Mulakan

Corak carta

EMA/VWAP/Volume/MACD指标// === 控制输出 === macd_plot_line = show_macd ? macd_line : na macd_signal_plot = show_macd ? signal_line : na macd_hist_plot = show_macd ? hist_line : na adx_plot_line = show_adx ? adx : na plusdi_plot_line = show_adx ? diplus : na minusdi_plot_line = show_adx ? diminus : na // === 绘制 MACD === plot(macd_plot_line, title="MACD Line", color=color.new(color.aqua, 0)) plot(macd_signal_plot, title="Signal Line", color=color.new(color.orange, 0)) plot(macd_hist_plot, title="Histogram", style=plot.style_columns, color=macd_hist_plot >= 0 ? color.new(color.green, 0) : color.new(color.red, 0))
Penunjuk Pine Script®
oleh jason823222
MACD-V with RSI Gradient## Overview MACD-V is a volatility-adjusted momentum indicator that normalizes MACD using ATR. This version adds a dynamic RSI-based background gradient to highlight momentum zones visually. ## Features - **MACD-V Line**: EMA-based momentum normalized by ATR - **Signal Line**: EMA of MACD-V - **Histogram**: Color-coded based on slope and polarity - **RSI Gradient Background**: Shading from bright green (RSI > 75) to bright red (RSI < 30), with intermediate tones for momentum context ## Use Case Designed for 30-minute oil futures charts, this indicator helps identify: - Trend strength and reversals - Momentum zones using RSI shading - Pullback opportunities and exhaustion zones ## Inputs - Fast EMA (default: 12) - Slow EMA (default: 26) - Signal EMA (default: 9) - ATR Length (default: 26) ## Notes - RSI shading is purely visual—no alerts are wired in yet - Histogram renders behind MACD-V and Signal lines for clarity - Colors are tuned for dark charts ## Credits The MACD-v is an indicator created in 2015 by Alex Spiroglou and presented to the public in 2022 as a paper called: "𝗠𝗔𝗖𝗗-𝘃: 𝗩𝗼𝗹𝗮𝘁𝗶𝗹𝗶𝘁𝘆 𝗡𝗼𝗿𝗺𝗮𝗹𝗶𝘀𝗲𝗱 𝗠𝗼𝗺𝗲𝗻𝘁𝘂𝗺" It received the following Awards: 1. “𝐅𝐨𝐮𝐧𝐝𝐞𝐫𝐬 𝐀𝐰𝐚𝐫𝐝” (2022), for advances in Active Investment Management from the National Association of Active Investment Managers (NAAIM) 2. “𝐂𝐡𝐚𝐫𝐥𝐞𝐬 𝐇. 𝐃𝐨𝐰 𝐀𝐰𝐚𝐫𝐝” (2022) for outstanding research in Technical Analysis, from the Chartered Market Technicians Association (CMTA) The RSI Gradient was my idea, but quite frankly, if I go looking around I suppose I'll find that others had the same idea. This is the first time I've ever published any code, so if I stepped on anyone's toes. I'm sorry.
Penunjuk Pine Script®
oleh sylvarocks
1
(SPY to ES) ETF→Futures Multi-Level (10 Levels + Select All)Converts selected ETF levels (SPY or QQQ) into equivalent futures levels (ES or NQ). Uses live price ratio between ETF and futures for real-time level translation. Supports 10 independent levels (A–J) with user-defined ETF price inputs. Provides checkboxes to toggle each level’s visibility or show all at once. Applies smoothing (ta.sma) to reduce noise from short-term price movement. Lets user customize each line’s color, width, and style (solid, dashed, dotted). Automatically updates lines as new bars form without user interaction. Uses persistent line objects to keep levels stable when scrolling or zooming. Adapts to either SPY→ES or QQQ→NQ depending on the “Convert SPY?” toggle. Draws clean horizontal lines without legend clutter for visual precision. SOME ONE PUBLISHED THIS FUNCTIONALITY FOR A CHARGE SO I MADE IT FREE. -rA
Penunjuk Pine Script®
oleh vKnit
Asia Range Breakout Table (Narrowness) Asia Range Breakout Table (Narrowness) Overview The Asia Range Breakout Table (Narrowness) is a professional trading tool designed to analyze and display range characteristics across key Asian trading sessions. This indicator provides real-time visual feedback on market range narrowness, helping traders identify potential breakout opportunities based on historical range comparisons. Better to use in M5 or M15 timeframe. Key Features - Multi-Session Analysis : Tracks 6 crucial Asian market sessions: - ORB Pre (Tokyo Pre-open) - ORB First (Tokyo First) - Sydney Box - Tokyo Launch Box - 2nd Session Pre-Open - 2nd ORB (Tokyo 2nd Session) - Historical Comparison : Compares current session ranges against 44 days of historical data - Visual Color Coding : - 🟢 Narrowest (<10%) - Extremely compressed ranges - 🟢 Narrow (10-59%) - Below average ranges - 🟣 Normal (60-79%) - Typical range behavior - 🔴 Wide (≥80%) - Expanded range conditions - Customizable Display : Adjustable table position and text size - Session Toggle : Enable/disable individual sessions based on your trading focus How It Works The indicator calculates the high-low range for each defined session and ranks it against historical data using percentile analysis. This helps traders quickly identify: - Unusually narrow ranges that may indicate impending breakouts - Expanded ranges suggesting increased volatility - Normal range behavior for context Use Cases - Breakout Trading : Identify sessions with compressed ranges for potential breakout setups - Volatility Assessment : Gauge market conditions across different Asian sessions - Session Analysis : Understand range behavior during specific market hours - Risk Management : Adjust position sizing based on range characteristics Input Parameters - Session Toggles : Enable/disable individual session tracking - Table Position : Choose from four corner positions - Text Size : Adjust table readability (Tiny, Small, Normal, Big) Ideal For - Asian session traders - Breakout strategy enthusiasts - Volatility analysis - Multi-timeframe analysts - Professional and retail traders focusing on Asian markets Disclaimer This tool is for educational and informational purposes only. Past performance is not indicative of future results. Always conduct your own research and risk management before trading.
