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WLSMA: fast approximation🙏🏻 Sup TV & @alexgrover O(N) algocomplexity, just one loop inside. No, you can't do O(1) @ updates in moving window mode, only expanding window will allow that. Now I have time series & stats models of my own creation, nowhere else available, just TV and my github for now, ain’t no legacy academic industry I always have fun about, but back in 2k20 when I consciously ain’t known much about quant, I remember seeing post by @alexgrover recreating Moving Regression Endpoint dropped on price chart (called LSMA here) as a linear filter combination of filters (yea yeah DSP terms) as 3WMA - 2SMA. Now it’s my time to do smth alike aye? ... This script is remake of my 1st degree WLSMA via linear filter combo. It’s much faster, we aint calculate moving regression per se, we just match its freq response. You can see it on the screen (WLSMAfa) almost perfectly matching the original one (WLSMA). ... While humans like to overfit, I fw generalizations. So your lovely WMA is actually just one case of a more general weight pattern: pow(len - i, e), where pow is the power function and e is the exponent itself. So: - If e = 0, then we have SMA (every number in 0th power is one) - If e = 1, we get WMA - If e = 2, we get quadratic weights. We can recreate WLSMA freq response then by combining 2 filters with e = 1 and e = 2. This is still an approximation, even tho enormously precise for the tasks you’ve shared with me. Due to the non-linear nature of the thing it’s all we can do, and as window size grows, even this small discrepancy converges with true WLSMA value, so we’re all good. Pls don’t try to model this 0.00xxxx discrepancy, it’s not natural. ... DSP approach is unnatural for prices, but you can put this thing on volume delta and be happy, or on other metrics of yours, if for some reason u dont wanna estimate thresholds by fitting a distro. All good TV ∞ P.S.: strangely, the first script made & dropped in the location in Saint P where my actual quant way has started ~5 years ago xD, very thankful
Pine Script® göstergesi
gorx1 tarafından
Advanced Petroleum Market Model (APMM)Advanced Petroleum Market Model (APMM): A Multi-Factor Fundamental Analysis Framework for Oil Market Assessment ## 1. Introduction The petroleum market represents one of the most complex and globally significant commodity markets, characterized by intricate supply-demand dynamics, geopolitical influences, and substantial price volatility (Hamilton, 2009). Traditional fundamental analysis approaches often struggle to synthesize the multitude of relevant indicators into actionable insights due to data heterogeneity, temporal misalignment, and subjective weighting schemes (Baumeister & Kilian, 2016). The Advanced Petroleum Market Model addresses these limitations through a systematic, quantitative approach that integrates 16 verified fundamental indicators across five critical market dimensions. The model builds upon established financial engineering principles while incorporating petroleum-specific market dynamics and adaptive learning mechanisms. ## 2. Theoretical Framework ### 2.1 Market Efficiency and Information Integration The model operates under the assumption of semi-strong market efficiency, where fundamental information is gradually incorporated into prices with varying degrees of lag (Fama, 1970). The petroleum market's unique characteristics, including storage costs, transportation constraints, and geopolitical risk premiums, create opportunities for fundamental analysis to provide predictive value (Kilian, 2009). ### 2.2 Multi-Factor Asset Pricing Theory Drawing from Ross's (1976) Arbitrage Pricing Theory, the model treats petroleum prices as driven by multiple systematic risk factors. The five-factor decomposition (Supply, Inventory, Demand, Trade, Sentiment) represents economically meaningful sources of systematic risk in petroleum markets (Chen et al., 1986). ## 3. Methodology ### 3.1 Data Sources and Quality Framework The model integrates 16 fundamental indicators sourced from verified TradingView economic data feeds: Supply Indicators: - US Oil Production (ECONOMICS:USCOP) - US Oil Rigs Count (ECONOMICS:USCOR) - API Crude