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Weekly Covered Calls Strategy with IV & Delta LogicWhat Does the Indicator Do? this is interactive you must use it with your options chain to input data based on the contract you want to trade. Visualize three strike price levels for covered calls based on: Aggressive (closest to price, riskier). Moderate (mid-range, balanced). Low Delta (farthest, safer). Incorporate Implied Volatility (IV) from the options chain to make strike predictions more realistic and aligned with market sentiment. Adjust the risk tolerance by modifying Delta inputs and IV values. Risk is defined for example .30 delta means 30% chance of your shares being assigned. If you want to generate steady income with your shares you might want to lower the risk of them being assigned to .05 or 5% etc. How to Use the Indicator with the Options Chain Start with the Options Chain: Look for the following data points from your options chain: Implied Volatility (IV Mid): Average IV for a particular strike price. Delta: ~0.30 Delta: Closest strike (Aggressive). ~0.15–0.20 Delta: Mid-range strike (Moderate). ~0.05–0.10 Delta: Far OTM, safer (Low Delta). Strike Price: Identify strike prices for the desired Deltas. Open Interest: Check liquidity; higher OI ensures tighter spreads. Input IV into the Indicator: Enter the IV Mid value (e.g., 0.70 for 70%) from the options chain into the Implied Volatility field of the indicator. Adjust Delta Inputs Based on Risk Tolerance: Aggressive Delta: Increase if you want strikes closer to the current price (riskier, higher premium). Default: 0.2 (20% chance of shares being assigned). Moderate Delta: Balanced risk/reward. Default: 0.12 (12%) Low Delta: Decrease for safer, farther OTM strikes. Default: 0.05 (5%) Visualize the Chart: Once inputs are updated: Red Line: Aggressive Strike (closest, riskiest, higher premium). Blue Line: Moderate Strike (mid-range). Green Line: Low Delta Strike (farthest, safer). Step-by-Step Workflow Example Open the options chain and note: Implied Volatility (IV Mid): Example 71.5% → input as 0.715. Delta for desired strikes: Aggressive: 0.30 Delta → Closest strike ~ $455. Moderate: 0.15 Delta → Mid-range strike ~ $470. Low Delta: 0.05 Delta → Farther strike ~ $505. Open the indicator and adjust: IV Mid: Enter 0.715. Aggressive Delta: Leave at 0.12 (or adjust to bring strikes closer). Moderate Delta: Leave at 0.18. Low Delta: Adjust to 0.25 for safer, farther strikes. View the chart: Compare the indicator's strikes (red, blue, green) with actual options chain strikes. Use the visualization to: Validate the risk/reward for each strike. Align strikes with technical trends, support/resistance. Adjusting Inputs Based on Risk Tolerance Higher Risk: Increase Aggressive Delta (e.g., 0.15) for closer strikes. Use higher IV values for volatile stocks. Moderate Risk: Use default values (0.12–0.18 Delta). Balance premiums and probability. Lower Risk: Increase Low Delta (e.g., 0.30) for farther, safer strikes. Focus on higher IV stocks with good open interest. Key Benefits Simplifies Strike Selection: Visualizes the three risk levels directly on the chart. Aligns with Market Sentiment: Incorporates IV for realistic forecasts. Customizable for Risk: Adjust inputs to match personal risk tolerance. By combining the options chain (IV, Delta, and liquidity) with the technical chart, you get a powerful, visually intuitive tool for covered call strategies.
Индикатор Pine Script®
от renderingnature1
1
Weekly COTAdjusted COT Index Improves upon: "COT Index Commercials vs large and small Speculators" by SystematicFutures How: CoT Indexes are adjusted by Open Interest to normalise data over time, and threshold background colours are in-line with Larry Williams recommendations from his book. Note: This indicator is **only** accurate on the Daily time-frame due to the mid-week release date for CoT data. This script calculates and plots the Adjusted Commitment of Traders (COT) Index for Commercial, Large Speculator, and Retail (Small Speculator) categories. The CoT Index is adjusted by Open Interest to normalise data through time, following the methodology of Larry Williams, providing insights into how these groups are positioned in the market with an arguably more historically accurate context. COT Categories ------------------- - Commercials (Producers/Hedgers): Large entities hedging against price changes in the underlying asset. - Large Speculators (Non-commercials): Professional traders and funds speculating on price movements. - Retail Traders (Nonreportable/Small Speculators): Small individual traders, typically less informed. Features ---------- - Open Interest Adjustment - The net positions for each category are normalized by Open Interest to account for varying contract sizes. - Customisable Look-back Period - You can adjust the number of weeks for the index calculation to control the historical range used for comparison. - Thresholds for Extremes - Upper and lower thresholds (configurable) are provided to mark overbought and oversold conditions. - Defaults - Overbought: <=20 - Oversold: >= 80 - Hide Current Week Option - Optionally hide the current week's data until market close for more accurate comparison. - Visual Aids - Plot the Commercials, Large Speculators, and Retail indexes, and optionally highlight extreme positioning. Inputs -------- - weeks - Number of weeks for historical range comparison. - upperExtreme and lowerExtreme - Thresholds to identify overbought/oversold conditions (default 80/20). - hideCurrentWeek - Option to hide current week's data until market close. - markExtremes - Highlight extremes where any index crosses the upper or lower thresholds. - Options to display or hide indexes for Commercials, Large Speculators, and Small Speculators. Outputs ---------- - The script plots the COT Index for each of the three categories and highlights periods of extreme positioning with customisable thresholds. Usage ------- - This tool is useful for traders who want to track the positioning of different market participants over time. - By identifying the extreme positions of Commercials, Large Speculators, and Retail traders, it can give insights into market sentiment and potential reversals. - Reversals of trend can be confirmed with RSI Divergence (daily), for example - Continuation can be confirmed with RSI overbought/oversold conditions (daily), and/or hidden RSI Hidden Divergence, for example
Индикатор Pine Script®
от madungandabas
Weekly BoxThe indicator shows a box based on the high and low of the previous week that extends into the current week. The box is used to monitor breakouts or break downs of the price with respect to the previous week levels. The box is colored: - green, if there is a breakout above the previous week high; or - red, if there is a break down below the previous week low; or - yellow, if the price stays inside of the box. during the current week. Labels for the box top and bottom prices can be enabled or disabled in the settings.
