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MTF-Hidden Breaker Blocks TrackerThe MT-Hidden Breaker Blocks Tracker is a powerful indicator designed for SMC traders. Rooted in Smart Money Concepts (SMC), it uncovers institutional order flow by identifying Order Blocks (OB), Breaker Blocks (BB), and Partial Breaker Blocks (PBB) across multiple timeframes, revealing hidden liquidity zones for precise market structure analysis. ═══════ Key Features ═══════ Smart Money Detection: Order Blocks (OB): Pinpoints key candles before major market moves, marking institutional entry zones. Breaker Blocks (BB): Detects OBs aligned with Fair Value Gaps (FVGs), signaling liquidity zones. Partial Breaker Blocks (PBB): Tracks partially mitigated BBs for reaccumulation or distribution setups. The MT-Hidden Breaker Blocks Tracker features a REPLAY-MODE that allows traders to analyze historical Order Blocks (OB), Breaker Blocks (BB), and Partial Breaker Blocks (PBB) with Fair Value Gaps (FVGs) directly on the current timeframe, enabling precise backtesting of SMC strategies. Multi-Timeframe Liquidity Analysis: 70 pre-configured timeframes across five groups: Group 1: Minutes & Hours (5m–4h) Group 2: Hours (5h–23h) Group 3: Days (1D–19D) Group 4: Weeks (1W–12W) Group 5: Months (1M–12M) Group 6: 19 customizable timeframes for tailored strategies. Advanced SMC Tools: FVG Filter: Enhances BB/PBB signals with 1–5 FVGs for high-probability setups. Dynamic Mitigation: Monitors block mitigation in real-time with adjustable thresholds. Columnar Confluence Display: Visualizes liquidity zones in timeframe-specific columns, highlighting multi-timeframe confluence. Non-24/7 Market Support: Handles gaps in equities and forex markets. Auto-Current Timeframe: Displays analysis for the chart’s active timeframe. Visual Customization: Configurable bull/bear block colors. Adjustable borders, widths, and timeframe labels with FVG counts. Extended box projections for forecasting price action. Clean, non-obtrusive overlay for seamless chart integration. ═══════ How It Works ═══════ The MT-HiddenLiquidityTracker leverages SMC principles to detect institutional order flow by analyzing Order Blocks and their evolution into Breaker or Partial Breaker Blocks. It scans multiple timeframes to uncover liquidity pools, using FVGs to filter high-probability signals. The columnar display highlights confluence zones, making it easy to spot where smart money activity converges, ideal for SMC trading strategies. ═══════ How to Use ═══════ Select Timeframe Group: Choose Current, Groups 1–5, or Custom timeframes. Configure Block Types: Enable OB-only, BB/PBB-only, or all blocks. Set FVG Filter: Specify 1–5 FVGs for BB/PBB detection (optional). Customize Visuals: Adjust colors, labels, borders, and box extensions. Tune Detection: Set OB sensitivity and mitigation thresholds. ═══════ Why It Stands Out ═══════ Unlike generic indicators, the MT-Hidden Breaker Blocks Tracker combines SMC-based liquidity hunting with multi-timeframe analysis, offering a unique approach to institutional order flow. Its FVG filtering, extensive timeframe options, and columnar confluence display provide clarity for ICT/SMC traders seeking high-probability setups in forex, crypto, and indices. ═══════ Best Practices ═══════ Prioritize higher-timeframe blocks (Groups 3–6) for major liquidity zones. Combine with volume or price action for signal confirmation. Use FVG counts to assess block strength. Target confluence zones for stronger trade setups. ═══════ Performance Notes ═══════ Optimized for real-time analysis with efficient rendering. Manages visuals within TradingView’s limits. Supports historical analysis up to 10,000 bars. Built in Pine Script v6, Beta version. ═══════ Access ═══════ This is an invite-only script. Contact LiquidityForgeSMC via TradingView’s messaging system for details. ═══════ Disclaimer ═══════ This indicator is for educational and analytical purposes only and does not constitute financial, investment, or trading advice. Always conduct your own analysis before trading. The indicator is in active development, with additional SMC features planned for future updates. INSTRUCTIONS: www.youtube.com
Penunjuk Pine Script®
oleh LiquidityForgeSMC
