-risk, low-reward environment, avoid trend strategies, and be cautious even with mean-reversion or scalping. Settings and Inputs The script is fully open-source; here are key inputs the user can adjust: Entropy Window (len_entropy) : Number of bars used for entropy and tradeability (default 50). Larger = smoother, more lag; smaller = more sensitivity. Rhythm Window (len_rhythm ): Bars used for cycle detection (default 30). This limits the longest cycle we detect. Dashboard Position : Choose any corner (Top Right default) so it doesn’t cover chart action. Show Heatmap : Toggles the entropy background coloring on/off. Heatmap Style : “Neon Rainbow” (colorful) or “Classic” (green→red). Show Mode Bar : Turn the bottom mode bar on/off. Show Dashboard : Turn the fixed table panel on/off. Each setting has a tooltip explaining its effect. In the description we will mention typical settings (e.g. default window sizes) and that the user can move the dashboard corner as desired. Oscillator Interpretation (Recap) Lines : Blue/Pink = Entropy (low=trend, high=chop); Green/Yellow = Tradeability (low=quiet, high=volatile). Fill : Orange tinted area between them (for visual emphasis). Bars : Green=Trending, Magenta=Choppy, Cyan=Neutral (at bottom). Star Line : White star = ideal conditions, Gold = good but not ideal. Horizontal Guides : 0.2 and 0.8 lines mark low/high thresholds for each metric. Using the chart, a coder or trader can see exactly what each output represents and make decisions accordingly. Disclaimer This indicator is provided as-is for educational and analytical purposes only. It does not guarantee any particular trading outcome. Past market patterns may not repeat in the future. Users should apply their own judgment and risk management; do not rely solely on this tool for trading decisions. Remember, TradingView scripts are tools for market analysis, not personalized financial advice. We encourage users to test and combine MERV with other analysis and to trade responsibly. -BullByte
مؤشر Pine Script®
من ‎BullByte‎
6
Market Zone Analyzer[BullByte]Understanding the Market Zone Analyzer --- 1. Purpose of the Indicator The Market Zone Analyzer is a Pine Script™ (version 6) indicator designed to streamline market analysis on TradingView. Rather than scanning multiple separate tools, it unifies four core dimensions—trend strength, momentum, price action, and market activity—into a single, consolidated view. By doing so, it helps traders: • Save time by avoiding manual cross-referencing of disparate signals. • Reduce decision-making errors that can arise from juggling multiple indicators. • Gain a clear, reliable read on whether the market is in a bullish, bearish, or sideways phase, so they can more confidently decide to enter, exit, or hold a position. --- 2. Why a Trader Should Use It • Unified View: Combines all essential market dimensions into one easy-to-read score and dashboard, eliminating the need to piece together signals manually. • Adaptability: Automatically adjusts its internal weighting for trend, momentum, and price action based on current volatility. Whether markets are choppy or calm, the indicator remains relevant. • Ease of Interpretation: Outputs a simple “BULLISH,” “BEARISH,” or “SIDEWAYS” label, supplemented by an intuitive on-chart dashboard and an oscillator plot that visually highlights market direction. • Reliability Features: Built-in smoothing of the net score and hysteresis logic (requiring consecutive confirmations before flips) minimize false signals during noisy or range-bound phases. --- 3. Why These Specific Indicators? This script relies on a curated set of well-established technical tools, each chosen for its particular strength in measuring one of the four core dimensions: 1. Trend Strength: • ADX/DMI (Average Directional Index / Directional Movement Index): Measures how strong a trend is, and whether the +DI line is above the –DI line (bullish) or vice versa (bearish). • Moving Average Slope (Fast MA vs. Slow MA): Compares a shorter-period SMA to a longer-period SMA; if the fast MA sits above the slow MA, it confirms an uptrend, and vice versa for a downtrend. • Ichimoku Cloud Differential (Senkou A vs. Senkou B): Provides a forward-looking view of trend direction; Senkou A above Senkou B signals bullishness, and the opposite signals bearishness. 2. Momentum: • Relative Strength Index (RSI): Identifies overbought (above its dynamically calculated upper bound) or oversold (below its lower bound) conditions; changes in RSI often precede price reversals. • Stochastic %K: Highlights shifts in short-term momentum by comparing closing price to the recent high/low range; values above its upper band signal bullish momentum, below its lower band signal bearish momentum. • MACD Histogram: Measures the difference between the MACD line and its signal line; a positive histogram indicates upward momentum, a negative histogram indicates downward momentum. 