Penunjuk Pine Script®
oleh MahdiSalari8
FluxGate Daily Swing Strategy Summary in one paragraph FluxGate treats long and short as different ecosystems. It runs two independent engines so the long side can be bold when the tape rewards upside persistence while the short side can stay selective when downside is messy. The core reads three directional drivers from price geometry then removes overlap before gating with clean path checks. The complementary risk module anchors stop distance to a higher timeframe ATR so a unit means the same thing on SPY and BTC. It can add take profit breakeven and an ATR trail that only activates after the trade earns it. If a stop is hit the strategy can re enter in the same direction on the next bar with a daily retry cap that you control. Add it to a clean chart. Use defaults to see the intended behavior. For conservative workflows evaluate on bar close. Scope and intent • Markets. Large cap equities and liquid ETFs major FX pairs US index futures and liquid crypto pairs • Timeframes. From one minute to daily • Default demo in this publication. SPY on one day timeframe • Purpose. Reduce false starts without missing sustained trends by fusing independent drivers and suppressing activity when the path is noisy • Limits. This is a strategy. Orders are simulated on standard candles. Non standard chart types are not supported for execution Originality and usefulness • Unique fusion. FluxGate extracts three drivers that look at price from different angles. Direction measures slope of a smoothed guide and scales by realized volatility so a point of slope does not mean a different thing on different symbols. Persistence looks at short sign agreement to reward series of closes that keep direction. Curvature measures the second difference of a local fit to wake up during convex pushes. These three are then orthonormalized so a strong reading in one does not double count through another. • Gates that matter. Efficiency ratio prefers direct paths over treadmills. Entropy turns up versus down frequency into an information read. Light fractal cohesion punishes wrinkly paths. Together they slow the system in chop and allow it to open up when the path is clean. • Separate long and short engines. Threshold tilts adapt to the skew of score excursions. That lets long engage earlier when upside distribution supports it and keeps short cautious where downside surprise and venue frictions are common. • Practical risk behavior. Stops are ATR anchored on a higher timeframe so the unit is portable. Take profit is expressed in R so two R means the same concept across symbols. Breakeven and trailing only activate after a chosen R so early noise does not squeeze a good entry. Re entry after stop lets the system try again without you babysitting the chart. • Testability. Every major window and the aggression controls live in Inputs. There is no hidden magic number. Method overview in plain language Base measures • Return basis. Natural log of close over prior close for stability and easy aggregation through time. Realized volatility is the standard deviation of returns over a moving window. • Range basis for risk. ATR computed on a higher timeframe anchor such as day week or month. That anchor is steady across venues and avoids chasing chart specific quirks. Components • Directional intensity. Use an EMA of typical price as a guide. Take the day to day slope as raw direction. Divide by realized volatility to get a unit free measure. Soft clip to keep outliers from dominating. • Persistence. Encode whether each bar closed up or down. Measure short sign agreement so a string of higher closes scores better than a jittery sequence. This favors push continuity without guessing tops or bottoms. • Curvature. Fit a short linear regression and compute the second difference of the fitted series. Strong curvature flags acceleration that slope alone may miss. • Efficiency gate. Compare net move to path length over a gate window. Values near one indicate direct paths. Values near zero indicate treadmill behavior. • Entropy gate. Convert up versus down frequency into a probability of direction. High entropy means coin toss. The gate narrows there. • Fractal cohesion. A light read of path wrinkliness relative to span. Lower cohesion reduces the urge to act. • Phase assist. Map price inside a recent channel to a small signed bias that grows with confidence. This helps entries lean toward the right half of the channel without becoming a breakout rule. • Shock control. Compare short volatility to long volatility. When short term volatility spikes the shock gate temporarily damps activity so the system waits for pressure to normalize. Fusion rule • Normalize the three drivers after removing overlap • Blend with weights that adapt to your aggression input • Multiply by the gates to respect path quality • Smooth just enough to avoid jitter while keeping timing responsive • Compute an adaptive mean and deviation of the score and set separate long and short thresholds with a small tilt informed by skew sign • The result is one long score and one short score that can cross their thresholds at different times for the same tape which is a feature not a bug Signal rule • A long suggestion appears when the long score crosses above its long threshold while all gates are active • A short suggestion appears when the short score crosses below its short threshold while all gates are active • If any required gate is missing the state is wait • When a position is open the status is in long or in short until the complementary risk engine exits or your entry mode closes and flips Inputs with guidance Setup Long • Base length Long. Master window for the long engine. Typical range twenty four to eighty. Raising it improves selectivity and reduces trade count. Lowering it reacts faster but can increase noise • Aggression Long. Zero to one. Higher values make thresholds more permissive and shorten smoothing Setup Short • Base length Short. Master window for the short engine. Typical range twenty eight to ninety six • Aggression Short. Zero to one. Lower values keep shorts conservative which is often useful on upward drifting symbols Entries and UI • Entry mode. Both or Long only or Short only Complementary risk engine • Enable risk engine. Turns on bracket exits while keeping your signal logic untouched • ATR anchor timeframe. Day Week or Month. This sets the structural unit of stop distance • ATR length. Default fourteen • Stop multiple. Default one point five times the anchor ATR • Use take profit. On by default • Take profit in R. Default two R • Breakeven trigger in R. Default one R Usage recipes Intraday trend focus • Entry mode Both • ATR anchor Week • Aggression Long zero point five Aggression Short zero point three • Stop multiple one point five Take profit two R • Expect fewer trades that stick to directional pushes and skip treadmill noise Intraday mean reversion focus • Session windows optional if you add them in your copy • ATR anchor Day • Lower aggression both sides • Breakeven later and trailing later so the first bounce has room • This favors fade entries that still convert into trends when the path stays clean Swing continuation • Signal timeframe four hours or one day • Confirm timeframe one day if you choose to include bias • ATR anchor Week or Month • Larger base windows and a steady two R target • This accepts fewer entries and aims for larger holds Properties visible in this publication • Initial capital 25.000 • Base currency USD • Default order size percent of equity value three - 3% of the total capital • Pyramiding zero • Commission zero point zero three percent - 0.03% of total capital • Slippage five ticks • Process orders on close off • Recalculate after order is filled off • Calc on every tick off • Bar magnifier off • Any request security calls use lookahead off everywhere Realism and responsible publication • No performance promises. Past results never guarantee future outcomes • Fills and slippage vary by venue and feed • Strategies run on standard candles only • Shapes can update while a bar is forming and settle on close • Keep risk per trade sensible. Around one percent is typical for study. Above five to ten percent is rarely sustainable Honest limitations and failure modes • Sudden news and thin liquidity can break assumptions behind entropy and cohesion reads • Gap heavy symbols often behave better with a True Range basis for risk than a simple range • Very quiet regimes can reduce score contrast. Consider longer windows or higher thresholds when markets sleep • Session windows follow the exchange time of the chart if you add them • If stop and target can both be inside a single bar this strategy prefers stop first to keep accounting conservative Open source reuse and credits • No reused open source beyond public domain building blocks such as ATR EMA and linear regression concepts Legal Education and research only. Not investment advice. You are responsible for your decisions. Test on history and in simulation with realistic costs
Strategi Pine Script®
oleh exlux
Experimental Supertrend [CHE]Experimental Supertrend — Combines EMA crossovers for trend regime detection with an adaptive ATR-based hull that selects the narrowest band to contain recent highs and lows, minimizing false breaks in varying volatility. Summary This indicator overlays a dynamic supertrend boundary around a midline derived from dual EMAs, using EMA crossovers to switch between bullish and bearish regimes. The hull adapts by evaluating multiple ATR periods and selecting the tightest one that fully encloses price action over a specified window, which helps in creating more stable trend lines that hug price without excessive gaps or breaches. Fills between the midline and hull provide visual cues for trend strength, darkening temporarily after regime changes to highlight transitions. Alerts trigger on crossovers, and markers label entry points, making it suitable for trend-following setups where standard supertrends might whipsaw. Overall, it offers robustness through auto-adjustment, reducing sensitivity to noise while maintaining responsiveness to genuine shifts. Motivation: Why this design? Standard supertrend indicators often flip prematurely in choppy markets due to fixed multipliers that do not account for localized volatility patterns, leading to frequent false signals and eroded confidence in trends. This design addresses that by incorporating an EMA-based regime filter for directional bias and an auto-adaptive hull that dynamically tunes the band width based on recent price containment needs. By prioritizing the narrowest effective enclosure, it avoids over-wide bands in calm periods that cause lag or under-wide ones in volatility spikes that invite breaks, providing a more consistent trailing reference without manual tweaking. What’s different vs. standard approaches? - Reference baseline: Diverges from the classic ATR-multiplier supertrend, which uses a single fixed period and constant factor applied to close or high/low deviations. - Architecture differences: - Auto-selection from candidate ATR lengths to find the optimal period for current conditions. - Dynamic multiplier clamped between floor and cap values, adjusted by padding to ensure reliable containment. - Regime-gated rendering, where hull position flips based on EMA relative positioning. - Post-transition visual fading to emphasize change points without altering core logic. - Practical effect: Charts show tighter, more reactive bands that rarely breach during trends, reducing visual clutter from flips; the adaptive nature means less intervention across assets, as the hull self-adjusts to volatility clusters rather than applying a one-size-fits-all scale. How it works (technical) The indicator first computes two EMAs from close prices using lengths derived from a preset pair or manual inputs, establishing a midline as their average. This midline serves as the central reference for the hull. True range values are then smoothed into multiple ATR candidates using exponential weighting over the specified lengths. For each candidate, deviations of recent highs and lows from the midline are ratioed against the ATR to determine a required multiplier that would enclose all extremes in the containment window—the highest ratio plus padding sets the base, clamped to user-defined bounds. Among valid candidates (those with sufficient history), the one yielding the narrowest overall band width is selected. The hull boundaries are then offset from the midline by this multiplier times the chosen ATR, and further smoothed with a fixed EMA to reduce jitter. Regime direction from EMA comparison gates which boundary acts as support or resistance, with initialization seeding arrays on the first bar to handle state persistence. No higher timeframe data is used, so all logic runs on the chart's native bars without lookahead. Parameter Guide EMA Pair — Selects preset lengths for fast and slow EMAs, influencing regime sensitivity and midline stability. Default: "21/55". Trade-offs/Tips: Faster pairs like "9/21" increase cross frequency for scalping but raise false signals; slower like "50/200" smooths for swings, potentially missing early turns. Use Manual for fine control. Manual Fast — Sets fast EMA length when Manual mode is active; shorter values make regime switches quicker. Default: 21. Trade-offs/Tips: Lower than 10 risks over-reactivity; pair with slow at least double for clear separation. Manual Slow — Sets slow EMA length when Manual mode is active; longer values anchor the midline more firmly. Default: 55. Trade-offs/Tips: Above 100 adds lag in trends; balance with fast to avoid perpetual neutrality. ATR Lengths (comma-separated) — Defines candidate periods for ATR smoothing; more options allow finer auto-selection. Default: "7,10,14,21,28,35". Trade-offs/Tips: Fewer candidates speed computation but may miss optimal fits; keep under 10 for efficiency. Containment Window — Number of recent bars the hull must fully enclose highs/lows of; larger windows favor stability. Default: 50. Trade-offs/Tips: Shorter (under 20) adapts faster to breaks but increases breach risk; longer smooths but delays response. Min Multiplier Floor — Lowest allowed multiplier for hull width; prevents overly tight bands in low volatility. Default: 0.5. Trade-offs/Tips: Raise to 0.75 for conservative enclosures; too low allows pinches that flip easily. Max Multiplier Cap — Highest allowed multiplier; caps expansion in spikes to avoid wide, lagging bands. Default: 1.0. Trade-offs/Tips: Lower to 0.75 tightens overall; higher permits more room but risks detachment from price. Padding (+) — Adds buffer to the auto-multiplier for safer containment without exact touches. Default: 0.05. Trade-offs/Tips: Increase to 0.10 in gappy markets; minimal values hug closer but may still breach on outliers. Fill Between (Mid ↔ Supertrend) — Toggles