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3D Institutional Battlefield [SurgeGuru]Professional Presentation: 3D Institutional Flow Terrain Indicator Overview The 3D Institutional Flow Terrain is an advanced trading visualization tool that transforms complex market structure into an intuitive 3D landscape. This indicator synthesizes multiple institutional data points—volume profiles, order blocks, liquidity zones, and voids—into a single comprehensive view, helping you identify high-probability trading opportunities. Key Features 🎥 Camera & Projection Controls Yaw & Pitch: Adjust viewing angles (0-90°) for optimal perspective Scale Controls: Fine-tune X (width), Y (depth), and Z (height) dimensions Pro Tip: Increase Z-scale to amplify terrain features for better visibility 🌐 Grid & Surface Configuration Resolution: Adjust X (16-64) and Y (12-48) grid density Visual Elements: Toggle surface fill, wireframe, and node markers Optimization: Higher resolution provides more detail but requires more processing power 📊 Data Integration Lookback Period: 50-500 bars of historical analysis Multi-Source Data: Combine volume profile, order blocks, liquidity zones, and voids Weighted Analysis: Each data source contributes proportionally to the terrain height How to Use the Frontend 💛 Price Line Tracking (Your Primary Focus) The yellow price line is your most important guide: Monitor Price Movement: Track how the yellow line interacts with the 3D terrain Identify Key Levels: Watch for these critical interactions: Order Blocks (Green/Red Zones): When yellow price line enters green zones = Bullish order block When yellow price line enters red zones = Bearish order block These represent institutional accumulation/distribution areas Liquidity Voids (Yellow Zones): When yellow price line enters yellow void areas = Potential acceleration zones Voids indicate price gaps where minimal trading occurred Price often moves rapidly through voids toward next liquidity pool Terrain Reading: High Terrain Peaks: High volume/interest areas (support/resistance) Low Terrain Valleys: Low volume areas (potential breakout zones) Color Coding: Green terrain = Bullish volume dominance Red terrain = Bearish volume dominance Purple = Neutral/transition areas 📈 Volume Profile Integration POC (Point of Control): Automatically marks highest volume level Volume Bins: Adjust granularity (10-50 bins) Height Weight: Control how much volume affects terrain elevation 🏛️ Order Block Detection Detection Length: 5-50 bar lookback for block identification Strength Weighting: Recent blocks have greater impact on terrain Candle Body Option: Use full candles or body-only for block definition 💧 Liquidity Zone Tracking Multiple Levels: Track 3-10 key liquidity zones Buy/Sell Side: Different colors for bid/ask liquidity Strength Decay: Older zones have diminishing terrain impact 🌊 Liquidity Void Identification Threshold Multiplier: Adjust sensitivity (0.5-2.0) Height Amplification: Voids create significant terrain depressions Acceleration Zones: Price typically moves quickly through void areas Practical Trading Application Bullish Scenario: Yellow price line approaches green order block terrain Price finds support in elevated bullish volume areas Terrain shows consistent elevation through key levels Bearish Scenario: Yellow price line struggles at red order block resistance Price falls through liquidity voids toward lower terrain Bearish volume peaks dominate the landscape Breakout Setup: Yellow price line consolidates in flat terrain Minimal resistance (low terrain) in projected direction Clear path toward distant liquidity zones Pro Tips Start Simple: Begin with default settings, then gradually customize Focus on Yellow Line: Your primary indicator of current price position Combine Timeframes: Use the same terrain across multiple timeframes for confluence Volume Confirmation: Ensure terrain peaks align with actual volume spikes Void Anticipation: When price enters voids, prepare for potential rapid movement Order Blocks & Voids Architecture Order Blocks Calculation Trigger: Price breaks fractal swing points Bullish OB: When close > swing high → find lowest low in lookback period Bearish OB: When close < swing low → find highest high in lookback period Strength: Based on price distance from block extremes Storage: Global array maintains last 50 blocks with FIFO management Liquidity Voids Detection Trigger: Price gaps exceeding ATR threshold Bull Void: Low - high > (ATR200 × multiplier) Bear Void: Low - high > (ATR200 × multiplier) Validation: Close confirms gap direction Storage: Global array maintains last 30 voids Key Design Features Real-time Updates: Calculated every bar, not just on last bar Global Persistence: Arrays maintain state across executions FIFO Management: Automatic cleanup of oldest entries Configurable Sensitivity: Adjustable lookback periods and thresholds Scientific Testing Framework Hypothesis Testing Primary Hypothesis: 3D terrain visualization improves detection of institutional order flow vs traditional 2D charts Testable Metrics: Prediction Accuracy: Does terrain structure predict future support/resistance? Reaction Time: Faster identification of key levels vs conventional methods False Positive Reduction: Lower rate of failed breakouts/breakdowns Control Variables Market Regime: Trending vs ranging conditions Asset Classes: Forex, equities, cryptocurrencies Timeframes: M5 to H4 for intraday, D1 for swing Volume Conditions: High vs low volume environments Data Collection Protocol Terrain Features to Quantify: Slope gradient changes at price inflection points Volume peak clustering density Order block terrain elevation vs subsequent price action Void depth correlation with momentum acceleration Control Group: Traditional support/resistance + volume profile Experimental Group: 3D Institutional Flow Terrain Statistical Measures Signal-to-Noise Ratio: Terrain features vs random price movements Lead Time: Terrain formation ahead of price confirmation Effect Size: Performance difference between groups (Cohen's d) Statistical Power: Sample size requirements for significance Validation Methodology Blind Testing: Remove price labels from terrain screenshots Have traders identify key levels from terrain alone Measure accuracy vs actual price action Backtesting Framework: Automated terrain feature extraction Correlation with future price reversals/breakouts Monte Carlo simulation for significance testing Expected Outcomes If hypothesis valid: Significant improvement in level prediction accuracy (p < 0.05) Reduced latency in institutional level identification Higher risk-reward ratios on terrain-confirmed trades Research Questions: Does terrain elevation reliably indicate institutional interest zones? Are liquidity voids statistically significant momentum predictors? Does multi-timeframe terrain analysis improve signal quality? How does terrain persistence correlate with level strength? LuxAlgo BigBeluga hapharmonic
Pine Script®指標
由SurgeGuru提供
2
Dual FUT/Spot price with next monthly expiryThis Pine Script dashboard indicator is specifically designed for pair trading strategies in Indian futures markets (NSE). Let me break down how it facilitates pair trading: Core Pair Trading Concept The script monitors two correlated stocks simultaneously (Symbol A and Symbol B), comparing their: Spot prices vs Futures prices Current month futures vs Next month futures Premium/discount relationships Key Pair Trading Features 1. Dual Symbol Monitoring symbolA = "NSE:TCS" (Default) symbolB = "NSE:INFY" (Default) Allows traders to watch two stocks in the same sector (like TCS and Infosys in IT) to identify relative value opportunities. 2. Basis Analysis for Each Stock The indicator calculates the basis (difference between futures and spot): Price Difference: FUT - SPOT Premium/Discount %: ((FUT - SPOT) / SPOT) × 100 This helps identify when one stock's futures are relatively more expensive than the other's. 3. Multi-Expiry View Near Month Futures (1!): Current active contract Next Month Futures (2!): Upcoming contract This enables calendar spread analysis within each stock and helps anticipate rollover effects. 