3. Price Action: • Highest High / Lowest Low (HH/LL) Range: Over a defined lookback period, this captures breakout or breakdown levels. A closing price near the recent highs (with a positive MA slope) yields a bullish score, and near the lows (with a negative MA slope) yields a bearish score. • Heikin-Ashi Doji Detection: Uses Heikin-Ashi candles to identify indecision or continuation patterns. A small Heikin-Ashi body (doji) relative to recent volatility is scored as neutral; a larger body in the direction of the MA slope is scored bullish or bearish. • Candle Range Measurement: Compares each candle’s high-low range against its own dynamic band (average range ± standard deviation). Large candles aligning with the prevailing trend score bullish or bearish accordingly; unusually small candles can indicate exhaustion or consolidation. 4. Market Activity: • Bollinger Bands Width (BBW): Measures the distance between BB upper and lower bands; wide bands indicate high volatility, narrow bands indicate low volatility. • Average True Range (ATR): Quantifies average price movement (volatility). A sudden spike in ATR suggests a volatile environment, while a contraction suggests calm. • Keltner Channels Width (KCW): Similar to BBW but uses ATR around an EMA. Provides a second layer of volatility context, confirming or contrasting BBW readings. • Volume (with Moving Average): Compares current volume to its moving average ± standard deviation. High volume validates strong moves; low volume signals potential lack of conviction. By combining these tools, the indicator captures trend direction, momentum strength, price-action nuances, and overall market energy, yielding a more balanced and comprehensive assessment than any single tool alone. --- 4. What Makes This Indicator Stand Out • Multi-Dimensional Analysis: Rather than relying on a lone oscillator or moving average crossover, it simultaneously evaluates trend, momentum, price action, and activity. • Dynamic Weighting: The relative importance of trend, momentum, and price action adjusts automatically based on real-time volatility (Market Activity State). For example, in highly volatile conditions, trend and momentum signals carry more weight; in calm markets, price action signals are prioritized. • Stability Mechanisms: • Smoothing: The net score is passed through a short moving average, filtering out noise, especially on lower timeframes. • Hysteresis: Both Market Activity State and the final bullish/bearish/sideways zone require two consecutive confirmations before flipping, reducing whipsaw. • Visual Interpretation: A fully customizable on-chart dashboard displays each sub-indicator’s value, regime, score, and comment, all color-coded. The oscillator plot changes color to reflect the current market zone (green for bullish, red for bearish, gray for sideways) and shows horizontal threshold lines at +2, 0, and –2. --- 5. Recommended Timeframes • Short-Term (5 min, 15 min): Day traders and scalpers can benefit from rapid signals, but should enable smoothing (and possibly disable hysteresis) to reduce false whipsaws. • Medium-Term (1 h, 4 h): Swing traders find a balance between responsiveness and reliability. Less smoothing is required here, and the default parameters (e.g., ADX length = 14, RSI length = 14) perform well. • Long-Term (Daily, Weekly): Position traders tracking major trends can disable smoothing for immediate raw readings, since higher-timeframe noise is minimal. Adjust lookback lengths (e.g., increase adxLength, rsiLength) if desired for slower signals. Tip: If you keep smoothing off, stick to timeframes of 1 h or higher to avoid excessive signal “chatter.” --- 6. How Scoring Works A. Individual Indicator Scores Each sub-indicator is assigned one of three discrete scores: • +1 if it indicates a bullish condition (e.g., RSI above its dynamically calculated upper bound). • 0 if it is neutral (e.g., RSI between upper and lower bounds). • –1 if it indicates a bearish condition (e.g., RSI below its dynamically calculated lower bound). Examples of individual score assignments: • ADX/DMI: • +1 if ADX ≥ adxThreshold and +DI > –DI (strong bullish trend) • –1 if ADX ≥ adxThreshold and –DI > +DI (strong bearish trend) • 0 if ADX < adxThreshold (trend strength below threshold) • RSI: • +1 if RSI > RSI_upperBound • –1 if RSI < RSI_lowerBound • 0 otherwise • ATR (as part of Market Activity): • +1 if ATR > (ATR_MA + stdev(ATR)) • –1 if ATR < (ATR_MA – stdev(ATR)) • 0 otherwise Each of the four main categories shares this same +1/0/–1 logic across their sub-components. B. Category Scores Once each sub-indicator reports +1, 0, or –1, these are summed within their categories as follows: • Trend Score = (ADX score) + (MA slope score) + (Ichimoku differential score) • Momentum Score = (RSI score) + (Stochastic %K score) + (MACD histogram score) • Price Action Score = (Highest-High/Lowest-Low score) + (Heikin-Ashi doji score) + (Candle range score) • Market Activity Raw Score = (BBW score) + (ATR score) + (KC width score) + (Volume score) Each category’s summed value can range between –3 and +3 (for Trend, Momentum, and Price Action), and between –4 and +4 for Market Activity raw. C. Market Activity State and Dynamic Weight Adjustments Rather than contributing directly to the netScore like the other three categories, Market Activity determines how much weight to assign to Trend, Momentum, and Price Action: 1. Compute Market Activity Raw Score by summing BBW, ATR, KCW, and Volume individual scores (each +1/0/–1). 2. Bucket into High, Medium, or Low Activity: • High if raw Score ≥ 2 (volatile market). • Low if raw Score ≤ –2 (calm market). • Medium otherwise. 3. Apply Hysteresis (if enabled): The state only flips after two consecutive bars register the same high/low/medium label. 4. Set Category Weights: • High Activity: Trend = 50 %, Momentum = 35 %, Price Action = 15 %. • Low Activity: Trend = 25 %, Momentum = 20 %, Price Action = 55 %. • Medium Activity: Use the trader’s base weight inputs (e.g., Trend = 40 %, Momentum = 30 %, Price Action = 30 % by default). D. Calculating the Net Score 5. Normalize Base Weights (so that the sum of Trend + Momentum + Price Action always equals 100 %). 6. Determine Current Weights based on the Market Activity State (High/Medium/Low). 7. Compute Each Category’s Contribution: Multiply (categoryScore) × (currentWeight). 8. Sum Contributions to get the raw netScore (a floating-point value that can exceed ±3 when scores are strong). 9. Smooth the netScore over two bars (if smoothing is enabled) to reduce noise. 10. Apply Hysteresis to the Final Zone: • If the smoothed netScore ≥ +2, the bar is classified as “Bullish.” • If the smoothed netScore ≤ –2, the bar is classified as “Bearish.” • Otherwise, it is “Sideways.” • To prevent rapid flips, the script requires two consecutive bars in the new zone before officially changing the displayed zone (if hysteresis is on). E. Thresholds for Zone Classification • BULLISH: netScore ≥ +2 • BEARISH: netScore ≤ –2 • SIDEWAYS: –2 < netScore < +2 --- 7. Role of Volatility (Market Activity State) in Scoring Volatility acts as a dynamic switch that shifts which category carries the most influence: 1. High Activity (Volatile): • Detected when at least two sub-scores out of BBW, ATR, KCW, and Volume equal +1. • The script sets Trend weight = 50 % and Momentum weight = 35 %. Price Action weight is minimized at 15 %. • Rationale: In volatile markets, strong trending moves and momentum surges dominate, so those signals are more reliable than nuanced candle patterns. 2. Low Activity (Calm): • Detected when at least two sub-scores out of BBW, ATR, KCW, and Volume equal –1. • The script sets Price Action weight = 55 %, Trend = 25 %, and Momentum = 20 %. • Rationale: In quiet, sideways markets, subtle price-action signals (breakouts, doji patterns, small-range candles) are often the best early indicators of a new move. 3. Medium Activity (Balanced): • Raw Score between –1 and +1 from the four volatility metrics. • Uses whatever base weights the trader has specified (e.g., Trend = 40 %, Momentum = 30 %, Price Action = 30 %). Because volatility can fluctuate rapidly, the script employs hysteresis on Market Activity State: a new High or Low state must occur on two consecutive bars before weights actually shift. This avoids constant back-and-forth weight changes and provides more stability. --- 8. Scoring Example (Hypothetical Scenario) • Symbol: Bitcoin on a 1-hour chart. • Market Activity: Raw volatility sub-scores show BBW (+1), ATR (+1), KCW (0), Volume (+1) → Total raw Score = +3 → High Activity. • Weights Selected: Trend = 50 %, Momentum = 35 %, Price Action = 15 %. • Trend Signals: • ADX strong and +DI > –DI → +1 • Fast MA above Slow MA → +1 • Ichimoku Senkou A > Senkou B → +1 → Trend Score = +3 • Momentum Signals: • RSI above upper bound → +1 • MACD histogram positive → +1 • Stochastic %K within neutral zone → 0 → Momentum Score = +2 • Price Action Signals: • Highest High/Lowest Low check yields 0 (close not near extremes) • Heikin-Ashi doji reading is neutral → 0 • Candle range slightly above upper bound but trend is strong, so → +1 → Price Action Score = +1 • Compute Net Score (before smoothing): • Trend contribution = 3 × 0.50 = 1.50 • Momentum contribution = 2 × 0.35 = 0.70 • Price Action contribution = 1 × 0.15 = 0.15 • Raw netScore = 1.50 + 0.70 + 0.15 = 2.35 • Since 2.35 ≥ +2 and hysteresis is met, the final zone is “Bullish.” Although the netScore lands at 2.35 (Bullish), smoothing might bring it slightly below 2.00 on the first bar (e.g., 1.90), in which case the script would wait for a second consecutive reading above +2 before officially classifying the zone as Bullish (if hysteresis is enabled). --- 9. Correlation Between Categories The four categories—Trend Strength, Momentum, Price Action, and Market Activity—often reinforce or offset one another. The script takes advantage of these natural correlations: • Bullish Alignment: If ADX is strong and pointed upward, fast MA is above slow MA, and Ichimoku is positive, that usually coincides with RSI climbing above its upper bound and the MACD histogram turning positive. In such cases, both Trend and Momentum categories generate +1 or +2. Because the Market Activity State is likely High (given the accompanying volatility), Trend and Momentum weights are at their peak, so the netScore quickly crosses into Bullish territory. • Sideways/Consolidation: During a low-volatility, sideways phase, ADX may fall below its threshold, MAs may flatten, and RSI might hover in the neutral band. However, subtle price-action signals (like a small breakout candle or a Heikin-Ashi candle with a slight bias) can still produce a +1 in the Price Action category. If Market Activity is Low, Price Action’s weight (55 %) can carry enough influence—even if Trend and Momentum are neutral—to push the netScore out of “Sideways” into a mild bullish or bearish bias. • Opposing Signals: When Trend is bullish but Momentum turns negative (for example, price continues up but RSI rolls over), the two scores can partially cancel. Market Activity may remain Medium, in which case the netScore lingers near zero (Sideways). The trader can then wait for either a clearer momentum shift or a fresh price-action breakout before committing. By dynamically recognizing these correlations and adjusting weights, the indicator ensures that: • When Trend and Momentum align (and volatility supports it), the netScore leaps strongly into Bullish or Bearish. • When Trend is neutral but Price Action shows an early move in a low-volatility environment, Price Action’s extra weight in the Low Activity State can still produce actionable signals. --- 10. Market Activity State & Its Role (Detailed) The Market Activity State is not a direct category score—it is an overarching context setter for how heavily to trust Trend, Momentum, or Price Action. Here’s how it is derived and applied: 1. Calculate Four Volatility Sub-Scores: • BBW: Compare the current band width to its own moving average ± standard deviation. If BBW > (BBW_MA + stdev), assign +1 (high volatility); if BBW < (BBW_MA × 0.5), assign –1 (low volatility); else 0. • ATR: Compare ATR to its moving average ± standard deviation. A spike above the upper threshold is +1; a contraction below the lower threshold is –1; otherwise 0. • KCW: Same logic as ATR but around the KCW mean. • Volume: Compare current volume to its volume MA ± standard deviation. Above the upper threshold is +1; below the lower threshold is –1; else 0. 2. Sum Sub-Scores → Raw Market Activity Score: Range between –4 and +4. 3. Assign Market Activity State: • High Activity: Raw Score ≥ +2 (at least two volatility metrics are strongly spiking). • Low Activity: Raw Score ≤ –2 (at least two metrics signal unusually low volatility or thin volume). • Medium Activity: Raw Score is between –1 and +1 inclusive. 4. Hysteresis for Stability: • If hysteresis is enabled, a new state only takes hold after two consecutive bars confirm the same High, Medium, or Low label. • This prevents the Market Activity State from bouncing around when volatility is on the fence. 5. Set Category Weights Based on Activity State: • High Activity: Trend = 50 %, Momentum = 35 %, Price Action = 15 %. • Low Activity: Trend = 25 %, Momentum = 20 %, Price Action = 55 %. • Medium Activity: Use trader’s base weights (e.g., Trend = 40 %, Momentum = 30 %, Price Action = 30 %). 6. Impact on netScore: Because category scores (–3 to +3) multiply by these weights, High Activity amplifies the effect of strong Trend and Momentum scores; Low Activity amplifies the effect of Price Action. 