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Candlestick analysis

BTC – 6 o'clock Windows (AM/PM) • stable v6Treat 02:30 and 14:30 UTC with Respect This study focuses on two recurring intraday windows on BTC: 02:30 and 14:30 UTC. Using a time-based overlay that highlights 60–90 minute windows around these timestamps, you’ll notice that many days feature a sharp move, often kicked off by a quick liquidity sweep. On the chart: • Boxes visualize each window’s High–Low range. • Labels show only the dollar change across the window (no decimals). • Gray label = net up (Close − Open > 0). Purple label = net down (Close − Open < 0). Why exactly 02:30 and 14:30 UTC? 1. Session overlap and peak liquidity. 02:30 sits inside Asia; 14:30 lands during prime U.S. hours. Block orders and rebalancing cluster here, lifting volatility. 2. Perpetuals mechanics. Funding, scheduled rolls, and liquidations often bunch around these times, triggering stop runs and occasional cascades. 3. Algorithmic execution. CTAs/HFTs batch orders near session turns and around key candle opens/closes. 4. Liquidity grabs. Fast sweeps above/below obvious highs/lows harvest stops before the real direction develops. How to trade around these windows • Time alerts at 02:25 and 14:25 UTC. • Reduce size or hedge from \~10–15 minutes before to 30–90 minutes after. • Avoid obvious swing-point stops; use ATR-based buffers. • Wait for confirmation: liquidity sweep plus structure shift (MSB/CHOCH) with volume—don’t chase the first spike. • Check the calendar first; CPI/FOMC/CME and major macro prints can magnify moves. Method Windows are highlighted strictly around 02:30 and 14:30 UTC on 15–30 minute charts. The magnitude cue comes from the window’s High–Low range, while label color reflects the net result (Close − Open): gray for net up, purple for net down. Repeated observations across recent days show this timing effect clearly. Bottom line The 02:30 and 14:30 UTC windows are liquidity magnets. Even if you trade swing or trend, acknowledging the elevated volatility here can materially improve entries, risk placement, and position durability. This is an analytical view, not financial advice.
Pine Script® göstergesi
Captain-MM8 tarafından
Мой скрипт//@version=5 indicator("Market Structure BOS/CHoCH", overlay=true, max_labels_count=500) // === Settings === swingLen = input.int(3, "Swing Length", minval=1) showBOS = input.bool(true, "Show BOS") showCHoCH = input.bool(true, "Show CHoCH") // === Identify swing highs and lows === var float lastHigh = na var float lastLow = na swingHigh = ta.pivothigh(high, swingLen, swingLen) swingLow = ta.pivotlow(low, swingLen, swingLen) if not na(swingHigh) lastHigh := swingHigh if not na(swingLow) lastLow := swingLow // === Determine HH, HL, LH, LL === hh = not na(swingHigh) and swingHigh > lastHigh hl = not na(swingLow) and swingLow > lastLow lh = not na(swingHigh) and swingHigh < lastHigh ll = not na(swingLow) and swingLow < lastLow // === Plot labels for structure points === if hh label.new(bar_index, swingHigh, "HH", style=label.style_label_down, color=color.green, textcolor=color.white, yloc=yloc.abovebar) if hl label.new(bar_index, swingLow, "HL", style=label.style_label_up, color=color.green, textcolor=color.white, yloc=yloc.belowbar) if lh label.new(bar_index, swingHigh, "LH", style=label.style_label_down, color=color.red, textcolor=color.white, yloc=yloc.abovebar) if ll label.new(bar_index, swingLow, "LL", style=label.style_label_up, color=color.red, textcolor=color.white, yloc=yloc.belowbar) // === BOS (Break of Structure) detection === bosUp = ta.crossover(close, lastHigh) bosDown = ta.crossunder(close, lastLow) if showBOS and bosUp label.new(bar_index, high, "BOS ↑", style=label.style_label_down, color=color.blue, textcolor=color.white, yloc=yloc.abovebar) if showBOS and bosDown label.new(bar_index, low, "BOS ↓", style=label.style_label_up, color=color.blue, textcolor=color.white, yloc=yloc.belowbar) // === CHoCH (Change of Character) detection === var int trend = 0 // 1 = uptrend, -1 = downtrend if hh or hl trend := 1 if lh or ll trend := -1 chochUp = trend == -1 and bosUp chochDown = trend == 1 and bosDown if showCHoCH and chochUp label.new(bar_index, high, "CHoCH ↑", style=label.style_label_down, color=color.lime, textcolor=color.white, yloc=yloc.abovebar) if showCHoCH and chochDown label.new(bar_index, low, "CHoCH ↓", style=label.style_label_up, color=color.lime, textcolor=color.white, yloc=yloc.belowbar) // === Arrows for signals === plotshape(bosUp, title="BOS Buy Arrow", location=location.belowbar, color=color.blue, style=shape.labelup, size=size.small, text="↑ BOS") plotshape(bosDown, title="BOS Sell Arrow", location=location.abovebar, color=color.blue, style=shape.labeldown, size=size.small, text="↓ BOS") plotshape(chochUp, title="CHoCH Buy Arrow", location=location.belowbar, color=color.lime, style=shape.labelup, size=size.small, text="↑ CHoCH") plotshape(chochDown, title="CHoCH Sell Arrow", location=location.abovebar, color=color.lime, style=shape.labeldown, size=size.small, text="↓ CHoCH")
Pine Script® göstergesi
shunderiukivan tarafından