4. Comparative Table The detailed table displays side-by-side: Symbol Spot Price Near Future Near Diff (%)Next Monthly Next Diff (%)Lot SizeTCS₹3,500₹3,520+20 (+0.57%)₹3,535+35 (+1.00%)125INFY₹1,450₹1,455+5 (+0.34%)₹1,460+10 (+0.69%)600 5. Lot Size Integration Critical for position sizing in pair trades - the indicator fetches actual contract lot sizes, enabling proper hedge ratio calculations. Pair Trading Strategies Enabled Strategy 1: Basis Divergence Trading When TCS futures trade at +0.8% premium and INFY at +0.2% Trade: Short TCS futures, Long INFY futures (betting on convergence) The indicator highlights these differences with color-coded cells Strategy 2: Calendar Spread Arbitrage Compare near month vs next month premium for each stock If TCS shows wider calendar spread than INFY, potential arbitrage exists Trade the relative calendar spread difference Strategy 3: Premium/Discount Reversal Monitor which stock moves from premium to discount (or vice versa) Color indicators (green/red) make this immediately visible Enter pairs when relative premium relationships normalize Strategy 4: Lot-Adjusted Pair Trading Use lot size data to create market-neutral positions Example: If TCS lot = 125 and INFY lot = 600 Ratio = 600/125 = 4.8:1 for rupee-neutral positioning Visual Trading Cues Green cells: Futures at premium (contango) Red cells: Futures at discount (backwardation) Purple values: Next month contracts Yellow highlights: Spot prices Practical Pair Trading Example Scenario: Both stocks in same sector, historically correlated Normal state: Both show +0.5% premium Divergence: TCS jumps to +1.2%, INFY stays at +0.5% Trade Signal: Short TCS futures (expensive) Long INFY futures (relatively cheap) Exit: When premiums converge back to similar levels Hedge ratio: Use lot sizes to maintain proper exposure balance Advantages for Pair Traders ✓ Single-screen monitoring of both legs ✓ Real-time basis calculations eliminate manual math ✓ Multi-timeframe view (near + next month) ✓ Automatic lot size fetching for position sizing ✓ Visual alerts through color coding ✓ Percentage normalization for easy comparison This indicator essentially transforms raw price data into actionable pair trading intelligence by highlighting relative value discrepancies between correlated assets in the futures market. Enjoy!!
Pine Script®指標
由kingshukghosh71提供
Scientific Correlation Testing FrameworkScientific Correlation Testing Framework - Comprehensive Guide Introduction to Correlation Analysis What is Correlation? Correlation is a statistical measure that describes the degree to which two assets move in relation to each other. Think of it like measuring how closely two dancers move together on a dance floor. Perfect Positive Correlation (+1.0): Both dancers move in perfect sync, same direction, same speed Perfect Negative Correlation (-1.0): Both dancers move in perfect sync but in opposite directions Zero Correlation (0): The dancers move completely independently of each other In financial markets, correlation helps us understand relationships between different assets, which is crucial for: Portfolio diversification Risk management Pairs trading strategies Hedging positions Market analysis Why This Script is Special This script goes beyond simple correlation calculations by providing: Two different correlation methods (Pearson and Spearman) Statistical significance testing to ensure results are meaningful Rolling correlation analysis to track how relationships change over time Visual representation for easy interpretation Comprehensive statistics table with detailed metrics Deep Dive into the Script's Components 1. Input Parameters Explained- Symbol Selection: This allows you to select the second asset to compare with the chart's primary asset Default is Apple (NASDAQ:AAPL), but you can change this to any symbol Example: If you're viewing a Bitcoin chart, you might set this to "NASDAQ:TSLA" to see if Bitcoin and Tesla are correlated Correlation Window (60): This is the number of periods used to calculate the main correlation Larger values (e.g., 100-500) provide more stable, long-term correlation measures Smaller values (e.g., 10-50) are more responsive to recent price movements 60 is a good balance for most daily charts (about 3 months of trading days) Rolling Correlation Window (20): A shorter window to detect recent changes in correlation This helps identify when the relationship between assets is strengthening or weakening Default of 20 is roughly one month of trading days Return Type: This determines how price changes are calculated Simple Returns: (Today's Price - Yesterday's Price) / Yesterday's Price Easy to understand: "The asset went up 2% today" Log Returns: Natural logarithm of (Today's Price / Yesterday's Price) More mathematically elegant for statistical analysis Better for time-additive properties (returns over multiple periods) Less sensitive to extreme values. Confidence Level (95%): This determines how certain we want to be about our results 95% confidence means we accept a 5% chance of being wrong (false positive) Higher confidence (e.g., 99%) makes the test more strict Lower confidence (e.g., 90%) makes the test more lenient 95% is the standard in most scientific research Show Statistical Significance: When enabled, the script will test if the correlation is statistically significant or just due to random chance. Display options control what you see on the chart: Show Pearson/Spearman/Rolling Correlation: Toggle each correlation type on/off Show Scatter Plot: Displays a scatter plot of returns (limited to recent points to avoid performance issues) Show Statistical Tests: Enables the detailed statistics table Table Text Size: Adjusts the size of text in the statistics table 2.Functions explained- calcReturns(): This function calculates price returns based on your selected method: Log Returns: Formula: ln(Price_t / Price_t-1) Example: If a stock goes from $100 to $101, the log return is ln(101/100) = ln(1.01) ≈ 0.00995 or 0.995% Benefits: More symmetric, time-additive, and better for statistical modeling Simple Returns: Formula: (Price_t - Price_t-1) / Price_t-1 Example: If a stock goes from $100 to $101, the simple return is (101-100)/100 = 0.01 or 1% Benefits: More intuitive and easier to understand rankArray(): This function calculates the rank of each value in an array, which is used for Spearman correlation: How ranking works: The smallest value gets rank 1 The second smallest gets rank 2, and so on For ties (equal values), they get the average of their ranks Example: For values Sorted: Ranks: (the two 2s tie for ranks 1 and 2, so they both get 1.5) Why this matters: Spearman correlation uses ranks instead of actual values, making it less sensitive to outliers and non-linear relationships. pearsonCorr(): This function calculates the Pearson correlation coefficient: Mathematical Formula: r = (nΣxy - ΣxΣy) / √ Where x and y are the two variables, and n is the sample size What it measures: The strength and direction of the linear relationship between two variables Values range from -1 (perfect negative linear relationship) to +1 (perfect positive linear relationship) 0 indicates no linear relationship Example: If two stocks have a Pearson correlation of 0.8, they have a strong positive linear relationship When one stock goes up, the other tends to go up in a fairly consistent proportion spearmanCorr(): This function calculates the Spearman rank correlation: How it works: Convert each value in both datasets to its rank Calculate the Pearson correlation on the ranks instead of the original values What it measures: The strength and direction of the monotonic relationship between two variables A monotonic relationship is one where as one variable increases, the other either consistently increases or decreases It doesn't require the relationship to be linear When to use it instead of Pearson: When the relationship is monotonic but not linear When there are significant outliers in the data When the data is ordinal (ranked) rather than interval/ratio Example: If two stocks have a Spearman correlation of 0.7, they have a strong positive monotonic relationship When one stock goes up, the other tends to go up, but not necessarily in a straight-line relationship tStatistic(): This function calculates the t-statistic for correlation: Mathematical Formula: t = r × √((n-2)/(1-r²)) Where r is the correlation coefficient and n is the sample size What it measures: How many standard errors the correlation is away from zero Used to test the null hypothesis that the true correlation is zero Interpretation: Larger absolute t-values indicate stronger evidence against the null hypothesis Generally, a t-value greater than 2 (in absolute terms) is considered statistically significant at the 95% confidence level criticalT() and pValue(): These functions provide approximations for statistical significance testing: criticalT(): Returns the critical t-value for a given degrees of freedom (df) and significance level The critical value is the threshold that the t-statistic must exceed to be considered statistically significant Uses approximations since Pine Script doesn't have built-in statistical distribution functions pValue(): Estimates the p-value for a given t-statistic and degrees of freedom The p-value is the probability of observing a correlation as strong as the one calculated, assuming the true correlation is zero Smaller p-values indicate stronger evidence against the null hypothesis Standard interpretation: p < 0.01: Very strong evidence (marked with **) p < 0.05: Strong evidence (marked with *) p ≥ 0.05: Weak evidence, not statistically significant stdev(): This function calculates the standard deviation of a dataset: Mathematical Formula: σ = √(Σ(x-μ)²/(n-1)) Where x is each value, μ is the mean, and n is the sample size What it measures: The amount of variation or dispersion in a set of values A low standard deviation indicates that the values tend to be close to the mean A high standard deviation indicates that the values are spread out over a wider range Why it matters for correlation: Standard deviation is used in calculating the correlation coefficient It also provides information about the volatility of each asset's returns Comparing standard deviations helps understand the relative riskiness of the two assets. 