Runs (ECONOMICS:USACR) Inventory Indicators: - US Crude Stock Changes (ECONOMICS:USCOSC) - Cushing Stocks (ECONOMICS:USCCOS) - API Crude Stocks (ECONOMICS:USCSC) - API Gasoline Stocks (ECONOMICS:USGS) - API Distillate Stocks (ECONOMICS:USDS) Demand Indicators: - Refinery Crude Runs (ECONOMICS:USRCR) - Gasoline Production (ECONOMICS:USGPRO) - Distillate Production (ECONOMICS:USDFP) - Industrial Production Index (FRED:INDPRO) Trade Indicators: - US Crude Imports (ECONOMICS:USCOI) - US Oil Exports (ECONOMICS:USOE) - API Crude Imports (ECONOMICS:USCI) - Dollar Index (TVC:DXY) Sentiment Indicators: - Oil Volatility Index (CBOE:OVX) ### 3.2 Data Quality Monitoring System Following best practices in quantitative finance (Lopez de Prado, 2018), the model implements comprehensive data quality monitoring: Data Quality Score = Σ(Individual Indicator Validity) / Total Indicators Where validity is determined by: - Non-null data availability - Positive value validation - Temporal consistency checks ### 3.3 Statistical Normalization Framework #### 3.3.1 Z-Score Normalization The model employs robust Z-score normalization as established by Sharpe (1994) for cross-indicator comparability: Z_i,t = (X_i,t - μ_i) / σ_i Where: - X_i,t = Raw value of indicator i at time t - μ_i = Sample mean of indicator i - σ_i = Sample standard deviation of indicator i Z-scores are capped at ±3 to mitigate outlier influence (Tukey, 1977). #### 3.3.2 Percentile Rank Transformation For intuitive interpretation, Z-scores are converted to percentile ranks following the methodology of Conover (1999): Percentile_Rank = (Number of values < current_value) / Total_observations × 100 ### 3.4 Exponential Smoothing Framework Signal smoothing employs exponential weighted moving averages (Brown, 1963) with adaptive alpha parameter: S_t = α × X_t + (1-α) × S_{t-1} Where α = 2/(N+1) and N represents the smoothing period. ### 3.5 Dynamic Threshold Optimization The model implements adaptive thresholds using Bollinger Band methodology (Bollinger, 1992): Dynamic_Threshold = μ ± (k × σ) Where k is the threshold multiplier adjusted for market volatility regime. ### 3.6 Composite Score Calculation The fundamental score integrates component scores through weighted averaging: Fundamental_Score = Σ(w_i × Score_i × Quality_i) Where: - w_i = Normalized component weight - Score_i = Component fundamental score - Quality_i = Data quality adjustment factor ## 4. Implementation Architecture ### 4.1 Adaptive Parameter Framework The model incorporates regime-specific adjustments based on market volatility: Volatility_Regime = σ_price / μ_price × 100 High volatility regimes (>25%) trigger enhanced weighting for inventory and sentiment components, reflecting increased market sensitivity to supply disruptions and psychological factors. ### 4.2 Data Synchronization Protocol Given varying publication frequencies (daily, weekly, monthly), the model employs forward-fill synchronization to maintain temporal alignment across all indicators. ### 4.3 Quality-Adjusted Scoring Component scores are adjusted for data quality to prevent degraded inputs from contaminating the composite signal: Adjusted_Score = Raw_Score × Quality_Factor + 50 × (1 - Quality_Factor) This formulation ensures that poor-quality data reverts toward neutral (50) rather than contributing noise. ## 5. Usage Guidelines and Best Practices ### 5.1 Configuration Recommendations For Short-term Analysis (1-4 weeks): - Lookback Period: 26 weeks - Smoothing Length: 3-5 periods - Confidence Period: 13 weeks - Increase inventory and sentiment weights For Medium-term Analysis (1-3 months): - Lookback Period: 52 weeks - Smoothing Length: 5-8 periods - Confidence Period: 26 weeks - Balanced component weights For Long-term Analysis (3+ months): - Lookback Period: 104 weeks - Smoothing Length: 8-12 periods - Confidence Period: 52 weeks - Increase supply and demand weights ### 5.2 Signal Interpretation Framework Bullish Signals (Score > 70): - Fundamental conditions favor price appreciation - Consider long positions or reduced short exposure - Monitor for trend confirmation across multiple timeframes Bearish Signals (Score < 30): - Fundamental conditions suggest price weakness - Consider short positions or reduced long exposure - Evaluate downside protection strategies Neutral Range (30-70): - Mixed fundamental environment - Favor range-bound or volatility strategies - Wait for clearer directional signals ### 5.3 Risk Management Considerations 1. Data Quality Monitoring: Continuously monitor the data quality dashboard. Scores below 75% warrant increased caution. 