PnL Bubble [%] | Fractalyst1. What's the indicator purpose? The PnL Bubble indicator transforms your strategy's trade PnL percentages into an interactive bubble chart with professional-grade statistics and performance analytics. It helps traders quickly assess system profitability, understand win/loss distribution patterns, identify outliers, and make data-driven strategy improvements. How does it work? Think of this indicator as a visual report card for your trading performance. Here's what it does: What You See Colorful Bubbles: Each bubble represents one of your trades Blue/Cyan bubbles = Winning trades (you made money) Red bubbles = Losing trades (you lost money) Bigger bubbles = Bigger wins or losses Smaller bubbles = Smaller wins or losses How It Organizes Your Trades: Like a Photo Album: Instead of showing all your trades at once (which would be messy), it shows them in "pages" of 500 trades each: Page 1: Your first 500 trades Page 2: Trades 501-1000 Page 3: Trades 1001-1500, etc. What the Numbers Tell You: Average Win: How much money you typically make on winning trades Average Loss: How much money you typically lose on losing trades Expected Value (EV): Whether your trading system makes money over time Positive EV = Your system is profitable long-term Negative EV = Your system loses money long-term Payoff Ratio (R): How your average win compares to your average loss R > 1 = Your wins are bigger than your losses R < 1 = Your losses are bigger than your wins Why This Matters: At a Glance: You can instantly see if you're a profitable trader or not Pattern Recognition: Spot if you have more big wins than big losses Performance Tracking: Watch how your trading improves over time Realistic Expectations: Understand what "average" performance looks like for your system The Cool Visual Effects: Animation: The bubbles glow and shimmer to make the chart more engaging Highlighting: Your biggest wins and losses get extra attention with special effects Tooltips: hover any bubble to see details about that specific trade. What are the underlying calculations? The indicator processes trade PnL data using a dual-matrix architecture for optimal performance: Dual-Matrix System: • Display Matrix (display_matrix): Bounded to 500 trades for rendering performance • Statistics Matrix (stats_matrix): Unbounded storage for complete statistical accuracy Trade Classification & Aggregation: // Separate wins, losses, and break-even trades if val > 0.0 pos_sum += val // Sum winning trades pos_count += 1 // Count winning trades else if val < 0.0 neg_sum += val // Sum losing trades neg_count += 1 // Count losing trades else zero_count += 1 // Count break-even trades Statistical Averages: avg_win = pos_count > 0 ? pos_sum / pos_count : na avg_loss = neg_count > 0 ? math.abs(neg_sum) / neg_count : na Win/Loss Rates: total_obs = pos_count + neg_count + zero_count win_rate = pos_count / total_obs loss_rate = neg_count / total_obs Expected Value (EV): ev_value = (avg_win × win_rate) - (avg_loss × loss_rate) Payoff Ratio (R): R = avg_win ÷ |avg_loss| Contribution Analysis: ev_pos_contrib = avg_win × win_rate // Positive EV contribution ev_neg_contrib = avg_loss × loss_rate // Negative EV contribution How to integrate with any trading strategy? Equity Change Tracking Method: //@version=6 strategy("Your Strategy with Equity Change Export", overlay=true) float prev_trade_equity = na float equity_change_pct = na if barstate.isconfirmed and na(prev_trade_equity) prev_trade_equity := strategy.equity trade_just_closed = strategy.closedtrades != strategy.closedtrades if trade_just_closed and not na(prev_trade_equity) current_equity = strategy.equity equity_change_pct := ((current_equity - prev_trade_equity) / prev_trade_equity) * 100 prev_trade_equity := current_equity else equity_change_pct := na plot(equity_change_pct, "Equity Change %", display=display.data_window) Integration Steps: 1. Add equity tracking code to your strategy 2. Load both strategy and PnL Bubble indicator on the same chart 3. In bubble indicator settings, select your strategy's equity tracking output as data source 4. Configure visualization preferences (colors, effects, page navigation) How does the pagination system work? The indicator uses an intelligent pagination system to handle large trade datasets efficiently: Page Organization: • Page 1: Trades 1-500 (most recent) • Page 2: Trades 501-1000 • Page 3: Trades 1001-1500 • Page N: Trades to Example: With 1,500 trades total (3 pages available): • User selects Page 1: Shows trades 1-500 • User selects Page 4: Automatically falls back to Page 3 (trades 1001-1500) 5. Understanding the Visual Elements Bubble Visualization: • Color Coding: Cyan/blue gradients for wins, red gradients for losses • Size Mapping: Bubble size proportional to trade magnitude (larger = bigger P&L) • Priority Rendering: Largest trades displayed first to ensure visibility • Gradient Effects: Color intensity increases with trade magnitude within each category Interactive Tooltips: Each bubble displays quantitative trade information: tooltip_text = outcome + " | PnL: " + pnl_str + " Date: " + date_str + " " + time_str + " Trade #" + str.tostring(trade_number) + " (Page " + str.tostring(active_page) + ")" + " Rank: " + str.tostring(rank) + " of " + str.tostring(n_display_rows) + " Percentile: " + str.tostring(percentile, "#.