3.Getting Price Data- price1: The closing price of the primary asset (the chart you're viewing) price2: The closing price of the secondary asset (the one you selected in the input parameters) Returns are used instead of raw prices because: Returns are typically stationary (mean and variance stay constant over time) Returns normalize for price levels, allowing comparison between assets of different values Returns represent what investors actually care about: percentage changes in value 4.Information Table- Creates a table to display statistics Only shows on the last bar to avoid performance issues Positioned in the top right of the chart Has 2 columns and 15 rows Populating the Table The script then populates the table with various statistics: Header Row: "Metric" and "Value" Sample Information: Sample size and return type Pearson Correlation: Value, t-statistic, p-value, and significance Spearman Correlation: Value, t-statistic, p-value, and significance Rolling Correlation: Current value Standard Deviations: For both assets Interpretation: Text description of the correlation strength The table uses color coding to highlight important information: Green for significant positive results Red for significant negative results Yellow for borderline significance Color-coded headers for each section => Practical Applications and Interpretation How to Interpret the Results Correlation Strength 0.0 to 0.3 (or 0.0 to -0.3): Weak or no correlation The assets move mostly independently of each other Good for diversification purposes 0.3 to 0.7 (or -0.3 to -0.7): Moderate correlation The assets show some tendency to move together (or in opposite directions) May be useful for certain trading strategies but not extremely reliable 0.7 to 1.0 (or -0.7 to -1.0): Strong correlation The assets show a strong tendency to move together (or in opposite directions) Can be useful for pairs trading, hedging, or as a market indicator Statistical Significance p < 0.01: Very strong evidence that the correlation is real Marked with ** in the table Very unlikely to be due to random chance p < 0.05: Strong evidence that the correlation is real Marked with * in the table Unlikely to be due to random chance p ≥ 0.05: Weak evidence that the correlation is real Not marked in the table Could easily be due to random chance Rolling Correlation The rolling correlation shows how the relationship between assets changes over time If the rolling correlation is much different from the long-term correlation, it suggests the relationship is changing This can indicate: A shift in market regime Changing fundamentals of one or both assets Temporary market dislocations that might present trading opportunities Trading Applications 1. Portfolio Diversification Goal: Reduce overall portfolio risk by combining assets that don't move together Strategy: Look for assets with low or negative correlations Example: If you hold tech stocks, you might add some utilities or bonds that have low correlation with tech 2. Pairs Trading Goal: Profit from the relative price movements of two correlated assets Strategy: Find two assets with strong historical correlation When their prices diverge (one goes up while the other goes down) Buy the underperforming asset and short the outperforming asset Close the positions when they converge back to their normal relationship Example: If Coca-Cola and Pepsi are highly correlated but Coca-Cola drops while Pepsi rises, you might buy Coca-Cola and short Pepsi 3. Hedging Goal: Reduce risk by taking an offsetting position in a negatively correlated asset Strategy: Find assets that tend to move in opposite directions Example: If you hold a portfolio of stocks, you might buy some gold or government bonds that tend to rise when stocks fall 4. Market Analysis Goal: Understand market dynamics and interrelationships Strategy: Analyze correlations between different sectors or asset classes Example: If tech stocks and semiconductor stocks are highly correlated, movements in one might predict movements in the other If the correlation between stocks and bonds changes, it might signal a shift in market expectations 5. Risk Management Goal: Understand and manage portfolio risk Strategy: Monitor correlations to identify when diversification benefits might be breaking down Example: During market crises, many assets that normally have low correlations can become highly correlated (correlation convergence), reducing diversification benefits Advanced Interpretation and Caveats Correlation vs. Causation Important Note: Correlation does not imply causation Example: Ice cream sales and drowning incidents are correlated (both increase in summer), but one doesn't cause the other Implication: Just because two assets move together doesn't mean one causes the other to move Solution: Look for fundamental economic reasons why assets might be correlated Non-Stationary Correlations Problem: Correlations between assets can change over time Causes: Changing market conditions Shifts in monetary policy Structural changes in the economy Changes in the underlying businesses Solution: Use rolling correlations to monitor how relationships change over time Outliers and Extreme Events Problem: Extreme market events can distort correlation measurements Example: During a market crash, many assets may move in the same direction regardless of their normal relationship Solution: Use Spearman correlation, which is less sensitive to outliers Be cautious when interpreting correlations during extreme market conditions Sample Size Considerations Problem: Small sample sizes can produce unreliable correlation estimates Rule of Thumb: Use at least 30 data points for a rough estimate, 60+ for more reliable results Solution: Use the default correlation length of 60 or higher Be skeptical of correlations calculated with small samples Timeframe Considerations Problem: Correlations can vary across different timeframes Example: Two assets might be positively correlated on a daily basis but negatively correlated on a weekly basis Solution: Test correlations on multiple timeframes Use the timeframe that matches your trading horizon Look-Ahead Bias Problem: Using information that wouldn't have been available at the time of trading Example: Calculating correlation using future data Solution: This script avoids look-ahead bias by using only historical data Best Practices for Using This Script 1. Appropriate Parameter Selection Correlation Window: For short-term trading: 20-50 periods For medium-term analysis: 50-100 periods For long-term analysis: 100-500 periods Rolling Window: Should be shorter than the main correlation window Typically 1/3 to 1/2 of the main window Return Type: For most applications: Log Returns (better statistical properties) For simplicity: Simple Returns (easier to interpret) 2. Validation and Testing Out-of-Sample Testing: Calculate correlations on one time period Test if they hold in a different time period Multiple Timeframes: Check if correlations are consistent across different timeframes Economic Rationale: Ensure there's a logical reason why assets should be correlated 3. Monitoring and Maintenance Regular Review: Correlations can change, so review them regularly Alerts: Set up alerts for significant correlation changes Documentation: Keep notes on why certain assets are correlated and what might change that relationship 4. Integration with Other Analysis Fundamental Analysis: Combine correlation analysis with fundamental factors Technical Analysis: Use correlation analysis alongside technical indicators Market Context: Consider how market conditions might affect correlations Conclusion This Scientific Correlation Testing Framework provides a comprehensive tool for analyzing relationships between financial assets. By offering both Pearson and Spearman correlation methods, statistical significance testing, and rolling correlation analysis, it goes beyond simple correlation measures to provide deeper insights. For beginners, this script might seem complex, but it's built on fundamental statistical concepts that become clearer with use. Start with the default settings and focus on interpreting the main correlation lines and the statistics table. As you become more comfortable, you can adjust the parameters and explore more advanced applications. Remember that correlation analysis is just one tool in a trader's toolkit. It should be used in conjunction with other forms of analysis and with a clear understanding of its limitations. When used properly, it can provide valuable insights for portfolio construction, risk management, and pair trading strategy development.