Most-Crossed Channels (FAST • Top-K • Flexible Window)//@version=5 indicator("Most-Crossed Channels (FAST • Top-K • Flexible Window)", overlay=true, max_boxes_count=60, max_labels_count=60) // ---------- Inputs ---------- windowMode = input.string(defval="Last N Bars", title="Scan Window", options= ) barsLookback = input.int(defval=800, title="If Last N Bars → how many?", minval=100, maxval=5000) sess = input.session(defval="0830-1500", title="Session (exchange tz)") sessionsBack = input.int(defval=1, title="If Last N Sessions → how many?", minval=1, maxval=10) minutesLookback = input.int(defval=120, title="If Last X Minutes → how many?", minval=5, maxval=24*60) sinceTs = input.time(defval=timestamp("2024-01-01T09:30:00"), title="Since time (chart tz)") channelsK = input.int(defval=3, title="How many channels (Top-K)?", minval=1, maxval=10) binTicks = input.int(defval=8, title="Bin width (ticks)", minval=1, maxval=200) // NQ tick=0.25; 8 ticks = 2.0 pts minSepTicks = input.int(defval=12, title="Min separation between channels (ticks)", minval=1, maxval=500) countSource = input.string(defval="Wick (H-L)", title="Count bars using", options= ) drawMode = input.string(defval="Use Candle", title="Draw channel as", options= ) anchorPart = input.string(defval="Body", title="If Use Candle → part", options= ) fixedTicks = input.int(defval=8, title="If Fixed Thickness → thickness (ticks)", minval=1, maxval=200) extendBars = input.int(defval=400, title="Extend to right (bars)", minval=50, maxval=5000) showLabels = input.bool(defval=true, title="Show labels with counts") // ---------- Colors ---------- colFill = color.new(color.blue, 78) colEdge = color.new(color.blue, 0) colTxt = color.white // ---------- Draw caches (never empty) ---------- var box g_boxes = array.new_box() var label g_lbls = array.new_label() // ---------- Helpers ---------- barsFromMinutes(mins, avgBarMs) => ms = mins * 60000.0 int(math.max(2, math.round(ms / nz(avgBarMs, 60000.0)))) // First (oldest) candle in whose selected part contains `level` anchorIndexForPrice(level, useBody, scanNLocal) => idx = -1 for m = 1 to scanNLocal - 1 k = scanNLocal - m // oldest → newest o = open c = close h = high l = low topZ = useBody ? math.max(o, c) : h botZ = useBody ? math.min(o, c) : l if level >= botZ and level <= topZ idx := k break idx // ---------- Window depth ---------- inSess = not na(time(timeframe.period, sess)) sessStartIdx = ta.valuewhen(inSess and not inSess , bar_index, 0) sessStartIdxN = ta.valuewhen(inSess and not inSess , bar_index, sessionsBack - 1) sinceStartIdx = ta.valuewhen(time >= sinceTs and time < sinceTs, bar_index, 0) avgBarMs = ta.sma(time - time , 50) depthRaw = switch windowMode "Last N Bars" => barsLookback "Today (session)" => bar_index - nz(sessStartIdx, bar_index) "Last N Sessions" => bar_index - nz(sessStartIdxN, bar_index) "Last X Minutes" => barsFromMinutes(minutesLookback, avgBarMs) "Since time" => bar_index - nz(sinceStartIdx, bar_index) avail = bar_index + 1 scanN = math.min(avail, math.max(2, depthRaw)) scanN := math.min(scanN, 2000) // performance cap // ---------- Early guard ---------- if scanN < 2 na else // ---------- Build price histogram (O(N + B)) ---------- priceMin = 10e10 priceMax = -10e10 for j = 0 to scanN - 1 loB = math.min(open , close ) hiB = math.max(open , close ) lo = (countSource == "Body only") ? loB : low hi = (countSource == "Body only") ? hiB : high priceMin := math.min(priceMin, nz(lo, priceMin)) priceMax := math.max(priceMax, nz(hi, priceMax)) rng = priceMax - priceMin tick = syminfo.mintick binSize = tick * binTicks if na(rng) or rng <= 0 or binSize <= 0 na else // Pre-allocate fixed-size arrays (never size 0) MAX_BINS = 600 var float diff = array.new_float(MAX_BINS + 2, 0.0) // +2 so iH+1 is safe var float counts = array.new_float(MAX_BINS + 1, 0.0) var int blocked = array.new_int(MAX_BINS + 1, 0) var int topIdx = array.new_int() binsN = math.max(1, math.min(MAX_BINS, int(math.ceil(rng / binSize)) + 1)) // reset slices for i = 0 to binsN + 1 array.set(diff, i, 0.0) for i = 0 to binsN array.set(counts, i, 0.0) array.set(blocked, i, 0) array.clear(topIdx) // Range adds for j = 0 to scanN - 1 loB = math.min(open , close ) hiB = math.max(open , close ) lo = (countSource == "Body only") ? loB : low hi = (countSource == "Body only") ? hiB : high iL = int(math.floor((lo - priceMin) / binSize)) iH = int(math.floor((hi - priceMin) / binSize)) iL := math.max(0, math.min(binsN - 1, iL)) iH := math.max(0, math.min(binsN - 1, iH)) array.set(diff, iL, array.get(diff, iL) + 1.0) array.set(diff, iH + 1, array.get(diff, iH + 1) - 1.0) // Prefix sum → counts run = 0.0 for b = 0 to binsN - 1 run += array.get(diff, b) array.set(counts, b, run) // Top-K with spacing sepBins = math.max(1, int(math.ceil(minSepTicks / binTicks))) picks = math.min(channelsK, binsN) if picks > 0 for _ = 0 to picks - 1 bestVal = -1e9 bestBin = -1 for b = 0 to binsN - 1 if array.get(blocked, b) == 0 v = array.get(counts, b) if v > bestVal bestVal := v bestBin := b if bestBin >= 0 array.push(topIdx, bestBin) lB = math.max(0, bestBin - sepBins) rB = math.min(binsN - 1, bestBin + sepBins) for bb = lB to rB array.set(blocked, bb, 1) // Clear old drawings safely while array.size(g_boxes) > 0 box.delete(array.pop(g_boxes)) while array.size(g_lbls) > 0 label.delete(array.pop(g_lbls)) // Draw Top-K channels sz = array.size(topIdx) if sz > 0 for t = 0 to sz - 1 b = array.get(topIdx, t) level = priceMin + (b + 0.5) * binSize useBody = (drawMode == "Use Candle") anc = anchorIndexForPrice(level, useBody, scanN) anc := anc == -1 ? scanN - 1 : anc oA = open cA = close hA = high lA = low float topV = na float botV = na if drawMode == "Use Candle" topV := (anchorPart == "Body") ? math.max(oA, cA) : hA botV := (anchorPart == "Body") ? math.min(oA, cA) : lA else half = (fixedTicks * tick) * 0.5 topV := level + half botV := level - half left = bar_index - anc right = bar_index + extendBars bx = box.new(left, topV, right, botV, xloc=xloc.bar_index, bgcolor=colFill, border_color=colEdge, border_width=2) array.push(g_boxes, bx) if showLabels txt = str.tostring(int(array.get(counts, b))) + " crosses" lb = label.new(left, topV, txt, xloc=xloc.bar_index, style=label.style_label_down, textcolor=colTxt, color=colEdge) array.push(g_lbls, lb)
Penunjuk Pine Script®
oleh yassine_marouani30
🟥 Synthetic 10Y Real Yield (US10Y - Breakeven)This script calculates and plots a synthetic U.S. 10-Year Real Yield by subtracting the 10-Year Breakeven Inflation Rate (USGGBE10) from the nominal 10-Year Treasury Yield (US10Y). Real yields are a core macro driver for gold, crypto, growth stocks, and bond pricing, and are closely monitored by institutional traders. The script includes key reference lines: 0% = Below zero = deeply accommodative regime 1.5% = Common threshold used by macro desks to evaluate gold upside breakout conditions 📈 Use this to monitor macro shifts in real-time and front-run capital flows during major CPI, NFP, and Fed events. Update Frequency: Daily (based on Treasury market data)
Penunjuk Pine Script®
oleh Saraicy
Spiderlines BTCUSD - daily/weekly📘 Documentation – Daily and Weekly Spider Lines for Bitcoin 🔹 Purpose of the Script This script draws dynamic “Spider Lines” in the Bitcoin chart. The lines connect certain historical candles with a reference candle and extend to the right. These act as guideline levels that can serve as potential support or resistance zones. 🔹 How It Works The script operates in two modes, depending on the active chart timeframe: Weekly Mode (timeframe.isweekly) The reference date is July 1, 2019. The number of weeks since that date is calculated. This defines the connection candle (connection_candle). Several predefined offsets (e.g., +32, +34, +36 …) are added to the reference to determine starting candles. Lines are drawn from these candles toward the connection candle. → Line color: green Daily Mode (timeframe.isdaily) Same reference date: July 1, 2019. The number of days since that date is calculated. Again, a connection candle is set. A different set of offsets (e.g., +224, +238, +252 …) defines the starting candles. Lines are drawn accordingly. → Line color: red 🔹 Line Logic Each line connects: Start → bar_index at high End → bar_index at close Lines are extended indefinitely to the right (extend.right). Appearance: dashed style, width 2. 🔹 Error Handling If a calculated candle index does not exist in the chart history (e.g., chart data does not go back far enough), a label is plotted in the chart showing the message: "Daily idx out of range: 252" This way, missing lines can be diagnosed easily. 🔹 Color Convention Weekly Spider Lines → Green Daily Spider Lines → Red 🔹 Use Cases Visualization of historical cyclic line patterns. Helps in technical chart analysis: spotting potential reaction zones in price movement. Designed mainly for long-term traders and analysts observing Bitcoin in Daily or Weekly timeframes. 🔹 Limitations Works only on Daily and Weekly charts. Requires chart data going back to July 1, 2019. Based purely on fixed offsets → not a classical indicator like Moving Averages or RSI.
