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Major Trading Sessions IndicatorsThis indicator displays vertical lines on your chart to mark the opening times of the major global trading sessions (Tokyo, Shanghai/HK, London, and New York). As a crypto trader I want to find price action patterns after sessions open. It's fully customizable and extendable (you could add closing time for sessions as well) Works best on short timeframes. Features: 6 configurable vertical lines (4 preset for major sessions + 2 custom) Each line shows a customizable label (e.g., "Tokyo", "London") Individual time and color settings for each line UTC offset for each line to handle Daylight Saving Time Option to fix all labels at a specific price level for cleaner appearance (need to set and save it for each chart, it becomes a mess if you don't). Default behavior and limit of Pine Script is that it will be attached to the price wick. Default Sessions: Tokyo: 00:00 UTC (midnight) Shanghai/HK: 01:30 UTC London: 08:00 UTC (winter) - adjust offset to +1 for summer New York: 13:00 UTC (winter) - adjust offset to -4 for summer DST Adjustments: Simply change the UTC offset when daylight saving time begins/ends: London: 0 (winter) or +1 (summer) New York: -5 (winter) or -4 (summer) Lines extend from top to bottom of the chart and appear precisely when each session opens. My preferred configuration: shorten names and reduce opacity of colors to 20-30%.
Pine Script®指標
由BitsOfRick提供
TriAnchor Elastic Reversion US Market SPY and QQQ adaptedSummary in one paragraph Mean-reversion strategy for liquid ETFs, index futures, large-cap equities, and major crypto on intraday to daily timeframes. It waits for three anchored VWAP stretches to become statistically extreme, aligns with bar-shape and breadth, and fades the move. Originality comes from fusing daily, weekly, and monthly AVWAP distances into a single ATR-normalized energy percentile, then gating with a robust Z-score and a session-safe gap filter. Scope and intent • Markets: SPY QQQ IWM NDX large caps liquid futures liquid crypto • Timeframes: 5 min to 1 day • Default demo: SPY on 60 min • Purpose: fade stretched moves only when multi-anchor context and breadth agree • Limits: strategy uses standard candles for signals and orders only Originality and usefulness • Unique fusion: tri-anchor AVWAP energy percentile plus robust Z of close plus shape-in-range gate plus breadth Z of SPY QQQ IWM • Failure mode addressed: chasing extended moves and fading during index-wide thrusts • Testability: each component is an input and visible in orders list via L and S tags • Portable yardstick: distances are ATR-normalized so thresholds transfer across symbols • Open source: method and implementation are disclosed for community review Method overview in plain language Base measures • Range basis: ATR(length = atr_len) as the normalization unit • Return basis: not used directly; we use rank statistics for stability Components • Tri-Anchor Energy: squared distances of price from daily, weekly, monthly AVWAPs, each divided by ATR, then summed and ranked to a percentile over base_len • Robust Z of Close: median and MAD based Z to avoid outliers • Shape Gate: position of close inside bar range to require capitulation for longs and exhaustion for shorts • Breadth Gate: average robust Z of SPY QQQ IWM to avoid fading when the tape is one-sided • Gap Shock: skip signals after large session gaps Fusion rule • All required gates must be true: Energy ≥ energy_trig_prc, |Robust Z| ≥ z_trig, Shape satisfied, Breadth confirmed, Gap filter clear Signal rule • Long: energy extreme, Z negative beyond threshold, close near bar low, breadth Z ≤ −breadth_z_ok • Short: energy extreme, Z positive beyond threshold, close near bar high, breadth Z ≥ +breadth_z_ok What you will see on the chart • Standard strategy arrows for entries and exits • Optional short-side brackets: ATR stop and ATR take profit if enabled Inputs with guidance Setup • Base length: window for percentile ranks and medians. Typical 40 to 80. Longer smooths, shorter reacts. • ATR length: normalization unit. Typical 10 to 20. Higher reduces noise. • VWAP band stdev: volatility bands for anchors. Typical 2.0 to 4.0. • Robust Z window: 40 to 100. Larger for stability. • Robust Z entry magnitude: 1.2 to 2.2. Higher means stronger extremes only. • Energy percentile trigger: 90 to 99.5. Higher limits signals to rare stretches. • Bar close in range gate long: 0.05 to 0.25. Larger requires deeper capitulation for longs. Regime and Breadth • Use breadth gate: on when trading indices or broad ETFs. • Breadth Z confirm magnitude: 0.8 to 1.8. Higher avoids fighting thrusts. • Gap shock percent: 1.0 to 5.0. Larger allows more gaps to trade. Risk — Short only • Enable short SL TP: on to bracket shorts. • Short ATR stop mult: 1.0 to 3.0. • Short ATR take profit mult: 1.0 to 6.0. Properties visible in this publication • Initial capital: 25000USD • Default order size: Percent of total equity 3% • Pyramiding: 0 • Commission: 0.03 percent • Slippage: 5 ticks • Process orders on close: OFF • Bar magnifier: OFF • Recalculate after order is filled: OFF • Calc on every tick: OFF • request.security lookahead off where used Realism and responsible publication • No performance claims. Past results never guarantee future outcomes • Fills and slippage vary by venue • Shapes can move during bar formation and settle on close • Standard candles only for strategies Honest limitations and failure modes • Economic releases or very thin liquidity can overwhelm mean-reversion logic • Heavy gap regimes may require larger gap filter or TR-based tuning • Very quiet regimes reduce signal contrast; extend windows or raise thresholds Open source reuse and credits • None Strategy notice Orders are simulated by TradingView on standard candles. request.security uses lookahead off where applicable. Non-standard charts are not supported for execution. Entries and exits • Entry logic: as in Signal rule above • Exit logic: short side optional ATR stop and ATR take profit via brackets; long side closes on opposite setup • Risk model: ATR-based brackets on shorts when enabled • Tie handling: stop first when both could be touched inside one bar Dataset and sample size • Test across your visible history. For robust inference prefer 100 plus trades.