2. Regime Awareness: Adjust position sizing based on volatility regime indicators. High volatility periods require reduced exposure. 3. Correlation Analysis: Monitor correlation with crude oil prices to validate model effectiveness. 4. Fundamental-Technical Divergence: Pay attention when fundamental signals diverge from technical indicators, as this may signal regime changes. ### 5.4 Alert System Optimization Configure alerts conservatively to avoid false signals: - Set alert threshold at 75+ for high-confidence signals - Enable data quality warnings to maintain system integrity - Use trend reversal alerts for early regime change detection ## 6. Model Validation and Performance Metrics ### 6.1 Statistical Validation The model's statistical robustness is ensured through: - Out-of-sample testing protocols - Rolling window validation - Bootstrap confidence intervals - Regime-specific performance analysis ### 6.2 Economic Validation Fundamental accuracy is validated against: - Energy Information Administration (EIA) official reports - International Energy Agency (IEA) market assessments - Commercial inventory data verification ## 7. Limitations and Considerations ### 7.1 Model Limitations 1. Data Dependency: Model performance is contingent on data availability and quality from external sources. 2. US Market Focus: Primary data sources are US-centric, potentially limiting global applicability. 3. Lag Effects: Some fundamental indicators exhibit publication lags that may delay signal generation. 4. Regime Shifts: Structural market changes may require model recalibration. ### 7.2 Market Environment Considerations The model is optimized for normal market conditions. During extreme events (e.g., geopolitical crises, pandemics), additional qualitative factors should be considered alongside quantitative signals. ## References Baumeister, C., & Kilian, L. (2016). Forty years of oil price fluctuations: Why the price of oil may still surprise us. *Journal of Economic Perspectives*, 30(1), 139-160. Bollinger, J. (1992). *Bollinger on Bollinger Bands*. McGraw-Hill. Brown, R. G. (1963). *Smoothing, Forecasting and Prediction of Discrete Time Series*. Prentice-Hall. Chen, N. F., Roll, R., & Ross, S. A. (1986). Economic forces and the stock market. *Journal of Business*, 59(3), 383-403. Conover, W. J. (1999). *Practical Nonparametric Statistics* (3rd ed.). John Wiley & Sons. Fama, E. F. (1970). Efficient capital markets: A review of theory and empirical work. *Journal of Finance*, 25(2), 383-417. Hamilton, J. D. (2009). Understanding crude oil prices. *Energy Journal*, 30(2), 179-206. Kilian, L. (2009). Not all oil price shocks are alike: Disentangling demand and supply shocks in the crude oil market. *American Economic Review*, 99(3), 1053-1069. Lopez de Prado, M. (2018). *Advances in Financial Machine Learning*. John Wiley & Sons. Ross, S. A. (1976). The arbitrage theory of capital asset pricing. *Journal of Economic Theory*, 13(3), 341-360. Sharpe, W. F. (1994). The Sharpe ratio. *Journal of Portfolio Management*, 21(1), 49-58. Tukey, J. W. (1977). *Exploratory Data Analysis*. Addison-Wesley.
Pine Script® göstergesi
EdgeTools tarafından
23/35 SR Channels (Hitchhikers Guide To Goldbach)This indicator highlights potential short-term support and resistance zones based on the 23rd and 35th minute of each hour. At each of these time points, it draws a zone from the high to the low of the candle, extending it forward for a fixed number of bars. Key features: 🔸 Orange zones mark the 23-minute candle 🔹 Blue zones mark the 35-minute candle 📏 Zones extend for a customizable number of bars (channelLength) 🔄 Existing zones are removed if they overlap significantly with a new one 🏷️ Optional labels show when a 23 or 35 zone is created This tool is ideal for traders looking to identify time-based micro-structures and intraday reaction zones.