Penunjuk Pine Script®
oleh osterhansi_
Analyst Targets ProbabilityThis indicator calculates the probability of the current stock price reaching or exceeding the analyst-provided high, average, and low price targets within a one-year time horizon. It utilizes a geometric Brownian motion (GBM) model, a standard approach in financial modeling that assumes log-normal price distribution with constant volatility. ### Key Features: - **Analyst Targets**: Automatically pulls the high, average, and low one-year price targets from TradingView's syminfo data. - **Risk-Free Rate**: Fetched from the 1-year US Treasury yield (symbol: TVC:US01Y). Defaults to 4% if unavailable. - **Dividend Yield**: Uses trailing twelve-month (TTM) dividends per share (DPS) from financial data, divided by current price. Defaults to 0% if unavailable. - **Volatility**: Computed as annualized historical volatility based on 252 trading days of daily log returns. Falls back to a 20-day period if insufficient data, or defaults to 30% if still unavailable. - **Probability Calculation**: Employs the barrier hitting probability formula under GBM: - Drift (μ) = risk-free rate - dividend yield - (volatility² / 2) - The formula for probability P of hitting target H from current price S₀ over time T is: P = Φ(d₊) + (H / S₀)^p ⋅ Φ(d₋) for H > S₀ (or adjusted for H < S₀) Where l = ln(max(H, S₀)/min(H, S₀)), ν = drift, p = -2ν / σ², d₊ = (-l + νT) / (σ√T), d₋ = (-l - νT) / (σ√T), and Φ is the standard normal CDF (approximated using a polynomial method for accuracy). - **Output Display**: A table in the top-right corner shows each target type, its value, and the estimated probability (as a percentage). "N/A" appears if data is unavailable or calculations cannot proceed (e.g., zero volatility). ### Assumptions and Limitations: - Assumes constant volatility and drift, no transaction costs, and continuous trading (real markets may deviate due to jumps, news events, or changing conditions). - Probabilities are model-based estimates and not guarantees; they represent the likelihood under risk-neutral measure. - Best suited for stocks with available analyst targets and historical data; may default to assumptions for less-liquid symbols. - No user inputs required—fully automated using TradingView's data sources. This script is provided under the Mozilla Public License 2.0. For educational and informational purposes only; not financial advice. Test on your charts and consider backtesting for validation.
Penunjuk Pine Script®
oleh TPolehn
PDD — Pullback & Breakout Alerts (PopsStocks) • INDICATOR🟢 Trader-Friendly (simple & clear) Description: This indicator highlights pullback and breakout trade opportunities on PDD (Pinduoduo). It automatically marks pullback buy zones, breakout levels, stops, and profit targets. Signals are based on bullish reversal candles (inside pullback zones) and confirmed breakouts above resistance. Includes optional EMAs for trend context and built-in alerts, making it easy to catch setups in real time. 🔵 Technical/Backtest-Friendly (for advanced users) Description: A price-action-based tool for identifying structured entries on PDD (Pinduoduo). The script plots dynamic pullback zones, breakout resistance levels, stops, and risk/reward targets. Signal logic combines candlestick reversals (bullish engulfing, hammer), volume filters, and optional higher-low buildup checks. 20/50 EMA overlays provide trend confirmation. Designed for traders who want defined rules, alert automation, and clear risk-to-reward planning.
Penunjuk Pine Script®
oleh PopsStock
Dow Theory Indicator## 🎯 Key Features of the Indicator ### 📈 Complete Implementation of Dow Theory - Three-tier trend structure: primary trend (50 periods), secondary trend (20 periods), and minor trend (10 periods). - Swing point analysis: automatically detects critical swing highs and lows. - Trend confirmation mechanism: strict confirmation logic based on consecutive higher highs/higher lows or lower highs/lower lows. - Volume confirmation: ensures price moves are supported by trading volume. ### 🕐 Flexible Timeframe Parameters All key parameters are adjustable, making it especially suitable for U.S. equities: Trend analysis parameters: - Primary trend period: 20–200 (default 50; recommended 50–100 for U.S. stocks). - Secondary trend period: 10–100 (default 20; recommended 15–30 for U.S. stocks). - Minor trend period: 5–50 (default 10; recommended 5–15 for U.S. stocks). Dow Theory parameters: - Swing high/low lookback: 5–50 (default 10). - Trend confirmation bar count: 1–10 (default 3). - Volume confirmation period: 10–100 (default 20). ### 🇺🇸 U.S. Market Optimizations - Session awareness: distinguishes Regular Trading Hours (9:30–16:00 EST) from pre-market and after-hours. - Pre/post-market weighting: adjustable weighting factor for signals during extended hours. - Earnings season filter: automatically adjusts sensitivity during earnings periods. - U.S.-optimized default parameters. ## 🎨 Visualization 1. Trend lines: three differently colored trend lines. 2. Background fill: green (uptrend) / red (downtrend) / gray (neutral). 3. Signal markers: arrows, labels, and warning icons. 4. Swing point markers: small triangles at key turning points. 5. Info panel: real-time display of eight key metrics. ## 🚨 Alert System - Trend turning to up/down. - Strong bullish/bearish signals (dual confirmation). - Volume divergence warning. - New swing high/low formed. ## 📋 How to Use 1. Open the Pine Editor in TradingView. 2. Copy the contents of dow_theory_indicator.pine. 3. Paste and click “Add to chart.” 4. Adjust parameters based on trading style: - Long-term investing: increase all period parameters. - Swing trading: use the default parameters. - Short-term trading: decrease all period parameters. ## 💡 Parameter Tips for U.S. Stocks - Large-cap blue chips (AAPL, MSFT): primary 60–80, secondary 25–30. - Mid-cap growth stocks: primary 40–60, secondary 18–25. - Small-cap high-volatility stocks: primary 30–50, secondary 15–20.
Penunjuk Pine Script®
oleh boyue_sw
Reference Point Extension StrategyThe script accepts the user to enter a date and time when live market starts trading. ex. Nasdaq starts live trading at 9.30 am New York time. Based on the time & candle characteristics and mathematical calculation it draws 2 line RED & green which are no trade zones and breakout on either side can result in achieving the marked targets. Wait for a candle to close above or below the no trade zone and next candle to break its high or low. Put the SL above or below the RED or Green line.