7. Market Context Tooltip: The dashboard includes a tooltip summarizing the current state—e.g., “High activity, trend and momentum prioritized,” “Low activity, price action prioritized,” or “Balanced market, all categories considered.” --- 11. Category Weights: Base vs. Dynamic Traders begin by specifying base weights for Trend Strength, Momentum, and Price Action that sum to 100 %. These apply only when volatility is in the Medium band. Once volatility shifts: • High Volatility Overrides: • Trend jumps from its base (e.g., 40 %) to 50 %. • Momentum jumps from its base (e.g., 30 %) to 35 %. • Price Action is reduced to 15 %. Example: If base weights were Trend = 40 %, Momentum = 30 %, Price Action = 30 %, then in High Activity they become 50/35/15. A Trend score of +3 now contributes 3 × 0.50 = +1.50 to netScore; a Momentum +2 contributes 2 × 0.35 = +0.70. In total, Trend + Momentum can easily push netScore above the +2 threshold on its own. • Low Volatility Overrides: • Price Action leaps from its base (30 %) to 55 %. • Trend falls to 25 %, Momentum falls to 20 %. Why? When markets are quiet, subtle candle breakouts, doji patterns, and small-range expansions tend to foreshadow the next swing more effectively than raw trend readings. A Price Action score of +3 in this state contributes 3 × 0.55 = +1.65, which can carry the netScore toward +2—even if Trend and Momentum are neutral or only mildly positive. Because these weight shifts happen only after two consecutive bars confirm a High or Low state (if hysteresis is on), the indicator avoids constantly flipping its emphasis during borderline volatility phases. --- 12. Dominant Category Explained Within the dashboard, a label such as “Trend Dominant,” “Momentum Dominant,” or “Price Action Dominant” appears when one category’s absolute weighted contribution to netScore is the largest. Concretely: • Compute each category’s weighted contribution = (raw category score) × (current weight). • Compare the absolute values of those three contributions. • The category with the highest absolute value is flagged as Dominant for that bar. Why It Matters: • Momentum Dominant: Indicates that the combined force of RSI, Stochastic, and MACD (after weighting) is pushing netScore farther than either Trend or Price Action. In practice, it means that short-term sentiment and speed of change are the primary drivers right now, so traders should watch for continued momentum signals before committing to a trade. • Trend Dominant: Means ADX, MA slope, and Ichimoku (once weighted) outweigh the other categories. This suggests a strong directional move is in place; trend-following entries or confirming pullbacks are likely to succeed. • Price Action Dominant: Occurs when breakout/breakdown patterns, Heikin-Ashi candle readings, and range expansions (after weighting) are the most influential. This often happens in calmer markets, where subtle shifts in candle structure can foreshadow bigger moves. By explicitly calling out which category is carrying the most weight at any moment, the dashboard gives traders immediate insight into why the netScore is tilting toward bullish, bearish, or sideways. --- 13. Oscillator Plot: How to Read It The “Net Score” oscillator sits below the dashboard and visually displays the smoothed netScore as a line graph. Key features: 1. Value Range: In normal conditions it oscillates roughly between –3 and +3, but extreme confluences can push it outside that range. 2. Horizontal Threshold Lines: • +2 Line (Bullish threshold) • 0 Line (Neutral midline) • –2 Line (Bearish threshold) 3. Zone Coloring: • Green Background (Bullish Zone): When netScore ≥ +2. • Red Background (Bearish Zone): When netScore ≤ –2. • Gray Background (Sideways Zone): When –2 < netScore < +2. 4. Dynamic Line Color: • The plotted netScore line itself is colored green in a Bullish Zone, red in a Bearish Zone, or gray in a Sideways Zone, creating an immediate visual cue. Interpretation Tips: • Crossing Above +2: Signals a strong enough combined trend/momentum/price-action reading to classify as Bullish. Many traders wait for a clear crossing plus a confirmation candle before entering a long position. • Crossing Below –2: Indicates a strong Bearish signal. Traders may consider short or exit strategies. • Rising Slope, Even Below +2: If netScore climbs steadily from neutral toward +2, it demonstrates building bullish momentum. • Divergence: If price makes a higher high but the oscillator fails to reach a new high, it can warn of weakening momentum and a potential reversal. --- 14. Comments and Their Necessity Every sub-indicator (ADX, MA slope, Ichimoku, RSI, Stochastic, MACD, HH/LL, Heikin-Ashi, Candle Range, BBW, ATR, KCW, Volume) generates a short comment that appears in the detailed dashboard. Examples: • “Strong bullish trend” or “Strong bearish trend” for ADX/DMI • “Fast MA above slow MA” or “Fast MA below slow MA” for MA slope • “RSI above dynamic threshold” or “RSI below dynamic threshold” for RSI • “MACD histogram positive” or “MACD histogram negative” for MACD Hist • “Price near highs” or “Price near lows” for HH/LL checks • “Bullish Heikin Ashi” or “Bearish Heikin Ashi” for HA Doji scoring • “Large range, trend confirmed” or “Small range, trend contradicted” for Candle Range Additionally, the top-row comment for each category is: • Trend: “Highly Bullish,” “Highly Bearish,” or “Neutral Trend.” • Momentum: “Strong Momentum,” “Weak Momentum,” or “Neutral Momentum.” • Price Action: “Bullish Action,” “Bearish Action,” or “Neutral Action.” • Market Activity: “Volatile Market,” “Calm Market,” or “Stable Market.” Reasons for These Comments: • Transparency: Shows exactly how each sub-indicator contributed to its category score. • Education: Helps traders learn why a category is labeled bullish, bearish, or neutral, building intuition over time. • Customization: If, for example, the RSI comment says “RSI neutral” despite an impending trend shift, a trader might choose to adjust RSI length or thresholds. In the detailed dashboard, hovering over each comment cell also reveals a tooltip with additional context (e.g., “Fast MA above slow MA” or “Senkou A above Senkou B”), helping traders understand the precise rule behind that +1, 0, or –1 assignment. --- 15. Real-Life Example (Consolidated) • Instrument & Timeframe: Bitcoin (BTCUSD), 1-hour chart. • Current Market Activity: BBW and ATR both spike (+1 each), KCW is moderately high (+1), but volume is only neutral (0) → Raw Market Activity Score = +2 → State = High Activity (after two bars, if hysteresis is on). • Category Weights Applied: Trend = 50 %, Momentum = 35 %, Price Action = 15 %. • Trend Sub-Scores: 1. ADX = 25 (above threshold 20) with +DI > –DI → +1. 2. Fast MA (20-period) sits above Slow MA (50-period) → +1. 3. Ichimoku: Senkou A > Senkou B → +1. → Trend Score = +3. • Momentum Sub-Scores: 4. RSI = 75 (above its moving average +1 stdev) → +1. 5. MACD histogram = +0.15 → +1. 6. Stochastic %K = 50 (mid-range) → 0. → Momentum Score = +2. • Price Action Sub-Scores: 7. Price is not within 1 % of the 20-period high/low and slope = positive → 0. 8. Heikin-Ashi body is slightly larger than stdev over last 5 bars with haClose > haOpen → +1. 9. Candle range is just above its dynamic upper bound but trend is already captured, so → +1. → Price Action Score = +2. • Calculate netScore (before smoothing): • Trend contribution = 3 × 0.50 = 1.50 • Momentum contribution = 2 × 0.35 = 0.70 • Price Action contribution = 2 × 0.15 = 0.30 • Raw netScore = 1.50 + 0.70 + 0.30 = 2.50 → Immediately classified as Bullish. • Oscillator & Dashboard Output: • The oscillator line crosses above +2 and turns green. • Dashboard displays: • Trend Regime “BULLISH,” Trend Score = 3, Comment = “Highly Bullish.” • Momentum Regime “BULLISH,” Momentum Score = 2, Comment = “Strong Momentum.” • Price Action Regime “BULLISH,” Price Action Score = 2, Comment = “Bullish Action.” • Market Activity State “High,” Comment = “Volatile Market.” • Weights: Trend 50 %, Momentum 35 %, Price Action 15 %. • Dominant Category: Trend (because 1.50 > 0.70 > 0.30). • Overall Score: 2.50, posCount = (three +1s in Trend) + (two +1s in Momentum) + (two +1s in Price Action) = 7 bullish signals, negCount = 0. • Final Zone = “BULLISH.” • The trader sees that both Trend and Momentum are reinforcing each other under high volatility. They might wait one more candle for confirmation but already have strong evidence to consider a long. --- • . --- Disclaimer This indicator is strictly a technical analysis tool and does not constitute financial advice. All trading involves risk, including potential loss of capital. Past performance is not indicative of future results. Traders should: • Always backtest the “Market Zone Analyzer ” on their chosen symbols and timeframes before committing real capital. • Combine this tool with sound risk management, position sizing, and, if possible, fundamental analysis. • Understand that no indicator is foolproof; always be prepared for unexpected market moves. Goodluck -BullByte! ---
مؤشر Pine Script®
من ‎BullByte‎
2