Pine Script®指標
由kingshukghosh71提供
ka66: Symbol InformationThis shows a table of all current (Pine v6) `syminfo.` values. Please note this is primarily of use to Pine Developers, or the curious trader. There are a few of these around on TradingView, but many seem to focus on the use case they have. This script just dumps all values, in alphabetical order of properties. You can use this to inspect the details of the symbol, which in turn, can be fed into various scripts covering tasks such as: Position Sizing calculation (which requires things like tick, pointvalue, and currency details) Recommendation engines (which use the recommendation_* properties) Fundamentals on stocks (which may use share count information, and possibly employee information) Note that not all table values are populated, as they depend on the instrument being introspected. For example, a share ticker will have some different details to a Forex pair. The `NaN` values (the "Not A Number" special value in programming parlance) are not a bug, they are simply Pine reporting that no value is set for it. I have opted to dump out values as-is as the focus is developers. My motivation to create it was to write a position sizing tool. Additionally, the output of this script is cleanly formatted, with monospace fonts and conventional alignment for tables/forms with key and values. It also allows customising the table position. Ideally this feature is made part of the default TradingView customisation, but at this time, it is not, and tables don't auto-adjust their positions.
Pine Script®指標
由ka66提供
Smart Money Volume Tools | Lyro RSSmart Money Volume Tools | Lyro RS Overview The Smart Money Volume Tools (SMVT) is a multi-dimensional volume-based analysis suite designed to visualize the interplay between price action, moving averages, and smart money behavior. By integrating dynamic moving averages, volume normalization, and multi-timeframe intelligence, SMVT helps traders identify when institutional (smart money) or retail participants are influencing price movements — all in a single, adaptive display. Unlike traditional oscillators or trend tools, SMVT dynamically adjusts its sensitivity and thresholds based on volume z-scores and normalized momentum, revealing true intent behind price shifts rather than reacting to them. 🔹 Key Features 4 Core Analytical Modes: Trail Mode – Identifies directional bias using dynamic volume-weighted trails based on adaptive ATR multipliers. Volume Mode – Displays normalized volume strength vs. price trend, highlighting volume-driven expansions. Smart Money Volume Mode – Detects institutional buying/selling spikes from lower timeframes using volume z-score outliers. Retail Money Volume Mode – Contrasts retail-driven impulses to visualize crowd behavior and exhaustion points. Dynamic Volume Normalization: Converts volume impulses into a 0–100 range using a sigmoid function for smoother interpretation. Multi-Timeframe Intelligence: Automatically reads lower timeframe volume data to distinguish smart vs. retail activity. Adaptive Color Systems: Multiple palette modes ( Classic , Mystic , Accented , Royal ) or full custom color control. Signal Table Overlay: Built-in real-time module summary showing status for Trail , Volume , Smart Money , and Retail Money — right on your chart. 🔹 How It Works Volume Strength Calculation: Calculates relative volume strength using a moving average baseline, then normalizes the result via a sigmoid function — mapping activity into a clean 0–100 range. Smart Money Detection: Scans lower timeframe data for extreme volume z-scores ( z > 2 ) to pinpoint institutional accumulation or distribution zones. Trail Logic: Uses adaptive upper and lower trails based on ATR and volume intensity to track volatility-adjusted trend direction. Color Logic: Trail, candle, and fill colors change dynamically according to the active signal type and selected palette — making directional bias instantly visible. 🔹 Practical Use Swing Confirmation (Trail Mode): Confirms sustained bullish or bearish momentum supported by volume, ideal for trailing positions and managing exits. Volume Expansion (Volume Mode): Highlights key moments when institutional liquidity pushes price before visible breakout confirmation. Smart vs. Retail Divergence: Identify conflicts between retail activity and smart money to detect exhaustion or reversal points early. Table Overlay Utility: Instantly see all active signals across modules in one compact, on-chart interface. 🔹 Customization Custom color palettes or manual bullish/bearish color selection. Adjustable EMA lengths and Volume SMA period . Selectable lower timeframe source for Smart Money analysis. Flexible table position & size controls — choose between Top, Middle, Bottom and Tiny to Huge. Switch freely between Trail , Volume , Smart Money , and Retail Money modes. Credits Thank you to @AlgoAlpha for the smart money and retail activity source code. ⚠️Disclaimer This indicator is a tool for technical analysis and does not provide guaranteed results. It should be used in conjunction with other analysis methods and proper risk management practices. The creators of this indicator are not responsible for any financial decisions made based on its signals.