Penunjuk Pine Script®
oleh RajeshAnilDeshpande
SMC Analysis - Fair Value Gaps (Enhanced)SMC Analysis - Fair Value Gaps (Enhanced) Script Summary Overview The "SMC Analysis - Fair Value Gaps (Enhanced)" script, written in Pine Script (version 6), is a technical analysis indicator designed for TradingView to identify and visualize Fair Value Gaps (FVGs) on a price chart. It supports both the main timeframe and multiple higher timeframes (MTF) for comprehensive market analysis. FVGs are price gaps formed by a three-candle pattern, indicating potential areas of market inefficiency where price may return to fill the gap. Key Features FVG Detection: Identifies bullish FVGs: Occur when the high of a candle two bars prior is lower than the low of the current candle, with the middle candle being bullish (close > open). Identifies bearish FVGs: Occur when the low of a candle two bars prior is higher than the high of the current candle, with the middle candle being bearish (close < open). Visualizes FVGs as colored boxes on the chart (green for bullish, red for bearish). Mitigation Tracking: Tracks when FVGs are touched (price overlaps the gap range) or mitigated (price fully closes the gap). Strict Mode: Marks an FVG as mitigated when price touches the gap range. Normal Mode: Requires a full breakthrough (price crossing the gap’s bottom for bullish FVGs or top for bearish FVGs) for mitigation. Optionally converts FVG box borders to dashed lines and increases transparency when partially touched. Multi-Timeframe (MTF) Support: Analyzes FVGs on three user-defined higher timeframes (default: 15m, 60m, 240m). Displays MTF FVGs with distinct labels and slightly more transparent colors. Ensures no duplicate processing of MTF bars to maintain performance. Customization Options: FVG Length: Adjustable duration for how long FVGs are displayed (default: 20 bars). Show/Hide FVGs: Toggle visibility for main timeframe and each MTF. Color Customization: User-defined colors for bullish and bearish FVGs (default: green and red). Display Options: Toggle for showing dashed lines after partial touches and strict mitigation mode. Performance Optimization: Limits the number of displayed boxes (50 for main timeframe, 20 per MTF) to prevent performance issues. Automatically removes older boxes to maintain a clean chart. Functionality Visualization: Draws boxes around detected FVGs, with customizable colors and text labels ("FVG" for main timeframe, "FVG " for MTF). Dynamic Updates: Extends or terminates FVG boxes based on mitigation status and user settings. Efficient Storage: Uses arrays to manage FVG data (boxes, tops, bottoms, indices, mitigation status, and touch status) separately for main and MTF analyses. Use Case This indicator is designed for traders using Smart Money Concepts (SMC) to identify areas of market inefficiency (FVGs) for potential price reversals or continuations. The MTF support allows analysis across different timeframes, aiding in confirming trends or spotting higher-timeframe support/resistance zones.
Penunjuk Pine Script®
oleh osterhansi_
Seasonality - Multiple Timeframes📊 Seasonality - Multiple Timeframes 🎯 What This Indicator Does This advanced seasonality indicator analyzes historical price patterns across multiple configurable timeframes and projects future seasonal behavior based on statistical averages. Unlike simple seasonal overlays, this indicator provides gap-resistant architecture specifically designed for commodity futures markets and other instruments with contract rolls. 🔧 Key Features Multiple Timeframe Analysis Three Independent Timeframes: Configure separate historical periods (e.g., 5Y, 10Y, 15Y) for comprehensive analysis Individual Control: Enable/disable historical lines and projections independently for each timeframe Color Customization: Distinct colors for historical patterns and future projections Advanced Architecture Gap-Resistant Design: Handles missing data and contract rolls in futures markets seamlessly Calendar-Day Normalization: Uses 365-day calendar system for accurate seasonal comparisons Outlier Filtering: Automatically excludes extreme price movements (>10% daily changes) Roll Detection: Identifies and excludes contract roll periods to maintain data integrity Real-Time Projections Forward-Looking Analysis: Projects seasonal patterns into the future based on remaining calendar days Configurable Projection Length: Adjust forecast period from 10 to 150 bars Data Interpolation: Optional gap-filling for smoother seasonal curves 📈 How It Works Data Collection Process The indicator collects daily price returns for each calendar day (1-365) over your specified historical periods. For each timeframe, it: Calculates daily returns while excluding roll periods and outliers Accumulates these returns by calendar day across multiple years Computes average seasonal performance from January 1st to current date Projects remaining seasonal pattern based on historical averages 🎯 Designed For Primary Use Cases Commodity Futures Trading: Corn, soybeans, coffee, sugar, cocoa, natural gas, crude oil Seasonal Strategy Development: Identify optimal entry/exit timing based on historical patterns Pattern Validation: Confirm seasonal tendencies across different time horizons Market Timing: Compare current performance against historical seasonal expectations Trading Applications Trend Confirmation: Use multiple timeframes to validate seasonal direction