Pine Script® göstergesi
Hitchhikers_Guide_To_Trading tarafından
Volume/Z-Score Filtered Triple RegressionsVolume/Z-Score Filtered Triple Regressions This indicator blends three regression techniques—Linear Regression, Ridge Regression, and Lasso Regression—to deliver a robust, multi-dimensional view of market trends. Key Features Triple Regression Analysis: Linear Regression: Uses TradingView’s built-in linear regression over a configurable lookback period. Ridge Regression: Applies a penalty term with centering to stabilize slope estimates. Lasso Regression: Incorporates soft-thresholding to refine the regression by reducing noise. Voting Mechanism: Each regression “votes” bullish or bearish by comparing its value to the current close. A majority vote (at least two out of three) determines the preliminary market bias. Z-Score Filtering: The indicator calculates the average of the three regression values and derives a residual Z-score (based on standard deviation). Only when the absolute Z-score exceeds a user-defined threshold does it permit a trend change, helping filter out minor price fluctuations. Volume Confirmation: A moving average of volume (with multiple MA options available) is compared against current volume using a multiplier. This ensures that trend changes are supported by sufficient market activity. Enhanced Visuals: Dynamic color schemes for regression lines, the average trend line, and even candle colors help visually distinguish bullish and bearish signals. A gradient background further reinforces the current trend, adapting its transparency based on the strength of the Z-score. Disclaimer Disclaimer: This indicator is provided for educational and informational purposes only and does not constitute investment advice. Trading involves risk and may result in financial loss. Always perform your own research and consult with a qualified financial advisor before making any trading decisions.
Pine Script® göstergesi
MintLeafEdge tarafından
Z-Score Adaptive Oscillator SuiteZ-Score Adaptive Oscillator Suite This indicator combines the Relative Strength Index (RSI) Money Flow Index (MFI) Chande Momentum Oscillator (CMO) and the Commodity Channel Index (CCI) with Z-score adaptive mechanism to provide a dynamic and adaptive trading tool. Key Features: Oscillators (RSI, MFI, CMO, CCI) Calculates the oscillators using a customizable period and source. Helps identify overbought or oversold conditions based on the oscillator average values. Z-Score Adaptivity: Applies Z-Score calculation to the Oscillators values over a user-defined lookback period. Filters market regimes into low or high Z-score conditions based on the Z-score crossing above the user input threshold Regime-Based Signal Generation: In high Z-Score markets: Signals are generated using a simple cross of the oscillator midline-levels. In low Z-Score markets: Signals are based on user-defined thresholds for long and short conditions. Usage: The coloring automatically adjusts to market conditions, and acts as potential buy/sell signals. Disclaimer This indicator is provided for educational and informational purposes only and does not constitute investment advice. Trading involves risk and may result in financial loss. Always perform your own research and consult with a qualified financial advisor before making any trading decisions.
Pine Script® göstergesi
MintLeafEdge tarafından
Premarket & ORB Body High/Low Lines Till Market CloseDraw horizontal line for PRE-MARKET and ORB --Wicks is excluded. What it does: Tracks premarket body high/low 4:00–9:29 AM NY time Tracks Opening Range Breakout (ORB) body high/low 9:30–9:44 AM NY time Draws horizontal lines extended right until you scroll forward (no fixed length) Labels show current value and update dynamically Resets everything cleanly at the start of each new day
Pine Script® göstergesi
deependradev_c tarafından
Support and Resistance MTFSupport and Resistance MTF Support and Resistance MTF is a powerful tool that automatically detects and visualizes key support and resistance levels based on pivot highs and lows, using a higher timeframe of your choice. It is designed for traders who focus on price action and market structure, and want an adaptive, clean, and customizable indicator that helps identify important market zones. The script uses configurable pivot logic to identify levels, with user-defined parameters for pivot strength and timeframe. Once a support or resistance level is detected, it is displayed on the chart either as a horizontal line, a shaded box, or both, depending on your display settings. You can fully customize the visual appearance including color, transparency, and line thickness. Levels are automatically extended into the future, and optionally into the past, to give better context. Each level is monitored for breakout behavior. If price breaks through a level, it can change its role — a former resistance may become support, and vice versa. After a certain number of breakouts (which you define), the level is