Pine Script®指標
由LyroRS提供
4
Trade Journal ProTrade Journal Pro A powerful, visual trading journal that enforces discipline with real-time feedback, reflective prompts, and strict risk limits — all in one clean overlay box. Jesus is King — trade with wisdom, not emotion. FEATURES • AUTO-CALCULATED DAILY TRADES → `Trades Today = Wins + Losses + Breakevens` (no manual input needed) • 4 ENFORCED RISK LIMITS 1. Max Trades Per Day 2. Max Risk Rule Violations 3. Max Consecutive Losses (tilt protection) 4. Max Total Losses Allowed (lifetime/session cap) • SMART VISUAL FEEDBACK • GREEN BOX = You hit a limit exactly → “WELL DONE!” • RED BOX = Breached any limit → “STOP & REFLECT” + ALERT • Dark = Normal (under all limits) • REFLECTIVE PROMPTS (Customizable) 1. Why this setup? 2. What was my emotional state? 3. Did I follow my plan? • LIVE ADVICE ENGINE → Win: “Great execution! Log what worked.” → Loss: “Loss = tuition. What did you learn?” → Breakeven: “Review entry/exit precision.” • DAILY REMINDER → Always visible: “Trade the plan, not the emotion.” • FULLY CUSTOMIZABLE • Font size (Tiny → Huge) • Box position (bars to the right) • Toggle: Metrics / Prompts / Advice • Custom colors, messages, limits • ALERTS • Breach any limit → Immediate alert • Hit limit exactly → Discipline win notification HOW TO USE 1. After each closed trade: → Update Wins, Losses, or Breakevens → Update Consecutive Losses (reset to 0 on win/BE) → Increment Risk Violations if you broke a rule 2. Answer the 3 prompts in your journal 3. Let the box guide your behavior: • GREEN = Celebrate discipline • RED = STOP TRADING. Reflect. Reset. Perfect for day traders, swing traders, or anyone building a professional edge through journaling and risk control. No strategy entries. No repainting. Pure accountability. “The market is a mirror. This journal is the polish.” Developed with integrity. Built to protect your capital — and your peace.
Pine Script®指標
由CreativeAdvance提供
Sunmool's NY Lunch Model BacktestingICT NY Lunch Model Backtesting (12:00–13:00 NY) 🗽🍔 This research indicator tests an ICT narrative using the New York lunch window (12:00–13:00 America/New_York). It records that hour’s high/low and measures, during the post-lunch session (default 13:00–16:00), how often: ⬆️ If the afternoon trends up, the Lunch Low gets swept first. ⬇️ If the afternoon trends down, the Lunch High gets swept first. It reports these as conditional probabilities, not trade signals. 📈 👀 What it shows 🟦 Lunch Range box (toggle): high/low from 12:00–13:00 NY 🔻🔺 Sweep signals (bar-anchored) Low sweep: triangle below bar + optional “L” High sweep: triangle above bar + optional “H” 🧱 Optional small box wrapping the swept candle 📊 Stats table (top-right) P(L-swept | Up) — % of Up-days where Lunch Low was swept P(H-swept | Down) — % of Down-days where Lunch High was swept 🔁 Contradictions + sample sizes (Up-days / Down-days) 🎯 Direction logic (Up/Down) Anchor: 13:00 open (pmOpen) ⏰ Threshold: ATR × multiple or % from 13:00 Close ≥ pmOpen + threshold → Up-day Close ≤ pmOpen − threshold → Down-day Tiny moves under the threshold are ignored to reduce noise 🧹 ⚙️ Inputs 🌐 Timezone: America/New_York (DST handled) 🍽️ Lunch window: 1200–1300 🕓 Post-lunch window: default 1300–1600 (try 17:00/20:00 for sensitivity) 📐 Trend threshold: ATR / Percent (with length/multiple or % level) 📅 Weekdays-only toggle (FX/Equities style) 👁️ Display toggles: Lunch box / sweep arrows / sweep text / sweep candle box / stats table 🔔 TF hint when chart TF > 15m 🧭 How to use Use 5–15m charts for accurate lunch range capture. Scroll ~1 year for meaningful samples. Run sensitivity checks: vary ATR/% thresholds and the post-lunch end time. For crypto, compare with vs without weekends. 🚀 🧠 Reading the results High P(L-swept | Up) with a solid Up-day count ⇒ on up afternoons, lunch low is often swept. High P(H-swept | Down) ⇒ on down afternoons, lunch high is often swept. Lower Contradictions = cleaner tendency. Remember: this is a probabilistic tendency, not a rule. 🎲 📝 Notes & limits All markers (arrows, text, sweep boxes) are bar-anchored; the lunch range box is a research overlay you can toggle. Real-time vs historical bar building can differ—interpret on bar close. 🔒
Pine Script®指標
由sunmool_提供
Gold THB per Baht (XAU -> Thai baht gold)What it does This indicator converts international gold prices (XAU) into Thai retail “baht gold” price (THB per 1 baht gold weight) in real time. It multiplies the XAU price (per troy ounce) by USD/THB and converts ounces to Thai baht-weight using the exact gram ratios. Formula THB per baht gold = XAU (USD/oz) × USDTHB × (15.244 / 31.1035) × (1 + Adjustment%) + FlatFeeTHB 1 troy ounce = 31.1035 g 1 Thai baht gold = 15.244 g Conversion factor ≈ 0.490103
Pine Script®指標
由golfcu提供
AutoPivot Levels with Alerts [ChartWhizzperer] – Dynamic EditionAuto-Pivot Levels 4 methods with alerts – Dynamic Edition Now with - Live Mode - 4 Pivot Methods - 7 Session Types (5m, 15m, 30m, Hourly, Daily, Weekly, Monthly) - PineConnector-Ready Alerts! Free, Open Source, Pine Script v6-compliant. NEW: Live Mode (Ultra-Dynamic, Repainting) – Switchable in UI! Instantly switch between Classic (session-based, repaint-free) and Live (rolling window, real-time, repainting) using the simple checkbox in the settings! Live Mode recalculates all pivots on every tick/bar, using the current high/low/close for the chosen session (5m, 15m, 30m, hourly, daily, weekly, monthly). Perfect for: - Scalping and high-frequency trading - Real-time bot/automation setups (PineConnector-ready) - Fast-moving or breakout markets Classic Mode: For traditional, stable levels based on confirmed session data – ideal for backtesting and trading history. Four Calculation Methods (Choose What Fits YOU) 1. Classic Standard pivot calculation. Based on previous session’s High, Low, Close. Simple, proven, and suitable for any asset. 2. Fibonacci Projects levels using Fibonacci ratios of the prior session’s range. Great for traders who want to align pivots with fib retracements and extensions. 3. Camarilla Uses unique multipliers for support/resistance, focusing on mean reversion and volatility. Popular among futures and forex day traders. 4. Woodie Puts extra weight on previous Close for more responsive pivots. Often used in trending or choppy conditions. Switch methods anytime in the UI – the script recalculates instantly and keeps your chart clean! Level-Specific Alerts – PineConnector Ready! Dedicated alert for EVERY level and direction (Up/Down): Pivot (P), R1, R2, R3, S1, S2, S3 No configuration hassle: All alerts are pre-defined in the TradingView Alert Panel and work across all session types (5m → monthly). Machine-readable message format: PIVOT=R1 DIR=UP SYMBOL={{ticker}} PRICE={{close}} Direct plug-and-play with PineConnector, webhooks, Discord, Telegram, bots, and other automation tools. Never miss a breakout, reversal, or key support/resistance touch! Powerful Customization & Performance - Session selection: 5m, 15m, 30m, Hourly, Daily, Weekly, Monthly (choose what suits your trading style). - Show/hide any level (Pivot, R1–R3, S1–S3) for minimal chart clutter. - Color selection for each level to match your theme or highlight key pivots. - Auto-cleanup: Old lines and labels are cleared on every recalculation or session change for maximum performance and visual clarity. - Zero runtime errors: Strict Pine Script v6 practices for stability. How To Use – Quick Start 1) Add the indicator to your TradingView chart. 2) Pick your calculation method (Classic, Fibonacci, Camarilla, Woodie). 3) Set session type (5m, 15m, 30m, Hourly, Daily, Weekly, Monthly). 4) Switch between Classic and Live Mode with a single click in settings. 5) Customize your levels (on/off, colors). 6) Open the Alert Panel, select any pre-configured alert (e.g. "R2 Cross Down"), and go live! 7) Connect with PineConnector or any webhook system instantly using the pre-formatted alert messages. Who Is It For? - Active scalpers & bot traders: Live Mode + PineConnector-ready alerts = instant, automated reactions. - Swing and position traders: Use Classic Mode for stable, repaint-free levels. - Strategy developers: Seamless integration into automated and manual trading workflows. License & Community Open Source, Non-Commercial: Free for personal & educational use under CC BY-NC-SA 4.0. Feedback, bug reports & ideas: Drop a comment, or contact me for feature requests. Trade smart. Trade dynamic. Unlock the true power of pivots – with ChartWhizzperer!