Risk Assessment: Understand seasonal volatility patterns Position Sizing: Adjust exposure based on seasonal performance consistency Calendar Spread Analysis: Identify seasonal price relationships ⚙️ Configuration Guide Timeframe Setup Configure each timeframe independently: Years: Set historical lookback period (1-20 years) Historical Display: Show/hide the seasonal pattern line Projection Display: Enable/disable future seasonal projection Colors: Customize line colors for visual clarity Display Options Current YTD: Compare actual year-to-date performance Info Table: Detailed performance comparison across timeframes Projection Bars: Control forward-looking projection length Fill Gaps: Interpolate missing data points for smoother curves Debug Features Enable debug mode to validate data quality: Data Point Counts: Verify sufficient historical data per calendar day Roll Detection Status: Monitor contract roll identification Empty Days Analysis: Identify potential data gaps Calculation Verification: Debug seasonal price computations 📊 Interpretation Guidelines Strong Seasonal Signal All three timeframes align in the same direction Current price follows seasonal expectation Sufficient data points (>3 years minimum per timeframe) Seasonal Divergence Different timeframes show conflicting patterns Recent years deviate from longer-term averages Current price significantly above/below seasonal expectation Data Quality Indicators Green Status: Adequate data across all calendar days Red Warnings: Insufficient data or excessive gaps Roll Detection: Proper handling of futures contract changes ⚠️ Important Considerations Data Requirements Minimum History: At least 3-5 years for reliable seasonal analysis Continuous Data: Best results with daily continuous contract data Market Hours: Designed for traditional market session data Limitations Past Performance: Historical patterns don't guarantee future results Market Changes: Structural shifts can alter traditional seasonal patterns External Factors: Weather, geopolitics, and policy changes affect seasonal behavior Contract Rolls: Some data gaps may occur during futures roll periods 🔍 Technical Specifications Performance Optimizations Array Management: Efficient data storage using Pine Script arrays Gap Handling: Robust price calculation with fallback mechanisms Memory Usage: Optimized for large historical datasets (max_bars_back = 4000) Real-Time Updates: Live calculation updates as new data arrives Calculation Accuracy Outlier Filtering: Excludes daily moves >10% to prevent data distortion Roll Detection: 8% threshold for identifying contract changes Data Validation: Multiple checks for price continuity and data integrity 🚀 Getting Started Add to Chart: Apply indicator to your desired futures contract or commodity Configure Timeframes: Set historical periods (recommend 5Y, 10Y, 15Y) Enable Projections: Turn on future seasonal projections for forward guidance Validate Data: Use debug mode initially to ensure sufficient historical data Interpret Patterns: Compare current price action against seasonal expectations 💡 Pro Tips Multiple Confirmations: Use all three timeframes for stronger signal validation Combine with Technicals: Integrate seasonal analysis with technical indicators Monitor Divergences: Pay attention when current price deviates from seasonal pattern Adjust for Volatility: Consider seasonal volatility patterns for position sizing Regular Updates: Recalibrate settings annually to maintain relevance --- This indicator represents years of development focused on commodity market seasonality. It provides institutional-grade seasonal analysis previously available only to professional trading firms.
Penunjuk Pine Script®
oleh joericke
Machine Learning : Neural Network Prediction -EasyNeuro-Machine Learning: Neural Network Prediction — An indicator that learns and predicts price movements using a neural network — Overview The indicator “Machine Learning: Neural Network Prediction” uses price data from the chart and applies a three-layer Feedforward Neural Network (FNN) to estimate future price movements. Key Features Normally, training and inference with neural networks require advanced programming languages that support machine learning frameworks (such as TensorFlow or PyTorch) as well as high-performance hardware with GPUs. However, this indicator independently implements the neural network mechanism within TradingView’s Pine Script environment, enabling real-time training and prediction directly on the chart. Since Pine Script does not support matrix operations, the backpropagation algorithm—necessary for neural network training—has been implemented entirely through scalar operations. This unique approach makes the creation of such a groundbreaking indicator possible. Significance of Neural Networks Neural networks are a core machine learning method, forming the foundation of today’s widely used generative AI systems, such as OpenAI’s GPT and Google’s Gemini. The feedforward neural network adopted in this indicator is the most classical architecture among neural networks. One key advantage of neural networks is their ability to perform nonlinear predictions. All conventional indicators—such as moving averages and oscillators like RSI—are essentially linear predictors. Linear prediction inherently lags behind past price fluctuations. In contrast, nonlinear prediction makes it theoretically possible to dynamically