shaded area between midline and active hull for trend visualization. Default: true. Trade-offs/Tips: Disable for cleaner charts; pairs well with transparency tweaks. Base Fill Transparency (0..100) — Sets default opacity of fills; higher values make them subtler. Default: 80. Trade-offs/Tips: Under 50 overwhelms price action; adjust with darken boost for emphasis. Darken on Trend Change — Enables temporary opacity increase after regime shifts to spotlight transitions. Default: true. Trade-offs/Tips: Off for steady visuals; on aids spotting reversals in real-time. Darken Fade Bars — Duration in bars for the darken effect to ramp back to base; longer prolongs highlight. Default: 8. Trade-offs/Tips: Shorter (4-6) for fast-paced charts; longer holds attention on changes. Darken Boost at Change (Δ transp) — Intensity of opacity reduction at crossover; higher values make shifts more prominent. Default: 50. Trade-offs/Tips: Cap at 70 to avoid blackout; tune down if fades obscure details. Show Supertrend Line — Displays the active hull boundary as a line. Default: true. Trade-offs/Tips: Hide for fill-only views; linewidth fixed at 3 for visibility. Show EMA Cross Markers — Places circles and labels at crossover points for entry cues. Default: true. Trade-offs/Tips: Disable in clutter; labels show "Buy"/"Sell" at absolute positions. Alert: EMA Cross Up (Long) — Triggers notification on bullish crossover. Default: true. Trade-offs/Tips: Pair with filters; once-per-bar frequency. Alert: EMA Cross Down (Short) — Triggers notification on bearish crossover. Default: true. Trade-offs/Tips: Use for exits; ensure broker integration. Show Debug — Reveals internal diagnostics like selected ATR details (if implemented). Default: false. Trade-offs/Tips: Enable for troubleshooting selections; minimal overhead. Reading & Interpretation Bullish regime shows a green line below price as support, with upward fill from midline; bearish uses red line above as resistance, downward fill. Crossovers flip the active boundary, marked by tiny green/red circles and "Buy"/"Sell" labels at the hull level. Fills start at base transparency but darken sharply at changes, fading over the specified bars to signal fresh momentum. If the hull rarely breaches during trends, containment is effective; frequent touches without flips indicate tight adaptation. Debug mode (when enabled) overlays text or plots for selected length and multiplier, helping verify auto-choices. Practical Workflows & Combinations - Trend following: Enter long on green "Buy" label above prior low structure; confirm with higher high. Trail stops along the green hull line, tightening as fills stabilize post-fade. - Exits/Stops: Conservative exit on opposite crossover or hull breach; aggressive hold until fade completes if volume supports. Use darken boost as a volatility cue—high delta suggests waiting for confirmation. - Multi-asset/Multi-TF: Defaults suit forex/stocks on 15m-4h; for crypto, widen containment to 75 for gaps. Layer on volume oscillator for cross filters; avoid on low-liquidity assets where ATR candidates skew. Behavior, Constraints & Performance Closed-bar logic ensures signals confirm at bar end, with live bars updating hull adaptively but no repaints since no future data or security calls are used. Arrays persist ATR states across bars, initialized once with candidates parsed from string. Small fixed loops (over 6 lengths max, inner up to 50) run per bar, capped by max_bars_back=500 for history needs. Resources stay low with 500 labels/lines limits, but dense charts may hit on markers. Known limits include initial lag until containment history builds (50+ bars), potential wide bands on gaps, and suboptimal selections if candidates omit ideal lengths. Sensible Defaults & Quick Tuning Start with "21/55" pair, 50-window, 0.5-1.0 multipliers, and 80% transparency for balanced responsiveness on daily charts. For too many flips, raise min floor to 0.75 or add lengths like "42"; for sluggishness, shorten window to 30 or pick faster pair. In high-vol environments, boost padding to 0.10; for smoother visuals, extend fade bars to 12. What this indicator is—and isn’t This is a visualization and signal layer for trend regime and adaptive boundaries, aiding entry/exit timing in directional markets. It is not a standalone system—pair with price structure, risk sizing, and broader context. Not predictive of turns, just reactive to containment and crosses. Disclaimer The content provided, including all code and materials, is strictly for educational and informational purposes only. It is not intended as, and should not be interpreted as, financial advice, a recommendation to buy or sell any financial instrument, or an offer of any financial product or service. All strategies, tools, and examples discussed are provided for illustrative purposes to demonstrate coding techniques and the functionality of Pine Script within a trading context. Any results from strategies or tools provided are hypothetical, and past performance is not indicative of future results. Trading and investing involve high risk, including the potential loss of principal, and may not be suitable for all individuals. Before making any trading decisions, please consult with a qualified financial professional to understand the risks involved. By using this script, you acknowledge and agree that any trading decisions are made solely at your discretion and risk. Do not use this indicator on Heikin-Ashi, Renko, Kagi, Point-and-Figure, or Range charts, as these chart types can produce unrealistic results for signal markers and alerts. Happy trading Chervolino
Penunjuk Pine Script®
oleh chervolino
Dollar Volume Ownership Gauge Dollar Volume Ownership Gauge (DVOG) By: Mando4_27 Version: 1.0 — Pine Script® v6 Overview The Dollar Volume Ownership Gauge (DVOG) is designed to measure the intensity of real money participation behind each price bar. Instead of tracking raw share volume, this tool converts every bar’s trading activity into dollar volume (price × volume) and highlights the transition points where institutional capital begins to take control of a move. DVOG’s mission is simple: Show when the crowd is trading vs. when the institutions are buying control. Core Concept Most retail traders focus on share count (volume) — but institutions think in dollar exposure. A small-cap printing a 1-million-share candle at $1 is very different from a 1-million-share candle at $10. DVOG normalizes this by displaying total traded dollar value per bar, then color-codes and alerts when the volume of money crosses key thresholds. This exposes the exact moments when ownership is shifting — often before major breakouts, reclaims, or exhaustion reversals. How It Works Dollar Volume Calculation Each candle’s dollar volume is computed as close × volume. Data is aggregated from the 5-minute timeframe regardless of your current chart, allowing consistent institutional-flow detection on any resolution. Threshold Logic Two customizable levels define interest zones: $500K Threshold → Early or moderate institutional attention. $1M Threshold → High-conviction or aggressive accumulation. Both levels can be edited to fit different market caps or trading styles. Bar Coloring Scheme Red = Dollar Volume ≥ $1,000,000 → Significant institutional activity / control bar. Green = Dollar Volume ≥ $500,000 and < $1,000,000 → Emerging accumulation / transition bar. Black = Below $500,000 → Retail or low-interest zone. (Colors