Pine Script®指標
由ChartWhizzperer提供
Cora Combined Suite v1 [JopAlgo]Cora Combined Suite v1 (CCSV1) This is an 2 in 1 indicator (Overlay & Oscillator) the Cora Combined Suite v1 . CCSV1 combines a price-pane Overlay for structure/trend with a compact Oscillator for timing/pressure. It’s designed to be clear, beginner-friendly, and largely automatic: you pick a profile (Scalp / Intraday / Swing), choose whether to run as Overlay or Oscillator, and CCSV1 tunes itself in the background. What’s inside — at a glance 1) Overlay (price pane) CoRa Wave: a smooth trend line based on a compound-ratio WMA (CRWMA). Green when the slope rises (bull bias), Red when it falls (bear bias). Asymmetric ATR Cloud around the CoRa Wave Width expands more up when buyer pressure dominates and more down when seller pressure dominates. Fill is intentionally light, so candlesticks remain readable. Chop Guard (Range-Lock Gate) When the cloud stays very narrow versus ATR (classic “dead water”), pullback alerts are muted to avoid noise. Visuals don’t change—only the alerting logic goes quiet. Typical Overlay reads Trend: Follow the CoRa color; green favors long setups, red favors shorts. Value: Pullbacks into/through the cloud in trend direction are higher-quality than chasing breaks far outside it. Dominance: A visibly asymmetric cloud hints which side is funding the move (buyers vs sellers). 2) Oscillator (subpane or inline preview) Stretch-Z (columns): how far price is from the CoRa mean (mean-reversion context), clipped to ±clip. Near 0 = equilibrium; > +2 / < −2 = stretched/extended. Slope-Z (line): z-score of CoRa’s slope (momentum of the trend line). Crossing 0 upward = potential bullish impulse; downward = potential bearish impulse. VPO (stepline): a normalized Volume-Pressure read (positive = buyers funding, negative = sellers). Rendered as a clean stepline to emphasize state changes. Event Bands ±2 (subpane): thin reference lines to spot extension/exhaustion zones fast. Floor/Ceiling lines (optional): quiet boundaries so the panel doesn’t feel “bottomless.” Inline vs Subpane Inline (overlay): the oscillator auto-anchors and scales beneath price, so it never crushes the price scale. Subpane (raw): move to a new pane for the classic ±clip view (with ±2 bands). Recommended for systematic use. Why traders like it Two in one: Structure on the chart, timing in the panel—built to complement each other. Retail-first automation: Choose Scalp / Intraday / Swing and let CCSV1 auto-tune lengths, clips, and pressure windows. Robust statistics: On fast, spiky markets/timeframes, it prefers outlier-resistant math automatically for steadier signals. Optional HTF gate: You can require higher-timeframe agreement for oscillator alerts without changing visuals. Quick start (simple playbook) Run As Overlay for structure: assess trend direction, where value is (the cloud), and whether chop guard is active. Oscillator for timing: move to a subpane to see Stretch-Z, Slope-Z, VPO, and ±2 bands clearly. Profile Scalp (1–5m), Intraday (15–60m), or Swing (4H–1D). CCSV1 adjusts length/clip/pressure windows accordingly. Overlay entries Trade with CoRa color. Prefer pullbacks into/through the cloud (trend direction). If chop guard is active, wait; let the market “breathe” before engaging. Oscillator timing Look for Funded Flips: Slope-Z crossing 0 in the direction of VPO (i.e., momentum + funded pressure). Use ±2 bands to manage risk: stretched conditions can stall or revert—better to scale or wait for a clean reset. Optional HTF gate Enable to green-light only those oscillator alerts that align with your chosen higher timeframe. What each signal means (plain language) CoRa turns green/red (Overlay): trend bias shift on your chart. Cloud width tilts asymmetrically: one side (buyers/sellers) is dominating; extensions on that side are more likely. Stretch-Z near 0: fair value around CoRa; pullback timing zone. Stretch-Z > +2 / < −2: extended; watch for slowing momentum or scale decisions. Slope-Z cross up/down: new impulse starting; combine with VPO sign to avoid unfunded crosses. VPO positive/negative: net buying/selling pressure funding the move. Alerts included Overlay Pullback Long OK Pullback Short OK Oscillator Funded Flip Up / Funded Flip Down (Slope-Z crosses 0 with VPO agreement) Pullback Long Ready / Pullback Short Ready (near equilibrium with aligned momentum and pressure) Exhaustion Risk (Long/Short) (Stretch-Z beyond ±2 with weakening momentum or pressure) Tip: Keep chart alerts concise and use strategy rules (TP/SL/filters) in your trade plan. Best practices One glance workflow Read Overlay for direction + value. Use Oscillator for trigger + confirmation. Pairing Combine with S/R or your preferred execution framework (e.g., your JopAlgo setups). The suite is neutral: it won’t force trades; it highlights context and quality. Markets Works on crypto, indices, FX, and commodities. Where real volume is available, VPO is strongest; on synthetic volume, treat VPO as a soft filter. Timeframes Use the Profile preset closest to your style; feel free to fine-tune later. For multi-TF trading, enable the HTF gate on the oscillator alerts only. Inputs you’ll actually use (the rest can stay on Auto) Run As: Overlay or Oscillator. Profile: Scalp / Intraday / Swing. Oscillator Render: “Subpane (raw)” for a classic panel; “Inline (overlay)” only for a quick preview. HTF gate (optional): require higher-timeframe Slope-Z agreement for oscillator alerts. Everything else ships with sensible defaults and auto-logic. Limitations & tips Not a strategy: CCSV1 is a decision support tool; you still need your entry/exit rules and risk management. Non-repainting design: Signals finalize on bar close; intrabar graphics can adjust during the bar (Pine standard). Very flat sessions: If price and volume are extremely quiet, expect fewer alerts; that restraint is intentional. Who is this for? Beginners who want one clean overlay for structure and one simple oscillator for timing—without wrestling settings. Intermediates seeking a coherent trend/pressure framework with HTF confirmation. Advanced users who appreciate robust stats and clean engineering behind the visuals. Disclaimer: Educational purposes only. Not financial advice. Trading involves risk. Use at your own discretion.