Индикатор Pine Script®
от danilogalisteu
1
[GYTS] VolatilityToolkit LibraryVolatilityToolkit Library 🌸 Part of GoemonYae Trading System (GYTS) 🌸 🌸 --------- INTRODUCTION --------- 🌸 💮 What Does This Library Contain? VolatilityToolkit provides a comprehensive suite of volatility estimation functions derived from academic research in financial econometrics. Rather than relying on simplistic measures, this library implements range-based estimators that extract maximum information from OHLC data — delivering estimates that are 5–14× more efficient than traditional close-to-close methods. The library spans the full volatility workflow: estimation, smoothing, and regime detection. 💮 Key Categories • Range-Based Estimators — Parkinson, Garman-Klass, Rogers-Satchell, Yang-Zhang (academically-grounded variance estimators) • Classical Measures — Close-to-Close, ATR, Chaikin Volatility (baseline and price-unit measures) • Smoothing & Post-Processing — Asymmetric EWMA for differential decay rates • Aggregation & Regime Detection — Multi-horizon blending, MTF aggregation, Volatility Burst Ratio 💮 Originality To the best of our knowledge, no other TradingView script combines range-based estimators (Parkinson, Garman-Klass, Rogers-Satchell, Yang-Zhang), classical measures, and regime detection tools in a single package. Unlike typical volatility implementations that offer only a single method, this library: • Implements four academically-grounded range-based estimators with proper mathematical foundations • Handles drift bias and overnight gaps, issues that plague simpler estimators in trending markets • Integrates with GYTS FiltersToolkit for advanced smoothing (10 filter types vs. typical SMA-only) • Provides regime detection tools (Burst Ratio, MTF aggregation) for systematic strategy integration • Standardises output units for seamless estimator comparison and swapping 🌸 --------- ADDED VALUE --------- 🌸 💮 Academic Rigour Each estimator implements peer-reviewed methodologies with proper mathematical foundations. The library handles aspects that are easily missed, e.g. drift independence, overnight gap adjustment, and optimal weighting factors. All functions include guards against edge cases (division by zero, negative variance floors, warmup handling). 💮 Statistical Efficiency Range-based estimators extract more information from the same data. Yang-Zhang achieves up to 14× the efficiency of close-to-close variance, meaning you can achieve the same estimation accuracy with far fewer bars — critical for adapting quickly to changing market conditions. 💮 Flexible Smoothing All estimators support configurable smoothing via the GYTS FiltersToolkit integration. Choose from 10 filter types to balance responsiveness against noise reduction: • Ultimate Smoother (2-Pole / 3-Pole) — Near-zero lag; the 3-pole variant is a GYTS design with tunable overshoot • Super Smoother (2-Pole / 3-Pole) — Excellent noise reduction with minimal lag • BiQuad — Second-order IIR filter with quality factor control • ADXvma — Adaptive smoothing based on directional volatility • MAMA — Cycle-adaptive moving average • A2RMA — Adaptive autonomous recursive moving average • SMA / EMA — Classical averages (SMA is default for most estimators) Using Infinite Impulse Response (IIR) filters (e.g. Super Smoother, Ultimate Smoother) instead of SMA avoids the "drop-off artefact" where volatility readings crash when old spikes exit the window. 💮 Plug-and-Play Integration Standardised output units (per-bar log-return volatility) make it trivial to swap estimators. The annualize() helper converts to yearly volatility with a single call. All functions work seamlessly with other GYTS components. 🌸 --------- RANGE-BASED ESTIMATORS --------- 🌸 These estimators utilise High, Low, Open, and Close prices to extract significantly more information about the underlying diffusion process than close-only methods. 💮 parkinson() The Extreme Value Method -- approximately 5× more efficient than close-to-close, requiring about 80% less data for equivalent accuracy. Uses only the High-Low range, making it simple and robust. • Assumption: Zero drift (random walk). May be biased in strongly trending markets. • Best for: Quick volatility reads when drift is minimal. • Parameters: smoothing_length (default 14), filter_type (default SMA), smoothing_factor (default 0.7) Source: Parkinson, M. (1980). The Extreme Value Method for Estimating the Variance of the Rate of Return. Journal of Business, 53 (1), 61–65. DOI 💮 garman_klass() Extends Parkinson by incorporating Open and Close prices, achieving approximately 7.4× efficiency over close-to-close. Implements the "practical" analytic estimator (σ̂²₅) which avoids cross-product terms whilst maintaining near-optimal efficiency. • Assumption: Zero drift, continuous trading (no gaps). • Best for: Markets with minimal overnight gaps and ranging conditions. • Parameters: smoothing_length (default 14), filter_type (default SMA), smoothing_factor (default 0.7) Source: Garman, M.B. & Klass, M.J. (1980). On the Estimation of Security Price Volatilities from Historical Data. Journal of Business, 53 (1), 67–78. DOI 💮 rogers_satchell() The drift-independent estimator correctly isolates variance even in strongly trending markets where Parkinson and Garman-Klass become significantly biased. Uses the formula: ln(H/C)·ln(H/O) + ln(L/C)·ln(L/O). • Key advantage: Unbiased regardless of trend direction or magnitude. • Best for: Trending markets, crypto (24/7 trading with minimal gaps), general-purpose use. • Parameters: smoothing_length (default 14), filter_type (default SMA), smoothing_factor (default 0.7) Source: Rogers, L.C.G. & Satchell, S.E. (1991). Estimating Variance from High, Low and Closing Prices. Annals of Applied Probability, 1 (4), 504–512. DOI 💮 yang_zhang() The minimum-variance composite estimator — both drift-independent AND gap-aware. Combines overnight returns, open-to-close returns, and the Rogers-Satchell component with optimal weighting to minimise estimator variance. Up to 14× more efficient than close-to-close. • Parameters: lookback (default 14, minimum 2), alpha (default 1.34, optimised for equities). • Best for: Equity markets with significant overnight gaps, highest-quality volatility estimation. • Note: Unlike other estimators, Yang-Zhang does not support custom filter types — it uses rolling sample variance internally. Source: Yang, D. & Zhang, Q. (2000). Drift-Independent Volatility Estimation Based on High, Low, Open, and Close Prices. Journal of Business, 73 (3), 477–491. DOI 🌸 --------- CLASSICAL MEASURES --------- 🌸 💮 close_to_close() Classical sample variance of logarithmic returns. Provided primarily as a baseline benchmark — it is approximately 5–8× less efficient than range-based estimators, requiring proportionally more data for the same accuracy. • Parameters: lookback (default 14), filter_type (default SMA), smoothing_factor (default 0.7) • Use case: Comparison baseline, situations requiring strict methodological consistency with academic literature. 💮 atr() Average True Range -- measures volatility in price units rather than log-returns. Directly interpretable for stop-loss placement (e.g., "2× ATR trailing stop") and handles gaps naturally via the True Range formula. • Output: Price units (not comparable across different price levels). • Parameters: smoothing_length (default 14), filter_type (default SMA), smoothing_factor (default 0.7) • Best for: Position sizing, trailing stops, any application requiring volatility in currency terms. Source: Wilder, J.W. (1978). New Concepts in Technical Trading Systems . Trend Research. 