#") + "%" + " Magnitude: " + str.tostring(magnitude_pct, "#.#") + "%" Example Tooltip: Win | PnL: +2.45% Date: 2024.03.15 14:30 Trade #1,247 (Page 3) Rank: 5 of 347 Percentile: 98.6% Magnitude: 85.2% Reference Lines & Statistics: • Average Win Line: Horizontal reference showing typical winning trade size • Average Loss Line: Horizontal reference showing typical losing trade size • Zero Line: Threshold separating wins from losses • Statistical Labels: EV, R-Ratio, and contribution analysis displayed on chart What do the statistical metrics mean? Expected Value (EV): Represents the mathematical expectation per trade in percentage terms EV = (Average Win × Win Rate) - (Average Loss × Loss Rate) Interpretation: • EV > 0: Profitable system with positive mathematical expectation • EV = 0: Break-even system, profitability depends on execution • EV < 0: Unprofitable system with negative mathematical expectation Example: EV = +0.34% means you expect +0.34% profit per trade on average Payoff Ratio (R): Quantifies the risk-reward relationship of your trading system R = Average Win ÷ |Average Loss| Interpretation: • R > 1.0: Wins are larger than losses on average (favorable risk-reward) • R = 1.0: Wins and losses are equal in magnitude • R < 1.0: Losses are larger than wins on average (unfavorable risk-reward) Example: R = 1.5 means your average win is 50% larger than your average loss Contribution Analysis (Σ): Breaks down the components of expected value Positive Contribution (Σ+) = Average Win × Win Rate Negative Contribution (Σ-) = Average Loss × Loss Rate Purpose: • Shows how much wins contribute to overall expectancy • Shows how much losses detract from overall expectancy • Net EV = Σ+ - Σ- (Expected Value per trade) Example: Σ+: 1.23% means wins contribute +1.23% to expectancy Example: Σ-: -0.89% means losses drag expectancy by -0.89% Win/Loss Rates: Win Rate = Count(Wins) ÷ Total Trades Loss Rate = Count(Losses) ÷ Total Trades Shows the probability of winning vs losing trades Higher win rates don't guarantee profitability if average losses exceed average wins 7. Demo Mode & Synthetic Data Generation When using built-in sources (close, open, etc.), the indicator generates realistic demo trades for testing: if isBuiltInSource(source_data) // Generate random trade outcomes with realistic distribution u_sign = prand(float(time), float(bar_index)) if u_sign < 0.5 v_push := -1.0 // Loss trade else // Skewed distribution favoring smaller wins (realistic) u_mag = prand(float(time) + 9876.543, float(bar_index) + 321.0) k = 8.0 // Skewness factor t = math.pow(u_mag, k) v_push := 2.5 + t * 8.0 // Win trade Demo Characteristics: • Realistic win/loss distribution mimicking actual trading patterns • Skewed distribution favoring smaller wins over large wins • Deterministic randomness for consistent demo results • Includes jitter effects to prevent visual overlap 8. Performance Limitations & Optimizations Display Constraints: points_count = 500 // Maximum 500 dots per page for optimal performance Pine Script v6 Limits: • Label Count: Maximum 500 labels per indicator • Line Count: Maximum 100 lines per indicator • Box Count: Maximum 50 boxes per indicator • Matrix Size: Efficient memory management with dual-matrix system Optimization Strategies: • Pagination System: Handle unlimited trades through 500-trade pages • Priority Rendering: Largest trades displayed first for maximum visibility • Dual-Matrix Architecture: Separate display (bounded) from statistics (unbounded) • Smart Fallback: Automatic page clamping prevents empty displays Impact & Workarounds: • Visual Limitation: Only 500 trades visible per page • Statistical Accuracy: Complete dataset used for all calculations • Navigation: Use page input to browse through entire trade history • Performance: Smooth operation even with thousands of trades 9. Statistical Accuracy Guarantees Data Integrity: • Complete Dataset: Statistics matrix stores ALL trades without limit • Proper Aggregation: Separate tracking of wins, losses, and break-even trades • Mathematical Precision: Pine Script v6's enhanced floating-point calculations • Dual-Matrix System: Display limitations don't affect statistical accuracy Calculation Validation: // Verified formulas match standard trading mathematics avg_win = pos_sum / pos_count // Standard average calculation win_rate = pos_count / total_obs // Standard probability calculation ev_value = (avg_win * win_rate) - (avg_loss * loss_rate) // Standard EV formula Accuracy Features: • Mathematical Correctness: Formulas follow established trading statistics • Data Preservation: Complete dataset maintained for all calculations • Precision Handling: Proper rounding and boundary condition management • Real-Time Updates: Statistics recalculated on every new trade 10. Advanced Technical Features Real-Time Animation Engine: // Shimmer effects with sine wave modulation offset = math.sin(shimmer_t + phase) * amp // Dynamic transparency with organic flicker new_transp = math.min(flicker_limit, math.max(-flicker_limit, cur_transp + dir * flicker_step)) • Sine Wave Shimmer: Dynamic glowing effects on bubbles • Organic Flicker: Random transparency variations for natural feel • Extreme Value Highlighting: Special visual treatment for outliers • Smooth Animations: Tick-based updates for fluid motion Magnitude-Based Priority Rendering: // Sort trades by magnitude for optimal visual hierarchy sort_indices_by_magnitude(values_mat) • Largest First: Most important trades always visible • Intelligent Sorting: Custom bubble sort algorithm for trade prioritization • Performance Optimized: Efficient sorting for real-time updates • Visual Hierarchy: Ensures critical trades never get hidden Professional Tooltip System: • Quantitative Data: Pure numerical information without interpretative language • Contextual Ranking: Shows trade position within page dataset • Percentile Analysis: Performance ranking as percentage • Magnitude Scaling: Relative size compared to page maximum • Professional Format: Clean, data-focused presentation 11. Quick Start Guide Step 1: Add Indicator • Search for "PnL Bubble | Fractalyst" in TradingView indicators • Add to your chart (works on any timeframe) Step 2: Configure Data Source • Demo Mode: Leave source as "close" to see synthetic trading data • Strategy Mode: Select your strategy's PnL% output as data source Step 3: Customize Visualization • Colors: Set positive (cyan), negative (red), and neutral colors • Page Navigation: Use "Trade Page" input to browse trade history • Visual Effects: Built-in shimmer and animation effects are enabled by default Step 4: Analyze Performance • Study bubble patterns for win/loss distribution • Review statistical metrics: EV, R-Ratio, Win Rate • Use tooltips for detailed trade analysis • Navigate pages to explore full trade history Step 5: Optimize Strategy • Identify outlier trades (largest bubbles) • Analyze risk-reward profile through R-Ratio • Monitor Expected Value for system profitability • Use contribution analysis to understand win/loss impact 12. Why Choose PnL Bubble Indicator? Unique Advantages: • Advanced Pagination: Handle unlimited trades with smart fallback system • Dual-Matrix Architecture: Perfect balance of performance and accuracy • Professional Statistics: Institution-grade metrics with complete data integrity • Real-Time Animation: Dynamic visual effects for engaging analysis • Quantitative Tooltips: Pure numerical data without subjective interpretations • Priority Rendering: Intelligent magnitude-based display ensures critical trades are always visible Technical Excellence: • Built with Pine Script v6 for maximum performance and modern features • Optimized algorithms for smooth operation with large datasets • Complete statistical accuracy despite display optimizations • Professional-grade calculations matching institutional trading analytics Practical Benefits: • Instantly identify system profitability through visual patterns • Spot outlier trades and risk management issues • Understand true risk-reward profile of your strategies • Make data-driven decisions for strategy optimization • Professional presentation suitable for performance reporting Disclaimer & Risk Considerations: Important: Historical performance metrics, including positive Expected Value (EV), do not guarantee future trading success. Statistical measures are derived from finite sample data and subject to inherent limitations: • Sample Bias: Historical data may not represent future market conditions or regime changes • Ergodicity Assumption: Markets are non-stationary; past statistical relationships may break down • Survivorship Bias: Strategies showing positive historical EV may fail during different market cycles • Parameter Instability: Optimal parameters identified in backtesting often degrade in forward testing • Transaction Cost Evolution: Slippage, spreads, and commission structures change over time • Behavioral Factors: Live trading introduces psychological elements absent in backtesting • Black Swan Events: Extreme market events can invalidate statistical assumptions instantaneously
Pine Script® göstergesi
Fractalyst tarafından
2
Bullish Single Candle Patterns [Crypto Varthagam]Description - This indicator highlights three well-known single bullish candlestick signals: Hammer – A small body with a long lower wick, often signaling potential reversal at the bottom of a downtrend. Inverted Hammer – A small body with a long upper wick, showing potential reversal if followed by bullish confirmation. Bullish Marubozu – A strong green candle with little to no shadows, representing clear buyer dominance. How it works: - The script measures candle body size relative to total range and wick size. - It identifies patterns based on common candlestick rules (wick-to-body ratios and body position). - Labels are plotted on the chart for easy recognition of these signals. Unique aspects of this script: -Clean, educational implementation focused only on three key single-candle bullish patterns. - Uses precise mathematical ratios for consistent detection. - Lightweight design that can be applied on any timeframe or asset. Disclaimer: This script is for educational purposes only. It does not provide financial advice. Always confirm signals with broader analysis, risk management, and additional tools before making trading decisions.