Chart Patterns [ActiveQuants]The Chart Patterns indicator is a comprehensive tool designed to automatically identify a variety of common chart patterns directly on your price chart. By detecting sequences of pivot highs and lows , this indicator helps traders spot potential trend continuations , reversals , and key market structures such as Double Tops and Double Bottoms . Enhance your technical analysis by quickly recognizing these formations as they emerge. How It Works The indicator operates in a two-stage process: Pivot Point Detection: It first identifies significant swing highs and swing lows (pivot points) based on a user-defined Period . These pivots form the fundamental building blocks for pattern recognition. Pattern Recognition: Using the sequence of these detected pivot points, the script then applies logical rules to identify the following patterns: Lower Low (LL) Lower Low & Lower High (LL & LH) Higher High (HH) Higher High & Higher Low (HH & HL) Double Tops Double Bottoms Patterns are drawn on the chart with connecting lines and labeled for easy identification. Double Tops and Double Bottoms also feature a status system: " Active " while forming, " Confirmed " upon neckline breakout, or " Invalid " if specific conditions negate the pattern before confirmation. █ KEY FEATURES Comprehensive Pattern Detection: Identifies six distinct types of chart patterns, offering insights into both trend continuation and potential reversals. Pivot-Based Analysis: Uses a robust method of identifying pivot highs and lows as the foundation for pattern formation. Pattern Status for Double Tops/Bottoms: - Active: A Double Top or Double Bottom pattern has formed its two peaks/troughs and the intervening neckline point, but the price has not yet broken beyond the neckline. The pattern is developing . - Confirmed: The price has decisively closed beyond the neckline (below for Double Top, above for Double Bottom), signaling a potential entry or validation of the pattern. - Invalid: An " Active " Double Top or Double Bottom pattern can be invalidated if, before a neckline breakout occurs, a new pivot point forms that negates the pattern’s structural integrity. For example, if a new pivot low forms above or at the neckline of an Active Double Top, the pattern is considered invalid because the market failed to break down and instead showed relative strength. Customizable Visuals: Allows users to define colors for bullish and bearish patterns, line widths, and the visibility of pivot points. Selective Pattern Display: Users can choose to display all patterns or filter by status (Active, Confirmed, Invalid) for Double Tops/Bottoms. Individual pattern types can also be toggled on or off. Historical Analysis Control: The Show Last History (Bars) input allows users to specify how far back the indicator should plot patterns, optimizing performance and chart readability. Clear Labeling: Patterns are clearly labeled on the chart, with Double Tops/Bottoms also showing " Top 1 ," " Top 2 ," or " Bottom 1 ," " Bottom 2 " labels. █ PATTERNS DETECTED Lower Low (LL): Indicates a potential bearish continuation or the start of a downtrend. Forms when price makes a lower low during an uptrend. Lower Low & Lower High (LL & LH): A stronger confirmation of a bearish trend, where the market forms a lower low followed by a lower high . Higher High (HH): Signals a potential bullish continuation or the start of an uptrend. Forms when price makes a higher high during a downtrend. Higher High & Higher Low (HH & HL): A stronger confirmation of a bullish trend, where the market forms a higher high followed by a higher low . Double Top: A bearish reversal pattern characterized by two distinct peaks at roughly the same price level, separated by a trough (neckline). Confirmation occurs when price breaks below the neckline. Double Bottom: A bullish reversal pattern featuring two distinct troughs at roughly the same price level, separated by a peak (neckline). Confirmation occurs when price breaks above the neckline. █ EXAMPLE: DOUBLE TOP INVALIDATION Understanding how a Double Top or Double Bottom can be invalidated is crucial. Here's an example for a Double Top: Formation: The indicator identifies two peaks (Top 1, Top 2) at a similar price level, with a corrective trough (Neckline Pivot P5) in between. The pattern is labeled " Double Top " and is in an " Active " state. ( Imagine points P4 and P6 are the two tops, and P5 is the low point of the neckline between them ). Pre-Breakout Condition: The price action continues, but before it breaks decisively below the P5 neckline level, a new significant swing low (a new pivot low) forms. Invalidation Check: The indicator checks the price level of this new pivot low. If this new pivot low occurs at a price equal to or higher than the P5 neckline level, the " Active " Double Top pattern is re-labeled as " Invalid Double Top ". ( See image below for a visual representation of this scenario ) In this example, the Double Top formed with Top 1 (P4) and Top 2 (P6). The neckline is at P5. Before price broke below P5, a new pivot low formed at the red circle. Since this new pivot low is above the P5 neckline, the Double Top is marked " Invalid ". The logic is that the