💮 chaikin_volatility() Rate of Change of the smoothed trading range. Unlike level-based measures, Chaikin Volatility shows whether volatility is expanding or contracting relative to recent history. • Output: Percentage change (oscillates around zero). • Parameters: length (default 10), roc_length (default 10), filter_type (default EMA), smoothing_factor (default 0.7) • Interpretation: High values suggest nervous, wide-ranging markets; low values indicate compression. • Best for: Detecting volatility regime shifts, breakout anticipation. 🌸 --------- SMOOTHING & POST-PROCESSING --------- 🌸 💮 asymmetric_ewma() Differential smoothing with separate alphas for rising versus falling volatility. Allows volatility to spike quickly (fast reaction to shocks) whilst decaying slowly (stability). Essential for trailing stops that should widen rapidly during turbulence but narrow gradually. • Parameters: alpha_up (default 0.1), alpha_down (default 0.02). • Note: Stateful function — call exactly once per bar. 💮 annualize() Converts per-bar volatility to annualised volatility using the square-root-of-time rule: σ_annual = σ_bar × √(periods_per_year). • Parameters: vol (series float), periods (default 252 for daily equity bars). • Common values: 365 (crypto), 52 (weekly), 12 (monthly). 🌸 --------- AGGREGATION & REGIME DETECTION --------- 🌸 💮 weighted_horizon_volatility() Blends volatility readings across short, medium, and long lookback horizons. Inspired by the Heterogeneous Autoregressive (HAR-RV) model's recognition that market participants operate on different time scales. • Default horizons: 1-bar (short), 5-bar (medium), 22-bar (long). • Default weights: 0.5, 0.3, 0.2. • Note: This is a weighted trailing average, not a forecasting regression. For true HAR-RV forecasting, it would be required to fit regression coefficients. Inspired by: Corsi, F. (2009). A Simple Approximate Long-Memory Model of Realized Volatility. Journal of Financial Econometrics . 💮 volatility_mtf() Multi-timeframe aggregation for intraday charts. Combines base volatility with higher-timeframe (Daily, Weekly, Monthly) readings, automatically scaling HTF volatilities down to the current timeframe's magnitude using the square-root-of-time rule. • Usage: Calculate HTF volatilities via request.security() externally, then pass to this function. • Behaviour: Returns base volatility unchanged on Daily+ timeframes (MTF aggregation not applicable). 💮 volatility_burst_ratio() Regime shift detector comparing short-term to long-term volatility. • Parameters: short_period (default 8), long_period (default 50), filter_type (default Super Smoother 2-Pole), smoothing_factor (default 0.7) • Interpretation: Ratio > 1.0 indicates expanding volatility; values > 1.5 often precede or accompany explosive breakouts. • Best for: Filtering entries (e.g., "only enter if volatility is expanding"), dynamic risk adjustment, breakout confirmation. 🌸 --------- PRACTICAL USAGE NOTES --------- 🌸 💮 Choosing an Estimator • Trending equities with gaps: yang_zhang() — handles both drift and overnight gaps optimally. • Crypto (24/7 trading): rogers_satchell() — drift-independent without the lag of Yang-Zhang's multi-period window. • Ranging markets: garman_klass() or parkinson() — simpler, no drift adjustment needed. • Price-based stops: atr() — output in price units, directly usable for stop distances. • Regime detection: Combine any estimator with volatility_burst_ratio(). 💮 Output Units All range-based estimators output per-bar volatility in log-return units (standard deviation). To convert to annualised percentage volatility (the convention in options and risk management), use: vol_annual = annualize(yang_zhang(14), 252) // For daily bars vol_percent = vol_annual * 100 // Express as percentage 💮 Smoothing Selection The library integrates with FiltersToolkit for flexible smoothing. General guidance: • SMA: Classical, statistically valid, but suffers from "drop-off" artefacts when spikes exit the window. • Super Smoother / Ultimate Smoother / BiQuad: Natural decay, reduced lag — preferred for trading applications. • MAMA / ADXvma / A2RMA: Adaptive smoothing, sometimes interesting for highly dynamic environments. 💮 Edge Cases and Limitations • Flat candles: Guards prevent log(0) errors, but single-tick bars produce near-zero variance readings. • Illiquid assets: Discretisation bias causes underestimation when ticks-per-bar is small. Use higher timeframes for more reliable estimates. • Yang-Zhang minimum: Requires lookback ≥ 2 (enforced internally). Cannot produce instantaneous readings. • Drift in Parkinson/GK: These estimators overestimate variance in trending conditions — switch to Rogers-Satchell or Yang-Zhang. Note: This library is actively maintained. Suggestions for additional estimators or improvements are welcome.
Библиотека Pine Script®
от GoemonYae
IV Rank & Percentile Suite V1.0What This Indicator Does The IV Rank & Percentile Suite provides the volatility context options traders need to time entries. It calculates two complementary metrics—IV Rank and IV Percentile—using historical volatility as a proxy, then displays clear visual zones to identify favorable conditions for premium selling strategies. Stop guessing if volatility is "high" or "low." This indicator tells you exactly where current volatility sits relative to recent history. The Two Metrics Explained IV Rank (0-100) Measures where current volatility sits within its 52-week high-low range. IV Rank = (Current HV - 52w Low) / (52w High - 52w Low) × 100 70 means current volatility is 70% of the way between the yearly low and high Sensitive to extreme spikes (a single high reading affects the range) IV Percentile (0-100) Measures what percentage of days in the lookback period had lower volatility than today. IV Percentile = (Days with lower HV / Total days) × 100 70 means volatility was lower than today on 70% of days in the past year More stable, less affected by outlier spikes Why Both? IV Rank reacts faster to volatility changes. IV Percentile is more stable and statistically robust. When both agree (e.g., both above 50), you have stronger confirmation. Divergence between them can signal transitional periods. Zone System The indicator divides readings into three zones: Zone ------- Default Range ---- Meaning ------------------ Premium Selling 🟢 High ≥ 50 Elevated volatility Favorable 🟡 Neutral 25-50 Normal volatility Selective 🔴 Low ≤ 25 Compressed volatility Avoid An additional Extreme threshold (default 75) highlights prime conditions when volatility is significantly elevated. Zone thresholds are fully customizable in settings. How to Use It For Premium Sellers (Iron Condors, Credit Spreads, Strangles) Wait for IV Rank to enter the green zone (≥50) Confirm IV Percentile agrees (also elevated) Enter premium selling positions when both metrics align Avoid initiating new positions when in the red zone For Premium Buyers (Long Options, Debit Spreads) Low IV Rank/Percentile means cheaper options Red zone can favor directional debit strategies Avoid buying premium when both metrics are in the green zone General Principle: Sell premium when volatility is high (it tends to revert to mean). Buy premium when volatility is low (if you have a directional thesis). Inputs Volatility Calculation HV Period — Lookback for historical volatility calculation (default: 20) Trading Days/Year — 252 for stocks, 365 for crypto Lookback Periods IV Rank Lookback — Period for high/low range (default: 252 = 1 year) IV Percentile Lookback — Period for percentile calculation (default: 252) Zone Thresholds High IV Zone — Readings above this are highlighted green (default: 50) Low IV Zone — Readings below this are highlighted red (default: 25) Extreme High — Threshold for "prime" conditions alert (default: 75) Display Options Toggle IV Rank, IV Percentile, and raw HV display Show/hide zone backgrounds Show/hide info panel Panel position