Pine Script® göstergesi
cryptovarthagam tarafından
Bullish & Bearish Engulfing Finder [Crypto Varthagam]Overview This script is designed to automatically detect Bullish and Bearish Engulfing Candlestick Patterns directly on your TradingView chart. Engulfing patterns are widely used in price action trading as potential reversal signals. Features - Detects both Bullish Engulfing and Bearish Engulfing patterns. - Option to require a prior trend filter (configurable consecutive bars) Flexible engulfing detection: - Strict mode (body must fully cover the previous candle’s body). - Ratio mode (current body must be at least X times larger). - Optional volume confirmation (engulfing candle volume > SMA × multiplier). - Clear chart labels and optional background highlights. - Built-in alert conditions for automated notifications. - Lightweight, clean, and open-source for the community. Why It’s Unique - Unlike many engulfing detectors, this script gives you full control over detection rules. You can fine-tune strictness, require prior trends, or add volume conditions to filter out weak signals. Both bullish and bearish engulfing patterns are supported in one script, keeping your chart clean. Housekeeping & Policy Notes - This script is for educational purposes only. It does not provide financial advice or guaranteed trading signals. - Always combine candlestick patterns with proper risk management and your own strategy. - Fully open-source: feel free to study, learn, and adapt it for your needs. Alerts - “Bullish Engulfing Detected” - “Bearish Engulfing Detected”
Pine Script® göstergesi
cryptovarthagam tarafından
Volume Profile + Pivot Levels [ChartPrime]⯁ OVERVIEW Volume Profile + Pivot Levels combines a rolling volume profile with price pivots to surface the most meaningful levels in your selected lookback window. It builds a left-side profile from traded volume, highlights the session’s Point of Control (PoC) , and then filters pivot highs/lows so only those aligned with significant profile volume are promoted to chart levels. Each promoted level extends forward until price retests it—so your chart stays focused on levels that actually matter. ⯁ KEY FEATURES Rolling Volume Profile (Period & Resolution) Calculates a profile over the last Period bars (default 200). The profile is discretized into Volume Profile Resolution bins (default 50) between the highest high and lowest low inside the window. Each bin accumulates traded volume and is drawn as a smooth left-side polyline for compact, lightweight rendering. HL = array.new() // collect highs/lows over 'start' bars to define profile range for i = 0 to start - 1 HL.push(high ), HL.push(low ) H = HL.max(), L = HL.min() bin_size = (H - L) / bins // accumulate per-bin volume for i = 0 to bins - 1 for j = 0 to start - 1 if close >= (L + bin_sizei) - bin_size and close < (L + bin_size*(i+1)) + bin_size Bins += volume Delta-Aware Coloring The script tracks up-minus-down volume across all period to compute a net Delta . The profile, PoC line, and PoC label adopt a teal tone when net positive, and maroon when net negative—an immediate read on buyer/seller dominance inside the window. Point of Control (PoC) + Volume Label Automatically marks the highest-volume bin as the PoC . A horizontal PoC line extends to the last bar, and a label shows the absolute volume at the PoC. Toggle visibility via PoC input. Pivot Detection with Volume Filter Identifies raw pivots using Length (default 10) on both sides of the bar. Each candidate pivot is then validated against the profile: only pivots that land within their bin and meet or exceed the Filter % threshold (percentage of PoC volume) are promoted to chart levels. This removes weak, low-participation pivots. // pivot promotion when volume% >= pivotFilter if abs(mid - p.value) <= bin_size and volPercent >= pivotFilter // draw labeled pivot level line.new(p.index - pivotLength, p.value, p.index + pivotLength, p.value, width = 2) Forward-Extending, Self-Stopping Levels Promoted pivot levels extend forward as dotted rays. As soon as price intersects a level (high/low straddles it), that level stops extending—so your chart doesn’t clutter with stale zones. Concise Level Labels (Volume + %) Each promoted pivot prints a compact label at the pivot bar with its bin’s absolute volume and percentage of PoC volume (ordering flips for highs vs. lows for quick read). Lightweight Visuals The volume profile is rendered as a smooth polyline rather than dozens of boxes, keeping charts responsive even at higher resolutions. ⯁ SETTINGS Volume Profile → Period : Lookback window used to compute the profile (max 500). Volume Profile → Resolution : Number of bins; higher = finer structure. Volume Profile → PoC : Toggle PoC line and volume label. Pivots → Display : Show/hide volume-validated pivot levels. Pivots → Length : Pivot detection left/right bars. Pivots → Filter % 0–100 : Minimum bin strength (as % of PoC) required to promote a pivot level. ⯁ USAGE Read PoC direction/color for a quick net-flow bias within your window. Prioritize promoted pivot levels —they’re backed by meaningful participation. Watch for first retests of promoted levels; the line will stop extending once tested. Adjust Period / Resolution to match your timeframe (scalps → higher resolution, shorter period; swings → lower resolution, longer period). Tighten or loosen Filter % to control how selective the level promotion is. ⯁ WHY IT’S UNIQUE Instead of plotting every pivot or every profile bar, this tool cross-checks pivots against the profile’s internal volume weighting . You only see levels where price structure and liquidity overlap—clean, data-driven levels that self-retire after interaction, so you can focus on what the market actually defends.