are intentionally inverted from standard expectation: when volume intensity spikes, the bar turns hotter in tone.) Plot Display Histogram style plot displays 5-minute aggregated dollar volume per bar. Dotted reference lines mark $500K and $1M levels, with live right-hand labels for quick reading. Optional debug label shows current bar’s dollar value, closing price, and raw volume for transparency. Alerts & Conditions DVOG includes three alert triggers for hands-off monitoring: Alert Name Trigger Message Purpose Green Bar Alert – Dollar Volume ≥ $500K When dollar volume first crosses $500K “Institutional interest starting on ” Signals early money entering. Dollar Volume ≥ $500K Same as above, configurable “Early institutional interest detected…” Broad alert option. Dollar Volume ≥ $1M When dollar volume first crosses $1M “Significant money flow detected…” Indicates heavy institutional presence or ignition bar. You can enable or disable alerts via checkbox inputs, allowing you to monitor just the levels that fit your style. Interpretation & Use Cases Identify Institutional “Ignition” Points: Watch for sudden green or red DVOG bars after long low-volume consolidation — these often precede explosive continuation moves. Confirm Breakouts & Reclaims: If price reclaims a key level (HOD, neckline, or coil top) and DVOG flashes green/red, odds strongly favor follow-through. Spot Trap Exhaustion: After a flush or low-volume fade, the first strong green/red DVOG bar can mark the institutional reclaim — the moment retail control ends. Filter Noise: Ignore standard volume spikes. DVOG only reacts when dollar ownership materially changes hands, not when small traders churn shares. Customization Setting Default Description $500K Threshold 500,000 Lower limit for “Green” institutional attention. $1M Threshold 1,000,000 Upper limit for “Red” heavy institutional control. Show Alerts ✅ Enable or disable global alerts. Alert on Green Bars ✅ Toggle only the $500K crossover alerts. Adjust thresholds to match the liquidity of your preferred tickers — for example, micro-caps may use $100K/$300K, while large-caps might use $5M/$20M. Reading the Output Black baseline = Noise / retail chop. First Green bar = Smart money starts building position. Red bar(s) = Ownership shift confirmed — institutions active. Flat-to-rising pattern in DVOG = Sustained accumulation; often aligns with strong trend continuation. Summary DVOG transforms raw volume into actionable context — showing you when capital, not hype, is moving. It’s particularly effective for: Momentum and breakout traders Liquidity trap reclaims (Kuiper-style setups) Identifying early ignition bars before halts Confirming frontside strength in micro-caps Use DVOG as your ownership radar — the visual cue for when the market stops being retail and starts being real.
Penunjuk Pine Script®
oleh Mando4_27
We Buy / We Sell - #TheStrat SignalsWe Buy / We Sell - #TheStrat SignalsDescription This indicator is inspired by the #TheStrat methodology from Rob Smith, designed to identify high-probability "We Buy" (bullish) and "We Sell" (bearish) signals for trading stocks, ETFs, or futures like AMEX:SPY or $VSAT. It combines price action reversal patterns, higher timeframe continuity (HTFC), and optional broadening formation (BF) breaks to time entries with market momentum. Key Features: We Buy Signals: Triggered on a 2d-2u reversal (bearish to bullish candle) when the higher timeframe (HTF) is bullish (green) and optionally at a BF bottom (pivot low break). Labeled as "We Buy" at the candle’s low with a green triangle. We Sell Signals: Triggered on a 2u-2d reversal (bullish to bearish candle) when the HTF is bearish (red) and optionally at a BF top (pivot high break). Labeled as "We Sell" at the candle’s high with a red triangle. Candle Numbering: Displays #TheStrat candle types (1=Inside, 2u=Up, 2d=Down, 3=Outside) for context. Debug Labels: Enabled by default, showing why signals don’t fire (e.g., "No HTFC Buy" if HTF isn’t bullish). Partial Signals: Optional faint circles for 2d-2u or 2u-2d reversals (without HTFC/BF), disabled by default. HTFC Background: Green (HTF bullish) or red (HTF bearish) background for timeframe alignment. How It Works Based on #TheStrat, the indicator seeks evidence of aggressive buying ("We Buy") or selling ("We Sell") by analyzing: Reversal Patterns: 2d-2u (We Buy): A bearish directional candle (2d) followed by a bullish directional candle (2u), signaling a potential bullish reversal. 2u-2d (We Sell): A bullish directional candle (2u) followed by a bearish directional candle (2d), signaling a potential bearish reversal. Higher Timeframe Continuity (HTFC): We Buy requires the HTF (e.g., 1H or Daily) to close above its open (bullish). We Sell requires the HTF to close below its open (bearish). Broadening Formation (BF): Optional pivot high/low breaks approximate BF extremes (tops for We Sell, bottoms for We Buy). Can be disabled (use_bf=false) for more frequent signals. How to Use Setup: Apply to a 5min chart of a liquid asset (e.g., AMEX:SPY , NASDAQ:VSAT ) for intraday trading, or higher timeframes for swing trading. Ensure sufficient chart history (TradingView > Chart Settings > Max Bars > 1000+). Settings: Higher Timeframe (htf): Default "60" (1H). Try "15" (15min) for faster signals or "D" (Daily) for swing trades. Pivot Lookback Length (pivot_len): Default 3. Lower to 1 for more signals, higher for stricter BF breaks. Require Broadening Formation (use_bf): Default true. Set to false to skip BF checks, increasing signal frequency. Show We Buy/We Sell Labels: Default true. Shows "We Buy" or "We Sell" on signal candles. Show Candle Numbers: Default true. Displays 1/2u/2d/3 for #TheStrat context. Show Debug Labels: Default true. Shows "No HTFC Buy", "No BF Buy", etc., to diagnose missing signals. Show Partial Signals: Default false. Enable to show faint circles for 2d-2u/2u-2d reversals without HTFC/BF. Trading: We Buy: Enter long on a green "We Buy" label (with triangle). Set stops below the signal candle’s low. Target BF highs or resistance. We Sell: Enter short on a red "We Sell" label (with triangle). Set stops above the signal candle’s high. Target BF lows or support. Use debug labels to understand why signals don’t fire (e.g., "No HTFC Buy" means HTF isn’t bullish). Partial signals (faint circles) indicate reversals without full conditions, useful for discretionary setups. Alerts: Right-click the indicator > "Add Alert" on we_buy or we_sell for real-time notifications. Tips Best Assets: Use on liquid tickers like AMEX:SPY , NASDAQ:QQQ , or NASDAQ:VSAT , as seen in @AlexsOptions ’ examples. Volatility: Signals are more frequent in trending or volatile markets. Check historical periods (e.g., September 2025) for testing. Risk Management: Always use stops (e.g., 1-2% risk per trade) and validate signals with market context (e.g., sector/index alignment). Learning #TheStrat: Study Rob Smith’s #TheStrat for deeper understanding of candle types and FTFC. Troubleshooting No Signals? Check debug labels (e.g., "No HTFC Buy" means HTF isn’t bullish). Adjust htf (e.g., "15" or "D"). Set use_bf=false or lower pivot_len to 1 for more signals. Ensure reversals (2d-2u or 2u-2d) are present (check candle numbers). Test on volatile periods or liquid tickers. No Partial Signals? Enable show_partial in settings to see faint circles for 2d-2u/2u-2d reversals. Confirm reversal patterns exist (e.g., "2d" → "2u" in candle numbers).