Pine Script®策略
由exlux提供
Aurum DCX AVE Gold and Silver StrategySummary in one paragraph Aurum DCX AVE is a volatility break strategy for gold and silver on intraday and swing timeframes. It aligns a new Directional Convexity Index with an Adaptive Volatility Envelope and an optional USD/DXY bias so trades appear only when direction quality and expansion agree. It is original because it fuses three pieces rarely combined in one model for metals: a convexity aware trend strength score, a percentile based envelope that widens with regime heat, and an intermarket DXY filter. Scope and intent • Markets. Gold and silver futures or spot, other liquid commodities, major indices • Timeframes. Five minutes to one day. Defaults to 30min for swing pace • Default demo used in this publication. TVC:GOLD on 30m • Purpose. Enter confirmed volatility breaks while muting chop using regime heat and USD bias • Limits. This is a strategy. Orders are simulated on standard candles only Originality and usefulness • Unique fusion. DCX combines DI strength with path efficiency and curvature. AVE blends ATR with a high TR percentile and widens with DCX heat. DXY adds an intermarket bias • Failure mode addressed. False starts inside compression and unconfirmed breakouts during USD swings • Testability. Each component has a named input. Entry names L and S are visible in the list of trades • Portable yardstick. Weekly ATR for stops and R multiples for targets • Open source. Method and implementation are disclosed for community review Method overview in plain language You score direction quality with DCX, size an adaptive envelope with a blend of ATR and a high TR percentile, and only allow breaks that clear the band while DCX is above a heat threshold in the same direction. An optional DXY filter favors long when USD weakens and short when USD strengthens. Orders are bracketed with a Weekly ATR stop and an R multiple target, with optional trailing to the envelope. Base measures • Range basis. True Range and ATR over user windows. A high TR percentile captures expansion tails used by AVE • Return basis. Not required Components • Directional Convexity Index DCX. Measures directional strength with DX, multiplies by path efficiency, blends a curvature term from acceleration, scales to 0 to 100, and uses a rise window • Adaptive Volatility Envelope AVE. Midline ALMA or HMA or EMA plus bands sized by a blend of ATR and a high TR percentile. The blend weight follows volatility of volatility. Band width widens with DCX heat • DXY Bias optional. Daily EMA trend of DXY. Long bias when USD weakens. Short bias when USD strengthens • Risk block. Initial stop equals Weekly ATR times a multiplier. Target equals an R multiple of the initial risk. Optional trailing to AVE band Fusion rule • All gates must pass. DCX above threshold and rising. Directional lead agrees. Price breaks the AVE band in the same direction. DXY bias agrees when enabled Signal rule • Long. Close above AVE upper and DCX above threshold and DCX rising and plus DI leads and DXY bias is bearish • Short. Close below AVE lower and DCX above threshold and DCX falling and minus DI leads and DXY bias is bullish • Exit and flip. Bracket exit at stop or target. Optional trailing to AVE band Inputs with guidance Setup • Symbol. Default TVC:GOLD (Correlation Asset for internal logic) • Signal timeframe. Blank follows the chart • Confirm timeframe. Default 1 day used by the bias block Directional Convexity Index • DCX window. Typical 10 to 21. Higher filters more. Lower reacts earlier • DCX rise bars. Typical 3 to 6. Higher demands continuation • DCX entry threshold. Typical 15 to 35. Higher avoids soft moves • Efficiency floor. Typical 0.02 to 0.06. Stability in quiet tape • Convexity weight 0..1. Typical 0.25 to 0.50. Higher gives curvature more influence Adaptive Volatility Envelope • AVE window. Typical 24 to 48. Higher smooths more • Midline type. ALMA or HMA or EMA per preference • TR percentile 0..100. Typical 75 to 90. Higher favors only strong expansions • Vol of vol reference. Typical 0.05 to 0.30. Controls how much the percentile term weighs against ATR • Base envelope mult. Typical 1.4 to 2.2. Width of bands • Regime adapt 0..1. Typical 0.6 to 0.95. How much DCX heat widens or narrows the bands Intermarket Bias • Use DXY bias. Default ON • DXY timeframe. Default 1 day • DXY trend window. Typical 10 to 50 Risk • Risk percent per trade. Reporting field. Keep live risk near one to two percent • Weekly ATR. Default 14. Basis for stops • Stop ATR weekly mult. Typical 1.5 to 3.0 • Take profit R multiple. Typical 1.5 to 3.0 • Trail with AVE band. Optional. OFF by default Properties visible in this publication • Initial capital. 20000 • Base currency. USD • request.security lookahead off everywhere • Commission. 0.03 percent • Slippage. 5 ticks • Default order size method percent of equity with value 3% of the total capital available • Pyramiding 0 • Process orders on close ON • Bar magnifier ON • Recalculate after order is filled OFF • Calc on every tick OFF Realism and responsible publication • No performance claims. Past results never guarantee future outcomes • Shapes can move while a bar forms and settle on close • Strategies use standard candles for signals and orders only Honest limitations and failure modes • Economic releases and thin liquidity can break assumptions behind the expansion logic • Gap heavy symbols may prefer a longer ATR window • Very quiet regimes can reduce signal contrast. Consider higher DCX thresholds or wider bands • Session time follows the exchange of the chart and can change symbol to symbol • Symbol sensitivity is expected. Use the gates and length inputs to find stable settings Open source reuse and credits • None Mode Public open source. Source is visible and free to reuse within TradingView House Rules Legal Education and research only. Not investment advice. You are responsible for your decisions. Test on historical data and in simulation before any live use. Use realistic costs.
Pine Script®策略
由exlux提供
2
FluxGate Daily Swing StrategySummary 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
Pine Script®策略
由exlux提供
Match on Selectable Percentage Change + RangeIndicator Overview: Match on Selectable Percentage Change + Range is a powerful analytical tool designed for traders and analysts who want to identify historical price bars that match a specific percentage variation, and then evaluate how price evolved in the following days. It combines precision filtering with visual tabular feedback, making it ideal for pattern recognition, backtesting, and scenario analysis. What It Does This indicator scans historical bars to find instances where the percentage change between two consecutive closes matches a user-defined target (± a customizable tolerance). Once matches are found, it displays: The date of each match (most recent first) The actual variation searched The percentage change after 2, 10, 20, and 30 bars The min-max range (in %) over those same periods All results are shown in a dynamic table directly on the chart. Inputs & Controls Input Description Which variation do you want to analyze? (%) Set the target percentage change to look for (e.g. 2.5%) % deviation from the variation to be considered (%) Define the tolerance range around the target (e.g. ±0.5%) Bars to analyze (max 9999) Set how many past bars to scan Show match table Toggle to enable/disable the entire table Show percentage variations (2d, 10d, 20d, 30d) Toggle to show/hide post-match percentage changes Show min-max ranges (2d, 10d, 20d, 30d) Toggle to show/hide post-match high/low ranges Table Structure Each row in the table represents a historical match. Columns include: Date: When the match occurred Variation in: The actual % change that triggered the match 2d / 10d / 20d / 30d: % change after those days Min-Max 2d / 10d / 20d / 30d: Range of price movement after those days Color coding helps quickly identify bullish (green) vs bearish (red) outcomes. Use Cases Backtesting: See how similar past moves evolved over time Scenario modeling: Estimate potential outcomes after a known variation Pattern recognition: Spot recurring setups or volatility clusters Risk analysis: Understand post-variation drawdowns and upside potential Tips for Use Use tighter deviation (e.g. 0.3%) for precision, or wider (e.g. 1%) for broader pattern capture. Combine with other indicators to validate setups (e.g. volume, RSI, trend filters). Toggle off variation or range columns to focus only on the metrics you need.