Pine Script® göstergesi
ChartPrime tarafından
22
Competition Signals — GBPUSD M15 (Manual)Here’s a brief and clear rundown on how to privately share your TradingView indicator: Quick Guide: Share a Private TradingView Indicator 1. You Need a Premium Account Only users with a Premium TradingView subscription can publish invite-only scripts, which allow private sharing. You can identify invite-only scripts by a lock icon next to the script’s name.  2. Publish Your Script as Invite-Only • Open your indicator in the Pine Editor. • Click “Publish Script”, choose “Private” visibility, then select Invite-Only as the access type.  • After publishing, a “Manage Access” button will appear on your script page, letting you control which TradingView users can use it.  3. Grant Access to Others • Use the “Manage Access” section to add specific TradingView usernames. • Those added will be able to see the script under their “Invite-Only Scripts” tab in their Indicators panel.  4. Privacy & Control Maintained • Invite-Only scripts are closed-source: Users can’t view or copy your code.  • You retain full control—only those you authorize can use it. Summary Table Step Action 1. Premium Required Needed to publish invite-only scripts 2. Publish Invite-Only Via Pine Editor → “Publish Script” → Invite-Only 3. Manage Access Use “Manage Access” to add users 4. Users Access They access via the “Invite-Only Scripts” tab 5. Code Privacy Script is hidden; users can’t see or copy it Let me know if you’d like help walking through these steps or setting up permissions for multiple users!
Pine Script® göstergesi
Harryford32 tarafından
Intrabar Volume Delta — RealTime + History (Stocks/Crypto/Forex)Intrabar Volume Delta Grid — RealTime + History (Stocks/Crypto/Forex) # Short Description Shows intrabar Up/Down volume, Delta (absolute/relative) and UpShare% in a compact grid for both real-time and historical bars. Includes an MTF (M1…D1) dashboard, contextual coloring, density controls, and alerts on Δ and UpShare%. Smart historical splitting (“History Mode”) for Crypto/Futures/FX. --- # What it does (Quick) * **UpVol / DownVol / Δ / UpShare%** — visualizes order-flow inside each candle. * **Real-time** — accumulates intrabar volume live by tick-direction. * **History Mode** — splits Up/Down on closed bars via simple or range-aware logic. * **MTF Dashboard** — one table view across M1, M5, M15, M30, H1, H4, D1 (Vol, Up/Down, Δ%, Share, Trend). * **Contextual opacity** — stronger signals appear bolder. * **Label density** — draw every N-th bar and limit to last X bars for performance. * **Alerts** — thresholds for |Δ|, Δ%, and UpShare%. --- # How it works (Real-Time vs History) * **Real-time (open bar):** volume increments into **UpVolRT** or **DownVolRT** depending on last price move (↑ goes to Up, ↓ to Down). This approximates live order-flow even when full tick history isn’t available. * **History (closed bars):** * **None** — no split (Up/Down = 0/0). Safest for equities/indices with unreliable tick history. * **Approx (Close vs Open)** — all volume goes to candle direction (green → Up 100%, red → Down 100%). Fast but yields many 0/100% bars. * **Price Action Based** — splits by Close position within High-Low range; strength = |Close−mid|/(High−Low). Above mid → more Up; below mid → more Down. Falls back to direction if High==Low. * **Auto** — **Stocks/Index → None**, **Crypto/Futures/FX → Approx**. If you see too many 0/100 bars, switch to **Price Action Based**. --- # Rows & Meaning * **Volume** — total bar volume (no split). * **UpVol / DownVol** — directional intrabar volume. * **Delta (Δ)** — UpVol − DownVol. * **Absolute**: raw units * **Relative (Δ%)**: Δ / (Up+Down) × 100 * **Both**: shows both formats * **UpShare%** — UpVol / (Up+Down) × 100. >50% bullish, <50% bearish. * Helpful icons: ▲ (>65%), ▼ (<35%). --- # MTF Dashboard (🔧 Enable Dashboard) A single table with **Vol, Up, Down, Δ%, Share, Trend (🔼/🔽/⏭️)** for selected timeframes (M1…D1). Great for a fast “panorama” read of flow alignment across horizons. --- # Inputs (Grouped) ## Display * Toggle rows: **Volume / Up / Down / Delta / UpShare** * **Delta Display**: Absolute / Relative / Both ## Realtime & History * **History Mode**: Auto / None / Approx / Price Action Based * **Compact Numbers**: 1.2k, 1.25M, 3.4B… ## Theme & UI * **Theme Mode**: Auto / Light / Dark * **Row Spacing**: vertical spacing between rows * **Top Row Y**: moves the whole grid vertically * **Draw Guide Lines**: faint dotted guides * **Text Size**: Tiny / Small / Normal / Large ## 🔧 Dashboard Settings * **Enable Dashboard** * **📏 Table Text Size**: Tiny…Huge * **🦓 Zebra Rows** * **🔲 Table Border** ## ⏰ Timeframes (for Dashboard) * **M1…D1** toggles ## Contextual Coloring * **Enable Contextual Coloring**: opacity by signal strength * **Δ% cap / Share offset cap**: saturation caps * **Min/Max transparency**: solid vs faint extremes ## Label Density & Size * **Show every N-th bar**: draw labels only every Nth bar * **Limit to last X bars**: keep labels only in the most recent X bars ## Colors * Up / Down / Text / Guide ## Alerts * **Delta Threshold (abs)** — |Δ| in volume units * **UpShare > / <** — bullish/bearish thresholds * **Enable Δ% Alert**, **Δ% > +**, **Δ% < −** — relative delta levels --- # How to use (Quick Start) 1. Add the indicator to your chart (overlay=false → separate pane). 