Penunjuk Pine Script®
oleh SmartGatorTrader
2
Wyckoff Accumulation / Distribution Detector (v3)🌱 Spring (Bullish Wyckoff Signature) 🧠 Definition A Spring happens when price dips below a well-defined support level, usually near the end of an accumulation phase, then quickly reverses back above support. This is not ordinary volatility — it's usually intentional by large operators (“Composite Man”) to: Trigger stop-losses of weak holders Create the illusion of a breakdown to scare late sellers in Absorb all remaining supply at low prices Launch the next markup leg once weak hands are flushed out 🧭 Typical Spring Characteristics Feature Behavior Location Near the bottom of a trading range after a decline Price Action Temporary breakdown below support, then sharp reversal above Volume Usually low to average on the break, indicating lack of real selling pressure. Sometimes a volume surge on the reversal as strong hands step in Candle Often shows a long lower wick, closes back inside the range Intent Shakeout of weak holders, allow institutions to accumulate more quietly 📈 Why It's Bullish Springs typically mark the final test of supply. If price can dip below support and immediately recover, it means: Selling pressure is exhausted (no follow-through) Strong hands are absorbing remaining shares A bullish breakout is often imminent 🪤 Upthrust (Bearish Wyckoff Signature) 🧠 Definition An Upthrust is the mirror image of a Spring. It happens when price pokes above a resistance level, usually near the end of a distribution phase, but then fails to hold above it and falls back inside the range. This is typically smart money distributing to eager buyers: Late breakout traders pile in Institutions sell into that strength Price collapses back into the range, trapping breakout buyers 🧭 Typical Upthrust Characteristics Feature Behavior Location Near the top of a trading range after a rally Price Action Temporary breakout above resistance, then quick reversal down Volume Frequently low on the breakout, suggesting a lack of real buying interest — or sometimes high but with no progress, showing hidden selling Candle Often shows a long upper wick, closes back inside the range Intent Trap breakout buyers, provide liquidity for institutional sellers to unload near highs 📉 Why It's Bearish Upthrusts show demand failure and supply swamping: Buyers cannot sustain the breakout. The sharp reversal signals large players are exiting. Typically precedes markdown phases or sharp declines. 📝 Trading Implications Spring → Often followed by a sign of strength rally → good long entry if confirmed with volume expansion and follow-through. Upthrust → Often followed by a sign of weakness → short setups, especially if the next rally fails at lower highs. The script looks for: 🌱 Spring: Price makes a low below recent pivot support, Closes back above, Does so on low volume → likely a shakeout. 🪤 Upthrust: Price makes a high above recent pivot resistance, Closes back below, On low volume → likely a bull trap.
Penunjuk Pine Script®
oleh padinroc
Forecast PriceTime Oracle [CHE] Forecast PriceTime Oracle — Prioritizes quality over quantity by using Power Pivots via RSI %B metric to forecast future pivot highs/lows in price and time Summary This indicator identifies potential pivot highs and lows based on out-of-bounds conditions in a modified RSI %B metric, then projects future occurrences by estimating time intervals and price changes from historical medians. It provides visual forecasts via diagonal and horizontal lines, tracks achievement with color changes and symbols, and displays a dashboard for statistical overview including hit rates. Signals are robust due to median-based aggregation, which reduces outlier influence, and optional tolerance settings for near-misses, making it suitable for anticipating reversals in ranging or trending markets. Motivation: Why this design? Standard pivot detection often lags or generates false signals in volatile conditions, missing the timing of true extrema. This design leverages out-of-bounds excursions in RSI %B to capture "Power Pivots" early—focusing on quality over quantity by prioritizing significant extrema rather than every minor swing—then uses historical deltas in time and price to forecast the next ones, addressing the need for proactive rather than reactive analysis. It assumes that pivot spacing follows statistical patterns, allowing users to prepare entries or exits ahead of confirmation. What’s different vs. standard approaches? - Reference baseline: Diverges from traditional ta.pivothigh/low, which require fixed left/right lengths and confirm only after bars close, often too late for dynamic markets. - Architecture differences: - Detects extrema during OOB runs rather than post-bar symmetry. - Aggregates deltas via medians (or alternatives) over a user-defined history, capping arrays to manage resources. - Applies tolerance thresholds for hit detection, with options for percentage, absolute, or volatility-adjusted (ATR) flexibility. - Freezes achieved forecasts with visual states to avoid clutter. - Practical effect: Charts show proactive dashed projections instead of retrospective dots; the dashboard reveals evolving hit rates, helping users gauge reliability over time without manual calculation. How it works (technical) The indicator first computes a smoothed RSI over a specified length, then applies Bollinger Bands to derive %B, flagging out-of-bounds below zero or above one hundred as potential run starts. During these runs, it tracks the extreme high or low price and bar index. Upon exit from the OOB state, it confirms the Power Pivot at that extreme and records the time delta (bars since prior) and price change percentage to rolling arrays. For forecasts, it calculates the median (or selected statistic) of recent deltas, subtracts the confirmation delay (bars from apex to exit), and projects ahead by that adjusted amount. Price targets use the median change applied to the origin pivot value. Lines are drawn from the apex to the target bar and price, with a short horizontal at the endpoint. Arrays store up to five active forecasts, pruning oldest on overflow. Tolerance adjusts hit checks: for highs, if the high reaches or exceeds the target (adjusted by tolerance); for lows, if the low drops to or below. Once hit, the forecast freezes, changing colors and symbols, and extends the horizontal to the hit bar. Persistent variables maintain last pivot states across bars; arrays initialize empty and grow until capped at history length. Parameter Guide Source: Specifies the data input for the RSI computation, influencing how price action is captured. Default is close. For conservative signals in noisy environments, switch to high; using low boosts responsiveness but may