market failed to break the neckline support and instead established a higher low (or a low at the support level), suggesting that the immediate bearish pressure has waned, thus invalidating the bearish reversal implication of the Double Top before it could confirm. A similar logic applies to Double Bottoms (a new pivot high forming below or at the neckline before an upside breakout). █ USER INPUTS Visibility and Common Styling - Show Last History (Bars): Specifies the number of recent bars the indicator will analyze and plot patterns on. Default: 3000 bars. Min: 10. - Patterns: Filters which patterns are displayed based on their status. Options: All, Active, Confirmed, Invalid. Default: All. - Pattern Line Width: Sets the thickness of the lines used to draw the patterns. Default: 1. Min: 1, Max: 10. - Bearish Color: Color for bearish patterns (LL, LL & LH, Double Tops). Default: Red. - Bullish Color: Color for bullish patterns (HH, HH & HL, Double Bottoms). Default: Green. Pivot Points - Period: The lookback period on either side of a bar to qualify it as a pivot high or low. Higher values detect more significant pivots. Default: 10 bars. Min: 2. - Show Pivot Highs: Toggles the visibility of detected pivot high markers. Default: Enabled. - Show Pivot Lows: Toggles the visibility of detected pivot low markers. Default: Enabled. - Pivot Highs Color: Color for the pivot high markers. Default: #ff5252 (Reddish). - Pivot Lows Color: Color for the pivot low markers. Default: #089981 (Greenish). Patterns (Toggles) - Lower Low: Enable/disable detection and display of Lower Low patterns. Default: Enabled. - Lower Low & Lower High: Enable/disable detection and display of Lower Low & Lower High patterns. Default: Enabled. - Higher High: Enable/disable detection and display of Higher High patterns. Default: Enabled. - Higher High & Higher Low: Enable/disable detection and display of Higher High & Higher Low patterns. Default: Enabled. - Double Tops: Enable/disable detection and display of Double Top patterns. Default: Enabled. - Double Bottoms: Enable/disable detection and display of Double Bottom patterns. Default: Enabled. █ CONCLUSION The Chart Patterns indicator is a versatile and powerful assistant for traders who utilize classical chart pattern analysis. By automating the detection of key formations and providing clear visual cues along with status updates for patterns like Double Tops and Bottoms, it allows traders to focus on strategy development and execution. With its customizable settings, it can be adapted to various instruments and timeframes, making it a valuable addition to any technical trader's toolkit. █ IMPORTANT NOTES ⚠ Pivot Period Sensitivity: The Period setting for pivot detection is crucial. A shorter period will identify more frequent, smaller swings, while a longer period will focus on more significant turning points. Adjust this setting based on the asset's volatility, the timeframe you are trading and your trading style. ⚠ Confirmation is Key: While the indicator identifies patterns, always wait for pattern confirmation (e.g., neckline breaks for Double Tops/Bottoms) and consider other factors like volume and market context before making trading decisions. ⚠ Confirmed Bars for Detection: Patterns are identified based on confirmed pivot points, which means a pivot is recognized period bars after it has formed. Status updates for Double Tops/Bottoms (Active, Confirmed, Invalid) also occur on confirmed bars. This approach enhances reliability and reduces the likelihood of repainting based on intra-bar price fluctuations. ⚠ Not a Standalone System: Chart patterns provide valuable insights, but they should be used in conjunction with other technical analysis tools (e.g., trendlines, moving averages, oscillators) and a sound risk management plan. ⚠ Lagging Nature: By their very definition, chart patterns are lagging indicators as they require a sequence of price action and several pivot points to complete their formation. █ RISK DISCLAIMER Trading involves a substantial risk of loss and is not suitable for every investor. The information provided by the Chart Patterns indicator is for educational and informational purposes only. It should not be considered as financial advice or a recommendation to buy or sell any security. Chart patterns indicate potential price movements but do not guarantee future results. Always perform your own due diligence and consult with a qualified financial advisor before making any investment decisions. Past performance is not indicative of future results.   📈 Happy trading! 🚀
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من ‎ActiveQuants‎
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