2. **History Mode**: * Crypto/Futures/FX → keep **Auto** or switch to **Price Action Based** for richer history. * Stocks/Index → prefer **None** or **Price Action Based** for safer splits. 3. **Label Density**: start with **Limit to last X bars = 30–150** and **Show every N-th bar = 2–4**. 4. **Contextual Coloring**: keep on to emphasize strong Δ% / Share moves. 5. **Dashboard**: enable and pick only the TFs you actually use. 6. **Alerts**: set thresholds (ideas below). --- # Alerts (in TradingView) Add alert → pick this indicator → choose any of: * **Delta exceeds threshold** (|Δ| > X) * **UpShare above threshold** (UpShare% > X) * **UpShare below threshold** (UpShare% < X) * **Relative Delta above +X%** * **Relative Delta below −X%** **Starter thresholds (tune per symbol & TF):** * **Crypto M1/M5**: Δ% > +25…35 (bullish), Δ% < −25…−35 (bearish) * **FX (tick volume)**: UpShare > 60–65% or < 40–35% * **Stocks (liquid)**: set **Absolute Δ** by typical volume scale (e.g., 50k / 100k / 500k) --- # Notes by Market Type * **Crypto/Futures**: 24/7 and high liquidity — **Price Action Based** often gives nicer history splits than Approx. * **Forex (FX)**: TradingView volume is typically **tick volume** (not true exchange volume). Treat Δ/Share as tick-based flow, still very useful intraday. * **Stocks/Index**: historical tick detail can be limited. **None** or **Price Action Based** is a safer default. If you see too many 0/100% shares, switch away from Approx. --- # “All Timeframes” accuracy * Works on **any TF** (M1 → D1/W1). * **Real-time accuracy** is strong for the open bar (live accumulation). * **Historical accuracy** depends on your **History Mode** (None = safest, Approx = fastest/simplest, Price Action Based = more nuanced). * The MTF dashboard uses `request.security` and therefore follows the same logic per TF. --- # Trade Ideas (Use-Cases) * **Scalping (M1–M5)**: a spike in Δ% + UpShare>65% + rising total Vol → momentum entries. * **Intraday (M5–M30–H1)**: when multiple TFs show aligned Δ%/Share (e.g., M5 & M15 bullish), join the trend. * **Swing (H4–D1)**: persistent Δ% > 0 and UpShare > 55–60% → structural accumulation bias. --- # Advantages * **True-feeling live flow** on the open bar. * **Adaptable history** (three modes) to match data quality. * **Clean visual layout** with guides, compact numbers, contextual opacity. * **MTF snapshot** for quick bias read. * **Performance controls** (last X bars, every N-th bar). --- # Limitations & Care * **FX uses tick volume** — interpret Δ/Share accordingly. * **History Mode is an approximation** — confirm with trend/structure/liquidity context. * **Illiquid symbols** can produce noisy or contradictory signals. * **Too many labels** can slow charts → raise N, lower X, or disable guides. --- # Best Practices (Checklist) * Crypto/Futures: prefer **Price Action Based** for history. * Stocks: **None** or **Price Action Based**; be cautious with **Approx**. * FX: pair Δ% & UpShare% with session context (London/NY) and volatility. * If labels overlap: tweak **Row Spacing** and **Text Size**. * In the dashboard, keep only the TFs you actually act on. * Alerts: start around **Δ% 25–35** for “punchy” moves, then refine per asset. --- # FAQ **1) Why do some closed bars show 0%/100% UpShare?** You’re on **Approx** history mode. Switch to **Price Action Based** for smoother splits. **2) Δ% looks strong but price doesn’t move — why?** Δ% is an **order-flow** measure. Price also depends on liquidity pockets, sessions, news, higher-timeframe structure. Use confirmations. **3) Performance slowdown — what to do?** Lower **Limit to last X bars** (e.g., 30–100), increase **Show every N-th bar** (2–6), or disable **Draw Guide Lines**. **4) Dashboard values don’t “match” the grid exactly?** Dashboard is multi-TF via `request.security` and follows the history logic per TF. Differences are normal. --- # Short “Store” Marketing Blurb Intrabar Volume Delta Grid reveals the order-flow inside every candle (Up/Down, Δ, UpShare%) — live and on history. With smart history splitting, an MTF dashboard, contextual emphasis, and flexible alerts, it helps you spot momentum and bias across Crypto, Forex (tick volume), and Stocks. Tidy labels and compact numbers keep the panel readable and fast.