Pine Script®指標
由FrancescoG65提供
Trend Telescope v4 Basic Configuration pine // Enable only the components you need Order Flow: ON Delta Volume: ON Volume Profile: ON Cumulative Delta: ON Volatility Indicator: ON Momentum Direction: ON Volatility Compression: ON 📊 Component Breakdown 1. Order Flow Analysis Purpose: Identifies buying vs selling pressure Visual: Histogram (Green=Buying, Red=Selling) Calculation: Volume weighted by price position Usage: Spot institutional order blocks 2. Delta Volume Values Purpose: Shows volume imbalance Bull Volume (Green): Volume on up bars Bear Volume (Red): Volume on down bars Usage: Identify volume divergences 3. Anchored Volume Profile Purpose: Finds high-volume price levels POC (Point of Control): Price with highest volume Profile Length: Adjustable (default: 50 bars) Usage: Identify support/resistance zones 4. Cumulative Volume Delta Purpose: Tracks net buying/selling pressure over time Trend Analysis: Rising=Buying pressure, Falling=Selling pressure Divergence Detection: Price vs Delta divergences Usage: Confirm trend strength 5. Volatility Indicator Purpose: Measures market volatility with cycle detection Volatility Ratio: ATR as percentage of price Volatility Cycle: SMA of volatility (identifies periods) Histogram: Difference between current and average volatility Usage: Adjust position sizing, identify breakout setups 6. Real-time Momentum Direction Purpose: Multi-factor momentum assessment Components: Price momentum (50%), RSI momentum (30%), Volume momentum (20%) Visual: Line plot with color coding Labels: Clear BULLISH/BEARISH/NEUTRAL signals Usage: Trend confirmation, reversal detection 7. Volatility Compression Analysis Purpose: Identifies low-volatility consolidation periods Compression Detection: True Range below threshold Strength Meter: How compressed the market is Histogram: Red when compressed, Gray when normal Usage: Predict explosive moves, prepare for breakouts ⚙️ Advanced Configuration Optimal Settings for Different Timeframes pine // Scalping (1-15 min) Profile Length: 20 ATR Period: 10 Momentum Length: 8 Compression Threshold: 0.3 // Day Trading (1H-4H) Profile Length: 50 ATR Period: 14 Momentum Length: 14 Compression Threshold: 0.5 // Swing Trading (Daily) Profile Length: 100 ATR Period: 20 Momentum Length: 21 Compression Threshold: 0.7 Alert Setup Guide Enable "Enable Alerts" in settings Choose alert types: Momentum Alerts: When momentum changes direction Compression Alerts: When volatility compression begins Set alert frequency to "Once Per Bar" Configure notification preferences 🎯 Trading Strategies Strategy 1: Compression Breakout pine Entry Conditions: 1. Volatility Compression shows RED histogram 2. Cumulative Delta trending upward 3. Momentum turns BULLISH 4. Price breaks above POC level Exit: When Momentum turns BEARISH or Compression ends Strategy 2: Momentum Reversal pine Entry Conditions: 1. Strong Order Flow in opposite direction 2. Momentum divergence (price makes new high/low but momentum doesn't) 3. Volume confirms the reversal Exit: When Order Flow returns to trend direction Strategy 3: Institutional Accumulation pine Identification: 1. High Cumulative Delta but flat/sideways price 2. Consistent Order Flow in one direction 3. Volume Profile shows accumulation at specific levels Trade: Enter in direction of Order Flow when price breaks level 📈 Interpretation Guide Bullish Signals ✅ Order Flow consistently green ✅ Cumulative Delta making higher highs ✅ Momentum above zero and rising ✅ Bull Volume > Bear Volume ✅ Price above POC level Bearish Signals ✅ Order Flow consistently red ✅ Cumulative Delta making lower lows ✅ Momentum below zero and falling ✅ Bear Volume > Bull Volume ✅ Price below POC level Caution Signals ⚠️ Momentum divergence (price vs indicator) ⚠️ Volatility compression (potential big move coming) ⚠️ Mixed signals across components 🔧 Troubleshooting Common Issues & Solutions Problem: Indicators not showing Solution: Check "Show on Chart" is enabled Problem: Alerts not triggering Solution: Verify alert is enabled in both script and TradingView alert panel Problem: Performance issues Solution: Reduce number of enabled components or increase timeframe Problem: Volume Profile not updating Solution: Adjust Profile Length setting, ensure sufficient historical data Performance Optimization Disable unused components Increase chart timeframe Reduce historical bar count Use on lower timeframes with fewer indicators enabled 💡 Pro Tips Risk Management Use Volatility Indicator for position sizing Monitor Cumulative Delta for trend confirmation Use POC levels for stop-loss placement Multi-Timeframe Analysis Use higher timeframe for trend direction Use current timeframe for entry timing Correlate signals across timeframes Market Condition Adaptation Trending Markets: Focus on Momentum + Order Flow Ranging Markets: Focus on Volume Profile + Compression High Volatility: Use smaller position sizes Low Volatility: Prepare for compression breakouts 📚 Educational Resources Key Concepts to Master Volume-price relationships Market microstructure Institutional order flow Volatility regimes Momentum vs mean reversion Recommended Learning Path Start with Order Flow + Momentum only Add Volume Profile once comfortable Incorporate Volatility analysis Master multi-component correlation 🆘 Support Getting Help Check component toggles are enabled Verify sufficient historical data is loaded Test on major pairs/indices first Adjust settings for your trading style Continuous Improvement Backtest strategies thoroughly Keep a trading journal Adjust parameters based on market conditions Combine with price action analysis Remember: No indicator is perfect. Use this tool as part of a comprehensive trading plan with proper risk management. Always test strategies in demo accounts before live trading. Happy Trading! 📈
Pine Script®指標
由lohanineeraj提供
Adaptive Pulse Frequency & Amplitude TrendAdaptive Pulse Frequency & Amplitude Trend Indicator This Pine Script indicator is designed to identify strong bullish or bearish trends by analyzing volume dynamics on a lower timeframe than the one currently displayed on the chart. It operates on the principle of detecting significant spikes in buying or selling pressure, referred to as "pulses," and then evaluating their frequency, strength, and dominance over the opposing market forces. Core Concepts Lower Timeframe Volume Analysis: The script requests up-volume and down-volume data from a more granular, lower timeframe (e.g., 1-minute data when on a 15-minute chart). This provides a higher-resolution view of the flow of buy and sell orders. Adaptive Pulse Detection: A "pulse" is defined as a bar with an unusually high net volume (up volume minus down volume). Instead of using a fixed value, the indicator calculates an adaptive threshold based on the 90th percentile of net volume over a 100-bar lookback period. Any bar with a net volume exceeding this dynamic threshold is flagged as a pulse, categorized as either bullish (positive net volume) or bearish (negative net volume). Frequency and Amplitude: The indicator measures two key aspects of these pulses over user-defined lookback periods: Net Frequency: The number of bullish pulses minus the number of bearish pulses. A positive value indicates more buying pulses, while a negative value indicates more selling pulses. Net Amplitude : The cumulative volume of bullish pulses minus the cumulative volume of bearish pulses. This measures the overall strength and conviction behind the pulses. Primary Trend Signal The indicator's primary signal comes from a strict dominance condition. It doesn't just look for more buying or selling pulses; it checks if these pulses are powerful enough to overwhelm the total opposite pressure in the market. Bullish Dominance (Green Background): A strong bullish signal is generated when the total volume of all bullish pulses within a lookback period is greater than the total down-volume from all bars (not just pulses) in that same period. Bearish Dominance (Red Background): A strong bearish signal is generated when the total volume of all bearish pulses is greater than the total up-volume from all bars in that period. The chart background is colored green for bullish dominance and red for bearish dominance, providing a clear visual cue for when one side has taken decisive control. Plotted Data In addition to the background coloring, the indicator plots several lines in its own pane for more detailed analysis: Net Frequency: Shows the trend in the number of bull vs. bear pulses. Net Amplitude: Shows the trend in the strength of bull vs. bear pulses. Bullish/Bearish Amplitude: The individual cumulative volumes for bull and bear pulses. Dynamic Threshold: The adaptive value used to identify pulses. By combining an adaptive detection method with a strict dominance condition, this tool aims to filter out market noise and highlight periods of genuinely strong, volume-backed trends.