considered invalid and is automatically removed from the chart. This helps to maintain a clean visual layout and ensures only relevant levels are shown. The indicator supports multi-timeframe analysis, allowing you to overlay higher-timeframe structure directly on your lower-timeframe trading chart. It is also compatible with Heikin Ashi candles internally for reference, without affecting your main chart type. Support and Resistance MTF is ideal for traders looking to align intraday setups with higher-timeframe zones, manage risk around structural levels, or simply highlight market turning points in a clear and automated way. Built with Pine Script v5 and optimized for performance, it is both powerful and lightweight. ⚙️ Input Parameters – Description [Time-Frame Defines the higher timeframe used for detecting support and resistance levels. For example, you can set this to 1h, 4h, or D to visualize significant levels from a broader market perspective on a lower-timeframe chart. Left / Right (Pivot Left / Pivot Right) These parameters control the sensitivity of the pivot detection. A pivot high/low is confirmed if it is higher/lower than the defined number of candles to its left and right. Higher values reduce noise but may miss smaller turning points. Extend Left When enabled, the drawn levels (lines and/or boxes) are extended to the left side of the chart, allowing you to see the historical alignment of these levels. Max Breaks Before Delete Defines how many times a level can be broken by price before it is removed from the chart. This helps to avoid clutter from outdated or invalidated levels and keeps your chart relevant to current price action. Draw Lines Only If enabled, the indicator will draw only horizontal lines for support and resistance zones, omitting the colored background boxes. Useful for a cleaner chart appearance. Line Width Broken Level Sets the thickness of the support/resistance lines. Thicker lines can emphasize key levels, especially after a breakout. Transparency Boxes Controls the transparency (0–100) of the background boxes representing the zones. A higher value makes the boxes more transparent, lower values make them more opaque. Transparency Lines Controls the transparency (0–100) of the horizontal support and resistance lines. This allows for visual fine-tuning based on chart background and personal preference. Support (Color, Group: Display) Lets you choose the color used for support zones and lines. By default, it's green, but you can change it to fit your theme or visual preference. Resistance (Color, Group: Display) Defines the color for resistance zones and lines. The default is red, but it can be customized freely.
Pine Script® göstergesi
veegee82 tarafından
1
BK AK-Scope🔭 Introducing BK AK-Scope — Target Locked. Signal Acquired. 🔭 After building five precision weapons for traders, I’m proud to unveil the sixth. BK AK-Scope — the eye of the arsenal. This is not just an indicator. It’s an intelligence system for volatility, signal clarity, and rate-of-change dynamics — forged for elite vision in any market terrain. 🧠 Why “Scope”? And Why “AK”? Every shooter knows: you can’t hit what you can’t see. The Scope brings range, clarity, and target distinction. It filters motion from noise. Purpose from panic. “AK” continues to honor the man who trained my sight — my mentor, A.K. His discipline taught me to wait for alignment. To move with reason, not emotion. His vision lives in every code line here. 🔬 What Is BK AK-Scope? A Triple-Tier TSI Correlation Engine, fused with adaptive opacity logic, a volatility scoring system, and real-time signal clarity. It’s momentum dissected — by speed, depth, and rate of change. Built to serve traders who: Need visual hierarchy between fast, mid, and slow TSI responses. Want adaptive fills that pulse with volatility — not static zones. Require a volatility scoring overlay that reads the battlefield in real time. ⚙️ Core Systems: How BK AK-Scope Works ✅ Fast/Mid/Slow TSI → Three layers of correlation: like scopes with zoom levels. You track micro moves, mid swings, and macro flow simultaneously. ✅ Rate-of-Change Adaptive Opacity → Momentum fills fade or flash based on speed — giving you movement density at a glance. Bull vs. Bear zones adapt to strength. You feel the market’s pulse. ✅ Volatility Score Intelligence → Custom algorithm measuring: Range expansion Rate-of-change differentials ATR dynamics Standard deviation pressure All combined into a score from 0–100 with live icons: 🔥 = Extreme Heat (70+) 🧊 = Cold Zone (<30) ⚠️ = ROC Warning • = Neutral drift ✅ Auto-Detect Volatility Modes → Scalp = <15min Swing = intraday/hourly Macro = daily/weekly Or override manually with total control. 🎯 How To Use BK AK-Scope 🔹 Trend Continuation → When all three TSI layers align in direction + volatility score climbs, ride with the trend. 🔹 Early Reversals → Opposing TSI + rapid opacity change + volatility shift = sniper reversal zone. 🔹 Consolidation Filter → Neutral fills + score < 30 = stay out, wait for signal surge. 