Pine Script®指標
由JopAlgo提供
No-Trade Zones UTC+7This indicator helps you visualize and backtest your preferred trading hours. For example, if you have a 9-to-5 job, you obviously can’t trade during that time — and when backtesting, you should avoid those hours too. It also marks weekends if you prefer not to trade on those days. By highlighting no-trade periods directly on the chart, you can easily see when you shouldn’t be taking trades, without constantly checking the time or date by hovering over the chart. It makes backtesting smoother and more realistic for your personal schedule.
Pine Script®指標
由AightBett提供
Lynie's V9 SELL🟢🔴 Lynie’s V8 — BUY & SELL (Mirrored, Interlocking System) Lynie’s V8 is a paired long/short engine built as two mirrored scripts—Lynie’s V8 BUY and Lynie’s V8 SELL—that read price the same way, flip conditions symmetrically, and manage trades with the exact logic on opposite sides. Use either one standalone or run both together for full two-sided automation of entries, re-entries, caution states, and adaptive SL/TP. ✳️ What “mirrored” means here Supertrend Tri-Stack (10/11/12): BUY: ST10 primary pierce; ST12 fallback; “PAG Buy” when price pierces any ST while above the other two. SELL: Exact inverse—ST10 primary pierce down; ST12 fallback; “PAG Sell” when price pierces any ST while below the other two. Re-Enter Clusters: BUY: Ratcheted up (Heikin-Ashi green holds/tightens). SELL: Ratcheted down (Heikin-Ashi red holds/tightens). Both sides use the same cluster age/decay math, care penalties, session awareness, and fast-candle tightening. Care Flags (context risk): Ichimoku, MACD, RSI combine into single and paired flags that tighten or widen offsets on both sides with the same scoring. VWAP–EMA50 (5m) cluster gate: Identical distance checks for BUY/SELL. When the mean cluster is present, offsets and labels adapt (tighter/“riskier scalp” messaging). Golden Pocket A/B/C (prev-day): Same fib boxes & labeling (gold tone) on both sides to call out TP-friendly zones. SL/TP Envelope: Shared dynamic engine: per-bar decay, fast-candle expansion, and care-based compress/relax—all mirrored for up/down. Caution Labels: BUY side prints CAUTION SELL if HA flips red inside an active long cluster. SELL side prints CAUTION BUY if HA flips green inside an active short cluster. Same latching & auto-release behavior. 🧠 Core workflow (both sides) Primary trigger via ST10 pierce (structure shift) with an ST12 fallback when ST10 didn’t qualify. PAG Mode when price is already on the right side of the other two STs—strongest conviction. Cluster phase begins after a signal: ratcheted re-entry level, session-aware offsets, dynamic tightening on fast bars. Care system shapes every re-entry & SL/TP label (Ichi/MACD/RSI combos + VWAP/EMA gate + QQE). Protective layer: SL-wick and SL-body logic, caution flips, and “hold 1 bar” cluster carry after SL to avoid whipsaw spam. 🔎 Labels & messages (shared vocabulary) Lynie’s / Lynie’s+ / Lynie’s++ — strength tiers (ST12 involvement & clean context). Re-Enter / Excellent Re-Enter — cluster pullback quality; ratchet shows the “must-hold” zone. SL&TP (n) — live offset multiplier the engine is using right now. CAUTION BUY / CAUTION SELL — HA flip against the active side inside the cluster. Restart Next Candle — visual cue to re-arm after a confirmed signal bar. ⚡ Why run both together Continuity: When a long cycle ends (SL or caution degradation), the SELL engine is already tracking the inverse without re-tuning. Symmetry: Same math, same signals, opposite direction—no hidden biases. Coverage: Trend hand-offs are cleaner; you don’t miss early shorts after a long fade (and vice versa). 🔧 Recommended usage Intraday futures (ES/NQ) or any liquid market. Keep the VWAP–EMA cluster ON; it filters FOMO chases. Honor Caution flips inside cluster—scale down or wait for the next clean re-enter. Treat Golden Zones as TP magnets, not guaranteed reversals. 📌 Notes Both scripts are Pine v6 and independent. Load BUY and SELL together for the full experience. All offsets (re-enter & SL/TP) are visible in labels—so you always know why a zone is where it is. Alerts are provided for signals, re-enter hits, caution, and SL events on both sides. Summary: Lynie’s V8 BUY & SELL are vice-versa twins—one framework, two directions—delivering consistent entries, adaptive re-entries, and contextual risk management whether the market is pressing up or breaking down.