Pine Script®指標
由Cmo22提供
Constant Auto Trendlines (Extended Right)📈 Constant Auto Trendlines (Extended Right) This indicator automatically detects market structure by connecting swing highs and lows with permanent, forward-projecting trendlines. Unlike standard trendline tools that stop at the last pivot, this version extends each trendline infinitely into the future — helping traders visualize where price may react next. 🔍 How It Works The script identifies pivot highs and lows using user-defined left/right bar counts. When a new lower high or higher low appears, the indicator draws a line between the two pivots and extends it forward using extend.right. Each new confirmed trendline stays fixed, creating a historical map of structure that evolves naturally with market action. Optional filters: Min Slope – ignore nearly flat trendlines Show Latest Only – focus on the most relevant trendline Alerts – get notified when price crosses the most recent uptrend or downtrend line 🧩 Why It’s Useful This tool helps traders: Spot emerging trends early Identify dynamic support/resistance diagonals Avoid redrawing trendlines manually Backtest structure breaks historically ⚙️ Inputs Pivot Left / Right bars Min slope threshold Line color, width, and style Show only latest line toggle Alert options
Pine Script®指標
由rrtaker86提供
1
NWOG/NDOG + EHPDA🌐 ENGLISH DESCRIPTION Hybrid NWOG/NDOG + EHPDA – Advanced Gaps & Event Horizon Indicator (Enhanced with Real-Time Alerts and Info Table) 📊 Overview This advanced indicator combines automatic detection of weekly gaps (NWOG) and daily gaps (NDOG) with the Event Horizon (EHPDA) concept, now featuring customizable alerts and a real-time info table for a more efficient trading experience. Designed for traders who operate based on institutional price structures, liquidity zones, and SMC/ICT confluences. ✨ Key Features 1. Gap Detection & Visualization NWOG (New Week Opening Gap): Identifies and visualizes the gap between Friday’s close and Monday’s open. NDOG (New Day Opening Gap): Detects daily gaps on intraday timeframes. Enhanced visualization: Semi-transparent boxes, price levels (top, middle, bottom), and lines extended to the current bar. Customizable labels: Display gap formation date and price levels (optional). 2. Event Horizon (EHPDA) Automatically calculates the Event Horizon level between two non-overlapping gaps. Dashed line marking the equilibrium zone between bullish and bearish gaps. 3. Advanced 5pm-6pm Mode Special option to detect the Sunday-Monday gap using 4H bars. 4. Real-Time Alerts New gaps (NWOG/NDOG): Immediate notification when a new gap forms. Gap fill: Alert when price completely fills a gap. Event Horizon active: Notification when the Event Horizon level is triggered. 5. Info Table Real-time display: number of active gaps, Event Horizon status, time remaining until weekly/daily close. Customizable: position, size, and style. 🎨 Customization Configurable colors for bullish gaps, bearish gaps, and Event Horizon line. Customizable price labels and date format. 📈 Use Cases Reversal trading, price targets, liquidity zones, SMC/ICT confluences. ⚙️ Recommended Settings Timeframes: Daily and intraday (15m, 1H, 4H, etc.). NWOG: Enable on all timeframes. NDOG: Enable only on intraday. Max Gaps: 3-5 for clean charts, 10-15 for historical analysis. 📝 Important Notes Works best on 24/5 markets (Forex, Crypto). Gaps automatically close when filled. Event Horizon only appears with at least 2 non-overlapping gaps.
Pine Script®指標
由CDC_Trading_LABN提供
CVD Divergence + Volume MarkerHere is a Pine Script concept to mark candlestick chart candles when cumulative delta is divergent to price action and volume is above average. Cumulative delta divergence typically occurs when the price forms new highs/lows while cumulative delta forms lower highs/lows (or vice versa). The script should include a marker only when this divergence occurs alongside above-average volume, increasing signal strength and filtering out weak setups.​ Coding Concept Calculate cumulative delta (approximation using price and volume if true bid/ask volume is unavailable, e.g., on spot). Calculate moving average of volume. Detect bullish divergence (price makes lower low, cumulative delta makes higher low) and bearish divergence (price makes higher high, cumulative delta makes lower high). Mark candle with above-average volume when divergence is present.
Pine Script®指標
由WallstMoonMan提供
Flip to GreenPurpose: This indicator applies a Lorentzian-distance–based machine-learning model to classify market conditions and highlight probable momentum shifts. Where traditional indicators react to price movement, this one uses statistical pattern recognition to predict when momentum is likely to flip direction — the classic “flip to green” signal. Concept: Financial markets don’t move linearly; they bend and distort around major catalysts (news, FOMC meetings, earnings, etc.) in a way similar to how gravity warps space-time. This indicator accounts for that distortion by measuring distance in Lorentzian space instead of the usual Euclidean space. In simple terms: it adapts to volatility “warping,” allowing the model to detect structural momentum changes that normal math misses. Core logic: Imports two custom libraries: MLExtensions for machine-learning utilities KernelFunctions for advanced distance calculations Computes relationships among multiple features (e.g., RSI, ADX, or other inputs). Uses Lorentzian geometry to weight how recent price-time behavior influences current classification. Outputs a visual “flip” cue when the probability of trend reversal exceeds threshold confidence. Why it matters: Most indicators measure what has already happened. Lorentzian Classification attempts to capture what’s about to happen by comparing the present market state to a trained historical distribution under warped “price-time” geometry. It’s particularly useful for spotting early accumulation or exhaustion zones before they become obvious on standard momentum tools. Recommended use: Run it as a background trend classifier or color overlay. Combine it with volume-based confirmation tools (e.g., Dollar Volume Ownership Gauge) and structural analysis. A “flip to green” suggests buyers are regaining control; a fade or flip to red implies control returning to sellers.