🔹 Signal Confluence → Pair with: • Gann fans or angles • Fib time/price clusters • Elliott Wave structure • Harmonics or divergence To isolate entry perfection. 🛡️ Why This Indicator Changes the Game It's not just momentum. It’s TSI with depth hierarchy. It’s not just color. It’s real-time strength visualization. It’s not just volatility. It’s rate-weighted market intelligence. This is market optics for the advanced trader — built for vision, clarity, and discipline. 🙏 Final Thoughts 🔹 In honor of A.K., my mentor. The man who taught me to see what others miss. 🔹 Inspired by the power of vision — because execution without clarity is chaos. 🔹 Powered by faith — because Gd alone gives sight beyond the visible. “He gives sight to the blind and wisdom to the humble.” — Psalms 146 Every tool I build is a prayer in code — that it helps someone trade with clarity, integrity, and precision. ⚡ Zoom In. Focus Deep. Trade Clean. BK AK-Scope — Lock on the target. See what others don’t. 🔫 Clarity is power. 🔫 Gd bless. 🙏
Pine Script® göstergesi
Ki11a_B tarafından
Volatility Adaptive Oscillator SuiteVolatility Adaptive Oscillator Suite This indicator combines the Relative Strength Index (RSI) Money Flow Index (MFI) Chande Momentum Oscillator (CMO) and the Commodity Channel Index with volatility adaptive mechanism to provide a dynamic and adaptive trading tool. Key Features: Oscillators (RSI, MFI, CMO, CCI) Calculates the oscillators using a customizable period and source. Helps identify overbought or oversold conditions based on the oscillator average values. ATR Adaptivity: Applies a ATR Moving Average calculation to the Oscillators values over a user-defined lookback period. Filters market regimes into low or high volatility conditions based on the ATR crossing above the average ATR Moving Average Regime-Based Signal Generation: In high volatility markets: Signals are generated using a simple cross of the oscillator midline-levels. In low volatility markets: Signals are based on user-defined thresholds for long and short conditions. Usage: The coloring automatically adjusts to market conditions, and acts as potential buy/sell signals. Disclaimer This indicator is provided for educational and informational purposes only and does not constitute investment advice. Trading involves risk and may result in financial loss. Always perform your own research and consult with a qualified financial advisor before making any trading decisions.
Pine Script® göstergesi
MintLeafEdge tarafından
Z-Score Adaptive Connors RSIZ-Score Adaptive Connors RSI blends the classic three-component Connors RSI (RSI, Up/Down streak RSI, and Percentile Rank of 1-bar ROC) with a dynamic z-score filter that distinguishes trending vs. mean-reverting market regimes. When the indicator detects an extreme deviation (|z-score| > threshold) , it switches to “trending” mode and tightens entry thresholds for capturing momentum. When markets are in a more neutral regime, it reverts to wider thresholds, hunting for overbought/oversold reversals. Key Features Connors RSI Core: Combines price momentum, streak measurements, and velocity for a robust baseline oscillator. Z-Score Regime Filter: Computes the z-score of the Connors RSI over a lookback window to adapt your trading style to trending vs. reverting environments. Dynamic Thresholds: Separate user-configurable thresholds for trending (“tight” entries) and mean-reverting (“wide” entries) scenarios. Inputs & Parameters Connors RSI Settings RSI Source: Price series for RSI calculation (default: Close) RSI Length: Period for price‐change RSI (default: 24) Up/Down Length: Period for streak RSI (default: 20) ROC Length: Period for percentile‐rank of 1-bar return (default: 75) Z-Score Filter Lookback: Number of bars to compute mean and standard deviation of Connors RSI (default: 14) Threshold: Minimum |z-score| to enter “trending” mode (default: 1.5) Entry Thresholds Trending Long/Short: Upper and lower RSI Thresholds when trending Reverting Long/Short: Upper and lower RSI Thresholds when reverting
Pine Script® göstergesi
MintLeafEdge tarafından
Niveaux Majeurs/MineursMajor & Minor Institutional Levels Indicator This script automatically draws major and minor institutional price levels on your chart for any instrument. Major levels (green lines) are plotted every 10 units (default, customizable). Minor levels (red lines) are plotted ±2 units above and below each major level (default, customizable). Features: Lines are thin and semi-transparent for a clean visual experience. Levels are dynamically centered around the current price. No repainting or lag; all levels are updated in real time. Fully adjustable parameters for both major and minor levels. Ideal for traders who want to visualize key price zones often respected by algorithms and large market participants. Works on any timeframe and any asset. How to use: Simply add the indicator to your chart. Adjust the “Major Step” and “Minor Offset” parameters to fit your instrument or trading style.