selection Info Panel The panel displays: Field ------- Description IV Rank ------- Current reading with color coding IV Pctl ------- Current percentile with color coding HV 20d ------- Raw historical volatility percentage 52w Range ------- Lowest to highest HV in lookback period Zone ------- Current zone status Premium ------- Signal quality for premium selling Lookback ------- Days used for calculations R/P Spread ------- Difference between Rank and Percentile Alerts Six alerts are available: Zone Transitions IV Entered High Zone — Favorable for premium selling IV Reached Extreme Levels — Prime conditions IV Dropped to Low Zone — Caution for premium sellers Threshold Crosses IV Rank Crossed Above High Threshold IV Rank Crossed Below Low Threshold IV Percentile Above 75 IV Percentile Below 25 Set up alerts to get notified when conditions change without watching charts. Technical Notes Volatility Calculation Method This indicator uses close-to-close historical volatility as an IV proxy: Calculate log returns: ln(Close / Previous Close) Take standard deviation over HV Period Annualize: multiply by √(Trading Days) This method correlates well with implied volatility for most liquid instruments. On highly liquid options underlyings (SPY, QQQ, major stocks), HV and IV tend to move together, making this a reliable proxy for IV Rank analysis. Non-Repainting All calculations use confirmed bar data. Values are fixed once a bar closes. Lookback Requirement The indicator needs sufficient history to calculate accurately. For a 252-day lookback, ensure your chart has at least 300+ bars of data. Best Used On ETFs: SPY, QQQ, IWM, DIA Indices: SPX, NDX High-volume stocks: AAPL, TSLA, NVDA, AMD, META Timeframe: Daily (recommended), Weekly for longer-term view The indicator works on any instrument but is most meaningful on underlyings with active options markets. Important Notes ⚠️ This indicator uses historical volatility as a proxy for implied volatility. While HV and IV are correlated, they are not identical. For precise IV data, consult your options broker's platform. ⚠️ High IV Rank does not guarantee profitable premium selling. It indicates favorable conditions, not guaranteed outcomes. Position sizing and risk management remain essential. ⚠️ Past volatility patterns do not guarantee future behavior. Volatility regimes can shift, and historical ranges may not predict future ranges. Suggested Workflow Add to daily chart of your preferred underlying Set up alert for "IV Entered High Zone" When alerted, check both IV Rank and IV Percentile If both elevated, evaluate premium selling opportunities Use your broker's actual IV data for final entry decisions Questions? Leave a comment below.
Индикатор Pine Script®
от VolForge
Smart Money Flow Oscillator [MarkitTick]💡This script introduces a sophisticated method for analyzing market liquidity and institutional order flow. Unlike traditional volume indicators that treat all market activity equally, the Smart Money Flow Oscillator (SMFO) employs a Logic Flow Architecture (LFA) to filter out market noise and "churn," focusing exclusively on high-impact, high-efficiency price movements. By synthesizing price action, volume, and relative efficiency, this tool aims to visualize the accumulation and distribution activities that are often attributed to "smart money" participants. ✨ Originality and Utility Standard indicators like On-Balance Volume (OBV) or Money Flow Index (MFI) often suffer from noise because they aggregate volume based simply on the close price relative to the previous close, regardless of the quality of the move. This script differentiates itself by introducing an "Efficiency Multiplier" and a "Momentum Threshold." It only registers volume flow when a price move is considered statistically significant and structurally efficient. This creates a cleaner signal that highlights genuine supply and demand imbalances while ignoring indecisive trading ranges. It combines the trend-following nature of cumulative delta with the mean-reverting insights of an In/Out ratio, offering a dual-mode perspective on market dynamics. 🔬 Methodology The underlying calculation of the SMFO relies on several distinct quantitative layers: • Efficiency Analysis The script calculates a "Relative Efficiency" ratio for every candle. This compares the current price displacement (body size) per unit of volume against the historical average. If price moves significantly with relatively low volume, or proportional volume, it is deemed "efficient." If significant volume occurs with little price movement (churn/absorption), the efficiency score drops. This score is clamped between a user-defined minimum and maximum (Efficiency Cap) to prevent outliers from distorting the data. • Momentum Thresholding Before adding any data to the flow, the script checks if the current price change exceeds a volatility threshold derived from the previous candle's open-close range. This acts as a gatekeeper, ensuring that only "strong" moves contribute to the oscillator. • Variable Flow Calculation If a move passes the threshold, the script calculates the flow value by multiplying the Typical Price and Volume (Money Flow) by the calculated Efficiency Multiplier. Bullish Flow: Strong upward movement adds to the positive delta. Bearish Flow: Strong downward movement adds to the negative delta. Neutral: Bars that fail the momentum threshold contribute zero flow, effectively flattening the line during consolidation. • Calculation Modes Cumulative Delta Flow (CDF): Sums the flow values over a rolling period. This creates a trend-following oscillator similar to OBV but smoother and more responsive to real momentum. In/Out Ratio: Calculates the percentage of bullish inflow relative to the total absolute flow over the period. This oscillates between 0 and 100, useful for identifying overextended conditions. 📖 How to Use Traders can utilize this oscillator to identify trend strength and potential reversals through the following signals: • Signal Line Crossovers The indicator plots the main Flow line (colored gradient) and a Signal line (grey). Bullish (Green Cloud): When the Flow line crosses above the Signal line, it suggests rising buying pressure and efficient upward movement. Bearish (Red Cloud): When the Flow line crosses below the Signal line, it suggests dominating selling pressure. • Divergences The script automatically detects and plots divergences between price and the oscillator: Regular Divergence (Solid Lines): Suggests a potential trend reversal (e.g., Price makes a Lower Low while Oscillator makes a Higher Low). Hidden Divergence (Dashed Lines): Suggests a potential trend continuation (e.g., Price makes a Higher Low while Oscillator makes a Lower Low). "R" labels denote Regular, and "H" labels denote Hidden divergences. • Dashboard A dashboard table is displayed on the chart, providing real-time metrics including the current Efficiency Multiplier, Net Flow value, and the active mode status. • In/Out Ratio Levels When using the Ratio mode: Values above 50 indicate net buying pressure. Values below 50 indicate net selling pressure. Approaching 70 or 30 can indicate overbought or oversold conditions involving volume exhaustion. ⚙️ Inputs and Settings Calculation Mode: Choose between "Cumulative Delta Flow" (Trend focus) or "In/Out Ratio" (Oscillator focus). Auto-Adjust Period: If enabled, automatically sets the lookback period based on the chart timeframe (e.g., 21 for Daily, 52 for Weekly). Manual Period: The rolling lookback length for calculations if Auto-Adjust is disabled. Efficiency Length: The period used to calculate the average body and volume for the efficiency baseline. Eff. Min/Max Cap: Limits the impact of the efficiency multiplier to prevent extreme skewing during anomaly candles. Momentum Threshold: A factor determining how much price must move relative to the previous candle to be considered a "strong" move. Show Dashboard/Divergences: Toggles for visual elements. 