Pine Script®指標
由Mando4_27提供
Dollar Volume Ownership GaugePurpose: DVOG tracks the real money moving through a ticker by converting share volume into dollar volume (price × volume). It helps identify when institutional-sized players enter, defend, or unload positions — information that plain volume bars often hide. How it works: Each bar represents 4-minute aggregated dollar volume. Green bars = moderate sponsorship ($400 K–$1 M per 4 min). Red bars = heavy sponsorship ($1 M+ per 4 min). Black bars = normal retail flow (under $400 K). Optional horizontal guides mark both thresholds for quick reference. Alerts: Green Bar Alert: fires every time a bar exceeds $400 K, signaling fresh institutional activity. Cross Alerts: trigger once when dollar volume crosses the $400 K or $1 M levels, perfect for automation or notifications. Why it’s useful: DVOG visually confirms when a breakout, knife-and-reclaim, or coil is being driven by real capital rather than low-liquidity noise. It turns abstract volume into a direct measure of who’s actually in control. Recommended use: Run it in a separate pane below price. Combine with your normal structure analysis — higher lows, double bottoms, coils, etc. — and act only when structure and sponsorship line up.
Pine Script®指標
由Mando4_27提供
Inside SwingsOverview The Inside Swings indicator identifies and visualizes "inside swing" patterns in price action. These patterns occur when price creates a series of pivots that form overlapping ranges, indicating potential consolidation or reversal zones. What are Inside Swings? Inside swings are specific pivot patterns where: - HLHL Pattern: High-Low-High-Low sequence where the first high is higher than the second high, and the first low is lower than the second low - LHLH Pattern: Low-High-Low-High sequence where the first low is lower than the second low, and the first high is higher than the second high Here an Example These patterns create overlapping price ranges that often act as: - Support/Resistance zones - Consolidation areas - Potential reversal points - Breakout levels Levels From the Created Range Input Parameters Core Settings - Pivot Lookback Length (default: 5): Number of bars on each side to confirm a pivot high/low - Max Boxes (default: 100): Maximum number of patterns to display on chart Extension Settings - Extend Lines: Enable/disable line extensions - this extends the Extremes of the Swings to where a new Swing Started or Extended Right for the Latest Inside Swings - Show High 1 Line: Display first high/low extension line - Show High 2 Line: Display second high/low extension line - Show Low 1 Line: Display first low/high extension line - Show Low 2 Line: Display second low/high extension line Visual Customization Box Colors - HLHL Box Color: Color for HLHL pattern boxes (default: green) - HLHL Border Color: Border color for HLHL boxes - LHLH Box Color: Color for LHLH pattern boxes (default: red) - LHLH Border Color: Border color for LHLH boxes Line Colors - HLHL Line Color: Extension line color for HLHL patterns - LHLH Line Color: Extension line color for LHLH patterns - Line Width: Thickness of extension lines (1-5) Pattern Detection Logic HLHL Pattern (Bullish Inside Swing) Condition: High1 > High2 AND Low1 < Low2 Sequence: High → Low → High → Low Visual: Two overlapping boxes with first range encompassing second Detection Criteria: 1. Last 4 pivots form High-Low-High-Low sequence 2. Fourth pivot (first high) > Second pivot (second high) 3. Third pivot (first low) < Last pivot (second low) LHLH Pattern (Bearish Inside Swing) Condition: Low1 < Low2 AND High1 > High2 Sequence: Low → High → Low → High Visual: Two overlapping boxes with first range encompassing second Detection Criteria: 1. Last 4 pivots form Low-High-Low-High sequence 2. Fourth pivot (first low) < Second pivot (second low) 3. Third pivot (first high) > Last pivot (second high) Visual Elements Boxes - Box 1: Spans from first pivot to last pivot (larger range) - Box 2: Spans from third pivot to last pivot (smaller range) - Overlap: The intersection of both boxes represents the inside swing zone Extension Lines - High 1 Line: Horizontal line at first high/low level - High 2 Line: Horizontal line at second high/low level - Low 1 Line: Horizontal line at first low/high level - Low 2 Line: Horizontal line at second low/high level Line Extension Behavior - Historical Patterns: Lines extend until the next pattern starts - Latest Pattern: Lines extend to the right edge of chart - Dynamic Updates: All lines are redrawn on each bar for accuracy Trading Applications Support/Resistance Levels Inside swing levels often act as: - Dynamic support/resistance - Breakout confirmation levels - Reversal entry points Pattern Interpretation - HLHL Patterns: Potential bullish continuation or reversal - LHLH Patterns: Potential bearish continuation or reversal - Overlap Zone: Key area for price interaction Entry Strategies 1. Breakout Strategy: Enter on break above/below inside swing levels 2. Reversal Strategy: Enter on bounce from inside swing levels 3. Range Trading: Trade between inside swing levels Technical Implementation Data Structures type InsideSwing int startBar // First pivot bar int endBar // Last pivot bar string patternType // "HLHL" or "LHLH" float high1 // First high/low float low1 // First low/high float high2 // Second high/low float low2 // Second low/high box box1 // First box box box2 // Second box line high1Line // High 1 extension line line high2Line // High 2 extension line line low1Line // Low 1 extension line line low2Line // Low 2 extension line bool isLatest // Latest pattern flag Memory Management - Pattern Storage: Array-based storage with automatic cleanup - Pivot Tracking: Maintains last 4 pivots for pattern detection - Resource Cleanup: Automatically removes oldest patterns when limit exceeded Performance Optimization - Duplicate Prevention: Checks for existing patterns before creation - Efficient Redraw: Only redraws lines when necessary - Memory Limits: Configurable maximum pattern count Usage Tips Best Practices 1. Combine with Volume: Use volume confirmation for breakouts 2. Multiple Timeframes: Check higher timeframes for context 3. Risk Management: Set stops beyond inside swing levels 4. Pattern Validation: Wait for confirmation before entering Common Scenarios - Consolidation Breakouts: Inside swings often precede significant moves - Reversal Zones: Failed breakouts at inside swing levels - Trend Continuation: Inside swings in trending markets Limitations - Lagging Indicator: Patterns form after completion - False Signals: Not all inside swings lead to significant moves - Market Dependent: Effectiveness varies by market conditions Customization Options Visual Adjustments - Modify colors for different market conditions - Adjust line widths for visibility - Enable/disable specific elements Detection Sensitivity - Increase pivot length for smoother patterns - Decrease for more sensitive detection - Balance between noise and signal Display Management - Control maximum pattern count - Adjust cleanup frequency - Manage memory usage Conclusion The Inside Swings indicator provides a systematic approach to identifying consolidation and potential reversal zones in price action. By visualizing overlapping pivot ranges The indicator's strength lies in its ability to: - Identify key price levels automatically - Provide visual context for market structure - Offer flexible customization options - Maintain performance through efficient memory management
Pine Script®指標
由mindyourbuisness提供
4
Torus Trend Bands — Windowed HammingTorus Trend Bands — Windowed Hamming This TradingView indicator creates dynamic support and resistance bands on your chart. It uses the mathematical model of a torus (a donut shape) to generate cyclical and responsive channel boundaries. The bands are further refined with an advanced smoothing method called a Hamming window to reduce noise and provide a clearer signal. How It Works The Torus Model: The indicator maps price action onto a geometric torus shape. This is defined by two key parameters: Major Radius (a): The distance from the center of the torus to the center of the tube. This controls the overall size and primary cycle. Minor Radius (b): The radius of the tube itself. This controls the secondary, faster "breathing" motion of the bands. Dual-Phase Engine: The behavior of the bands is driven by two different cyclical inputs, or "phases": Major Rotation (φ): A slow, time-based cycle (φ period) that governs the long-term oscillation of the bands. Minor Rotation (q): A fast, momentum-based cycle derived from the Relative Strength Index (RSI). This makes the bands react quickly to price momentum, expanding and contracting as the market becomes overbought or oversold. Standard Technical Core : The torus model is anchored to the price chart using standard indicators: Midline : A central moving average that acts