anticipate future price movements based on past patterns. This offers a significant benefit for using neural networks as prediction tools among the multitude of available indicators. Moreover, neural networks excel at pattern recognition. Since technical analysis is largely based on recognizing market patterns, this makes neural networks a highly compatible approach. Structure of the Indicator This indicator is based on a three-layer feedforward neural network (FNN). Every time a new candlestick forms, the model samples random past data and performs online learning using stochastic gradient descent (SGD). SGD is known as a more versatile learning method compared to standard gradient descent, particularly effective for uncertain datasets like financial market price data. Considering Pine Script’s computational constraints, SGD is a practical choice since it can learn effectively from small amounts of data. Because online learning is performed with each new candlestick, the indicator becomes a little “smarter” over time. Adjustable Parameters Learning Rate Specifies how much the network’s parameters are updated per training step. Values between 0.0001 and 0.001 are recommended. Too high causes divergence and unstable predictions, while too low prevents sufficient learning. Iterations per Online Learning Step Specifies how many training iterations occur with each new candlestick. More iterations improve accuracy but may cause timeouts if excessive. Seed Random seed for initializing parameters. Changing the seed may alter performance. Architecture Settings Number of nodes in input and hidden layers: Increasing input layer nodes allows predictions based on longer historical periods. Increasing hidden layer nodes increases the network’s interpretive capacity, enabling more flexible nonlinear predictions. However, more nodes increase computational cost exponentially, risking timeouts and overfitting. Hidden layer activation function (ReLU / Sigmoid / Tanh): Sigmoid: Classical function, outputs between 0–1, approximates a normal distribution. Tanh: Similar to Sigmoid but outputs between -1 and 1, centered around 0, often more accurate. ReLU: Simple function (outputs input if ≥ 0, else 0), efficient and widely effective. Input Features (selectable and combinable) RoC (Rate of Change): Measures relative price change over a period. Useful for predicting movement direction. RSI (Relative Strength Index): Oscillator showing how much price has risen/fallen within a period. Widely used to anticipate direction and momentum. Stdev (Standard Deviation, volatility): Measures price variability. Useful for volatility prediction, though not directional. Optionally, input data can be smoothed to stabilize predictions. Other Parameters Data Sampling Window: Period from which random samples are drawn for SGD. Prediction Smoothing Period: Smooths predictions to reduce spikes, especially when RoC is used. Prediction MA Period: Moving average applied to smoothed predictions. Visualization Features The internal state of the neural network is displayed in a table at the upper-right of the chart: Network architecture: Displays the structure of input, hidden, and output layers. Node activations: Shows how input, hidden, and output node values dynamically change with market conditions. This design allows traders to intuitively understand the inner workings of the neural network, which is often treated as a black box. Glossary of Terms Feature: Input variables fed to the model (RoC/RSI/Stdev). Node/Unit: Smallest computational element in a layer. Activation Function: Nonlinear function applied to node outputs (ReLU/Sigmoid/Tanh). MSE (Mean Squared Error): Loss function using average squared errors. Gradient Descent (GD/SGD): Optimization method that gradually adjusts weights in the direction that reduces loss. Online Learning: Training method where the model updates sequentially with each new data point.
Penunjuk Pine Script®
oleh EazyNeuro
Event Contract Signal Predictor [10-min Chart]Description: This script is designed for high-probability event contract trading on 10-minute charts. It combines proprietary LSMA wave trend analysis with custom high-pass filtering and dynamic volume-based order book detection to generate precise long and short entry signals. Key Features: • LSMA Wave Trend: Captures short-term momentum with a custom linear regression over smoothed RSI values. • High-Pass Filter & Peak Detection: Reduces noise and identifies extreme price movements for precise timing. • Dynamic Order Book Ratio: Monitors buy/sell volume imbalance in real-time to confirm trade validity. • Signal Confluence: Long or short signals appear only when multiple conditions align (trend, momentum, volume), reducing false triggers. • Immediate Signal Display: Signals appear on the first candle after condition confirmation; no need to wait for candle close. • Adjustable Parameters: Users can customize resonance thresholds, smoothing periods, and trigger sensitivity for different markets. How to Use: 1. Apply the script to a 10-minute chart. 2. Observe green circles (long) and red circles (short) marking potential entries. 3. Combine with your risk management strategy for optimal results. Note: This script is closed-source to protect proprietary logic. While the exact calculations are not revealed, this description provides enough context for traders to understand how signals are generated and applied.