increase false positives. RSI Length: Sets the smoothing period for the RSI calculation, with longer values helping to filter out whipsaws. Default is 32. Opt for shorter lengths like 14 to 21 on faster timeframes for quicker reactions, or extend to 50 or more in strong trends to enhance stability at the cost of some lag. BB Length: Defines the period for the Bollinger Bands applied to %B, directly affecting how often out-of-bounds conditions are triggered. Default is 20. Align it with the RSI length: shorter periods detect more potential runs but risk added noise, while longer ones provide better filtering yet might overlook emerging extrema. BB StdDev: Controls the multiplier for the standard deviation in the bands, where wider settings reduce false out-of-bounds alerts. Default is 2.0. Narrow it to 1.5 for highly volatile assets to catch more signals, or broaden to 2.5 or higher to emphasize only major movements. Show Price Forecast: Enables or disables the display of diagonal and target lines along with their updates. Default is true. Turn it off for simpler chart views, or keep it on to aid in trade planning. History Length: Determines the number of recent pivot samples used for median-based statistics, where more history leads to smoother but potentially less current estimates. Default is 50. Start with a minimum of 5 to build data; limit to 100 to 200 to prevent outdated regimes from skewing results. Max Lookahead: Limits the number of bars projected forward to avoid overly extended lines. Default is 500. Reduce to 100 to 200 for intraday focus, or increase for longer swing horizons. Stat Method: Selects the aggregation technique for time and price deltas: Median for robustness against outliers, Trimmed Mean (20%) for a balanced trim of extremes, or 75th Percentile for a conservative upward tilt. Default is Median. Use Median for even distributions; switch to Percentile when emphasizing potential upside in trending conditions. Tolerance Type: Chooses the approach for flexible hit detection: None for exact matches, Percentage for relative adjustments, Absolute for fixed point offsets, or ATR for scaling with volatility. Default is None. Begin with Percentage at 0.5 percent for currency pairs, or ATR for adapting to cryptocurrency swings. Tolerance %: Provides the relative buffer when using Percentage mode, forgiving small deviations. Default is 0.5. Set between 0.2 and 1.0 percent; higher values accommodate gaps but can overstate hit counts. Tolerance Points: Establishes a fixed offset in price units for Absolute mode. Default is 0.0010. Tailor to the asset, such as 0.0001 for forex pairs, and validate against past wick behavior. ATR Length: Specifies the period for the Average True Range in dynamic tolerance calculations. Default is 14. This is the standard setting; shorten to 10 to reflect more recent volatility. ATR Multiplier: Adjusts the ATR scale for tolerance width in ATR mode. Default is 0.5. Range from 0.3 for tighter precision to 0.8 for greater leniency. Dashboard Location: Positions the summary table on the chart. Default is Bottom Right. Consider Top Left for better visibility on mobile devices. Dashboard Size: Controls the text scaling for dashboard readability. Default is Normal. Choose Tiny for dense overlays or Large for detailed review sessions. Text/Frame Color: Sets the color scheme for dashboard text and borders. Default is gray. Align with your chart theme, opting for lighter shades on dark backgrounds. Reading & Interpretation Forecast lines appear as dashed diagonals from confirmed pivots to projected targets, with solid horizontals at endpoints marking price levels. Open targets show a target symbol (🎯); achieved ones switch to a trophy symbol (🏆) in gray, with lines fading to gray. The dashboard summarizes median time/price deltas, sample counts, and hit rates—rising rates indicate improving forecast alignment. Colors differentiate highs (red) from lows (lime); frozen states signal validated projections. Practical Workflows & Combinations - Trend following: Enter long on low forecast hits during uptrends (higher highs/lower lows structure); filter with EMA crossovers to ignore counter-trend signals. - Reversal setups: Short above high projections in overextended rallies; use volume spikes as confirmation to reduce false breaks. - Exits/Stops: Trail stops to prior pivot lows; conservative on low hit rates (below 50%), aggressive above 70% with tight tolerance. - Multi-TF: Apply on 1H for entries, 4H for time projections; combine with Ichimoku clouds for confluence on targets. - Risk management: Position size inversely to delta uncertainty (wider history = smaller bets); avoid low-liquidity sessions. Behavior, Constraints & Performance Confirmation occurs on OOB exit, so live-bar pivots may adjust until close, but projections update only on events to minimize repaint. No security or HTF calls, so no external lookahead issues. Arrays cap at history length with shifts; forecasts limited to five active, pruning FIFO. Loops iterate over small fixed sizes (e.g., up to 50 for stats), efficient on most hardware. Max lines/labels at 500 prevent overflow. Known limits: Sensitive to OOB parameter tuning—too tight misses runs; assumes stationary pivot stats, which may shift in regime changes like low vol. Gaps or holidays distort time deltas. Sensible Defaults & Quick Tuning Defaults suit forex/crypto on 1H–4H: RSI 32/BB 20 for balanced detection, Median stats over 50 samples, None tolerance for exactness. - Too many false runs: Increase BB StdDev to 2.5 or RSI Length to 50 for filtering. - Lagging forecasts: Shorten History Length to 20; switch to 75th Percentile for forward bias. - Missed near-hits: Enable Percentage tolerance at 0.3% to capture wicks without overcounting. - Cluttered charts: Reduce Max Lookahead to 200; disable dashboard on lower TFs. What this indicator is—and isn’t This is a forecasting visualization layer for pivot-based analysis, highlighting statistical projections from historical patterns. It is not a standalone system—pair with price action, volume, and risk rules. Not predictive of all turns; focuses on OOB-derived extrema, ignoring volume or news impacts. Disclaimer The content provided, including all code and materials, is strictly for educational and informational purposes only. It is not intended as, and should not be interpreted as, financial advice, a recommendation to buy or sell any financial instrument, or an offer of any financial product or service. All strategies, tools, and examples discussed are provided for illustrative purposes to demonstrate coding techniques and the functionality of Pine Script within a trading context. Any results from strategies or tools provided are hypothetical, and past performance is not indicative of future results. Trading and investing involve high risk, including the potential loss of principal, and may not be suitable for all individuals. Before making any trading decisions, please consult with a qualified financial professional to understand the risks involved. By using this script, you acknowledge and agree that any trading decisions are made solely at your discretion and risk. Do not use this indicator on Heikin-Ashi, Renko, Kagi, Point-and-Figure, or Range charts, as these chart types can produce unrealistic results for signal markers and alerts. Best regards and happy trading Chervolino