as the baseline for the channel. You can choose from EMA, SMA, HMA, or VWAP. Width Source: A volatility measure that determines the fundamental width of the bands. You can choose between the Average True Range (ATR) or Standard Deviation. Hamming Window Smoothing: This is a sophisticated weighted averaging technique (a Finite Impulse Response filter) used in digital signal processing. It provides exceptionally smooth results with less lag than traditional moving averages. You can apply this smoothing to the RSI, the midline, and the width source independently to filter out market noise. How to Interpret and Use the Indicator Dynamic Support & Resistance: The primary use is to identify potential reversal or continuation points. The upper band acts as dynamic resistance, and the lower band acts as dynamic support. Trend Identification: The color of the bands helps you quickly see the current trend. Teal bands indicate an uptrend (the midline is rising), while red bands indicate a downtrend (the midline is falling). Volatility Gauge: When the bands widen, it signals an increase in market volatility. When they contract, it suggests volatility is decreasing. Alerts: The indicator includes built-in alerts that can notify you when the price touches or breaks through the upper or lower bands, helping you stay on top of key price action. Key Settings Torus Parameters : Adjust Major radius a and Minor radius b to change the shape and cyclical behavior of the bands. Phase Controls: φ period: Controls the length of the main, slow cycle in bars. RSI length → q: Sets the lookback for the RSI that drives the momentum-based cycle. Midline & Width: Choose the type and length for the central moving average and the volatility source (ATR/StDev) that best fits your trading style. Width & Bias Shaping: Min/Max width ×: Control how much the bands expand and contract. Bias ×: Shifts the entire channel up or down based on RSI momentum, helping the bands better capture strong trends. Hamming Controls: Enable or disable the advanced smoothing on different parts of the indicator and set the Hamming length (a longer length results in more smoothing). This indicator provides a unique and highly customizable way to visualize market cycles, volatility, and trend, combining geometry with proven technical analysis tools.
Pine Script®指標
由Cmo22提供
Divergence for Many Indicators v5 - No RepaintUses confirmed bar processing to prevent repainting, ensuring signals never change after they appear. Automatically draws divergence lines on the chart and labels show which indicators are diverging. Customizable settings include pivot period, minimum divergence threshold, line styles, and colors for different divergence types. Ideal for identifying potential trend reversals (regular divergence) and trend continuations (hidden divergence) with high-confidence multi-indicator confirmation.
Pine Script®指標
由mnights提供
1
Smart Money Dynamics Blocks — Pearson MatrixSmart Money Dynamics Blocks — Pearson Matrix A structural fusion of Prime Number Theory, Pearson Correlation, and Cumulative Delta Geometry. 1. Mathematical Foundation This indicator is built on the intersection of Prime Number Theory and the Pearson correlation coefficient, creating a structural framework that quantifies how price and time evolve together. Prime numbers — unique, indivisible, and irregular — are used here as nonlinear time intervals. Each prime length (2, 3, 5, 7, 11…97) represents a regression horizon where correlation is measured between price and time. The result is a multi-scale correlation lattice — a geometric matrix that captures hidden directional strength and temporal bias beyond traditional moving averages. 2. The Pearson Matrix Logic For every prime interval p, the indicator calculates the linear correlation: r_p = corr(price, bar_index, p) Each r_p reflects how closely price and time move together across a prime-defined window. All r_p values are then averaged to create avgR, a single adaptive coefficient summarizing overall structural coherence. - When avgR > 0.8 → strong positive correlation (labeled R+). - When avgR < -0.8 → strong negative correlation (labeled R−). This approach gives a mathematically grounded definition of trend — one that isn’t based on pattern recognition, but on measurable correlation strength. 3. Sequential Prime Slope and Median Pivot Using the ordered sequence of 25 prime intervals, the model computes sequential slopes between adjacent primes. These slopes represent the rate of change of structure between two prime scales. A robust median aggregator smooths the slopes, producing a clean, stable directional vector. The system anchors this slope to the 41-bar pivot — the median of the first 25 primes — serving as the geometric midpoint of the prime lattice. The resulting yellow line on the chart is not an ordinary regression line; it’s a dynamic prime-slope function, adapting continuously with correlation feedback. 4. Regression-Style Parallel Bands Around this prime-slope line, the indicator constructs parallel bands using standard deviation envelopes — conceptually similar to a regression channel but recalculated through the prime–Pearson matrix. These bands adjust dynamically to: - Volatility, via standard deviation of residuals. - Correlation strength, via avgR sign weighting. Together, they visualize statistical deviation geometry, making it easier to observe symmetry, expansion, and contraction phases of price structure. 5. Volume and Cumulative Delta Peaks Below the geometric layer, the indicator incorporates a custom lower-timeframe volume feed — by default using 15-second data (custom_tf_input_volume = “15S”). This allows precise delta computation between up-volume and down-volume even on higher timeframe charts. From this feed, the indicator accumulates delta over a configurable period (default: 100 bars). When cumulative delta reaches a local maximum or minimum, peak and trough markers appear, showing the precise bar where buying or selling pressure statistically peaked. This combination of geometry and order flow reveals the intersection of market structure and energy — where liquidity pressure expresses itself through mathematical form. 6. Chart Interpretation The primary chart view represents the live execution of the indicator. It displays the relationship between structural correlation and volume behavior in real time. Orange “R+” and blue “R−” labels indicate regions of strong positive or negative Pearson correlation across the prime matrix. The yellow median prime-slope line serves as the structural backbone of the indicator, while green and red parallel bands act as dynamic regression boundaries derived from the underlying correlation strength. Peaks and troughs in cumulative delta — displayed as numerical annotations — mark statistically significant shifts in buying and selling pressure. The secondary visualization (Prime Regression Concept) expands on this by illustrating how regression behavior evolves across prime intervals. Each colored regression fan corresponds to a prime number window (2, 3, 5, 7, …, 97), demonstrating how multiple regression lines would appear if drawn independently. The indicator integrates these into one unified geometric model — eliminating the need to plot tens of regression lines manually. It’s a conceptual tool to help visualize the internal logic: the synthesis of many small-scale regressions into a single coherent structure. 7. Interpretive Insight This model is not a prediction tool; it’s an instrument of mathematical observation. By translating price dynamics into a prime-structured correlation space, it reveals how coherence unfolds through time — not as a forecast, but as a measurable evolution of structure. It unifies three analytical domains: - Prime distribution — defines a nonlinear temporal architecture. - Pearson correlation — quantifies statistical cohesion. - Cumulative delta — expresses behavioral imbalance in order flow. The synthesis creates a geometric analysis of liquidity and time — where structure meets energy, and where the invisible rhythm of market flow becomes measurable. 8. Contribution & Feedback Share your observations in the comments: - The time gap and alternation between R+ and R− clusters. - How different timeframes change delta sensitivity or reveal compression/expansion. - Prime intervals/clusters that tend to sit near turning points or liquidity shifts. - How avgR behaves across assets or regimes (trending, ranging, high-vol). - Notable interactions with the parallel bands (touches, breaks, mean-revert). Your field notes help others read the model more effectively and compare contexts. Summary - Primes define the structure. - Pearson quantifies coherence. - Slope median stabilizes geometry. - Regression bands visualize deviation. - Cumulative delta locates imbalance. Together, they construct a framework where mathematics meets market behavior.