🔍 Deconstruction of the Underlying Scientific and Academic Framework This indicator represents a hybrid synthesis of academic Market Microstructure theory and classical technical analysis. It utilizes an advanced algorithm to quantify "Price Impact," leveraging the following theoretical frameworks: • 1. The Amihud Illiquidity Ratio (2002) The core logic (calculating body / volume) functions as a dynamic implementation of Yakov Amihud’s Illiquidity Ratio. It measures price displacement per unit of volume. A high efficiency score indicates that "Smart Money" has moved the price significantly with minimal resistance, effectively highlighting liquidity gaps or institutional control. • 2. Kyle’s Lambda (1985) & Market Depth Drawing from Albert Kyle’s research on market microstructure, the indicator approximates Kyle's Lambda to measure the elasticity of price in response to order flow. By analyzing the "efficiency" of a move, it identifies asymmetries—specifically where price reacts disproportionately to low volume—signaling potential manipulation or specific Market Maker activity. • 3. Wyckoff’s Law of Effort vs. Result From a classical perspective, the algorithm codifies Richard Wyckoff’s "Effort vs. Result" logic. It acts as an oscillator that detects anomalies where "Effort" (Volume) diverges from the "Result" (Price Range), predicting potential reversals. • 4. Quantitative Advantage: Efficiency-Weighted Volume Unlike linear indicators such as OBV or Chaikin Money Flow—which treat all volume equally—this indicator (LFA) utilizes Efficiency-Weighted Volume. By applying the efficiency_mult factor, the algorithm filters out market noise and assigns higher weight to volume that drives structural price changes, adopting a modern quantitative approach to flow analysis. ● Disclaimer All provided scripts and indicators are strictly for educational exploration and must not be interpreted as financial advice or a recommendation to execute trades. I expressly disclaim all liability for any financial losses or damages that may result, directly or indirectly, from the reliance on or application of these tools. Market participation carries inherent risk where past performance never guarantees future returns, leaving all investment decisions and due diligence solely at your own discretion.
Индикатор Pine Script®
от MarkitTick
PHEN ATLAS - Market Map & Playbook [PhenLabs]📊 PHEN ATLAS 🎂 #50 🎂 Version: PineScript™ v6 📌 Description The PHEN ATLAS marks a historic milestone as the 50th official release from PhenLabs . This is a critical release you do not want to miss, serving as a comprehensive Market Map and Playbook designed to provide traders with a complete structural overview of price action. By synthesizing Market Structure, Liquidity concepts, and Regime detection, this script solves the problem of "analysis paralysis" by grading price action in real-time. It moves beyond simple indicators by offering a quantified "Playbook" that scores trade setups from 0 to 100, helping traders focus exclusively on high-probability opportunities while automating the complex math of position sizing and risk management. 🚀 Points of Innovation Proprietary Scoring Engine: Unlike standard indicators, this script assigns a quantitative score (0-100) to every potential trade based on confluence factors like HTF alignment and displacement. Dynamic Regime Detection: Features an integrated dashboard that classifies the market into specific phases (Expansion, Trend, Range) using ADX and EMA alignment logic. Smart Liquidity Pools: Automatically identifies and visualizes resting liquidity, tracking when these pools are "swept" to generate high-probability reversal signals. Integrated Trade Manager: Automates the calculation of Stop Loss, Take Profit (1:2 and 1:3), and Position Size based on account balance and risk percentage directly on the chart. Multi-Mode Interface: Offers three distinct visual modes—Clean, Pro, and Sniper—allowing users to toggle between deep analysis and clutter-free execution instantly. 🔧 Core Components Structure Module: Identifies Pivots, Break of Structure (BOS), and Change of Character (CHoCH) to define the current market bias. Liquidity Engine: Plots liquidity pools at key swing points and detects "Sweeps" where price grabs liquidity before reversing. Regime Filter: Uses a combination of EMAs (21/50) and ADX to determine if the market is trending or ranging, filtering out low-quality signals. Setup Validator: Monitors for three specific setup types (Sweep, Snapback, FVG Retest) and triggers alerts only when specific scoring thresholds are met. 🔥 Key Features Automated detection of High Timeframe (HTF) structure without repainting issues. Real-time grading of price displacement to validate institutional intent. Visual Risk/Reward boxes that automatically adjust to the volatility (ATR) of the asset. Fair Value Gap (FVG) detection with auto-mitigation tracking to clean up the chart. Customizable alerts for A+ setups, regime changes, and trade invalidations. Detailed dashboard displaying current Trend, Phase, Bias, and the score of the last setup. 🎨 Visualization Structure Points: Triangles for BOS and Diamonds for CHoCH events clearly mark trend shifts. Liquidity Lines: Dotted lines extending from pivots indicate un-swept liquidity pools; these dim automatically when swept. Setup Signals: Prominent "A+" labels appear on the chart when a setup meets the minimum score threshold defined by the user. Risk Boxes: Color-coded boxes (Green for Long, Red for Short) show Entry, Stop Loss, and Take Profit levels visually. Dashboard: A compact table in the bottom right corner provides a "Heads Up Display" of the market state. 📖 Usage Guidelines Display Mode: Select between 'Clean' for signals only, 'Pro' for full analysis including FVGs and Structure, or 'Sniper' for only high-score setups. HTF Timeframe: Sets the higher timeframe for structural analysis (Default: 240/4-Hour) to ensure you trade with the dominant trend. Min Score for A+ Setup: Threshold (0-100) required to trigger a signal (Default: 83); increase this to filter for only the absolute best trades. Risk %: Defines the percentage of your account you are willing to risk per trade (Default: 1.0%), used for the position size calculation. Account Balance: Input your current capital (Default: 10,000) to receive accurate unit sizing for every trade setup. ADX Threshold: Adjusts the sensitivity of the Regime detection filter (Default: 20) to determine when the market is trending versus ranging. ✅ Best Use Cases Confluence Trading: Use the scoring system to filter discretionary entries, taking trades only when the system scores them above 80. Prop Firm Trading: Utilize the built-in position size calculator to strictly adhere to risk management rules during evaluations. Trend Following: Wait for the Regime Dashboard to show "Bullish Expansion" before taking Long "Snapback" entries. Reversal Trading: Focus on "Sweep Reclaim" setups where price sweeps a liquidity pool and immediately closes back within range. ⚠️ Limitations This tool is a trend-following and reversal system; it may produce lower scores during undefined, low-volatility chop. The position size calculator is an estimation based on the entry candle; actual execution slippage is not accounted for. HTF data relies on closed candles to prevent repainting, which may result in a slight lag during rapid volatility spikes. 