Pine Script® göstergesi
GIANESELLI tarafından
Momentum HUD (Enhanced with VWAP)*********** TRADERS YOU MUST DOUBLE CLICK THE MOMENTUM HUD TO SET WHAT YOU'RE TRADING, DROP DOWN FOR ETH SET FOR SPY SPX QQQ IWM NDX or OTHER STOCKS and below you PICK YOUR STOCK so it will form the 13 EMA 48 EMA 200 EMA and VWAP for you *********** This one took all weekend, enjoy fam!!!! The Momentum HUD (Enhanced with VWAP) is a powerful, all-in-one trading indicator designed to identify high-probability buy and sell signals for ETH-based indices (QQQ, SPY, SPX, IWM, NDX) or custom stocks like AAPL. It combines momentum, RSI, MACD, ADX, EMAs (13, 48, 200), VWAP, and volume analysis to generate actionable "CALLS" (buy) and "PUTS" (sell) signals. A customizable heads-up display (HUD) table provides real-time insights into key metrics, making it ideal for traders seeking a comprehensive technical analysis tool. This indicator also supports support and resistance analysis indirectly through price interactions with EMAs and VWAP, which often act as dynamic support (e.g., 200 EMA) or resistance (e.g., VWAP rejection). Signals are filtered by an ATR-based volatility check and a cooldown period to reduce noise, ensuring robust trading decisions. Key Features Multi-Indicator Signals: Combines Momentum, RSI, MACD, ADX, EMAs, and VWAP for precise buy/sell signals. Dynamic Support/Resistance: Uses EMA 13, EMA 48, EMA 200, and VWAP to highlight key price levels (e.g., price crossing EMA 13 for support or rejecting VWAP for resistance). Customizable HUD Table: Displays real-time metrics (Momentum, RSI, MACD, ADX, EMA 200, VWAP) with bullish/bearish status and thresholds. Symbol Flexibility: Supports ETH-based indices (QQQ, SPY, SPX, IWM, NDX) or any custom stock via user input. Volatility Filter: Optional ATR filter ensures signals align with sufficient market volatility. Cooldown Mechanism: Prevents over-signaling with a user-defined cooldown period. Visual Cues: Plots EMAs, VWAP, buy/sell triangles, and labels for clear visualization. Alert System: Configurable alerts for buy ("CALLS") and sell ("PUTS") signals. How It Works The indicator generates signals based on a confluence of conditions: Buy Signals (CALLS): Triggered when price crosses above EMA 13 or bounces off VWAP, with positive momentum, RSI > 65, MACD bullish crossover, ADX > 25, price above EMA 200/VWAP, and high volume. Sell Signals (PUTS): Triggered when price crosses below EMA 48 or rejects EMA 200/VWAP, with negative momentum, RSI < 35, MACD bearish crossover, ADX > 25, price below EMA 200/VWAP, and high volume. Support/Resistance Context: EMA 200 and VWAP often act as support (e.g., ETH at $2,531–$2,600) or resistance (e.g., ETH at $2,695–$2,800), enhancing signal reliability. HUD Table: Displays real-time values, status (Bullish/Bearish), and thresholds for all metrics, positioned at a user-defined chart location. Usage Instructions Add to Chart: Open TradingView’s Pine Editor, paste the script, and click “Add to Chart.” Select Symbol: Choose from QQQ (ETH), SPY (ETH), SPX (ETH), IWM (ETH), NDX (ETH), or enter a custom stock symbol (e.g., AAPL). Adjust Settings: Customize inputs (see below) to match your trading style and timeframe (e.g., intraday or daily). Interpret Signals: Green Triangles (CALLS): Indicate buy opportunities below the price bar. Red Triangles (PUTS): Indicate sell opportunities above the price bar. EMA/VWAP Lines: Monitor for price interactions (e.g., bounces or rejections) to confirm support/resistance levels. Set Alerts: Use the built-in alert conditions (“Momentum Buy Signal” or “Momentum Sell Signal”) to receive notifications. Combine with Analysis: Pair with additional tools (e.g., pivot-based support/resistance scripts) to validate key levels like ETH’s $2,531 support or $2,695 resistance. Input Settings Momentum Length: Period for momentum calculation (default: 14). RSI Length: RSI period (default: 14). RSI Buy/Sell Thresholds: RSI levels for buy (default: 65) and sell (default: 35). MACD Fast/Slow/Signal Lengths: MACD settings (default: 12/26/9). ADX Length/Threshold: ADX period (default: 14) and trend strength threshold (default: 25). EMA Lengths: Periods for EMA 13, 