Pine Script®指標
由ata_sabanci提供
2
Tradytics Levels with EMA CloudThis indicator has tradytics price chart levels where you can put in the input code seen below. The code has positive gamma (green lines), negative gamma (Red lines) and white dotted line are the darkpool levels. This is Amazon's 5 minute from Sep30th to October 20th Gammas and weekly Darkpool levels. Just copy and paste code below in the input code and the chart would show the levels. 212.8*1*neutral 220.07*1*neutral 216.038*1*neutral 215.57*1*neutral 219.988*1*neutral 217.401*1*neutral 217.351*1*neutral 212.815*1*neutral 212.75*1*neutral 212.4*1*neutral 215*0*negative 222.5*0*positive 217.5*0*positive 220*0*positive
Pine Script®指標
由Mstr_Robobot提供
4h 相对超跌筛选器 · Webhook v2.0## 指标用途 用于你的「框架第2步」：在**美股 RTH**里，按**4h 收盘**（06:30–10:30 PT 为首根）筛出相对大盘/行业**显著超跌**且结构健康的候选标的，并可**通过 Webhook 自动推送**`symbol + ts`给下游 AI 执行新闻甄别（第3步）与进出场评估（第4步）。 ## 工作原理（核心逻辑） * **结构健康**：最近 80 根 4h 中，收盘 > 4h_SMA50 的占比 ≥ 阈值（默认 55%）。 * **跌深条件**：4h 跌幅 ≤ −4%，且近两根累计（≈8h）≤ −6%。 * **相对劣化**：相对大盘（SPY/QQQ）与相对行业（XLK/XLF/… 或 KWEB/CQQQ）各 ≤ −3%。 * **流动性与价格**：ADV20_USD ≥ 2000 万；价格 ≥ 3 美元。 * **只在 4h 收盘刻评估与触发**，历史点位全部保留，便于回放核验。 * **冷却**：同一标的信号间隔 ≥ N 天（默认 10）。 ## 主要输入参数 * **bench / sector**：大盘与行业基准（例：SPY/QQQ，XLK/XLF/XLY；中概用 KWEB/CQQQ）。 * **advMinUSD / priceMin**：20 日美元成交额下限、最小价格。 * **pctAboveTh**：结构健康阈值（%）。 * **drop4hTh / drop8hTh**：4h/8h 跌幅阈值（%）。 * **relMktTh / relSecTh**：相对大盘/行业阈值（%）。 * **coolDays**：冷却天数。 * **fromDate**：仅显示此日期后的历史信号（图表拥挤时可用）。 * **showTable / tableRows**：是否显示右上角“最近信号表”及行数。 ## 图表信号 * **S2 绿点**：当根 4h 收盘满足全部筛选条件。 * **右上角表格**：滚动列出最近 N 条命中（`SYMBOL @ yyyy-MM-dd HH:mm`，按图表本地时区）。 ## Webhook 联动（生产用） 1. 添加指标 → 🔔 新建警报（Alert）： * **Condition**：`Any alert() function call` * **Options**：`Once per bar close` * **Webhook URL**：填你的接收地址（可带 `?token=...`） * **Message**：留空（脚本内部 `alert(payload)` 会发送 JSON）。 2. 典型 JSON 载荷（举例）： ```json { "event": "step2_signal", "symbol": "LULU", "symbol_id": "NASDAQ:LULU", "venue": "NASDAQ", "bench": "SPY", "sector": "XLY", "ts_bar_close_ms": 1754524200000, "ts_bar_close_local": "2025-06-06 10:30", "price_close": 318.42, "ret_4h_pct": -5.30, "ret_8h_pct": -7.45, "rel_mkt_pct": -4.90, "rel_sec_pct": -3.80 } ``` > 建议以 `symbol + ts_bar_close_ms` 做去重键；接收端先快速 `200 OK`，后续异步处理并交给第3步 AI。 ## 使用建议 * **时间框架**：任意周期可用，指标内部统一拉取 240 分钟数据并仅在 4h 收盘刻触发。 * **行业映射**：尽量选与个股业务最贴近的 ETF；中国 ADR 可用 `PGJ/KWEB/CQQQ` 叠加细分行业对照。 * **回放验证**：Bar Replay **不发送真实 Webhook**；仅用于查看历史命中与表格。测试接收端请用 Alert 面板的 **Test**。 ## 适配说明 * Pine Script **v5**。 * 不含成分筛查逻辑（请在你的 500–600 只候选池内使用）。 * 数字常量不使用下划线分隔；如需大数可用 `20000000` 或 `2e7`。 ## 常见问题 * ⛔️ 报错 `tostring(...)`：Pine 无时间格式化重载，脚本已内置 `timeToStr()`。 * ⛔️ `syminfo.exchange` 不存在：已改用 `syminfo.prefix`（交易所前缀）。 * ⛔️ 多行字符串拼接报 `line continuation`：本脚本已用括号包裹或 `str.format` 规避。 ## 免责声明 该指标仅供筛选与研究使用，不构成投资建议。请结合你的第3步新闻/基本面甄别与第4步执行规则共同决策。
Pine Script®指標
由lvyaofeng19920413提供
Trend Strength Detector TSDTrend Strength Detector (TSD) *Objective Trend Quality Measurement for Educational Market Analysis* Note: This mathematical framework is a proprietary quantitative model developed by Ario Pinelab, inspired by classical EMA, ADX, RSI and MACD principles, yet not documented in any public technical or academic publication. ## 🎯 Purpose & Design Philosophy The ** Trend Strength Detector- TSD ** is an educational research tool that provides **quantitative measurement of trend quality** through two independent scoring systems (0-100 scale). It answers the analytical question: *"How strong and aligned is the current market trend environment?"* This indicator is designed with a **modular, complementary approach** to work alongside various analysis methodologies, particularly pattern-based recognition systems. ## 🔗 Complementary Research Framework ### Designed to Work With Pattern Detection Systems This indicator provides **environmental context measurement** that complements qualitative pattern recognition tools. It works particularly well alongside systems like: - **RMBS Smart Detector - Multi-Factor Momentum System** - Traditional chart pattern analyzers - Any momentum-based pattern identification tools 🔍 **To find RMBS Smart Detector:** - Search in TradingView Indicators Library: `" RMBS Smart Detector - Multi-Factor Momentum System"` - Look for: *Multi-Factor Momentum System* - By author: ` ` ### Why This Complementary Approach? **Trend Quality Measurement** (TSD - this tool) provides: - ✅ Structural trend alignment (0-100 score) - ✅ Momentum intensity levels (0-100 score) - ✅ Environment classification (Strong/Moderate/Weak) - 📌 **Answers:** *"HOW STRONG is the underlying trend environment?"