💡 What Makes This Unique Playbook Scoring: Most indicators just give a signal; PHEN ATLAS gives you a "Grade" (e.g., 85/100), allowing you to make informed decisions based on quality, not just frequency. Context Awareness: The script understands "Market Regime" and creates a context-aware bias, rather than blindly firing signals in a range. 🔬 How It Works Step 1 - Regime Definition: The script analyzes the 21/50 EMA relationship and ADX to define if the market is in a Trend or Range. Step 2 - Structure & Liquidity: It maps key pivots and liquidity pools, waiting for a "Sweep" event or a structural break. Step 3 - Setup Trigger: When a specific pattern occurs (like a Sweep Reclaim), the engine calculates a score based on displacement, volume, and key level alignment. Step 4 - Execution Logic: If the score > Threshold, the Trade Manager calculates the invalidation point (SL) and projects 2R/3R targets automatically. 🎉 Message From The Team 🎉 2025 was an amazing year. 12 months of building, shipping, and improving together with you. Hitting our 50th indicator release marks one full year of weekly drops , and we couldn't have done it without this community, and of course, BIG thank you to TradingView and it's team. Thank you for all the feedback, charts, and support. Let's make 2026 even bigger. We can't wait to show you what we've been working on. 🚀 💡 Note For best results, we recommend using the "Pro" mode during analysis to understand the narrative, and switching to "Sniper" or "Clean" during execution to maintain focus. Always ensure your "Account Balance" input matches your broker balance for accurate risk calculations.
Индикатор Pine Script®
от PhenLabs
1
US Election Cycle Strategy [Druckenmiller]US Election Cycle Strategy This indicator allows you to visually backtest and monitor the "US Presidential Election Cycle" theory, famously advocated by legendary investors like Stanley Druckenmiller. The core premise of this strategy is that the stock market tends to demonstrate strong performance in the two years leading up to a US Presidential Election, largely driven by fiscal stimulus, increased government spending, and economic maneuvering aimed at securing re-election. How it works: The script algorithmically calculates the exact date of US Presidential Elections (defined as the Tuesday next after the first Monday in November) for every cycle from 1900 to 2040. It creates a theoretical "Buy" signal exactly two years prior to the election and a "Sell" signal on Election Day itself. Key Features of this Version: Dynamic Date Calculation: Unlike scripts with hard-coded dates, this version uses a mathematical algorithm to determine the precise election date for any given year, ensuring historical accuracy and future-proofing. Maximized History: The script automatically utilizes all available historical data provided by your chart. It does not arbitrarily cut off data (e.g., at 1970) unless you specifically choose a different start year in the settings. Performance Statistics: An integrated dashboard displays key metrics based on the available history, including Average Return, Median Return, and the overall Win Rate of the strategy. Visual Feedback: The "Entry" point is marked with a dashed line, which automatically colors itself Green (Profit) or Red (Loss) once the cycle is completed, giving you an immediate visual heatmap of historical performance. Settings: You can customize the "Start Calculation From Year" to filter the statistics for specific eras (e.g., set it to 2000 to see only modern market behavior). The visual appearance of lines and the statistics table are fully customizable. Note: This "strategy" is best applied to major US Indices (such as the S&P 500 or Dow Jones Industrial Average) on a Daily or Weekly timeframe.
Индикатор Pine Script®
от robinzawa
DAYOFWEEK performance1 -Objective "What is the ''best'' day to trade .. Monday, Tuesday...." This script aims to determine if there are different results depending on the day of the week. The way it works is by dividing data by day of the week (Monday, Tuesday, Wednesday ... ) and perform calculations for each day of the week. 1 - Objective 2 - Features 3 - How to use (Examples) 4 - Inputs 5 - Limitations 6 - Notes 7 - Final Tooughs 2 - Features AVG OPEN-CLOSE Calculate de Percentage change from day open to close Green % (O-C) Percentage of days green (open to close) Average Change Absolute day change (O-C) AVG PrevD. Close-Close Percentage change from the previous day close to the day of the week close (Example: Monday (C-C) = Friday Close to Monday close Tuesday (C-C) = Monday C. to Tuesday C. Green % (C1-C) Percentage of days green (open to close) AVG Volume Day of the week Average Volume Notes: *Mon(Nº) - Nº = Number days is currently calculated Example: Monday (12) calculation based on the last 12 Mondays. Note: Discrepancies in numbers example Monday (12) - Friday (11) depend on the initial/end date or the market was closed (Holidays). 3 - How to use (Examples) For the following example, NASDAQ:AAPL from 1 Jan 21 to 1 Jul 21 the results are following. The highest probability of a Close being higher than the Open is Monday with 52.17 % and the Lowest Tuesday with 38.46 %. Meaning that there's a higher chance (for NASDAQ:AAPL ) of closing at a higher value on Monday while the highest chance of closing is lower is Tuesday. With an average gain on Tuesday of 0.21% Long - The best day to buy (long) at open (on average) is Monday with a 52.2% probability of closing higher Short - The best day to sell (short) at open (on average) is Tuesday with a 38.5% probability of closing higher (better chance of closing lower) Since the values change from ticker to ticker, there is a substantial change in the percentages and days of the week. For example let's compare the previous example ( NASDAQ:AAPL ) to NYSE:GM (same settings) For the same period, there is a substantial difference where there is a 62.5% probability Friday to close higher than the open, while Tuesday there is only a 28% probability. With an average gain of 0.59% on Friday and an average loss of -0.34% Also, the size of the table (number of days ) depends if the ticker is traded or not on that day as an example COINBASE:BTCUSD 4 - Inputs DATE RANGE Initial Date - Date from which the script will start the calculation. End Date - Date to which the script will calculate. TABLE SETTINGS Text Color - Color of the displayed text Cell Color - Background color of table cells Header Color - Color of the column and row names Table Location - Change the position where the table is located. Table Size - Changes text size and by consequence the size of the table 5 - LIMITATIONS The code determines average values based on the stored data, therefore, the range (Initial data) is limited to the first bar time. As a consequence the lower the timeframe the shorter the initial date can be and fewer weeks can be calculated. To warn about this limitation there's a warning text that appears in case the initial date exceeds the bar limit. Example with initial date 1 Jan 2021 and end date 18 Jul 2021 in 5m and 10 m timeframe: 6 - Notes and Disclosers The script can be moved around to a new pane if need. -> Object Tree > Right Click Script > Move To > New pane The code has not been tested in higher subscriptions tiers that allow for more bars and as a consequence more data, but as far I can tell, it should work without problems and should be in fact better at lower timeframes since it allows more weeks. The values displayed represent previous data and at no point is guaranteed future values 7 - Final Tooughs This script was quite fun to work on since it analysis behavioral patterns (since from an abstract point a Tuesday is no different than a Thursday), but after analyzing multiple tickers there are some days that tend to close higher than the open. PS: If you find any mistake ex: code/misspelling please comment.