Pine Script®指標
由CoderPAG提供
Scissors&Knifes V3.1✂️ The Scissors (PAG Chop V4 Engine) 🧠 Core idea Scissors measure market compression and breakout readiness. They use a modified Choppiness Index that looks at the relationship between: True Range volatility (ATR × period length) The total high–low range over the same window. The smaller the ratio (sum of TR vs range), the more directional and impulsive the market is. The higher the ratio, the more “sideways” the market trades. This version smooths the result over PAG_SMOOTHLEN bars and applies several color bands that correspond to volatility states. 🎨 Color code meaning Range State Color Interpretation ≤ 30 Strong Red #8B0000 Momentum exhaustion on downside, sellers dominating — about to reverse or already strong down-trend. 30 – 38 Brick Red #A52A2A Fading downside pressure; often the “bleeding edge” of a bearish climax. 38 – 55 Transparent black (α≈100) Neutral chop zone — indecision, range-building. 55 – 61.8 Yellow (optional) #DAA520 Early compression pocket where volatility starts contracting; the calm before a trend. 61.8 – 70 Bright Green #556B2F Energy release phase: volatility breaking out upward. ≥ 70 Strong Green #355E3B Sustained bullish drive, often continuation leg of a trend. 🪶 Secret nuance: The transition bands (38–45 and 45–55) are treated as fully transparent to mark “dead zones.” When PAG Chop sits here, all label activity pauses — the system resets its cluster memory so the next colored print begins a new “cluster”, letting you clearly see where fresh directional momentum starts. 🧩 Cluster logic Every time a colored (non-transparent) reading appears, it belongs to a “color cluster.” Grey labels (= count 1) mark the genesis of a new cluster, and following counts 2, 3, 4 … represent the internal continuity of that trend state. You can optionally hide the first N grey or count 2 labels to reduce clutter on the initial stabilization bars. ✂️ Label meaning Each label shows: Emoji ✂️ Current count (e.g. ✂️ = 3 means 3 timeframes are simultaneously firing) Optional list of the timeframes that contribute. So a high count (e.g. 8–10) means many lower TFs are synchronizing volatility breakout — a multiframe alignment, often just before an acceleration burst. 🔪 The Knife (Mr Blonde V4 Engine) 🧠 Core idea Mr Blonde converts the slope of a long EMA into an angle-of-attack metric — literally the “tilt” of market momentum. It computes the EMA gradient relative to price span and rescales it into degrees (-5 ° to +5 °). The steeper the angle, the stronger the directional push. 🎨 Color code meaning Angle range Color Interpretation ≥ +5 ° Transparent (Black 1) Fully over-extended up move — wait for reset. +3.57 – +5 ° Dark Red Strong upward slope, momentum apex. +2.14 – +3.57 ° Orange Medium upward slope, trend acceleration zone. +0.71 – +2.14 ° Light Orange Mild upward bias, pre-momentum phase. 0 to -0.71 ° Yellow Neutral transition. -0.71 – -2.14 ° Olive Green Soft bearish slope. -2.14 – -3.57 ° Olive Drab Building bearish momentum. -3.57 – -5 ° Hunter Green Strong downward angle, aggressive push. ≤ -5 ° Transparent (Black 2) Oversold/over-tilted — likely exhaustion. 🪶 Secret nuance: Mr Blonde uses a “span normalization” factor that divides EMA slope by the dynamic range of highs and lows. This lets it compare angles fairly across assets with different volatility profiles (e.g. BTC vs ES) — it’s one of the rare EMA-angle implementations that self-scales properly. 🗡 Label meaning Emoji 🔪 Count = how many TFs share the same momentum angle bias. When many TFs show the same slope polarity (e.g. knife = 8), you’re in a deep momentum cascade — a “knife trend.” 💫 Yellow knife The yellow state marks neutrality or slope flattening. If you enable yellow visibility (mb_show_yellow), you can see where momentum cools off — often the earliest reversal hint. ⚙️ Shared mechanics between ✂️ and 🔪 Multi-timeframe sweep The script cycles through 1 m → 10 m by default, running both engines once per TF. Each returning true adds +1 to the count. So: sc_hits = count of timeframes where PAG fires + 1 knife_hits = count of timeframes where MB fires + 1 That “+1 shift” means there’s always at least 1, letting count = 1 represent the local TF itself. Cluster limiter If Limit max labels per cluster is on, you cap how many total symbols (both ✂️ & 🔪, including trails) can appear within one color phase — avoiding chart spam during extended trends. Trails Each printed label seeds a short-lived “trail” sequence — faded copies extending N bars forward. Trails visualize the linger effect of the last signal, useful for visually connecting bursts in momentum. Grey or count = 1 labels can have shorter or longer trails depending on your overrides (*_trail_bars_grey). They’re purely visual and do not affect alerting. Alerts Alerts fire independently of whether you hide labels — unless you enable “respect filters”. This guarantees you never miss a structural signal even if you suppress visuals for clarity. 🌈 Interpreting Both Together Scenario Interpretation ✂️ = low (1–2) + 🔪 rising (red/orange) Market just leaving chop, early thrust stage. ✂️ = high (≥ 5) + 🔪 green Fully aligned breakout continuation — trend in progress. ✂️ = yellow cluster + 🔪 yellow Volatility squeeze, energy buildup — next expansion near. ✂️ = green cluster → 🔪 turns red Cross-state conflict; likely transition or correction. ✂️ = grey + 🔪 grey Reset condition — both engines cooling; stand aside. 💡 Hidden edge: Scissors signal potential, Knife measures kinetic force. The perfect storm is when ✂️ goes from yellow→green one bar before 🔪 shifts from orange→green — it catches the birth of directional flow while volatility is still tight. 🧭 Reading the labels intuitively Grey ✂️/🔪 = 1 → embryonic state, may fizzle or bloom. ✂️/🔪 = 2 or 3 → expansion taking hold. ✂️/🔪 ≥ 4 (mid black) → strong synchronized drive across TFs. Transparent gap → cluster reset; prepare for new phase. Trail lines → echo of previous cluster strength. Final secret tip 🗝 Because both engines are mathematically uncorrelated (volatility vs EMA angle), when they agree in color polarity on multiple TFs, you have one of the cleanest probabilistic trend windows possible. If you ever see ✂️ = 6 + 🔪 = 6 both pointing the same way — that’s a “knife-through-the-scissors” moment: volatility expansion and directional slope synchronized — those are the bars where institutional algorithms tend to add size.
Pine Script®指標
由CoderPAG提供
Zarattini Intra-day Threshold Bands (ZITB)This indicator implements the intraday threshold band methodology described in the research paper by Carlo Zarattini et al. Overview: Plots intraday threshold bands based on daily open/close levels. Supports visualization of BaseUp/BaseDown levels and Threshold Upper/Lower bands. Optional shading between threshold bands for easier interpretation. Usage Notes / Limitations: Originally studied on SPY (US equities), this implementation is adapted for NSE intraday market timing, specifically the NIFTY50 index. Internally, 2-minute candles are used if the chart timeframe is less than 2 minutes. Values may be inaccurate if the chart timeframe is more than 1 day. Lookback days are auto-capped to avoid exceeding TradingView’s 5000-bar limit. The indicator automatically aligns intraday bars across multiple days to compute average deltas. For better returns, it is recommended to use this indicator in conjunction with VWAP and a volatility-based position sizing mechanism. Can be used as a reference for Open Range Breakout (ORB) strategies. Customizations: Toggle plotting of base levels and thresholds. Toggle shading between thresholds. Line colors and styles can be adjusted in the Style tab. Intended for educational and research purposes only. This indicator implements the approach described in the research paper by Zarattini et al. Note: This implementation is designed for the NSE NIFTY50 index. While Zarattini’s original study was conducted on SPY, this version adapts the methodology for the Indian market. Methodology Explanation This indicator is primarily designed for Open Range Breakout (ORB) strategies. Base Levels BaseUp = Maximum of today’s open and previous day’s close BaseDown = Minimum of today’s open and previous day’s close Delta Calculation For the past 14 trading days (lookbackDays), the delta for each intraday candle is calculated as the ab solute difference from the close of the first candle of that day. Average Delta For a given intraday time/candle today, deltaAvg is computed as the average of the deltas at the same time across the previous 14 days. Threshold Bands ThresholdUp = BaseUp + deltaAvg ThresholdDown = BaseDown − deltaAvg Signals Spot price moving above ThresholdUp → Long signal Spot price moving below ThresholdDown → Short signal Tip: For better returns, combine this indicator with VWAP and a volatility-based position sizing mechanism.
Pine Script®指標
由gokul4trading提供