* ### Educational Research Value When used together in a research context, these tools enable systematic study of questions like: - How do reversal patterns behave when Strength Score is above 70 vs below 30? - Do continuation patterns in weakening environments (declining scores) show different characteristics? - What is the correlation between high Alignment Scores and pattern "success rates"? - Can environment classification help identify genuine trend initiation vs false starts? ⚠️ **Important Note:** Both tools are **independent and work standalone**. TSD provides value whether used alone or with other analysis methods. The relationship with RMBS (or any pattern tool) is **complementary for research purposes**, not dependent. --- ###Mathematical Foundation ##TSA Formula: scoring method developed by Ario -Trend Model (0 – 100) TAS = EMA Alignment (0–40) + Price Position (0–30) + Trend Consistency (0–30) EMA Alignment checks EMA_fast vs EMA_slow vs EMA_trend structure. Price Position evaluates if Close is above/below all EMAs. Consistency = 3 × max(bullish,bearish bars within 10 candles). -Strength Model (0 – 100) Strength = ADX (0–50) + EMA Slope (0–25) + RSI (0–15) + MACD (0–10) ADX measures trend energy; Slope shows EMA momentum %; RSI assesses zone positioning; MACD confirms directional agreement. Note: This formula represents a proprietary quantitative model by Ario_Pinelab, inspired by classical technical concepts but not published in any external reference.________________________________________ 📊 Environment Classification Based on Total Strength Score: 🟢 Strong Environment: Score ≥ 60 → Well-defined momentum, clear directional bias 🟡 Moderate Environment: 40 ≤ Score < 60 → Mixed signals, transitional conditions 🔴 Weak Environment: Score < 40 → Ranging, choppy, low conviction movement Color Coding: • Green background: Strong (≥60) • Yellow background: Moderate (40-59) • Red background: Weak (<40) ________________________________________ 📈 Visual Components Main Chart Display Score Labels (Top-Right Corner): ┌─────────────────────────────────┐ │ 📊 Alignment: 75 | Strength: 82 │ │ Environment: Strong 🟢 │ └─────────────────────────────────┘ Color-Coded Background: • Environment strength visually indicated via background color • Helps quick identification of market regime • Customizable transparency (default: 90%) Reference Lines: • Dotted line at 60: Strong/Moderate threshold • Dotted line at 40: Moderate/Weak threshold • Mid-line at 50: Neutral reference ________________________________________ 🔧 Customization Settings Input Parameters The best setting is the default mode. 🚫 Important Disclaimers & Limitations What This Indicator IS: ✅ Educational measurement tool for trend quality research ✅ Quantitative assessment of current market environment ✅ Complementary analysis tool for pattern-based systems ✅ Historical data analyzer for systematic study ✅ Multi-factor scoring system based on technical calculations What This Indicator IS NOT: ❌ NOT a trading system or signal generator ❌ NOT financial advice or trade recommendations ❌ NOT predictive of future price movements ❌ NOT a guarantee of pattern success/failure ❌ NOT a substitute for comprehensive risk management ________________________________________ Known Limitations 1. Lagging Nature: ⚠️ All components (EMA, ADX, RSI, MACD) are calculated from historical price data → Scores reflect CURRENT and RECENT conditions → Cannot predict sudden reversals or black swan events → Trend measurements lag actual price turning points 2. Whipsaw Risk: ⚠️ In choppy/ranging markets, scores may fluctuate rapidly → Moderate zone (40-60) can see frequent transitions → Low timeframes more susceptible to noise → Consider higher timeframes for stable measurements 3. Component Conflicts: ⚠️ Individual components may disagree → Example: Strong ADX but weak RSI alignment → Scores average these conflicts (may hide nuance) → Check individual components for deeper insight 4. Not Predictive: ⚠️ High scores do NOT guarantee continuation ⚠️ Low scores do NOT guarantee reversal → Measurement ≠ Prediction → Use for CONTEXT, not SIGNALS → Combine with comprehensive analysis ________________________________________ Risk Acknowledgments Market Risk: • All trading involves substantial risk of loss • Past performance (even systematic studies) does not guarantee future results • No indicator, system, or methodology can eliminate market risk Measurement Limitations: • Scores are mathematical calculations, not market predictions • Environmental classification is descriptive, not prescriptive • Strong measurements can deteriorate rapidly without warning Educational Purpose: • This tool is designed for LEARNING about market structure • Not designed, tested, or validated as a standalone trading system • Any trading decisions are user’s sole responsibility No Warranty: • Indicator provided “as-is” for educational purposes • No guarantee of accuracy, reliability, or profitability • Users must verify calculations and apply critical thinking Open Source Full Pine Script code available for educational study and modification. Feedback and improvement suggestions welcome. “All logic is presented for research and educational visualization.” --- **Attribution & Fair Use Notice** The Trend Strength Detector (TSD) scoring framework (Multi-Factor Momentum System) was originally designed and formulated by *Ahmadrezarahmati( Ario or Ario_ Pine Lab)*. If you build upon, modify, or republish this logic—please include proper attribution to the original author. This request is made under a spirit of open collaboration and educational fairness.
Pine Script®指標
由Ario_pinelab提供
2