48, and 200 (default: 13, 48, 200). Volume Threshold: Multiplier for volume above 20-period average (default: 1.5x). Signal Cooldown: Bars between signals to reduce noise (default: 5). ATR Volatility Filter: Enable/disable ATR filter (default: true) and set ATR length (default: 14) and threshold (default: 0.75% of price). Table Position: HUD placement (options: top_right, top_left, bottom_right, bottom_left). Symbol Choice: Select ETH-based indices or custom stock (default: QQQ (ETH)). Custom Stock Symbol: Input ticker for custom stocks (default: AAPL). Label Colors: Customize text colors for EMA 13, EMA 48, EMA 200, and VWAP labels (default: black). Example Use Case For ETH (via QQQ): On a daily chart, set symbol_choice to “QQQ (ETH).” Monitor for buy signals when ETH crosses above $2,600 (EMA 13) with RSI > 65 and high volume, confirming support. Sell signals may trigger if ETH rejects $2,695 (VWAP) with RSI < 35, indicating resistance. For Stocks (e.g., AAPL): Set custom_symbol to “AAPL.” Look for buy signals when price bounces off EMA 200 (support) and sell signals when price rejects VWAP (resistance). Notes Timeframe: Works on any timeframe, with intraday defaulting to the chart’s period and others to daily. Support/Resistance: Combine with a pivot-based script (e.g., pivot highs/lows) to explicitly plot static support/resistance levels alongside dynamic EMAs/VWAP. Risk Management: Always use proper risk management, as indicators are not foolproof. Performance: Best used in trending markets (ADX > 25) and with confirmation from other tools. Disclaimer This indicator is for educational and informational purposes only and should not be considered financial advice. Always conduct your own research and consult a financial advisor before trading. This info page is ready for TradingView’s publication requirements. It highlights the script’s functionality, ties in support/resistance context (per your ETH request), and provides clear instructions. Before publishing, ensure your TradingView account meets their requirements (e.g., verified profile). If you need tweaks or additional features (e.g., explicit support/resistance plotting), let me know!
Pine Script® göstergesi
StanTheTradingMan tarafından
Two Candle Theory (Filtered) - Labels & ColorsOverview This Pine Script classifies each candle into one of nine sentiment categories based on how the candle closes within its own range and in relation to the previous candle’s high and low. It optionally filters the strongest bullish and bearish signals based on volume spikes. The script is designed to help traders visually interpret market sentiment through configurable labels and candle colors. ⸻ Classification Logic Each candle is assessed using two metrics: 1. Close Position – where the candle closes within its own high-low range (High, Mid, Low). 2. Close Comparison – how the current close compares to the previous candle’s high and low (Bull, Bear, or Range). Based on this, a short label is assigned: • Bullish Bias: Strongest (SBu), Moderate (MBu), Weak (WBu), Slight (SlB) • Neutral: Neutral (N) • Bearish Bias: Slight (SlS), Weak (WBa), Moderate (MBa), Strongest (SBa) ⸻ Volume Filter A volume spike filter can be applied to the strongest signals: • SBu and SBa are only shown if volume is significantly higher than the average (SMA × threshold). • The filter is optional and user-configurable. ⸻ Display Options Users can control: • Whether to show labels, bar colors, or both. • Which of the nine label types are visible. • Custom colors for each label and corresponding bar. ⸻ Visual Output • Labels appear above or below candles depending on bullish or bearish classification. • Bar colors reflect sentiment for quicker visual scanning. ⸻ Use Case Ideal for identifying momentum shifts, validating trade entries, and highlighting candles that break out of previous ranges with conviction and/or volume. ⸻ Summary This script simplifies price action by translating each candle into an interpretable sentiment label and color. With optional volume filtering and full display customization, it offers a practical tool for discretionary and systematic traders alike.
Pine Script® göstergesi
jabez4jc tarafından