Penunjuk Pine Script®
oleh chervolino
Herd Flow Oscillator — Volume Distribution Herd Flow Oscillator — Scientific Volume Distribution (herd-accurate rev) A composite order-flow oscillator designed to surface true herding behavior — not just random bursts of buying or selling. It’s built to detect when market participants start acting together, showing persistent, one-sided activity that statistically breaks away from normal market randomness. Unlike traditional volume or momentum indicators, this tool doesn’t just look for “who’s buying” or “who’s selling.” It tries to quantify crowd behavior by blending multiple statistical tests that describe how collective sentiment and coordination unfold in price and volume dynamics. What it shows The Herd Flow Oscillator works as a multi-layer detector of crowd-driven flow in the market. It examines how signed volume (buy vs. sell pressure) evolves, how persistent it is, and whether those actions are unusually coordinated compared to random expectations. HerdFlow Composite (z) — the main signal line, showing how statistically extreme the current herding pressure is. When this crosses above or below your set thresholds, it suggests a high probability of collective buying or selling. You can optionally reveal component panels for deeper insight into why herding is detected: DVI (Directional Volume Imbalance): Measures the ratio of bullish vs. bearish volume. If it’s strongly positive, more volume is hitting the ask (buying); if negative, more is hitting the bid (selling). LSV-style Herd Index : Inspired by academic finance measures of “herding.” It compares how often volume is buying vs. selling versus what would happen by random chance. If the result is significantly above chance, it means traders are collectively biased in one direction. O rder-Flow Persistence (ρ 1..K): Averages autocorrelation of signed volume over several lags. In simpler terms: checks if buying/selling pressure tends to continue in the same direction across bars. Positive persistence = ongoing coordination, not just isolated trades. Runs-Test Herding (−Z) : Statistical test that checks how often trade direction flips. When there are fewer direction changes than expected, it means trades are clustering — a hallmark of herd behavior. Skew (signed volume): Measures whether signed volume is heavily tilted to one side. A positive skew means more aggressive buying bursts; a negative skew means more intense selling bursts. CVD Slope (z): Looks at the slope of the Cumulative Volume Delta — essentially how quickly buy/sell pressure is accelerating. It’s a short-term flow acceleration measure. Shapes & background ▲ “BH” at the bottom = Bull Herding; ▼ “BH-” at the top = Bear Herding. These markers appear when all conditions align to confirm a herding regime. Persistence and clustering both confirm coordinated downside flow. Core Windows Primary Window (N) — the main sample length for herding calculations. It’s like the "memory span" for detecting coordinated behavior. A longer N means smoother, more reliable signals. Short Window (Nshort) — used for short-term measurements like imbalance and slope. Smaller values react faster but can be noisy; larger values are steadier but slower. Long Window (Nlong) — used for z-score normalization (statistical scaling). This helps the indicator understand what’s “normal” behavior over a longer horizon, so it can spot when things deviate too far. Autocorr lags (acLags) — how many steps to check when measuring persistence. Higher values (e.g., 3–5) look further back to see if trends are truly continuing. Calculation Options Price Proxy for Tick Rule — defines how to decide if a trade is “buy” or “sell.” hlc3 (average of high, low, and close) works as a neutral, smooth price proxy. Use ATR for scaling — keeps signals comparable across assets and timeframes by dividing by volatility (ATR). Prevents high-volatility periods from dominating the signal. Median Filter (bars) — smooths out erratic data spikes without heavily lagging the response. Odd values like 3 or 5 work best. Signal Thresholds Composite z-threshold — determines how extreme behavior must be before it counts as “herding.” Higher values = fewer, more confident signals. Imbalance threshold — the minimum directional volume imbalance to trigger interest. Plotting Show component panels — useful for analysts and developers who want to inspect the math behind signals. Fill strong herding zones — purely visual aid to highlight key periods of coordinated trading. How to use it (practical tips) Understand the purpose: This is not just a “buy/sell” tool. It’s a behavioral detector that identifies when traders or algorithms start acting in the same direction. Timeframe flexibility: 15m–1h: reveals short-term crowd shifts. 4h–1D: better for swing-trade context and institutional positioning. Combine with structure or trend: When HerdFlow confirms a bullish regime during a breakout or retest, it adds confidence. Conversely, a bearish cluster at resistance may hint at a crowd-driven rejection. Threshold tuning: To make it more selective, increase zThr and imbThr. To make it more sensitive, lower those thresholds but expand your primary window N for smoother results. Cross-market consistency: Keep “Use ATR for scaling” enabled to maintain consistency across different instruments or timeframes. Denoising: A small median filter (3–5 bars) removes flicker from volume spikes but still preserves the essential crowd patterns. Reading the components (why signals fire) Each sub-metric describes a unique “dimension” of crowd behavior: DVI: how imbalanced buying vs selling is. Herd Index: how biased that imbalance is compared to random expectation. Persistence (ρ): how continuous those flows are. Runs-Test: how clumped together trades are — clustering means the crowd’s acting in sync. Skew: how lopsided the volume distribution is — sudden surges of one-sided aggression. CVD Slope: how strongly accelerating the current directional flow is. When all of these line up, you’re seeing evidence that market participants are collectively moving in the same direction — i.e., true herding.
Penunjuk Pine Script®
oleh Cmo22