Penunjuk Pine Script®
oleh HunterX8869
1
ESTP MeterAuto Entry/SL/TP + Meter (no dashboard / no MA50 plot / no fixed levels) Idea The indicator builds Entry / SL / TP1–TP3 zones and highlights bars when the odds of trend continuation are high. Under the hood it runs a multi-factor Meter with HTF filtering, volume, volatility, and breakout context. It does not draw a dashboard, MA50 line, or fixed levels — only the working zones and setup highlights. How it works Signal LONG/SHORT comes from a combo of: RSI(14), MACD (line/signal/hist), and trend vs SMA50 (used internally only, not plotted). HTF filter (tfHTF): direction alignment on the higher timeframe via EMA50, RSI, MACD-hist. Breakout factor: a brLen lookback high/low break in the trend direction boosts the score. Meter/Score (0–100): weighted sum of RVOL, ATR%, TREND, ADX, BREAK, with a chop penalty when EMA20–EMA50 gap is small. Bar highlight: when Score ≥ 70 and there’s a breakout in the aligned trend direction. Zones: On signal change (bar close) it pins Entry at the close. SL: at the most recent confirmed pivot (5×5). If no pivot yet, a fallback SL = ±2% from Entry. TP1/TP2/TP3: from wave = |Entry − SL| using your Fib multipliers. Zones are drawn 20 bars forward with labels for Entry/SL/TP. Key Inputs TP1/TP2/TP3 Fib: 0.618 / 1.0 / 1.618 by default. HTF (tfHTF): higher-timeframe filter (default 60m). brLen: breakout lookback (suggest 20–50). rvolMin / atrNorm: normalization floors for relative volume and ATR%. emaBandMin: minimum EMA20–EMA50 gap; below this, score is penalized. showBarHL: toggle bar highlighting. Note: adxMin is reserved for future use (not enforced as a hard filter in this version). Practical use Timeframes: best from M15 to H4. On M1–M5, raise brLen and rvolMin to fight noise. Markets: liquid futures/crypto/FX. For thin symbols, reduce RVOL impact. Exits: scale out across TP1/TP2/TP3; after TP1, move to break-even. Context filter: trade only when HTF & LTF align (built into the logic). Risk: position size from SL distance; keep risk ≤ 1–2% per trade. Caveats (repainting / behavior) Pivot-based SL confirms after 5 bars — by design it’s delayed. Until then, a ±2% safety SL is used. Zones/labels are placed on bar close when the signal flips — this reduces flicker and intrabar artifacts. HTF data uses request.security — prefer closed bars to avoid intrabar higher-TF whipsaws. This is an indicator, not a strategy; no guarantees. Forward-test and tune per market/TF. Suggested presets Trend/Swing (H1–H4): brLen=30–50, rvolMin=1.2–1.5, atrNorm=0.02–0.03, emaBandMin=0.002–0.004. Intraday (M15–M30): brLen=20–30, rvolMin=1.1–1.3, atrNorm=0.03–0.05, emaBandMin=0.0015–0.003.
Penunjuk Pine Script®
oleh Bonavivitalik
Futty (Futures Lot Calculator)Futty – Futures Risk & Position Sizing Tool Futty is a risk management and position sizing indicator designed for futures traders. It automatically detects the dollar value per point for popular CME futures (Equity, Forex, Commodities, Bonds, Metals, etc.) and helps you calculate the optimal lot size based on: Account size 💰 Risk percentage (%) Entry, Stop Loss, and Take Profit levels The indicator plots Entry, SL, and TP zones on the chart, shows risk/reward labels, and provides a clean info table displaying account size, risk %, dollar per point, cash at risk, and recommended lot size. With Futty, you can trade with clarity, knowing your exact risk exposure and position size before entering any futures trade.
Penunjuk Pine Script®
oleh Vignesh_Baskar
TLThe Trade Lean Indicator is a custom-built market tool designed for traders who want a clean, professional, and actionable view of price action without unnecessary noise. It combines trend tracking, liquidity mapping, and momentum signals into a single framework that adapts across multiple timeframes. Unlike generic indicators, Trade Lean focuses on clarity over clutter. It highlights the key zones that truly matter: supply and demand levels, liquidity pockets, and directional momentum shifts. Whether you’re day trading, swing trading, or just scanning charts for setups, the indicator helps you quickly identify: Trend bias (bullish, bearish, or neutral) Liquidity zones where market reactions are most likely Momentum impulses vs corrective moves Breakout and recovery points to confirm direction This makes it easier to lean into high-probability setups and avoid overtrading.
Penunjuk Pine Script®
oleh Trade-Lean
Planetary Speed - CEPlanetary Speed - Community Edition Welcome to the Planetary Speed - Community Edition , a specialized tool designed to enhance W.D. Gann-inspired trading by plotting the speed of selected planets. This indicator measures changes in planetary ecliptic longitudes, which may correlate with market timing and volatility, making it ideal for traders analyzing equities, forex, commodities, and cryptocurrencies. Overview The Planetary Speed - Community Edition calculates the speed of a chosen planet (Mercury, Venus, Mars, Jupiter, Saturn, Uranus, Neptune, or Pluto) by comparing its ecliptic longitude across time. Supporting heliocentric and geocentric modes, the script plots speed data with high precision across various chart timeframes, particularly for markets open 24/7 like cryptocurrencies. Traders can customize line colors and add multiple instances for multi-planet analysis, aligning with Gann’s belief that planetary cycles influence market trends. Key Features Plots the speed of eight planets (Mercury, Venus, Mars, Jupiter, Saturn, Uranus, Neptune, Pluto) based on ecliptic longitude changes Supports heliocentric and geocentric modes for flexible analysis Customizes line colors for clear visualization of planetary speed data Projects future speed data up to 250 days with daily resolution Works across default TradingView timeframes (except monthly) for continuous markets Enables multiple script instances for tracking different planets on the same chart How to Use Access the script’s settings to configure preferences Choose a planet from Mercury, Venus, Mars, Jupiter, Saturn, Uranus, Neptune, or Pluto Select heliocentric or geocentric mode for calculations Customize the line color for speed data visualization Review plotted speed data to identify potential market timing or volatility shifts Add multiple instances to track different planets simultaneously Get Started The Planetary Speed - Community Edition provides full functionality for astrological market analysis. Designed to highlight Gann’s planetary cycles, this tool empowers traders to explore celestial influences. Trade wisely and harness the power of planetary speed!
Penunjuk Pine Script®
oleh NasserHumood