Pine Script® göstergesi
a_jabbaroff tarafından
K線虛擬幣// This source code is subject to the terms of the Mozilla Public License 2.0 at mozilla.org // © dear.simpson //@version=5 indicator("月季線視覺操盤", "", true) // Getting inputs length = input(5, "操盤線週期") // Calculating ma = ta.sma(close, length) spread = close-ma // Plotcandle plotcandle(open, high, low, close, title='操盤K線', editable = false , display =display.pane+display.price_scale , color = (spread>=0 ? #ef5350 : #26a69a) , bordercolor= (spread>=0 ? #ef5350 : #26a69a) , wickcolor = #5d606b) // Getting inputs maPeriods1 = input( 5 , "MA 1" , group="移動平均線") maPeriods2 = input(20 , "MA 2" , group="移動平均線") maPeriods3 = input(60 , "MA 3" , group="移動平均線") line0 = ta.sma(close, 2) line1 = ta.sma(close, maPeriods1) line2 = ta.sma(close, maPeriods2) line3 = ta.sma(close, maPeriods3) // Plot Moving Average Line p0PlotID = plot(line0 ,"MA 0" , color.new(color.black ,100), display = display.none , editable = false) p1PlotID = plot(line1 ,"MA 1" , color.new(#787b86, 50), display = display.pane+display.price_scale ) p2PlotID = plot(line2 ,"MA 2" , color.new(#787b86, 0), display = display.pane+display.price_scale ) p3PlotID = plot(line3 ,"MA 3" , color.new(color.blue , 30), display = display.pane+display.price_scale ) // Plot Zone Color fill(p0PlotID, p2PlotID, close > line2 ? color.new(#ef5350, 70) : color.new(#26a69a, 90), '高/低於月線區域顏色') fill(p0PlotID, p3PlotID, close > line3 ? color.new(#ef5350, 70) : color.new(#26a69a, 90), '高/低於季線區域顏色' , display = display.none )
Pine Script® göstergesi
hung099kj tarafından
Student wyckoff rs symbol/moexRelative Strength Indicator Student wyckoff rs symbol/market v.2 Description The Relative Strength (RS) Indicator compares the price performance of the current financial instrument (e.g., a stock) against another instrument (e.g., an index or another stock). It is calculated by dividing the closing price of the first instrument by the closing price of the second, then multiplying by 100. This provides a percentage ratio that shows how one instrument outperforms or underperforms another. The indicator helps traders identify strong or weak assets, spot market leaders, or evaluate an asset’s performance relative to a benchmark. Key Features Relative Strength Calculation: Divides the closing price of the current instrument by the closing price of the second instrument and multiplies by 100 to express the ratio as a percentage. Simple Moving Average (SMA): Applies a customizable Simple Moving Average (default period: 14) to smooth the data and highlight trends. Visualization: Displays the Relative Strength as a blue line, the SMA as an orange line, and colors bars (blue for rising, red for falling) to indicate changes in relative strength. Flexibility: Allows users to select the second instrument via an input field and adjust the SMA period. Applications Market Comparison: Assess whether a stock is outperforming an index (e.g., S&P 500 or MOEX) to identify strong assets for investment. Sector Analysis: Compare stocks within a sector or against a sector ETF to pinpoint leaders. Trend Analysis: Use the rise or fall of the RS line and its SMA to gauge the strength of an asset’s trend relative to another instrument. Trade Timing: Bar coloring helps quickly identify changes in relative strength, aiding short-term trading decisions. Interpretation Rising RS: Indicates the first instrument is outperforming the second (e.g., a stock growing faster than an index). Falling RS: Suggests the first instrument is underperforming. SMA as a Trend Filter: If the RS line is above the SMA, it may signal strengthening performance; if below, weakening performance. Settings Instrument 2: Ticker of the second instrument (default: QQQ). SMA Period: Period for the Simple Moving Average (default: 14). Notes The indicator works on any timeframe but requires accurate ticker input for the second instrument. Ensure data for both instruments is available on the selected timeframe for precise analysis.
Pine Script® göstergesi
StudentWyckoff tarafından