Индикатор Pine Script®
от MA_PT
25
ZLT - Date and Time MarkerPine Script v5 indicator called “DateTime Marker” that overlays on the chart and marks bars whose timestamp matches a user-defined schedule. When a bar “matches,” it can draw: a vertical line through the bar, a label with a time/date string, and a triangle marker below the bar (always plotted on matches). What you can configure Marker Type (the matching rule) You choose one of five modes: Every Minute Inputs: everyNMinutes (default 15), minuteOffset (default 0) Match condition: minute % everyNMinutes == minuteOffset Example with defaults: marks bars at :00, :15, :30, :45 each hour. Hourly Inputs: everyNHours (default 4), hourlyMinute (default 0) Match condition: hour % everyNHours == 0 AND minute == hourlyMinute Example with defaults: marks bars at 00:00, 04:00, 08:00, 12:00, 16:00, 20:00 (at minute 00). Daily Time Inputs: dailyHour (default 10), dailyMinute (default 0) Match condition: hour == dailyHour AND minute == dailyMinute Example with defaults: marks 10:00 every day. Weekly Day & Time Inputs: weekDay (default Tuesday), weeklyHour (default 16), weeklyMinute (default 0) It converts the weekday name to Pine’s dayofweek number via getDayNumber(). Match condition: dayofweek == targetDay AND hour == weeklyHour AND minute == weeklyMinute Example with defaults: marks Tuesday 16:00. Monthly Date & Time Inputs: monthlyDay (default 2), monthlyHour (default 23), monthlyMinute (default 0) Match condition: dayofmonth == monthlyDay AND hour == monthlyHour AND minute == monthlyMinute Example with defaults: marks the 2nd day of each month at 23:00. Visual settings showLine: whether to draw the vertical line. lineStyle: Solid/Dashed/Dotted (mapped to Pine line styles by getLineStyle()). lineColor, lineWidth: styling for the line (width is rounded to an integer because Pine line width is integer). showLabel: whether to draw a label. labelColor: background color of the label (text is forced white). What happens when a bar matches When isMatch becomes true on a bar: Vertical line: line.new() at that bar’s bar_index, from low to high, extended extend.both (so it spans the full chart vertically). Label: label.new() at the bar’s high, with mode-specific text: Minute/Hourly/Daily: "HH:mm" Weekly: "Tuesday HH:mm" (or whatever day selected) Monthly: "Day 2 - HH:mm" (or chosen day) Triangle marker: plotshape() draws a triangle up below the bar on every match (this happens regardless of showLine / showLabel). Important practical implications This uses the bar’s exchange/chart time (TradingView’s time, hour, minute, etc.), so results depend on the symbol/session and chart timezone settings. On timeframes coarser than 1 minute, “Every Minute” still checks only the bar’s timestamp minute value; it won’t mark intra-bar minutes that don’t exist as separate bars. Because it can create many objects (lines/labels), it sets max_labels_count=500. Lines are not capped here, so very dense marking can still clutter the chart. If you tell me your intended use (e.g., “mark NY open,” “mark every 15m candle close,” “mark macro events weekly”), I can point out whether the current matching logic fits that precisely or needs adjustments (sessions, timezones, avoiding duplicates, limiting lines, etc.).
Индикатор Pine Script®
от Kaeya
ES Multi-Timeframe SMC Entry SystemOverviewThis is a comprehensive Smart Money Concepts (SMC) trading strategy for ES1! (E-mini S&P 500) futures that provides simultaneous buy and sell signals across three timeframes: Daily, Weekly, and Monthly. It incorporates your complete entry checklists, confluence scoring system, and automated risk management.Core Features1. Multi-Timeframe Signal Generation Daily Signals (D) - For intraday/swing trades (1-3 day holds) Weekly Signals (W) - For swing trades (3-10 day holds) Monthly Signals (M) - For position trades (weeks to months) All three timeframes can trigger simultaneously (pyramiding enabled) 2. Smart Money Concepts ImplementationOrder Blocks (OB) Automatically detects bullish and bearish order blocks Bullish OB = Down candle before strong impulse up Bearish OB = Up candle before strong impulse down Validates freshness (< 10 bars = higher quality) Visual boxes displayed on chart Fair Value Gaps (FVG) Identifies 3-candle imbalance patterns Bullish FVG = Gap between high and current low Bearish FVG = Gap between low and current high Tracks unfilled gaps as targets/entry zones Auto-removes when filled Premium/Discount Zones Calculates 50-period swing range Premium = Upper 50% (short from here) Discount = Lower 50% (long from here) Deep zones (<30% or >70%) for higher quality setups Visual shading: Red = Premium, Green = Discount Liquidity Sweeps Sell-Side Sweep (SSL) = False break below lows → reversal up Buy-Side Sweep (BSL) = False break above highs → reversal down Marked with yellow labels on chart Valid for 10 bars after occurrence Break of Structure (BOS) Identifies when price breaks recent swing high/low Confirms trend continuation Marked with small circles on chart 3. Confluence Scoring SystemEach timeframe has a 10-point scoring system based on your checklist requirements:Daily Score (10 points max) HTF Trend Alignment (2 pts) - 4H and Daily EMAs aligned SMC Structure (2 pts) - OB in correct zone with HTF bias Liquidity Sweep (1 pt) - Recent SSL/BSL occurred Volume Confirmation (1 pt) - Volume > 1.2x 20-period average Optimal Time (1 pt) - 9:30-12 PM or 2-4 PM ET (avoids lunch) Risk-Reward >2:1 (1 pt) - Built into exit strategy Clean Price Action (1 pt) - BOS occurred FVG Present (1 pt) - Near unfilled fair value gap Minimum Required: 6/10 (adjustable)Weekly Score (10 points max) Weekly/Monthly Alignment (2 pts) - W and M EMAs aligned Daily/Weekly Alignment (2 pts) - D and W trends match Premium/Discount Correct (2 pts) - Deep zone + trend alignment Major Liquidity Event (1 pt) - SSL/BSL sweep Order Block Present (1 pt) - Valid OB detected Risk-Reward >3:1 (1 pt) - Built into exit Fresh Order Block (1 pt) - OB < 10 bars old Minimum Required: 7/10 (adjustable)Monthly Score (10 points max) Monthly/Weekly Alignment (2 pts) - M and W trends match Weekly OB in Monthly Zone (2 pts) - OB in deep discount/premium Major Liquidity Sweep (2 pts) - Significant SSL/BSL Strong Trend Alignment (2 pts) - D, W, M all aligned Risk-Reward >4:1 (1 pt) - Built into exit Extreme Zone (1 pt) - Price <20% or >80% of range Minimum Required: 8/10 (adjustable)4. Entry ConditionsDaily Long Entry ✅ Daily score ≥ 6/10 ✅ 4H trend bullish (price > EMAs) ✅ Price in discount zone ✅ Bullish OB OR SSL sweep OR near bullish FVG ✅ NOT during avoid times (lunch/first 5 min)Daily Short Entry ✅ Daily score ≥ 6/10 ✅ 4H trend bearish ✅ Price in premium zone ✅ Bearish OB OR BSL sweep OR near bearish FVG ✅ NOT during avoid timesWeekly Long Entry ✅ Weekly score ≥ 7/10 ✅ Weekly trend bullish ✅ Daily trend bullish ✅ Price in discount ✅ Bullish OB OR SSL sweepWeekly Short Entry ✅ Weekly score ≥ 7/10 ✅ Weekly trend bearish ✅ Daily trend bearish ✅ Price in premium ✅ Bearish OB OR BSL sweepMonthly Long Entry ✅ Monthly score ≥ 8/10 ✅ Monthly trend bullish ✅ Weekly trend bullish ✅ Price in DEEP discount (<30%) ✅ Bullish order block presentMonthly Short Entry ✅ Monthly score ≥ 8/10 ✅ Monthly trend bearish ✅ Weekly trend bearish ✅ Price in DEEP premium (>70%) ✅ Bearish order block present5. Automated Risk ManagementPosition Sizing (Per Entry) Daily: 1.0% account risk per trade Weekly: 0.75% account risk per trade Monthly: 0.5% account risk per trade Formula: Contracts = (Account Equity × Risk%) ÷ (Stop Points × $50) Minimum = 1 contractStop Losses Daily: 12 points ($600 per contract) Weekly: 40 points ($2,000 per contract) Monthly: 100 points ($5,000 per contract) Profit Targets (Risk:Reward) Daily: 2:1 = 24 points ($1,200 profit) Weekly: 3:1 = 120 points ($6,000 profit) Monthly: 4:1 = 400 points ($20,000 profit) Example with $50,000 AccountDaily Trade: Risk = $500 (1% of $50k) Stop = 12 points × $50 = $600 Contracts = $500 ÷ $600 = 0.83 → 1 contract Target = 24 points = $1,200 profit Weekly Trade: Risk = $375 (0.75% of $50k) Stop = 40 points × $50 = $2,000 Contracts = $375 ÷ $2,000 = 0.18 → 1 contract Target = 120 points = $6,000 profit Monthly Trade: Risk = $250 (0.5% of $50k) Stop = 100 points × $50 = $5,000 Contracts = $250 ÷ $5,000 = 0.05 → 1 contract Target = 400 points = $20,000 profit 6. Visual Elements on ChartKey Levels Previous Daily High/Low - Red/Green solid lines Previous Weekly High/Low - Red/Green circles Previous Monthly High/Low - Red/Green crosses Equilibrium Line - White dotted line (50% of range) Zones Premium Zone - Light red shading (upper 50%) Discount Zone - Light green shading (lower 50%) SMC Markings Bullish Order Blocks - Green boxes with "Bull OB" label Bearish Order Blocks - Red boxes with "Bear OB" label Bullish FVGs - Green boxes with "FVG↑" Bearish FVGs - Red boxes with "FVG↓" Liquidity Sweeps - Yellow "SSL" (down) or "BSL" (up) labels Break of Structure - Small lime/red circles Entry Signals Daily Long - Small lime triangle ▲ with "D" below price Daily Short - Small red triangle ▼ with "D" above price Weekly Long - Medium green triangle ▲ with "W" below price Weekly Short - Medium maroon triangle ▼ with "W" above price Monthly Long - Large aqua triangle ▲ with "M" below price Monthly Short - Large fuchsia triangle ▼ with "M" above price 7. Information TablesConfluence Score Table (Top Right) ┌──────────┬────────┬────────┬────────┐ │ TF │ SCORE │ STATUS │ SIGNAL │ ├──────────┼────────┼────────┼────────┤ │ 📊 DAILY │ 7/10 │ ✓ PASS │ 🔼 │ │ 📈 WEEKLY│ 6/10 │ ✗ WAIT │ ━ │ │ 🌙 MONTH │ 9/10 │ ✓ PASS │ 🔽 │ ├──────────┴────────┴────────┴────────┤ │ P&L: $2,450 │ └─────────────────────────────────────┘ Green scores = Pass (meets minimum threshold) Orange/Red scores = Fail (wait for better setup) 🔼 = Long signal active 🔽 = Short signal active ━ = No signal Entry Checklist Table (Bottom Right) ┌──────────────┬───┐ │ CHECKLIST │ ✓ │ ├──────────────┼───┤ │ ━ DAILY ━ │ │ │ HTF Trend │ ✓ │ │ Zone │ ✓ │ │ OB │ ✗ │ │ Liq Sweep │ ✓ │ │ Volume │ ✓ │ │ ━ WEEKLY ━ │ │ │ W/M Align │ ✓ │ │ Deep Zone │ ✗ │ │ ━ MONTHLY ━ │ │ │ M/W/D Align │ ✓ │ │ Zone: Discount│ │ └──────────────┴───┘ Green ✓ = Condition met Red ✗ = Condition not met Real-time updates as market conditions change 8. Alert SystemIndividual Alerts: "Daily Long" - Triggers when daily long setup appears "Daily Short" - Triggers when daily short setup appears "Weekly Long" - Triggers when weekly long setup appears "Weekly Short" - Triggers when weekly short setup appears "Monthly Long" - Triggers when monthly long setup appears "Monthly Short" - Triggers when monthly short setup appears Combined Alerts: "Any Long Signal" - Catches any bullish opportunity (D/W/M) "Any Short Signal" - Catches any bearish opportunity (D/W/M) Alert Messages Include: 🔼/🔽 Direction indicator Timeframe (DAILY/WEEKLY/MONTHLY) Current confluence score
Стратегия Pine Script®
от Prototype1111